From fef2d710e035fb45a2f61604399b6b7aa0040843 Mon Sep 17 00:00:00 2001 From: clinssen Date: Wed, 12 Jun 2024 12:19:45 +0200 Subject: [PATCH] Fix special handling of NEST delay and weight variables in synapse (#1044) --- .github/workflows/nestml-build.yml | 2 +- doc/nestml_language/synapses_in_nestml.rst | 76 - doc/running/running_nest.rst | 117 +- .../stdp_dopa_synapse/stdp_dopa_synapse.ipynb | 4267 ++++++++-------- doc/tutorials/stdp_windows/stdp_windows.ipynb | 4545 +++++++---------- .../triplet_stdp_synapse.ipynb | 1724 +++---- .../neuromodulated_stdp_synapse.nestml | 4 +- models/synapses/noisy_synapse.nestml | 4 +- models/synapses/static_synapse.nestml | 4 +- .../stdp_nn_pre_centered_synapse.nestml | 2 +- .../stdp_nn_restr_symm_synapse.nestml | 2 +- models/synapses/stdp_nn_symm_synapse.nestml | 4 +- models/synapses/stdp_synapse.nestml | 4 +- models/synapses/stdp_triplet_synapse.nestml | 2 +- .../synapses/third_factor_stdp_synapse.nestml | 2 +- pynestml/cocos/co_co_all_variables_defined.py | 2 +- .../co_co_nest_delay_decorator_specified.py | 49 - ...o_co_nest_synapse_delay_not_assigned_to.py | 60 + .../co_co_no_kernels_except_in_convolve.py | 4 +- pynestml/cocos/co_cos_manager.py | 1 - .../codegeneration/nest_code_generator.py | 47 +- .../nest_code_generator_utils.py | 3 + .../printers/nest_variable_printer.py | 12 +- .../point_neuron/common/NeuronClass.jinja2 | 7 +- .../common/SynapseHeader.h.jinja2 | 292 +- .../CommonPropertiesDictionaryReader.jinja2 | 2 +- .../CommonPropertiesDictionaryWriter.jinja2 | 2 +- .../directives_cpp/WriteInDictionary.jinja2 | 2 +- .../@SYNAPSE_NAME@_impl.c.jinja2 | 58 +- pynestml/meta_model/ast_external_variable.py | 3 +- pynestml/meta_model/ast_variable.py | 3 +- .../synapse_post_neuron_transformer.py | 45 +- .../ast_mechanism_information_collector.py | 3 +- pynestml/utils/ast_utils.py | 6 +- pynestml/utils/messages.py | 6 - pynestml/utils/with_options.py | 3 + tests/cocos_test.py | 2 +- .../invalid/CoCoResolutionLegallyUsed.nestml | 6 +- ...tdp_synapse_missing_delay_decorator.nestml | 2 +- tests/nest_compartmental_tests/cocos_test.py | 2 +- tests/nest_tests/delay_decorator_specified.py | 59 - .../nest_tests/nest_custom_templates_test.py | 2 + tests/nest_tests/nest_multithreading_test.py | 4 +- .../nest_resolution_builtin_test.py | 4 +- .../nest_set_with_distribution_test.py | 4 +- tests/nest_tests/noisy_synapse_test.py | 4 +- .../TimeVariablePrePostSynapse.nestml | 3 +- .../resources/TimeVariableSynapse.nestml | 3 +- .../delay_test_assigned_delay2_synapse.nestml | 17 + .../delay_test_assigned_delay_synapse.nestml | 18 + .../delay_test_assigned_synapse.nestml | 18 + .../delay_test_plastic_synapse.nestml | 21 + .../resources/delay_test_synapse.nestml | 23 + .../dopa_second_order_synapse.nestml | 3 +- .../homogeneous_parameters_synapse.nestml | 8 +- .../weight_test_assigned_synapse.nestml | 18 + .../weight_test_plastic_synapse.nestml | 21 + tests/nest_tests/stdp_neuromod_test.py | 4 +- tests/nest_tests/stdp_nn_pre_centered_test.py | 4 +- tests/nest_tests/stdp_nn_restr_symm_test.py | 4 +- tests/nest_tests/stdp_nn_synapse_test.py | 4 +- tests/nest_tests/stdp_synapse_test.py | 4 +- tests/nest_tests/stdp_triplet_synapse_test.py | 4 +- tests/nest_tests/stdp_window_test.py | 11 +- .../test_delay_variable_specified.py | 182 + .../test_dopa_second_order_synapse.py | 6 +- .../test_homogeneous_parameters_synapse.py | 8 +- tests/nest_tests/test_ignore_and_fire.py | 4 +- tests/nest_tests/test_priority_synapse.py | 6 +- tests/nest_tests/test_static_synapse.py | 7 +- tests/nest_tests/test_time_variable.py | 6 +- .../test_weight_variable_specified.py | 154 + .../third_factor_stdp_synapse_test.py | 4 +- .../resources/SynapseEventSequenceTest.nestml | 4 + .../neuron_event_inv_priority_test.nestml | 3 +- .../neuron_event_priority_test.nestml | 3 +- .../synapse_event_inv_priority_test.nestml | 4 +- .../synapse_event_priority_test.nestml | 4 +- tests/valid/CoCoResolutionLegallyUsed.nestml | 3 +- 79 files changed, 5829 insertions(+), 6215 deletions(-) delete mode 100644 pynestml/cocos/co_co_nest_delay_decorator_specified.py create mode 100644 pynestml/cocos/co_co_nest_synapse_delay_not_assigned_to.py delete mode 100644 tests/nest_tests/delay_decorator_specified.py create mode 100644 tests/nest_tests/resources/delay_test_assigned_delay2_synapse.nestml create mode 100644 tests/nest_tests/resources/delay_test_assigned_delay_synapse.nestml create mode 100644 tests/nest_tests/resources/delay_test_assigned_synapse.nestml create mode 100644 tests/nest_tests/resources/delay_test_plastic_synapse.nestml create mode 100644 tests/nest_tests/resources/delay_test_synapse.nestml create mode 100644 tests/nest_tests/resources/weight_test_assigned_synapse.nestml create mode 100644 tests/nest_tests/resources/weight_test_plastic_synapse.nestml create mode 100644 tests/nest_tests/test_delay_variable_specified.py create mode 100644 tests/nest_tests/test_weight_variable_specified.py diff --git a/.github/workflows/nestml-build.yml b/.github/workflows/nestml-build.yml index 5750c3a05..a129fc47d 100644 --- a/.github/workflows/nestml-build.yml +++ b/.github/workflows/nestml-build.yml @@ -227,7 +227,7 @@ jobs: done; exit $rc - # Run only the nest_integration_test for the NEST versions other than master and 2.20.2 + # Run only the nest integration tests for NEST versions other than master and 2.20.2 - name: Run integration tests if: ${{ !(matrix.nest_branch == 'master' || matrix.nest_branch == 'v2.20.2') }} env: diff --git a/doc/nestml_language/synapses_in_nestml.rst b/doc/nestml_language/synapses_in_nestml.rst index 84550613d..1816a95cf 100644 --- a/doc/nestml_language/synapses_in_nestml.rst +++ b/doc/nestml_language/synapses_in_nestml.rst @@ -488,82 +488,6 @@ Further integration with NEST Simulator is planned, to achieve a just-in-time co Code generator options instruct the target platform code generator (in this case, NEST) how to process the models. - -The NEST target ---------------- - -Event-based updating -~~~~~~~~~~~~~~~~~~~~ - -NEST target synapses are not allowed to have any time-based internal dynamics (ODEs). This is due to the fact that synapses are, unlike nodes, not updated on a regular time grid. - -The synapse is allowed to contain an ``update`` block. Statements in the ``update`` block are executed whenever the internal state of the synapse is updated from one timepoint to the next; these updates are typically triggered by incoming spikes. The NESTML ``resolution()`` function will return the time that has elapsed since the last event was handled. - - -Dendritic delay -~~~~~~~~~~~~~~~ - -In NEST, all synapses are expected to specify a nonzero dendritic delay, that is, the delay between arrival of a spike at the dendritic spine and the time at which its effects are felt at the soma (or conversely, the delay between a somatic action potential and the arrival at the dendritic spine due to dendritic backpropagation). To indicate that a given parameter is specifying this NEST-specific delay value, use an annotation: - -.. code:: nestml - - parameters: - dend_delay ms = 1 ms @nest::delay - - -Generating code ---------------- - -When NESTML is invoked to generate code for plastic synapses, the code generator needs to know which neuron model the synapses will be connected to, so that it can generate fast C++ code for the neuron and the synapse that is mutually dependent at runtime. These pairs can be specified as a list of two-element dictionaries of the form :python:`{"neuron": "neuron_model_name", "synapse": "synapse_model_name"}`, for example: - -.. code-block:: python - - generate_target(..., - codegen_opts={..., - "neuron_synapse_pairs": [{"neuron": "iaf_psc_exp_dend", - "synapse": "third_factor_stdp"}]}) - -Additionally, if the synapse requires it, specify the ``"post_ports"`` entry to connect the input port on the synapse with the right variable of the postsynaptic neuron: - -.. code-block:: python - - generate_target(..., - codegen_opts={..., - "neuron_synapse_pairs": [{"neuron": "iaf_psc_exp_dend", - "synapse": "third_factor_stdp", - "post_ports": ["post_spikes", - ["I_post_dend", "I_dend"]]}]}) - -This specifies that the neuron ``iaf_psc_exp_dend`` has to be generated paired with the synapse ``third_factor_stdp``, and that the input ports ``post_spikes`` and ``I_post_dend`` in the synapse are to be connected to the postsynaptic partner. For the ``I_post_dend`` input port, the corresponding variable in the (postsynaptic) neuron is called ``I_dend``. - -Simulation of volume-transmitted neuromodulation in NEST can be done using "volume transmitter" devices [5]_. These are event-based and should correspond to a "spike" type input port in NESTML. The code generator options keyword "vt_ports" can be used here. - -.. code-block:: python - - generate_target(..., - codegen_opts={..., - "neuron_synapse_pairs": [{"neuron": "iaf_psc_exp_dend", - "synapse": "third_factor_stdp", - "vt_ports": ["dopa_spikes"]}]}) - - - -Implementation notes -~~~~~~~~~~~~~~~~~~~~ - -Note that ``access_counter`` now has an extra multiplicative factor equal to the number of trace values that exist, so that spikes are removed from the history only after they have been read out for the sake of computing each trace. - -.. figure:: https://www.frontiersin.org/files/Articles/1382/fncom-04-00141-r1/image_m/fncom-04-00141-g003.jpg - - Potjans et al. 2010 - -Random numbers -~~~~~~~~~~~~~~ - -In case random numbers are needed inside the synapse, the random number generator belonging to the postsynaptic target is used. - - - References ---------- diff --git a/doc/running/running_nest.rst b/doc/running/running_nest.rst index e2874efbb..5483f6c64 100644 --- a/doc/running/running_nest.rst +++ b/doc/running/running_nest.rst @@ -1,5 +1,5 @@ NEST Simulator target ---------------------- +===================== *NESTML features supported:* :doc:`neurons `, :doc:`synapses `, :ref:`vectors `, :ref:`delay differential equations `, :ref:`guards ` @@ -7,7 +7,7 @@ After NESTML completes, the NEST extension module (by default called ``"nestmlmo Simulation loop -~~~~~~~~~~~~~~~ +--------------- Note that NEST Simulator uses a hybrid integration strategy [Hanuschkin2010]_; see :numref:`fig_integration_order`, panel A for a graphical depiction. @@ -18,14 +18,18 @@ Then, the code is run corresponding to the NESTML ``update`` block. At the end of the timestep, variables corresponding to convolutions are updated according to their ODE dynamics. -Code generation options -~~~~~~~~~~~~~~~~~~~~~~~ +Event-based updating of synapses +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ -Several code generator options are available; for an overview see :class:`pynestml.codegeneration.nest_code_generator.NESTCodeGenerator`. +The synapse is allowed to contain an ``update`` block. Statements in the ``update`` block are executed whenever the internal state of the synapse is updated from one timepoint to the next; these updates are typically triggered by incoming spikes. The NESTML ``resolution()`` function will return the time that has elapsed since the last event was handled. + +Synapses in NEST are not allowed to have any nonlinear time-based internal dynamics (ODEs). This is due to the fact that synapses are, unlike nodes, not updated on a regular time grid. Linear ODEs are allowed, because they admit an analytical solution, which can be updated in a single step from the previous event time to the current event time. However, nonlinear dynamics are not allowed because they would require a numeric solver evaluating the dynamics on a regular time grid. + +If ODE-toolbox is not successful in finding the propagator solver to a system of ODEs that is, however, solvable, the propagators may be entered "by hand" in the ``update`` block of the model. This block may contain any series of statements to update the state of the system from the current timestep to the next, for example, multiplications of state variables by the propagators. Setting and retrieving model properties -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ +--------------------------------------- - All variables in the ``state`` and ``parameters`` blocks are added to the status dictionary of the neuron. - Values can be set using the PyNEST API call ``node_collection. = `` where ```` is the name of the corresponding NESTML variable. @@ -33,13 +37,13 @@ Setting and retrieving model properties Recording values with devices -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ +----------------------------- All values in the ``state`` block are recordable by a ``multimeter`` in NEST. Solver selection -~~~~~~~~~~~~~~~~ +---------------- Currently, there is support for GSL, forward Euler, and exact integration. ODEs that can be solved analytically are integrated to machine precision from one timestep to the next. To allow more precise values for analytically solvable ODEs *within* a timestep, the same ODEs are evaluated numerically by the GSL solver. In this way, the long-term dynamics obeys the "exact" equations, while the short-term (within one timestep) dynamics is evaluated to the precision of the numerical integrator. @@ -47,7 +51,7 @@ In the case that the model is solved with the GSL integrator, desired absolute e Manually building the extension module -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ +-------------------------------------- Sometimes it can be convenient to directly edit the generated code. To manually build and install the NEST extension module, go into the target directory and run: @@ -60,14 +64,8 @@ Sometimes it can be convenient to directly edit the generated code. To manually where ```` is the installation directory of NEST (e.g. ``/home/nest/work/nest-install``). -Custom templates -~~~~~~~~~~~~~~~~ - -See :ref:`Running NESTML with custom templates`. - - Gap junctions (electrical synapses) -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ +----------------------------------- Each neuron model can be endowed with gap junctions. The model does not need to be (necessarily) modified itself, but additional flags are passed during code generation that identify which model variables correspond to the membrane potential and the gap junction current. For instance, the code generator options can look as follows: @@ -83,7 +81,7 @@ For a full example, please see `test_gap_junction.py `_ for the neuron model and ``test_multisynapse_with_vector_input_ports`` in `tests/nest_tests/nest_multisynapse_test.py `_ for the corresponding test. + +Generating code +--------------- + +.. note:: + + Several code generator options are available; for an overview see :class:`pynestml.codegeneration.nest_code_generator.NESTCodeGenerator`. + +Generating code for plastic synapses +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +When NESTML is invoked to generate code for plastic synapses, the code generator needs to know which neuron model the synapses will be connected to, so that it can generate fast C++ code for the neuron and the synapse that is mutually dependent at runtime. These pairs can be specified as a list of two-element dictionaries of the form :python:`{"neuron": "neuron_model_name", "synapse": "synapse_model_name"}`, for example: + +.. code-block:: python + + generate_target(..., + codegen_opts={..., + "neuron_synapse_pairs": [{"neuron": "iaf_psc_exp_dend", + "synapse": "third_factor_stdp"}]}) + +Additionally, if the synapse requires it, specify the ``"post_ports"`` entry to connect the input port on the synapse with the right variable of the postsynaptic neuron: + +.. code-block:: python + + generate_target(..., + codegen_opts={..., + "neuron_synapse_pairs": [{"neuron": "iaf_psc_exp_dend", + "synapse": "third_factor_stdp", + "post_ports": ["post_spikes", + ["I_post_dend", "I_dend"]]}]}) + +This specifies that the neuron ``iaf_psc_exp_dend`` has to be generated paired with the synapse ``third_factor_stdp``, and that the input ports ``post_spikes`` and ``I_post_dend`` in the synapse are to be connected to the postsynaptic partner. For the ``I_post_dend`` input port, the corresponding variable in the (postsynaptic) neuron is called ``I_dend``. + +Simulation of volume-transmitted neuromodulation in NEST can be done using "volume transmitter" devices [5]_. These are event-based and should correspond to a "spike" type input port in NESTML. The code generator options keyword ``"vt_ports"`` can be used here. + +.. code-block:: python + + generate_target(..., + codegen_opts={..., + "neuron_synapse_pairs": [{"neuron": "iaf_psc_exp_dend", + "synapse": "third_factor_stdp", + "vt_ports": ["dopa_spikes"]}]}) + + +Dendritic delay and synaptic weight +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +In NEST, all synapses are expected to specify a nonzero dendritic delay, that is, the delay between arrival of a spike at the dendritic spine and the time at which its effects are felt at the soma (or conversely, the delay between a somatic action potential and the arrival at the dendritic spine due to dendritic backpropagation). As delays and weights are hard-wired into the NEST C++ base classes for the NESTML synapse classes, special annotations must be made in the NESTML model to indicate which state variables or parameters correspond to weight and delay. To indicate the correspondence, use the code generator options ``delay_variable`` and ``weight_variable``. For example, given the following model: + +.. code:: nestml + + synapse my_synapse: + state: + w real = 1. + + parameters: + dend_delay ms = 1 ms + +the variables might be specified as: + +.. code-block:: python + + generate_target(..., + codegen_opts={..., + "delay_variable": {"my_synapse": "dend_delay"}, + "weight_variable": {"my_synapse": "w"}}) + + +Custom templates +~~~~~~~~~~~~~~~~ + +See :ref:`Running NESTML with custom templates`. + + Compatibility with different versions of NEST ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ @@ -182,9 +254,18 @@ To generate code that is compatible with particular versions of NEST Simulator, - The default is the empty string, which causes the NEST version to be automatically identified from the ``nest`` Python module. - ``"master"``: Latest NEST GitHub master branch version (https://github.com/nest/nest-simulator/). - ``"v2.20.2"``: Latest NEST 2 release. -- ``"v3.0"``, ``"v3.1"``, ``"v3.2"``, ``"v3.3"``, ``"v3.4"``: NEST 3 release versions. +- ``"v3.0"``, ``"v3.1"``, ``"v3.2"``, etc.: NEST 3 release versions. For a list of the corresponding NEST Simulator repository tags, please see https://github.com/nest/nest-simulator/tags. +Random numbers +-------------- + +In case random numbers are needed inside the synapse, the random number generator belonging to the postsynaptic target is used. + + +References +---------- + .. [Hanuschkin2010] Alexander Hanuschkin and Susanne Kunkel and Moritz Helias and Abigail Morrison and Markus Diesmann. A General and Efficient Method for Incorporating Precise Spike Times in Globally Time-Driven Simulations. Frontiers in Neuroinformatics, 2010, Vol. 4 diff --git a/doc/tutorials/stdp_dopa_synapse/stdp_dopa_synapse.ipynb b/doc/tutorials/stdp_dopa_synapse/stdp_dopa_synapse.ipynb index eb3f9b787..09158002b 100644 --- a/doc/tutorials/stdp_dopa_synapse/stdp_dopa_synapse.ipynb +++ b/doc/tutorials/stdp_dopa_synapse/stdp_dopa_synapse.ipynb @@ -120,7 +120,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -138,7 +137,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -164,7 +162,7 @@ " post_tr real = 0.\n", "\n", " parameters:\n", - " d ms = 1 ms @nest::delay\n", + " d ms = 1 ms\n", " tau_tr_pre ms = 20 ms # STDP time constant for weight changes caused by pre-before-post spike pairings.\n", " tau_tr_post ms = 20 ms # STDP time constant for weight changes caused by post-before-pre spike pairings.\n", " tau_c ms = 1000 ms # Time constant of eligibility trace\n", @@ -224,7 +222,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -243,11 +240,13 @@ "name": "stdout", "output_type": "stream", "text": [ + "codegen_opts = {'delay_variable': {'neuromodulated_stdp_synapse': 'd'}, 'weight_variable': {'neuromodulated_stdp_synapse': 'w'}}\n", + "_codegen_opts = {'neuron_parent_class': 'StructuralPlasticityNode', 'neuron_parent_class_include': 'structural_plasticity_node.h', 'neuron_synapse_pairs': [{'neuron': 'iaf_psc_delta_neuron', 'synapse': 'neuromodulated_stdp_synapse', 'post_ports': ['post_spikes'], 'vt_ports': ['mod_spikes']}]}\n", "[1,GLOBAL, INFO]: List of files that will be processed:\n", - "[2,GLOBAL, INFO]: /home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/iaf_psc_delta_neuron.nestml\n", - "[3,GLOBAL, INFO]: /home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/neuromodulated_stdp_synapse.nestml\n", - "[4,GLOBAL, INFO]: Target platform code will be generated in directory: '/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target'\n", - "[5,GLOBAL, INFO]: Target platform code will be installed in directory: '/tmp/nestml_target_2nbwam92'\n", + "[2,GLOBAL, INFO]: /home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/iaf_psc_delta_neuron.nestml\n", + "[3,GLOBAL, INFO]: /home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/neuromodulated_stdp_synapse.nestml\n", + "[4,GLOBAL, INFO]: Target platform code will be generated in directory: '/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target'\n", + "[5,GLOBAL, INFO]: Target platform code will be installed in directory: '/tmp/nestml_target_b49vsj8e'\n", "\n", " -- N E S T --\n", " Copyright (C) 2004 The NEST Initiative\n", @@ -264,23 +263,23 @@ " Type 'nest.help()' to find out more about NEST.\n", "\n", "[6,GLOBAL, INFO]: The NEST Simulator version was automatically detected as: master\n", - "[7,GLOBAL, INFO]: Given template root path is not an absolute path. Creating the absolute path with default templates directory '/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/pynestml/codegeneration/resources_nest/point_neuron'\n", - "[8,GLOBAL, INFO]: Given template root path is not an absolute path. Creating the absolute path with default templates directory '/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/pynestml/codegeneration/resources_nest/point_neuron'\n", - "[9,GLOBAL, INFO]: Given template root path is not an absolute path. Creating the absolute path with default templates directory '/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/pynestml/codegeneration/resources_nest/point_neuron'\n", + "[7,GLOBAL, INFO]: Given template root path is not an absolute path. Creating the absolute path with default templates directory '/home/charl/julich/nestml-fork-nest-delay/nestml/pynestml/codegeneration/resources_nest/point_neuron'\n", + "[8,GLOBAL, INFO]: Given template root path is not an absolute path. Creating the absolute path with default templates directory '/home/charl/julich/nestml-fork-nest-delay/nestml/pynestml/codegeneration/resources_nest/point_neuron'\n", + "[9,GLOBAL, INFO]: Given template root path is not an absolute path. Creating the absolute path with default templates directory '/home/charl/julich/nestml-fork-nest-delay/nestml/pynestml/codegeneration/resources_nest/point_neuron'\n", "[10,GLOBAL, INFO]: The NEST Simulator installation path was automatically detected as: /home/charl/julich/nest-simulator-install\n", - "[11,GLOBAL, INFO]: Start processing '/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/iaf_psc_delta_neuron.nestml'!\n", + "[11,GLOBAL, INFO]: Start processing '/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/iaf_psc_delta_neuron.nestml'!\n", "[13,iaf_psc_delta_neuron_nestml, INFO, [51:79;51:79]]: Implicit magnitude conversion from pA to pA buffer with factor 1.0 \n", "[14,iaf_psc_delta_neuron_nestml, INFO, [51:15;51:74]]: Implicit magnitude conversion from mV / ms to pA / pF with factor 1.0 \n", - "[15,GLOBAL, INFO]: Start processing '/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/neuromodulated_stdp_synapse.nestml'!\n", - "[17,neuromodulated_stdp_synapse_nestml, WARNING, [12:8;12:28]]: Variable 'd' has the same name as a physical unit!\n", + "[15,GLOBAL, INFO]: Start processing '/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/neuromodulated_stdp_synapse.nestml'!\n", + "[17,neuromodulated_stdp_synapse_nestml, WARNING, [12:8;12:17]]: Variable 'd' has the same name as a physical unit!\n", "[18,neuromodulated_stdp_synapse_nestml, INFO, [40:13;40:20]]: Implicit casting from (compatible) type '1 / ms' to 'real'.\n", "[19,neuromodulated_stdp_synapse_nestml, INFO, [63:13;63:123]]: Implicit casting from (compatible) type 'ms' to 'real'.\n", - "[22,neuromodulated_stdp_synapse_nestml, WARNING, [12:8;12:28]]: Variable 'd' has the same name as a physical unit!\n", + "[22,neuromodulated_stdp_synapse_nestml, WARNING, [12:8;12:17]]: Variable 'd' has the same name as a physical unit!\n", "[23,neuromodulated_stdp_synapse_nestml, INFO, [40:13;40:20]]: Implicit casting from (compatible) type '1 / ms' to 'real'.\n", "[24,neuromodulated_stdp_synapse_nestml, INFO, [63:13;63:123]]: Implicit casting from (compatible) type 'ms' to 'real'.\n", "[26,iaf_psc_delta_neuron_nestml, INFO, [51:79;51:79]]: Implicit magnitude conversion from pA to pA buffer with factor 1.0 \n", "[27,iaf_psc_delta_neuron_nestml, INFO, [51:15;51:74]]: Implicit magnitude conversion from mV / ms to pA / pF with factor 1.0 \n", - "[29,neuromodulated_stdp_synapse_nestml, WARNING, [12:8;12:28]]: Variable 'd' has the same name as a physical unit!\n", + "[29,neuromodulated_stdp_synapse_nestml, WARNING, [12:8;12:17]]: Variable 'd' has the same name as a physical unit!\n", "[30,neuromodulated_stdp_synapse_nestml, INFO, [40:13;40:20]]: Implicit casting from (compatible) type '1 / ms' to 'real'.\n", "[31,neuromodulated_stdp_synapse_nestml, INFO, [63:13;63:123]]: Implicit casting from (compatible) type 'ms' to 'real'.\n", "[32,GLOBAL, INFO]: State variables that will be moved from synapse to neuron: ['post_tr']\n", @@ -296,9 +295,7 @@ "[42,GLOBAL, INFO]: In synapse: replacing variables with suffixed external variable references\n", "[43,GLOBAL, INFO]: \t• Replacing variable post_tr\n", "[44,GLOBAL, INFO]: ASTSimpleExpression replacement made (var = post_tr__for_neuromodulated_stdp_synapse_nestml) in expression: A_minus * post_tr\n", - "[47,neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml, WARNING, [12:8;12:28]]: Variable 'd' has the same name as a physical unit!\n", - "[48,neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml, INFO, [40:13;40:20]]: Implicit casting from (compatible) type '1 / ms' to 'real'.\n", - "[49,neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml, INFO, [63:13;63:123]]: Implicit casting from (compatible) type 'ms' to 'real'.\n" + "[47,neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml, WARNING, [12:8;12:17]]: Variable 'd' has the same name as a physical unit!\n" ] }, { @@ -336,20 +333,26 @@ "Processing differential-equation form shape V_m with defining expression = \"(-(V_m - E_L)) / tau_m + 0 * (1.0 / 1.0) + (I_e + I_stim) / C_m\"\n", "INFO:\tReturning shape: Shape \"V_m\" of order 1\n", "INFO:Shape V_m: reconstituting expression E_L/tau_m - V_m/tau_m + I_e/C_m + I_stim/C_m\n", - "INFO:All known variables: [V_m], all parameters used in ODEs: {tau_m, I_e, C_m, I_stim, E_L}\n", + "INFO:All known variables: [V_m], all parameters used in ODEs: {I_e, I_stim, tau_m, C_m, E_L}\n", "INFO:No numerical value specified for parameter \"I_stim\"\n", "INFO:\n", "Processing differential-equation form shape V_m with defining expression = \"(-(V_m - E_L)) / tau_m + 0 * (1.0 / 1.0) + (I_e + I_stim) / C_m\"\n", "INFO:\tReturning shape: Shape \"V_m\" of order 1\n", "INFO:Shape V_m: reconstituting expression E_L/tau_m - V_m/tau_m + I_e/C_m + I_stim/C_m\n", "INFO:Finding analytically solvable equations...\n", - "INFO:Saving dependency graph plot to /tmp/ode_dependency_graph.dot\n" + "INFO:Saving dependency graph plot to /tmp/ode_dependency_graph.dot\n", + "INFO:Shape V_m: reconstituting expression E_L/tau_m - V_m/tau_m + I_e/C_m + I_stim/C_m\n", + "INFO:Saving dependency graph plot to /tmp/ode_dependency_graph_analytically_solvable_before_propagated.dot\n", + "INFO:Saving dependency graph plot to /tmp/ode_dependency_graph_analytically_solvable.dot\n", + "INFO:Generating propagators for the following symbols: V_m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ + "[48,neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml, INFO, [40:13;40:20]]: Implicit casting from (compatible) type '1 / ms' to 'real'.\n", + "[49,neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml, INFO, [63:13;63:123]]: Implicit casting from (compatible) type 'ms' to 'real'.\n", "[50,GLOBAL, INFO]: Successfully constructed neuron-synapse pair iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml, neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml\n", "[51,GLOBAL, INFO]: Analysing/transforming model 'iaf_psc_delta_neuron_nestml'\n", "[52,iaf_psc_delta_neuron_nestml, INFO, [43:0;94:0]]: Starts processing of the model 'iaf_psc_delta_neuron_nestml'\n" @@ -359,10 +362,6 @@ "name": "stderr", "output_type": "stream", "text": [ - "INFO:Shape V_m: reconstituting expression E_L/tau_m - V_m/tau_m + I_e/C_m + I_stim/C_m\n", - "INFO:Saving dependency graph plot to /tmp/ode_dependency_graph_analytically_solvable_before_propagated.dot\n", - "INFO:Saving dependency graph plot to /tmp/ode_dependency_graph_analytically_solvable.dot\n", - "INFO:Generating propagators for the following symbols: V_m\n", "INFO:update_expr[V_m] = -E_L*__P__V_m__V_m + E_L + V_m*__P__V_m__V_m - I_e*__P__V_m__V_m*tau_m/C_m + I_e*tau_m/C_m - I_stim*__P__V_m__V_m*tau_m/C_m + I_stim*tau_m/C_m\n", "WARNING:Not preserving expression for variable \"V_m\" as it is solved by propagator solver\n", "INFO:In ode-toolbox: returning outdict = \n", @@ -431,7 +430,7 @@ "Processing differential-equation form shape post_tr__for_neuromodulated_stdp_synapse_nestml with defining expression = \"(-post_tr__for_neuromodulated_stdp_synapse_nestml) / tau_tr_post__for_neuromodulated_stdp_synapse_nestml\"\n", "INFO:\tReturning shape: Shape \"post_tr__for_neuromodulated_stdp_synapse_nestml\" of order 1\n", "INFO:Shape post_tr__for_neuromodulated_stdp_synapse_nestml: reconstituting expression -post_tr__for_neuromodulated_stdp_synapse_nestml/tau_tr_post__for_neuromodulated_stdp_synapse_nestml\n", - "INFO:All known variables: [V_m, post_tr__for_neuromodulated_stdp_synapse_nestml], all parameters used in ODEs: {tau_m, I_e, C_m, I_stim, E_L, tau_tr_post__for_neuromodulated_stdp_synapse_nestml}\n", + "INFO:All known variables: [V_m, post_tr__for_neuromodulated_stdp_synapse_nestml], all parameters used in ODEs: {I_e, I_stim, tau_m, C_m, E_L, tau_tr_post__for_neuromodulated_stdp_synapse_nestml}\n", "INFO:No numerical value specified for parameter \"I_stim\"\n", "INFO:\n", "Processing differential-equation form shape V_m with defining expression = \"(-(V_m - E_L)) / tau_m + 0 * (1.0 / 1.0) + (I_e + I_stim) / C_m\"\n", @@ -442,7 +441,12 @@ "INFO:Shape V_m: reconstituting expression E_L/tau_m - V_m/tau_m + I_e/C_m + I_stim/C_m\n", "INFO:Shape post_tr__for_neuromodulated_stdp_synapse_nestml: reconstituting expression -post_tr__for_neuromodulated_stdp_synapse_nestml/tau_tr_post__for_neuromodulated_stdp_synapse_nestml\n", "INFO:Finding analytically solvable equations...\n", - "INFO:Saving dependency graph plot to /tmp/ode_dependency_graph.dot\n" + "INFO:Saving dependency graph plot to /tmp/ode_dependency_graph.dot\n", + "INFO:Shape V_m: reconstituting expression E_L/tau_m - V_m/tau_m + I_e/C_m + I_stim/C_m\n", + "INFO:Shape post_tr__for_neuromodulated_stdp_synapse_nestml: reconstituting expression -post_tr__for_neuromodulated_stdp_synapse_nestml/tau_tr_post__for_neuromodulated_stdp_synapse_nestml\n", + "INFO:Saving dependency graph plot to /tmp/ode_dependency_graph_analytically_solvable_before_propagated.dot\n", + "INFO:Saving dependency graph plot to /tmp/ode_dependency_graph_analytically_solvable.dot\n", + "INFO:Generating propagators for the following symbols: V_m, post_tr__for_neuromodulated_stdp_synapse_nestml\n" ] }, { @@ -457,11 +461,6 @@ "name": "stderr", "output_type": "stream", "text": [ - "INFO:Shape V_m: reconstituting expression E_L/tau_m - V_m/tau_m + I_e/C_m + I_stim/C_m\n", - "INFO:Shape post_tr__for_neuromodulated_stdp_synapse_nestml: reconstituting expression -post_tr__for_neuromodulated_stdp_synapse_nestml/tau_tr_post__for_neuromodulated_stdp_synapse_nestml\n", - "INFO:Saving dependency graph plot to /tmp/ode_dependency_graph_analytically_solvable_before_propagated.dot\n", - "INFO:Saving dependency graph plot to /tmp/ode_dependency_graph_analytically_solvable.dot\n", - "INFO:Generating propagators for the following symbols: V_m, post_tr__for_neuromodulated_stdp_synapse_nestml\n", "INFO:update_expr[V_m] = -E_L*__P__V_m__V_m + E_L + V_m*__P__V_m__V_m - I_e*__P__V_m__V_m*tau_m/C_m + I_e*tau_m/C_m - I_stim*__P__V_m__V_m*tau_m/C_m + I_stim*tau_m/C_m\n", "INFO:update_expr[post_tr__for_neuromodulated_stdp_synapse_nestml] = __P__post_tr__for_neuromodulated_stdp_synapse_nestml__post_tr__for_neuromodulated_stdp_synapse_nestml*post_tr__for_neuromodulated_stdp_synapse_nestml\n", "WARNING:Not preserving expression for variable \"V_m\" as it is solved by propagator solver\n", @@ -536,21 +535,7 @@ "INFO:Finding analytically solvable equations...\n", "INFO:Saving dependency graph plot to /tmp/ode_dependency_graph.dot\n", "INFO:Shape pre_tr: reconstituting expression -pre_tr/tau_tr_pre\n", - "INFO:Saving dependency graph plot to /tmp/ode_dependency_graph_analytically_solvable_before_propagated.dot\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[57,GLOBAL, INFO]: Analysing/transforming synapse neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.\n", - "[58,neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml, INFO, [2:0;66:0]]: Starts processing of the model 'neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml'\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ + "INFO:Saving dependency graph plot to /tmp/ode_dependency_graph_analytically_solvable_before_propagated.dot\n", "INFO:Saving dependency graph plot to /tmp/ode_dependency_graph_analytically_solvable.dot\n", "INFO:Generating propagators for the following symbols: pre_tr\n", "INFO:update_expr[pre_tr] = __P__pre_tr__pre_tr*pre_tr\n", @@ -582,25 +567,27 @@ "name": "stdout", "output_type": "stream", "text": [ - "[60,neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml, WARNING, [12:8;12:28]]: Variable 'd' has the same name as a physical unit!\n", + "[57,GLOBAL, INFO]: Analysing/transforming synapse neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.\n", + "[58,neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml, INFO, [2:0;66:0]]: Starts processing of the model 'neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml'\n", + "[60,neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml, WARNING, [12:8;12:17]]: Variable 'd' has the same name as a physical unit!\n", "[61,neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml, INFO, [40:13;40:20]]: Implicit casting from (compatible) type '1 / ms' to 'real'.\n", "[62,neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml, INFO, [63:13;63:123]]: Implicit casting from (compatible) type 'ms' to 'real'.\n", - "[64,neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml, WARNING, [12:8;12:28]]: Variable 'd' has the same name as a physical unit!\n", + "[64,neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml, WARNING, [12:8;12:17]]: Variable 'd' has the same name as a physical unit!\n", "[65,neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml, INFO, [40:13;40:20]]: Implicit casting from (compatible) type '1 / ms' to 'real'.\n", "[66,neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml, INFO, [63:13;63:123]]: Implicit casting from (compatible) type 'ms' to 'real'.\n", - "[67,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_delta_neuron_nestml.cpp\n", - "[68,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_delta_neuron_nestml.h\n", - "[69,iaf_psc_delta_neuron_nestml, INFO, [43:0;94:0]]: Successfully generated code for the model: 'iaf_psc_delta_neuron_nestml' in: '/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target' !\n", - "[70,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml.cpp\n", - "[71,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml.h\n", - "[72,iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml, INFO, [43:0;94:0]]: Successfully generated code for the model: 'iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml' in: '/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target' !\n", + "[67,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_delta_neuron_nestml.cpp\n", + "[68,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_delta_neuron_nestml.h\n", + "[69,iaf_psc_delta_neuron_nestml, INFO, [43:0;94:0]]: Successfully generated code for the model: 'iaf_psc_delta_neuron_nestml' in: '/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target' !\n", + "[70,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml.cpp\n", + "[71,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml.h\n", + "[72,iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml, INFO, [43:0;94:0]]: Successfully generated code for the model: 'iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml' in: '/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target' !\n", "Generating code for the synapse neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.\n", - "[73,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h\n", - "[74,neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml, INFO, [2:0;66:0]]: Successfully generated code for the model: 'neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml' in: '/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target' !\n", - "[75,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/nestml_9557cf48dd76469a8f5dc4ea86b34c42_module.cpp\n", - "[76,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/nestml_9557cf48dd76469a8f5dc4ea86b34c42_module.h\n", - "[77,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/CMakeLists.txt\n", - "[78,GLOBAL, INFO]: Successfully generated NEST module code in '/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target' !\n", + "[73,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h\n", + "[74,neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml, INFO, [2:0;66:0]]: Successfully generated code for the model: 'neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml' in: '/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target' !\n", + "[75,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/nestml_1f94265a976d4c6991a70527349fa66f_module.cpp\n", + "[76,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/nestml_1f94265a976d4c6991a70527349fa66f_module.h\n", + "[77,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/CMakeLists.txt\n", + "[78,GLOBAL, INFO]: Successfully generated NEST module code in '/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target' !\n", "CMake Warning (dev) at CMakeLists.txt:95 (project):\n", " cmake_minimum_required() should be called prior to this top-level project()\n", " call. Please see the cmake-commands(7) manual for usage documentation of\n", @@ -615,7 +602,7 @@ "-- Detecting CXX compile features - done\n", "\n", "-------------------------------------------------------\n", - "nestml_9557cf48dd76469a8f5dc4ea86b34c42_module Configuration Summary\n", + "nestml_1f94265a976d4c6991a70527349fa66f_module Configuration Summary\n", "-------------------------------------------------------\n", "\n", "C++ compiler : /usr/bin/c++\n", @@ -627,15 +614,15 @@ "\n", "-------------------------------------------------------\n", "\n", - "You can now build and install 'nestml_9557cf48dd76469a8f5dc4ea86b34c42_module' using\n", + "You can now build and install 'nestml_1f94265a976d4c6991a70527349fa66f_module' using\n", " make\n", " make install\n", "\n", - "The library file libnestml_9557cf48dd76469a8f5dc4ea86b34c42_module.so will be installed to\n", - " /tmp/nestml_target_2nbwam92\n", + "The library file libnestml_1f94265a976d4c6991a70527349fa66f_module.so will be installed to\n", + " /tmp/nestml_target_b49vsj8e\n", "The module can be loaded into NEST using\n", - " (nestml_9557cf48dd76469a8f5dc4ea86b34c42_module) Install (in SLI)\n", - " nest.Install(nestml_9557cf48dd76469a8f5dc4ea86b34c42_module) (in PyNEST)\n", + " (nestml_1f94265a976d4c6991a70527349fa66f_module) Install (in SLI)\n", + " nest.Install(nestml_1f94265a976d4c6991a70527349fa66f_module) (in PyNEST)\n", "\n", "CMake Warning (dev) in CMakeLists.txt:\n", " No cmake_minimum_required command is present. A line of code such as\n", @@ -647,169 +634,184 @@ " information run \"cmake --help-policy CMP0000\".\n", "This warning is for project developers. Use -Wno-dev to suppress it.\n", "\n", - "-- Configuring done (0.5s)\n", + "-- Configuring done (0.1s)\n", "-- Generating done (0.0s)\n", - "-- Build files have been written to: /home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target\n", - "[ 25%] Building CXX object CMakeFiles/nestml_9557cf48dd76469a8f5dc4ea86b34c42_module_module.dir/nestml_9557cf48dd76469a8f5dc4ea86b34c42_module.o\n", - "[ 50%] Building CXX object CMakeFiles/nestml_9557cf48dd76469a8f5dc4ea86b34c42_module_module.dir/iaf_psc_delta_neuron_nestml.o\n", - "[ 75%] Building CXX object CMakeFiles/nestml_9557cf48dd76469a8f5dc4ea86b34c42_module_module.dir/iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml.o\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml.cpp: In member function ‘void iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml::init_state_internal_()’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml.cpp:183:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + "-- Build files have been written to: /home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target\n", + "[ 25%] Building CXX object CMakeFiles/nestml_1f94265a976d4c6991a70527349fa66f_module_module.dir/nestml_1f94265a976d4c6991a70527349fa66f_module.o\n", + "[ 50%] Building CXX object CMakeFiles/nestml_1f94265a976d4c6991a70527349fa66f_module_module.dir/iaf_psc_delta_neuron_nestml.o\n", + "[ 75%] Building CXX object CMakeFiles/nestml_1f94265a976d4c6991a70527349fa66f_module_module.dir/iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml.o\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml.cpp: In member function ‘void iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml::init_state_internal_()’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml.cpp:183:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", " 183 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml.cpp: In member function ‘virtual void iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml::update(const nest::Time&, long int, long int)’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml.cpp:287:24: warning: comparison of integer expressions of different signedness: ‘long int’ and ‘const size_t’ {aka ‘const long unsigned int’} [-Wsign-compare]\n", - " 287 | for (long i = 0; i < NUM_SPIKE_RECEPTORS; ++i)\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml.cpp: In member function ‘virtual void iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml::update(const nest::Time&, long int, long int)’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml.cpp:283:24: warning: comparison of integer expressions of different signedness: ‘long int’ and ‘const size_t’ {aka ‘const long unsigned int’} [-Wsign-compare]\n", + " 283 | for (long i = 0; i < NUM_SPIKE_RECEPTORS; ++i)\n", " | ~~^~~~~~~~~~~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml.cpp:282:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 282 | auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml.cpp:278:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 278 | auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_delta_neuron_nestml.cpp: In member function ‘void iaf_psc_delta_neuron_nestml::init_state_internal_()’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_delta_neuron_nestml.cpp:173:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_delta_neuron_nestml.cpp: In member function ‘void iaf_psc_delta_neuron_nestml::init_state_internal_()’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_delta_neuron_nestml.cpp:173:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", " 173 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_delta_neuron_nestml.cpp: In member function ‘virtual void iaf_psc_delta_neuron_nestml::update(const nest::Time&, long int, long int)’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_delta_neuron_nestml.cpp:266:24: warning: comparison of integer expressions of different signedness: ‘long int’ and ‘const size_t’ {aka ‘const long unsigned int’} [-Wsign-compare]\n", - " 266 | for (long i = 0; i < NUM_SPIKE_RECEPTORS; ++i)\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_delta_neuron_nestml.cpp: In member function ‘virtual void iaf_psc_delta_neuron_nestml::update(const nest::Time&, long int, long int)’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_delta_neuron_nestml.cpp:262:24: warning: comparison of integer expressions of different signedness: ‘long int’ and ‘const size_t’ {aka ‘const long unsigned int’} [-Wsign-compare]\n", + " 262 | for (long i = 0; i < NUM_SPIKE_RECEPTORS; ++i)\n", " | ~~^~~~~~~~~~~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_delta_neuron_nestml.cpp:261:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 261 | auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", - " | ^~~~~\n", - "In file included from /home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/nestml_9557cf48dd76469a8f5dc4ea86b34c42_module.cpp:36:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_delta_neuron_nestml.cpp:257:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 257 | auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", + " | ^~~~~\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "In file included from /home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/nestml_1f94265a976d4c6991a70527349fa66f_module.cpp:36:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_model.h:164:25: required from ‘nest::GenericConnectorModel::GenericConnectorModel(std::string) [with ConnectionT = nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:62:5: required from ‘void nest::ModelManager::register_connection_model(const std::string&) [with ConnectionT = nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/nest_impl.h:37:70: required from ‘void nest::register_connection_model(const std::string&) [with ConnectorModelT = neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:671:106: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:862:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 862 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:656:106: required from here\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:858:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 858 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::recompute_internal_variables() [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:876:3: required from ‘nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierPtrRport]’\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::recompute_internal_variables() [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:873:3: required from ‘nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierPtrRport]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_model.h:164:25: required from ‘nest::GenericConnectorModel::GenericConnectorModel(std::string) [with ConnectionT = nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:62:5: required from ‘void nest::ModelManager::register_connection_model(const std::string&) [with ConnectionT = nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/nest_impl.h:37:70: required from ‘void nest::register_connection_model(const std::string&) [with ConnectorModelT = neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:671:106: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:849:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 849 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:656:106: required from here\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:845:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 845 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierIndex]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierIndex]’:\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_model.h:164:25: required from ‘nest::GenericConnectorModel::GenericConnectorModel(std::string) [with ConnectionT = nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:103:34: required from ‘void nest::ModelManager::register_specific_connection_model_(const std::string&) [with CompleteConnecionT = nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:67:80: required from ‘void nest::ModelManager::register_connection_model(const std::string&) [with ConnectionT = nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/nest_impl.h:37:70: required from ‘void nest::register_connection_model(const std::string&) [with ConnectorModelT = neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:671:106: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:862:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 862 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:656:106: required from here\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:858:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 858 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::recompute_internal_variables() [with targetidentifierT = nest::TargetIdentifierIndex]’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:876:3: required from ‘nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierIndex]’\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::recompute_internal_variables() [with targetidentifierT = nest::TargetIdentifierIndex]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:873:3: required from ‘nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierIndex]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_model.h:164:25: required from ‘nest::GenericConnectorModel::GenericConnectorModel(std::string) [with ConnectionT = nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:103:34: required from ‘void nest::ModelManager::register_specific_connection_model_(const std::string&) [with CompleteConnecionT = nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:67:80: required from ‘void nest::ModelManager::register_connection_model(const std::string&) [with ConnectionT = nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/nest_impl.h:37:70: required from ‘void nest::register_connection_model(const std::string&) [with ConnectorModelT = neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:671:106: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:849:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 849 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:656:106: required from here\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:845:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 845 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘bool nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport; size_t = long unsigned int]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘bool nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport; size_t = long unsigned int]’:\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:391:22: required from ‘void nest::Connector::send_to_all(size_t, const std::vector&, nest::Event&) [with ConnectionT = nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:383:3: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:589:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 589 | auto get_t = [_tr_t](){ return _tr_t; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:574:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 574 | auto get_t = [_tr_t](){ return _tr_t; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:614:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 614 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:599:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 599 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:649:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 649 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:634:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 634 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:517:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 517 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:502:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 502 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:519:10: warning: variable ‘get_thread’ set but not used [-Wunused-but-set-variable]\n", - " 519 | auto get_thread = [tid]()\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:504:10: warning: variable ‘get_thread’ set but not used [-Wunused-but-set-variable]\n", + " 504 | auto get_thread = [tid]()\n", " | ^~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::trigger_update_weight(size_t, const std::vector&, double, const CommonPropertiesType&) [with targetidentifierT = nest::TargetIdentifierPtrRport; size_t = long unsigned int; CommonPropertiesType = nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::trigger_update_weight(size_t, const std::vector&, double, const CommonPropertiesType&) [with targetidentifierT = nest::TargetIdentifierPtrRport; size_t = long unsigned int; CommonPropertiesType = nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties]’:\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:446:38: required from ‘void nest::Connector::trigger_update_weight(long int, size_t, const std::vector&, double, const std::vector&) [with ConnectionT = nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:433:3: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:1009:18: warning: unused variable ‘_tr_t’ [-Wunused-variable]\n", - " 1009 | const double _tr_t = start->t_;\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:1003:18: warning: unused variable ‘_tr_t’ [-Wunused-variable]\n", + " 1003 | const double _tr_t = start->t_;\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:991:10: warning: unused variable ‘timestep’ [-Wunused-variable]\n", - " 991 | double timestep = 0;\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:985:10: warning: unused variable ‘timestep’ [-Wunused-variable]\n", + " 985 | double timestep = 0;\n", " | ^~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘bool nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex; size_t = long unsigned int]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘bool nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex; size_t = long unsigned int]’:\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:391:22: required from ‘void nest::Connector::send_to_all(size_t, const std::vector&, nest::Event&) [with ConnectionT = nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:383:3: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:589:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 589 | auto get_t = [_tr_t](){ return _tr_t; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:574:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 574 | auto get_t = [_tr_t](){ return _tr_t; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:614:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 614 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:599:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 599 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:649:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 649 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:634:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 634 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:517:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 517 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:502:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 502 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:519:10: warning: variable ‘get_thread’ set but not used [-Wunused-but-set-variable]\n", - " 519 | auto get_thread = [tid]()\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:504:10: warning: variable ‘get_thread’ set but not used [-Wunused-but-set-variable]\n", + " 504 | auto get_thread = [tid]()\n", " | ^~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::trigger_update_weight(size_t, const std::vector&, double, const CommonPropertiesType&) [with targetidentifierT = nest::TargetIdentifierIndex; size_t = long unsigned int; CommonPropertiesType = nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::trigger_update_weight(size_t, const std::vector&, double, const CommonPropertiesType&) [with targetidentifierT = nest::TargetIdentifierIndex; size_t = long unsigned int; CommonPropertiesType = nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties]’:\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:446:38: required from ‘void nest::Connector::trigger_update_weight(long int, size_t, const std::vector&, double, const std::vector&) [with ConnectionT = nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:433:3: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:1009:18: warning: unused variable ‘_tr_t’ [-Wunused-variable]\n", - " 1009 | const double _tr_t = start->t_;\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:1003:18: warning: unused variable ‘_tr_t’ [-Wunused-variable]\n", + " 1003 | const double _tr_t = start->t_;\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:991:10: warning: unused variable ‘timestep’ [-Wunused-variable]\n", - " 991 | double timestep = 0;\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:985:10: warning: unused variable ‘timestep’ [-Wunused-variable]\n", + " 985 | double timestep = 0;\n", " | ^~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::process_mod_spikes_spikes_(const std::vector&, double, double, const nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:563:9: required from ‘bool nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport; size_t = long unsigned int]’\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::process_mod_spikes_spikes_(const std::vector&, double, double, const nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:548:9: required from ‘bool nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:391:22: required from ‘void nest::Connector::send_to_all(size_t, const std::vector&, nest::Event&) [with ConnectionT = nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:383:3: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:699:12: warning: unused variable ‘cd’ [-Wunused-variable]\n", - " 699 | double cd;\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:684:12: warning: unused variable ‘cd’ [-Wunused-variable]\n", + " 684 | double cd;\n", " | ^~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::update_internal_state_(double, double, const nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:584:9: required from ‘bool nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport; size_t = long unsigned int]’\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::update_internal_state_(double, double, const nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:569:9: required from ‘bool nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:391:22: required from ‘void nest::Connector::send_to_all(size_t, const std::vector&, nest::Event&) [with ConnectionT = nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:383:3: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:935:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 935 | auto get_t = [t_start](){ return t_start; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:929:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 929 | auto get_t = [t_start](){ return t_start; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::process_mod_spikes_spikes_(const std::vector&, double, double, const nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex]’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:563:9: required from ‘bool nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex; size_t = long unsigned int]’\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::process_mod_spikes_spikes_(const std::vector&, double, double, const nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:548:9: required from ‘bool nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:391:22: required from ‘void nest::Connector::send_to_all(size_t, const std::vector&, nest::Event&) [with ConnectionT = nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:383:3: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:699:12: warning: unused variable ‘cd’ [-Wunused-variable]\n", - " 699 | double cd;\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:684:12: warning: unused variable ‘cd’ [-Wunused-variable]\n", + " 684 | double cd;\n", " | ^~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::update_internal_state_(double, double, const nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex]’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:584:9: required from ‘bool nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex; size_t = long unsigned int]’\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::update_internal_state_(double, double, const nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:569:9: required from ‘bool nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:391:22: required from ‘void nest::Connector::send_to_all(size_t, const std::vector&, nest::Event&) [with ConnectionT = nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:383:3: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:935:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 935 | auto get_t = [t_start](){ return t_start; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", - " | ^~~~~\n", - "[100%] Linking CXX shared module nestml_9557cf48dd76469a8f5dc4ea86b34c42_module.so\n", - "[100%] Built target nestml_9557cf48dd76469a8f5dc4ea86b34c42_module_module\n", - "[100%] Built target nestml_9557cf48dd76469a8f5dc4ea86b34c42_module_module\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:929:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 929 | auto get_t = [t_start](){ return t_start; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + " | ^~~~~\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[100%] Linking CXX shared module nestml_1f94265a976d4c6991a70527349fa66f_module.so\n", + "[100%] Built target nestml_1f94265a976d4c6991a70527349fa66f_module_module\n", + "[100%] Built target nestml_1f94265a976d4c6991a70527349fa66f_module_module\n", "Install the project...\n", "-- Install configuration: \"\"\n", - "-- Installing: /tmp/nestml_target_2nbwam92/nestml_9557cf48dd76469a8f5dc4ea86b34c42_module.so\n" + "-- Installing: /tmp/nestml_target_b49vsj8e/nestml_1f94265a976d4c6991a70527349fa66f_module.so\n" ] } ], "source": [ "# generate and build code\n", - "module_name, neuron_model_name, synapse_model_name = NESTCodeGeneratorUtils.generate_code_for(\"../../../models/neurons/iaf_psc_delta_neuron.nestml\",\n", - " nestml_stdp_dopa_model,\n", - " post_ports=[\"post_spikes\"],\n", - " mod_ports=[\"mod_spikes\"],\n", - " logging_level=\"INFO\")\n" + "module_name, neuron_model_name, synapse_model_name = \\\n", + " NESTCodeGeneratorUtils.generate_code_for(\"../../../models/neurons/iaf_psc_delta_neuron.nestml\",\n", + " nestml_stdp_dopa_model,\n", + " post_ports=[\"post_spikes\"],\n", + " mod_ports=[\"mod_spikes\"],\n", + " logging_level=\"INFO\",\n", + " codegen_opts={\"delay_variable\": {\"neuromodulated_stdp_synapse\": \"d\"},\n", + " \"weight_variable\": {\"neuromodulated_stdp_synapse\": \"w\"}})" ] }, { @@ -875,13 +877,12 @@ " # set up custom synapse models\n", " wr = nest.Create('weight_recorder')\n", " nest.CopyModel(synapse_model_name, \"stdp_nestml_rec\",\n", - " {\"weight_recorder\": wr[0],\n", - " \"w\": 1.,\n", - " \"delay\": delay,\n", - " \"receptor_type\": 0,\n", - " \"volume_transmitter\": vt,\n", - " \"tau_tr_pre\": 10.,\n", - " })\n", + " {\"weight_recorder\": wr[0],\n", + " \"w\": 1.,\n", + " \"delay\": delay,\n", + " \"receptor_type\": 0,\n", + " \"volume_transmitter\": vt,\n", + " \"tau_tr_pre\": 10.})\n", "\n", " # create parrot neurons and connect spike_generators\n", " pre_neuron = nest.Create(\"parrot_neuron\")\n", @@ -974,635 +975,641 @@ "output_type": "stream", "text": [ "\n", - "Apr 19 11:33:12 Install [Info]: \n", - " loaded module nestml_9557cf48dd76469a8f5dc4ea86b34c42_module\n", + "Apr 30 14:14:09 Install [Info]: \n", + " loaded module nestml_1f94265a976d4c6991a70527349fa66f_module\n", "\n", - "Apr 19 11:33:12 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:14:09 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:12 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:14:09 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:12 SimulationManager::set_status [Info]: \n", + "Apr 30 14:14:09 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 0.1 ms.\n", "\n", - "Apr 19 11:33:12 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:14:09 NodeManager::prepare_nodes [Info]: \n", " Preparing 11 nodes for simulation.\n", "\n", - "Apr 19 11:33:12 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:09 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 11\n", " Simulation time (ms): 10000\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:12 SimulationManager::run [Info]: \n", + "Apr 30 14:14:09 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:12 Install [Info]: \n", - " loaded module nestml_9557cf48dd76469a8f5dc4ea86b34c42_module\n", + "Apr 30 14:14:09 Install [Info]: \n", + " loaded module nestml_1f94265a976d4c6991a70527349fa66f_module\n", "\n", - "Apr 19 11:33:12 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:14:09 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:12 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:14:09 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:12 SimulationManager::set_status [Info]: \n", + "Apr 30 14:14:09 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 0.1 ms.\n", "\n", - "Apr 19 11:33:12 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:14:09 NodeManager::prepare_nodes [Info]: \n", " Preparing 11 nodes for simulation.\n", "\n", - "Apr 19 11:33:12 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:09 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 11\n", " Simulation time (ms): 10000\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:13 SimulationManager::run [Info]: \n", + "Apr 30 14:14:09 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:13 Install [Info]: \n", - " loaded module nestml_9557cf48dd76469a8f5dc4ea86b34c42_module\n", + "Apr 30 14:14:09 Install [Info]: \n", + " loaded module nestml_1f94265a976d4c6991a70527349fa66f_module\n", "\n", - "Apr 19 11:33:13 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:14:09 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:13 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:14:09 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:13 SimulationManager::set_status [Info]: \n", + "Apr 30 14:14:09 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 0.1 ms.\n", "\n", - "Apr 19 11:33:13 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:14:09 NodeManager::prepare_nodes [Info]: \n", " Preparing 11 nodes for simulation.\n", "\n", - "Apr 19 11:33:13 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:09 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 11\n", " Simulation time (ms): 10000\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:13 SimulationManager::run [Info]: \n", + "Apr 30 14:14:09 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:13 Install [Info]: \n", - " loaded module nestml_9557cf48dd76469a8f5dc4ea86b34c42_module\n", + "Apr 30 14:14:09 Install [Info]: \n", + " loaded module nestml_1f94265a976d4c6991a70527349fa66f_module\n", "\n", - "Apr 19 11:33:13 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:14:09 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:13 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:14:09 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:13 SimulationManager::set_status [Info]: \n", + "Apr 30 14:14:09 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 0.1 ms.\n", "\n", - "Apr 19 11:33:13 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:14:09 NodeManager::prepare_nodes [Info]: \n", " Preparing 11 nodes for simulation.\n", "\n", - "Apr 19 11:33:13 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:09 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 11\n", " Simulation time (ms): 10000\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:13 SimulationManager::run [Info]: \n", + "Apr 30 14:14:09 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:13 Install [Info]: \n", - " loaded module nestml_9557cf48dd76469a8f5dc4ea86b34c42_module\n", + "Apr 30 14:14:09 Install [Info]: \n", + " loaded module nestml_1f94265a976d4c6991a70527349fa66f_module\n", "\n", - "Apr 19 11:33:13 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:14:09 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:13 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:14:09 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:13 SimulationManager::set_status [Info]: \n", + "Apr 30 14:14:09 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 0.1 ms.\n", "\n", - "Apr 19 11:33:13 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:14:09 NodeManager::prepare_nodes [Info]: \n", " Preparing 11 nodes for simulation.\n", "\n", - "Apr 19 11:33:13 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:09 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 11\n", " Simulation time (ms): 10000\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:13 SimulationManager::run [Info]: \n", + "Apr 30 14:14:09 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:13 Install [Info]: \n", - " loaded module nestml_9557cf48dd76469a8f5dc4ea86b34c42_module\n", + "Apr 30 14:14:09 Install [Info]: \n", + " loaded module nestml_1f94265a976d4c6991a70527349fa66f_module\n", "\n", - "Apr 19 11:33:13 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:14:09 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:13 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:14:09 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:13 SimulationManager::set_status [Info]: \n", + "Apr 30 14:14:09 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 0.1 ms.\n", "\n", - "Apr 19 11:33:13 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:14:09 NodeManager::prepare_nodes [Info]: \n", " Preparing 11 nodes for simulation.\n", "\n", - "Apr 19 11:33:13 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:09 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 11\n", " Simulation time (ms): 10000\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:13 SimulationManager::run [Info]: \n", + "Apr 30 14:14:09 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:13 Install [Info]: \n", - " loaded module nestml_9557cf48dd76469a8f5dc4ea86b34c42_module\n", + "Apr 30 14:14:09 Install [Info]: \n", + " loaded module nestml_1f94265a976d4c6991a70527349fa66f_module\n", "\n", - "Apr 19 11:33:13 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:14:09 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:13 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:14:09 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:13 SimulationManager::set_status [Info]: \n", + "Apr 30 14:14:09 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 0.1 ms.\n", "\n", - "Apr 19 11:33:13 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:14:09 NodeManager::prepare_nodes [Info]: \n", " Preparing 11 nodes for simulation.\n", "\n", - "Apr 19 11:33:13 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:09 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 11\n", " Simulation time (ms): 10000\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:13 SimulationManager::run [Info]: \n", + "Apr 30 14:14:09 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:13 Install [Info]: \n", - " loaded module nestml_9557cf48dd76469a8f5dc4ea86b34c42_module\n", + "Apr 30 14:14:09 Install [Info]: \n", + " loaded module nestml_1f94265a976d4c6991a70527349fa66f_module\n", "\n", - "Apr 19 11:33:13 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:14:09 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:13 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:14:09 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:13 SimulationManager::set_status [Info]: \n", + "Apr 30 14:14:09 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 0.1 ms.\n", "\n", - "Apr 19 11:33:13 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:14:09 NodeManager::prepare_nodes [Info]: \n", " Preparing 11 nodes for simulation.\n", "\n", - "Apr 19 11:33:13 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:09 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 11\n", " Simulation time (ms): 10000\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:13 SimulationManager::run [Info]: \n", + "Apr 30 14:14:09 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:13 Install [Info]: \n", - " loaded module nestml_9557cf48dd76469a8f5dc4ea86b34c42_module\n", + "Apr 30 14:14:09 Install [Info]: \n", + " loaded module nestml_1f94265a976d4c6991a70527349fa66f_module\n", "\n", - "Apr 19 11:33:13 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:14:09 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:13 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:14:09 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:13 SimulationManager::set_status [Info]: \n", + "Apr 30 14:14:09 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 0.1 ms.\n", "\n", - "Apr 19 11:33:13 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:14:09 NodeManager::prepare_nodes [Info]: \n", " Preparing 11 nodes for simulation.\n", "\n", - "Apr 19 11:33:13 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:09 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 11\n", " Simulation time (ms): 10000\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:13 SimulationManager::run [Info]: \n", + "Apr 30 14:14:09 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:13 Install [Info]: \n", - " loaded module nestml_9557cf48dd76469a8f5dc4ea86b34c42_module\n", + "Apr 30 14:14:09 Install [Info]: \n", + " loaded module nestml_1f94265a976d4c6991a70527349fa66f_module\n", "\n", - "Apr 19 11:33:13 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:14:09 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:13 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:14:09 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:13 SimulationManager::set_status [Info]: \n", + "Apr 30 14:14:09 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 0.1 ms.\n", "\n", - "Apr 19 11:33:13 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:14:09 NodeManager::prepare_nodes [Info]: \n", " Preparing 11 nodes for simulation.\n", "\n", - "Apr 19 11:33:13 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:09 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 11\n", " Simulation time (ms): 10000\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:13 SimulationManager::run [Info]: \n", + "Apr 30 14:14:09 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:13 Install [Info]: \n", - " loaded module nestml_9557cf48dd76469a8f5dc4ea86b34c42_module\n", + "Apr 30 14:14:09 Install [Info]: \n", + " loaded module nestml_1f94265a976d4c6991a70527349fa66f_module\n", "\n", - "Apr 19 11:33:13 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:14:09 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:13 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:14:09 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:13 SimulationManager::set_status [Info]: \n", + "Apr 30 14:14:09 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 0.1 ms.\n", "\n", - "Apr 19 11:33:13 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:14:09 NodeManager::prepare_nodes [Info]: \n", " Preparing 11 nodes for simulation.\n", "\n", - "Apr 19 11:33:13 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:09 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 11\n", " Simulation time (ms): 10000\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:13 SimulationManager::run [Info]: \n", + "Apr 30 14:14:09 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:13 Install [Info]: \n", - " loaded module nestml_9557cf48dd76469a8f5dc4ea86b34c42_module\n", + "Apr 30 14:14:09 Install [Info]: \n", + " loaded module nestml_1f94265a976d4c6991a70527349fa66f_module\n", "\n", - "Apr 19 11:33:13 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:14:09 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:13 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:14:09 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:13 SimulationManager::set_status [Info]: \n", + "Apr 30 14:14:09 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 0.1 ms.\n", "\n", - "Apr 19 11:33:13 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:14:09 NodeManager::prepare_nodes [Info]: \n", " Preparing 11 nodes for simulation.\n", "\n", - "Apr 19 11:33:13 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:09 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 11\n", " Simulation time (ms): 10000\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:13 SimulationManager::run [Info]: \n", + "Apr 30 14:14:09 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:13 Install [Info]: \n", - " loaded module nestml_9557cf48dd76469a8f5dc4ea86b34c42_module\n", + "Apr 30 14:14:09 Install [Info]: \n", + " loaded module nestml_1f94265a976d4c6991a70527349fa66f_module\n", "\n", - "Apr 19 11:33:13 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:14:09 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:13 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:14:09 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:13 SimulationManager::set_status [Info]: \n", + "Apr 30 14:14:09 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 0.1 ms.\n", "\n", - "Apr 19 11:33:13 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:14:09 NodeManager::prepare_nodes [Info]: \n", " Preparing 11 nodes for simulation.\n", "\n", - "Apr 19 11:33:13 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:09 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 11\n", " Simulation time (ms): 10000\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:13 SimulationManager::run [Info]: \n", + "Apr 30 14:14:09 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:13 Install [Info]: \n", - " loaded module nestml_9557cf48dd76469a8f5dc4ea86b34c42_module\n", + "Apr 30 14:14:09 Install [Info]: \n", + " loaded module nestml_1f94265a976d4c6991a70527349fa66f_module\n", "\n", - "Apr 19 11:33:13 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:14:09 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:13 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:14:09 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:13 SimulationManager::set_status [Info]: \n", + "Apr 30 14:14:09 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 0.1 ms.\n", "\n", - "Apr 19 11:33:13 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:14:09 NodeManager::prepare_nodes [Info]: \n", " Preparing 11 nodes for simulation.\n", "\n", - "Apr 19 11:33:13 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:09 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 11\n", " Simulation time (ms): 10000\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:13 SimulationManager::run [Info]: \n", - " Simulation finished.\n", + "Apr 30 14:14:09 SimulationManager::run [Info]: \n", + " Simulation finished.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "\n", - "Apr 19 11:33:13 Install [Info]: \n", - " loaded module nestml_9557cf48dd76469a8f5dc4ea86b34c42_module\n", + "Apr 30 14:14:09 Install [Info]: \n", + " loaded module nestml_1f94265a976d4c6991a70527349fa66f_module\n", "\n", - "Apr 19 11:33:13 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:14:09 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:13 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:14:09 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:13 SimulationManager::set_status [Info]: \n", + "Apr 30 14:14:09 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 0.1 ms.\n", "\n", - "Apr 19 11:33:13 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:14:09 NodeManager::prepare_nodes [Info]: \n", " Preparing 11 nodes for simulation.\n", "\n", - "Apr 19 11:33:13 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:09 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 11\n", " Simulation time (ms): 10000\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:13 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:13 Install [Info]: \n", - " loaded module nestml_9557cf48dd76469a8f5dc4ea86b34c42_module\n", + "Apr 30 14:14:10 Install [Info]: \n", + " loaded module nestml_1f94265a976d4c6991a70527349fa66f_module\n", "\n", - "Apr 19 11:33:13 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:14:10 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:13 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:14:10 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:13 SimulationManager::set_status [Info]: \n", + "Apr 30 14:14:10 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 0.1 ms.\n", "\n", - "Apr 19 11:33:13 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:14:10 NodeManager::prepare_nodes [Info]: \n", " Preparing 11 nodes for simulation.\n", "\n", - "Apr 19 11:33:13 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 11\n", " Simulation time (ms): 10000\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:13 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:13 Install [Info]: \n", - " loaded module nestml_9557cf48dd76469a8f5dc4ea86b34c42_module\n", + "Apr 30 14:14:10 Install [Info]: \n", + " loaded module nestml_1f94265a976d4c6991a70527349fa66f_module\n", "\n", - "Apr 19 11:33:13 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:14:10 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:13 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:14:10 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:13 SimulationManager::set_status [Info]: \n", + "Apr 30 14:14:10 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 0.1 ms.\n", "\n", - "Apr 19 11:33:13 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:14:10 NodeManager::prepare_nodes [Info]: \n", " Preparing 11 nodes for simulation.\n", "\n", - "Apr 19 11:33:13 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 11\n", " Simulation time (ms): 10000\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:13 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:13 Install [Info]: \n", - " loaded module nestml_9557cf48dd76469a8f5dc4ea86b34c42_module\n", + "Apr 30 14:14:10 Install [Info]: \n", + " loaded module nestml_1f94265a976d4c6991a70527349fa66f_module\n", "\n", - "Apr 19 11:33:13 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:14:10 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:13 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:14:10 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:13 SimulationManager::set_status [Info]: \n", + "Apr 30 14:14:10 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 0.1 ms.\n", "\n", - "Apr 19 11:33:13 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:14:10 NodeManager::prepare_nodes [Info]: \n", " Preparing 11 nodes for simulation.\n", "\n", - "Apr 19 11:33:13 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 11\n", " Simulation time (ms): 10000\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:13 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:13 Install [Info]: \n", - " loaded module nestml_9557cf48dd76469a8f5dc4ea86b34c42_module\n", + "Apr 30 14:14:10 Install [Info]: \n", + " loaded module nestml_1f94265a976d4c6991a70527349fa66f_module\n", "\n", - "Apr 19 11:33:13 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:14:10 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:13 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:14:10 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:13 SimulationManager::set_status [Info]: \n", + "Apr 30 14:14:10 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 0.1 ms.\n", "\n", - "Apr 19 11:33:13 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:14:10 NodeManager::prepare_nodes [Info]: \n", " Preparing 11 nodes for simulation.\n", "\n", - "Apr 19 11:33:13 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 11\n", " Simulation time (ms): 10000\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:13 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:13 Install [Info]: \n", - " loaded module nestml_9557cf48dd76469a8f5dc4ea86b34c42_module\n", + "Apr 30 14:14:10 Install [Info]: \n", + " loaded module nestml_1f94265a976d4c6991a70527349fa66f_module\n", "\n", - "Apr 19 11:33:13 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:14:10 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:13 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:14:10 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:13 SimulationManager::set_status [Info]: \n", + "Apr 30 14:14:10 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 0.1 ms.\n", "\n", - "Apr 19 11:33:13 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:14:10 NodeManager::prepare_nodes [Info]: \n", " Preparing 11 nodes for simulation.\n", "\n", - "Apr 19 11:33:13 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 11\n", " Simulation time (ms): 10000\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:13 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:13 Install [Info]: \n", - " loaded module nestml_9557cf48dd76469a8f5dc4ea86b34c42_module\n", + "Apr 30 14:14:10 Install [Info]: \n", + " loaded module nestml_1f94265a976d4c6991a70527349fa66f_module\n", "\n", - "Apr 19 11:33:13 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:14:10 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:13 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:14:10 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:13 SimulationManager::set_status [Info]: \n", + "Apr 30 14:14:10 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 0.1 ms.\n", "\n", - "Apr 19 11:33:13 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:14:10 NodeManager::prepare_nodes [Info]: \n", " Preparing 11 nodes for simulation.\n", "\n", - "Apr 19 11:33:13 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 11\n", " Simulation time (ms): 10000\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:14 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:14 Install [Info]: \n", - " loaded module nestml_9557cf48dd76469a8f5dc4ea86b34c42_module\n", + "Apr 30 14:14:10 Install [Info]: \n", + " loaded module nestml_1f94265a976d4c6991a70527349fa66f_module\n", "\n", - "Apr 19 11:33:14 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:14:10 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:14 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:14:10 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:14 SimulationManager::set_status [Info]: \n", + "Apr 30 14:14:10 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 0.1 ms.\n", "\n", - "Apr 19 11:33:14 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:14:10 NodeManager::prepare_nodes [Info]: \n", " Preparing 11 nodes for simulation.\n", "\n", - "Apr 19 11:33:14 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 11\n", " Simulation time (ms): 10000\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:14 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:14 Install [Info]: \n", - " loaded module nestml_9557cf48dd76469a8f5dc4ea86b34c42_module\n", + "Apr 30 14:14:10 Install [Info]: \n", + " loaded module nestml_1f94265a976d4c6991a70527349fa66f_module\n", "\n", - "Apr 19 11:33:14 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:14:10 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:14 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:14:10 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:14 SimulationManager::set_status [Info]: \n", + "Apr 30 14:14:10 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 0.1 ms.\n", "\n", - "Apr 19 11:33:14 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:14:10 NodeManager::prepare_nodes [Info]: \n", " Preparing 11 nodes for simulation.\n", "\n", - "Apr 19 11:33:14 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 11\n", " Simulation time (ms): 10000\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:14 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:14 Install [Info]: \n", - " loaded module nestml_9557cf48dd76469a8f5dc4ea86b34c42_module\n", + "Apr 30 14:14:10 Install [Info]: \n", + " loaded module nestml_1f94265a976d4c6991a70527349fa66f_module\n", "\n", - "Apr 19 11:33:14 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:14:10 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:14 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:14:10 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:14 SimulationManager::set_status [Info]: \n", + "Apr 30 14:14:10 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 0.1 ms.\n", "\n", - "Apr 19 11:33:14 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:14:10 NodeManager::prepare_nodes [Info]: \n", " Preparing 11 nodes for simulation.\n", "\n", - "Apr 19 11:33:14 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 11\n", " Simulation time (ms): 10000\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:14 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n" ] }, { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 6, @@ -1611,7 +1618,7 @@ }, { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "
" ] @@ -1744,7 +1751,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -1761,18 +1767,18 @@ "output_type": "stream", "text": [ "\n", - "Apr 19 11:33:15 Install [Info]: \n", - " loaded module nestml_9557cf48dd76469a8f5dc4ea86b34c42_module\n", + "Apr 30 14:14:10 Install [Info]: \n", + " loaded module nestml_1f94265a976d4c6991a70527349fa66f_module\n", "\n", - "Apr 19 11:33:15 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:14:10 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:15 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:14:10 iaf_psc_delta_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:33:15 SimulationManager::set_status [Info]: \n", + "Apr 30 14:14:10 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 0.1 ms.\n" ] } @@ -1850,7 +1856,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -1911,7 +1916,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -1932,4007 +1936,4031 @@ "output_type": "stream", "text": [ "0 out of 400\n", + "1 out of 400\n", + "2 out of 400\n", + "3 out of 400\n", + "4 out of 400\n", "\n", - "Apr 19 11:33:15 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:14:10 NodeManager::prepare_nodes [Info]: \n", " Preparing 47 nodes for simulation.\n", - "1 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", - "2 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "3 out of 400\n", - "4 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", + "5 out of 400\n", + "6 out of 400\n", + "7 out of 400\n", + "8 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "5 out of 400\n", - "6 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", - "7 out of 400\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "8 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "9 out of 400\n", "10 out of 400\n", + "11 out of 400\n", + "12 out of 400\n", + "13 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "11 out of 400\n", - "12 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "13 out of 400\n", - "14 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", - " Simulation finished.\n", + "Apr 30 14:14:10 Simulat14 out of 400\n", "15 out of 400\n", + "16 out of 400\n", + "17 out of 400\n", + "18 out of 400\n", + "ionManager::run [Info]: \n", + " Simulation finished.\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "16 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", - "17 out of 400\n", - "18 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "19 out of 400\n", - "20 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", + "19 out of 400\n", + "20 out of 400\n", "21 out of 400\n", "22 out of 400\n", + "23 out of 400\n", + "24 out of 400\n", + "25 out of 400\n", + "26 out of 400\n", + "27 out of 400\n", + "28 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "23 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "24 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "25 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "26 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "27 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "28 out of 400\n", "29 out of 400\n", "30 out of 400\n", "31 out of 400\n", + "32 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", - "32 out of 400\n", + "33 out of 400\n", + "34 out of 400\n", + "35 out of 400\n", + "36 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 Simulat33 out of 400\n", - "34 out of 400\n", - "35 out of 400\n", - "ionManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "36 out of 400\n", - "37 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", - "38 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", + "37 out of 400\n", + "38 out of 400\n", + "39 out of 400\n", + "40 out of 400\n", + "41 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "39 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "40 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "41 out of 400\n", - "42 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", - " Simulation finished.\n", + "Apr 30 14:14:10 Simulat42 out of 400\n", "43 out of 400\n", "44 out of 400\n", + "45 out of 400\n", + "46 out of 400\n", + "47 out of 400\n", + "48 out of 400\n", + "49 out of 400\n", + "50 out of 400\n", + "51 out of 400\n", + "ionManager::run [Info]: \n", + " Simulation finished.\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "45 out of 400\n", - "46 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: 52 out of 400\n", + "53 out of 400\n", + "54 out of 400\n", + "55 out of 400\n", + "\n", " Simulation finished.\n", - "47 out of 400\n", - "48 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "49 out of 400\n", - "50 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "51 out of 400\n", - "52 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "53 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "54 out of 400\n", - "55 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "56 out of 400\n", - "57 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", + "56 out of 400\n", + "57 out of 400\n", + "58 out of 400\n", + "59 out of 400\n", + "60 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "58 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "59 out of 400\n", - "60 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "61 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 Simulat61 out of 400\n", + "62 out of 400\n", + "63 out of 400\n", + "64 out of 400\n", + "65 out of 400\n", + "ionManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "62 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "63 out of 400\n", - "64 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "65 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", + "66 out of 400\n", + "67 out of 400\n", + "68 out of 400\n", + "69 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", - "66 out of 400\n", - "67 out of 400\n", + "70 out of 400\n", + "71 out of 400\n", + "72 out of 400\n", + "73 out of 400\n", + "74 out of 400\n", + "75 out of 400\n", + "76 out of 400\n", + "77 out of 400\n", + "78 out of 400\n", + "79 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "68 out of 400\n", - "69 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 Simulat80 out of 400\n", + "81 out of 400\n", + "82 out of 400\n", + "83 out of 400\n", + "84 out of 400\n", + "85 out of 400\n", + "86 out of 400\n", + "87 out of 400\n", + "88 out of 400\n", + "ionManager::run [Info]: \n", " Simulation finished.\n", - "70 out of 400\n", - "71 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "72 out of 400\n", - "73 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "74 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: 89 out of 400\n", + "90 out of 400\n", + "91 out of 400\n", + "92 out of 400\n", + "93 out of 400\n", + "94 out of 400\n", + "95 out of 400\n", + "96 out of 400\n", + "97 out of 400\n", + "\n", " Simulation finished.\n", - "75 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "76 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", - "77 out of 400\n", - "78 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "79 out of 400\n", - "80 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", - " Simulation finished.\n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", + " Simulation finished98 out of 400\n", + "99 out of 400\n", + "100 out of 400\n", + "101 out of 400\n", + "102 out of 400\n", + "103 out of 400\n", + "104 out of 400\n", + "105 out of 400\n", + "106 out of 400\n", + ".\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "81 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "82 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "83 out of 400\n", - "84 out of 400\n", "\n", - "Apr 19 11:33:15 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 Simul107 out of 400\n", + "108 out of 400\n", + "109 out of 400\n", + "110 out of 400\n", + "111 out of 400\n", + "112 out of 400\n", + "113 out of 400\n", + "114 out of 400\n", + "ationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:15 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "85 out of 400\n", - "86 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "87 out of 400\n", - "88 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_upda115 out of 400\n", + "116 out of 400\n", + "117 out of 400\n", + "118 out of 400\n", + "119 out of 400\n", + "120 out of 400\n", + "121 out of 400\n", + "122 out of 400\n", + "123 out of 400\n", + "ting_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "89 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "90 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 47\n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", + " Numbe124 out of 400\n", + "125 out of 400\n", + "126 out of 400\n", + "127 out of 400\n", + "128 out of 400\n", + "129 out of 400\n", + "130 out of 400\n", + "131 out of 400\n", + "132 out of 400\n", + "r of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "91 out of 400\n", - "92 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "93 out of 400\n", - "94 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "95 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", - " Simulation time (ms): 30\n", + " 133 out of 400\n", + "134 out of 400\n", + "135 out of 400\n", + "136 out of 400\n", + "137 out of 400\n", + "138 out of 400\n", + "139 out of 400\n", + "140 out of 400\n", + " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "96 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "97 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "98 out of 400\n", - "99 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", - " Simulation time (ms): 30\n", + " Simulation time (ms): 3141 out of 400\n", + "142 out of 400\n", + "143 out of 400\n", + "144 out of 400\n", + "145 out of 400\n", + "146 out of 400\n", + "147 out of 400\n", + "148 out of 400\n", + "149 out of 400\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "150 out of 400\n", + "151 out of 400\n", + "152 out of 400\n", + "153 out of 400\n", + "154 out of 400\n", + "0\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "100 out of 400\n", - "101 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "102 out of 400\n", - "103 out of 400\n", - "104 out of 400\n", - "105 out of 400\n", - "106 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "107 out of 400\n", - "108 out of 400\n", - "109 out of 400\n", - "110 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 Simulat111 out of 400\n", - "ionManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "112 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "113 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "114 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Inf155 out of 400\n", + "156 out of 400\n", + "157 out of 400\n", + "158 out of 400\n", + "159 out of 400\n", + "160 out of 400\n", + "161 out of 400\n", + "162 out of 400\n", + "o]: \n", " Simulation finished.\n", - "115 out of 400\n", - "116 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", - "117 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "118 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "119 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "120 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "121 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "122 out of 400\n", - "123 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "124 out of 400\n", - "125 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 S163 out of 400\n", + "164 out of 400\n", + "165 out of 400\n", + "166 out of 400\n", + "167 out of 400\n", + "168 out of 400\n", + "169 out of 400\n", + "170 out of 400\n", + "171 out of 400\n", + "172 out of 400\n", + "173 out of 400\n", + "174 out of 400\n", + "175 out of 400\n", + "176 out of 400\n", + "177 out of 400\n", + "178 out of 400\n", + "179 out of 400\n", + "180 out of 400\n", + "181 out of 400\n", + "182 out of 400\n", + "183 out of 400\n", + "imulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "126 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "127 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "128 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "129 out of 400\n", - "130 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", - "131 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "132 out of 400\n", - "133 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "134 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "135 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "136 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "137 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "138 out of 400\n", - "139 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "140 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "141 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "142 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "143 out of 400\n", - "144 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "145 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "146 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "147 out of 400\n", - "148 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "149 out of 400\n", - "150 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", - "151 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "152 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "153 out of 400\n", - "154 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "155 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", - "156 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run 184 out of 400\n", + "185 out of 400\n", + "186 out of 400\n", + "187 out of 400\n", + "[Info]: \n", " Simulation finished.\n", - "157 out of 400\n", - "158 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "159 out of 400\n", - "160 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "161 out of 400\n", - "162 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "163 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "164 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "165 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "166 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "167 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "168 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "169 out of 400\n", - "170 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "171 out of 400\n", - "172 out of 400\n", - "173 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "174 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "175 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "176 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "177 out of 400\n", - "178 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "179 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", - "180 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", - " Simulation time (ms): 30\n", + " Simulation time188 out of 400\n", + "189 out of 400\n", + "190 out of 400\n", + "191 out of 400\n", + " (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "181 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "182 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "183 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", - "184 out of 400\n", - "185 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "186 out of 400\n", - "187 out of 400\n", - "188 out of 400\n", - "189 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "190 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "191 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "192 out of 400\n", + "193 out of 400\n", + "194 out of 400\n", + "195 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", + "196 out of 400\n", + "197 out of 400\n", + "198 out of 400\n", + "199 out of 400\n", + "200 out of 400\n", + "201 out of 400\n", + "202 out of 400\n", + "203 out of 400\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "193 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "194 out of 400\n", - "195 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "196 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", + "204 out of 400\n", + "205 out of 400\n", + "206 out of 400\n", + "207 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "197 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "198 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "199 out of 400\n", - "200 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "201 out of 400\n", - "202 out of 400\n", - "203 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "204 out of 400\n", - "205 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updati208 out of 400\n", + "209 out of 400\n", + "210 out of 400\n", + "211 out of 400\n", + "212 out of 400\n", + "213 out of 400\n", + "214 out of 400\n", + "215 out of 400\n", + "ng_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "206 out of 400\n", - "207 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", - "208 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "209 out of 400\n", - "210 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 47\n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", + " Number 216 out of 400\n", + "217 out of 400\n", + "218 out of 400\n", + "219 out of 400\n", + "of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "211 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "212 out of 400\n", - "213 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", - " Simulation time (ms): 30\n", + " S220 out of 400\n", + "221 out of 400\n", + "222 out of 400\n", + "223 out of 400\n", + "imulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "214 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "215 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "216 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", + "224 out of 400\n", + "225 out of 400\n", + "226 out of 400\n", + "227 out of 400\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "228 out of 400\n", + "229 out of 400\n", + "230 out of 400\n", + "231 out of 400\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "217 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "218 out of 400\n", - "219 out of 400\n", - "220 out of 400\n", - "221 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "222 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "223 out of 400\n", - "224 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "225 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "226 out of 400\n", - "227 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "228 out of 400\n", - "229 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 Simul232 out of 400\n", + "233 out of 400\n", + "234 out of 400\n", + "235 out of 400\n", + "236 out of 400\n", + "237 out of 400\n", + "238 out of 400\n", + "239 out of 400\n", + "ationManager::run [Info]: \n", " Simulation finished.\n", - "230 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "231 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "232 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]240 out of 400\n", + "241 out of 400\n", + "242 out of 400\n", + "243 out of 400\n", + "244 out of 400\n", + "245 out of 400\n", + "246 out of 400\n", + "247 out of 400\n", + ": \n", " Simulation finished.\n", - "233 out of 400\n", - "234 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "235 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:16 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "236 out of 400\n", "\n", - "Apr 19 11:33:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", - " Simulation finished.\n", - "237 out of 400\n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", + " Simulation finish248 out of 400\n", + "249 out of 400\n", + "250 out of 400\n", + "251 out of 400\n", + "252 out of 400\n", + "253 out of 400\n", + "254 out of 400\n", + "255 out of 400\n", + "ed.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "238 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "239 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "240 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "241 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 Sim256 out of 400\n", + "257 out of 400\n", + "258 out of 400\n", + "259 out of 400\n", + "260 out of 400\n", + "261 out of 400\n", + "262 out of 400\n", + "263 out of 400\n", + "ulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "242 out of 400\n", - "243 out of 400\n", - "244 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "245 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_up264 out of 400\n", + "265 out of 400\n", + "266 out of 400\n", + "267 out of 400\n", + "268 out of 400\n", + "269 out of 400\n", + "270 out of 400\n", + "271 out of 400\n", + "dating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "246 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "247 out of 400\n", - "248 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", - "249 out of 400\n", - "250 out of 400\n", - "251 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "252 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 47\n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", + " Num272 out of 400\n", + "273 out of 400\n", + "274 out of 400\n", + "275 out of 400\n", + "276 out of 400\n", + "277 out of 400\n", + "278 out of 400\n", + "ber of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "253 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", - " Simulation time (ms): 30\n", + " 279 out of 400\n", + "280 out of 400\n", + "281 out of 400\n", + "282 out of 400\n", + " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "254 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "255 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "256 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "257 out of 400\n", - "258 out of 400\n", - "259 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", - " Simulation time (ms): 30\n", + " Simulation time (ms):283 out of 400\n", + "284 out of 400\n", + "285 out of 400\n", + "286 out of 400\n", + "287 out of 400\n", + "288 out of 400\n", + "289 out of 400\n", + "290 out of 400\n", + " 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "260 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "261 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", - " Number of OpenMP threads: 1\n", + " Number of OpenMP291 out of 400\n", + "292 out of 400\n", + "293 out of 400\n", + "294 out of 400\n", + "295 out of 400\n", + "296 out of 400\n", + "297 out of 400\n", + "298 out of 400\n", + " threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "262 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "263 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "264 out of 400\n", - "265 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "266 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", - " Not using MPI\n", + " Not usin299 out of 400\n", + "300 out of 400\n", + "301 out of 400\n", + "302 out of 400\n", + "g MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "267 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "268 out of 400\n", - "269 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 S303 out of 400\n", + "304 out of 400\n", + "305 out of 400\n", + "306 out of 400\n", + "307 out of 400\n", + "308 out of 400\n", + "309 out of 400\n", + "310 out of 400\n", + "imulationManager::run [Info]: \n", " Simulation finished.\n", - "270 out of 400\n", - "271 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "272 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "273 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [I311 out of 400\n", + "312 out of 400\n", + "313 out of 400\n", + "314 out of 400\n", + "315 out of 400\n", + "316 out of 400\n", + "317 out of 400\n", + "318 out of 400\n", + "nfo]: \n", " Simulation finished.\n", - "274 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "275 out of 400\n", - "276 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "277 out of 400\n", - "278 out of 400\n", - "279 out of 400\n", - "280 out of 400\n", - "281 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "282 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 Simulat283 out of 400\n", - "ionManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "284 out of 400\n", - "285 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "286 out of 400\n", - "287 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "288 out of 400\n", - "289 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "290 out of 400\n", - "291 out of 400\n", - "292 out of 400\n", - "293 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "294 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "295 out of 400\n", - "296 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 47\n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", + " Number of local nodes: 319 out of 400\n", + "320 out of 400\n", + "321 out of 400\n", + "322 out of 400\n", + "47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "297 out of 400\n", - "298 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "299 out of 400\n", - "300 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", - " Simulation time (ms): 30\n", + " Simulation time (323 out of 400\n", + "324 out of 400\n", + "325 out of 400\n", + "ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "301 out of 400\n", - "302 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", + " Simulation finished.\n", + "\n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", + " Number of local nodes: 47\n", + " Simulation time (ms): 30\n", + " Number of Op326 out of 400\n", + "327 out of 400\n", + "328 out of 400\n", + "329 out of 400\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "330 out of 400\n", + "331 out of 400\n", + "332 out of 400\n", + "333 out of 400\n", + "334 out of 400\n", + "335 out of 400\n", + "336 out of 400\n", + "337 out of 400\n", + "338 out of 400\n", + "339 out of 400\n", + "340 out of 400\n", + "341 out of 400\n", + "342 out of 400\n", + "343 out of 400\n", + "344 out of 400\n", + "345 out of 400\n", + "enMP threads: 1\n", + " Not using MPI\n", + "\n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "303 out of 400\n", - "304 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "305 out of 400\n", - "306 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", - " Not using MPI\n", + " Not 346 out of 400\n", + "347 out of 400\n", + "348 out of 400\n", + "349 out of 400\n", + "350 out of 400\n", + "351 out of 400\n", + "352 out of 400\n", + "353 out of 400\n", + "using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "307 out of 400\n", - "308 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "309 out of 400\n", - "310 out of 400\n", - "311 out of 400\n", - "312 out of 400\n", - "313 out of 400\n", - "314 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:354 out of 400\n", + "355 out of 400\n", + "356 out of 400\n", + "357 out of 400\n", + "358 out of 400\n", + "359 out of 400\n", + "360 out of 400\n", + "361 out of 400\n", + "362 out of 400\n", + "363 out of 400\n", + "364 out of 400\n", + "10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "315 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "316 out of 400\n", - "317 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "318 out of 400\n", - "319 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", - " Simulation finished.\n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", + " Simulatio365 out of 400\n", + "366 out of 400\n", + "367 out of 400\n", + "368 out of 400\n", + "369 out of 400\n", + "370 out of 400\n", + "371 out of 400\n", + "372 out of 400\n", + "373 out of 400\n", + "374 out of 400\n", + "375 out of 400\n", + "n finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "320 out of 400\n", - "321 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "322 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:1376 out of 400\n", + "377 out of 400\n", + "378 out of 400\n", + "379 out of 400\n", + "380 out of 400\n", + "381 out of 400\n", + "382 out of 400\n", + "4:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "323 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "324 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "325 out of 400\n", - "326 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::383 out of 400\n", + "384 out of 400\n", + "385 out of 400\n", + "386 out of 400\n", + "387 out of 400\n", + "388 out of 400\n", + "389 out of 400\n", + "390 out of 400\n", + "start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "327 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "328 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", - "329 out of 400\n", - "330 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "331 out of 400\n", - "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 47\n", - " Simulation time (ms): 30\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", - " Simulation finished.\n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: 391 out of 400\n", + "392 out of 400\n", + "393 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "332 out of 400\n", - "333 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "334 out of 400\n", - "335 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "336 out of 400\n", - "337 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 47\n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", + " Number of local nod394 out of 400\n", + "395 out of 400\n", + "396 out of 400\n", + "397 out of 400\n", + "es: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "338 out of 400\n", - "339 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "340 out of 400\n", - "341 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "342 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "343 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "344 out of 400\n", - "345 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "346 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "347 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "348 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", - " Not using MPI\n", + " 398 out of 400\n", + "399 out of 400\n", + "Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "349 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "350 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "351 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "352 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", - "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "353 out of 400\n", - "354 out of 400\n", - "355 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "356 out of 400\n", - "357 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 Simulat358 out of 400\n", - "ionManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "359 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "360 out of 400\n", - "361 out of 400\n", - "362 out of 400\n", - "363 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "364 out of 400\n", - "365 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "366 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "367 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "368 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", - "369 out of 400\n", - "370 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "371 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "372 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:11 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:11 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "373 out of 400\n", - "374 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:11 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:11 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "375 out of 400\n", - "376 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:11 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:11 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:11 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:11 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:11 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:17 SimulationManager::run [Info]: \n", + "Apr 30 14:14:11 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "377 out of 400\n", "\n", - "Apr 19 11:33:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:11 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", - "378 out of 400\n", - "379 out of 400\n", "\n", - "Apr 19 11:33:18 SimulationManager::run [Info]: \n", + "Apr 30 14:14:11 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:18 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:11 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:18 SimulationManager::run [Info]: \n", + "Apr 30 14:14:11 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:18 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:11 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:18 SimulationManager::run [Info]: \n", + "Apr 30 14:14:11 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "380 out of 400\n", "\n", - "Apr 19 11:33:18 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:11 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", - "381 out of 400\n", "\n", - "Apr 19 11:33:18 SimulationManager::run [Info]: \n", + "Apr 30 14:14:11 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:18 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:11 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:18 SimulationManager::run [Info]: \n", + "Apr 30 14:14:11 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "382 out of 400\n", "\n", - "Apr 19 11:33:18 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:11 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:18 SimulationManager::run [Info]: \n", + "Apr 30 14:14:11 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "383 out of 400\n", - "384 out of 400\n", "\n", - "Apr 19 11:33:18 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:11 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:18 SimulationManager::run [Info]: \n", + "Apr 30 14:14:11 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:18 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:11 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:18 SimulationManager::run [Info]: \n", + "Apr 30 14:14:11 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "385 out of 400\n", "\n", - "Apr 19 11:33:18 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:11 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:18 SimulationManager::run [Info]: \n", + "Apr 30 14:14:11 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "386 out of 400\n", "\n", - "Apr 19 11:33:18 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:11 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", - "387 out of 400\n", - "388 out of 400\n", "\n", - "Apr 19 11:33:18 SimulationManager::run [Info]: \n", + "Apr 30 14:14:11 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:18 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:11 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:18 SimulationManager::run [Info]: \n", + "Apr 30 14:14:11 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "389 out of 400\n", - "390 out of 400\n", "\n", - "Apr 19 11:33:18 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:11 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:18 SimulationManager::run [Info]: \n", + "Apr 30 14:14:11 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:18 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:11 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:18 SimulationManager::run [Info]: \n", + "Apr 30 14:14:11 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:18 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:11 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:18 SimulationManager::run [Info]: \n", + "Apr 30 14:14:11 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "391 out of 400\n", "\n", - "Apr 19 11:33:18 SimulationManager::start_updating_ [Info]: \n", - "392 out of 400\n", + "Apr 30 14:14:11 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:18 SimulationManager::run [Info]: \n", + "Apr 30 14:14:11 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:18 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:11 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:18 SimulationManager::run [Info]: \n", + "Apr 30 14:14:11 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "393 out of 400\n", "\n", - "394 out of 400\n", - "Apr 19 11:33:18 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:11 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:18 SimulationManager::run [Info]: \n", + "Apr 30 14:14:11 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:18 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:11 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:18 SimulationManager::run [Info]: \n", + "Apr 30 14:14:11 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "395 out of 400\n", "\n", - "Apr 19 11:33:18 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:11 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", - "396 out of 400\n", - "397 out of 400\n", "\n", - "Apr 19 11:33:18 SimulationManager::run [Info]: \n", + "Apr 30 14:14:11 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:18 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:11 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:18 SimulationManager::run [Info]: \n", + "Apr 30 14:14:11 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "398 out of 400\n", - "399 out of 400\n", "\n", - "Apr 19 11:33:18 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:11 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:18 SimulationManager::run [Info]: \n", + "Apr 30 14:14:11 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:18 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:11 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:18 SimulationManager::run [Info]: \n", + "Apr 30 14:14:11 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 11:33:18 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:14:11 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 47\n", " Simulation time (ms): 30\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 11:33:18 SimulationManager::run [Info]: \n", + "Apr 30 14:14:11 SimulationManager::run [Info]: \n", " Simulation finished.\n" ] } @@ -5959,7 +5987,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -5975,7 +6002,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/tmp/ipykernel_335797/2151756254.py:23: UserWarning:FigureCanvasAgg is non-interactive, and thus cannot be shown\n" + "/tmp/ipykernel_1193945/2151756254.py:23: UserWarning:FigureCanvasAgg is non-interactive, and thus cannot be shown\n" ] }, { @@ -5995,7 +6022,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -6003,7 +6029,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -6124,7 +6149,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -6165,7 +6189,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -6174,7 +6197,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 16, "metadata": { "scrolled": true, "tags": [] @@ -6184,11 +6207,13 @@ "name": "stdout", "output_type": "stream", "text": [ + "codegen_opts = {'delay_variable': {'neuromodulated_stdp_synapse': 'd'}, 'weight_variable': {'neuromodulated_stdp_synapse': 'w'}}\n", + "_codegen_opts = {'neuron_parent_class': 'StructuralPlasticityNode', 'neuron_parent_class_include': 'structural_plasticity_node.h', 'neuron_synapse_pairs': [{'neuron': 'iaf_psc_exp_neuron', 'synapse': 'neuromodulated_stdp_synapse', 'post_ports': ['post_spikes'], 'vt_ports': ['mod_spikes']}]}\n", "[1,GLOBAL, INFO]: List of files that will be processed:\n", - "[2,GLOBAL, INFO]: /home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/iaf_psc_exp_neuron.nestml\n", - "[3,GLOBAL, INFO]: /home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/neuromodulated_stdp_synapse.nestml\n", - "[4,GLOBAL, INFO]: Target platform code will be generated in directory: '/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target'\n", - "[5,GLOBAL, INFO]: Target platform code will be installed in directory: '/tmp/nestml_target_nxqmze5r'\n", + "[2,GLOBAL, INFO]: /home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/iaf_psc_exp_neuron.nestml\n", + "[3,GLOBAL, INFO]: /home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/neuromodulated_stdp_synapse.nestml\n", + "[4,GLOBAL, INFO]: Target platform code will be generated in directory: '/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target'\n", + "[5,GLOBAL, INFO]: Target platform code will be installed in directory: '/tmp/nestml_target_i949bk_d'\n", "\n", " -- N E S T --\n", " Copyright (C) 2004 The NEST Initiative\n", @@ -6205,23 +6230,23 @@ " Type 'nest.help()' to find out more about NEST.\n", "\n", "[6,GLOBAL, INFO]: The NEST Simulator version was automatically detected as: master\n", - "[7,GLOBAL, INFO]: Given template root path is not an absolute path. Creating the absolute path with default templates directory '/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/pynestml/codegeneration/resources_nest/point_neuron'\n", - "[8,GLOBAL, INFO]: Given template root path is not an absolute path. Creating the absolute path with default templates directory '/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/pynestml/codegeneration/resources_nest/point_neuron'\n", - "[9,GLOBAL, INFO]: Given template root path is not an absolute path. Creating the absolute path with default templates directory '/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/pynestml/codegeneration/resources_nest/point_neuron'\n", + "[7,GLOBAL, INFO]: Given template root path is not an absolute path. Creating the absolute path with default templates directory '/home/charl/julich/nestml-fork-nest-delay/nestml/pynestml/codegeneration/resources_nest/point_neuron'\n", + "[8,GLOBAL, INFO]: Given template root path is not an absolute path. Creating the absolute path with default templates directory '/home/charl/julich/nestml-fork-nest-delay/nestml/pynestml/codegeneration/resources_nest/point_neuron'\n", + "[9,GLOBAL, INFO]: Given template root path is not an absolute path. Creating the absolute path with default templates directory '/home/charl/julich/nestml-fork-nest-delay/nestml/pynestml/codegeneration/resources_nest/point_neuron'\n", "[10,GLOBAL, INFO]: The NEST Simulator installation path was automatically detected as: /home/charl/julich/nest-simulator-install\n", - "[11,GLOBAL, INFO]: Start processing '/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/iaf_psc_exp_neuron.nestml'!\n", + "[11,GLOBAL, INFO]: Start processing '/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/iaf_psc_exp_neuron.nestml'!\n", "[13,iaf_psc_exp_neuron_nestml, INFO, [67:39;67:63]]: Implicit magnitude conversion from pA to pA buffer with factor 1.0 \n", "[14,iaf_psc_exp_neuron_nestml, INFO, [67:15;67:30]]: Implicit magnitude conversion from mV / ms to pA / pF with factor 1.0 \n", - "[15,GLOBAL, INFO]: Start processing '/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/neuromodulated_stdp_synapse.nestml'!\n", - "[17,neuromodulated_stdp_synapse_nestml, WARNING, [12:8;12:28]]: Variable 'd' has the same name as a physical unit!\n", + "[15,GLOBAL, INFO]: Start processing '/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/neuromodulated_stdp_synapse.nestml'!\n", + "[17,neuromodulated_stdp_synapse_nestml, WARNING, [12:8;12:17]]: Variable 'd' has the same name as a physical unit!\n", "[18,neuromodulated_stdp_synapse_nestml, INFO, [40:13;40:20]]: Implicit casting from (compatible) type '1 / ms' to 'real'.\n", "[19,neuromodulated_stdp_synapse_nestml, INFO, [63:13;63:123]]: Implicit casting from (compatible) type 'ms' to 'real'.\n", - "[22,neuromodulated_stdp_synapse_nestml, WARNING, [12:8;12:28]]: Variable 'd' has the same name as a physical unit!\n", + "[22,neuromodulated_stdp_synapse_nestml, WARNING, [12:8;12:17]]: Variable 'd' has the same name as a physical unit!\n", "[23,neuromodulated_stdp_synapse_nestml, INFO, [40:13;40:20]]: Implicit casting from (compatible) type '1 / ms' to 'real'.\n", "[24,neuromodulated_stdp_synapse_nestml, INFO, [63:13;63:123]]: Implicit casting from (compatible) type 'ms' to 'real'.\n", "[26,iaf_psc_exp_neuron_nestml, INFO, [67:39;67:63]]: Implicit magnitude conversion from pA to pA buffer with factor 1.0 \n", "[27,iaf_psc_exp_neuron_nestml, INFO, [67:15;67:30]]: Implicit magnitude conversion from mV / ms to pA / pF with factor 1.0 \n", - "[29,neuromodulated_stdp_synapse_nestml, WARNING, [12:8;12:28]]: Variable 'd' has the same name as a physical unit!\n", + "[29,neuromodulated_stdp_synapse_nestml, WARNING, [12:8;12:17]]: Variable 'd' has the same name as a physical unit!\n", "[30,neuromodulated_stdp_synapse_nestml, INFO, [40:13;40:20]]: Implicit casting from (compatible) type '1 / ms' to 'real'.\n", "[31,neuromodulated_stdp_synapse_nestml, INFO, [63:13;63:123]]: Implicit casting from (compatible) type 'ms' to 'real'.\n", "[32,GLOBAL, INFO]: State variables that will be moved from synapse to neuron: ['post_tr']\n", @@ -6237,9 +6262,7 @@ "[42,GLOBAL, INFO]: In synapse: replacing variables with suffixed external variable references\n", "[43,GLOBAL, INFO]: \t• Replacing variable post_tr\n", "[44,GLOBAL, INFO]: ASTSimpleExpression replacement made (var = post_tr__for_neuromodulated_stdp_synapse_nestml) in expression: A_minus * post_tr\n", - "[47,neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml, WARNING, [12:8;12:28]]: Variable 'd' has the same name as a physical unit!\n", - "[48,neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml, INFO, [40:13;40:20]]: Implicit casting from (compatible) type '1 / ms' to 'real'.\n", - "[49,neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml, INFO, [63:13;63:123]]: Implicit casting from (compatible) type 'ms' to 'real'.\n" + "[47,neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml, WARNING, [12:8;12:17]]: Variable 'd' has the same name as a physical unit!\n" ] }, { @@ -6297,7 +6320,7 @@ "Processing differential-equation form shape V_m with defining expression = \"(-(V_m - E_L)) / tau_m + (I_syn_exc - I_syn_inh + I_e + I_stim) / C_m\"\n", "INFO:\tReturning shape: Shape \"V_m\" of order 1\n", "INFO:Shape V_m: reconstituting expression E_L/tau_m - V_m/tau_m + I_e/C_m + I_stim/C_m + I_syn_exc/C_m - I_syn_inh/C_m\n", - "INFO:All known variables: [I_syn_exc, I_syn_inh, V_m], all parameters used in ODEs: {tau_syn_exc, E_L, tau_m, I_e, C_m, I_stim, tau_syn_inh}\n", + "INFO:All known variables: [I_syn_exc, I_syn_inh, V_m], all parameters used in ODEs: {I_stim, tau_m, tau_syn_inh, I_e, C_m, E_L, tau_syn_exc}\n", "INFO:No numerical value specified for parameter \"I_stim\"\n", "INFO:\n", "Processing differential-equation form shape I_syn_exc with defining expression = \"(-I_syn_exc) / tau_syn_exc\"\n", @@ -6312,13 +6335,21 @@ "INFO:Shape I_syn_inh: reconstituting expression -I_syn_inh/tau_syn_inh\n", "INFO:Shape V_m: reconstituting expression E_L/tau_m - V_m/tau_m + I_e/C_m + I_stim/C_m + I_syn_exc/C_m - I_syn_inh/C_m\n", "INFO:Finding analytically solvable equations...\n", - "INFO:Saving dependency graph plot to /tmp/ode_dependency_graph.dot\n" + "INFO:Saving dependency graph plot to /tmp/ode_dependency_graph.dot\n", + "INFO:Shape I_syn_exc: reconstituting expression -I_syn_exc/tau_syn_exc\n", + "INFO:Shape I_syn_inh: reconstituting expression -I_syn_inh/tau_syn_inh\n", + "INFO:Shape V_m: reconstituting expression E_L/tau_m - V_m/tau_m + I_e/C_m + I_stim/C_m + I_syn_exc/C_m - I_syn_inh/C_m\n", + "INFO:Saving dependency graph plot to /tmp/ode_dependency_graph_analytically_solvable_before_propagated.dot\n", + "INFO:Saving dependency graph plot to /tmp/ode_dependency_graph_analytically_solvable.dot\n", + "INFO:Generating propagators for the following symbols: I_syn_exc, I_syn_inh, V_m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ + "[48,neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml, INFO, [40:13;40:20]]: Implicit casting from (compatible) type '1 / ms' to 'real'.\n", + "[49,neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml, INFO, [63:13;63:123]]: Implicit casting from (compatible) type 'ms' to 'real'.\n", "[50,GLOBAL, INFO]: Successfully constructed neuron-synapse pair iaf_psc_exp_neuron_nestml__with_neuromodulated_stdp_synapse_nestml, neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml\n", "[51,GLOBAL, INFO]: Analysing/transforming model 'iaf_psc_exp_neuron_nestml'\n", "[52,iaf_psc_exp_neuron_nestml, INFO, [55:0;115:0]]: Starts processing of the model 'iaf_psc_exp_neuron_nestml'\n" @@ -6328,12 +6359,6 @@ "name": "stderr", "output_type": "stream", "text": [ - "INFO:Shape I_syn_exc: reconstituting expression -I_syn_exc/tau_syn_exc\n", - "INFO:Shape I_syn_inh: reconstituting expression -I_syn_inh/tau_syn_inh\n", - "INFO:Shape V_m: reconstituting expression E_L/tau_m - V_m/tau_m + I_e/C_m + I_stim/C_m + I_syn_exc/C_m - I_syn_inh/C_m\n", - "INFO:Saving dependency graph plot to /tmp/ode_dependency_graph_analytically_solvable_before_propagated.dot\n", - "INFO:Saving dependency graph plot to /tmp/ode_dependency_graph_analytically_solvable.dot\n", - "INFO:Generating propagators for the following symbols: I_syn_exc, I_syn_inh, V_m\n", "WARNING:Under certain conditions, the propagator matrix is singular (contains infinities).\n", "WARNING:List of all conditions that result in a singular propagator:\n", "WARNING:\ttau_m = tau_syn_exc\n", @@ -6364,7 +6389,7 @@ " \"__P__I_syn_exc__I_syn_exc\": \"exp(-__h/tau_syn_exc)\",\n", " \"__P__I_syn_inh__I_syn_inh\": \"exp(-__h/tau_syn_inh)\",\n", " \"__P__V_m__I_syn_exc\": \"tau_m*tau_syn_exc*(-exp(__h/tau_m) + exp(__h/tau_syn_exc))*exp(-__h*(tau_m + tau_syn_exc)/(tau_m*tau_syn_exc))/(C_m*(tau_m - tau_syn_exc))\",\n", - " \"__P__V_m__I_syn_inh\": \"tau_m*tau_syn_inh*(exp(__h/tau_m) - exp(__h/tau_syn_inh))*exp(-__h/tau_syn_inh - __h/tau_m)/(C_m*(tau_m - tau_syn_inh))\",\n", + " \"__P__V_m__I_syn_inh\": \"tau_m*tau_syn_inh*(exp(__h/tau_m) - exp(__h/tau_syn_inh))*exp(-__h*(tau_m + tau_syn_inh)/(tau_m*tau_syn_inh))/(C_m*(tau_m - tau_syn_inh))\",\n", " \"__P__V_m__V_m\": \"exp(-__h/tau_m)\"\n", " },\n", " \"solver\": \"analytical\",\n", @@ -6442,7 +6467,7 @@ "Processing differential-equation form shape post_tr__for_neuromodulated_stdp_synapse_nestml with defining expression = \"(-post_tr__for_neuromodulated_stdp_synapse_nestml) / tau_tr_post__for_neuromodulated_stdp_synapse_nestml\"\n", "INFO:\tReturning shape: Shape \"post_tr__for_neuromodulated_stdp_synapse_nestml\" of order 1\n", "INFO:Shape post_tr__for_neuromodulated_stdp_synapse_nestml: reconstituting expression -post_tr__for_neuromodulated_stdp_synapse_nestml/tau_tr_post__for_neuromodulated_stdp_synapse_nestml\n", - "INFO:All known variables: [I_syn_exc, I_syn_inh, V_m, post_tr__for_neuromodulated_stdp_synapse_nestml], all parameters used in ODEs: {tau_syn_exc, tau_tr_post__for_neuromodulated_stdp_synapse_nestml, E_L, tau_m, I_e, C_m, I_stim, tau_syn_inh}\n", + "INFO:All known variables: [I_syn_exc, I_syn_inh, V_m, post_tr__for_neuromodulated_stdp_synapse_nestml], all parameters used in ODEs: {I_stim, tau_m, tau_syn_inh, I_e, tau_tr_post__for_neuromodulated_stdp_synapse_nestml, C_m, E_L, tau_syn_exc}\n", "INFO:No numerical value specified for parameter \"I_stim\"\n", "INFO:\n", "Processing differential-equation form shape I_syn_exc with defining expression = \"(-I_syn_exc) / tau_syn_exc\"\n", @@ -6461,7 +6486,14 @@ "INFO:Shape V_m: reconstituting expression E_L/tau_m - V_m/tau_m + I_e/C_m + I_stim/C_m + I_syn_exc/C_m - I_syn_inh/C_m\n", "INFO:Shape post_tr__for_neuromodulated_stdp_synapse_nestml: reconstituting expression -post_tr__for_neuromodulated_stdp_synapse_nestml/tau_tr_post__for_neuromodulated_stdp_synapse_nestml\n", "INFO:Finding analytically solvable equations...\n", - "INFO:Saving dependency graph plot to /tmp/ode_dependency_graph.dot\n" + "INFO:Saving dependency graph plot to /tmp/ode_dependency_graph.dot\n", + "INFO:Shape I_syn_exc: reconstituting expression -I_syn_exc/tau_syn_exc\n", + "INFO:Shape I_syn_inh: reconstituting expression -I_syn_inh/tau_syn_inh\n", + "INFO:Shape V_m: reconstituting expression E_L/tau_m - V_m/tau_m + I_e/C_m + I_stim/C_m + I_syn_exc/C_m - I_syn_inh/C_m\n", + "INFO:Shape post_tr__for_neuromodulated_stdp_synapse_nestml: reconstituting expression -post_tr__for_neuromodulated_stdp_synapse_nestml/tau_tr_post__for_neuromodulated_stdp_synapse_nestml\n", + "INFO:Saving dependency graph plot to /tmp/ode_dependency_graph_analytically_solvable_before_propagated.dot\n", + "INFO:Saving dependency graph plot to /tmp/ode_dependency_graph_analytically_solvable.dot\n", + "INFO:Generating propagators for the following symbols: I_syn_exc, I_syn_inh, V_m, post_tr__for_neuromodulated_stdp_synapse_nestml\n" ] }, { @@ -6476,13 +6508,6 @@ "name": "stderr", "output_type": "stream", "text": [ - "INFO:Shape I_syn_exc: reconstituting expression -I_syn_exc/tau_syn_exc\n", - "INFO:Shape I_syn_inh: reconstituting expression -I_syn_inh/tau_syn_inh\n", - "INFO:Shape V_m: reconstituting expression E_L/tau_m - V_m/tau_m + I_e/C_m + I_stim/C_m + I_syn_exc/C_m - I_syn_inh/C_m\n", - "INFO:Shape post_tr__for_neuromodulated_stdp_synapse_nestml: reconstituting expression -post_tr__for_neuromodulated_stdp_synapse_nestml/tau_tr_post__for_neuromodulated_stdp_synapse_nestml\n", - "INFO:Saving dependency graph plot to /tmp/ode_dependency_graph_analytically_solvable_before_propagated.dot\n", - "INFO:Saving dependency graph plot to /tmp/ode_dependency_graph_analytically_solvable.dot\n", - "INFO:Generating propagators for the following symbols: I_syn_exc, I_syn_inh, V_m, post_tr__for_neuromodulated_stdp_synapse_nestml\n", "WARNING:Under certain conditions, the propagator matrix is singular (contains infinities).\n", "WARNING:List of all conditions that result in a singular propagator:\n", "WARNING:\ttau_m = tau_syn_exc\n", @@ -6517,7 +6542,7 @@ " \"__P__I_syn_exc__I_syn_exc\": \"exp(-__h/tau_syn_exc)\",\n", " \"__P__I_syn_inh__I_syn_inh\": \"exp(-__h/tau_syn_inh)\",\n", " \"__P__V_m__I_syn_exc\": \"tau_m*tau_syn_exc*(-exp(__h/tau_m) + exp(__h/tau_syn_exc))*exp(-__h*(tau_m + tau_syn_exc)/(tau_m*tau_syn_exc))/(C_m*(tau_m - tau_syn_exc))\",\n", - " \"__P__V_m__I_syn_inh\": \"tau_m*tau_syn_inh*(exp(__h/tau_m) - exp(__h/tau_syn_inh))*exp(-__h/tau_syn_inh - __h/tau_m)/(C_m*(tau_m - tau_syn_inh))\",\n", + " \"__P__V_m__I_syn_inh\": \"tau_m*tau_syn_inh*(exp(__h/tau_m) - exp(__h/tau_syn_inh))*exp(-__h*(tau_m + tau_syn_inh)/(tau_m*tau_syn_inh))/(C_m*(tau_m - tau_syn_inh))\",\n", " \"__P__V_m__V_m\": \"exp(-__h/tau_m)\",\n", " \"__P__post_tr__for_neuromodulated_stdp_synapse_nestml__post_tr__for_neuromodulated_stdp_synapse_nestml\": \"exp(-__h/tau_tr_post__for_neuromodulated_stdp_synapse_nestml)\"\n", " },\n", @@ -6577,21 +6602,7 @@ "INFO:Finding analytically solvable equations...\n", "INFO:Saving dependency graph plot to /tmp/ode_dependency_graph.dot\n", "INFO:Shape pre_tr: reconstituting expression -pre_tr/tau_tr_pre\n", - "INFO:Saving dependency graph plot to /tmp/ode_dependency_graph_analytically_solvable_before_propagated.dot\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[57,GLOBAL, INFO]: Analysing/transforming synapse neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.\n", - "[58,neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml, INFO, [2:0;66:0]]: Starts processing of the model 'neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml'\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ + "INFO:Saving dependency graph plot to /tmp/ode_dependency_graph_analytically_solvable_before_propagated.dot\n", "INFO:Saving dependency graph plot to /tmp/ode_dependency_graph_analytically_solvable.dot\n", "INFO:Generating propagators for the following symbols: pre_tr\n", "INFO:update_expr[pre_tr] = __P__pre_tr__pre_tr*pre_tr\n", @@ -6623,25 +6634,27 @@ "name": "stdout", "output_type": "stream", "text": [ - "[60,neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml, WARNING, [12:8;12:28]]: Variable 'd' has the same name as a physical unit!\n", + "[57,GLOBAL, INFO]: Analysing/transforming synapse neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.\n", + "[58,neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml, INFO, [2:0;66:0]]: Starts processing of the model 'neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml'\n", + "[60,neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml, WARNING, [12:8;12:17]]: Variable 'd' has the same name as a physical unit!\n", "[61,neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml, INFO, [40:13;40:20]]: Implicit casting from (compatible) type '1 / ms' to 'real'.\n", "[62,neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml, INFO, [63:13;63:123]]: Implicit casting from (compatible) type 'ms' to 'real'.\n", - "[64,neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml, WARNING, [12:8;12:28]]: Variable 'd' has the same name as a physical unit!\n", + "[64,neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml, WARNING, [12:8;12:17]]: Variable 'd' has the same name as a physical unit!\n", "[65,neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml, INFO, [40:13;40:20]]: Implicit casting from (compatible) type '1 / ms' to 'real'.\n", "[66,neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml, INFO, [63:13;63:123]]: Implicit casting from (compatible) type 'ms' to 'real'.\n", - "[67,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_exp_neuron_nestml.cpp\n", - "[68,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_exp_neuron_nestml.h\n", - "[69,iaf_psc_exp_neuron_nestml, INFO, [55:0;115:0]]: Successfully generated code for the model: 'iaf_psc_exp_neuron_nestml' in: '/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target' !\n", - "[70,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_exp_neuron_nestml__with_neuromodulated_stdp_synapse_nestml.cpp\n", - "[71,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_exp_neuron_nestml__with_neuromodulated_stdp_synapse_nestml.h\n", - "[72,iaf_psc_exp_neuron_nestml__with_neuromodulated_stdp_synapse_nestml, INFO, [55:0;115:0]]: Successfully generated code for the model: 'iaf_psc_exp_neuron_nestml__with_neuromodulated_stdp_synapse_nestml' in: '/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target' !\n", + "[67,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_exp_neuron_nestml.cpp\n", + "[68,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_exp_neuron_nestml.h\n", + "[69,iaf_psc_exp_neuron_nestml, INFO, [55:0;115:0]]: Successfully generated code for the model: 'iaf_psc_exp_neuron_nestml' in: '/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target' !\n", + "[70,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_exp_neuron_nestml__with_neuromodulated_stdp_synapse_nestml.cpp\n", + "[71,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_exp_neuron_nestml__with_neuromodulated_stdp_synapse_nestml.h\n", + "[72,iaf_psc_exp_neuron_nestml__with_neuromodulated_stdp_synapse_nestml, INFO, [55:0;115:0]]: Successfully generated code for the model: 'iaf_psc_exp_neuron_nestml__with_neuromodulated_stdp_synapse_nestml' in: '/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target' !\n", "Generating code for the synapse neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.\n", - "[73,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h\n", - "[74,neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml, INFO, [2:0;66:0]]: Successfully generated code for the model: 'neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml' in: '/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target' !\n", - "[75,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/nestml_6a0e5b32a83c4b3a83ce6c87a2445436_module.cpp\n", - "[76,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/nestml_6a0e5b32a83c4b3a83ce6c87a2445436_module.h\n", - "[77,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/CMakeLists.txt\n", - "[78,GLOBAL, INFO]: Successfully generated NEST module code in '/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target' !\n", + "[73,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h\n", + "[74,neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml, INFO, [2:0;66:0]]: Successfully generated code for the model: 'neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml' in: '/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target' !\n", + "[75,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/nestml_f744604f1acb4f80848d611720e6af63_module.cpp\n", + "[76,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/nestml_f744604f1acb4f80848d611720e6af63_module.h\n", + "[77,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/CMakeLists.txt\n", + "[78,GLOBAL, INFO]: Successfully generated NEST module code in '/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target' !\n", "CMake Warning (dev) at CMakeLists.txt:95 (project):\n", " cmake_minimum_required() should be called prior to this top-level project()\n", " call. Please see the cmake-commands(7) manual for usage documentation of\n", @@ -6656,7 +6669,7 @@ "-- Detecting CXX compile features - done\n", "\n", "-------------------------------------------------------\n", - "nestml_6a0e5b32a83c4b3a83ce6c87a2445436_module Configuration Summary\n", + "nestml_f744604f1acb4f80848d611720e6af63_module Configuration Summary\n", "-------------------------------------------------------\n", "\n", "C++ compiler : /usr/bin/c++\n", @@ -6668,15 +6681,15 @@ "\n", "-------------------------------------------------------\n", "\n", - "You can now build and install 'nestml_6a0e5b32a83c4b3a83ce6c87a2445436_module' using\n", + "You can now build and install 'nestml_f744604f1acb4f80848d611720e6af63_module' using\n", " make\n", " make install\n", "\n", - "The library file libnestml_6a0e5b32a83c4b3a83ce6c87a2445436_module.so will be installed to\n", - " /tmp/nestml_target_nxqmze5r\n", + "The library file libnestml_f744604f1acb4f80848d611720e6af63_module.so will be installed to\n", + " /tmp/nestml_target_i949bk_d\n", "The module can be loaded into NEST using\n", - " (nestml_6a0e5b32a83c4b3a83ce6c87a2445436_module) Install (in SLI)\n", - " nest.Install(nestml_6a0e5b32a83c4b3a83ce6c87a2445436_module) (in PyNEST)\n", + " (nestml_f744604f1acb4f80848d611720e6af63_module) Install (in SLI)\n", + " nest.Install(nestml_f744604f1acb4f80848d611720e6af63_module) (in PyNEST)\n", "\n", "CMake Warning (dev) in CMakeLists.txt:\n", " No cmake_minimum_required command is present. A line of code such as\n", @@ -6688,174 +6701,188 @@ " information run \"cmake --help-policy CMP0000\".\n", "This warning is for project developers. Use -Wno-dev to suppress it.\n", "\n", - "-- Configuring done (0.5s)\n", + "-- Configuring done (0.1s)\n", "-- Generating done (0.0s)\n", - "-- Build files have been written to: /home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target\n", - "[ 25%] Building CXX object CMakeFiles/nestml_6a0e5b32a83c4b3a83ce6c87a2445436_module_module.dir/nestml_6a0e5b32a83c4b3a83ce6c87a2445436_module.o\n", - "[ 50%] Building CXX object CMakeFiles/nestml_6a0e5b32a83c4b3a83ce6c87a2445436_module_module.dir/iaf_psc_exp_neuron_nestml.o\n", - "[ 75%] Building CXX object CMakeFiles/nestml_6a0e5b32a83c4b3a83ce6c87a2445436_module_module.dir/iaf_psc_exp_neuron_nestml__with_neuromodulated_stdp_synapse_nestml.o\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_exp_neuron_nestml__with_neuromodulated_stdp_synapse_nestml.cpp: In member function ‘void iaf_psc_exp_neuron_nestml__with_neuromodulated_stdp_synapse_nestml::init_state_internal_()’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_exp_neuron_nestml__with_neuromodulated_stdp_synapse_nestml.cpp:196:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + "-- Build files have been written to: /home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target\n", + "[ 25%] Building CXX object CMakeFiles/nestml_f744604f1acb4f80848d611720e6af63_module_module.dir/nestml_f744604f1acb4f80848d611720e6af63_module.o\n", + "[ 50%] Building CXX object CMakeFiles/nestml_f744604f1acb4f80848d611720e6af63_module_module.dir/iaf_psc_exp_neuron_nestml.o\n", + "[ 75%] Building CXX object CMakeFiles/nestml_f744604f1acb4f80848d611720e6af63_module_module.dir/iaf_psc_exp_neuron_nestml__with_neuromodulated_stdp_synapse_nestml.o\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_exp_neuron_nestml__with_neuromodulated_stdp_synapse_nestml.cpp: In member function ‘void iaf_psc_exp_neuron_nestml__with_neuromodulated_stdp_synapse_nestml::init_state_internal_()’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_exp_neuron_nestml__with_neuromodulated_stdp_synapse_nestml.cpp:196:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", " 196 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_exp_neuron_nestml__with_neuromodulated_stdp_synapse_nestml.cpp: In member function ‘virtual void iaf_psc_exp_neuron_nestml__with_neuromodulated_stdp_synapse_nestml::update(const nest::Time&, long int, long int)’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_exp_neuron_nestml__with_neuromodulated_stdp_synapse_nestml.cpp:310:24: warning: comparison of integer expressions of different signedness: ‘long int’ and ‘const size_t’ {aka ‘const long unsigned int’} [-Wsign-compare]\n", - " 310 | for (long i = 0; i < NUM_SPIKE_RECEPTORS; ++i)\n", - " | ~~^~~~~~~~~~~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_exp_neuron_nestml__with_neuromodulated_stdp_synapse_nestml.cpp:305:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 305 | auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", - " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_exp_neuron_nestml.cpp: In member function ‘void iaf_psc_exp_neuron_nestml::init_state_internal_()’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_exp_neuron_nestml.cpp:186:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_exp_neuron_nestml.cpp: In member function ‘void iaf_psc_exp_neuron_nestml::init_state_internal_()’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_exp_neuron_nestml.cpp:186:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", " 186 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_exp_neuron_nestml.cpp: In member function ‘virtual void iaf_psc_exp_neuron_nestml::update(const nest::Time&, long int, long int)’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_exp_neuron_nestml.cpp:289:24: warning: comparison of integer expressions of different signedness: ‘long int’ and ‘const size_t’ {aka ‘const long unsigned int’} [-Wsign-compare]\n", - " 289 | for (long i = 0; i < NUM_SPIKE_RECEPTORS; ++i)\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_exp_neuron_nestml__with_neuromodulated_stdp_synapse_nestml.cpp: In member function ‘virtual void iaf_psc_exp_neuron_nestml__with_neuromodulated_stdp_synapse_nestml::update(const nest::Time&, long int, long int)’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_exp_neuron_nestml__with_neuromodulated_stdp_synapse_nestml.cpp:306:24: warning: comparison of integer expressions of different signedness: ‘long int’ and ‘const size_t’ {aka ‘const long unsigned int’} [-Wsign-compare]\n", + " 306 | for (long i = 0; i < NUM_SPIKE_RECEPTORS; ++i)\n", + " | ~~^~~~~~~~~~~~~~~~~~~~~\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_exp_neuron_nestml.cpp: In member function ‘virtual void iaf_psc_exp_neuron_nestml::update(const nest::Time&, long int, long int)’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_exp_neuron_nestml.cpp:285:24: warning: comparison of integer expressions of different signedness: ‘long int’ and ‘const size_t’ {aka ‘const long unsigned int’} [-Wsign-compare]\n", + " 285 | for (long i = 0; i < NUM_SPIKE_RECEPTORS; ++i)\n", " | ~~^~~~~~~~~~~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_exp_neuron_nestml.cpp:284:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 284 | auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_exp_neuron_nestml__with_neuromodulated_stdp_synapse_nestml.cpp:301:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 301 | auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", " | ^~~~~\n", - "In file included from /home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/nestml_6a0e5b32a83c4b3a83ce6c87a2445436_module.cpp:36:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h: In instantiation of ‘nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_exp_neuron_nestml.cpp:280:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 280 | auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", + " | ^~~~~\n", + "In file included from /home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/nestml_f744604f1acb4f80848d611720e6af63_module.cpp:36:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h: In instantiation of ‘nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_model.h:164:25: required from ‘nest::GenericConnectorModel::GenericConnectorModel(std::string) [with ConnectionT = nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:62:5: required from ‘void nest::ModelManager::register_connection_model(const std::string&) [with ConnectionT = nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/nest_impl.h:37:70: required from ‘void nest::register_connection_model(const std::string&) [with ConnectorModelT = neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:671:104: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:862:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 862 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", - " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h: In instantiation of ‘void nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml::recompute_internal_variables() [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:876:3: required from ‘nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierPtrRport]’\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:656:104: required from here\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:858:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 858 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " | ^~~~~~~~~~~~\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h: In instantiation of ‘void nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml::recompute_internal_variables() [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:873:3: required from ‘nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierPtrRport]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_model.h:164:25: required from ‘nest::GenericConnectorModel::GenericConnectorModel(std::string) [with ConnectionT = nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:62:5: required from ‘void nest::ModelManager::register_connection_model(const std::string&) [with ConnectionT = nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/nest_impl.h:37:70: required from ‘void nest::register_connection_model(const std::string&) [with ConnectorModelT = neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:671:104: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:849:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 849 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:656:104: required from here\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:845:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 845 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h: In instantiation of ‘nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierIndex]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h: In instantiation of ‘nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierIndex]’:\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_model.h:164:25: required from ‘nest::GenericConnectorModel::GenericConnectorModel(std::string) [with ConnectionT = nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:103:34: required from ‘void nest::ModelManager::register_specific_connection_model_(const std::string&) [with CompleteConnecionT = nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:67:80: required from ‘void nest::ModelManager::register_connection_model(const std::string&) [with ConnectionT = nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/nest_impl.h:37:70: required from ‘void nest::register_connection_model(const std::string&) [with ConnectorModelT = neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:671:104: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:862:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 862 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:656:104: required from here\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:858:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 858 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h: In instantiation of ‘void nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml::recompute_internal_variables() [with targetidentifierT = nest::TargetIdentifierIndex]’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:876:3: required from ‘nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierIndex]’\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h: In instantiation of ‘void nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml::recompute_internal_variables() [with targetidentifierT = nest::TargetIdentifierIndex]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:873:3: required from ‘nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierIndex]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_model.h:164:25: required from ‘nest::GenericConnectorModel::GenericConnectorModel(std::string) [with ConnectionT = nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:103:34: required from ‘void nest::ModelManager::register_specific_connection_model_(const std::string&) [with CompleteConnecionT = nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:67:80: required from ‘void nest::ModelManager::register_connection_model(const std::string&) [with ConnectionT = nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/nest_impl.h:37:70: required from ‘void nest::register_connection_model(const std::string&) [with ConnectorModelT = neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:671:104: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:849:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 849 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:656:104: required from here\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:845:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 845 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h: In instantiation of ‘bool nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml::send(nest::Event&, size_t, const nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport; size_t = long unsigned int]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h: In instantiation of ‘bool nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml::send(nest::Event&, size_t, const nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport; size_t = long unsigned int]’:\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:391:22: required from ‘void nest::Connector::send_to_all(size_t, const std::vector&, nest::Event&) [with ConnectionT = nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:383:3: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:589:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 589 | auto get_t = [_tr_t](){ return _tr_t; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:574:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 574 | auto get_t = [_tr_t](){ return _tr_t; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:614:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 614 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:599:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 599 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:649:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 649 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:634:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 634 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:517:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 517 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:502:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 502 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:519:10: warning: variable ‘get_thread’ set but not used [-Wunused-but-set-variable]\n", - " 519 | auto get_thread = [tid]()\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:504:10: warning: variable ‘get_thread’ set but not used [-Wunused-but-set-variable]\n", + " 504 | auto get_thread = [tid]()\n", " | ^~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h: In instantiation of ‘void nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml::trigger_update_weight(size_t, const std::vector&, double, const CommonPropertiesType&) [with targetidentifierT = nest::TargetIdentifierPtrRport; size_t = long unsigned int; CommonPropertiesType = nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestmlCommonSynapseProperties]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h: In instantiation of ‘void nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml::trigger_update_weight(size_t, const std::vector&, double, const CommonPropertiesType&) [with targetidentifierT = nest::TargetIdentifierPtrRport; size_t = long unsigned int; CommonPropertiesType = nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestmlCommonSynapseProperties]’:\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:446:38: required from ‘void nest::Connector::trigger_update_weight(long int, size_t, const std::vector&, double, const std::vector&) [with ConnectionT = nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:433:3: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:1009:18: warning: unused variable ‘_tr_t’ [-Wunused-variable]\n", - " 1009 | const double _tr_t = start->t_;\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:1003:18: warning: unused variable ‘_tr_t’ [-Wunused-variable]\n", + " 1003 | const double _tr_t = start->t_;\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:991:10: warning: unused variable ‘timestep’ [-Wunused-variable]\n", - " 991 | double timestep = 0;\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:985:10: warning: unused variable ‘timestep’ [-Wunused-variable]\n", + " 985 | double timestep = 0;\n", " | ^~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h: In instantiation of ‘bool nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml::send(nest::Event&, size_t, const nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex; size_t = long unsigned int]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h: In instantiation of ‘bool nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml::send(nest::Event&, size_t, const nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex; size_t = long unsigned int]’:\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:391:22: required from ‘void nest::Connector::send_to_all(size_t, const std::vector&, nest::Event&) [with ConnectionT = nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:383:3: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:589:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 589 | auto get_t = [_tr_t](){ return _tr_t; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:574:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 574 | auto get_t = [_tr_t](){ return _tr_t; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:614:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 614 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:599:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 599 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:649:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 649 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:634:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 634 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:517:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 517 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:502:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 502 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:519:10: warning: variable ‘get_thread’ set but not used [-Wunused-but-set-variable]\n", - " 519 | auto get_thread = [tid]()\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:504:10: warning: variable ‘get_thread’ set but not used [-Wunused-but-set-variable]\n", + " 504 | auto get_thread = [tid]()\n", " | ^~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h: In instantiation of ‘void nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml::trigger_update_weight(size_t, const std::vector&, double, const CommonPropertiesType&) [with targetidentifierT = nest::TargetIdentifierIndex; size_t = long unsigned int; CommonPropertiesType = nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestmlCommonSynapseProperties]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h: In instantiation of ‘void nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml::trigger_update_weight(size_t, const std::vector&, double, const CommonPropertiesType&) [with targetidentifierT = nest::TargetIdentifierIndex; size_t = long unsigned int; CommonPropertiesType = nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestmlCommonSynapseProperties]’:\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:446:38: required from ‘void nest::Connector::trigger_update_weight(long int, size_t, const std::vector&, double, const std::vector&) [with ConnectionT = nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:433:3: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:1009:18: warning: unused variable ‘_tr_t’ [-Wunused-variable]\n", - " 1009 | const double _tr_t = start->t_;\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:1003:18: warning: unused variable ‘_tr_t’ [-Wunused-variable]\n", + " 1003 | const double _tr_t = start->t_;\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:991:10: warning: unused variable ‘timestep’ [-Wunused-variable]\n", - " 991 | double timestep = 0;\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:985:10: warning: unused variable ‘timestep’ [-Wunused-variable]\n", + " 985 | double timestep = 0;\n", " | ^~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h: In instantiation of ‘void nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml::process_mod_spikes_spikes_(const std::vector&, double, double, const nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:563:9: required from ‘bool nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml::send(nest::Event&, size_t, const nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport; size_t = long unsigned int]’\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h: In instantiation of ‘void nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml::process_mod_spikes_spikes_(const std::vector&, double, double, const nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:548:9: required from ‘bool nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml::send(nest::Event&, size_t, const nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:391:22: required from ‘void nest::Connector::send_to_all(size_t, const std::vector&, nest::Event&) [with ConnectionT = nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:383:3: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:699:12: warning: unused variable ‘cd’ [-Wunused-variable]\n", - " 699 | double cd;\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:684:12: warning: unused variable ‘cd’ [-Wunused-variable]\n", + " 684 | double cd;\n", " | ^~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h: In instantiation of ‘void nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml::update_internal_state_(double, double, const nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:584:9: required from ‘bool nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml::send(nest::Event&, size_t, const nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport; size_t = long unsigned int]’\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h: In instantiation of ‘void nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml::update_internal_state_(double, double, const nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:569:9: required from ‘bool nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml::send(nest::Event&, size_t, const nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:391:22: required from ‘void nest::Connector::send_to_all(size_t, const std::vector&, nest::Event&) [with ConnectionT = nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:383:3: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:935:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 935 | auto get_t = [t_start](){ return t_start; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:929:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 929 | auto get_t = [t_start](){ return t_start; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h: In instantiation of ‘void nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml::process_mod_spikes_spikes_(const std::vector&, double, double, const nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex]’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:563:9: required from ‘bool nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml::send(nest::Event&, size_t, const nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex; size_t = long unsigned int]’\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h: In instantiation of ‘void nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml::process_mod_spikes_spikes_(const std::vector&, double, double, const nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:548:9: required from ‘bool nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml::send(nest::Event&, size_t, const nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:391:22: required from ‘void nest::Connector::send_to_all(size_t, const std::vector&, nest::Event&) [with ConnectionT = nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:383:3: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:699:12: warning: unused variable ‘cd’ [-Wunused-variable]\n", - " 699 | double cd;\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:684:12: warning: unused variable ‘cd’ [-Wunused-variable]\n", + " 684 | double cd;\n", " | ^~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h: In instantiation of ‘void nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml::update_internal_state_(double, double, const nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex]’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:584:9: required from ‘bool nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml::send(nest::Event&, size_t, const nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex; size_t = long unsigned int]’\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h: In instantiation of ‘void nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml::update_internal_state_(double, double, const nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:569:9: required from ‘bool nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml::send(nest::Event&, size_t, const nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:391:22: required from ‘void nest::Connector::send_to_all(size_t, const std::vector&, nest::Event&) [with ConnectionT = nest::neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:383:3: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:935:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 935 | auto get_t = [t_start](){ return t_start; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", - " | ^~~~~\n", - "[100%] Linking CXX shared module nestml_6a0e5b32a83c4b3a83ce6c87a2445436_module.so\n", - "[100%] Built target nestml_6a0e5b32a83c4b3a83ce6c87a2445436_module_module\n", - "[100%] Built target nestml_6a0e5b32a83c4b3a83ce6c87a2445436_module_module\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml.h:929:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 929 | auto get_t = [t_start](){ return t_start; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + " | ^~~~~\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[100%] Linking CXX shared module nestml_f744604f1acb4f80848d611720e6af63_module.so\n", + "[100%] Built target nestml_f744604f1acb4f80848d611720e6af63_module_module\n", + "[100%] Built target nestml_f744604f1acb4f80848d611720e6af63_module_module\n", "Install the project...\n", "-- Install configuration: \"\"\n", - "-- Installing: /tmp/nestml_target_nxqmze5r/nestml_6a0e5b32a83c4b3a83ce6c87a2445436_module.so\n" + "-- Installing: /tmp/nestml_target_i949bk_d/nestml_f744604f1acb4f80848d611720e6af63_module.so\n" ] } ], "source": [ "# generate and build code\n", "\n", - "module_name, neuron_model_name, synapse_model_name = NESTCodeGeneratorUtils.generate_code_for(\"../../../models/neurons/iaf_psc_exp_neuron.nestml\",\n", - " nestml_stdp_dopa_model,\n", - " post_ports=[\"post_spikes\"],\n", - " mod_ports=[\"mod_spikes\"],\n", - " logging_level=\"INFO\")" + "module_name, neuron_model_name, synapse_model_name = \\\n", + " NESTCodeGeneratorUtils.generate_code_for(\"../../../models/neurons/iaf_psc_exp_neuron.nestml\",\n", + " nestml_stdp_dopa_model,\n", + " post_ports=[\"post_spikes\"],\n", + " mod_ports=[\"mod_spikes\"],\n", + " logging_level=\"INFO\",\n", + " codegen_opts={\"delay_variable\": {\"neuromodulated_stdp_synapse\": \"d\"},\n", + " \"weight_variable\": {\"neuromodulated_stdp_synapse\": \"w\"}})" ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -6864,7 +6891,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 17, "metadata": {}, "outputs": [], "source": [ @@ -6944,7 +6971,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -6953,7 +6979,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 18, "metadata": {}, "outputs": [ { @@ -6961,21 +6987,21 @@ "output_type": "stream", "text": [ "\n", - "Apr 19 11:34:22 Install [Info]: \n", - " loaded module nestml_6a0e5b32a83c4b3a83ce6c87a2445436_module\n", + "Apr 30 14:16:39 Install [Info]: \n", + " loaded module nestml_f744604f1acb4f80848d611720e6af63_module\n", "\n", - "Apr 19 11:34:22 iaf_psc_exp_neuron_nestml [Warning]: \n", + "Apr 30 14:16:39 iaf_psc_exp_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:34:22 iaf_psc_exp_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:16:39 iaf_psc_exp_neuron_nestml__with_neuromodulated_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:34:22 SimulationManager::set_status [Info]: \n", + "Apr 30 14:16:39 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 0.1 ms.\n", - "--> Stimuli will be presented at times: [137.0, 168.0, 197.0, 242.0, 351.0, 400.0, 410.0, 712.0, 1254.0, 1284.0, 1651.0, 1858.0, 1921.0, 2093.0, 2210.0, 2242.0, 2252.0, 2675.0, 2734.0, 2768.0, 3022.0, 3040.0, 3229.0, 3371.0, 3434.0, 3712.0, 3887.0, 4080.0, 4209.0, 4808.0, 5490.0, 5581.0, 5621.0, 5701.0, 6040.0, 6262.0, 6491.0, 6754.0, 6837.0, 6980.0, 7042.0, 7222.0, 7273.0, 7472.0, 8103.0, 8126.0, 8451.0, 8489.0, 8676.0, 8745.0, 8876.0, 9068.0, 9152.0, 9224.0, 9433.0, 9447.0, 9580.0, 9633.0, 9643.0, 9920.0, 10113.0]\n", - "--> t_dopa_spikes = [163.0, 209.0, 425.0, 731.0, 1883.0, 2106.0, 2230.0, 2701.0, 2785.0, 3050.0, 3052.0, 3395.0, 3904.0, 5514.0, 5633.0, 5721.0, 6055.0, 6290.0, 6510.0, 6781.0, 6999.0, 7069.0, 7500.0, 8126.0, 8463.0, 8768.0, 9164.0, 9237.0, 9449.0, 9459.0, 9593.0]\n" + "--> Stimuli will be presented at times: [460.0, 596.0, 722.0, 961.0, 1039.0, 1861.0, 2262.0, 2272.0, 2300.0, 3094.0, 3207.0, 3442.0, 3935.0, 3983.0, 4310.0, 5128.0, 5322.0, 5438.0, 5563.0, 5622.0, 6011.0, 6164.0, 6223.0, 6288.0, 6403.0, 6528.0, 6667.0, 6693.0, 6818.0, 7208.0, 7274.0, 7318.0, 7665.0, 7807.0, 7867.0, 8177.0, 8295.0, 8570.0, 8618.0, 8688.0, 8838.0, 9254.0, 9300.0, 9491.0, 9507.0, 9738.0, 9846.0, 10064.0]\n", + "--> t_dopa_spikes = [738.0, 2298.0, 3958.0, 4008.0, 5343.0, 5448.0, 5646.0, 6244.0, 6306.0, 6422.0, 6550.0, 6681.0, 7224.0, 7827.0, 7892.0, 8320.0, 8587.0, 8862.0, 9273.0, 9502.0, 9530.0, 9760.0, 9866.0, 10090.0]\n" ] } ], @@ -7103,7 +7129,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -7112,7 +7137,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 19, "metadata": {}, "outputs": [], "source": [ @@ -7120,7 +7145,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -7129,7 +7153,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 20, "metadata": {}, "outputs": [], "source": [ @@ -7175,7 +7199,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 21, "metadata": { "scrolled": true, "tags": [] @@ -7185,1208 +7209,1226 @@ "name": "stdout", "output_type": "stream", "text": [ - "0.0%\n", "\n", - "Apr 19 11:34:22 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:16:42 NodeManager::prepare_nodes [Info]: \n", " Preparing 1087 nodes for simulation.\n", + "0.0%\n", "\n", - "Apr 19 11:34:22 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:16:42 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 100.0 ms, Real-time factor: 3.9082\n", + "[ 100% ] Model time: 100.0 ms, Real-time factor: 0.9375\n", "\n", - "Apr 19 11:34:23 SimulationManager::run [Info]: \n", + "Apr 30 14:16:42 SimulationManager::run [Info]: \n", " Simulation finished.\n", "1.0%\n", "\n", - "Apr 19 11:34:25 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:16:43 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 200.0 ms, Real-time factor: 8.043620\n", + "[ 100% ] Model time: 200.0 ms, Real-time factor: 1.82775\n", "\n", - "Apr 19 11:34:26 SimulationManager::run [Info]: \n", + "Apr 30 14:16:43 SimulationManager::run [Info]: \n", " Simulation finished.\n", "2.0%\n", "\n", - "Apr 19 11:34:29 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:16:44 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 300.0 ms, Real-time factor: 12.32186\n", + "[ 100% ] Model time: 300.0 ms, Real-time factor: 2.726760\n", "\n", - "Apr 19 11:34:29 SimulationManager::run [Info]: \n", + "Apr 30 14:16:44 SimulationManager::run [Info]: \n", " Simulation finished.\n", "3.0%\n", "\n", - "Apr 19 11:34:31 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:16:44 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 400.0 ms, Real-time factor: 17.752280\n", + "[ 100% ] Model time: 400.0 ms, Real-time factor: 3.593060\n", "\n", - "Apr 19 11:34:32 SimulationManager::run [Info]: \n", + "Apr 30 14:16:44 SimulationManager::run [Info]: \n", " Simulation finished.\n", "4.0%\n", "\n", - "Apr 19 11:34:35 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:16:45 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 500.0 ms, Real-time factor: 22.306230\n", + "[ 100% ] Model time: 500.0 ms, Real-time factor: 4.483470\n", "\n", - "Apr 19 11:34:35 SimulationManager::run [Info]: \n", + "Apr 30 14:16:45 SimulationManager::run [Info]: \n", " Simulation finished.\n", "5.0%\n", "\n", - "Apr 19 11:34:37 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:16:46 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 600.0 ms, Real-time factor: 26.830080\n", + "[ 100% ] Model time: 600.0 ms, Real-time factor: 5.396865\n", "\n", - "Apr 19 11:34:38 SimulationManager::run [Info]: \n", + "Apr 30 14:16:46 SimulationManager::run [Info]: \n", " Simulation finished.\n", "6.0%\n", "\n", - "Apr 19 11:34:40 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:16:46 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 700.0 ms, Real-time factor: 31.369480\n", + "[ 100% ] Model time: 700.0 ms, Real-time factor: 6.339054\n", "\n", - "Apr 19 11:34:41 SimulationManager::run [Info]: \n", + "Apr 30 14:16:46 SimulationManager::run [Info]: \n", " Simulation finished.\n", "7.0%\n", "\n", - "Apr 19 11:34:43 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:16:47 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 800.0 ms, Real-time factor: 35.899100\n", + "[ 100% ] Model time: 800.0 ms, Real-time factor: 7.287057\n", "\n", - "Apr 19 11:34:44 SimulationManager::run [Info]: \n", + "Apr 30 14:16:47 SimulationManager::run [Info]: \n", " Simulation finished.\n", "8.0%\n", "\n", - "Apr 19 11:34:46 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:16:48 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 900.0 ms, Real-time factor: 40.469433\n", + "[ 100% ] Model time: 900.0 ms, Real-time factor: 8.302670\n", "\n", - "Apr 19 11:34:47 SimulationManager::run [Info]: \n", + "Apr 30 14:16:48 SimulationManager::run [Info]: \n", " Simulation finished.\n", "9.0%\n", "\n", - "Apr 19 11:34:49 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:16:49 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 1000.0 ms, Real-time factor: 44.99197\n", + "[ 100% ] Model time: 1000.0 ms, Real-time factor: 9.27302\n", "\n", - "Apr 19 11:34:50 SimulationManager::run [Info]: \n", + "Apr 30 14:16:49 SimulationManager::run [Info]: \n", " Simulation finished.\n", "10.0%\n", "\n", - "Apr 19 11:34:52 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:16:49 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 1100.0 ms, Real-time factor: 49.572998\n", + "[ 100% ] Model time: 1100.0 ms, Real-time factor: 10.31993\n", "\n", - "Apr 19 11:34:53 SimulationManager::run [Info]: \n", + "Apr 30 14:16:49 SimulationManager::run [Info]: \n", " Simulation finished.\n", "11.0%\n", "\n", - "Apr 19 11:34:55 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:16:50 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 1200.0 ms, Real-time factor: 54.278378\n", + "[ 100% ] Model time: 1200.0 ms, Real-time factor: 11.323850\n", "\n", - "Apr 19 11:34:56 SimulationManager::run [Info]: \n", + "Apr 30 14:16:50 SimulationManager::run [Info]: \n", " Simulation finished.\n", "12.0%\n", "\n", - "Apr 19 11:34:59 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:16:51 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 1300.0 ms, Real-time factor: 58.832242\n", + "[ 100% ] Model time: 1300.0 ms, Real-time factor: 12.357790\n", "\n", - "Apr 19 11:34:59 SimulationManager::run [Info]: \n", + "Apr 30 14:16:51 SimulationManager::run [Info]: \n", " Simulation finished.\n", "13.0%\n", "\n", - "Apr 19 11:35:01 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:16:52 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 1400.0 ms, Real-time factor: 63.269854\n", + "[ 100% ] Model time: 1400.0 ms, Real-time factor: 13.434310\n", "\n", - "Apr 19 11:35:02 SimulationManager::run [Info]: \n", + "Apr 30 14:16:52 SimulationManager::run [Info]: \n", " Simulation finished.\n", "14.0%\n", "\n", - "Apr 19 11:35:04 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:16:52 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 1500.0 ms, Real-time factor: 67.680667\n", + "[ 100% ] Model time: 1500.0 ms, Real-time factor: 14.507070\n", "\n", - "Apr 19 11:35:05 SimulationManager::run [Info]: \n", + "Apr 30 14:16:53 SimulationManager::run [Info]: \n", " Simulation finished.\n", "15.0%\n", "\n", - "Apr 19 11:35:07 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:16:53 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 1600.0 ms, Real-time factor: 72.092067\n", + "[ 100% ] Model time: 1600.0 ms, Real-time factor: 15.549010\n", "\n", - "Apr 19 11:35:08 SimulationManager::run [Info]: \n", + "Apr 30 14:16:53 SimulationManager::run [Info]: \n", " Simulation finished.\n", "16.0%\n", "\n", - "Apr 19 11:35:10 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:16:54 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 1700.0 ms, Real-time factor: 76.708270\n", + "[ 100% ] Model time: 1700.0 ms, Real-time factor: 16.684260\n", "\n", - "Apr 19 11:35:11 SimulationManager::run [Info]: \n", + "Apr 30 14:16:54 SimulationManager::run [Info]: \n", " Simulation finished.\n", "17.0%\n", "\n", - "Apr 19 11:35:13 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:16:55 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 1800.0 ms, Real-time factor: 81.506157\n", + "[ 100% ] Model time: 1800.0 ms, Real-time factor: 17.725170\n", "\n", - "Apr 19 11:35:14 SimulationManager::run [Info]: \n", + "Apr 30 14:16:55 SimulationManager::run [Info]: \n", " Simulation finished.\n", "18.0%\n", "\n", - "Apr 19 11:35:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:16:56 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 1900.0 ms, Real-time factor: 87.605451\n", + "[ 100% ] Model time: 1900.0 ms, Real-time factor: 18.802460\n", "\n", - "Apr 19 11:35:17 SimulationManager::run [Info]: \n", + "Apr 30 14:16:56 SimulationManager::run [Info]: \n", " Simulation finished.\n", "19.0%\n", "\n", - "Apr 19 11:35:19 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:16:57 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 2000.0 ms, Real-time factor: 93.715430\n", + "[ 100% ] Model time: 2000.0 ms, Real-time factor: 19.858900 22.9204\n", "\n", - "Apr 19 11:35:20 SimulationManager::run [Info]: \n", + "Apr 30 14:16:57 SimulationManager::run [Info]: \n", " Simulation finished.\n", "20.0%\n", "\n", - "Apr 19 11:35:23 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:16:58 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 2100.0 ms, Real-time factor: 99.787984\n", + "[ 100% ] Model time: 2100.0 ms, Real-time factor: 21.268030\n", "\n", - "Apr 19 11:35:23 SimulationManager::run [Info]: \n", + "Apr 30 14:16:58 SimulationManager::run [Info]: \n", " Simulation finished.\n", "21.0%\n", "\n", - "Apr 19 11:35:26 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:16:58 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 2200.0 ms, Real-time factor: 105.96668\n", + "[ 100% ] Model time: 2200.0 ms, Real-time factor: 22.327760e: 2152.0 ms, Real-time factor: 41.9455\n", "\n", - "Apr 19 11:35:26 SimulationManager::run [Info]: \n", + "Apr 30 14:16:58 SimulationManager::run [Info]: \n", " Simulation finished.\n", "22.0%\n", "\n", - "Apr 19 11:35:29 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:16:59 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 2300.0 ms, Real-time factor: 110.354440\n", + "[ 100% ] Model time: 2300.0 ms, Real-time factor: 23.395255\n", "\n", - "Apr 19 11:35:29 SimulationManager::run [Info]: \n", + "Apr 30 14:16:59 SimulationManager::run [Info]: \n", " Simulation finished.\n", "23.0%\n", "\n", - "Apr 19 11:35:32 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:00 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 2400.0 ms, Real-time factor: 114.504260\n", + "[ 100% ] Model time: 2400.0 ms, Real-time factor: 24.388120\n", "\n", - "Apr 19 11:35:32 SimulationManager::run [Info]: \n", + "Apr 30 14:17:00 SimulationManager::run [Info]: \n", " Simulation finished.\n", "24.0%\n", "\n", - "Apr 19 11:35:35 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:01 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 2500.0 ms, Real-time factor: 118.613960\n", + "[ 100% ] Model time: 2500.0 ms, Real-time factor: 25.454460\n", "\n", - "Apr 19 11:35:35 SimulationManager::run [Info]: \n", + "Apr 30 14:17:01 SimulationManager::run [Info]: \n", " Simulation finished.\n", "25.0%\n", "\n", - "Apr 19 11:35:37 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:01 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 2600.0 ms, Real-time factor: 122.836110\n", + "[ 100% ] Model time: 2600.0 ms, Real-time factor: 26.446105\n", "\n", - "Apr 19 11:35:38 SimulationManager::run [Info]: \n", - " Simulation finished.\n", + "Apr 30 14:17:02 SimulationManager::run [Info]: \n", + " Simulation finished.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "26.0%\n", "\n", - "Apr 19 11:35:40 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:02 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 2700.0 ms, Real-time factor: 127.048340\n", + "[ 100% ] Model time: 2700.0 ms, Real-time factor: 27.448295\n", "\n", - "Apr 19 11:35:41 SimulationManager::run [Info]: \n", + "Apr 30 14:17:02 SimulationManager::run [Info]: \n", " Simulation finished.\n", "27.0%\n", "\n", - "Apr 19 11:35:43 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:03 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 2800.0 ms, Real-time factor: 131.240150\n", + "[ 100% ] Model time: 2800.0 ms, Real-time factor: 28.530195\n", "\n", - "Apr 19 11:35:44 SimulationManager::run [Info]: \n", + "Apr 30 14:17:03 SimulationManager::run [Info]: \n", " Simulation finished.\n", "28.0%\n", "\n", - "Apr 19 11:35:46 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:04 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 2900.0 ms, Real-time factor: 135.360930\n", + "[ 100% ] Model time: 2900.0 ms, Real-time factor: 29.497765\n", "\n", - "Apr 19 11:35:47 SimulationManager::run [Info]: \n", + "Apr 30 14:17:04 SimulationManager::run [Info]: \n", " Simulation finished.\n", "29.0%\n", "\n", - "Apr 19 11:35:49 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:04 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 3000.0 ms, Real-time factor: 139.438050\n", + "[ 100% ] Model time: 3000.0 ms, Real-time factor: 30.461900\n", "\n", - "Apr 19 11:35:50 SimulationManager::run [Info]: \n", + "Apr 30 14:17:05 SimulationManager::run [Info]: \n", " Simulation finished.\n", "30.0%\n", "\n", - "Apr 19 11:35:52 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:05 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 3100.0 ms, Real-time factor: 143.641890\n", + "[ 100% ] Model time: 3100.0 ms, Real-time factor: 31.509740-time factor: 36.4780\n", "\n", - "Apr 19 11:35:53 SimulationManager::run [Info]: \n", + "Apr 30 14:17:05 SimulationManager::run [Info]: \n", " Simulation finished.\n", "31.0%\n", "\n", - "Apr 19 11:35:55 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:06 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 3200.0 ms, Real-time factor: 147.738860\n", + "[ 100% ] Model time: 3200.0 ms, Real-time factor: 32.6310833169.0 ms, Real-time factor: 46.8224\n", "\n", - "Apr 19 11:35:56 SimulationManager::run [Info]: \n", + "Apr 30 14:17:06 SimulationManager::run [Info]: \n", " Simulation finished.\n", "32.0%\n", "\n", - "Apr 19 11:35:58 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:07 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 3300.0 ms, Real-time factor: 151.965970\n", + "[ 100% ] Model time: 3300.0 ms, Real-time factor: 33.776217 3269.0 ms, Real-time factor: 48.3738\n", "\n", - "Apr 19 11:35:59 SimulationManager::run [Info]: \n", + "Apr 30 14:17:07 SimulationManager::run [Info]: \n", " Simulation finished.\n", "33.0%\n", "\n", - "Apr 19 11:36:01 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:08 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 3400.0 ms, Real-time factor: 157.258930\n", + "[ 100% ] Model time: 3400.0 ms, Real-time factor: 34.809180\n", "\n", - "Apr 19 11:36:02 SimulationManager::run [Info]: \n", + "Apr 30 14:17:08 SimulationManager::run [Info]: \n", " Simulation finished.\n", "34.0%\n", "\n", - "Apr 19 11:36:04 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:08 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 3500.0 ms, Real-time factor: 162.003430\n", + "[ 100% ] Model time: 3500.0 ms, Real-time factor: 35.897017\n", "\n", - "Apr 19 11:36:05 SimulationManager::run [Info]: \n", + "Apr 30 14:17:08 SimulationManager::run [Info]: \n", " Simulation finished.\n", "35.0%\n", "\n", - "Apr 19 11:36:07 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:09 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 3600.0 ms, Real-time factor: 166.656710\n", + "[ 100% ] Model time: 3600.0 ms, Real-time factor: 36.842860\n", "\n", - "Apr 19 11:36:08 SimulationManager::run [Info]: \n", + "Apr 30 14:17:09 SimulationManager::run [Info]: \n", " Simulation finished.\n", "36.0%\n", "\n", - "Apr 19 11:36:10 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 3700.0 ms, Real-time factor: 171.139480\n", + "[ 100% ] Model time: 3700.0 ms, Real-time factor: 37.8292007.7670\n", "\n", - "Apr 19 11:36:11 SimulationManager::run [Info]: \n", + "Apr 30 14:17:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "37.0%\n", "\n", - "Apr 19 11:36:13 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:11 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 3800.0 ms, Real-time factor: 175.338290\n", + "[ 100% ] Model time: 3800.0 ms, Real-time factor: 39.136087\n", "\n", - "Apr 19 11:36:14 SimulationManager::run [Info]: \n", + "Apr 30 14:17:11 SimulationManager::run [Info]: \n", " Simulation finished.\n", "38.0%\n", "\n", - "Apr 19 11:36:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:11 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 3900.0 ms, Real-time factor: 179.436560\n", + "[ 100% ] Model time: 3900.0 ms, Real-time factor: 40.454123\n", "\n", - "Apr 19 11:36:17 SimulationManager::run [Info]: \n", + "Apr 30 14:17:12 SimulationManager::run [Info]: \n", " Simulation finished.\n", "39.0%\n", "\n", - "Apr 19 11:36:19 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:12 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 4000.0 ms, Real-time factor: 183.708100\n", + "[ 100% ] Model time: 4000.0 ms, Real-time factor: 41.512868: 120.0268\n", "\n", - "Apr 19 11:36:20 SimulationManager::run [Info]: \n", + "Apr 30 14:17:12 SimulationManager::run [Info]: \n", " Simulation finished.\n", "40.0%\n", "\n", - "Apr 19 11:36:22 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:13 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 4100.0 ms, Real-time factor: 187.850330\n", + "[ 100% ] Model time: 4100.0 ms, Real-time factor: 42.564458\n", "\n", - "Apr 19 11:36:23 SimulationManager::run [Info]: \n", + "Apr 30 14:17:13 SimulationManager::run [Info]: \n", " Simulation finished.\n", "41.0%\n", "\n", - "Apr 19 11:36:25 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:14 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 4200.0 ms, Real-time factor: 192.070740\n", + "[ 100% ] Model time: 4200.0 ms, Real-time factor: 43.518165\n", "\n", - "Apr 19 11:36:26 SimulationManager::run [Info]: \n", + "Apr 30 14:17:14 SimulationManager::run [Info]: \n", " Simulation finished.\n", "42.0%\n", "\n", - "Apr 19 11:36:28 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:15 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 4300.0 ms, Real-time factor: 196.311790\n", + "[ 100% ] Model time: 4300.0 ms, Real-time factor: 44.452600\n", "\n", - "Apr 19 11:36:29 SimulationManager::run [Info]: \n", + "Apr 30 14:17:15 SimulationManager::run [Info]: \n", " Simulation finished.\n", "43.0%\n", "\n", - "Apr 19 11:36:31 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:16 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 4400.0 ms, Real-time factor: 200.388120\n", + "[ 100% ] Model time: 4400.0 ms, Real-time factor: 45.441398\n", "\n", - "Apr 19 11:36:31 SimulationManager::run [Info]: \n", + "Apr 30 14:17:16 SimulationManager::run [Info]: \n", " Simulation finished.\n", "44.0%\n", "\n", - "Apr 19 11:36:34 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:16 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 4500.0 ms, Real-time factor: 204.522525\n", + "[ 100% ] Model time: 4500.0 ms, Real-time factor: 46.392475\n", "\n", - "Apr 19 11:36:35 SimulationManager::run [Info]: \n", + "Apr 30 14:17:16 SimulationManager::run [Info]: \n", " Simulation finished.\n", "45.0%\n", "\n", - "Apr 19 11:36:37 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:17 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 4600.0 ms, Real-time factor: 208.628985\n", + "[ 100% ] Model time: 4600.0 ms, Real-time factor: 47.312103% ] Model time: 4569.0 ms, Real-time factor: 68.1602\n", "\n", - "Apr 19 11:36:38 SimulationManager::run [Info]: \n", + "Apr 30 14:17:17 SimulationManager::run [Info]: \n", " Simulation finished.\n", "46.0%\n", "\n", - "Apr 19 11:36:40 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:18 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 4700.0 ms, Real-time factor: 212.699730\n", + "[ 100% ] Model time: 4700.0 ms, Real-time factor: 48.225025\n", "\n", - "Apr 19 11:36:41 SimulationManager::run [Info]: \n", + "Apr 30 14:17:18 SimulationManager::run [Info]: \n", " Simulation finished.\n", "47.0%\n", "\n", - "Apr 19 11:36:43 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:18 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 4800.0 ms, Real-time factor: 217.743655\n", + "[ 100% ] Model time: 4800.0 ms, Real-time factor: 49.164590\n", "\n", - "Apr 19 11:36:44 SimulationManager::run [Info]: \n", + "Apr 30 14:17:19 SimulationManager::run [Info]: \n", " Simulation finished.\n", "48.0%\n", "\n", - "Apr 19 11:36:46 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:19 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 4900.0 ms, Real-time factor: 221.758590\n", + "[ 100% ] Model time: 4900.0 ms, Real-time factor: 50.158080\n", "\n", - "Apr 19 11:36:47 SimulationManager::run [Info]: \n", + "Apr 30 14:17:19 SimulationManager::run [Info]: \n", " Simulation finished.\n", "49.0%\n", "\n", - "Apr 19 11:36:49 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:20 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 5000.0 ms, Real-time factor: 225.805775\n", + "[ 100% ] Model time: 5000.0 ms, Real-time factor: 51.082096\n", "\n", - "Apr 19 11:36:49 SimulationManager::run [Info]: \n", + "Apr 30 14:17:20 SimulationManager::run [Info]: \n", " Simulation finished.\n", "50.0%\n", "\n", - "Apr 19 11:36:52 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:21 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 5100.0 ms, Real-time factor: 229.738330\n", + "[ 100% ] Model time: 5100.0 ms, Real-time factor: 51.998568\n", "\n", - "Apr 19 11:36:52 SimulationManager::run [Info]: \n", + "Apr 30 14:17:21 SimulationManager::run [Info]: \n", " Simulation finished.\n", "51.0%\n", "\n", - "Apr 19 11:36:55 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:21 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 5200.0 ms, Real-time factor: 233.717475\n", + "[ 100% ] Model time: 5200.0 ms, Real-time factor: 53.007102\n", "\n", - "Apr 19 11:36:55 SimulationManager::run [Info]: \n", - " Simulation finished.\n", + "Apr 30 14:17:21 SimulationManager::run [Info]: \n", + " Simulation finished.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "52.0%\n", "\n", - "Apr 19 11:36:58 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:22 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 5300.0 ms, Real-time factor: 237.654490\n", + "[ 100% ] Model time: 5300.0 ms, Real-time factor: 53.966624\n", "\n", - "Apr 19 11:36:58 SimulationManager::run [Info]: \n", + "Apr 30 14:17:22 SimulationManager::run [Info]: \n", " Simulation finished.\n", "53.0%\n", "\n", - "Apr 19 11:37:01 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:23 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 5400.0 ms, Real-time factor: 241.620775e: 5385.0 ms, Real-time factor: 283.5706\n", + "[ 100% ] Model time: 5400.0 ms, Real-time factor: 54.936086\n", "\n", - "Apr 19 11:37:01 SimulationManager::run [Info]: \n", + "Apr 30 14:17:23 SimulationManager::run [Info]: \n", " Simulation finished.\n", "54.0%\n", "\n", - "Apr 19 11:37:04 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:24 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 5500.0 ms, Real-time factor: 245.678255\n", + "[ 100% ] Model time: 5500.0 ms, Real-time factor: 55.914930\n", "\n", - "Apr 19 11:37:04 SimulationManager::run [Info]: \n", + "Apr 30 14:17:24 SimulationManager::run [Info]: \n", " Simulation finished.\n", "55.0%\n", "\n", - "Apr 19 11:37:07 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:24 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 5600.0 ms, Real-time factor: 249.818500\n", + "[ 100% ] Model time: 5600.0 ms, Real-time factor: 56.955628\n", "\n", - "Apr 19 11:37:07 SimulationManager::run [Info]: \n", + "Apr 30 14:17:24 SimulationManager::run [Info]: \n", " Simulation finished.\n", "56.0%\n", "\n", - "Apr 19 11:37:10 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:25 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 5700.0 ms, Real-time factor: 254.011505\n", + "[ 100% ] Model time: 5700.0 ms, Real-time factor: 57.908482\n", "\n", - "Apr 19 11:37:10 SimulationManager::run [Info]: \n", + "Apr 30 14:17:25 SimulationManager::run [Info]: \n", " Simulation finished.\n", "57.0%\n", "\n", - "Apr 19 11:37:13 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:26 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 5800.0 ms, Real-time factor: 258.028620\n", + "[ 100% ] Model time: 5800.0 ms, Real-time factor: 58.853528\n", "\n", - "Apr 19 11:37:13 SimulationManager::run [Info]: \n", + "Apr 30 14:17:26 SimulationManager::run [Info]: \n", " Simulation finished.\n", "58.0%\n", "\n", - "Apr 19 11:37:16 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:27 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 5900.0 ms, Real-time factor: 261.964470\n", + "[ 100% ] Model time: 5900.0 ms, Real-time factor: 59.945702\n", "\n", - "Apr 19 11:37:16 SimulationManager::run [Info]: \n", + "Apr 30 14:17:27 SimulationManager::run [Info]: \n", " Simulation finished.\n", "59.0%\n", "\n", - "Apr 19 11:37:19 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:27 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 6000.0 ms, Real-time factor: 265.921750\n", + "[ 100% ] Model time: 6000.0 ms, Real-time factor: 60.894403\n", "\n", - "Apr 19 11:37:19 SimulationManager::run [Info]: \n", + "Apr 30 14:17:27 SimulationManager::run [Info]: \n", " Simulation finished.\n", "60.0%\n", "\n", - "Apr 19 11:37:22 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:28 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 6100.0 ms, Real-time factor: 269.958005\n", + "[ 100% ] Model time: 6100.0 ms, Real-time factor: 62.060147\n", "\n", - "Apr 19 11:37:22 SimulationManager::run [Info]: \n", + "Apr 30 14:17:28 SimulationManager::run [Info]: \n", " Simulation finished.\n", "61.0%\n", "\n", - "Apr 19 11:37:25 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:29 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 6200.0 ms, Real-time factor: 274.147785\n", + "[ 100% ] Model time: 6200.0 ms, Real-time factor: 62.982232\n", "\n", - "Apr 19 11:37:25 SimulationManager::run [Info]: \n", + "Apr 30 14:17:29 SimulationManager::run [Info]: \n", " Simulation finished.\n", "62.0%\n", "\n", - "Apr 19 11:37:28 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:30 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 6300.0 ms, Real-time factor: 278.180890me: 6268.0 ms, Real-time factor: 407.2064\n", + "[ 100% ] Model time: 6300.0 ms, Real-time factor: 63.929497\n", "\n", - "Apr 19 11:37:28 SimulationManager::run [Info]: \n", + "Apr 30 14:17:30 SimulationManager::run [Info]: \n", " Simulation finished.\n", "63.0%\n", "\n", - "Apr 19 11:37:31 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:30 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 6400.0 ms, Real-time factor: 282.224865\n", + "[ 100% ] Model time: 6400.0 ms, Real-time factor: 64.875848\n", "\n", - "Apr 19 11:37:31 SimulationManager::run [Info]: \n", + "Apr 30 14:17:30 SimulationManager::run [Info]: \n", " Simulation finished.\n", "64.0%\n", "\n", - "Apr 19 11:37:34 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:31 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 6500.0 ms, Real-time factor: 287.381755l time: 6485.0 ms, Real-time factor: 337.1852\n", + "[ 100% ] Model time: 6500.0 ms, Real-time factor: 65.849913\n", "\n", - "Apr 19 11:37:34 SimulationManager::run [Info]: \n", + "Apr 30 14:17:31 SimulationManager::run [Info]: \n", " Simulation finished.\n", "65.0%\n", "\n", - "Apr 19 11:37:37 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:32 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 6600.0 ms, Real-time factor: 292.719700\n", + "[ 100% ] Model time: 6600.0 ms, Real-time factor: 66.819457\n", "\n", - "Apr 19 11:37:37 SimulationManager::run [Info]: \n", + "Apr 30 14:17:32 SimulationManager::run [Info]: \n", " Simulation finished.\n", "66.0%\n", "\n", - "Apr 19 11:37:40 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:33 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 6700.0 ms, Real-time factor: 297.928300time: 6668.0 ms, Real-time factor: 435.7229\n", + "[ 100% ] Model time: 6700.0 ms, Real-time factor: 67.754537\n", "\n", - "Apr 19 11:37:40 SimulationManager::run [Info]: \n", + "Apr 30 14:17:33 SimulationManager::run [Info]: \n", " Simulation finished.\n", "67.0%\n", "\n", - "Apr 19 11:37:43 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:33 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 6800.0 ms, Real-time factor: 303.177260\n", + "[ 100% ] Model time: 6800.0 ms, Real-time factor: 68.684433\n", "\n", - "Apr 19 11:37:44 SimulationManager::run [Info]: \n", + "Apr 30 14:17:33 SimulationManager::run [Info]: \n", " Simulation finished.\n", "68.0%\n", "\n", - "Apr 19 11:37:46 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:34 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 6900.0 ms, Real-time factor: 308.374353odel time: 6885.0 ms, Real-time factor: 361.9108\n", + "[ 100% ] Model time: 6900.0 ms, Real-time factor: 69.596333\n", "\n", - "Apr 19 11:37:47 SimulationManager::run [Info]: \n", + "Apr 30 14:17:34 SimulationManager::run [Info]: \n", " Simulation finished.\n", "69.0%\n", "\n", - "Apr 19 11:37:49 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:35 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 7000.0 ms, Real-time factor: 313.505170\n", + "[ 100% ] Model time: 7000.0 ms, Real-time factor: 70.501357\n", "\n", - "Apr 19 11:37:50 SimulationManager::run [Info]: \n", + "Apr 30 14:17:35 SimulationManager::run [Info]: \n", " Simulation finished.\n", "70.0%\n", "\n", - "Apr 19 11:37:53 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:35 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 7100.0 ms, Real-time factor: 319.070813\n", + "[ 100% ] Model time: 7100.0 ms, Real-time factor: 71.398766\n", "\n", - "Apr 19 11:37:53 SimulationManager::run [Info]: \n", + "Apr 30 14:17:36 SimulationManager::run [Info]: \n", " Simulation finished.\n", "71.0%\n", "\n", - "Apr 19 11:37:56 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:36 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 7200.0 ms, Real-time factor: 323.023983\n", + "[ 100% ] Model time: 7200.0 ms, Real-time factor: 72.288359\n", "\n", - "Apr 19 11:37:56 SimulationManager::run [Info]: \n", + "Apr 30 14:17:36 SimulationManager::run [Info]: \n", " Simulation finished.\n", "72.0%\n", "\n", - "Apr 19 11:37:59 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:37 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 7300.0 ms, Real-time factor: 327.331420\n", + "[ 100% ] Model time: 7300.0 ms, Real-time factor: 73.19176633\n", "\n", - "Apr 19 11:37:59 SimulationManager::run [Info]: \n", + "Apr 30 14:17:37 SimulationManager::run [Info]: \n", " Simulation finished.\n", "73.0%\n", "\n", - "Apr 19 11:38:02 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:38 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 7400.0 ms, Real-time factor: 332.593820 Model time: 7385.0 ms, Real-time factor: 390.3997\n", + "[ 100% ] Model time: 7400.0 ms, Real-time factor: 74.090727\n", "\n", - "Apr 19 11:38:02 SimulationManager::run [Info]: \n", + "Apr 30 14:17:38 SimulationManager::run [Info]: \n", " Simulation finished.\n", "74.0%\n", "\n", - "Apr 19 11:38:05 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:38 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 7500.0 ms, Real-time factor: 336.802090\n", + "[ 100% ] Model time: 7500.0 ms, Real-time factor: 74.983429\n", "\n", - "Apr 19 11:38:05 SimulationManager::run [Info]: \n", + "Apr 30 14:17:38 SimulationManager::run [Info]: \n", " Simulation finished.\n", "75.0%\n", "\n", - "Apr 19 11:38:08 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:39 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 7600.0 ms, Real-time factor: 340.891773\n", + "[ 100% ] Model time: 7600.0 ms, Real-time factor: 75.870774\n", "\n", - "Apr 19 11:38:08 SimulationManager::run [Info]: \n", + "Apr 30 14:17:39 SimulationManager::run [Info]: \n", " Simulation finished.\n", "76.0%\n", "\n", - "Apr 19 11:38:11 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:40 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 7700.0 ms, Real-time factor: 345.941543\n", + "[ 100% ] Model time: 7700.0 ms, Real-time factor: 76.873181\n", "\n", - "Apr 19 11:38:11 SimulationManager::run [Info]: \n", + "Apr 30 14:17:40 SimulationManager::run [Info]: \n", " Simulation finished.\n", "77.0%\n", "\n", - "Apr 19 11:38:14 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:41 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 7800.0 ms, Real-time factor: 351.548327Model time: 7768.0 ms, Real-time factor: 514.7829\n", + "[ 100% ] Model time: 7800.0 ms, Real-time factor: 77.826991\n", "\n", - "Apr 19 11:38:15 SimulationManager::run [Info]: \n", + "Apr 30 14:17:41 SimulationManager::run [Info]: \n", " Simulation finished.\n", "78.0%\n", "\n", - "Apr 19 11:38:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:41 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[ 100% ] Model time: 7900.0 ms, Real-time factor: 78.751227tor: 229.8747\n", "\n", - "[ 100% ] Model time: 7900.0 ms, Real-time factor: 356.748190\n", - "\n", - "Apr 19 11:38:18 SimulationManager::run [Info]: \n", + "Apr 30 14:17:41 SimulationManager::run [Info]: \n", " Simulation finished.\n", "79.0%\n", "\n", - "Apr 19 11:38:20 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:42 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 8000.0 ms, Real-time factor: 361.131403\n", + "[ 100% ] Model time: 8000.0 ms, Real-time factor: 79.696011\n", "\n", - "Apr 19 11:38:21 SimulationManager::run [Info]: \n", + "Apr 30 14:17:42 SimulationManager::run [Info]: \n", " Simulation finished.\n", "80.0%\n", "\n", - "Apr 19 11:38:23 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:43 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 8100.0 ms, Real-time factor: 365.055957\n", + "[ 100% ] Model time: 8100.0 ms, Real-time factor: 80.634769\n", "\n", - "Apr 19 11:38:24 SimulationManager::run [Info]: \n", + "Apr 30 14:17:43 SimulationManager::run [Info]: \n", " Simulation finished.\n", "81.0%\n", "\n", - "Apr 19 11:38:26 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:44 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 8200.0 ms, Real-time factor: 369.042590\n", + "[ 100% ] Model time: 8200.0 ms, Real-time factor: 81.619257\n", "\n", - "Apr 19 11:38:27 SimulationManager::run [Info]: \n", + "Apr 30 14:17:44 SimulationManager::run [Info]: \n", " Simulation finished.\n", "82.0%\n", "\n", - "Apr 19 11:38:29 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:44 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 8300.0 ms, Real-time factor: 373.174913\n", + "[ 100% ] Model time: 8300.0 ms, Real-time factor: 82.674708\n", "\n", - "Apr 19 11:38:30 SimulationManager::run [Info]: \n", + "Apr 30 14:17:44 SimulationManager::run [Info]: \n", " Simulation finished.\n", "83.0%\n", "\n", - "Apr 19 11:38:32 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:45 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 8400.0 ms, Real-time factor: 377.813927\n", + "[ 100% ] Model time: 8400.0 ms, Real-time factor: 83.573099\n", "\n", - "Apr 19 11:38:33 SimulationManager::run [Info]: \n", + "Apr 30 14:17:45 SimulationManager::run [Info]: \n", " Simulation finished.\n", "84.0%\n", "\n", - "Apr 19 11:38:35 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:46 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 8500.0 ms, Real-time factor: 381.832757\n", + "[ 100% ] Model time: 8500.0 ms, Real-time factor: 84.547516\n", "\n", - "Apr 19 11:38:36 SimulationManager::run [Info]: \n", + "Apr 30 14:17:46 SimulationManager::run [Info]: \n", " Simulation finished.\n", "85.0%\n", "\n", - "Apr 19 11:38:38 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:47 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 8600.0 ms, Real-time factor: 386.786580 85% ] Model time: 8585.0 ms, Real-time factor: 454.1770\n", + "[ 100% ] Model time: 8600.0 ms, Real-time factor: 85.507656r: 498.3424\n", "\n", - "Apr 19 11:38:39 SimulationManager::run [Info]: \n", + "Apr 30 14:17:47 SimulationManager::run [Info]: \n", " Simulation finished.\n", "86.0%\n", "\n", - "Apr 19 11:38:41 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:48 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 8700.0 ms, Real-time factor: 391.085007\n", + "[ 100% ] Model time: 8700.0 ms, Real-time factor: 86.458454\n", "\n", - "Apr 19 11:38:42 SimulationManager::run [Info]: \n", + "Apr 30 14:17:48 SimulationManager::run [Info]: \n", " Simulation finished.\n", "87.0%\n", "\n", - "Apr 19 11:38:44 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:48 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 8800.0 ms, Real-time factor: 395.228320\n", + "[ 100% ] Model time: 8800.0 ms, Real-time factor: 87.356531l-time factor: 102.6180\n", "\n", - "Apr 19 11:38:45 SimulationManager::run [Info]: \n", + "Apr 30 14:17:48 SimulationManager::run [Info]: \n", " Simulation finished.\n", "88.0%\n", "\n", - "Apr 19 11:38:47 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:49 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 8900.0 ms, Real-time factor: 399.164097\n", + "[ 100% ] Model time: 8900.0 ms, Real-time factor: 88.301119\n", "\n", - "Apr 19 11:38:48 SimulationManager::run [Info]: \n", + "Apr 30 14:17:49 SimulationManager::run [Info]: \n", " Simulation finished.\n", "89.0%\n", "\n", - "Apr 19 11:38:50 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:50 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 9000.0 ms, Real-time factor: 403.140237\n", + "[ 100% ] Model time: 9000.0 ms, Real-time factor: 89.268438\n", "\n", - "Apr 19 11:38:51 SimulationManager::run [Info]: \n", + "Apr 30 14:17:50 SimulationManager::run [Info]: \n", " Simulation finished.\n", "90.0%\n", "\n", - "Apr 19 11:38:53 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:50 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 9100.0 ms, Real-time factor: 407.147390\n", + "[ 100% ] Model time: 9100.0 ms, Real-time factor: 90.198226\n", "\n", - "Apr 19 11:38:54 SimulationManager::run [Info]: \n", + "Apr 30 14:17:51 SimulationManager::run [Info]: \n", " Simulation finished.\n", "91.0%\n", "\n", - "Apr 19 11:38:56 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:51 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 9200.0 ms, Real-time factor: 413.148308\n", + "[ 100% ] Model time: 9200.0 ms, Real-time factor: 91.312207\n", "\n", - "Apr 19 11:38:57 SimulationManager::run [Info]: \n", + "Apr 30 14:17:51 SimulationManager::run [Info]: \n", " Simulation finished.\n", "92.0%\n", "\n", - "Apr 19 11:38:59 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:52 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 9300.0 ms, Real-time factor: 417.084235\n", + "[ 100% ] Model time: 9300.0 ms, Real-time factor: 92.258660\n", "\n", - "Apr 19 11:39:00 SimulationManager::run [Info]: \n", + "Apr 30 14:17:52 SimulationManager::run [Info]: \n", " Simulation finished.\n", "93.0%\n", "\n", - "Apr 19 11:39:02 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:53 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 9400.0 ms, Real-time factor: 421.012175\n", + "[ 100% ] Model time: 9400.0 ms, Real-time factor: 93.268796\n", "\n", - "Apr 19 11:39:03 SimulationManager::run [Info]: \n", + "Apr 30 14:17:53 SimulationManager::run [Info]: \n", " Simulation finished.\n", "94.0%\n", "\n", - "Apr 19 11:39:05 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:53 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 9500.0 ms, Real-time factor: 425.045858\n", + "[ 100% ] Model time: 9500.0 ms, Real-time factor: 94.197652\n", "\n", - "Apr 19 11:39:06 SimulationManager::run [Info]: \n", + "Apr 30 14:17:53 SimulationManager::run [Info]: \n", " Simulation finished.\n", "95.0%\n", "\n", - "Apr 19 11:39:08 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:54 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 9600.0 ms, Real-time factor: 429.079772\n", + "[ 100% ] Model time: 9600.0 ms, Real-time factor: 95.096162\n", "\n", - "Apr 19 11:39:08 SimulationManager::run [Info]: \n", + "Apr 30 14:17:54 SimulationManager::run [Info]: \n", " Simulation finished.\n", "96.0%\n", "\n", - "Apr 19 11:39:11 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:55 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 9700.0 ms, Real-time factor: 433.271405\n", + "[ 100% ] Model time: 9700.0 ms, Real-time factor: 96.199429\n", "\n", - "Apr 19 11:39:11 SimulationManager::run [Info]: \n", + "Apr 30 14:17:55 SimulationManager::run [Info]: \n", " Simulation finished.\n", "97.0%\n", "\n", - "Apr 19 11:39:14 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:56 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 9800.0 ms, Real-time factor: 437.196325\n", + "[ 100% ] Model time: 9800.0 ms, Real-time factor: 97.343078actor: 284.0776\n", "\n", - "Apr 19 11:39:14 SimulationManager::run [Info]: \n", + "Apr 30 14:17:56 SimulationManager::run [Info]: \n", " Simulation finished.\n", "98.0%\n", "\n", - "Apr 19 11:39:17 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:56 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 9900.0 ms, Real-time factor: 441.222980\n", + "[ 100% ] Model time: 9900.0 ms, Real-time factor: 98.475973\n", "\n", - "Apr 19 11:39:17 SimulationManager::run [Info]: \n", + "Apr 30 14:17:56 SimulationManager::run [Info]: \n", " Simulation finished.\n", "99.0%\n", "\n", - "Apr 19 11:39:20 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:17:57 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 1087\n", " Simulation time (ms): 100\n", " Number of OpenMP threads: 4\n", " Not using MPI\n", "\n", - "[ 100% ] Model time: 10000.0 ms, Real-time factor: 445.25468\n", + "[ 100% ] Model time: 10000.0 ms, Real-time factor: 99.42664\n", "\n", - "Apr 19 11:39:20 SimulationManager::run [Info]: \n", + "Apr 30 14:17:57 SimulationManager::run [Info]: \n", " Simulation finished.\n" ] } @@ -8405,7 +8447,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -8414,7 +8455,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 22, "metadata": {}, "outputs": [ { @@ -8426,16 +8467,14 @@ "Number of synapses: 100000\n", " Exitatory : 81000\n", " Inhibitory : 20000\n", - "Excitatory rate : 14.43 Hz\n", - "Inhibitory rate : 3.42 Hz\n", - "Actual times of stimulus presentation: [ 169. 243. 352. 401. 1255. 1285. 1652. 1922. 2243. 2253. 2735. 3230.\n", - " 3435. 3713. 4081. 4210. 4809. 5582. 6838. 7223. 7274. 8127. 8490. 8677.\n", - " 8877. 9069. 9634. 9644. 9921. 138. 198. 411. 713. 1859. 2094. 2211.\n", - " 2676. 2769. 3023. 3041. 3372. 3888. 5491. 5622. 5702. 6041. 6263. 6492.\n", - " 6755. 6981. 7043. 7473. 8104. 8452. 8746. 9153. 9225. 9434. 9448. 9581.]\n", - "Actual t_dopa_spikes = [ 164. 210. 426. 732. 1884. 2107. 2231. 2702. 2786. 3051. 3053. 3396.\n", - " 3905. 5515. 5634. 5722. 6056. 6291. 6511. 6782. 7000. 7070. 7501. 8127.\n", - " 8464. 8769. 9165. 9238. 9450. 9460. 9594.]\n" + "Excitatory rate : 11.38 Hz\n", + "Inhibitory rate : 2.70 Hz\n", + "Actual times of stimulus presentation: [ 461. 597. 962. 1040. 1862. 2263. 2301. 3095. 3208. 3443. 4311. 5129.\n", + " 5564. 6012. 6165. 6694. 6819. 7275. 7319. 7666. 8178. 8619. 8689. 9301.\n", + " 723. 2273. 3936. 3984. 5323. 5439. 5623. 6224. 6289. 6404. 6529. 6668.\n", + " 7209. 7808. 7868. 8296. 8571. 8839. 9255. 9492. 9508. 9739. 9847.]\n", + "Actual t_dopa_spikes = [ 739. 2299. 3959. 4009. 5344. 5449. 5647. 6245. 6307. 6423. 6551. 6682.\n", + " 7225. 7828. 7893. 8321. 8588. 8863. 9274. 9503. 9531. 9761. 9867.]\n" ] } ], @@ -8461,7 +8500,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -8472,12 +8510,12 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 23, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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" ] @@ -8569,7 +8607,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -8580,12 +8617,12 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 24, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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nZh+kMC7jf+Z0FmNKvpeQ/kvvK3vU7hsWoOWh1eh4Y3Az3Ze/fTk2d2zGj974UaryWScb/i7m0u9Dg3B7HfSoMGT7MZY0LMGXHv0srvnFFzH76X+lfGovyDLWvwp07ACsHuDV3/V/e/sJLr300rLUo9sn3wsbKMOPwbUtfcH3CMo1p/ZFOM6+OeHLyuj3wxCUa06J1hYG3AETchCzD+eiwTy7D2ll9xZIwpDsa3tU52sD6/NVdjAfKOlbsSgUGNPgyrRPhQpDth/j/xb8H05eMxKT9tTgnYfuR66rU1OSYuHQY/HYuLOxV2gU1l/MTop4VVF2B7jqqqsAAMV8DtQtj35n39FFlgdWR2QHn1u2fAB7MjgQzKn3IgajhiwdBne/yz2nKAX+N3s7FlV/D9i5uCx1bmrfFHu/s4U/l4w+aMjYR/fZKafD0z8AbjsT6NiVXFYDmjC0+8UetZ/YuZcyfXt6uvutH8C+YYFSKioM2X6MjJHBgU2Rx6yVVzM/naQanzrpNvzwmF/jwc7SHY5LDurBOof20TxmMKG/99xp06Zhw8J5uOWbX8azf72hLHXuH8dEelA7euMkQuC9gGnTpg10FwYMr6zsX5/PwYAtuQJarBgzI+UaSL+fU0oxd+5cvPnmm3B9IVG551Q98hhv5gBiwHzky2Wp8zPTPoPd3erv37itE41bdcLLXoCTeu1HRGTLJmDxA8CeZcBzP+u3Zso1n3bvfgbbtz+49wj5/eRbE8a4v5Qjkwqly574ff8YXg4Vhmw/RsbIcESnTquyIzMi/P339tIi6YggaZaswbThBtqyaHWVex+jlGLZsmXYvHlzeSuW2unX6nH44Yfjtbtvg+s4WDt7RvIDabC/EgsaVA+LiNPqKYMv6uHexns56tUvn1iGhs7knFQDDZmATLdOV4bpLVaip5+Sy+7atQsvvPAC3nzzTaxduxZA+efUp6pX4TWcibvwJZDu8iVl1+XMbNyiYsb6sDdyKrLeVzPoYDMmac3rel1NkhlcOeZTd/cGrFh5Gdas/Q1a2+b0uT4RyUzevif9W7unE48t2CaQCOknsO1EZy3pj4m/H5r/Vhiy/RgmMeGyQQxcdQ6JDCMB2Sv6Kk5DpugTswOUQ6qybNkyPPHEE7j//vuR4/LL7Fuora1FZ1NjcsESsFdNFgsDn5PKMKO3NIYOSf3c/sqr1tbWDnQXBhRrdw/8nEwCFawI0hJF12zYCQDocVzMbmPeM+n5Erbcpqam8PfKlSsB9HFOKbpWR/wE9hja+3oVsKlac1h2DQrZT33IDMaaxu2noDMozx7F5tNraHi+z/VJUH7Wfftbf/qvM3H540vBUYUlvJJTQs6yXmHfHl4lKgzZfgyDGJyGzHU0C4Q5gHozx0s+wAxm2mmYxFLqpq6Ltx64G289cLey/MKF3mbsOA727Nkj3S8X+ttkcd68ef3bQH9iwd3A9ROBV34z0D0J0dv9vDffuezmGmVCmjm1dt5uvPSP5ZJfzf4Aq580R71FOrqufymRUvZzg9nLbdsjysu2T+mWTFt5giY4CWcP25G+uOzutz5kKfc0p72Artk7+QiT7EAY8W4S5ZhPhERtOE5Pn+t7L6Do7429PrmEB/Mal5neouJDVsE+BZOYoIyGrFyBIIA+LoYkDVmJWDNnJhZMfxILpj+JLcuWSPdZosHRMaW9xV7cFL71rW8JTfeubfaxvUYsPHuZ9++sm/qtiTvevQM/eO0HaM41a8uwphPvhbxrSRDnlAqv3L0S6xc0YNZjvTdLGqwoS1L7foa0zq3StfxcDWUUDrB7a+BDlmZO9QnTf1yWahzN2aPcFvoyTfZbjiwdmu5ZgbanN6Bt+obwGmUEIdlJH4h9vhzziWXIaBloDgnKOTO4hD29Ry/nrLDPvPFGurxnqbE/aZt9VBiy/RiE8Ja7OgKeddpMO8XdvoRjJMy0Szig0mgWWnZEeT92rF4ZW4dbRqZ0b+Oyyy7j/nad0s1EHMeBw9l2R9iXJU4t+RbcvORmvL397diEwKyj8frGhMhg+/BcSQtxTsVhw+LymssOBuwLU15al6ueSfWcdudMfOneaciCvbWUOdUrbHi9LNXoGDIV+sS4s1TWPjDfSsGs2hrMr6mOnVPWbi/aXm5pZN5KGWLaGH1YbBvlmE+EEQLTfjGvFN6/pwXYPp/tQD+0uXfAUZElzV+i+FVGpOhLz/z5aLnvfrjFfSP/X4Uh24/haciiv8upIXN10ok0K08Z1KP3IAxRoHpHlmjYl5mOe++9l/u7VOaSUop77rkHmzZuVN/vdc8GHpYT5RR7c9ub+nLMltdjFbTlAAja2315dPQQ51QFgxDinuWUTlxohXF9pJRUDNm+MqdcnQZDMVZxwvjmoo1VXTFay/1UQ7akeSUunTAO3zxgPDYZpb0XYYWyCURDOeYTx5ChfzRkLaQLS80tyMMC3v7f8rcxQBDE+umf6+dgNtSOp3/cQgFbvvZ17LnuOrQ+9FD5O9APqDBk+zEIIakYMlZrQFPGAmc1ZGUJe097K4UBDIbBEx3gvfsy0bAv4oILLuD+LpXBdhwH27dv54aXcN++L70bWJjMHIiTfJeS2FIvLNh3pZ0ixDlVweCDuL9SZ/AkNGeJroDp21fmlG6f2L2xQ7qmM2+2XYrzFq7Fx+avwWvN8nOAwI+lNLPq6dmCxUsuwY4dj6QqPxB4fmcU6fedTGmHBzenE6QC5ZhPLAOoohH6DAo8WT0X87LrMSO7Elj/qtiD8rfZj+AEOKR3tFl1dXX5OgQgKwzhrj/Og5vXazspk5i66Ra91cxgQoUh249hEpPb+HQEvMsS5SnrphqTxVRh7zmTRdWhWNrmlaQh219MFqdPn879rQ3SMgjQ2FnAqyv3oJggxSoX2HmnlXyXij76GuwL2lhxTg1WBAEjyo194BPJ6pl+MLlybBubly5GoacHvTVZDOZ7X+bU3vwcuqAea+bulnrianrWatvYmvc0lv+zSWMCbZSuKVi+4sdoaZmB1Wt+ne6BAUBfGBvuhE8QAvdmPi3csxDzd7Mmg6zQtj/OzejDbjGb9mkTRSBuXyxhbzDZFEp9X9nH1AjsikPRNTvG7YALHrdv0H0VhmwQ4aWXXsLtt9+OlpaWstQnRVnUMmSlw9FEJ0ulLUvIQ1aqMIkkaMD2msliP2/Coi19OU1QgfISQxfePBPfvm8B/vflNWWsVQ+W6Y7TkJX0jq6DLVv/gQULv4B8cVPvOzeI0e/+Pn3ESy+9hN/97ne49tprMXPmzIHuTr9DtT9Je2pKhiyVcMzHzEfuwxN/uApPXHdV6mcAtbBrsM+pADrBTaZKQRZptlqTef+tOY0paS821s7OZaU/tNfRO1M2CQnnZqnzaWP7Rlzy4iX45kvfxOqW1V4TSBIC9w3Ssj3i31I/m+/uwrp578Aq9C0KYdkEkQJYk0VSAv1U7sjCQwy5PrcrxnybJisjBhsqDNkgQbFYxOzZs7F792688MILZanTY8iYSalZTG4vpkGfgnqAs+GQb5dqAcmazexthmwvinR/8IMfcH+XqiFTvTu72ZZzbHa2e4fLnW+r/dVUsNsLaH16PfLr20puj+17OTVk69dfj/b2Rdi+5+ry1DnIIM6pwYR8Po/Zs2eHf7/6qmgG1HfsE4JscV32QkOWtLIXTH8SALBrXWkCFJXJ4mCeUyx0gpvsVDk3nc7SkD0522wH127Yye1FlFI03b0czIWS+6nSRFHqwHUHNlCBxVo/lIkcUKHU+cT6ED+38TmvCaJwa+huBnYu7hc1ucu6ZQDY1Z7Dp/46Q1n26f+9Fs/833WYN+2xXrf32NrH8MGHPohH1zwaW66Y0v+Ud2sYHIxNupQgGgxiayIWFYZsL+PV5g6cOnsl7t3RxF1nN/GNmqALpULUkOlMDNirqU0WNSdUOqksa5MctK55LkV1Rgkmi/uCGZkOb7/9Nvd3OTbHg7qW9rmOcqH5vpXonr0LTf8oXTrMahHiGLIRtAQpJDO+3bnFJfdpMGF39248te4pdBV5YlOcU4MJe2Ot9rqJJQ8BL/0aKPZ/TiNKBRdbTUJjEb1mNkt4TuWfO5jnFAvdPuGaRYgkadoUGTdvbcAbLZ1RXd2Cv18v5ptoYue6FubMPR8zZ30IhcLART7d1BS9Z6HEJMD8MMSToaXOJ4OpL/jGUlAP1wFuORW486PAmjIkiha+66Or+Xf686vrsGKn2sdw+0qPYZ/z5L963fzVs69Gj92Da+ZcE1vupkXp0s7wey/zuwSag62jHHIvdWaBmAUlCEb2BVQYsr2Mry7diG35In65dru2TLkmj0EM3qhAZ7LIMiwp6+6bhoxBeCj2vr4kk8X9xYds5MiRnHOyW4YIlYd3zu1zHeWCtSNiFhobX8H8BZ9HS8s7JdcTx5BlmQhbE0eMjq9IZ9qSdLp0NQL/+iqwY2FCwb2Hr73wNfxm1m9w1SzeJG3kyJED1KNkDNZk2ujcA0z7f8Dsm4FZf+n35ih1Beswzfxu3wG88CtgS+lrRmgxdUmVsGswzykWKg1Zd/dGHDT5dzj07PkAJ+RRj4nq6qKOiEknCjOrUiEKUpub30BPz3pYVgs2brqxz/X3FhzBXerxzXkoxI9RqfOJm5NBQ2JQj+4moMfPV1mOvHbC/FgteJ1sbu7uextlwH0r7yv5GVZDltlUnpQTpYBSimL383DsnaqbcQ9Gvysasgp6i3IxZHLYe3W9DhcQId3E1fmQpdGQFbfvRtOqIbBzhpK4SBnoMWrTUERtZLCvhb0vbt6MzldfBRUCGUycODExgEkcVO9uMOM1mIZm6bJL0dGxGIuXfK3kZ+2UGoTE9+0tw/v8z4FV04GNb/Tu+X7AiKYa3L/+D5i0oJ67PnHixAHqUTIGLUOWb4t+L3+y/9uj4Cl/3bx89OvA3NuAe84rofK+jbGKISvXnOrv/UgluFm1+gqYZjeGTmpE1bBIu6Xri+qyE9Px3ryTqBFlTRVtS6112TvoywdK7zPel/kUzEkCIagHSzPk+38MyT5GalPNX6Rtay/r6D12rVsDt7gaVGHd4jouNi9ZiFxXp+JJtuC+IYjft2bJewRl1ZCxPmSaSdmdjQ74optOkpM2fK8Km75/FRrfHYbtM0dFxEUf3jlJAzbYNWSUUuTzu0ApBXUcbDj3PGz/rx+i7Qme2HvppZc4iWtvoyyyI+04Geb6IOLISgTvt+ECj34DmHunoqRCeqqtVD2+iXzCllm+GTBzkJWBudjcvhnbOrYlF1TgD1t/iDH2SHyp+Rzu+ksvvdTnfvUX9orJYm8e4tJ29L/klQozVRslbseCXtUuXenluAd7a5/mFNP2b55ejrtm8sF0unZVw+opD9miirJoWa3hb8Nk9xSAOhRuT3LKAf5bxd1NC/7MIoTdswdQ8q8zaysZ8d+z1PmkFApzuQccoGNH1GMnIR9lHNq3A46V+Pp9VZQufiU9I1RusBoyZ9jBvaujD3t5ocenSRV1NG7aiCeu/y2euv538oODScKcEhWGbJCgP4gPyYdMI1l1mTKO46CYj0lyGTzTB5NFt8eTdOSaq5QETal7Vylh7/s3ymLvHlu/4X8w650zsXnzzaBMRvnd117LlfvZz36WaJ5ZKnZ0Tu1zHSWjnzdKh7rAymnAC5fH+vj0VkOW9JxVlcU7HxgJnLwFhJRHALCtcxsumHYBLph2AZpyTckPCKhza5XXf/azn/W1a4MehWLp4xULLpxyeQlitZ+Ey5sNpGQC2e2otBWXvrQYwAIo35wq2C6ueXYld23bW6Ox+dUxZalfpSHjEhYzwkzXddFw2xLs/MNcFLZGGhXVXhCnIeudDxmvIev3nFopQbjf6V5sccNi+QxOODfLMp+YNotWAfe/MBe/x2V4GH3IcbbmReDG44B7P5N4KBh95MjeeWJ9n54vFdzrMF23RxyuKNu/53lAv6kEqI2bPYHNrvV7J5pzf6PCkO3HkMLeazZvPiBCFHErDmX3IeuDBoEP6qEwyxvkURa3bv07AGDjpr/wNyxeGnvJJZfw71KGKIsWrWbul1Rd7+E6oJYDp70PkkkBWm2XEMSCl+n2TkOWhI0HOChUm0B9EaPH9E6yadud2LnzceTznt38Y2u9CFwOdTBt/bRe1RmAXSOXXHJJn+pS1l+miVRqPdSysOPyX+A7LzrcZO7p2RTzVISuri7k8ymCvnAasr0vhU0d1IN7Jk2pEvthOehZ3BD+HQiI+mNOsbB7MqCUwrIs9PT0PqiKQx309PTg9ttvxyOPPCLPN//PcVV1yD61Adb2LsChaH18rVhEqLfXXWLABqYQ9iESb6K/t9Abi4oX7nsYc3bN4SYkNbJoHK0XDJZnPkXtNTU2YMNWb19dgyPQXHtY76p85Cvev1vfUZrEsaNTBlfCvQoKCtPXzOZpNrquoK/sRrUA3ymX31YMQxZnebIvuKeIqDBk+zG8oB7JJotsYmgXBhq3bE6sm2XI+jTxgwOF3aBLrILXkCk0bnvLZLEMm64bYwr66KOPlqQhW/TyFrx23ypYBf3GyIW0LaGffQG1Lez562Ls+uM8Ttrcpzp1c1CYD9vIsORnfOxYv0F5PUl2YDH0Um81ZKvX/AarVv8SCxddDADIGtGhaJcpMfBfXl2LptO+j2Xb28tS30Cj9V+PomP6dHxyMcX7N0Tf1iBZ7TPBHGhtbcWNN96Im266CYVCgqAgMbF9mUEpx1Dl7AIeXv0wVjav1D8DngjUJTbuCx5+cwNuaumB5fvjBGP56KPxobfLAatYxN/+9jf8+c9/7nXeTpe6eOONN7B7926sXr0aW7duhcv4RrsZzzTwzBEHwdwRmfI7nfFmi07cWCtuUUrx23U78Nv1OyKfpxizWNYfifYqi2h5kFYrxuLrTRfg78v+Ll1fNvVS7TOlzidlUA8Gopmnw0itr597PS595VJ0FhN8kgCOGaa2vGdQliAg+xap/cy0p/CV6kU4wOgAO2lV9ElRc4ZbMfvo5ncX4cFf/xTrFyQHFYtMUBUMWVniNw4e7FuzZD9Gf5kssvO1u9CF3d275baFSZ3GDMLVBPXY2NiND17/Gv6cNiGwkqkgzK/kBTdoEkOXAa+tkr9PgAsuuIALYBIX1KNtTw9mP7kBq9/ZhcUvb9GWY6Nj7a2hsZt7PKkaBdqmRaYYNvH+KysYYibvmNhKoohdSRLeZ+/6Z++a5PwVNC/UuRuYeSPQrGb69ux5BgCQz3s+YyZDoPU5z5r/of/y6jpsbOrGf/5zft/qk+ovb3VpUdwazfMDW4Csk0VDQwNvhqbBjBkz4DgOcrkcVq1alb7RMpssqiDuWXd1rcZ1c6/Dl579UuxzbNJit8zrvNtx8NNMD546ZBjmHHac14a/H11wQe/NwDry6YQNmzZuREdHB2zbxptvvtmrthzqoLMzIry7u7vR1RoxW7mDj+bXcgBOeCgPJheRMcVgP93Qhju2N+KObY14udkjbvlousKYcPvL4DBZLAVHzPw49mxOL4hLM59suzv0rVTTDKw/L/9Nevwjd03LGjy0+iHM2jkL/1j6DzRu64Rjx4wviTddZgXdZsrB6otvfm+go4dWLF+ODKE4p2oN8nakAVNNN1JlyheBWMnlE9f9BrvXr8XTN8SH6QeiSKXqPKr7Fwuzf71NBRzEKIvXz7kO5zxxDja0iUQgIwGBkSp6n06T87fX12FXex5/fT2lzXPCgZLGLGJv+JAtXboUa9b0v53ykm1t2nvTp08X8v7Ih4Ddlkf7y5vRw0ittq3yJMjqd48nLvoDrNbI7fGIjS7bwWc/XI+LPlyPbs3+Hgdt35kx2kOr+FsJc6Grra30jkBw96GaLfaRi4FXfwfcfW6qOg3m8NcltNWhvSBowITXbuoqn+loOeE4eYwevRXZbLJPKwAQMwp2YLjAJ3Z+Arfeeiu279hVUruWlRS4gSW49fvXho1/xqpVV/Q5gS+llJtUT/RsDn/HMecsORSrtZEeVJelLkVhczvcooMeRiC3YezEqJ/w9qneYpUmV1Mccrl080OES13pbLDyDOEOCpqtUjyYVG9p/VjbE5nJLu30TDC5wB2CiapVjP7OF0rIq1h29O68GN54IOxi+j0saT51da3BjJmnYcGCz2vP982bb2X+4svkm7w50G1FWtBd7xTx6B/m44U7YnJislpMJUMW7dlpgjpNqjsaO38/Gx1v9i5wU2+QRri3viGi5VTjmxlVw/29csYbmPXog2WjJuJ8yGLHdZAL31WoMGT7MQghnKlKV7ELLnWl5ICsJIcSko4h0xjKF+IkSiqUIw8Ze6j2Q5TFdevW4cknn8TDDz+MpiYxQEB5F73VotdmXXnllfy7KLSUTXevQOfr2+A+HTHdca9sgODHqMa5yO7F/Ys5vPxGH9jZjF21BnbXGnhqkt7ErGQwB86C2mr+Vj+9MDVYIs/73ZpvxeKGxVGhHQvRZB2Cadt+gLXz9VrRAAbpvZb35sU3Cx2ksAoOagZfwFEOW7f+Bcce9xamnvBKqvLEjMbIILWot70Q/2+9qU8sG4xkr7XoGua4rW0BNm++BTt3PYrtOx5MX51SZsJfDLYAJzMOX353Ax7a2aysy+CYjdRdkN7/jXv/jvnPPIGOV7eg8falaL5vJa99I7wE+8orr0zfWFyfhXuWYWLZYUfBIYQr11szdIc6EkPGClAIoertPWEwgxnhujY2brsRrZNfi302o9BkcomMhTm2e/ee8Hfzti3Y9fvfD4zlB9OmUcI5KJLQSaxK0nxavfrXcN08OjqXcv6itU41xjYNQ3f3ZrS0zora0wgcTMb65OCVpwIAtixTry2vIlZDpvIhYzVkyQzZh8ZfBFpw0PHi5sSySbBtG22MQPGtlk4s7pD9LfM5Oap23FyiKrpPeLcXbv4/zHniYdjFSNDXG/NWsX4lQ8aMcX6XkKeswpBV0Fv0eUOlFNizAsi1hZdMYnK7XaCY6LH4hckHOjBAnORpUb6gHvGSsjQmi0nEVF9NFlkTpk2b4gIElG7EsWcjr0kk6+dwibpZfOUrX0n0l7Mb/G/LMMaSGQRT/2hjDL6Aavw3apGx4gmb1nwrvvLsV3DljCtLG8ftYoJk1q8RaCra2FOMtBIt1WW0W2QlgEK1pc6E+gnLkKlpS25SoSG7f9X9+Prz38CShiXhvWktV2NH8QS8cle8LxDQNw2ZaKZs5R08cNVsXNpRg6Fu/Fj3Zr2U6xjctfsBAEB9fUofN4agYvPrWVbyeJWkRWfva0wWC4VozNvb+pYgvG3PLm5QA3qyfcxleLu1Gz9do5CoU8od7uFodOwCSbJKEN5p0fNP4+0H70Hn6147hfVt3FJy/T0pYIy+8pWvJLyRHuzWJ87MV449FT+6/Pd4+JwLld9rT/ceLGlYknrOutQVLA5cgGPIXKhmM7ufqpoKNO87djyIrbvuRMMx96NQv0PbD5N50yBCI68h4zW2HLNWLKDt4UfQMzfZF6fs6OU2LTNk8RUlzSfHjTSkrpsLCfffb/8+znl7KjrmCmesxJB5tJO59PHYdiQYJWjI+iGqR+fMHWi6byWcTl4DTynF3XffjetuuQ2fmb0MX1yyHl96dwPOW7gWjjkiLHf8hmG4/Vv/IQVxEwUcdt3Q8HcuR7Dghc1o2p7Cx65MCOdHgsnifT8+B69sUQvvGkeMQqGrW8rtOthQYcgGEEkmUyVh/avAbWcAf/9YKK0RoywGE9uFi/Xz5+CRP12Fz917Pl40owVNiYlD8ker22CdxNmgHqCoLwzHJ9dcgmO7SwxJXAYfjCQfskQNmZUDHP1CNU3Gf0d8vo+f8IErfsJ3pboWxSqFmQyAZcuW8e+q8eMTERAoShvs0VEUwGyCdvOmRTdhefNyTN84HWtaSzDfvPtsvk3mmzdnKE6ZvQK3bWuM+tuLkz4uqMem9k3Y0bVD+lSlMhuTP/JXHPTxPyb3hdU4+wtweG4c/nP+9Xj6odnhvQIdKj0LqP0IknzIdO/S3daKsa82cNc2vduIno4isiA4M+cRfmu785jZ2jnofSxj4WvI1k88CI+dcw0WHOztY3GBcoLXlQjztBC+RdF28aM56/C5dWOxCYd69dHk3FVxeP2eO7i5awKY0ELhVE3SP+Q6gg8Z9fwV/3I8aIeeOQAAmmJf4YV4vIZs2bIYM68ExK38raMnAADuuvBL3J6+pz2HolPERU9fhK+98DXM3DEzVVsqk8V0GjJvTjVt74SjmFsBU9XaFjFJxSE7w2dFsLR6sDPGach4KatXYXFr7/NUiQQ9i67WAraubFauoe0tjHalBF+2Unf3pPnEj1XUj6k9RwIAut9pEMor+nrbGSBzbyutY6yGTEE/sOdAOXLcs3uzW3TQ/uxG5Fc2o20674Ji2zZ27tyJGUe+D/PyDt5ujSINW9XHhb9PWTMSoBRvPXA397y4/zUe+T68fGIdto7JYN0KE3Of3oh/XZvG77hMTGjgQ5ZgsjiizcFP3/xpdNMfr3emnoQvXn8Lznv8RWz43OdLjk69N1FhyAYQ5VIyAQCe+p73b8tGoKcJlFI/ymIEw//DcR08/b/XYsfCxTjmbRuLjWgzoSAYa09UNsHm0hAX7cfXfw2Ht7wf57QcxpRJ8YLKjbz3A5MUZVEiONu3A/97NHDr6YCtPpjSatjm7ZoraR87i3oiV3fdZfMcFfiw7UaCv5yyHfE7MO12HhKZ05AE5nhn104QF5iyeSg2LikhCa1rw6XAirZx2NEzlPtGDx1gIi/0zymjMHFL13Z8ZtpncOG0C9Fm8NtdEvNhVMnjWzUkxoQlAKsh8/84uvE0VDu1GLNaI+xgwIYSj6okGN1Whbq8KWnItnRswTlPnIMrZlwhPffynX9D/UbBLIUZbwKAZgg+Mm81Pr9kA2a28vOtP90Ku2wH3Z2d2LVuDSyrA7lcPKOQhCDgza+/fzlah0/EgkOOAQA4ynVCOTOa0vxM9Rqyf8zciEdz3VhvVeNaXOPX1zepbKGnm1O7HtQI/PUOvl05ZLvLa7EA4O0bANfm9lwVodjZ3ChfBNBIOrDG3AkHLiesDgJf6BjZLVu24KabbsKsWbOU9zlwayemGNPxDY1daOhpQJflzd1r5iQHCgC8c1DWkLFENFX3glK88+R6/Ova+Zj3rGwxEZzrHKNAvO8l1tbjuFjfE5l2RRqy6FnLEn082VxpwYP8fLBSCusAoP0FvdXHv66dh+l/fRcrn5kF6thckAtH2EfSYunBVXhg+KfQjTptmfz6NnTP350yyAUfdVLUuBHJj1ehIQOQQYlgvlFurawxYldgYOGwAKdiBs4qeVtdflAVps5agQcD82RmAeZW8lFGg72gcegIRZ9TWD8J6/il4z6AuUfX4N5PDFM/oKNvtH+UBtP3DVb7iUdjfOw2YFg3uzF5v3/9/csBACsPPhxLDAOF9Xs3p1spqDBkAwjLdfHUuqfw0uaXEomAwoYNyK/x859QKi8C09OqFJHB/z2zECdd8wp2tPaAMur5WncoxuTGcBL2kV1VYCc1q2Zv3r41ypIOniETbYkndnjSKAqKOuoxNnYqhixBWpFGtMStwRJNFt+4Dii0A83rgI1vaLqQzl9h9q45uHlJ5K/z+tbX8eFHPowrZ2ps4HUbGfvOd30yLDd16lReSpZSuxh0efHixd4PzZge3vh6bD2GYeDorUNx+spRWHXHI8h1eg741p496Jk/Xz2H/Wsr2sfjxV1H45EtJ6LI2K2rHinUqQnCOHz/te8rrz+4+TmvTqeAN2p5AsClFHnLUQoOHAM45su6sPd8+bzjosP2v8W8v0u5z0R05Xuwa1w1qobJDAilFB2vy9LuwsbduOCdA3DhjANALQdv/PNOvPqPW9D23HNY8q2vgG7biWc3PovmHM8wbl32bmxfCAA6JPLZ+9Mm3ryx1HPUdSm+/4Bnokdd2T8hwOruHKbOWo4PvzYHD/3mp5g54+N4Z/ZZ6OxcUWKLDHwNWcOoSEtPoRJcUJxXtRpfrF6CQo/3rXqvIePX4J9fjnJU5YmXjNsqREKaQo8FO8GEsqMph56OSDhECOE+xKfny/2ThHvU4cPeU6okxlzXxcqVK+FURY75eXu1VI4Sgqer52NGdiVWmdu5eREIkLrNDDb05DF1Kp9T6p577kFrayteeSXZFzAtYc++CQFFlRlZFaRNC6HSkMkmiwpQ4N1XPfPNVbN2SreDACpc6PrAaNTf8Ao9LVi27L/wmbmz8K/dEUEdbUXRs6tf460R2FD3M2vPxFXf+yl2MOX/+MJqHP/bl/Di8nTBbJwuvQY33+3de+vFIh6/6jn885ez0NEcmAjqd4f1DZ14eM4adBeib+HCRc4Enjx9CN6sPxWP4j/U/eksoukfy9D6xDr0vNsozScRcSkCvGsCgyaaLPrfxCh1s2P2jO6lMkNWyBiwMl7bBiFwh2RwI/kVbic/wrs4qaSmnvrgEDRZNn6mMU9WgSiuB4bMWUu/0sRzvHHYSE3JBMSYH5cCw7dQUvuQMbQdAf5revzeveTEE+H2MgjQ3kDJQoEK0mP16tU47rjjtPdn7pyF37zzGwDAQ598KLyeyeTx7pNfRM3aLI74we1wu7ux8VOfBgAcPv1JVL18CXrMDG496TM4BIejtrEWp9MRGIlduIN+G51r5+J7XVPx6JwuHO2vBFJj4PPHdSFfGILX26PDa8wJzWgb+evw70Cqs3nJQjxx/W8x8oCJ+Mx/X4yW1hkwa98H2/Ic5R2HwnULMIxqbGrfhCP957uHbMYXa7dhoTVRac4hIVj8Oxdr7/e0t6FhyyYcdNwJWLR4MTZu3IjzzjsPQ4d6Jl/dzTtRPaKAYkdVSHz1zJ+PjhdeRMfnP463Z0RO/SyxtbM7hxv2HItzuk/HufVzgEIndrfncc2zK3HW0WPxxVMme2PHHNqrdrZj8qoWbFrahJPPPTi83n7gTLy/Zite+9cu4FSgeeNi/HjGjwEAz258Ftd/+HoAQLHYhM2bb8Po0R/FyJFnqF+ZZZgaVgJWD1BVj3/d90+MbIy0J8ViHu0vbYY5shpDTjsA3fPmcfWsnpjFosMMnLXodfzulq1Ao4rYjb7RyG69pBTwzOaO3F4f/t26aydq6uqx8YLPwO3owMQb/4xh553nV0vxqYYXMLrYgs5DqrCk9QA0jJ6A1z70aZg7l+LMY17FmA0XwnXHAOCDeHSMXcr9PW/ePMyePRsfOOts7HCG4vypB6C2yvRMsObcij1Hn4f1bWqpVxVzWB+TOwmnjfkglrW+jZzTBdt1cfI1r+C4sSb+ddw8zO8Ygw58CB/DbLQON5GtdWAhgyKqUA9G82l3YceaVVg143Ucd/5ncf6mJrRaBTw7eQeOf/7nwFSNJNHHL++7Ev8+ZSgOm/I7rH70TgTHVcOWDjx3y1KcVcsTzj97+VLUPLMRo1CFastE3RPvYtF2j5GgW/fgqNYu/Hw38PNvZ9Bj9WB07WgAwNatW5EbeyDMBpHxE53pojnQk7Mw64n1OPHfJmPTtnVYOWsnko6J5ua3YVltGD/+Ary1rhEvrdiDo9r/Beq2gGQmAvi49Myv1+5AzqXIDR+LjsNHwoXHBKxd9wecfNJD6LIdPIBv4EisxQcQmXlSSpWRtZa8/Dwa1q+CaMSXqc7hkEPncNfGkm6MN7zxW/f6G9g9ZqxSQ0Ypxeuvv45cLoezP/FR7H7rBQwfeTKGH8mqcbz9ZOOSRrTs7EKNYUBkx4t578quNxdg2iOtqB9ehf/4w4eBfA4N//M/OG8zxQuHnA4AaG/owWPXzEOm2sQ3rv8QivY6jH7fOmRqI0LTMQlEYtgB5b8SdbGtOZqzLkXIkLV2bwV13kW27mOY/847mLVkFnD48RiyagEIgEPP2S6Nb/vQkXj6Ax/C8dnFmLj+RZyML3L3bWLg4WNPx21zV+OCua/g7wIRPWnycmSzebiuDcPI4Pnnn0dzczMybgY2Y6EhftuxRC3cYMtN6GnhtCKBBvmxuQ9jV+N2fOH0D6B59xOoGXoqajqjPbvoa+7DIaM0NDH2GqFIIiVVWS08eamDptaVeBHnYzMOw89NB8GucO0jc/DG8GZ8q3oRlpNvc8/u6sjhT9Mfw8mMz9n6Rdsw+hNrcPTaN4A9y2FM+mB475/DvgmcCPy4ox1T/zQLF5xwIG5/yxMkXfrAImz+46fCd3u38V0cMuwQjKgZwbWpk3mKhHlDy1AAFt55Yj3O/e5UdNVGgrOgCru9gPzqFry27RJMHr4Fc677PI7GOWgmnXiuahFGGmMAeHN9Jj6C/wSfk2x3eyeeWbMbp1URjClSdL+zE4+v/Qca3z8Vp3/2S6gdNhxvP7IWuc4iPnBULf7WtAEbx56LL2EFqmBhlxjYATzR3ozReCbzOdQPr8MB7bzwymTW1O4RJt6ZUoNT1vPayXD/eeW3QK6VGUN+rLLZHBadOgyUjsD4lh58sOopPNv5y/D+QpwK5DuAVc9I/U3Cnj17MHb46PBv13Fx5sbPY/vwtdg8emmUy07BkJ29CHjnCIqzlowDANhmBrNO+TgOmLcZ5zdRDPvEQdG7AtjFtBPAznRj6xgTC9q7ccrwerRMfxbfP+VINFcR/GNeukTtmToLB36gAR3bhnhtOQ4eufMeLBx7IP77wrMxIhvtZp3NfiA1lcsFFwSI4MRN3n78zoYm7L7hzzgGAHFd0MDP1TCAErTHexsVhqwf8dprr+Hcc89FfX298v6MHe+EvxftWRT+PvKoOWgasQ04DRhx623IThgf3mu58b8xYdxq/HXUSDy46gF8btPnAAAbjQ/hm9iMZl8q21W/Dp/bchaW1b8FADjkjCKGj2jAcDTg+JVHh7bquz94MHaSiIwJGLLnbv4/AEDrrh14d+k3AQBjp56G7bO+AwDotl7Em2/9CQcf/F1sbN8YPp8b4klwTs7ugO26YCV9SqSwPX/4qsvRtmcXzvr6d/DsfI9xc2wLX7n4P1Do6cbiOX/BMV/ahY5t9cit8wiBLV/7OgBg3oq3gWM+FDXHLOpvvr0QS446Ew8fdSa2PvtxVLkOfvroEryzoRnPLduFL5w8CYQQTno+bfEO5F9dAgDoaMzhzMOHwapuxe7j/4FaACc1j8WGRctx0DOfBA49QHqXlat+iebmN7Ft+z/x0Y+o/bCk3DdOEUA9Tho1BJsY5cmW+etQv80bv5rDR2Dr17+BoRfdGd5/7EyPYd09/Exc+tD/ofuoE/WDDKDWig+eYBADE1ppmPjYdWy4PT1wOzxN2c5f/3fIkI0tNuGwHi9i5IyGQ2ASin9d8E3ka+rwRwo8OPnXcKra4fRcJrXjCor7559/HgDw4rR/4Z/5U7FmTyeuPP8Y4L4LgfZt2LjsfuCA8VI9gBdFMsAlbd8FHeqiKlONmbufQt5y0F10cP6eu9DQvBDP4+sATsMIdOBQrIaFDH6Bm9CGkbgeP8UE+Nqj5rV45Dc3en1rz2PXSZ8AkMX1W9ZAH08vmnefOey58Dcxi6COF/3xuVuWoqejiJwQaOPlXTPxaSOaSyOW7ULPSO/bttfVYFJrFw7yaSPWnPHuu+8Gho2GkeXDEnPEPHEAGq3R5t1NWPKqjUUr16HZ8XxgRmTej6yt9nfr6dmMJe/+JwAgmx2B7sIRXguun2rB3gHquujuWYfa2oNgmt7+lGMEIxaTuNlxPK3atRt34QXyGbwA4B4aOfW7rsv5dAJeYJzX7vLCWtvjeALiyKNnY+QIMYpl9P75jg488aeFmPIFWYu+adMmzJgxAwAwBI/CqZuFoetPx0njfhsdnK6DfLeFF273/FyuHDIHP8VFfGu+yeLbN8+AO+Z96Gx3sHVlCxoeegxVL7yCHxXaMOPAE9BVVYfFL20BpV7glc3vNmJ7z6cx7DDw9SkYMptSsDFE1zd0Yt6mFmCSd/a4AGCYaCnUws557/SBUafipSWMf45haEOyvvyRC9FQMxav42x88aiHJGK9aehwdPtathmnHI1cx07UDjsQADBsWAMOPdTbt3fvfhLAmZjnC4+mDJ+C5aOWh/WIvMGnqtU54dhyIwudsBZEAj2XutjRtA0ffGoSgElYWXeJ93qnvIYj34j8hN5Z34hiw24ELJoU1KOXdlYOpVi77ho0FZtxP/kWAGDchE24YgfgOC5uHl8DYCLupD+Qnn1++W7cN/lXwrs6+NrzX8W89Z72lbgOMJx/bsWw4fj3jS1YvXETJg0xsD3Df8dnNz6LK2deiUOHH4qnL3xaEECU9n5drR6Tkq9mUhQEZnK3v4tCVyOO+JgnIKs6aQYw+xy8kV2OIrGx1YiYICrs826xiC89+ybWHDgZJ55Yg3/My4G6FMN2b8biFzaju60NJ579HSx/y2NW20dMw61jvwm44zES5+PTeBrPv/Acxp3zIehwI36BTZkjgBOBS9+aFvYk+r+Huz45DK5BsOLgakhwLGDWX/hrwsQ94MC1MDKedrFpvIkJWAdrFPvRKPDsZcDyxwF8WNtfFR599FH84Dv/L/zbAMHxez6M4/d8GLef/mPmuvxhJzcZ+FCRYlKjtw/PPumjmPf+j2BedxtOmN2FySZB9Vmer+ba8ZPxxpST+Vc3Clh38Ho8fsrH8OCidXiz3sY78+Zj3tc98/D7D6nC6HXJ73Dwx3Zh6KRujDrKm0PNjz6Ky6acAgCw5y3DXz70/rDs0//3BwA6DRkzj5lv8N1b3sBjb04DAGQcB5ZPwznEAI2JFzDQqJgs9jM6OvR5VUwj0lSxmpsxYyK1dNfMGUCGibjk25O/Ul/L1dXsDgVhTBmK8CZdMImr66N8JXVmJPVpxSiunsDnxTDkqTFkYqSB6XD/AEotbN58i/b97DROcgqzuwYmb1BHc6MXZQzAm/f/I7y+Zu06rHjrNaybNxsHfdS7P2xyN4o53g+s1hnBN8eM85KaIeHvYmcGoA7e2RAdGJYTmJ6wu230TluWe2Xt6khSNuKwTmxbsQZZqM1AmpvfVNbFQmLI/DFaspCP1lbdyPgZNOglU931amJabjieOTaJiaG5qM/UdXnxKhPBiCVmWop1IKDI1/Amg13jFyGjsnJMkErf+bYvAGj31kkxxqyVjWDmGgVsOvOXyJ99O4ysExKVXzDfQhtD4azEYXirpharcBwayAQUSTUexcVRpSSas6y/TSeG+v1n1k7wfowE1WEYIGJ4dXXN34VTXAcjTQIKfk0YAFz1FJRmkCrgh1vLC4RYYa5Zs52rxKEeQ5Rrj9ZgsUbvN9fREZlE7tz1OEwix0zbPe2TmDvvfCxe8o3wGhfqmxHaBE750xvawms9qENINFEK27bx2GOP4dlnnwWlFK27Im3CuqOOBIuhI+S+c/OLyGs82CPYsNFOnef/1HnAHNhtbNoGB3nG5MvJ8e177fn+Q4y29o37V2FB29FYdOJPAADDi964s9HYHFtjiqSY7u6mGdzfm5u6uO/qmSyayDkR8zu5dlxyxT5ah0fnRA51yAuJfQ2Gqu+ybfzrvo+G/q81NZGWq7V1DorFaI8eVeDPn7TBD9jTiRICe9OW8G+HOshtbpWecYV8drbrIMeYj3oaMmZtErdXtlY2BbZvvx8FRGf0O8O8sWYDea0meusZDgZFzmHyjTWu1ZcFcIgln92B2fym9k2SSWdOlxNMc3yr/LoC2sNpLXA+W3atp93IESsoGEIUvOUWL8GaAz2rlCUjfZqHaWvt7BnoYQKQ7BwTrftleJ9ffTzNsYkcEXs/7FtcVMQ0AUwE1WkBvFCMAD4zVjqam/X78clNJ+Mf//DoJJWGzDENHNASXd9wcOTTvKeGoGdRQ3guvq0Q4FpVbVg3PhLgP7O7BYVstKdsq2P9+TSHFoChkyJzdte10b0qMpN+pKi24FAH9WBNFqPnsswcNxn/SjdG6DQYUGHI+hlx/giEUVDqEvRR6nAJT4OFnk3gdYLJG+wLnCkGM7FNIcsl9Se4iiGLg6vIlumkEb0pbL5Xzo+IvPY9rHSbX6gv3nqjJC0X/UUMYVz1ATYgMYeBySU7FtI2TeWwva4iik/RKkpzQRf0RGbIvM3l2OOO5fvHEu6lZiNVIIn2MIjBEfPi+7Bjzzo0u5RAd75lFTY/4kGdhANtDUEBfoNrm/w6rLpG2LUtGHNcK4J1YMOEwczf9dlq3D98KCdh7ELE1LoMYW1w7+xL4agq0ijDyLJO5r6fStsT6zEyY+CMIaZ07BgA5wvKBT4QlaklhsQ3qlo5EXk49yh7sOrnFjGiw5hSh/MzDbByxGYAQHt7JFDgQrKzh6o/17PMGnC8EfDKui7mzp2LFStWYMGCBdi0aRMMVmAljodiLnmEggs2w6/Kz1TcW6JKhT3GZLUN8jOBhowNN5/r9AjUfO1Yry1/7+EDJ6nHXUUs2o98lfs7a4D7roGGzND5RSHa+1UQ57mb44l6liEDMbCFFoHNHpPInj0utfj9VPLvSckBMWNJCeGCWrjUhZnNqp7iQVwhIiqFHNQjoRuKXTPI/WkiGiNHiESp75NcHxGcmzrzpe/1bJTWopCofNE2mXkFtPyYcl7qGCFK9PuRuM+TjGLtCG2x64MfX+/ZNN9M0Uv//2nnnqINoV0qnWt9P5+TqrMz3Tik6xA0Njb6XZILUWJwvnLsunYIP96GknY1+GdME6ZQR6mg1AHNpDDWo/JJxFrAsPfYMyXLaMScFEFNBhIVk8V+RqyDOJPHwtZE4qLUDp3VHULCBaNOxMhKnXmGjLNSYv4wFIwUEEUsU6GzhqAb9agHE5yB8OYeAFL6kMntG4qNWQdimmCVUWKURXFT0jNkJGR8AgQmlyyRYKTY8EWGrMauwY1/vhH19fU4huGpxPwy4XWNhmzVqtUYxkkY2Vxjid1KhGoDZ+Ed6oKGjH2Gy/HB23brDmyVI3WpDFlcr9mZlBsRBekYNrkbDUtc1BzwLzS1ZThiudHMwKWAwTC8bJ8cZttknwvKUMW2yh4lbkzggAwh0nlvEOEdOQ0ZP1dSMWRsZZSvPCDKSYx0kwVhR5g6yCTk26HUBSEGF5LdYcbDafeIQ5Ob5yYIoaDU209ZCXFLSwuGcwQ+355qLmXNIk459WkQQrFkzpe95xQaMh1zIH4fVqslmmF5F2WGTEQgOOLq0u2fiiZswu+ZpvAdAg1Z/NfR3yUcc2dIfWPvU5hwCPF8X8ETp1RIxiwKs7hXi+ssQ2RRQrxQ1oEpNXVBMmkoQ8qtH9d1pbD3WUNhspbQx0AQyZ6twRAkHYknNK+H5AgpbJJJgk7WUmbOE49gx9pVqB+bRUfW8Z/n94ick8K1gIFqGnNnBycwCtqizP89OCTDX1AJgYV3ZdcHe6aE67wXDBlR9C0eyQxpUl1Jmrze5X/kP4zqPHeJgSxTjBVYuwSAS8O2DcXzhBJuXjuikLZXDJmt/vYM7Opa/Oajx6F9aB3unpfDBF8oIQb1YGoNf2UYuiRW8zkIMLjZxf0AsQxZQm4hwD/AXAs7RgzBy1MPxRLf2tBMrSHzC3IrhQl7rGXI1FOjpd7ATReMwE9xC/KMGt5VSF5TRVlUmCyWop0Ty4oaMiL0Qfs9XADU4QiZoCivISudITu29Vjkcjk0NTXxfe1Wmx7oNGTHHMtryDitZBk0ZEkSQkOQrkkMGds3VutB9ZLLcmjI4sDW1D12Sfh7yIE9oHCQHbEYfxtdxwk4iL8q2IOH7RM7gwxXJgr4cfR/M+/vslJ4I5mBMiDJOkKIw6fbR1jEKSHCA0sKbqCriw85rdKQsQhyKpkc0caMrZ96gsuhBSOcP64rJ/M1GOERBRWYB5nQPG3iPNTWdqGmphsTJnqBblQaMu0+JAwxO56quRuaoMZ8GzMMd87UVQJD5gqSX/GtIw2ZyEix31n/7SQNmSPWw2vIfPYSAK8RpkIy5t5qyFjBW8iQATikysFH6roBIoaK9/Bo1TvYFvgxEZeXTSiiLI6tOQilIvpsUe2Bhizp+BiXa5MvGsK8SSDWhxGPEa5x8pj16APYvGQhTlkxPOqLcOZqZ2UJ6Vq0wjy/70ksJOALV0WIa42Z5qZCYKY+n9Wt19W1oa6uLbZnqSFFbhTncYmMQNI2rhxvUbghl3EM/gxnhUQ2IRwdofum3P5qGDApy6AxwhdW8EKBbIc6mTSlDpAghN96whlYN24sGmpN3HQUIyRhXnnFxLGwFecPqyFziZG4fgYSFYasnxEn6WClyzrJNqU2yKtX4d2Dx4MSglX+3JINmwTBd5zJIrN56DRkOmLk7eNrQQ2CLjIUixE5fIrSGcCLxJgMuYwRo50TITKOFLyWK62GzKUAXJcjBG2FpFy5rQqbr8j0mQozJgCgOxepr2sYsq1C8k+O+N4Lm4yoIYsTNnCSZxDpcAj+yiqqKDUxdKyGjLlZ0x5FR+jaFfl3vF2f5dYBod6xrjrwAfBpgDgNmfedi64+vw4AuOx8UAgyxCuehkz3lqImJI1/g37E1GZrcQwZn8DWTCCoI4aMPbhlE05TYHICTaIYZZFSyu9VlF/zjoIhyzBMcKYq579Heg2ZOH5cTi4VQxZoyGKorEBS3dgdmZPpNWQ+AeuyxJSoIXN5zScFQAyJYOVMfmK+HTvPHRhwhSTy/D5rcCbLnFmga3PjmnUNvG/dcNTlfJMzbQ8EiESWPxY/GV/AecPzaOy8U/lYh5HDS1VL/LZ4DZkqyqKVQCiqvlB07DFzKnzn+H3aVXwD0WQxreyNnW/jmyJ/dZHWkGZlVwMw9w7QdjliIaCel2xb1N+ttmMSI6RK0WkFQyZpYllrFYXArBSTxZNPmY6TT5kOe4g6R5wKFEh51vLfseTTuRcCVokFVGnIDIPj7zmBom+yGIy5mrklPENGDJhMHXEmi5zNBTfpHM5aTAV2b9rO+KmxGrKG4fVYMdFzF2CnQYYRkDsluuLsbQzu3u0H6I2GjDvgrS7AkvP5qD8ce7gC1O2JlhRnURD9YULNCOo0ZOzZUGDielGlhkzD7A2fjOwRZwPZWuX92vp4gpbvp7CQae9MFh2YkoZM7UMmPi//LWrpqOaQcJVmqlRrsjhm7Fj+MmeymH4Dz2bz3N/hYZlQhWmY3EYXpyHjJc9yoIeAcFVpelVajd6CncX1jSeGv3saornnEP67EhA4omkG0yeXk/yx2hivFjfRZJH1U5HXiDgkBgBXp6wRBjZtDiYdVCaLsT5kIkOWqCHz+mcoidWorVI0ZPxeJWrI5IFzBbM071+eMAf0Qqm4tUYVqsxAQ6aTOPfUjMGHMQmn5TN4nskdpeOtqT/GBlXPT8DTkJmMJqSzvc3XkPF1sd8hTkPG21cYoIIfHW/gasBmNaCcDxmfjHl4VxXev24Ezp7nRUklTg5WbhYcS5FviQWzz1Mj0pAF6Oh+Mf55QNKQiVEWRwzfg83jquTnEqAyKQw0B0nbtKuYc9RQn2Exs9D/P6+hCCDuERIF8PBXgBd+ATz0RfGO18dEHzKKZ/BZ/JLchL/j/3Hl1MI2fw0qNWRCgCNGUsOZhMaYLCYxg7lD0zNkQY0iREawr+JR6lLUEOCwKgM1aaUUorZZx5BpNGSeySLCziv3K8ozZI5BONNGl8hmyOGj7G9hT1B+ewashp6NWSO2tXv4EIgwWR+yCkP23ka8LTBD5LksQ8YSB64kIQOSTRYBoNBxb6Qhc1kiMIWGTLNAVCZagJrpcDXvXv+xq1Bz/OdR876vKu8ffHSkyZjyobOiG4p1LpksJthR6xhkm5iAyxOUgcklryFLHnhXIFZ0B4JKm0GIKx/K/gFaKPLO2NzzJfiQGZKjdSARi4dJTN5XJGW0Igr5wAqCLaiiLJZsshjTcXYWE9fEOzgTc3CGv6Z8IonwGrzA401nssiCPSgoDH+9KTrEvD8f1COlySIvUWF+l64hi9uSQuaI0xTEVCYwZIYiyiLfdrzJYrB+OYZNYMhEbRYRfMh43xJ5H+MY4qA9RWJorYYshqpWCxMCHzL1t15+/HcwmtThrHyWW8bas8PvFu+QL2rIgOFWW/j3lncX+A/qNWSlmCzSOOuHwGRRMZdEH7KgzIhuLwiHvf15OPm5sLoe09cPfu8Rg3qkh7wzs2tzwgHq3IZJcBUMkZu4u3pwFJoCYqr3a50lAQn/ZfY0jgDm9whpx9ixwPu3UZOWRTH/RTriUeKd7W+TjyvrUEJFLPe0cX+yPmRKDZnqrNUtY9GMtESrQh5JdIGoMUtozKU4fUgGU+tMnFavChSU3IbKB8w1DJjMp2LPc5t4FQcuF0ofMgj7KyGcyaLehyw6b72CzB3XAo1hyKjQF5vbPoS4BaY8D7JM0C+XGL3yz9tbqDBk/YzYKIuGLsoiq+miakYkwWTRu5CL6ECOwOq9D5koKY3aLt2HLDvpVPXGwkRuq66L15bJ/eydhsz2NWQsreAoGTIBKoZCkOrpNGRieHOvLVfWkPmEnGXxkk1uzEvYZCSzqpRmHgYx+O8foyHjylHZZDGQ6Ks1ZOI3je9f3F223aW143ELuQx/Iz/DtiGHc9I1dh0QX6OndBoHv5RELUWS1Brgg1gQ0T8EMr1vEMoLP6nyp193MmFKY5g2WqIEkdOkUQcZM57QCDRknAaMM1kMNGTRJVeIsij6exkxGjJVlEXOZNSQGbJEHzJh0Nk9RWmymKAh6xrC5oFk+qlheoLhMmNMFg2B93L2rARm/hniDsazz+lMFl0YQD2vBRbZPM6XRGDI4uC0qfOOiaAuH9RjVncBH9qtzz+lBHHBnbWCD1krRmL6CWfg7kP1WjJVYujgs3EMWaghi9/LVBoyOfJR0n6oYJjYuSD5kJVGoGp9GwPECnD0F1UCkCDNT1iSkxOpTRapQzE8x1uTqKASnmSdahzZeEr8gymiLConhgAHQFFzj7oUw/1NcGSmd2S6ijl1COGjLArMlGey6AukNH5qvEaMN4GMjbKo05o7Vhi4Tv0c36bNBXZJHmfTrWjIKvARa7LIRm5jnZRFfy/FnFNryOSCx20e5tfJXo3+EMPehzXpTBY5pQwjVVaZLKbKQ6a4ZrIhi+MXnOxDFq8hizVZdPkocelMFsUOyZojrYZMEdCEEJXJorehjBknmCyyZq6Jh6ROmkoRzoeEKmQNmZNK2kRBpGACwdwxVVI8MRxyr0IZw68/+j2/PkquvGHIMXwb3O/gL7WmhV+ePNOmP4fVGjK1yaJI3urPd3GupNGQuX4kLdW3U/mwxIEQNiWHC0P1PDtnFBoylgiloQ8Zq10ww3FKMlmkoDzBoPTpYq0FZG1YsGf3xmSxSBVm2CETkkJ7yfVTs28oNWRiUA/KM+6a72pwgoY4hkwcUzHaAl8rp+kTmHYWcW3Ggtk7c3V1WG85mJCbUGol8ngzc+NufBc7Ro7DrUdVI1eCFbXKZFHSxuieVTJk/J/RvChh7Jh2xYjOpeoWk7eY3u3XyvkumADrggZFDJkL16L40pIrEvsTCmv8b04BfGTjF/GJ9V8rqd8AkB0hzGvhvqgRI6D43MQJ+MRBE9UVliONTQofMl7QAl9DFsOQCSaLtsAscVMjZm2zVTuOFRvVW4TFMeXJayBrC/6mgxiVsPf9jFiClSFm2JxSHsEW2DVTJUFa8rTS5FfRB/UIFojA0JAC4EdXjIhUqtQCpQl7r/Iv0kMuKRFNJJ4hizVZpGlMFpP7FW+yGBEzapNFvQ/Zhg0bweoLe60h6+Vebxp82Ox4YQNTjhJpb47zE5PNOXqvIWNbYevVzXtAvcnrNGRE1JDpQqUTkaANKkhhskgELSsraRTKptGQWZ0daB32Kgi1MKRnBJj8tbG5qFTgfMjgKAUWhKFz1UE9ZPUfS3c5fth773k5qId4mCcF9WDNx4L+lmSyWJrCgtGQpWDIWEZVs38SlQ8ZEd+TctphSqqVXU1tsigEr7EdnWzfm0Pcm7JRFiUhTt8Zsl5Dyh3FJ4Zei0hoUzAIalMFqVKz3YHGMEmApdKQEY2JeVxNp7YtxAkdy6I6YjVkaujM6krxVw7bTGNTr6xWEM5xDBkjPA3WOaFY8O5sTMEXUvTJ5NqlAI5siteO6UbeHCJ+I9FEUcaGqhjNa9IYpzjEdSaLjLU+54LiEAAu4DqBn69iLxfqFU0WHe0eIhIAvIaMxmnIhGdt9vjUCZqZPmYEk8VKlMUBxKuvvoqPf/zjGD58OIYOHYqTTz4Z//rXv6RyzzzzDE466STU1NTgoIMOwm9/+1vYdt8c5IH4DZiNEMMS8ZyJB6jynEyKsij3g/0raqvUKItWTSNTi+HXIWumgHRh7/kIZcrOxkLS5PUyqEfgQ8ZK+FUaMnX+N6Y9IAzJHGh/eGaVJZzUJos6H7L3v//93GWnlz5k4kEbBfWIJ448DRnzXCxDxhCDkPOQBdJJ1aEvEtEqLVJahIcH5evV1Tly5A6879B3McLkzZl4JooldNm1SvpFQ2YiTkPG/y0SWyosffc1OPXVsIcMwbDcHqG+JJNDYf5zzJFG2849LzNkXIoEf2wzpQT14LpMtaamAaptxgyK6H3I9GHvSz3Q0zNknGZJxwAoiCnRZBEUmMCoId3aI8LrLIyUYe+J4DvsOnwORX4dG14IbQRMSHTHFQUGveTHqNP3s5lATgzNhejnW1T3Q3HNDoNusHM43YsqGTIxNUbC+ZiBg9Nb56HOyYXX2O+cGGUxAclWESrNuzwmAawYHZ1oAswJY9j6GR+yNV07EvrH1x0X/VT9oEpzJNSRKKRJmA8xzH/a3adkDVkgNIgxWawfvVGKssidkzGvxZ2V7J7gWJxgT/ks89vmBOTJrjWZfchkcb/WkN1zzz341re+hU9+8pO47rrrYJom1qxZg23b+AhOL7zwAi666CJ89KMfxd/+9jcsW7YM1157LRoaGnDbbbf1qQ9xWgSWEOFDmLObjluCySIPAoKe6hoQSsEmIU6jIdP6kCn8MzyTKrmedImhvX/epqdi2cgDcUhxLQ4oIcuxqM2ggjTREOrSmyxmIAb1SGWyqKguJOjgkWI8gc1sXqk1ZN6G8vaMGRjPWoiVYrLItyL8Sb33SMOQscSu66RinimFwmRRvwGXarIYd5f9/pyeUqOZOn7q6wCAr7rALuY6pyHT0enKoB4+g2ENi65wTmgKhkwkmklE0EhlhbmShiErUDvsoitsJEofFrY9l4JwETlYRtPxcs4Jz3BMfBhlkblmyMwuq4tlNWQqhowbL5qsIZvaviJqThEwKYngLFnAGkRyTGXem6IfCh8y0WQRcGEye3JBYxLE7Z8pNWQUBty4aJ6hhkw1tvGahNRIqZ2PhZ9snAN39oraGMX3UHRftRUHZ33SDFAF9RCtPmgMcwMAhxs7YSnv+G2kZsg05oFlMKdjscUMhLyqetMR0KwPmSFu0Jq9M9KQRSaLvYbopiAdEiXOc5eihXShjXTjEJd3VaAgqVwFVBoyR8glyps9+03HMGRmVY6jAUSNGOtDFttDVkDgFhPzkLHDl0ZDxkIKe5/CimSgsN8yZJs3b8YPfvAD/PCHP8RNN90UW/bnP/85TjjhBLz88svIZLwhGTZsGK677jr8+Mc/xpQpU3rdj9igHszws5skJ7VThXGl6m1K3KBztUNwx8U/AaEU1276HzAkIdOHBIZMot1l6bNHMKo0ZClMdHyRypz643DyCc8CAHaunMU0WOqB3TeTRZWGLNlkkUcgYcpQCosQYWzY4AEqhkwR1MMnfj728Y9j5duvR5fZdy3lkBSK5kauRnXnIYlSO4MYqTRklPI1uQoNWVwkxXIyZME2T0A46Z0R+A5R72wQ66gRlZRMn/j+sFLwyGRxIw5HBlZ4O2NHdoFsUAnZHEkmkEQfMoH/CDGkMBJrbnbRffC7OP/7J0j1Mo1qbyWZLLou1aeMoZrwAJQi0pZ478tqwHgtY+BDxrQpBPWQQtRzQTVEHzJVhDJ2PSuCqiTsW5KPKLsmYpZQnIbMJTYMmuGl/gkaMjasvU2EIBuui6wjnylijb3JQ+bCgONY0O2GFCZPqHH8u2Cy2FsfsrIQVQphHUdIq7UxibXG+HglEdIqCb60RyTUEWeODchCG7sE7R+g1tz2wc1XsgjgERfgSbZgIISm8isCWB8yueZ4KGgyRwy4JVqh8H8n+aJbRQtPVs8FAJxhHQVgeHjPJUTjx8fXqWKoHNMUwt6zzJVff0D3aIKXsN/aJfy78UE9ROKRjcjL1OEUQeN8yIRquCiLWg1Z1EBG8iEbvAzZ4Nbf9QG33347HMfB1VdfDQDo6upSboYrV67EypUr8d3vfjdkxgDg+9//PiilePzxx/vUj3gfMrWGjDNZVCaOJcpgCLbAXy894WRY2WoUq2owc0xkG50mSII27L2CITOhZsjS+ZB5/44YuTu8lq/fzPQ14XlQYXMSGDKhD3oNmQG4NhclTpkYOmnsCMKwsYyHHVMg+ub5vFpDJmkp/M1+5qxZ3GWOoStFbC+M6faT/4yNZ16erCEz+KAeruMq2/UusZoTOaiHSnOhu9cXk8WMYO8eICBa4qvmtTTRZfVDgYZsefYwXEX+hCvIjdhaf6BcjkkqJpkjQZ6jJqEcM0k1zMyHNn0OdgeweVkzWnf1cHW0kC4sNjchhyJ3botfT60hY75lzHipooYCag0ZZ5LImiz61AInGBF8yFTmhWxXkzRkghOgX290KdE3stf+S+p6c7W70DzuHXQN2cibLOq64Y+X6bAMmexDlmW0WLqq+LipcQwZv+87bpwORm8ElhRlkSsbd0/5DUrkCki8ySJXs2ZoVC06Mf1I2qbVJos6czjd90pg+vposshryCgkdiPmjFSOY6ChUqw7mjInJRvUw3DltaB+RkxGnlI4oDRZFK4lfOck4Wd3d5R79t3MFv5ZQlJZxCgZMsPkE0OrQtaHFj6qNlzed5WCs3CIM1mEUR/95qIs2iCxPmT8eMXlIVOhkhh6EODVV1/FlClT8Pzzz2PSpEkYOnQoRo8ejauuuoo7cBcvXgwAOOUU3pnzwAMPxKRJk8L7OjQ0NGDFihXcf+vXR/lL4g/3aOPQRllU2WNTtVxADPGcmRDVWT2yLbrB+sBoJrSOIeMPZq+MF3Sgdz5k0WnAEFEpQsaGoFSOSgn2zxI0ZK7D+baoGErlJiX0NzhYAuZVx5Cp+kKIGyZ+jQp6hNXpp5/OX2aO0hKsPPn2guczhcTNLUMyvOZLk/tHHCEKeaMJ5o7qU5ceZTHO1IqGJYrsHPVN9SLfivh3Z30ZVEwUEDFktw6NEqo+dPhFcl1cHjIVEcLD05Axa5ZjyKJy9cVIilos8BLbJ6vnYmF2I16rWgYelHv1pChUIiHAzu3AZFEEz5D5OW7YNlUmi6KGLM5kURgxVmjkUJWGjGkuHH/2PSj3rwjZ1DgdI6DTkHUNXwcQIDdkO2eaqjUN818/KaiHqKVWV8XZ/+i6LqR3MOAKDBkXnZMYvqScSNWKVgHliLLYeyiEdZzJYoRm0pm61ijsfelQEoy+hkycqVoNVpIWTox0qSuoOYeDT1hLKK6YkMePxhWU5UqFqHnzd2j+GidMYr9VYNGjMFnUIDhn+qDcYyoTx1TUkJWGnnb9mLqGodaeC59LdNfwniXaPGSBdosmashYGlConxMcio8y34s17nGseA2Z8GIuJyBPlpRkHFFDVpYv3i/YbxmydevWYdu2bfjP//xPfPOb38Tjjz+O8847D9deey1+/etfh+V27fI8RQ444ACpjgMOOAA7d+6MbefWW2/F8ccfz/130UUXhfdXr16NG264AS0tLfjGN77BTa233p4Z/t6+cztzh5m4quT1lCjlRqI0mCXs2cXJaxw0B7XGZFGlIdMF9ZgxcxbmzZuHa665Bj09PfjiF78oHRaUEjz00ENcM3krquvFF19K6qrAjNi44YYbmEf49t555x0AwKWXXspdL2YPxsL5czkm6fJf/goA8PDDD2vre/bZZ6X+dHV1AYjsganGxG3GO29LzxLiSkRxZ0cbbrjhBsyfv4C77rB+HG5ARPZem9TT1c39fcEFFwAArrzySixbtgzLly0XNGQ2vvZVPrn3Nddcg3nz5vHEICXaxNBqCXOyhqylpSX8Hbe9Llv6blAL8mDGy6f4jRjiiXfKZ00WGeGJoMmhhMAi8ZbgLo1n7igowGjRPIEH8zxnvshqmqK6Xn7xZWXbu4222AGjhoFN4/T9v/POO7Fjx45w/Vzxq1+G9yyrgKeeelJ6hhMvUQeXXXYZujs6mH4bUuF3GUGYg8h3cf369Xj++eeZ+ih++5vfRH+DcnudTeV3oS57oHv1tra2hddm+Zrov/zlL9KzAJDv4deJMjCRAqmiLDK/i0V1JMPAJM5kAkGJc+6F559XeDLKhGJaHzLW0sBBBjNmvsX3iduzDDgg+OdDj2P16tWc5sN1bfz973/neqBFDGOh1pCVCMKb2E6bNo3rDztWz1cvSV1tc2ur9HyAJDN+RyEIDfaIYPfqdMbE1pEkWFu3YR0eeughPPTQQ1i2bFnJBlyuS/HpCy7A2cMtjM9SHFbtIjPCwFtveXNC0roLvZPhC1uEB33jZe5aPp8XngrKRiaLU8hojD/pAeycejso0Rlk+n7jTEVpyPT/9/3vK0uuWZ0uf15avHbvSu09z2QxeS9R+pAZZqIPWUA/qRgyYjjc9TXr1/Mmi5q+UAKAAsuWLcNDDz3ECdFtu4C7772XKx/QEU899ZTu9bz+KObT9u3bwSeGZoN6EKxevTq2zoHEPsGQua6LfD6f6r+A4O/q6kJrayt+//vf4+qrr8bnPvc5PPjggzj33HNx0003obPTk3jlcl4kourqaqndmpqa8L4O3//+97F8+XLuP29j93DkkUfi8ssvx6hRo3Dvvfdykt8Pn/XR8Pf48ePD35wE3YS0/vUmi/zm5TJSB87qIYUJmC4vBOfQGWrIqNJk8dTTPoDTTjsNV111Ferq6vDoo48qVfsXX3wxpIs+zj33nNh+UgqIJkiXX365tnygZbr99tu5McwfeBlOmHIGqrMRYXPtH64DAHz5y18Or4kask9/+tNSG7U13lwyVRoyhsM+44O8xgvwDhRRQza0rhqXX345jjjqKO17heOqJVQ00k7md30tn0Np+jPPAACuu+46TJ06Fe8/8f28tsO2cf9993HPXHXVVTjl1FO5ay4MGIJkLc5kMY2GbNSoUdrnWRx//LFRvUw9Af1IYmws2FY57bMiEAcQachU78bWlRxlESBMGVPoO+XM/Zj2GYbsE5/4N2Uf/UbFC9xfD3xsmJY4+cYll2DixIm4/fbbAQDXX//HqJ8mcNFFn5Wb4wJ/2LjxxhsxesSIqN8KrcCpJ50c3WdMFg855JBQUAB4Z8Pvf/97bXuOyk2a2y+88R8xPNIufuADHwAA/OQnP5GfBVBVlVVeT0IahoyFaagZYyPrJ1V39SaL5557Lve3Lr9cWh8yUUP2wdOFNc7uWcTE8at/hc3ZI/DII48IPrguvv3tbzNltU3GQk2Qlir5plwHLrzwQq4/YlAPla+TSok0bPgIbYvKPH0MVEE9gj0iiC5HwwAhfF3zjqzGugOyyBtx5qTAQQcfhIsvvhgXX3wxpk6d2quw99OfeQb1BrufEpx11lnhkyx4AZIeYroYVZLhmuoa5bNOyJC5mDiiAyOPeAudB8xB2+TXta0G54xFahP7FuDWW25VXj/yyCO4v+Wui4KQ+NaMmIXhEo2GTGpRwZCZJkf+8SaLXps/+9nP/HsKhozwqU0OPvwI7tUcgyDUjCvYi2OPOxYXX3wxJ0R3bAvf/M53uHJXXXUVTjvtNHz2s/J5wvXHbyM/bhJ6Jh8Japg44EBeucKaLLrE6FNMiP7GPsGQvf3226itrU3135o1awAAtT5x+ZWvfIWr6ytf+QpyuVxoihiUKxRkFXE+nw/v6zBu3Dgcd9xx3H9HHBEtTtEsjU94GoFN1shHYZPbpCk1ZCzhxUs7qOIXj4AYkEg3rQ+ZzAjYtoI5EB3iVQSxzlRCI11jF7doby8+w34PU1DX9+yexPmQWY58VEk9oFS6GhALoQ8ZZyLK+g2qNjwqm435hJcjBRNg/Q75sr0BSZC6iVEWHSv+4GdhgCLDvG4wV3urIWMRezT540HEkv43SWuyyIfMjzdZlP15hHJsUA+FhsybF4yGDPyS4OY0Z77IaiLSEqfqcpbGpt+Swo2zzJYbkrjjag7GhQf9F04YeZbSZJEzSVSMV4Zp3oHJmSzGvQIl/B6l1JCx0yDoHNdHyv0rPy+MAVef8hHvXokaMu039BthpdtiUA9Qlx93TXtpw96zbbkw4QpjIO5Z9Xl1wlsKcf7ErTv9HE4TTTSpTkLkxND8EPDmi3ZKb6vIh0x+t6RVqfTh9Nd18MbR+ufrf+mkejzykaFor4kXGPQ1MTQAKZpq3Fe047fWcExEJsNW0T7cX7x1gneFoiYTCdEL9bugQ8DErR1eIoGu2hektUqFv0QTxvhBibvrEpKOIVOFvScGb7Ko0JAhxmTRO4tFGpb5DgnfuhjQDGyURbsQH2Uxbk8lBG5VNazRE+AMGY7C+ElwKM80clrAEhJQDwT2iSiLU6ZMwT333JOqbGB6eOCBB2LdunWc5gnwGCgAaPXNCoLyu3btwuTJk7myu3btwmmnndanvosEhCf58CYL6yvFluNyoWhMFjMqdbRIyDK/dVJ5vQ+ZRjqrYsgIlD5kliqPG6XYYjRiXmY93m8firFyiZJBFRJvfdmo/2wuN5t4po9cYmhVNKkUcjTXcYBslJpA60MmEnaA2ofMz/nTzph5SfUG71Vi9DG2JZVEjIUYZdG1bSXRSqm8mRuEwnQjh9xAc6FqUYyM15egHgHTSkTjBv8PRdRzuZDQJ5bpV5osJjiiU8YcUZUYmgIgrhmufYMALtNRTivGPMdqqbU5rMIGmN8K6JyfLUsf7pxlVN4/6uOoMetxzIjTsZXeEvXRT7+hi7IYICOMa7DuVImheRBuHqsYMq50wOgxA5EYZVGzxkZNeQFVY9cD+K26rRLXJnU0u7Mi7L0oBJCimgbaFamqdGQ1ZwaKjBT2XtTAvXDSUJy6w6+RFUgJURarqnMYMrELXTvrJUI3bq+1OeaW4phj30R1dbw1C+BbIITnhRwVNI6h9nx2kwm6WB+yhOND5cMZmiwSomYGBHTU1mJEzH1b/HaJNZYKgbFKZMj8NSi8mvI5LqKqvD9761moKCHsfXeVCRdaOXAqSHtCH+oCeB9bES4hWLG9HZOS6lBGWRTC3rPr2m/TFXzg+UrFCJ3CGRjTb4MQFC0LtdU1nCDesYvIQC9E8PJ76iomoIwlgVNd681vQUgXQGcpMFiwTzBkEyZMwCWXXFLSMyeffDLWrVuHHTt24LDDDguvBz5hY8d6rMCJJ54IAFiwYAHHfO3cuRPbt2/Hd7/73T71XdaQRb/ZaExc2HuWYDPlPdwF4bQNUX16hoz9K1WUxfCA58seNGkpZuN4vx++ySKgNFm0FUEfKKV4pWopAODNqhX4oOIMLUVtSynlKdSkEOnMJpOlFEHzNiGAC5gZhiFLGdRDXOKuL70NgljrEkNTOCAmP25qDZl3gB511FFYtX0T/y4CYU1dW30WpNiHkphNSgWHXstSEhgq0x4DlMud11eTRa49lZIV/isz6yrLMlU+GWK4akJVBGeyqNWQmaBE0PiopJRpfMgoqyGjvIZMFzK+NxoyzbxwNYtQJOZ4DZkdRU2tHhc1wRJRriLKooL5Y+/byHB5yESGjAssAn6NKueZKmoqK2hIYMjEgBYAQMwCxp3wJKyYIzWNhoz9HK6riTHnU2tslMUgqMfmrhEwCQV1Xe2c4dtLGdSDlTLDDBnrsK/CnrXoiDpM7hyFAzpauOsi4XrqB6bBMFxsnzUepUQmchjrhREjdmHMmO0xpSMQ4kbCScJKJmQNmaiJdhSsi1KgFOf7lrDTOArNdKCRFxmUtDpwEfIa1kE/HygAw2HHDsq9DgAcLpNATJ2CEMlLnZDuLVmTRQKC+fgA2jACnxMyshnUCfdnNg+ZhWyvx9PvfPxt4e80gt2orKBdIwaueGIp7jeHxraijbLIXDdcdg/x/o0YMoWFkGCB5HgdlOpQodasgmV734ML6mEXQVGveSoesg8ZUQStYZg/w0gl1Bgo7BMmi73Bl770JQDAXXfdFV5zXRf33HMPRo0ahZNP9nwUjjvuOEyZMgV33nknHOaAu+2220AIwec///k+9cMRmBIuuhirIWMj5rGHhEZDpmIMRB8yFtwc5CKLySvIBeO/INyuqYrCaTsJGjJbYfKny+HD65BYzWHy4uFMFsV+CP1niS128juG15ksQxwGDtgsE6faSCVjhXBDC+6zRCuzOdAijrl4E/dsXB6yWX5AkrAs23CCD1maLShJQybleLLVJovK4ExEbbKoOvNlhoyXhsv9khGOQpjkUjzcqX89bEVRr05Dph5jB4bEyJiKQ41yechU9ylHKJtE9CGD8jdrNhwfFpllYKhSiKGTJFrCN+fnthzxEIBgsugnhk4wWTRFDVkMQ8ZJzQnP+Dg03nwrGH+218kaMiHnEKXhnIgzRSqZIdNpOUMNWfS9LSODdeZYLDh6JJ53DkdX4x6utlBmJVTZuzxkJh9QCGqmuqPWI7J4Sw3hPPQJvEkf2iMxZHFEq8XMb9NMy2CI6002WWS3HnG3UGbZUwxZpCFT7ClJGjKVZtofo0DUFqx53Vwj1MWGg47G7JM+Ckth6ZKWIYuby5RSjO6sCv8u9NRFZ4/wmJ2glQjaEZedymQxTFoMYc0yGrJmYyT+Qn6Bf5Lv4s063u+azdEWRvoF8awbYnsZ9BVqIZvrYsSIXTj4kMXIZAqKuSswVcq5wdIZeriEIJOit2qGjDdZ5M2e/e/g6DVkxOCTOjgAWDeMOG0oBVAseIGKuKAeThG9FS8QhUbZcR3t3pEURXigsU9oyHqDCy+8EJ/4xCdw/fXXo6mpCe973/swbdo0zJw5E3fccQcXxOOGG27AZz7zGZx99tn48pe/jOXLl+Pmm2/Gt7/9bRxzzDF96oekIWMPSZZA1YW9N6g0Vx1KlB9O1pBpNmziIo4XdwlgaGxtDcbiPPIho3ySYh8qDZm06zK9jeC9sF0/DHN3NsIYcyCqmzTRLil4PzRNwIWoecaHTDJZJIkmi3GmBAAAEmnIgvp1iaE76RJU1fGR1JR5yPwD9PxPfRpznogiPvLEcPBDw5BpErWykyvefE+GazvQb6SCtA7U99nzGi8tDxnPECfZ3wOepC5DBQKQE0p4/xgxdiocQUaM8ILOhNJBRiJqq1w5Uh4XtEepIfNMFsMiEJkwhojmiG6G2IgxWayiESFVlxkKldGSY6j3GNmHjOkXVTPoPEMmmyyqDkk+7L0ZaiWVDBnXGG+yKIeDl+eTVxHTnkIQw8Itg/+SDnzidXV5EmjIBJPFtQePwshJzRhyYA8a1q4BEPlxaU3TNf6IUjm2LZigcWHvgzZV9SnMtMM6/HGtz4xAt90Wux85LIMo5Z3Sg1u7giAi3oeMwCGu9AlV4xqXhyxpCqiDeqg1ZDq49TaePPNr3jOZDD4871W+jbIk1RbXNQnPKfElbc5FQgXvqjjfVe+rW3vB/kyIi91VE8Lrs2sPw2cRCZFNOLB987hIQxYIs9NqaBVv4bqYeoI3znW1HWhrmyCXSYALF2boC6f/Ri4xYKboq9pkUchDpvAhC9J6KH3IhHe3KH82OXHMN6GwCr5NEkOzuTFnSgDdslHRuKKPJLuoK3nIBgiEEEybNg0/+tGP8Mwzz+Cyyy7D7t278cADD0hmiJ/+9Kfx5JNPoqWlBT/84Q/x5JNP4sorr8Qtt9yiqT09xEOdT3gaoRw+ZLEaMo3Jomqi28RLAqyCSsKkzUOmDOqRnurPHXQUbJeiOFZOrhuAgs9DJhLLkjOtYLIY9tUXufGJoVXSflX/hYPdlzAFGiGecWJ8yKAwfRJ8yChFeNCx4fe9ey74gghNwkTonVmZsZMiYArvJbynbiNVa8ggmCzG+ZDpNWQqzbBaQxaIkaNnucMkYMhcvo5HcTF+i+vQGOfdyDBRfMhfQzKfVJl98P6cGoaMDepBRGmwWqvBpp6I0yxXuRFDVp8ZBpXfpU5DZot+oVwERSfs6LY6gscmZ9GV4eeVS9kgK/41xSGZ5UwWIzGWSnvFzjeXED6oh5vOh4xyBH7vfMj8GjXPpNv3WAJDH9TD+4cnpkzUTGoGAGRrHYlwjb5nHMGkJwdEk0UHYv3ys2pTYtaHTCDAHRtHDjsJn578PZw25nxlJOGwLFWfl0ngzZ/57GyeZprtKy/EUgkdVXDCfqu07vHzQEUwcj5k/B1lHVZ91MbqKVOl+6KGLCWfx4FCoVjXrAs7QUgKeHuEuO6UGjJu/5F7Lpq3iwwEm7LcYTRkdh91E+z+MWbsVpnZTzHK/Hmu94dMrSFTlHENk9eQKRJDuz7dpjZZtHkGx28p/JswfwnzlQKwil7aAnZpO04xdn888KhjtfcMxb5j2UWFeN+DS4xUKQMGCvuthgwAhgwZgr/85S/afDIsLrroIi5/WLkgmixyPmTMTNFGWdTlIVPM3zgfMu53sEES9UbhsgxZzD4StKeLsii+OwA52ACFRMGXekBw+0aCv5EuyqJtEFBbDOohS8oNsX7FyRQmv1VtmiyzTV3pZSWTRYowqMdXv/Y1zPrX/ULjwYv5v3USxBSSobhQu15/BYbMstTcF+RvSKnIkOnzkEkMmcEzZGnku2FEsjDKIuG/k/87SlZJYBkGniYXAQBupz/El/GAsm6OiRI0OVIyTBUDmeBD5ql9o4pM8MIbnckiOzJxGjLHpRg3bqOnWeg8XM2QGeojzY7RDrGmfJ/98BAAwNujHVzJaX0socZkHzI2yqI6qIcg9EqZXgFg5hYn7Y/fQ2STRYDSglgNAI/kN0D9PSF5Z+MYVd039AtxJouCJtB1HN78LjRz0yNt2HsXpjQGKga+pi4IQsQzQTpYjoWTRn8SAHDo0KlArlVb1uGY1fRCvuB7e0YiiudiTCBUPmSmonjQNaXoLqGrSpOqIOw9or0qDtV1URJrMyv32VL4QKqQxERw0fps6DVkpgMpuKYAAiq5EKp8yFxHLQwL6yEuL6AV+6yw8AGQ2mTRa1ilIeP3xWRDGpVgkT3n9DW4BimltxzEPGRslMWAAQ4sm9R5yPgPaQMc48Uy0SKzREEjhozTkBVj5fSZ6hqIIxpn4+UxZLLwFfAEHnE+ngON/ZohGwyIC3vPnreuRuKn1JDBUC7IOA0Zb5mSYNZHAKJNbstKrr0yno9LSpNFlR9FH5IZe9QQswGXZLIYwSYAXIIMcyBbKg2ZqA2TvgMND41AQ8ZKvfmw97aCIeNNFikFiH/QPf300+BSgjLvHQ6hRkrJm26piRmiYBDj4Dq28nDSSYFVGjIV4kwWg5ERpdlS3/yIZKw2g+PH/D6yJovsuG/FwVqCRDfHHJKBSwjq3G70GJ7/zHCrUyrHJyZWSCFBQJiFL9KIaYJ6xPmQkdEbcPQUL/nx9ubhyj7oNWTi/OI1ZGKrs8fXg7QxpRUma1RpssgyZJnwe7muyzFMUqJ5QUMWN8+AaPw5liHJZFH1DrQLLgx0YwhfFgYMOL6pZmkMma79YLjYxNCiaaYXEITVxqdZ2PoynNYRJpyEsPeAmtHmv79IbPPzsFUldfTBBcRy0ueFM/zvbToEtsEz8x6zz/wt9FTlQzYhqzBZjCP4Eo46bVAPGpnwhWkZ4qvynlWZdJVDQ0aB+ihHMzLdRsiUiEIpi2HItHsqHF8jzNAXKg2riqZg6yGUswInoNzGbyo0ZKAknnZKAVnrItIJ4l2F9pQV/HJlxT1OTf+lmQ+iySJ3z++S4/sJa33ImOfFr8EH9RAYMkJRLPqCK+YMLOS6kjsuDJdNgCrNCwdthO1yZv1KMfmgwX5rsjhYIIe9Z+4xv/U+ZOHFqGxKDZlwvDNXqaaMXw+JfMjiNuswMTSgNFl0FEE9pDxklHgbecIqoYCkAvcr4AlccUYLj7DfgzX7tD36HRk2qEeKPGSqszfKQxavHVHpegihvKTaJeFB97GPfVTflzA6ioaI1JgsdmMI/oDf4Q78IFEiKpksqtIaaLtAkGGYhNBcRCVhljS97EHl/bYYaYaquXBkw7D3QsnA7IuRZqfeqIleSksJ8In82+HfB3XvkB5nmXKVD5lBAD7KIg99otV0Jos1YzZGv0fvgSpqpKM5GexYHzIHbODP6Dqr0fKe5xggBTHPBDuFAyNknMT9lFIqm4Vze6WKIVMwxKxZZakmi76W7mpcgx+Sv3O3gnmuisyYBJFBCRHM3Ziw95R0cw7vOu0Xt6ZTR1nMyHnI4pxruVuultEUA4XEmfexe3MpJotNdcPRWV0LU5H/Uo6yyIUHVGrIVEyanC+MayW2fyomlhguCKWhGbZjB9YFmm/Kkg8KwWp6HzL9N6WgoMycKzg1WusMx0xujxBXsp5RMWTBHJF1Z349hiswvcLeoGLI4PtFpmZNlYd+wjPJdXMaspi16BI5D60nF0g+wUSTRRaBSaxjB8LKNBoywu0bvCBPZkptqyjd2rZiXqxVguoeb87K37fyPdqhcAwjDNY2GFHRkPUzJIaMnbysdD5OQ2Z7jurBZHepOlxHbB4ylQ8Z0RCzRJVjPagnQkA466MspvQhk8KUlibD4BNDxz+rzUPmR04wGRuUwCyGl1wJm4zQnKeY8YN6qF6Vi6ypYshcSUMGn5hbtXIVX5YT4SYf9IyhXPhrNs7ESuL5GSwZ3oizZYUO339W2mQ7Gg2Z2iSD00iGPmQqgkZvshj4ANiuiypiSnMnrCOQJofrjyhteA03/gBRQRdlEfAIX0PxXbkynIZMMQdAQFiGjFDegV6bwytdlEV2zL2dROGXRdSbg3JNJ4DLXRcwZOw1BUNmCBqy4HslMUsAb16nDnvPvH9oChndTjZZFBkyFz3VJtYROcGsp6ErehqyFPQe9zW1URa9UqzJopgYmpjd3N+6PGT8Q+mYKgcmXCRryNRg1jKhWI8jsRFH4KN4LSLWwiZjNGTcN0p3XmzA4Xhg6mcASjF53VMA+DHy0oiw1gzMPQIuqEfAELgKiVJkEqUSIMZPArXJogPTSR/UI2milUNDBvB7T49drzVZtHiVlQKeVlvKQ9YrHzIX1Bb9yNnzmzVZ7E2URao+a8XOE6ANI1CHblQpfMW1dUePa+ExZCKjmQ6ShkyRQ8wJTRZVPmT83ucgpbAHBJQAVtGPssicgcVcR+wSJq68E8StBaunh9s7KMcwDu6w9xWGrJ8Rn4eM+R2Thwy2SNSoZ2P6PGQJZn0QtHQM+CAGAUNGlSaLKgmva7vYNPoA7Bo+GidvWRNcBAAUUOVJsJSiL01/JA2ZSFTzz+k0ZA7xNgnOZDFNYmhX1q24oYZM1V+W2VJryNhDmY1eNXLUKDRuYcpyMc9LYciisqtwXPi7oYo3t0qC1mRRw6SxDGpgv29XtwKo5euNC+pBKED9gCtmFrAdpWQzCurBmCxy2gDK/uPfTwc+Uht/jxq8ZD1sk/CHU/hLYT9iBBX5EOcRr11i7zAashgfMj6huNg3D46GwBY1ZJI5jVJ6LGvIWChDfbN9ERJDc1VTKu0XvHldOpNFtpIkk0XJh8x1uMTdLIL2xbxdOnCpODTfMDRZ5BgyYe+nQkj3FAlR05QBfH8bYe9SM2QJjC2A35I/AgCa6WicUshz9/lpKWhPFNruJDyJL/rlCayaYwAsABGEEUSzTj1REE8wUwCFul0AhnF16JYehcuZIqvgmIooi4YL0wWs4PsYQVAezYtzQ6PQLsQwZIVxtUCH6o7QhOodNQGlgqAemUwB4l7v1wYCxwuGlWG0Vor5mBSRjwi55UQBqlJDRn0NWW85U/ACdQDYVTUOv8MvMB678Sf8OJX2jQ3qQTSCAcBba/J7pYNjmBjGxAthawmYHCcM6iF/ZMOwAY4GVEHPoNnFIA8ZewbGyymqXXnOWIZORwrYwj7CJa42jHiT4gFGxWSxnyEF9WA1DMx1Lsoi63MUxtZgmAeqtoNN70NGw0uqjcI2GGI/JkgGa7KoWhyqAAC2U8RLx38ASycfgXeOON4XMzroMuvwX/g7foabYRGFT4CGQHRdl1vNkoaMKMr7YDccmxBPQ6YI6sFC1pApmI8gMbSSWYnqL7h56b4U1MNFGNQjmxGk4Fy9YQVSnQBvssiWyDDSO8sQiVfFu7ImPSVqSzKc7blPqJoyoSqZLCp8yGyHAiSQcMoIbdlDk0WBNBE0ZFTUoLGFpMt6k0VXo3XWQqUhI4KGTLjvcoc1y+ykY8gkZ21FH3QmaLalj7Ko+DPoZPTTTWeyyBZwhMTQfHt8YmiAfz8ngQAOfchYYUFSYmiRDHFsLcEVmua6ViqijC2hM1kM9jjDZfcvr51u1HntSuZ/qhaEuerPK6tHHjNRECdHWdS/m+R3G/hAMZ/9BXwaToGPLBc8N27cBnzg9Me5eyxRlTbJbobR6hE/9LkY0IZopf18UI+g65nxK6WyQd/EXlHDTtwcHMOQqFxCHGSYuBi1VWOV9QcwY9Y+EDFkyrOL9c+M7yrfRwDaKIumizFjN+P0Dz6KQw5drHleoSFTfAqHYci0QT1i1hkb1GMHkxYibZRFVRAhIDrzAzw1/tNwiYldZCK2Y7K6T6Jsl9Pk6eFFWRQtr1TVKwSVpokhMtkBINJIOp16Mxli2hzzZFMofYC99oW/CYUdJIZm8kOOOfgItaAt/C3XbcUMkJXr0c4Al5DUEW8HAhWGrJ8Rd7iz+yanIRN8yCj4gFBpNWQsUcXJ/RRSYa4eEseHqTRk/PWwfQXBblsRAb5+3CS/Gy7eHHUmesgQNJOxeHfYidJzKuktBUBdVzBZ1PXbf4ZZjGzoWNvwxp0NJqAO6iHUpygTEMbB1+CCerDaAsgBBVRBPQLb/O07tvN94ULsJWjIFM7iAJBlGLKixJDFw3UcqVmPQFYTSayGzA7NRRS+hxJDxkdZBHxmOaa/QRADPqgHQ8QFDJlGCh+X7yzJZDGJ8GaZelVdwzPZEoJ6MP1K6UMm3VEG9VCXt205r1oiOA2ZzIDrDvQAST5kHAhvzq1KOs3pPcKNjiUAEjQ7opaPuqAaT/lQQ5bWh4zd57VRFhVCNJLBs7gQ3yX342n8O1yryG3icQwTUzEAIN8a5ejMdcvCMZUPWW/y+3Bm9ADcgjy3XEpw9JR3UFXFU5FOivQp4t7C7kmRD5nIkDHPs/OSgAt7H5RrU0QW0J341IjX7gCeBkOSjxAXGRdMjqeE+cmtXfm7W66FNS1rcMJ9J+Dzz3we/NxP7KIeIVPCVzJvRC2OOWYGCPFDwrOPgMD/+tJ8V5ospgjqwc51N9vJrwOG5H2SfNl/SI6yaGjmlycAlu+J/vKOykpC7KsY9IIhZOJ9yOSgHqkNhqV1ytBzgVFJzPOqKIu68pLPOSiKvoaMjVZnZOTe26wQz5KFWbEmi4Jgh+2FY/Q2PuXeQYUh62dIBATz2/F3znHFUTipOcooz/uQ+dos1unct8f1fjOO3QIhqwuPrTfL8GDptcEcwiiLmvuOihnlJFw+XJszuVFGBFNtUITAdR1IibQZlGKyKOrNHYXpktKHTAx7HySGVkogmchnxAsE8HP8Dd2o919JyEPmktAU5KT3n8TVxfU2zm8BvBaC7RXLkBWM+Ghlch4yxeGoYNKCNtnxCJguQuU2RSKa15B5vy2XAqbvh6aSpIaV+Royyk+hIqr866XbqcSZ/FIiaK0U85ZLTKzQTo3MVHMvJW7SfJJvlsFnw96X4LicGPY+giMFchHXm3yNfZfQh4w1EVQEnOH2SWTCNaaMsihKV5nftiqoB7td+O9ubYukwskmi8J4ObwZD3cr8JVMabLIMZPaxNDydZuYeJh8HQDwKPkPuE5BabIYu62rhF6K4BcODNBe+5BxtUdNg8LNyRoy3SxOM5pUWFssYRwIPMS8VXorQMJFdgyKTRt7pr59URtJ7ESzOKWGzAg0ZIHVSlJnWZ9bBfNAHXx++ucBAGta14AY0bjzpfWdDWNIsRc1Jot3HzReW0+YyxRUjPcVG2XRI1HUGjKu/izvJ6jShBHQkHZy/Dmji0SoE7BLgllOUKYS7FKYQkJzdraLb8YyiFTh46/k31TnomGiUDVcWSYM6hFnXSH5kAUMdTIoy5BxQgB53ljsHq8wU7ViggjZ+SJ3JvA+ZCRWWDnQqDBk/QzRZJEjRPx/r932X7hgx0fUFZgAqGiGw04wvQO7TssVbloa8yqbzUQrSueZ34G0SWfO69jy5sUTM347TprjVb3juI4T60Mmgg97z2jIiEd8cMScyodMYr7kNkQNGWeyxXy7JWQq1pBjsZscGPo3KPOQ+dL1l158ke8L50Mm94OFzk+HNVlsMhMYMsqzZJ49vzAetm+Wo/gMvA+ZH30uwZ8R4A/Z4As5DgWMDBQuRN79QNrHmCyym/Rj+AoANjG0fLBoNV0xqRVEhkwFbpbp6mJ9yIhAqGurjw6uOJNFCNNLGfaePfCYn04KDZnoe8BHWXTCdsO2VEmFmRJOQmLoOKiDerC/vXYKK5qj/iiTT7PvIPuQ6Uab9yFLJlzYEvqgHop2BCGGmTW5usLuS1WqCRexQ5wfBjKS2aZyf9HxC/784D87hSuEq0aMlprzA9EddIaeIYuC+fDMvcSgMXCJTDAXVOb1Uim/fkM/T8I2TFlDRoiDjM0yKAkasoQ2RB8yg9mDeGFH/HztNIfhMtyK6/EbjyEINGQxYyhpOnwCh8CRzlJH0XwQkl0HQijXb89nLJkAD6OhBgyZ5hEvqJFCKyoJ3lntr0qLasAQhEV8vlNu9fIWUorE0Kq8ZUrazjQx/5RfKe4wJosxWkh1HjJtca4vnsmiKmWI7Ituc6azVGojzmTRLuS0XRrsecgqDFk/I15D5v07uThBuMNMRv+c5U0WIz0Ne0jIPmSaaZmQPNkyoNUcKIN6aDY8V+FDJkdAAuAUhL6m15BR1+WYEWLIYbC59tgoi6IPWZGX0KYJ6iH5sBBI9uS69vOITIM6MdR7XDJZjDRkF332IqEv6npVsDXmfayGrC1TpSyjg+vIURap7UiaNA8kzMsGMHNVoSESYTBz/PeoxgkwYbkueoqnYmfhEdTnPys9E0iTqSaoh6eFo2EeslLIfD4xtKCBJYTXRuppXLkurgzrQyZKXzVrM8aHrGHoCDx3/OnYOmocV1vV0Fao3l6fhyxBQ6YM6MJqfGWCytGkZAjvM4mhlSaLMXM/MTG0ihlVMGQuE2hJ8iGjeqIvjCbqWqmCBnBrWifJ9bvCMklilMWqmmpu3FPlIVNpcxXFvCiL/He0e2WyyLfjikE9oO83S7Dp3kzUkLHryAids4VvrWMiCR/23owL86+Ba9gopNlixS3BcJF1jCjIRcAkp/imSh9xgSEzNbnX4uuleGrcf6CRjMdy8j7sGHl4KDiMB9+fHOpA4U1pkVC2FWOcFNSjqiontcFiDBqjnlCWdvJYnIgh09E0OtVZDBMD+Ts4MKM56INPDM1eB0yXPbsMLjhJWD6BrgMAx8yiWBUFoWH7FTD8wRirajMMR6ABgVI0ZFZRzZCJbXHuIhQ48MDV/H1NkxmjCnZByEMmRFms+JC9hyEuYH6eqWcVd9X/QpzJIo1IS1GSnAYGdwjJfbBIRAzELbUwqAcBVIH4xchDAGA5goSdEklDRhUbi7eoRBMQjyHjDnZC+SSNQrc4DRnLkBkARQaHdS2KrqUyWVT0lcq+YcxNpm/y+Eh5yChCM8+HH36YL6vyIdMG9dBpyKIN0hJNFiVTMOFvlSTNtvzHhLen6sTQqnQJIlip9XgQ/AG1sB2Klo5LQTEEw/JflbsRjANnviPAiBJDO0I7sf1hJO/iE1TQOivNaljTJ4WGLO/yUlhPA51Cu8KGexcEH8+e8CFsGz0Bz089g7s+7KC1yGZEzQTgaIN6CGtVnBOQx1mZh4yT+Ko0ZExfYHI+ZKLJovTVOG1OvDmkoRh/9YEta/miRmztuis1DxmnCdVoyFR+caKGDKIWT/hXvO41no6wUgf1UOTPouIPoW2mPQIq+5BRqmXI0kRKE322CEfwBv1Va4eUbbLP++GSaQwJJdZmEytGu830U6Ehy9pmuFMHe4qut2ITBhNNEFBEWeRyaiT3D/DWb3t2ePh3rmYId44fSteHvz+3R87FGOC/yD+QNzI4uKY2VR4yNyGox9ChzbHRQqsRMf1nYIb3g1A/DxnDkGlNFtUCIFdgkPi+ybuiC8MzWWSHPiZQDRdlWxX2XvnK8kXdvg4wViWBA5dKQCNonW1AHm8i/fDqJRSWRkMmMuPc+qbAuPGbuPusySLbSn1mBJxiUamVBAINWWlWFnsTFYasnyGbLDL3mD96iNoUiJoAdQm3IB0NcSYSH5yUhbVA4vKQKRgyg0ibI/M00x7rQ6aSZskTv6gyT3SKXD+U0imdD5kwvsQAHEtP/LAMGWceRADAxLjC5vCanSaoh6KrIkPGB/VgGTJZeyPlIXMRasi+/OUv6/uScJC6goN6AFZD5iiSiPJNCJumSkPmOGqiHMKhEiaGTkEBMEybSyhGwoCV4CNVDA4XGsjwiNSWYUT5vWyhxyqppqo/IqhRWlAPlYZQ3JTTbtIGa8ps8+9azDDMttC9kdUdEOFqJpdjpUjyKjFpTL9ShL0XGR4HmbBOlclLHMQUCl7/mN/E03CzPVb5kPHBeEQNma0VLNicD1kyNT6hu4Xph05D5hPkTHWOFPbe0fgQx/TB32PZrTY0hRKYXNHUWBXUQydDCMeVPZMUJoueD5nmrOMEnTqGT9SQMXt/4EMWz6JyV1nRX6Ahi9M8SuZ5GbV/rbIxFsRF1jFDIVNSVMlqwoQJJ4Dhz42AyRATQxushoyqdm9FF1V+m6GwlXKCvmpq8+UEzBp9GCZX12ujLLLnJ3veaxNjs1GXPWM5ZTmXoVwckSHTDLGrMVmUfcgYekZR3kZGNlnkhHDR8zlS5M39DUOaA2mTTkiCWWYIg/lFbf38Ek0WHSSfd2x/bCtwl2HnnGyyaEnzS1hLzGsYMHHwIYtx7HFvoKOqFU6xwEcSFjRkg5cdqzBk/Q7ZZJHRdDHX38yuiP5gCUfTI8o5cyvmL3azEhPq8mA2qQSthGUASBEUgNWQqaBiyFjpHPWoXsAuCmdA4NijXlTMRbgufyQSIwqtCsgLWWcfbROAIguTOazShL2HS2UJMHW12krRvFGEqCFjTRZffullvmxJecjYsPdRWdaHTGfWqANVRJyitiztAmTCJYyymEJDxhEMft+ToqwVgzGM8TkiBg19SZyU2gHvOb3JoqchY00WVfWyGjIFQ0YIN0/S6b0Fhix2/YrSVbmsbjychLD3oDLByIXpVzFkRGTIbK5aG2a4VpTrNyaoh8ioAOAZAUWURaUPGWOyKDJkNMavpdQ8ZGfuWs60qZ7j0XBFLyKmrCCwOeIpjbmkirBS7e22wodMZXZKhH/l9vi/nLwcj1ufTiB+HwUAGuNDFgX1SEueES8xtA/DiH871ZezTFmAlaplw/FNFsW61W2L688MGDJ/EliuhfF1UaANVktPgTB6bRyh7boK/z47YqgpNzehvB7WRYjnSeZSmIwGLNDYsObbbFAPLQRGX3czCvARBfUIBA2lmiyKgX6S2HwHJsyYlBwRXUf9/jB1EcLlswVKyUMm7LXseASm0HFnh+HwTJzXWTVEf3tC5bQp8PZTSZssBm4SwJos1gwt4qCDlmP06O049LBFcARNO2diaahTRg0WVBiyfoakIdNounIJGjJ2g9CFvRcjCPE0FbONE4oqoxYEmoPDAFw7cNAV+sP8jnzI1GvSUfqQsdcCKquoXiRcpBxDbiTwIWMvGRRujBSd/R4c0WcQAFkYHENG/XJ6UwKVeR6lLlyi8axjv6MbORR0YYj/SoKGzCGhbf4pp5zCVaXWvKnnBlcnUybLSDKLCRoyUIDNWa4kjnUMGSW8RL+XQT0CKbWdENwhSKIaacgU9RqRs7QtMEGATDyEI8zlIePhEpH5lFvmNTTye5ggXKGMpv8i2EM7LlKW3B/5OzqaNAmOHa8hU4VhYM1kQpNF5r4YZdF1eZ8Cl0kMLWrIVHnIuLpSHXECA6kM6sGuH2F/cYoS8RHeYnzI0n1FZqy0GjL5usR4EhfVw5uiR2o8/9hYQlFpokSlcovIaaEmIWo/bpw17yG0JzJkBFTLv1gaSwe+ghgNWejDGk/4sY2wZmkZv+86X0tHsWo9hkzfhLZp4vuQCUR6Ks0EBQx/Xw8YMtu1UZOpCYuwAhlKwaQTiWHIhP2FUIQaMnE9FhP87QgoTGLAcShMhhkIfMgMZm45MT5k4b4rMGS6NABWQC8R1ofMqz82yqJqnsT4kKl2xRrkYbgZPS9DgKOOnolTT3sKNTUdnHuF0ocspTwxLj1FaLLouDAMy08CLUDwIVOaLAZFM9Hz2ay3ttXnh5zHkdOQUXnZsEx+VTXFo7gYP8df0Tq0Fk5RH3jKNYySA0PtTVQYsn5G3MdPNS1MryBvsqghlsSw97o6iYsac4i2SYsQuIoIiV6drEaOyUMW7HpsP5XO8QoTTqfIiXDDXwkassCHjNuADRprsug4jvKbOASgNAOTkeCrTRZF5ks4mAgFfIZMBU5D6kZmZEvIKbCRkaIseiaL3pht3bqFb4ttOuGg1/mQsegm1YllXI5gVAX18LQb4jiJc9YJD8PSfMgCokgMuCIGoYk0ZEzkQbFek4bPpUlxHa6vmD67Qh4y1WfhAhgqNGRictqMTnIiPseU0a1fFZQaMl3Yeyu5I+K372aYO6oIjS0S87LJYuRD5jhOfNAeUSOuWYfcM6L5nS9o4JPkst9U9CHTJ30OJe8KzWCA2tp2nHTSdBx88BLeAT0h7D0f1EMwWYQNYjKCg5jIoNFDAUHLtKtoC4DEkKXZX+T2eEGXk8+jNUvwsxNr8M9Dq7guiUgzvePC3sNPDE1SGjBR8Fo5k3fLkmApwqvbMfkLY+FryEKNUSLxzXEkksmi7dqoNqO9niXuKSiQEG0XgJR3y7tYDNtUaV6kvkWNYkPnYrgOhcnQB6HJIrM/xAX1iMzghco1X4kVYHsmiwSu0bsoi05KDXiAcdgTryHLdmP8+E2oqenG0VNmcQyiSwjqqndy5VPnIYuZPKHPnuvg5FOmY6zgtwXIJouUEH0eSWZfzfh5BIN5w3dDka+W23tdiPOGZfIJIXiafA67yET8tf4yif7jTbsNdTqmQYIKQ9bPiIuymCodgp+wWA7qIS8s2WRRLaknhDILQq7HMsBEQ9R3MiBQh3C7F0O4CFELAaCrU1gMjGSNveT9iGfIgjxk3CVDCI2reCwkuFjVOwEoMjA4hkxhsihqDDVBPXQaMt6HjK9/NybIURYdEjpL19TUcOW5QColaMi4/jDlM3ZyHjLOSlKlSXAcvYaM+TuYq6JZUdRWBJZpCTVkAkNWJdjjRwxZ8CyRiErPZNH7bYMkEjph7jSuz/xDNjF44l0ZuY6dAzoiLSqTTB55SKshE+8Yim+gZcgkrajAkLsuF1wE4JnxwHQvTkNGqcXdt5koi2qTRea3QAz2RkOmLMEFJhHmfWoNmRrHHvcG6oe04aCDl0HUkBFFWHVVag9Lyt3HBzvSBzqI32NVQWcAKEwW03qxMD56PN+A7vY2/PWoarw1Poubj6qGndV/OzuND5kk4WetRGQNWWxdIJyGLPAh0zPiWVmqbyaHvQdkopkQBxlGQxbUoatL7JNosuhQBzUmc5ZwYe/BaMhi+ijtL5QzWWRRTFiCBEDRzXsaMpYh858zoGbI1CH0AY27tIRgbbJ5yEKTxTgNmQoxPk/efi9aWxAvyiK7/DgaLfpdW9shh703e7j6vOkofBNVAnlTzwQGGklatRk1Nd1SnwH9fsAimL/s00a4fytoBshCNlYYrprnLJNvMntfpzEMjsUH9RDzdtpxmvABRoUh62fEBvVIYXJATSrl52BNFlnNgBj2XpshnrgA8YgcdVAPMJF2pKejfvjtfXiorbw/tHWtVHdnW4xkTWyJffG4sPfsJYNykeCUjKuCqAuiLLIaMkthsihCHbDHjTRAEBknPSFRBUsyWXRdEposDh06lCvPvZmrusjc1viQsRovmagSDxnKmSy6jiuNDbVspaDBobxJYDA+OpNFdvyMFCaLVS4fTzpMP+mPHaGyLNwzWfSJFEIkyaocqtg/wFWmHD5skuE1nP6/HSNXoHuIJ3HkxCSGnJdLRJakM3bjpKglJIbOKBgyVchpAHBiHL4BWbsFADkMZ+4HURZ5Exy+DlvYJyPTHpXJYhzEcPAAZCKcxBk9Bu2wfoFCH2wLeil8oCErapmiurooKTU3dxzKaQcCBGHK2RaLhhBPnTjQCeR0UAoPDPXGkiaoR/iIVG0w5/l1snb9Rrw7Mtqn3Co9eVJM4RQnasiaMZZpL5gXYpRFzUwgfJRFMzCJ1nxTC1lIwhrTjTWvDZ8VmHDPhywTmmEnhTcXGTozMFn0/WVt10Z1JtKQcWbTDEMW60PmUOH7VXFBPfj3ibcYAChMkoHjgDNZjDSCzJxw9MIwld+2GNSDN1mMxtnx/VQDzS/R7CuqQFYAJDokCRQEpqtnfNmZbxiOZLIowlR8K6VAWPJ5ZrXswUUXnRiCNZgiPa8++8Q6Tan9MEquUrUtjylriFG0FCaNnDCH/+5OsRi7RJIzaQ4cKgxZP0POmxP9tjWHCsfd+z5kLBxXzWrJJoua+gkFicn9YxMS79gZlANL5PtSkaSDUtlxcYn4dYg+ZBJkk0UYNNaGGIiIOs6fjxBANFnUjAF3qKoO8ViTRRZ8/SZsEELhMFIs6iCUPG7cuJErb3BS+4RDmvneupK2xm+IBUcou7b86sWi0tRK1pDF5yErMoelkUJDVk15Iib0IeuO/GgkDZnJ+JClIFhDDZnJMPzCY5aZ0a67niHbIMaN0zN30fuJSUBFBLOInQ9JjBOLjKIPjug1HrQl1CsRmNSWBUFcUA+VNk70IePXrwsjNFtVmSxKc5/VfCtMx0RQhdma4zgo9HQzbbBEpfAOrqUlzG1/HsdpyHiw5p0URMFQEjPQMEVtFgSGjECIspim6RgfMhGOsFXE+5DxCAO7cMF6CGzb0gZTEFHgzPJ0GjL/O/kDsYycyDxTFfusVBd4JjRYHknfnYVlOKmaK4oMmWkh42SiRMkJ1hDg5iqRTBZbC62oMqP5wjJkaU0Wbcvl5ouLoTFBPYjyOguDmHBsIMMwXEHUP5NjyIK5I9cRCMwMt1a+qXqH4Bspwt7rUNREmY3LPQrI68+BCcMV0jlzTEb0h2kma6PT+pDFpV0I55cL/AJ/xU4yWS6k0vIKdUa0Bqvx8xmykDaItxJhw967kMePC3sv7D1i8nBxjaawuh8wVBiyfoasIYtmQxoikGbgma0xRR2qjhQTR3yw5Q3DheHnnFLVYxkA0RB0SqKaQ/w7SZIkCsAW8kb4C4zTkBmGVDclMmNqGBROQmjs0GSRuWYRwIuyKGvIFG8R/XJlohygnsmiyu+NzYslSJkpiMeQscyTSwDbs78+7bTTuPIGu7smHNL65LvswRnvb0Mpb7KoND8oFrQ+ZOyVMBy4Nlx4RBRwJosk8CHjn8sKDFlRZL4A1LpCWG2DgoRRFnliQWVmEvSZd3bmyxRJlvezEyWShs2Zn7DMndRhH5mEbcL1DyczpYasqpYPc2+WYrIoSjglUx0rVlYbMFvcPiLMO8fNc0yWhSzA+JDxzcdoNaDRkEn7iDxWtm1j3bzZyjpdMaiHXdSmbwg1wTE+ZHxfmL65UJssmnJ/RYasyhRDahN4ObSFd+drltsiUGoQiwJRGOdDJkXdDJlTnlB3bN5mROMq7bXPrVVdw96YE4WvDjUCczVxLHVziXA+ZEHXtMItyIIZy3RjZir7LP/NDdNG1slE7xwwg7q9XrhsCCaLSxuXIsOtC9FkUSaopTaKAmFOKcR8ogGSg3p4gUdEk8UgcIPB9JU3WeRhhxYMwj7OCSaiPzaTw8L2g6Ae4V6g6XLeKipaBlyFoImF+K0KqFZoyKIyhrCfcOeu4pxOS8jH5WgLTEup66KDDFeWIcSRxkayJPEFylz6ASPYv4ML3BOSYK/gsnNSHm82qAeEPd61bMSdCYWKyeJ7F5KJDfPbSpElMl+XkcziHM1zcYmhuTxfhuNtugRQ7TyWgZiII6xUTNFegoZMabIhaMhqzHq/MKshU9RrGLLJYobCsdJpyFgUDQAky/mQFTQR5VgCTud4T3UGo5weX1GCuHDZIAgOCSWPzz37LF+UfTxhj7EzrAllBJZ5sBMc80UfMkdIYAwAtFDwfMiE/tjU4L59ER4B6Wp8yCyNhswOgnrk+W9Y7Wo0ZMy1IW4Uxe0DdBanIRPDvKtmseX3WctEAciZ1eDC3gv3RQ2ZEVNXgCR5dWCixNLpEuPEQph3WSKvB91cWNK2GZaG8AIA0ALiJqPrM8VsCVGb7Fq876mFqlBDplq7ceerpRg9aSshMkHgOA7yXZ1QgUJ4fyEqJIswvUPKKIsicWOIydoBGKbfW+ZF8oRnyEZkRwsmZUSbvzJEaBInXqbSoBVEqXRJGrIg+AOvIbMch8u3RE0531KAYgrSJdCQEUceQzdkdFNqyAhvshiIl3RMkaXQaxeMNAaLgKX45lXIMEKm+FpkH7IgyiLTFycSThHRbFPRvghxfyEAENRJeGFW0Z8beVRDtQYIpTCJCcfhTQUDBkGlISMAqMvvG+FaZ140Lg8ZADRhDACKIuUDWume6ClYyg1HGxEVgCp5+IvkAmRtU99QnCbLMEAFZk7F86qqliIHM+s6YJzj8iarhEGiMMY2FVr9wMzaHye2F6rAVgXJh0wQbnAVCOeHzas6JGZ48PJjFYasv2GJEV/Ye7pVxxK9VQSuIPJyXEPJ90hBPTRSW8NwYMQ47lqEgOotA0KoNHIkgeiQ8nVQAjiihiwQAbI+ZCofBfmAMkwhyqJqnBQastcneJu5yURLyvtJDGWTKOYAc9Ubvm5/Zs2jRMKQgsAwXN5kkdGQXXTRRVx51kQtKViYapP0e8GUKdVkUbb9dvMFZVAP2zU5ojdgbnQasuA+wDNkAVFUv4UnlqskDRlfHxFIu3p0gxiMXwUlXDRHQP6qgRllnMli3qiSCGGuTsKHmSCG7+MGEVHr2QQ62lFpyOJMFoVOj1EwLbbGZNF0M3h2IysYEMbMLUghmTkBgCs7/ksasnynsE9mw6/n2Ja8HqXASYzWV6FhEiEHf/AZP4002RVSlFC7qJVDlZqHLEUIPRDTlfyERA2Za8qRH904lRP00nPV1lsUzg9bqV3XCKuoz5RzzRGMqq1DlnVnko6z6CbPkGnaCQQNivd2jchcLeqXfs3sHjaaC+qRZHqoMlksZLRd5VBElXStihjIC1S3rioxkE1kssgw8HYknGJNcF2K8IPHddWyRB9F6gkOFftGwTDxKs7Gt3E/nsQXpPsEgIGMpP0u+HWZzBpmfciIGMhJeabED3gLRgMEKNLqVMxy0/YOzR29hkzFUABARjBZFFartj7HMACHN8s0kWpqxWrICikSXlIQafIXM/yDdkYhRPLNEsOtmukGMeWE6TlG8Kby5/vLlBpceUKN986GqCET9lrhlcWk04MJFYasnyE7oTP3tBJLplCGomtHDXe4um5k/sUyQHJQD0ZlzIYYJhQwPDdQXVAPt6hW3fMR5KLpE7FGSdI7hVpHF9SDlZIoqAJKDDnsvOnCYnzIVO8X+pCJ1wmQZcJy53X24hA1ZAqJGaMkIlpfL/k5gziyD5nlHZ6PP/44V1aZh0zn08AyZBwfxxCvCaYllPLmH6rwsbSoZsgsjYZMx5DxPmSMo7d/8NmChLZaCOpRVGjIRBCDwvSJFEsK6iHPnVBDZljQpWvOm9W8Dkz8HsQFewzHadsCZOQzkEPg5M0SXHEasp62A7m/P2pPkMroTBZNamJ503LmisjEFuTcamzaAicvPeWIxH2hi/u7iKpw3kn+AQl5yNQmi+KeITOJtm2DaLSELhE1ZJZWkxPm23OL0Im32jEM9+JbWIhTZAZesZYMnyFj70gMmWHzplqE+IF1RMiCMEmBaFBpbRRFqXQJYe8Dppzbv+DNc44hE4h79gwoCqH05uF0TMeFnFAyZLRV2gOjtLD3cw4/XmmyqIMqqEdeF0tdgGrOZonJ7GnR6a+CLqiHyQh2804eB1c5mJBxwRL/LqXoSagfAGzxbKQU1C765oL8iiwSA/eQ74ESE3PJh5T1mcSEZfG+mHmVhoxNmyGmOgnOFFM8t3lNLItrcTUoPGE25erUrNWWbqhOlbj0RhRqF5OMo8vgGi+XcQwTYoRm5XatqMSNOeMLwT3R5lWqln+bQpZnwFTCXyMKZyzXZzoQjXnzXHJndVTxlw/IYuEoMxQ4BHAtWxuUBQCKg5cfqzBk/Q2RIWMnnpUgsQQAZCmsbn6CpzZZZA4tcUITUz8rLQMwU5qgBMSnoXDMrEZeuqbUHDlFPqx/aCTP+pAp3tkwAEq5fcfIUFg5dfjdsDlV6GwAeRMYkp8U/l3Q5WJjNWSin5nfl6KdPH5STjMQGKbDh71nNGSf+9zn9JUpNiB2TJ0UGjJLJKqSAoVQKkS9gm+yKL+b7fLMcxJDpjVZ9MuLDJmoIQtNFlmiVGiDGBQZ//DxmFFB4isg6DNvZigSXTxhLNZCCe8nk44hi/8OKg1ZXFAPu1CHAqpC7U332MXaOv1eh78MN4OcLaeziIoWpMOQMKewSkMmJYYWGDIL2ZDJU5ks8oMsMtHJGjJiygIh27ZhZtg1wwqHLN4Xy7agUy4HTHy+s02rRXsen8HL5Hz8mVyhjKAmwjBcuAafxkFkyCjhNWR9Mlk0qHSxIDDRsVEWBQQmi5QjlA24to0sa6YeQzyyDGHeqMJN5HI8Qr6OZ/DZ8LorfNexdE90L9SQCeZ6MXseG9Qj6SupNGTFlGoMS6chS6E9BWQtSECwZhi6YYjbhsvGF/CrA/LIVrWH13vcRnxoaBFv1/IpVkQ4litrYO3IHJm9V0jwTQalMEiGi47sPRdoyNQ+ZKKUKrS6YM4LAoAaMXlJSQat2RGpgv8A/v6jnCN6X0TdJ884hvAKvIAC6ltYP26SJPRK1mmqwX2nMLderBhTMjEsZASBWvg3I3j0n4noP0ZBoDCDzBVZKxRHyZABQEsVCaM6Rh0QciQK66ESZfE9DF0iYgCwtFEWmd8ZeXHoE0OLjtzRswXwG2ymKghtq+iXARwx7ARlG2L5gODJKIiaIqrkiGhi/hgKrYaMAzFkbZ1CQ2ZkXFiFeCJXSdQByBsEDuqjvy05QazXF0FDxipEfCmo5cp5aIB4E1DACxjhmma4ibiMD9nbb78t1KXiNlgNJqM9ZTZNXkcXw5CpILyUGEDFLWhMFgUNWTBvxNDU0f14k0UUXbBmIpIPmSiAgKwBM0waSo2Lyi+jlsB6TJT3LuKbFgzeT0IkjnJ1OzkNGcvczc6sxZNVc9GJHDdWiUE9Ah8ypjNxQT06zRr8F/6On+JmFJGFVdMuldGFvTcpz5BJh7dbVAhmowPT8f34+AingslLoYuXsKOKMVm05fUomkEz7acxWSQZtYbMZIQYXKwNowjKzE/qWtqEq8Gc2bJ8obb9Z0nEROyYyAfuUYXTVpksioIA15RN5VXnBk8PqiX5qkiLBUGLo/IhC9NViKbAgQ+ZQIC6tsNpyI53Mtr9kmXIerKR+dYMfCyq0+DDsLMCSyf0kxL2H7+vKrNB1oeMSD94WIqgHgVT3oOUzyrmbIaYeH5IPW4cOTxsUxvUg7WmgVpDdmw2ij5bPypKT2OjCzYBfjBhnLZ+wI+yKIDaBSWvImpTVTCJCavICxGK/mNcUA+bDeqh3p9F7RG7FpQWQSQjWRfpvpPoghK2IfzNi7MMZbtmjCZK1EJJ7Qn3jUTKIhmWQeAAUuAfFlTRN1FDZmXkgHEHHbwMw4Y1KLVvxHBlk0XWyilO22WACULjl3fEhFKikG7wosKQ7QWwDAA7t9JoyAyFJstNEQwE4M0xnjMv5O4dNPwof54qNiiWGJM2BvUmaGYUzvYwYEsh6GWtkBhlUbX8dEE9xJVMTAorzxBYiseKmqAfuQyQYQggrckiw0SIzrwB8VJ0q9RyJnZoZZ1NyHwEWjJWQ3bMMcco++MVjN/A7RShjBNNFhVvZAtjSfMF0aXHK+fynkUBw6XLQ8ZpyAjLkHm/HdsFYYJRJEdZVJhrGRQZP7GaJZiAEcXbFlMF9RC/u0CU1TZySyrwIbNgY0VmG1qMLrxZtYJ7JqNZpwHCKIvMYWdrAtIAwCvjT0MPGYJmMhZzcYaybq3JYpKGDAVI5AnLzIRBPRjtrehDZnVz07lAapEzPKd7x1ELU3RQ5yET/swUpG/tOA6MjFpqTk0LXKgV29LalBbh9du283LDPqpotF8VhGWqChZgmC4cgzfjETVkNslJgheLmrFEtgcC2aRToSEjoomkIjdSRu0f6VLfcoLwK85xXI4hs02CKhr0n4fFMIBsZL4CouAM1OQZMjYIVaAhI+xe7k+6ZozCD/B36X1Y65ak8Py2MqhH4jYNQM2QZf33vXvE8Hj7ZQBFRoJD4cLw3zvD5CroZiwbDIXJrv+wFo5kshhpyHyyPeqP0mw4AkGQh4xf24GGjI0IGZgse7NUTYsYQvLiiDHXt99iDINFs0jygdfvq/FMjApZJ45RjTelFX02VS6/qfRlwnOWIQdZ4uskkjVUQfAhi6xx+Mrfd+JL4BKZ+jAyrmQ6VeDiAMRZcxGIechgqwLlR1ALXwcHKgzZXgDHkDHXu2kGNMGkRqchS7PYjJhQrI5CoxUgsN1O2pyAiODImmp7/UKPIH13+UOYIgtqiaaNGuZLgBf2ntdQGaYL643/i+1zd9HLLySOYd4gnJZBZ7LYNTTKByYG9QhMQS1FZK8kUACmP45h6FjH/59jobGxMbEO3RezdcQlpyEjyRGIGN+slUe+D/NygiRe40NmU95eJ5RmGjqGTK0hC0wWc6AcQybnIYt/Dc88NDJZLBKSGE8hOvDZw0IkVKsFM0mFRJD5bWQ8bZvNHMBNpJM7hJI0ZEGESHYoHYUEOwAbxU0MABA+r7HBEzVksk1mQSHdZZgvR2HGbJhcNa7VI5V5ZcQnAAC2Iuw9x7QIzGsak0VUydEUbduGoTHzpYYFyhD+iMkxVgjMqFz9fptljGgs4WMX8zIDahgeQ8ZOJJEhc0iRn3uEwFIQQxIUi8DIKMLsCwyZym9k5MidyiaiKIusJofAcR1UM9/SMvUnEBtUhLMEYL63aLLIznWdySIFxSP4GnrIEO7ZQ5p2odmI5klvTBYLRpoTVT1nswpzNt1WzVrLU5DQB8tkBLldaRiyGDhCMieDGH4wBSoR0IkMGfW0eI5tcXtnQaEhcyy2r6LJYtYvL5isxdA6AELzvxXFs2PLAYClsa4RlUq8gFlO2QMAY5p7eOEca+KX0A/b5JkQI81DKZA3k4QGhA/XCSAvasiCvUBljhkqIRjhhulKPmQ5huGPo3YLBsIUFgHGHHwc97fk/6qtbeBRYcj2Alg1tzi1eoadLz/ArtKsbBrFOmfHbfGxDJnh5dNQEYw5RXSjADqpVEajNSh08VGJRGKdohpUCHOt0sRQolD7E0MaUCNDUSwyUk/F+/UUevx7PPImkGFy1hRs1zukhT7bDAEnBvUINGT57qzmxGSZEjHUrkZDBoRaMh4c5e9fItyfATIjbVRXd0GEyJB1xuWyYyKVrDn8eDz3iS/gu7kM2uuHhmXcgjoPmeUavP9k6EOmM1lkzMVUJou2CzahZJVgslgIxyG075FATDcyWVTljJNMHQINmSOZxQTorqpBpir6VqI5HiCvWWLYXAQ38XAyDRof1MMgcAlgMKpJqxgnYWUPfrXHQHoNmfC0wkeMrUkV9h7gza2dYk7q1Z7sWAA6CbV+cBySkZlO8YAeskOqI86HzDWKoJRhSBwLuj4Ea9yNYdqyjI9dUVp+ag2ZaFJqi1FzDYdjVCj1Ip0m1q5iyLJyUI+CwqRPhnoORSaLfFnHpahmPm+RCS8qnTtsoAemz+y+IWpG2IAfgRSfKPafPOTEwhlfC9dMvL2/N0E9CoYu9IvwrH/uFjqiYDtZ7rtEp78KRUFdEvqQMRp0XkOmI1FjTBZtB4TpU51Zha17RoddY98zyWSRADCNrBTZtKAI6sGmtJEJbW+tEUlDFm+yaFAXlmFibe3URGZXFVk4rnxwT3V/WIcseAqficlDBigYMuWnSubQJLNayZdahiEwZLIPmV4IRhVWYUaWSoK2nM36kMn+igEsAxhTfQh37bUTT8YwZs7IOeAqGrL3NHgNmUjcHwQAGO8OVz5LDIAKC8BNY4gO3mRRhGsWAMJP1mrqEVo5fy5njeRDNzARMTO8eUiA7i5eQ+a4vIRphz0asxbs5CVKqtdTEcyGIspihsKi8RK5XFFtcpUzCQjl7+m0ZAHEPGTBZtW8qAYnL/ATXGs2APn7RAxZpCELGLICxowZo+2H5Ksn3M+McnDkUXKiW9GHrJOLVijWGZVectwHAAB5EGycODkqowt7r8tDllExmjEasmDMLBdssIhqys/VXMDQMtdES18z60ZBPQh/CKq+GOtXEmhCxTcVfU9sBTEi2vsT04LDSuqFw9iM48YIRSGTwZtTDkahsBbU9bS/dkEvjCGZ6LAjGqGMzocs41YlmCwWZQ0ZG2XRT/osvhHrVO/aMqGSMzwi2bIdhQ9ZTHfAE+mA/G0NU5Z6x0VZpCbvQwa7qKVhChxDpi7EasjsFKGnAcCuMmJDWEN4J0pIKhN5SojUTU9Dxl/MkfigD3GIAruwe74Bx3W5oB5WhksQwdXBaV2IupSoGVH6kIlBPcBHng0QmIh1EW+/ShrJIqplQtAkHBOjQ8CQUSeaY5kEc3IWYv9VPmRFZjM0NQxZnHmrqCEDCIp5Eu797LMqoZTYUoZktSaLbFAP29Jr84IzwyB6hkwNgmdPOAOPn/IxrD9wVGxJz2QymSGTNWSK/maqUlkhKZ8VGDJl0ok0VYuCFlPNNIV1QhZiFLICQxZoyJTtG8p7tpAWhHUXoYZ+LhYMgqzBa7NbMtUYCgPI1MAYNlHaJ9UUx+BAhSHbC2AZMkcg4CmRpXEiqCBsS2uyGFdGZbJYDW+zCzRkGaNKWgZinVaChqynU9SQsYSngRmFozF3VYc6yiILTR4ykThrN4fjrpO+gIVTjlf2BwC682qTxR6TICPsYoUY0y8AUpTF4OxxzAzOfCf+IBqHPdI10+BNFndUn4Q1uY8Adh6rV63i2+I6EtsUiqjCyJG75f6ztv4GQTetl8qomskyB2OuOiLOaLGAjrxqLhAlQ2Znu5Xt6KIsBj5khsWbLIoash6FD5kII+tGYe+hkgyqNWQA49tJxDJCCGBFvj+ZIbC4gAEeGJMOA0on7wmnNOCEb65B+wcp8lUZAA6cgheSXpewHACq6luYvqjL6XLSZZ3q2KAelCaZP1GlhoQjlu281KuC70NmOy4XJEkV9l63R+lwwIR10jXbtjW6w8BkkQnqYeVVqa4ARFL7+hHDtO1nGTdzK12wNzhJsjKRIQOB5ZoK4b7IPKczWcwjmSGL9haRgS6qrsIF5f1MY00W1RJwLslxoCEjFN2oR57UhfdCDZm47ihVEtABARwIhJIIJ9X4dA3dlYrgChgylzF7NxVRT3VEqkiABgwNqyFj35ok+FipIPmQAejszkn0TRoQUGSMrGeyyLxTYLJoGjqTRfXey2rICCjHmKvGbM7IU7Bn+GgAwBvvP0RVdQjb1fmw6rkfqmnXylZpz+0kvl1kyLzpUfrYiygaJLZxVR6yUjRkuo2yy+LNxvNMUKq4ACcFQxa0dplZVBMDdWf+DObHr0DTeD6tSyGFUGSgUGHI9gJYk8WiEOSCGiqGjJ+AbZfYOPDiHcjUepuBC8ahO86UKeama1gwhM9f48sOcr4fQ5ZUK/YZUf3rERwZRXJVAOjuauP+Fk3UDh/6Pr/WqK+bqyZKbVGVtNowIA7A/fgW3jzyQ/jNdy9TddfrU0831syeCdvl+9KTAQzBFykfExwBAKhLJY0GIJsUBOCPVb5zFIBhRhqy7roJmHfAD/Fq+2XYtaEdZ555prY2W4iqJxOl7HvpN6QOMhQza2tw1kETcdvSO4U6o1qrGNORrrER8eEWCrh75qZEuZ9LTN+ESGN2o4uy6Es/TZvPnxOEva/zifWcT8Cwxj3smFB4phKRyaI4v/RBPQDfbFHTb/a7qjRkIoYf8g6X40iFrCK4z4STm3F/5pu47VM/Qq7a20dct0UqJ4I14fMIUvkbFDPpGDKZ2C5IRK7I9DlOQXqM05A5OWk0eph9UtpDEyIlSD45wuuOGbtV/tbFotI0CfD2Tk5DZvVoaZhgzhSQV0qs6ycs433IpCzgXh9W4xi8jPNCbZ9brY7cFsIsylrIVD5kcrw2tcliGobM/78oDXeC+cPfsClBsTaav+wclBh0k2GImcFn51pAiFMAz+FC7nmSqcP/rLoEpqghI+ojNdCQzciuBBBFNB1VVCcKzqNWnlMkC7u+QVmeRSfxmHdqs0Ip5r0IxQychUU4Rfm8KNDM+JYurA8ZW0KnIYs7JzwfVf4N87kgXAKNfVbVToZUwbJt3ofM38M5H7JCd9gz3f4shoRP0pDNH35S6p66jtpkESBowhgswUmSibROQ1bMygJv9qk4WAITlCmByRBEyNxfng9ZXF1ECpqi1ZCpntb0c+F6PpBVnk0AHjMWRVM2uu80TdQQA+aIg/FuZgssQbhYSJnSaSAweHu2H8G2LGDrXLgdu6R71PA0EnHLL/8+iurxRUz6sPd8WpPFWJMDsxBu1AEiDZn3t3i/CWMwB3xix9CHLKPe1HNdvOTDFUJUTxnhmb6xPM3soSfCGjYKzhBGqqxJDC3mIZtLzgAA9NTWaUNRt27aimf/8kc0Cf5t3RkiM2SWwkSKfR+NRDBuU4ogMmQEhmEDoLAzGbQPOyS8t2p+G6ZNm6atqaEjkBwmMTg8cbWGHMuV68II/GLsGLSYJm5ddieufXYlHpizJXg0RJZhyJo/Go1ZbuFCvLGmEUkHCt8nGayE2Qt04tUXSKgzgmYyYMjqfYash8gmi2KPjAxrskiUjLWuv3NOOAt/+eZVWH34VKkMz5AJ5nKuPC/GnvAk50Om6m1WoaVoxii8TM7HKnI8Xv3wBf5jyUF9eY2CGqy5GDsuWVdkyHg0dnTA0IQSD/Du47Nkv0yGIduwdTXWzePNa9kqRIaMHypZwpuGeRAhtsFKaalZBKWM/6edFzshtT0fB+LOCz6E5iH8Pjb5I39FhjG9tcRUkvDm1DXkWtxLvo3pfp4tpzrBJCnDB/XwTBajynW6p8LYA6VrKpPFdGNKOGFKACeYP0IXHAL0jNgQ9XlYJ4YO8cKzi2dZd3V0NrD7PGs7QhlG42nC53B0MlmcgNNwbGF8VJ56ugy1hsybn0FQoaCdU9tXhmUm0a3hb5WG7DlyIQpDt0nXRTxS81VQCFooM7IkWDb0MNxOfoR7yXeUz1PhrAxcD1gNGRdIOSHohQpS2HtKdfGZkkEpCCGgQsCMQEOWYXzZ7ZyaAQaYoEsskw0C2ougJTo4to1FLSslCwxKKH5M7sAN5Nd4Cefx9wAohV5V1dK1EMTFP3AprsD/ohmjpMctgb5QUxvJdKIkaDFIbC5Ez2SR/9B5bR4y/jnvX79BMfCLy58peZfVkOlp2aYDFsCu4edEexXFMF/w30Q6FUntBy/bM3h7th/B2jQLuPts0L9/UjIncE3ZlEW3jOrGeBuLQ0lYKNYGWZRMso7zZh5Zg7dzr0HgQ+ZryASG7Ge4GZvJYdy1wCTH1Jks9vCBJGTCM+ioIG2byLdDVRqn0IdMTQz1VNcoF3Ln5oAxFg75DIEh+J/1FBM0ZJok02JY2hAsYSffBCHehmdnM8g4TDjsbgsXXXShWDxEvhhEufRllBqJtopAYtFtDEcnI1H6x8yN+O9py7F6dwfXZJUd9a17TER8FNatx2FtO0AUse/FuV+A+vsAQI7JB0dIFH3S9on9jODbF+Qhq/cZ5G7B54KASG2ZWTcMe58mqAcbUvuNE8+HVVWNtYcfL5ThCTGRIaPEVZpgROuCYtSobSgM4wk3lYaMjeS2c/xB/uPBOtQzl6KJl1IjYBph9EbAheMfcFmnGhYboEJgrBZt2ZUYEnzRgnbsXMVrCtigHjmrA/luft84KhflSioURAIr3mSxB3VIgiUmOy3IofDD+s0i2CiLtChr9MJ6/HKPD/825h1zCO77uLzfswkhpEjYBtDNrIXX4EWCcxMs3YnvIxz2EUSpIZO0aMNHa3zIeBQQQ0wybZoZPqUJAFiBj6DIkAHhPAMAc1wDJk1epqy7u0pnWs1okoQ8ZCy6st6oj3LlelRJgouCGRbxA2ax7/ZbXIkhPd4+mUMNVCf58iHxJuEBOjEMTpHpd1U05xcPOzL2WUlD5kfENJmw92wJQ3N2x61iWxH9kzLCpuT0ChGCMXRt/ozIK+iQOH/8giaoh5NhTazTCrPVKDhd+Macq3Dl2NHcdbbFB8g3JR8yVX1WtppriNUeNVZX4Q3ySWwlh+IefE9ep5KGTP8uIv4/e+8dbslVnXn/dqWTbu57OydJHaRWDkggCSQRRBA5GoRJY8KAAxgzZoyHYGPDZ7DBY4OxxzbYYDAyUUSBBAKJIIESymqp1Wp1Tjffk6pqf39U1am9d+0697asGcuY9Tz99D0Vd1XtsN613rVWP0NOy11Ep6RIIWwZHrKu14dPXWIkF8b61jQy5zYtiXYAFoI2c1uu1LZFuDy5nswbLi4FL+Bihcr/A+VXgOz/gbRuuQIAOVtMA+y371/ydbIMftYYK4uYk4+qmMTePJ7jG4AsoSy21KQeyiVCS9bFHmXR0yf1btrp2y3d8iFM63nWnkWsFtJxC+ubdNy+3qv5mq6IZUpve2DMOjEvuOAYHoxZy8KjzmhRaL+/SikQJTOgjbIICfg4OnIckZsrPZ1WyNe//g3t+OxsKSLcRSgL2bd3SzyZmTTFoL5BJMc/46PX8cCh3NupAjLTGnzZrhv4zV98qXBtm6Jc9vXMCTij1XTSuDHPeO89yqLUPWTKgxR+ZzFkQiYessVGVXMJin1yTH6lrpnyWdgBUFboc3DwMCefcm1hv2cBZGp726m11Z7BThe13yWpVuxPnllhpYgJneR7u9LDsWTry6TmtQqLSpEC1+LgfjMleX6UGxQ9Mh0lzXrHLBq6CABcCiDrCMM63y7SKnv3dEJCNalF2Cy1ou0R6+jiMeklCXnmavnbGT/5q7ara78EUns3PeW1lvwqkyQTqH6lbmyrQ7a4J9vx4oISt9QYMltscRjOWu8cOQIUg1ibas8QU/DQKR5cde3QPWTpHFXi+f7gtgq+QuPLjHs2sKkCshjZS0Nv0iWz2No2Neu4uqdeHkuoyhyDhK2ZXtd2KgoQWWSiMg1fnsVDthRA1q9/dVvFddzJ2C+iLPqy/108IQm9fN6f9wRTvuC9F53GVU96XuI11Kj5evuy+dlM6hE/AkBWdliclq+4pmHoFoX1t5/hNZF2UCltTUtBWAdZUThuKYBsad9AP3HOE6UUy+x4E/DOVXQA1luLlGt/itcnVE4hiUKzcHM25+cyqwCyyIWPit+3tqZFlTjQ49CP5wHGg1n+fGuFP37SE9g9OqG3ryRZ02NBHrst+yWSVpoBzgakJIIFx6C8lIzSnqVSLi19rnkhVTEZ2np1wQNWyWLIsqQeYnEraDYJ5guv5O6VG/iHC5/NDzefTscAZKGhPGUgaUmAzNzmpkUzlMf0FYX0no0naMerMXPd0fHCwrbgCQSBRiGabXWLoE/kiQTikiKEWdCtXwLY0gtZt7peh4c2XMLdJ/46kCgK7YUOT396Yh0PlQlxYfRetj/5v9M85a/73AcWUit7WfKVTFpGxiLh5jmJrr47T0LiyfwdmcrZudERVs4vHsu0QLm12FSiM8DfSb+Nb1IW0+yQmYdswZKVTKcvJoAMwO86NEXRg1bwoPZpr9pu9T5qza9cLN7D9P9l43ZKk42yqMYqdPx0rC4JkDnarzLp0WKEpKPQfrw4UMaEfn7dW8A3aMnF7Ja2dM8KSAyKz9py8rnI9JAtFkNWZl1Vpevqi3qz2aTfu+l4ytzYbfYNPP83Xl7YVhnezfjJXwf072jOSSbdSQdk/UWjWSLoDEuinh53DB4MXyJ9fS1YMiCzGICisFj3DZJSH1IBZC2qxCn4L3oIcg9uWVKPsgyumXxpXUDD5IhSLEcC0HHzQs9dxYemtksAldRQNV/yfua8pVnnZxkA2SUOk2cbP2sHI26c3rP/tzP3++nYCULVQ5a3XAVkqllKyiprfUHFcrtuq0ixjiI/5bocCxxTABlRXh8ulS+s87lrYohfbHscB8ZXE6dlaGxvoDc/a9lyJbFXnl7+WEW9r/qUKiATRrmhxENmoyw2yr+kUP+URXaJ0Y/cJRgU8/aUy6wH/WCBRGhlaADmqvp4aVeKff8ecTLX8hSkCOnOFce/OefPRB6TX70f2Y3ZvmxVaXuSWE29vU2qOBXJ5zYGtD23ED7S+ZWH7L+2ZEquRBQGlnTqFIeIfchknbacpGdcxTjItPCbgKyX1MNNrr+UtPdzJM+mBgbfufo4EIK7Vh9XDMA3Wh4SIxClBWp74loSQDg+tZk6Qjm3Rj75vvcNb2OhYi6ukpGRvQRritebdwVS1hhMryEFJRkD6SUniSLL1xCyl9Sj3kcnKH71FAh7HQ4PuewdS67Rnb+Sh7f/Lbf+8IeAWuxeMLX2+0i3QzhxM7Eve89kXrsjKoR4eH5/Pn1bmICsJF5IpUsaCm/QXrDqe0UPWYMyxdDsqxklNhIxIREVQx9oRHXWTm2lnm5vOg7h0z5Mhq0FRWU3M3BUuk7qUdMXcrO9S/GQLdDQFt+mWy1cp2FZDzK/mVnUNJOKJzht9CI2D52tnKMo8lma/0WzHBaVyLJv0POQEdNVAFkQVWlHWT0x/elqfhMzqYdJAXOCooKke8iiokemJKnH0jxkBpC2PG7k6xTJ5vyccVmDdqd4r+m0+irJ3xDPL2zz60fsB5vATkojCUu6fyQqrCUFUS3ZfofwqU32PV7v50sJRxaDFaKq3vebYnHjhARcrzh/RnH6rgv2D6EBsjYVLdOgKb3+qRhfVKARlWRwVcVTsntmwN5aTFwIOm6yvUOo1AXTVfQgTenfLPGQzS0ptjjxkAG4fv48v4bgjPuGFwVkJsDP1vFKV+lHyiXKwg068Qs5u+HxjGGf9YF+z26hrIakG6sen2Pg0KXfzLWkNrpmZf6+ZgZHsrsDRbNWmYEvshqA+rembEZRjRxNtbC5EcdYBG4WQOabgaDK9QotMs619CO3MJ4KhxS2m1d+MJgrjb3PjjfDHmYND1krqFqv/RAbiJ2QQ6keo4rj60fPOAHzP9nH7I/29O1K04xo9QUhWaelqSAo0n0Me8iWmGRXl6NHF7d+95Ph4WHckix0v4yywBC3zj+HEf/BohLuJBSnpQCsbJws1f5kgpyC18EJkAqFsEGaDl4I5ryU6tA/5KhnlVIpi4d7Eyd0uwY1SZrKWoTvVhiIFlk8hYOZ2MP1qqzcuYruOetY4O7eM8yQ3//h5Yl1pV6f4qRtP6BezwNAP3fo2dr1FjyQ1BgSCxzasJpw6zBXzs7xWktzpAhBennhZrVdQUyYPnajTanZo8wjEwXw6SduJXIdfv2aKVZOJoHuTqtY2Hl+/Be9v+P8sa19ZIE6ntvF6VNnpO0MUIvjXh0voXkOJC0/4N7jtrFQyxc/01oezM9ihQXGRN+PSmbuUxW76/17OLF7IupMvW7uOJ69981MrvwC9VU/5He/HLN9519weqNB7Q2yUKhFIno0iaDrJFkZF9EhDrKCDgEB5V6oeRq95DiQFCYOHRdfyejZcGXh/WTxLmFoN4Ks8ZZz0sjjARj0x7j1yDV2I8YxesjKYsgAOhktRsR03SZjW76DjF2qccB8d56qV7SE1r0mA45hhTDeaxDYYq5MyqIuTSe/V/+kHjBf0Q0EJpC26RuRtwAdJTnNwgLVPoEZoedBF5qhx3cfFsSbHgAeV3q82VwVaKjfY6lze+PSGaJF8kNEaibQNAtuZyj1DFs8Qz0xHlsML5ZBxC4xjtUjH0d2DxmgURYXaBBFmVHAAm6qdapz04aB4dgA2Ywyr8gwBleWJhv6zOMv5VU/+TaxkHl5FMMbMzY+yS6gJavW+eRYAFksBd/iMnxCnspVrPdjWvePcPXjFinFonTwKWcETyRGtUABZObM0a0exm/pdS678pLe32fWPXZ18ncVtqKC7aCjlEw5lhgymQZOeiIuaELqPZqpUUDGTbAYi23riUQcs4esfy3A/N1Pug715/4t8itvQiVsiAKks7+Ljt8v1ir/00GmsdN5wzqWxBlmvcrSsgjaffRj7qtM8sRWv28nepmgM1kooSzariKdkP0f/nt4jU4RNz1ks+ncu3DLwb5Tzy6xkU/I39bbQ4M4KP+IZobKx5I8Iqg4Pj7OxMTEI/73gx/84NF+jse0HJ45nh/Nvo6vTb4bs5smgOwYRaEs9ndU91eAfYOSOMh07++pQOA7waJQcT71kPlek6PjP8M1rN9zwnTfG4BMxNS9AepR0ziuKGZij1DESPQ6RHX0RXi2PgLA6tX3amAMipPAvCeIZZ0hFpDrk8XlW1ELaUtQoab5NylZQUTGDmkUdNPyiTrbc3RgiChNrHHdKUVukvq8XiePSYhGZV9QsUADz2+XxrQBzPjDDEeSDQckj7svRjj6+/zGJc/jyqe/gptOzLNtNqlrmfgqRvbKfu0pT+pR0wCHp3hg73f3M+kc0qhqo1RY4QnG9r+YJ9wt2brXpz04xuFNT+ZJ91QRxpuXCNxq0jcrXYemLYun0baDYiVv56/SgH272LxobSMhgDkGAGSqNIQlHoE1Tl6wdPPQWWwZflyJV/nYYsj6je9u6hGQQhKM7mT5Gf/GirP+lT/c8iA77v4Ehx56sOCdGvbmeE3tXwt3VGWoUlSQ1CPcIKIQH6J4yBYWjPMVI8/u5Ws5MjCs7V5KDFns6f281dIHrgniQs9FSo+7Z5ZzuOUhl/Dee9cOhKZpajFihaLa+vdSE4CEqxaBbxplURlLteL71c/L90U4uN4jy1LXJUhiVo1nisKZtE0WWrFST3CaYR6qrqFj81gBXzj7Eh4eXa49m6NRFhfSsdbnPSk1rrbvuB8pZWnduq7n89CypKaRIwQu5liCesquWGDAcgWYWwLrBBJAtqe2ns+I1/FJ8QZu5az0u9kIz7oU5oV0HGseMuOcBy/4n0Re0eBXJt2W7sWWxHTiRqHo/VLkqJMA9IojkEZ8knq1VmZokS3L3txDZrbgWGPIWoXSE4o4MY1uAyEFU44Lrk/sD3Cok88xghhHG9/2pB6doIIT27+JCa06hh41F1R5sGEYqMtbrV+tz+O1Pd9usVLEKSlx1LtGUL4+xqJLq1u8vukhW/CSfi5bUaE94+Eh7fcOsUn73aSGqI2WtqHjP3YB2SNu2fOf/3xOO+20Yzpnfn6eP//zP3+kt/xPK1FU4fiBeXZ6BwA9wDAWNZpyjkOOrsR28ehQ6XmtMlldO4G1tQ1E9d2MezEdT9DZ2GXl4Snmp/Rr2yliidzPZuToBCggbJDccnnfoMv1K7YwuvMutvEAZZIBMuGF3PC45aB4xwCa1WTwXn/rVXjTFRYWDFBFxFNXv5rruUnb/vDYBDvHVnHG7vsZaqUUQoP7KwVc69/FqJijBtzNth7Vo/fMGx02B/eyavV9mGLq4FO+IGaYVc5uolo+NPbekyRemQ8qHBocZf2R/cQiYrYq+Mkqj2cKwc2czR7W8iy+hhvERI4kEoJ1+weYXOPS8nwODI1xkii3hmeLxYqN9/a2zVfsyoQUDpOViIqyPO/eNMahAY/ZAZfTp4quzXnqpeUJMrlnYJDH7zyNV3zhNrquy+EXtzjlge+yq7qcG9d1uX7bRYVzFqhzwynHsX316Vx088+Yqw5RbR3AES4T1Q38YnPM8IH9heedNxJgqLJLHMer5b/yHL7MS/lcod2TzjRhNE5IyG7nKGsY47wBl08NHGD1vou49rURzdYg7fYAm1vP5hb5/cJi7FUjguE2rxaChx8a4sjqxRfro2KcX8gzSvfP0yg8Z9sPGOgkSsTA4GGigWKB7vbZf8MsT+Rz/gt4LftZwx5t/1hQ584hh2oEJ8zHnDr6JL6Lbtg6afgJzIVTHAgPEIb3EgnB7tHlrJjRGQ1LTerRWL2X4fgwM0fXIU7eyz5WsYIDXMdFDB64FfdDNyAufwoL9fN5PD8GYNw5zL+ilwIwr98NZrlnTbk11w2KXruWWyNG4iCYn50msyVmZScEgtjx+OIlLyw8hwnIoqrFyOEvgOJZ7xxq403bFYsIh5sbj0MefiUz8aeJarPFyaSPtAOBEDH3shUPHRypylLHPUBTeHwvzaxoylFvzLo9EzP4PhO3FhGW2ExqtWnqy5pMMsJ+VvPPvI4jyyYYmV3c22RKhwqe26WjJIGRwL3e8cxWarjCQl1VUvNHwuevJ/47F8tNvJp/tN7jlnWbuXg6LyejGRiETJXxckC2s9ImUKaWQzSZMxMbKTJXqfUMYoEoXnkoXU/nhJ1aOOssHpcNMMMQV214S+/3jTye0+q3UFm2adG+ZlJZ7932HYL9ELUdOsFJjM3MMB7vhVHFO+h2mV92J62Dowx3Blg3NEVr8CGu3XYDq6eHOPWep+PRY4ATFpJ6SNqyThjMEAWzSPr3TVt7B906sZGQ496hvD+Mjp5CbeQgB7etZujhIqU8Y+uY26NABZqLz/FrB9y+oOUZu5/BtNzHX9bHeMq9DkMPn83KtXn5mISyuHgNgGa1TrVbRzgxfiMp6HLDmMuW2VgzcNrg3EPLlvOSC+H/u7XJUw6kia6M7z5nmecAou5OpOsSu34xtMHzifswaKTFQ2bKoWUr+MTlv8e8azATSAzZtnY5vmG4F4J5DxrNNgN1HVy9cu4zXN96Kj9fqa8zmTSp0+njHW/1ywL5HyyPGJC96EUv4hWveMUxnXPkyBE+/OEPP9Jb/qeVNl3ubNzJrGgRO0kxRyHTQE2nwterd/ZmkSClbPwJ7+N+NvNO/phTyFP/Pm75M2ivvYUTN7b57Qg+OHwWDzXW85xVX2LDT9qEoTrhGwM0BSs7OY73iA/iXxTxLAWEDZGv0n+1pcLu+moa617J07mm9NmySXD/0DJ+7pxZ2L9QEVz9i69zywf+BgeHeMvL4OR8fwe7teWabWfTdqssVKo8484bAdg2fhE3s1s77gF3P6eKLnfyOD4i3lm4TnzyDJu40XoPc107UhFIqjQ3n6Ftv+vAXlzgytMvZLo+yBPuv50nTnb5l4sGOTTisXffWv6N36MrAmqyycbq3XRExM6JYdYfWMYyMci/Pfl8Dg2N4i4c5uV8CiixEAMfEn+Yv7+qRZkQ0Fq1kbuHm4wrhUb3nryGD66ZYKFS5fl33wcGOJ1jkGGv03dNalUdzn38vRw8scvnH/h1bnzSsxDjt/DBj/0Zz3/B/7KeM8cgn3rOK7h33an84KwLeeE3PwGMce6yp3PduSv45/UnsCrew8CULJznl3x/SIpHf5UX81L5OfxA91g0RYcoGuKHlbt50D3I5mglR0Y28LGzNlML1/K/3TfgtuFnN76AfVWn995618bBcSXrnnyEweXT1A50+cl+c4K3v6jDhlFFlXkGCt8185ANDB7mzDO/ZWcBNw7zb7yEjqhwhbyct/Fn2u4dQ0O8dUsDP4p45Y3f50WzWwqW8FPGnoQDfGPvF2l3HuDG417Fbes240X6Oy6mvbc/p7dsjpNHvseXHvoNvjL8WwzIWV7HJ/g78Zs4lYiXrPwUn29cBFzEoJzhZO6AQPKSmefwTeU6psH1E+vPY7ahL8oaSPRlL6OsKsefcgMj/hHuvOPJxN3k/OmDC8Tr4eKVv8anztxUOAdgBt1jFteK3guT1tQUbQYWRiAoZsb9JG/g+1vP5WXVDifs2MzCeJN2vb/VWJWw5nCgUeMj4k9xZYir9giRsAkfnNjPkNjO7c4L+aZ4bm935gGKEewVa/veR1WctG++ogGW+sSe1+ass79OhMMf8iGmRK5Uzw/ZPT79pE0F32/R6ebA9sdcyMerb6N+ZpMX3P/dwjnFctZwrXgar5J2QLZ3dAI5Y09WAQltsZ8fcarisKzrcN+KdayZOsQ3Bi/pc7R+/YojaHnqaJYMp4CsLaq0ZRF8NUs8ZK+Q/8RW7uY94oMA3MgTOBLk73+aYRxHcnj5CNEiMTDmeN617g5WnzPNd/ZcwPTKV9AZnmftbe+CDbrSerSyjxsqc/xGMMa6iYN8ceIbfET8PkPD03z54SNUZ4aZS3FG1ImN+NGIO1fB+55Q50kcADb0baMq1TQRSmV0Rep9sYPWuLGc6y75Nb6/wudJy7uY5ZwXaBTmxKWmP1NlrOEuqhhPLTuDb536BL4RS7604nfpip3KXqnV6kraVJxjF6p1BhcaHPeM3Qytm+ef9k3zT6vXs2064rUP5sftZh1hxe4l/rsTgh4gU8P8IiHYO2Jfp9rzX6N73DakXykm6/H8xWPIFgFkALOGYR6Sb7F24y0c3rWcTbXjWSAPt3AtMV/TvmCwKRn0dUDme+2e4cMmbVFlplIevP9YBmSPiLL4kY98hHPOsVeJ7ycDAwN85CMfYevWrY/ktv9pZUG0mRMtraMvJ7eSH67kn6EqfTrCZ7s4ESlcvsRLtWt51ZCpdd8DYMiFhxpJ/aGvOS+kVi/vpABHU6vVLzgDSDIB3sATevsHFUC2u560ab421LeAb6bsTIsR6/75is93f/rFlMogkbFeHHtBZMkBdGm7ySK+czwvVBqWZKgSSH7Ik637Jil3XWMofUeDxK713Q0jxjMkbZmuJwDnZ8edROy2OTSSTNufXbWWbpqW+zs8i6AREtPm/uXJvQflIIeGkr+/Xn+O1nLzScx3XUxKkryrcHisUGqAasRC2tZrNq4pnDfJGIHfP/OYHIyo12cIV0u+9KRnAXDDKQnQnh7dZj3nKGPcuy4BMw+sz5XE4wZP5bNrkkVhn7OGOcPhMMnYkpbLEJdKoFNam6KD5/g86Caa5XZ3P99YnXyPplfjfrZQqSxQqSRKh0lZzGRweTJmhlYUXQZlbZvsY/3tiErPa9xra7roLRvbbTtFOxfg5+K8wr4bBpJYyK7rcu/ECm70HygoH3OpFjHq+YDgtnVJvSIzy1SkkFsEcDXPsLZnilFcN+KB1ckYnBOD/BuJES4WLj8/7fzesdfyFCBJQjA+uEK7zjX+U7Q4w1sbRcumqUSaFBaAcCxkcPAoK1dt721bmOlAV7K8tp4rNtgVuX7fKxPXAPxtERJp1vq8Pd8XTwPg8xsCjjpJv2zVl5D2MJWw6nD/6AiQxBh2NOq45CvnDfD5i7Zx43Hb+Kb7XO1cmZrurYkn+ojmgRyv9ajumVI9EFeo1WZwnJgFGhoYe6TSpkJQaWpf9hqeDsBCpcZ0xQR55epzv1TcqoJYAGTBDL8QeX97svyOtr/pV7jxuJP4wdYz+fbJ53F9/cLS+wA4MochVTPWDqkpitOKxzWTlrD3k2Gm2MR2NjST+eqgWKntV+Oiw0W8L6ZCfZRxRk7ez+0nJhCmWWuwv1EsAD5VTbLorlt3DwA/SNfUGTHMfaMLVC2Za3si4apTxpkSo1wpXtT3exUlue7t3kM4fapLH6kIvr8i6fc/XOkXls9YuEwbxhdLMxeVyUAsWkbmgYlkfY0cwS2jbq9sCUBb1Aqp921Gr/l6g2pYZ2hd8s0/t2oLAHcNu3SUWqC2ckO9dgzmc7ka8truAzqk6/eAmJmsZ75So5iUXhWBu0gt036yceNtrD8nQhh9ya0Vv/uhVC82faG+36be6a/H9IywFonNUjSPIXlEgOx3fud3mJgotxKXSaVS4Xd+53dYs6aoLP4yy5xIOo+a2n1CMVHOKUHodSpEIh9k9wpdCQ4r5aDLVFrNyecoSTHDLL09wAHyiX+4xOpwqI9H4DDjxAhq2LPxtYKAQ2FOmYqlbpXLANlSqOfzov8gtMlUH2XM9JBFjmDawh9f8GvaEhi6HpFjp/7NMojfCJF0+tIepLRRFvUCuZBQE0vbb0z6biWP9ZitFTNOHWEZlepcXx79gm9XGGbrfVLUG5kZI4Va2lae52BVv8YRxnttETLij+Tv80qLJfwI4wRGbOKCJW2ICtcz40O1mtBV/NjT3rftHZRRvGztOZb9s+miFxv1u8Jw6Uq17+ae7JlqnYPOdAGQHUwXobpXTrkCuF2c0ftbEHObMG3NiWQKpZr5UTUYdJR0x/tQDCfVSe06XwlezKetqXFU0b+HsACyyXT+Wj6xU9kqIe6vZi0FkFUrRYqLrY+Zcuz2d+jUIipxMdkFAEJyz7rkHWeAWtud/m/OE/a2CevfQaU4V9eo9I4JlxyN0l9a1FKDiB5Pk8mMAcgiS+KmTKb6GNZcpWhyoQh19SjXiZxmvZt1HCfz2p8LQbX3no8O9FfmIWG2ZM9TcQS+koREkACrTFRwsKqjGyLLZEja19GpdCy6bmfR7JomGDqczkdqKN9MpfisTqU8hmx/o1MAoPo94eGhdb3fSxlzpiyI/nT6I0b+fTO7HhTn3mKtz8UVjX01p1QfOTwwzD0r1lMJ87YeqjiFtX63s165p97OAZnM5QvVBvVuPgZUw8zB6rF7cVQPWT8vF4qHNTYSi8xXarT7AH5b2vulS9IBw5O+X9jj1YoMgwO19BmMGNTAbzEQ96dQ760ujRr8WJNHnP9x5cqVvOAFL+ALX/hCoS7Mr0SXbqrQqINEBWRqVjBPupoFu3Ct2iG81jLrPrdmTOYFS1lyngqeVIW/SpOBuDgp76e8DkQkfKYYLW1z7MdEoaJ8SB1UzYvF+04rpXyVHitgGYesu472Wxgsvf+AbdXxBokNmkjk2tviEuEPZM+bTSj6NWMc2u1iyneJ6PvtTTETALhB/xpjRxm3Kp6qTHp2pWT3xErrdptMDeXK0/IwB1Im1UZdPAVwAvezkQcx5QCrCCompay4eI+08m2HWQ5AtZYsfqvay0sV1EwqhWQT9kXtYNz/XZQBsm6oLxKddp04tk/BZiKDmpODnOx6kQHwdqdFhxve0orPglLM1SLZfDHGYaVd+QI+OZTPQ4fS9w0QVaYK17pWPLVvO8wajW5aI86TeZ/OxnKlqs9RnfnF+r3hiVXGTaddt14TljY3ZXP3sQCzueEWvixRaowuVzUU9MxDtpR5ohyQLWg1GQF86ZIlLV8K2NPa2NXfUyNVOI+wjMAwEi5T+tJkVZ9rZgeHrLU6Afb1WYNiJc7WMZTJbu2Q9q4OR8v5X+TU62a/THfAe6VOg1fHS02vIABIRsnH6WFlTNS7/Y2JGZCciO0ZrDNwV6ksLAoqzL54JDWoDs5P5duqRSOrbxi91G+1eyDWPGSm10IAlW7+rcs8gdb2ppcdkJW+4+iIkXr/ECsKxxxlWenbKZtrTdlbK0+VduUZF3LtiWexffk67fi4Tx1CM+dikBp6ItdloD3S2z4i876ztyT+yyZZj1ScagV9RRNRPnd0PJ/JRYf/EqznfU8vviu/VpwP96cGRjORtRBSW5NssidY+hr4WJJHDMhe/OIXc/XVV/Oyl72MFStW8LrXvY5rrrlm0SKd/6/l6quv5slPfjLDw8MMDg5y9tln8/nPf147ZuPGjQghCv/e9KY3PaptUQfJCoWyOK14MwRoHjLQlbNOYz9e2640zw/qi4v5JQ6wMvXClA/IiajY0fsBMkiUsbJF3PU7OG1lRBkZeqbFAllYfplMpzEf05Yg8Eyq2Be8A33anr1mdSJ8cMBhoKu/ual6o1C4eqZuV2QdYirDCTDIrWbmQjJBp123LKzCap2eq9q9U6alSrUU2+QgK6hU+wOyI5UcTNUVb+aulUWKS5kcHckByYpu+f2OMkZoAI/lHCgct5+V1GqzqD26K6KCUhApKd8PpIt1vZZ4fVe2lmvH2gHZ0rKM7Y/7vwuTYpIBKNN6LxG0WgPM0+Df+DVt30F00Bcp/W8mnS/MPrm7njxTIwXVtUVoHQBOt9xLt4e16fVy79ysyOeeubryt8gXwG7Nvlj2rzVoUBbTDKgjTPZA2f7UC+dqsVHQnEnmlEpkX3vaoqZ5WNQ7hc3kGaoWQDbpzPcU9rLZabI+YGs+AL8u/8F6zv5hSZluaD6BY0YcyqIXa7W0U2HLAFmtNsvG4bMK9xtI+61ZN04VFSBnMrygv7sV6Rg+yAqq1TnN86xS+o4agGx6cLQUbDzEcaVtmqmq66fhIasd0oyfZ8/cRoUOdZm0eabWoN4uHyeb2a79btSmWIiS4wcdva6oQLKSPOYwGz8AjT73UGUVxZhFSAyfMYKgsrAo+DfnhcxYUpf5+nm4WgQzVBPadquVzFdVxXC7q+bT0GhmxVYsa9qNootLcq1Baa/dlslRw0O2TxTX9gOsKKe9Snsslyl7auXHZAbsVpAb1/bUHKK+3kP9vr0+KgRDnZHe9gll7dtdX7zweib3VZN1r658n4Fp3WC5RknKIxeJQXy4j3cuAZf/TkDWu1IuIih+tew7SFHUtdb6O/tefcE9Nkr3Y0UeMSD7l3/5Fw4ePMhnPvMZnvjEJ/Iv//IvXHrppaxZs4a3v/3t3HTTTYtf5P+yfPKTn+TSSy/F933+9E//lA996EM86UlP4uGHiwVczjjjDD796U9r/173utc9qu1RPWR15hlrJ4vTYYMqIY0Fcb9CB2o39vSKEptytNGfqjQrhjnKstIFVyBZERUn1T2s67sIPMjxpdesVBfwu+oA1690xMkU7fI7HG0kyp7NK5JJGSCcEqM9uocpmaKwij04qcX6/gGHlS19Atg/NFygABwYKQGgRNSWtQDZW6ylwVnezTqkJV6icfD0AkABOLBynb4hbYpjWJrMNP6m7OR4HC9EuOUJCOa9BrNpMhDVQvrQqqXTjI+MJot9J2qlWeTsEgmfh0moHdnbGONIz8KeyW7W43ldfCP+bUbo1vc5J1cW96bKUL2RjLGJlu4lyeobqVKt54plUhjavvC0/KUvlgCHB0aQ2CmRzeYQV/ByviJeom3fjf7NVQV8ujYAolgYePtgMp2PBivZMHAyAy07/clXikeH7XJL4owYYZohcJdmZMu8Z+1BO0Awn0kV8w5eWpLAJWItyXy9U1HK1dTLzdnk79VN/f0Oz+XPuVNT6JW7LSSeglpttlcg102zjH1l80b+6fxnccs6PVmIo3i3Juvlc26DeStYerhRISqzqBvbTTpwRntV54njuR+blAGyRmMSr25+d8FAes1+BrsRJqkYLIdRA5BloGRBDHDUGaNRn8rbr1z7iJGa+uDYylKq1c4+gOzhQO1X+vtrDz2EqyQOOmv/XQBsYGfShoFhhptLT/c+MrSf2W4ad+oWi5hUaTMhE8Va7e+jM31qryky4d9bum8/qxMK6KKURX3/To5P2lnPt++vF8GMqB3BcUI6aQp3tR88VBliJP0p4siqJA92i++xVkLB1Buc0tYR9ANMZt+wzScPxFu03+oXWqqH7N6hY/MQP9xwCsZBVUyvb9YmCYy2c+OlmlF71zHEpN4wkMxzyudl+f4cfD/1rp9x4n5lHlokS+f2gfI5TT6CeoS92yp/lxntVLl7yD4PCSRjg0XDrSo2w/Yr5T9SWUp//A+Uf1fJ6lqtxstf/nK+9rWvsX//fj7+8Y+zefNmPvrRj3Luuedy4okn8v73v58dO3Y8Wu1dsuzcuZO3vOUt/NZv/RZXXXUVb3nLW3jTm97ERz7yEX7v936vcPyaNWt45Stfqf0799xz/11tqEgPT0njq2YTdYlYH+0E4MDwGJEy2bhGYoc7lTTSzbG7kalnxJwCHqxtxE3rNQ3Edg7tPWzrQ0mRbOjuLGy9k1OtQbpDMlmY7panlC6YwolZUcnvZyqR86LNrGj1BXx7FI9LWbv7KRF3Y09GkS1cPh3WpNkbfz7mFZaEh4eHCY2U+w8vW45NXCK8akx1LFcGY1d/d3el3zMK9e9QmzzR+hwPG7EkEmg5rUIMWVnsxwqZxC8siAa7WQ+LpL7P+puauvfmrafgREUgZ7OYP7TmeAC6sk1oUR6y9kDSH1URUKAt3sUpSCAwkrDsd6aoylwxDRUL4UNsZJZBhoYOIkREJaxrfawbFkHV0JBujDhWX/94XExnD7BQqTJdaxQCvWu1GWZmJriFYoKkOzlF+616yGLHoXL8gYLH6aZlSZtr3gBnj19aqtuo47/TLI/NgeTdL5XCdnczKYzcHrKXyfhFN/HKDMiicprNL91mAkAcJevWRpL1Ywcn0E7nxqHh3OsxezgZa2Zixlddk3u+zX6WSXUqAVtCSAbT7z8mkzbsGE8MCzccf0qvL7Sbg1ryoz1ZJrOSd71Jbi9se7gyzHTFDuodITFru6kShj6d2QltnigDZGXiuhEzy4pAcZhECez3vQWSjcYacfK0Pgds4Z7e33dzsvat2lGuaLY8fY3avWpjqRHkdk7v/d1o6UyJu5W0vVmK8LiV9JPW4C7ilArhypDWbGL8zOaYI43i3G7K6+Qn8nvXp7hx4CG+499GxY2N7y61a88r6fMHpzu4Up8/l8l8vtmfesQ3BreUtuMetjE8dNBK61TnYXONnRKjHGAV3mDer3Y3NhTKQQgnTsdAcpzaD+531xE35vAFDM4+hDk7uvU5Yst73NRdWuwcQKxkfF0u7XOpKg+IHHyNprUJ7+PE0oQiMnaXNKfvrzkcSOnfS2nHvprD/j4xSx0lPhMUQCYEo+08pEJdv/fU7LUTT9ldnFtvGUvWQEf57ioby41jWko8rLSU3ql22r1svA8M2nUbgGh+XHuHQ02dAbN2YWlx2J2BxGjjzWe6Xd727JrbBx1mPbQSAFmrBweP8EL5ecrENoc9k2+wieJ8/FiSfxcgU2V0dJQ3vvGN/OAHP2DXrl188IMfpF6v8+53v5vNmzdz/vnnL36RR1E+8YlPEEURf/RHfwTA3NzconTKTqfD/Pyx11spE4FgTaykDlYy5rlEnBMktXtafoW7Vh+HBLqtozSkbhXdTp6VMqxOMbPmOqDY6X7K+VSO2w/EjLZdbbHIvA7f5tnMUG4V39K9u7DtsFjOdVxU2H4KtwHwc+c8viGeX3JFwcaRiDhLr2rpcbd6O/ta/XaOr+JIoz8n2Oahyyh33+bZvcWn8YvXsP+nr9USKgjgTH4OwJ0jLtsH9YVlvlLhzjU64Lxr1UZrO7IYhuVnHOl5RMyF6nqexCFnnEOH9WsEc2utgOyuTacwPZj3o1rHxcGxADK7InUqt/b+vpIXWhWQupzHj5JF/dtcxgI1rX/du/EEYiNbXyDbXMAPC9d6ePVx7F65AYFjBWQr2dezIquBzJWZxFt2plGTbp9Yw085n5PCNZzbzb0Vd7oP0xK5IqJaUKVwuJIXgCtZs/ZuDolZQjU5RadogdSSHUj9HZ3xYLnlOpOTmndqv11FSbpl/ZYCrcVxYqYmV7GSotLyEy7kvqMnIQ4mz2uC7Z+Mn13IyLm/GvC1NblNOCqxhMYKJXph1u75rKb0pm/z7J7HdDH5jngxLSpEjUnr/u+5T2V6/gRrMH7W5j37M+NDZjWXnJH2h7ao8W0uI0awdu1dOKlHdPpQomyEyvvddHA3AzPb2dROwMp1XGxNTrTs6Ck9q+/oSPId1keJkjCnZCC7zr0YgFanpo3Rh8dWcGBw1KroCSSnyjuKzyocrllTTNgBsL7i4Jc7lWl7AQd+/usEh3PAPsQMW6Q+b8vI7Rsz6W3+GXPOHNmbF8A4Rc+IKV0CNjV1g8mmeT2H/nHs0NYbZzBXBlt9PLIPrj2B+wN7Kv+WyL/FaXseoBK3lH35WM56f3df+q2dqDd2XBnRbg2ysDDEiSSesthxehlwy+TUdJ0DcL0Q0Zhhl3uYG7z7UBfZXde9luZCo9dfVXHjmC0dXRl8EnlygxNJvt8Eh1gl9RqEmVzFM6mMH7WmHb+MK3t/26jBV/ICxKhi1BEuX+f5hbG4du1dvey96noSC5d/PO0ox1Udxo/cAUJqMcyNjTu0eSWT8abHBqkb5Ie6MwgthlLSiuaIlFF0IndpnvzF5LijRwCYdkd62SEBpBLeEVSafel2pucXYBPF+qU2+de15aERav1XUOMchcaaWIrh6+xd97BqWjcc3rJ2gFmDfaEm1jLjhHXKokiPkaw7mozjKUvCl0zC6Q3a77VHdU/VEw4vvfwHgBcOEh8e0batS68ZOYIvrAssgCyRF3EFb5d/at1nZqF9sfwcoOtCj0X5v5L/cc2aNbzjHe/gGc94Bu9+97v56le/yg033PB/41alcvXVV3PiiSfyzW9+k3e84x3s2bOH0dFR3vKWt/C+970Px+DRfu9736NerxNFERs2bOBtb3sbv/M7v7PofQ4ePMihQ/oAuf/+RAn47jkncNKq73COeJCfOufz5eD5vWM8Qh7n3sAV8uXMiBF+tOk07j1+Jf+j80GmfN060k0/UxwLYsfluzydWzinENvVFA3+Ys1vU13dxA9hNs2Y58iIS7iar/MCdohN7MBer0cAE/Fh1h/Zz65legzL34nfLBx/Kd/ixzyp7/uJETSDCtc87QUcHppg94i++AXBPNPrf8B3xvPg6QE5qxXnDF2PfzvnyVRki4B2PqFJQdgN8PyLtbTaAE+Q1zPCJN/iOdwvtvJ6Pk0jbuKfVAEpicWT0sLEySJ+Mdfwjeh5RAroOCO6lfudE5gTg9yyXi/VUBY068iYlqhy3eancPvmM5iSoxw1kjzMiSHeM/THuAP6whpJn+8tvJZs/j5L3sjN4lzmKw3+7vLfpSqbOJGEyMFxQjyvwz/yvPz8kuG8nAOc1L6Luyvb+Imwp3X26XDi4Z3cvOJktosTeYP859IMjy+QV7CC/UxwkDrz/FBejBSqJ9jhc89/PV+UbSOldyKCmKdyFZ/jVfk5UvCj287nnCfu4nyu4zNGVr6/Fm/Hf0JEI5ZIsR6cGJAgciXMXPi+KZ7HVfIyqsc18Y4LtT7SbtfpVKoEQYsFanyLZ/Ndnpm3JwzYf2QT2RDbcng3xx/dx63rt7Jjwr74nt+5hRsqT6KTJqFZI/fQYI67xSncu3ID75PvpM48LhECiYhhy+hesGS1aooG71v2foK4TZUmHcObcGP1PG6kmB7/j04Z4AMnd6giezUC+0lzwW4NvYRremPnfrZajzHl1tp6fkN+prTfHHBX8uaBP7PukzjcyOO5cugVdOWrelnKEkB2M8vkIY6ICa4Qr+R+uZVXjf4D919Y5365jnkG+RAtDjvJnDHRPMx/lx9l3XM7TAUncD+/w7QY5a18gqpcwDkO/HQe8R43Qp0P8wb+moobAjHDa3bw0AYd7H7BeykX8x32iNVavFzsOHz5rIvwZdHrLJCcG93Mxyz4xozzya8XETuSMpdbM6jywSecjXBzr6pLxFO5ivs4qbdteN8FyLWqJVyhq7GSb01cyl88dY45thHh4suQl4rPsJY1/C3FuT4Tnw7nLNzEN4bzsbLqjE/zuNlN/Cy1rNdZ4Ml8l6/xQnaK43kD/0xNzhPQYaFWDsik49BNAcKm6F4OihXMOCOF4wZbTX5/6s/YPrqRz4lXafsyr357/0r8FU2c+tEewHRkTENW2Lt3K41NS6cpqrS367iYzkmDTLojRBVJ2837iew22PfQGZx30o/5vHwlM0JXbM94+G7u3pR/ow3s5M1H/pHtU1sZrbfIwkYv5Zv8E6/vHXfOzrv5+caT2C028Ba/GJdYlQucy0/4Ki9K2qEYpjzZJRQ+PxBPKWh7XxUv4uvyufihJHBauE4XNQeWOZ/+69ipXPHsGP+Zr8Cny5yv6wjS4vQ9HHW4cOEGHmoc39v2+oc/zdhxD/Iuspq0gsML3yQ+5WGa4gIgCem4kB/yfZISExXZpN0nUci6Qw9yx4oVdPyAXWJjb7uYXclMZYhv8hzujk9hl1tOfT2B7XRlUnIok4A2Z8ibuFWcXXoewE0j5SBmjgENIOQeMgiqM9zKmVzLU7hbnFJ2CQAukD/gqed9inXyBt7PH/W2z/s1vvjkT3BqeBf73adzt3My9zp5P9u29YfslWv4Eacl9z/R577NQ2wXW3m4nhjkPL/NCwc+x5/z9r5taO8/mdk1eeKZV6z4G/6QD/V+n7LiA/wb77Gemz33QZbzLZ7DA2xidnCYdlwDJbThySu+zCF5OQfFSv5hc8yvcy1q8Vp1ZjyDm633Uo0J/0P+MaenQOxpUw/zr/RPAvUfKY+ahyyTzDt2+umnc8YZZ/DVr36V888/n7/+679+tG/VV7Zv387DDz/Ma1/7Wl73utfxhS98gWc+85m8//3v513vepd27GmnncZ73/tevvjFL/IP//APrF+/nre+9a38/u///qL3+fjHP84pp5yi/Xv+858PJJb966rn8X8qb+LvAz1ByAmdfVRp8RY+2tt22FnOLyqn8nFHXxBnZ8e59ZZncMddl/Dn8p18RryOO8VpHBG5xTejD0JiMZxV0pcPMc0rjt7GSRZrbUabqMom9ZTD/Jro73u0svXywVJL1WbuY1moc4GH5DQnHcoDk2cZ4mMr38Ct67cUwBjA+rN+wsdWv7H3O5Bt3hZ9iEY8h5CxZvltiyqzYphpMZr8c0aYr9SZdkZoi2Q1CMKQ8/f8ghd0vsiL+Ve2yrt65887NaYCh6mKy4w3RJTGdg0ywwoOcPnMpzRayTpnB2/ho4VMZ6PyiPZ7TObvwJ+FP47/mCvEK7lbnMI+Zw1tJ1emh5UEIpHhqfrDU0b5duPM3u/nTN7DRTIvyt0SNRa8OguVKnP+AFNijEmxrPdPVQBGZD5pjnGUF05eyfhCOX9aILlgz01sjhKLoKpUN+I5LW5mmCmeyA8Y2hsxeetJvIpP9vYtjw/0rJ+a90s2e0rrCg7wTL7G5unc0j7QatKUPrfe8gxmd6/mJbdfxcl7dvC0/T/ondd1XaZ8j2lviGlnhGkn6QdTYowpMabdL3vPkfCYF4NMi1FtQY9xueeeC1kIB/hj3s+XxK9pCSsGuiEPtnQgsnxuiifddzOj8zll7TXh/+F4uZ0L5A+YaB3kkntuxokTpbA6I3hd9+963sBYuMyJoV6bJ90xbtpwIlOzOSgajGc4W+aFzDtOhRkxonkBsuup8sr25wjScdoVAbNiqGexNmPyVCkDBpc1v6GNHQAhY2ph0occGTEQ5kptFivVr0yDKcfP5rG8X+Yl/KV4Bw+Or9FSRg8yg0/Ib/KR3rabxeP4fT7Cd8Rl7HA2c8BZyWEnnwvPrf6IlcsfpDu0hwv4IRfLvABxS9RZ8OpMi1EmxTIOVV0ecjYmVnUh2XLiz/m9E8/gW/VnaW2dFUPcxSn82VC+JvhK6vqsDqEpvox47q3X4Yddqt0Wvzn511oSIdC/zwP1BxYt/DtVqzKpJBUYYZLzuU47ZnT7S7mFXImcFMu4mku5+cATeRcf5mrxTHaIzRwUKzkiJtjvrOKv+F3+F3/GwyK3gp8tb+TX5T9yiky8RMdzP9HRQS697Tp82WG93Mky5xC/3f0EF8lruEx+lVXs4fnxF1gzmXvOmqLBtBil6+T0QXVdeVz00zSlfCLj8giX3/Jt1sUPFZ5/KHbZNHQHz+arPEd+Wds3SPIujw43uPWex9PpVHqGKldKXt6+kFMeejEzk+W0LFNUQHaXOJX7hzZypDHClDdKUySgZVDO4AufIwe3MLN/NW/mo5oXaHDyECfdfx3PlF/rbevsGud5Nz2Ds3bN88B9T+BnNz6PVqvBU/gO58mEPTM+O8WZu+5j4xF7wox6p8lfdX9bq2uqgu838NeF+cKRMY0oWesj4dPyA2bcIW0tmRTLemtq8nyJfhE7Dm0/YM7Xwdo8DXZUi4beVhgwfoducPJFG5Xy6Lkdpp55DV9dd2lvW3NmhM0/OMhx4f1UZJP/wZ9wjsyN+qNtnbY63JznKffcRBDqHppWaxnv6vxvviZeyP2uHl9mysLsCL/R/YRGJR3nENu4vfScQLa1420yx4BW9qNXCF7AfZfu5EPiD/mZyOvB2jx1kBjxHSfmJPdO3i3fxavl/+ntm3EG+ZPgXXzFe7EGxgDG/f1attO/P/01fK/x5B4YAxgRk5xV/THPk1/o+yy3EPENxQi81t3Ff5OfwJERy+V+jgvu4H/K93GavJmNhmcUYC9reBcf4jviWTwgtnDQXcG0n6yJmYy5R7iQa4FE58nizG3iIPlT+bssk4eoxvkzziue+HghHf/tYTbd8kqe2bm27zP+R8qj4iE7fPgwV1xxBZ/97Gf5yU9+gpSSE088kT/6oz/i8ssvZ+PGjf+u68dxTKfTP+4lk0qlghCCubk54jjmgx/8YA9YvehFL+Lo0aP85V/+JX/wB3/A4GBiUb3yyiu1a7z2ta/lmc98Jn/xF3/Bb/3Wb7F2rZ1GAfDmN7+Zl7xED8i///77e6Ds1s5ZHKzolqST5h7khJ88l+7gFJtH7+PtQx/lz1e9FYCrwmdxyNczIFUXhhjbt5brl9f5hZMo7CPdSVZMTlENXdbKfVx+i+Rmbx+7nz7LFKO0OxWk7+CIiIvntzM6+17ePbyLG5t/w66BUeYZ4BxuYPSHJ3P3xDCr1v+UoNFlZGQ/y9w9fJC3sae9iVVTXY7KcW4Sj+NfV1xceP6VnS5HlF70wavuJghH+I1nJ4lIviRe1utlq+Qe9gmdIvXV4EVMpYNxQ+chzjp4B0cePI1f43tUxqdYW3uQQ9VRpipncdSrM01MhyaVgWTSCsMAN42JcibHePU9W9g8u457nZcQrt7O24Lvc0N7jmZtM7HXIBJJGtXZaIYmMQPrfsYznWSRfPrItziTm7mhcz6t9gBnz9/CQCj5A+cvuau6hWlnGSvCGZ7Q/Bm311byQHA8K8Mu21o/4h2rPwjAjuFcmVkR72eD2IFPF4+QifAQF+/8Cfu9E7mvfRFzzig3bPZ6wHp/LVFWVrUOc/q+aeK9T+CtjXt42vhX+cWaOaYYIQxr4IZIIYili9ceQbSHmFkYZEY0qVTm2SB3ckHzRzxUWUcsY7ZM7SN66HQ+Nvd9blq5mi+dvJb7h3SvnUCyetkDvNv5GrfJM9jBJuYYoEaTp4tv0qbCzfIcJA7nzN7C3pmt7Np1Gp7X5lKu5BT5C/Z0NnJ28BMOsIKftS/kcLSGrvRBxpy+/RCVuUEm1zU5MfwJB+ZO4AW7rmPXsoc4MDLC8ZNzjLcH8VvL8SdP5/HErH7wNs5eM89zVvwLN8nHcTBcRdfziHAJFyr4YoBQJtTgqD0PRAgBF8/cwqqoyvenz2N3UMUZmUPWBa7nct1gDni7O5vcNPC/2XVCAsTG549yuJGYiDcfDbkxpaUGYZfxhZDjWsfRYoFXXXs9+8Yq+O0JVk2fz28edy1D9SYL+57JMzqC86Z+wUMjQ1x0CG4Ozuf1E59lx+haDlbHaYoqzsI499YmODw4QuS4yDSW8OQjc/zWVd9hYeo6zpv4MQ9sOpXm5gpeY54YByHhCeJ6NnMfN8nHsYsNzHRHce8fZOiAw5tWf5qd4yuZD0boiioxkno0y9MXfsI1Y2fxzcozMSUs0f3v/PnTeF7jp7TdKpODDWaHZjlz7yRD7k4eOHkXJ7CdATHHbfJMVrKPyo4GPzp6GYdHx3CXT3Lt0OO0671Mfoatswv8vLOFaNk8A3KG1QN7+avUIptZoCvdkPWTk9Rkh0H/KJeNJmB/C/dymfxKjxqdgesN7YdYHezCI0RGDsNiksucK4kil2hyDUFniN9o/pxLGju5c2WNaUZpTq7BGz1IjMNP4qfQdgVdfFaPHOYrtYs1C7sqn+L1PeB1tryRV3Q+TVhxuI0zOdJex1XVpxhnSDqxYPX0EV7z428xNP0gQ8e3+PDIb/Iz+Xj2s4rTuZkVHOAtJJ4PbyI39jx/4UrOnNvNgfZGPr4uB4jDC7OsnD6KAI5r7WfzxnsRwBPl97lOXMJ4OMWXV43SErrL4pPijWwePtQD91uaexiJp7i/spaj3jBSuLRTb9KpR5tsbf2I56/6GwSJ1+b7X7qQ6opVHA43cDxHWH/dt7jggs/hOBK/spc38PHevQK6PPsXP+bh0QmCsTG61Q5hZ5S43SCOWzz1yF7WD+3h+1v3MsAcx089zOvuOoGrz/gpDMzzuPbPOG//2zj4UMDDhlPj9OFWL9Pmr+18kBX3foO/f8ZlQFLS5Rs8h9vXnstZd+zk3ht+jQOnHQ8jEIQ+ELEhWsGW7a/EdDCftPcArxr/M/5n8OfadjP90oCcZSt3U2MB2XGJIo/j9h1gXgzREiH33Xc+m3fO8kH55/xYXIgMj7LiwTsRKyWv5FNcKK8FBFunz2eZHOQFnXPZHu3mvv072LH3OVTW7+UFlR+zZXKewTkYWTPG+/bE3HPwPnaO1fjx6AAPBcma6XS77PrCGjZeDKRLj1SCKZdzgNd/6yPsdp/A9KUhHQLO3n2EFZWHuH1iGXvi9UzvPY/QEUghcSrT1P0IT7p0FkaJIjhffoPj117Dz+LzuGvPk6mv3UkXn9s5o7d2fZ3nYxO33cY5FOHGUc8AuWxoL6o2t2zlLu6sbuNGkYS1LAuPsPbBaRxZ5+nX38bQxFXU6x5v3fhn3ClPZZIxzujexmzQ4BZ5FpUHNrCtNUJlweM3Dk/zvZUuHztpBIAfrhvJ7zM3zabGHYwwxTwNrhcXa21dcXiGh/c9gTeMf5Ydy9Yg3CqPX9jJz1YXs+r+Zvg31BZGWDm/mzic4bbaNj4z/vLe/svuuINvnJJ4vH7G49kvkmuslw9yHDvYwzraQY3PyZcCEMgWG4/O0IgOcUnre/heh/9vte6t8nZ1yLDJVu5hnEM9T+o3whdwxE/rNHYPsr59kLoM2dx6mPXju7hX8Z5nQHu9fJBV7KXBPBe1r6eya4KXzXyB00Zu5483vc/6PW9Zv7kXXvLEo3cSHDqNi7w9bKi9H58Oh+UJLBMLvJrPs6NyFh9bdrx2/md5VS9R0XELD1ObnWMo9ohijzjosJFdrG8O80BjgLTqCtfKp2puMXM8buAhPsp/54Ejp/LeicQ7N7u/DhuT/buvHmews4VllV/nrm6HtbfbY5wfC/KIAdn8/Dxf/vKX+exnP8s111xDt9tl1apVvPWtb+Xyyy/nrLPsxUYfifzwhz/kkksuWdKxd999NyeeeCK1Wo35+Xle/vKXa/tf/vKX8+1vf5tbbrmFJz3JTrcTQvC2t72Nq666imuvvZZXvvKVpfdbvnw5y5eXW9tMMAaw7YSzOPc5L+j9vukvPtKjRmVgbHhmkhV+k/tqq5lvH+Howz/izlMTekatOc+rP/txBuuvRDgDfGh4Ldf48D+2f5WLtu1JKr8rBtt1d/5Plp82zMjTnsvcv/4N5wxcnT/r3CYu3jjNLe1d0MhTSvtRzFN/8ga8djLxX+IIrr5kmsNpSm0hY5xujWprFDU2+OuDRzjpYJHitE3ezjv4U17L57TtPyWZhDce3scz7kwCmmM8fGLig0PsSoO539I6nWY4xzd2/y0Mdjj15WlMT9qDD84u46c/fx8ny2TjqfGpsPtUBi5YzdMvnuAHv/cxThnN6XrXH/weh/1LWF35McMrcwvXyMIkYzdXiWM4uncdsv4yXvUn53PPj77LNf+QKBx3LltJuHw1G2hxvDzAA+Lx1MdbLAS5AjTUnON1O6/glBN/0Nt2xz0X83t7/0fv97ffegFfv+u/8WFyj+1AN+Z3bvg73tt6NTPrR3jtxALrbjqekysfZmH8Dm3ELvuIx9DAqwk2buawmOErlVt7+x7kXH49vIITLngOvCy3pF0ErPnpT/kds2QdkhUrduAQc1r7Xp4Q3URLTdsEPINv0jh8Klff+UzCNH7N8xIr92r2sDpIYh9GW4K/ePqf4Lp9guX/8Rkw/A8QAoeB90yBEFz7219hUz2ZiX/c3coAN+JyhEv5du/Z169/PZs3/Ta735l7BWa/8gbwfTZ99zv4K3+Hv/37WznxvqMk5JNkTJ16+AbufPU0RweG2T88RuCdyL+tTIwyKyePcPkVf8nH/9t7aXoO9442mKsm3/O8HXcSLAwxM5Nk9RoCnuf8Nd+fSTzZk3e/iCcMe/gZVSgE5uGomONGp8rRfccxsg9GmAamGai2aa2MODw4ghSCyE28HaNRlTPdAdZfcS0ivda3v/3r+Pw4+0g9eQI/4gn8iJnmMm479Cxip0Jnf4Wz9g5wWec0BIKr6fKDrQO8696tHH/Gj7GU7WFHSfkGKV3OO3oxG+IJkmzMdWAFsxPzTPCvyUEOPJ4f8/Udl/Ll+5+d2vysxgAAxB5JREFUbDsKX77wCCfs+wT/IHJWgEvI2c2DnHHvL2g+cR8I+AVnFO772ROGeNP1r2UK2NeGS2stMqZp5v3IZMv+XTzrzlvZesqPGFr+gFYZ/N/2reAGpqj5bWaDWV4/G/C8lVMA7Ll7OWvOT7w3d3Yv4ZCbxFvJ2iQ/wARVuRxI02w/T36Rl/JZSJ1UI/uO8Hc/ehUjlx5halivEXn4aHLOgruG9z3pAJ/c06JGiyelFmBAS65wk0JFvGj4abz8sicw8+2rFKgDT7vr54zPT1PZv4tg8iDRqx28atyjcsc4fHO1Pe3z9lqiQL9kV4ffv3sIGOL3zqhyrdI3Xr2jzW9tD7ljxQ1kmcUdJMuOHGZ22cbecZ6UhEc2EEzcT7de9BIIYP3kIWq/+DGXzP+c8Wc9leN3fQaAqe4bmJt8Lqz8QxjezUJ1kLXs40nN7zE+sIt5OcygN8yyqOh57CxLPBb+wgS7b/51VoUua6e77B72eYiN/FycB8Nw+wXbWO977A1DkLBNcUzWKF73zM6DrPaLGZhNBfDdvIs17GF2T5077zqZwD2FeQ8OOjO9M/bcu4fV+w/wotlPcfu6RD9YPZ1YPzamGR7H4sRA4uGyZUay9gfJ2vizs97B7NDGTJ/ktX94IfWhgKenv38+Pc+zb07j0aSk1Yw4dFejB8iaShZYn5D2QY+Ld3yVyqWJl2vOOZ3B0Xu5iDYDB89hzV25bjXrhgxGOq1031k1ZljgYvF9TpmtMs63ALhn72/wx2uSZ8hofo1wnnkv954dHT6Ov/HrWiKS8bHdWiH5anWOH6ZxX9V2izdddyVH/FFwBOAyc3gNK2qvwD3+W5wSfzE5qQGDTDHRPpXN20+m4qYMgggu2Lu7B8gyWT11iOfc9iOe9KRPA/B5XqHtP2FqgTMe3k5Ihcn9GzhzR4OnOo8HLuKW0Wsx8p9w5rbf5bI1iZ7z+Xs+z1U3vB83eilRuua5EXgyIhRuD4w1uhGv3fc5blyXJ2nrpqyO19+6i9ceXMXnKruYF+sIhYPyivDiLluvvZVDF5/AxPoMUOT9MgNjY3PTPP+mnzCw4w7cdrLIT714OWKZ3odPknfwLt6TfJUurHiPjzsjEH7AE7/zCd5/974e22Gj3MFOkQCrB5Ynzok1+x7ivK9+jiwFTfPkkwjjACHzcj/O0Kk9UAUwzQi3kuCCCw4c5L7WH+BHktWdFh0huKFWZbeU/MHzruTaL9/RO7flmFTVYkyZgyRWSrio/c2JY+aOuHSGKpx8QcyD9y/NufMfIY8YkC1fvpxWq8XAwACveMUruPzyy3nyk59ciM16NOTEE0/kk5/85OIHAqtWJSvI6tWr2b59OytW6FpIBp4mJ+2B55msW5coX0eP2gs1/nvEMxId2PJZbH3gdppbNyZtGFnGjvVb2JNa7DftvJuqXI5wBomzOBpBQvkw+qrXHKM2tSXPdGqkLZ11W4hGMbA/mlzfA2MAlY1DgPrOJAOHzsCp60q3E0e2un9cyA+wDaRsQtp8QF8IB+Mas46OGnbP30skQ1xL6tUfHzi3kIgBoH7mcmuNEOmuQggXYVzryL5VxLEHcYQ312LDucuoNsprWjyczhqu1Pv9CQf34BrBtLFyzLZVQ5y4cohv6KwwnnjkMFd1EqVs/VidPLmB3k73KAT3C3Kd1uhT3Q4bXHtNG2HpcALZK4ws968lGL2DliUF/9De8xFKxiZbrMvg4NP6gzHzPMfPB4HSRc4f8JjxHAzsyMoVz8Mmjcc9Dn9lagCxPOPY1L2I1ADQDKp88LLc67DlvptxZNzru3sGUqVGSjYd3AMUPYqPVOZaUyBzQ42bUgs9KWmcc6L2fRYtAmv0+U3Ryl5f6SK58cFs/rIDr70jE9btoeiyLtafOThuCOaK7fnpvhxEjNZ9lg1UMcf6KvbROHwq8wt54hNhtGl1cy+n1/VsiOoRMvRQu+SWAw/zorlTuUf+VDunGwb8OJ5BCsFsJwFxtUg5URT/lAgmGemBrn6SzGW5TG4fJnR8jXKXXfvQoY0AbFq3Hse5tSR1Z74xYxDU23O8+EJ7ll9HxiAl/nTqTUvnsIwKNefUODrcf/w9a2+auEEWe9gz9yW0r7o3pEVbSKNCa0d0cWL73BiF+vYTt1W4b9lZHL/jM9nVgGRek0C9PsuR8/+Y8Sw5gcySDRSvHdcSOn1l37lMhslzdtLjDgl9vd/VzSlsT9ybK2LmGuXJLudVrraOa3PbahLD09Htw1R3zhOfYBzf6eK05kHA4YFEmQwkDLaF9j61OV2hN5r3c1xjbrf+nf+1x0l0l6pcYC27uFsez91r4fT0bfsDB5CpIW3owLnIsMO+hQOsHlpXAGOgx6Q1ViQLVnX6OIKDp4GhOmzav4fb1hapgUHYph2kMe2Fdyy4J/XgPP7O2xhymhxR6ga63QanXbyZI3y7cN31K59b2HZn5T5Ap+1tPrBbe29m4pMn7J/W9q9sV6GHA4pz3jKLzqQmlXLiOJkPlFPPPDRLVep0TYCBcI5nH9ITuZl3XD/7EI3mPELxettWhk2HkhI+Tkddo91Cn3oi1/bOr94lcGeSX/XHPQ5/1SrkPTnNNdDW+0S2bb+1d/7UQAfHixEdQ71c0HXs+9jaA3n1hZ+AC5Oe4DovB1wnO2OsGT0eIYrhNYvJzPRED8QeHsvngYH5zJAnObJ7aUla/qPkEQOypz71qVx++eU897nPpVo9tro8xyorV67kNa95zTGdc/bZZ7N9+3b27NnD8cfnbtO9exMldWLCrohkkqXqX+y4RyK+Ccgsi86a/Q/xQArIpobH+eKz8uDl1QceRriJspQpLFuWDyLukYWMybWpLej1PfJ7x6HPDio83nEKQA0jm05QAGRQnT4Bx1j4hYysE8Vm7rNMxLmsntZj0VbIYWYNVfxIOwUYlmyZ26dOwFgXEYGDv2qAuDVfrBPiJEDKvNL0bKIou60FBA6rThhJrlWiF3fTODTXeOqVM0dTC18uUgFkZ21IrjsyKbRA6rOm7+dv0hV+3VidXoZt4/sEDzjpd7W/Uz9q4fkl77sEkGUyMC1Q1kNNKjMbQMk8ZUtcumZ1MSNn3zYoRRwLGZWM5/a8QQYG7EkmamfnXnnzCSutSUQJNx9g1YFd1u3L5meoRF2EAbiF0U5ZnofBKur7lk7Sh/wY6uduNY7TLzrfXE6jlsfmmPXUVsYjvb+7wHwnUfQiJY5RlSx76UBrQcsqOBPM4DT1e1c2DiPuMJTyaIB98/nid/aGUYQ4UFAAjuN+vCNPhzhXkM3XtW36brxBnUemXiVu1jVAdsZ991EbOq1wpbnWcqTQDWl+XFbTJpcHsGc+VKXWbbHK07Pgze+v0woqBUA2Jo9yZDYJpD9uxTB07B3EBgJWTR3F9zMvjgH0pMTpxohYTwqUecg6Tv6Stsq7uFfoIDeIJCfOxMRSMhVJbf2pdmNOmEuuU3fVMs5JS1WZ85rFdSOVblfx0oQRQyefa8w76U2V89WMc9n46sZteq7IrP0iURA7R/IZv6ysmyonTUa9ZzDNxht4kJHhHUsCZFmLF/bXIJY4Rtyk22r3zGizteQbjqY5iDRR5hTZVTO86ge6vjH3qH/LDNgWDS7H80BSB1IKdk0IzkjXC7+R02KrUycQTT3IVH0ZRWJedr/8jpXhPb3zhGVMrZqc5DYlwiM78+Ttt3D3ttM5hV/gEWrPcJiJXgzR6ZN7EAYK9ztDrN48whEjY3mn02B06DgWjDIpO/1iSYdV00e03yYg2zzd1HLd1qP82Ww9fGVFSdKR1RtVnBGOxdCxZWoBGsX+tHL2KMvkiHG0fkwtbIKoIVGBe/Gbr5w+gtNqIlRjsDS1Ez17pL8zb7e6hmYSUPQord33UO/vgyNtVmB5Tx2d0ZDRW91YcsS11yk+YzyhefZbSsv2zc7kBsTpNHPqUBQxNDcFgIznmNz3oO3Ux4w8YnfWV7/6VV760pf+Xwdjj1Re9rKXAfAP/5BnJYrjmE9+8pOMjY1x9tlJzMLRo0eJIn1h63a7fPCDHyQIgiVTJY9FPENRdywK8rLJQ6VW+OVH9iHSjGLt9NRNywfSRclQoub0aVYFBVFriO3OEK5wiotFSwei/vK61h4BVGY34FZ0hdDWZk92WcE+ysBD0O1Q7eqDfiweKBw31UkVUctl9s4VqaHeeA3hinTCNBRoJ7u+ofB2k+d2WgsIUWFsVd16nCmOoZiMzs8WjunG+bs6cWWiCE8c0he1lXO7WUg5WutG68piaACTfaliURuzts7rJScpttvmxVa/22hzprC/d932qAESTNAJq1efWXp+fprSBkWBLH5b/fr12nGIksQRlROUoHLjsesL+1moVUtrPE0c2W87jZGF9Dsa39e2GD5SaflJH6i1W9RONM3t+n27UvdaxSogkzAkc2ujao33YntinlaaHGJsXv/mc36x//ori7VxZqI1qG9t0/JBRAFGwkg8g3t4wPi++rdYFx3B8XUqmac6ETr6WrNxNPPM6XdrGsqN71RwFeUxKzot41yRj3E4QD6HDLftzIjRpm5JlzG0p31aTnEdXLcwT5x6kFaO1kutOratKxTPjtlnHSkJmvl8me11LH3ypXy2sG39QowvYS6GWDfiMzKXk338wjPp7VhwmyWth26oJvTpwPJtLFaQVhUvjQtuh8UyNBMJh5a5+RWFfWUy4rmMt/oYBNmDV5teEiCDpMhweyZI/9YTSbjtZOTFAuZTxX3ICsgUT3invNyO6xnvTfXwZoAsLrZxdVpbU0o4MiJ686aTFkB3ujW89hjxzD6avt1gY97QcZNnrcwV4+odGTExaxq9knMHFmb5BK/lrb3MirnsV8bdiXK28L7dsMbIinqh/8TxChzXLRhbD3k6+HLiuFAva4WSBAVg+YKif0hprOfFPr48KGfNQFLmwHyONfPt9GoGIJsOcUqYMJl4YQfHneiz8iYyOj+L01YN2QGJmm8yFnL2jL9bAdyK8yK/gq6biThmRAG4k4MlWQvb9kyma1uSKc9eGPq09Ulyk34zRYWiYTXq1InCIg15Tdjtvafu3BeYPbx4Xbn/SHn0+YWPEXne857HU57yFD7wgQ/wxje+kY9//OM84xnP4Prrr+cDH/gAlbQm2JVXXsnWrVt55zvfyd/+7d/ygQ98gLPOOosf/ehHvPe972XlyqKi/+8V3xhJJoVMxDFDc1OlEGBodgpSz0wz1SjWjtWsyqbfNIoqK4fIdpX9wVorhc1p63Fx7pi+OAe08ZvjOL4CKGQIyIKleDkHcClOUJkMN+cKzzooTd4wzId2oBBGLjOdwcLVvdGszaLwamJRVC4BWu20MG23A06NoXFLql3LY6g0yiCSDLYXCofNK8W614wm16229CdvNHM73aqRaqkS56bzodOwxy86PUuaRcGwXNMjVyqWtY6WWpzLKEqZdLsNan1SW1tFrW9mjg3j0Fp9Y+ll/LUW02wq9eZhWrWqdUxVw5Bq2yRGJjLUmk8vZ06Vxgs6Bu8Y6Bb9uVThGui0EIG5qOgXDl3dUBIpIN8LBY7SzqbSxvXzP+vbnmFDYWl6+vuQnoMzEBSA6VyoG3zWjWXjJb/3sJzEb4/Awqz22goKC3OF97zMVTyJXf3djMh0DBtt6jh6/1sWrNKon8FQmrVzzu8pQA+xkSt5YbK/26ZuAQIAw4aS0ZnzkbFDy9XBfl3OMdjJn2V4oAKIAkUa7OB+1OlTnFlK/LYCsNPbmoDMiyVbuIfXy49p21c1kxPmosy7kktDAS22tqrSdNuUdfyuAp6rThdGzExpeS0mm2TfK4z1fhjINkPMQOyw4C5e1iGTtVW975jzW0ZDtLXGtm61W/Vev+sYxg4nBdPNwO/R/QZwip42zUOW9zf1ONd3cEwDrm4SsLQ4keyZpBS0V+X090yChYTeHC8cpu2Wz+vSLaqJwcKKAngYDmfwu/p1siMkIvHWWdp9mHwN21CNCs80UB/B9ZzC/Vx3RWEti4k57E1pY3GwtVBg51zC1drvWqR6lKQG8sy+MuRK6so7MT2kAE5c9JBNpEYUsx+sXehTeDAVt91BOEO9mom26/hhl2rYSXSX7Bh3qHCsLzva+3CPKHPjcccV7m2W9Biam8JTvPPztUTvM0V07Gvq6lCUIo9V49vsOxRZRhHMdZpD1rG7ysi6+ViXR60O2fXXX88//uM/smPHDiYnJwtFmIUQ3HbbbY/W7RYVIQRf+cpX+MM//EM+//nP86lPfYqtW7fymc98hssvv7x33Kmnnsq2bdv4zGc+w6FDhwiCgDPOOIMrrriikD3x0RIzhsycLAbnZ3Dj2Erx88IutdYC1JMe3Upni3WjdRYsMWR+06RcKgO6E9AdXI1wHiyc53T04HRvTFc4xjiC1xnC8Z2eKV7ILl4cFAbGKEeNO+sy2CoqPwNGUZNOHBJmE4MZB9ccwqbWZCAyed2GhyybRJVrdTrVnkVbdDsIUWNgtJJeo1w5EVJoi+RYK7XKGO1ciHOlYO1Ioriak+pCO5/8Vg5V84nLpO6lk2g0sxtnoAjK3Lh8kjcXeEhKIwDE3QrDcoqHS4rDCun1VQeiaLT0vvqFlKuotXxM5Gw8d61anvE0WJvz+s0nrLYO0x6xpyYfazbLjR/NJK5OGLFaZm/r1z/skj9nN40RGewWqSGmEiKCMe23Sln0jGDJDJB5jmAw7h8LW+/oVseWp/92xzJjgn6PlhFntm60nrZaUYiYwWuPQWtafxZTMfG6BZrviKccE+pW/Iat8BHQ8XVANuiPgciNOaMnJN6/7oLfc87uErkiMjQ7abLk8n1tfa7qzCYXaDlVPNXLzCRxmLfP830QdtK2recMqwpywUMW47dbuQdUZtfR++SyToRTkYX3vLqZHNeSkoYQmsLpWjwtSROKLIqu0y1zOGsesrrXheF1sFstrp6d2H/cdCMd7IySZJf02qPIWn6P+Up/2/Laqg4UzKOzNcomNkDWauZgMJJdVC6tCJO5t+3lc0ZNCsI+3n/NQ6bWEQssbAbLKzONoJCUOwEghsaKCYQ4pH0vrz2StLMzhR8EUKa7mh46kvdvJroY7swiI33gZG0t6VYAHEoBmYhj1lZj7jIcLlNTk9nVtO3VyhqEENqa0RRzRCJG5cTY9AvXGCvaE5Z16lRWBLrabANkrtQN0EEcMdyJmC88BUwoU20n/QgmCHQ7UY8VpTRU+zXYWkAATjcfM14wCuzS2jIWzWkJkNyp/G9vRdHr7EWR9oKGZqe0/XO1ECzOMBHaWRlrhcvBknG/aiiJf3T6zAuBpY5YszVg/W7j0aPHZPl/IY8KIPuLv/gL3vGOd1CtVtm6dStjY2OLn/T/QAYGBvjoRz/KRz/60dJjzj777ELa+//bEhQoY3rnG0jpQ66lTw7OJZSZzJKchXmsGq7yABQWzSwxh5sCC1XBdTsutcYYgge1NsSxwFcLLQtw6r7WyrF4FiFHEK4KyNrUuiYtKalblVzGPjhq3eLAbUh9Ym9qC7N+g7mW3SPjDmVgyinQGqLspwrI2vkK44QdgkoNJ7OEqTQR41p1dBA61iwq1qB7yFZlgMyYRHYrz71iuNq7samYO5OpdXb7VfhrzyRYOwR5aFFe68QqxQVkKA1WizoDVMQeYLjP+SqPzGiXUk+kvyjnOf28boZVN8gNBdGRW3GXnUHz5k8iqlWc4bzNJkAKOjN0/Amr4jLaymvamEMuAyqFGLKCBUP0tI5O1CJw+1O5bR7IQds3M73nlRFUBolKWXQjV1tos6daMVQlivtbCk1A1nR166Y/XEnfqeGNkno/WTVchdAEZLP4rVGcsKl5Xcx3uMx1cESfJUmxvjtxTE2mANt4l2GgKy5DwTJIM9tpxzU9azcfnJuhWbF7XwY6ev2jsOmBELSdQFtMR5jkgOI5cQMv/ZY2RaPYGZYp8XzS0GYdKXVAll7THPPLOpEVWK5opcWTY2g4eotcbYpWAIPFQNNxutifB7rd/MaDXgeG14LYXjywv+5LGOv90k87v98aQ3r5G5+r2w1Imayp9PeQDRvRctqxlkZ22uXj2wmTl9hVAFlFCEJj+dM8ZAogE8p5flB8Lu2NS+N/RYbSdVdKwYrhNcDd2n63nXT+6bhNxXfKAZklQZPbHkbU9Js22k3c2F682YwsV9/pkTQx1tjMNPWROszqY2zLlpSKbsyFtfqawjzfdOdJXoYke1M1i6GrKLqZsRBzrsjKigE6LWMgoZDm1xjvtrTRpMpyRbXpiNB6jNOJwRnU4g5N804jW6uU5w1qI0ipz8fj4UK+ToTgKCwdd7g4IbpdqcXu1g02xXwtsgMyadf3VnmuFcR6EsZriYHvWM2blfaI9ZyRkjY8VuVRAWQf+tCHuOCCC/ja177GsOWD/leXoNumo3C0zaQeZgxZrbVAdWAQx6K11Ztpz087dCsNgB2pB5pVKJP4wXsInQEa52Qp35V7dR3GUiqNel4U+TScfAFz6h7C0Qf1UJQMelcN8ojbVMJaYWCMpMlAygaZGT8GUDXSEreUIqzmGJsPE+UlcB214DtOPe3elhtHlvm2q3CQRdglGLDTGk2pSQOQzafZCgvehLwPNNKF1lzsj5Aok/XAZbDi0eplHzT6TDonxpMPMvKcCv7xG+FvchqGWsjZlCSGTH+JmYdMdhoIAZHNGpCKuseXhrXQXSJdUZ2QlTTNFuKD9sv3c2NPuPtbNG/8NLI9i7dypb44G833u/PM+/YMeg01oN44sRJmXtn+lEX11u24uSggcywZQYdsKeXM724AMpWy6MQ6IMs8ZOMDAe1FFiYTkHVcg4ZV90EUFdlOrM/3I/WA9ozer2ssJPXy4m5f/XtZpVYaHwiAkinRkTHVTEswni3ydaVw2B+z3jdsFoPdASqdFvPCtEan+4y5Kmy5OJUkPkwF+yNMEioUS6/qA0KjHCXSQFiymK0bGbHeHzLKYrNnV8nualIWJ9oRDBa3j6QpCdtSIg11UvOQqTFOuJh93q/4IO1W8FCZSwe8LjTGtUEiFqMsprcKY90animhbmcIGfhgsZbbZFnQX9XJwItNbIAs7JQbkURUnHsrCAp+GvX9dhWjkAI0/Up/QJa1zbEY2YazjFASxgdW59bbVDIP2TTgu8U1odc2T2+D41RxoirC+PaVTogT6+u2l/YnacyfYTfoleZppeEDQ/OzeMMNnIeVEgpSsO9gEu9kzg21atKnVPDUcjNGQ/56qxaDrynaOy0Y7fT3trKqA7JyD1kuib6UbDGB1KqWLabb+N2OEY4ZV69fJ9OjRJQj60qjGIs/1un0DDXunMH8sMSXu4Zrt654HCWSth9TpPQnhiObjPqeFcQOyhyoHSvhZKK9krq0ZIX+TwbIHpUYsoWFBS6//PJfgbESqRs0l7rByTY7X7XdpDY0bF2qqu1Mcco8ZBkg89PxqUzyEbRv+Cc691+ByBRsN1/A4q7LsoEgAYTK2IkiD8/JB6pTt3T0KLmOUJ5FyI5V0Rzps9gBVMMiIDNd1t0+AGOhm0zodWPxygFZEaqquYoyCRWrrogigppqJe/jQpe+lp55bCFdXI35qCUVwCcyz5c+YUzL5J6j9SA5pndbFUiDUF6ZN1ocd7YA//zmxU2Zh4wwmcBj28xg2VgxJkHPXeIcoHZ6XwW+/SmLvq944BwH2U7oZwXLngWQNV27Cbgalmdf7C1yJmXRRCbK83QiO3deFbNMAsCwxRquXjeOBW5VBwoqZdE1wHEGyIZqfs9wUyb1jq60dIWhCNe99J3q7e4aHrLhWnGucIhxuo1kQlKUGbOP1urLCkrX3oW8b6jeNS+O8TL0aTxa7OtgeMgfw9bpw5ZrTavud7uFLGyZmHNV1HJxqkWvwDBThAptzwuy0g6Gp0AMWmeW9RMKZdyW1KOt9NkeZVE/bqxjnwOG0mHQjpOvqb6DQJ3PtZYV30ejOlgwOmWiArJqAHiVY7Z6A0ipj9lsvnS7dSUL5eIyZIAK853285DZzERhuyQzbOxYY++qwimWRVDicVVA5iht9SxzgmrAzbwQNgU3B5mCoepoYWx5ncR4dlQ4KSCziwnIAn8cW+KeoBPhGjHGfloqweyJoSUBw+DCPN5wA/V9O7HP2PhI7zlUqdXGix4ybx4JxAqwsBl8+4rUvVvm5x/3F6csJjFkCksg0gpI9P5yZcR4uLhfxA0jhKhq4818/5UeIMu1m9rgICCYJwdmQ928LU57cQjgGrS/msIo6fhxYqgTlrWrhKc6GnhWin9D8Q+VJTcpk8HuMl7aPr+wfagfV/YxKI8KILvkkku4/fbbH41L/VLKoBEIXu0bpAvV9gKVet1uve0lH8hiyJJfIzUfkPo80kwCYVWFwfFzZbHb9Vk2UEEY7YkiH1+hkTmWOlwDqRXG0QBZGyGdghW9YfNnK1KzADJTtFgCMzYrA2RVY6JMgaQQToFebPeQZbROCXFEpbG0oPGK4Wge7im3poesf0IMgBmSew5Uyr17zoI+YblDRa9UP8qibfIcTBUSkXobpWXCzECJeu/ABGT+Uo0ydkBm6jLmxOwHo+rOnpiArHBed46jlUkiiwWwFilB0Ma+HJD1pyyqa3I7XhyQORZwO2ilJ+Ut6nariWKviE5Z1PdlrRiq+bS9flnUoBLqACx0jZTqtZRyZ4ybtgLIGoFLkMabqO/HIcYN68g4gooKlvSLVRoTBQvtvuZK1q/7b5xz9r/pYYexXWGKIhc8/T3UvKKVGCC2FSgE/LBt7f9QBGRhy8WtFsdMnQVN6XQcB4RT8BQkgExXeIJui/ERe5shiyFTaF3p8/8MvWTAQJgp6/p7HuxmHjIIjOesaJ7x/pTFRqWcQaAat4J0Hpaa4pq2ySs3hgBIwxCXgXgZ1gjc/n1alREDVJjz/2BqkApjy7xnA2QKfVbdaxpuAKqNgURpN2046nqgeOmPxUPmxHZPoye71JSyMYPBYOEYp5usNQedAL8PIwJjTGZGN/MMvxPqzwQEvXFq6BhhcS0cnJ/DqevAXcQ+1YaXXkG/RqMxUTC2tnyd7ghLoyzq15bFWGZFTHBvTYpmxJANZcklDPpgNWpRlUVAZl7RjUIQFb0PGd6fbA5XPWTVgUGQggVyXaaq0Neddp/vnt3b8JD5isex7SdtcCxku1IPWcWuBw04qrHOLmdO3WJvY2fAqi8PW8auX1n6vPH/Wh4VQPZXf/VXXHPNNXz4wx/+v1JI+T+7DBn1GGqGNaq5oE8i1VaToFa3LgTVjFqUURZT9DNcS2O81FNSioKjlCZwg9xb1+kG6XlFD5kGyNIFtS3ybYNp4LI6VycesmI4Zq1Q2leXerQ47SSK1ElVfy8ZZbFuBtumHjJbUg+b7binQMUJ470+kHsj+iVtCKRHV3kP9XRCNL+eDZCZ9IXMQzZYVb17aEjFmTcW1iEL7zt7QsukaHuUgRQ0O2kMgDXBmkXZMAFZxUg6USqah0zxMCwSUB0olEX1myzmIQu6czgDNbpuceGohWY0Tt6WIFvkCoDMDAhRPGRp3Eu/pc5GMRqs2Cyl+VWiqILjGIqlRlk0AVk+N7QH+2eL9UNzDBpemZ6XXH+qUClPMVJXPMCqFZgYJ6yBjBDKXFSwsA8VKaU1b4zNm/+A4eGzNEOPttgrf0dRkSpa8+pWyqKMi8WcISnDEZeVVjAC1cOWi1NNxmzoKV4hWhoF2vM8kic2xq5T9JBVui2Ga4oHoVC3UuJ3i0Bmr1in/W70sijqzziUArJQSgIH7b1q8c0ae9Erzut+rWSi0D0glbQ4sq0OmXT708liIzlR9iyyW8W3jOUyGV4EkGUZAFsWkG4FZO383qqHLKFu6dcI6kVKK6DR+8ooizYPWaxcJwNkAsFz5Jd72+ss9Fohie2ALKohO/PMBrVyD5korn1eiYEj6EZJHKsifrYMGcdGkQWQtVs4vq8d7UiPnbt3pG3R29hoJFkWVTDV8VuFieWRecjKfw+aFE7LXJ6kvVfOiexrTBB38ZcQOeRGIUJU9Ng2w7tV7aaVmRWgVhscQALrlBja1a08wZFQMsHaYgUhTeqhtiXOr9/xUo+1UzzXtVB3IXEe2LyKA06uB5ij8MLbH+IpN17PW+//39Zrut0Be1y2LfN4zR7n+FiQRwWQrVu3jje+8Y28853vZGJigkajwdDQkPbvvzKdsQDIDItTq6UDllp7gUptaR6yppDUAxcvnVC17pcq7kLpgG6QT/ztbtCLZdIVPx9PSbvs1JK/55UBM9iNjbNIOeVFK3p1EUBW6ZMRMG9TroCYY2wutfTVjcUra7d9SU2PUSicWSB65vJP3P29S5RKBZ95xcLYyJ7HUFZa6QJcU0oFCMMCPI0OyHJqowLIDCOg06gXFk2nn4fM4iUK0jgWN6VV2vSsDJSouyoYgKyyVECmxpD1mSAthaGVi/T+ckcMD5nRfjdq4TUCul5x8aurgEzpKJWw25sgi1kWTQ/Zv5+yOFS3ULDUB5GVAu1I9ZA50g7Ihqo+LUtmTVX8SKeGmeMlpyzq14nJv11GV0xswEp/JcLp1iGOoaKCNsMzZAFkw5X8u2ogTwNkyp9xrTBWa57d0y1j3zqs+1IWuzpwjdq5h6zr5++/QkvzErmumyrlRnY3ZwDzbfudTu4ht4grYw2QirQ0wIQ8oB3XCO2AbDDMAFlSgkV9B36JhwyLh6zqVimbGFVA5veYBkVAhl82VpJji5TFFJBFlb5GMlNGDJpZt4TK1LZ4ru2ALH8fqlPNNNwABNWa1bssVFCiFsVWPWSWLIuqw0L3kOU71FpNzeoMQ0GRReGEVWR3gVm/XgrIROBS8L6l5QYKHrIoQhjenride4a07VGxPw2FXRBCM1KK2OXSZz7F2raBgQmEELiKobjrdTBfdKB4teduXoMz4zL2s7dpx2geMokGfMwEHwPGu7JSFmWsnTWkpF9X570g6uKna4vsowe5UQSiooP/pn7fSthBxLpBvDY4BFJwDjfyRPl9Lm5dz3nTu/J2KqDOphcAOIb1wlHa2UkRt2tJxmQzdgGM1X2sMWRq6IIxtp9+4z384Sc/xmBoZ1s5XbuHzKZZVKrlnv3/aHlUknq8+93v5k/+5E9Ys2YN55xzzn9p8GWToa7eiUwPWcFC2m4RjC+3pr3vechShaEtFOVdok18IuUzOoqL1lEoIu3IY6ziFZS8KPLxXZ/MjyTSRaGrgLShLkCsDSwRd3BkManHYh4yP7b5q3QJw2LMRCbz3WTYBb4xUaaALFGW85PUqdLxcgttVlhQpBNOfaicNqRKID2aykhqEFMkTuSAzFWUY6EEg3mxZKbnITMtiMo5yut06kUwBoqHzJojubjNT4PjXZEBMoulOF04QnVBMRbganWUpYndQ1bMbqW3w3WVyVRZQJxBQ+EwvQpApepbPWR1zeshe/fUQMpilEVl8enE/WlYQKGQOMDQQNG7oy9cRSVUjSETBjjOWjFc82nPlI9BLwwtVdaMRbg3x+j3lyJXvIdqeVtUQJNQFtMYMl8FZLlU5QLB4MZC2wYrI9bjXbV5GjYrLsFVt0FxlgUZB1bY5XfbBr0uF89QmuLQwavVoQ0dxUNWo0kY5saDzEPmO/p3cIRb6Et+p1OIh1VloDOqGQCctDTAi/g8n+C3e9sbJZTF4cxDRgKz1CetaEqZSlksvo+qX7UkKUlETXvvVNN51OIhw+3vvSgA2HTuicJjA2RDnqsR58tCSzpLBGRxN/8+mpIsiwDGr1aTTaZTXfVoS8UopOgHnqUfRKqHLIshk0KLyVTX3MOjUwwGg8wafdoJa8juAnN+Da+EsigCt6A8uyWAzInjwvzQaqZF2E3KYlSch4eiMDXU6e/zb/7ur/nYEz6MmTjCdZO4TE9h84ReF9MW6Suems5Pl7Pq8x7xU7cUHza7p/G9Tfqi6SGzUhZjSVOZGweiSBtNedtCgnTOisM+c3QUAp42Lzttg/IddpPETorUhgZhRuAS8yb+mubMJqQ8q9cW0VXabjFWAjjGGHUUfa2tAbJ26XGqjNQDWpa4bdVoYOq+I7OpU6Nk3LphzUquCSyGSN8S8/tYkUcFkH3iE5/gsssu4ytf+Uqawe1XokrdsJjXnf6AzA87BLUisIEErCXnJHu7Qve4aNdNx4eoK65gxRLXDBMPmSgk9cgAWXIBx0KbGOwKhBvqZYNkGyEbBdfxYh6yoE/CjrxN5TFkzZSm5Bsu92xhSyz2isVLaaDqIQtTi2XmIas0VBe6akEzLHB4xMqkPCDgEMVFaC5tp/rOVDXBk11m0uIuPcpidrByS6HwvkXDbu3pH0NWHKMZIMsWN+u8l072kbLwe4ZXJjBSjvdphHLzfhYrA1ip8W+qYmLQEGy6WjXwiGzUigW1KKvSLAWQFWJDhLHYKFZEMzOcTWyW9JFh23vQYAvC8FTEKmURu4dssOrRispBYmChDJuATGTzRKF1eXtyyrAoADIniyFT4rv0TIxN/AG99iFAzc+NIuob87QYMrWtxfiAmlu3GkiIA2tH98NuKWWx4CHsOrhpLFWogM0KLcIwf57MQ2YqGkIU02J4nVBLrmHKxPSJCKU2lJPShlayTzuu0eu++j2r6dQQSgoJnQI3mSsTGrvaMsPzQUzNK88kGqlJG4LUQ2aLIXP6z/1mpuGsz4RRsd5lPxk2AFkZY6Jt8dzYAFmkKLLaa5JOYfIJanVkt1tIBOSoNbuU9U0DZJa1N1S9oz3A6mh9S/WQtQOZALICZbGKDCdpeYFmJNSOqRQBZg+QGa8lqZ1qsH+a9rnQBsgGyDy6uQjp8t4/eg/mjswQIISDo6wJodMpADLViOJ3u9Z+o20zCkObiv6QoWfYsyxKIqVdauFpbY0JQ9z0ncV95uiEsqgblukYnss4KuhGtUadLF8XAFFALJWvpOoVJZRF16iHoAKtbgrIPMu6WuYhG6j61vVopJo7coqZx+cL7dXaFFWtYSjmdQCC+mMXkD0q6KnT6XDZZZf9CoyVSMMAZNU+iy0kCkFZDFnQC6hMOlqIpKoCMnWApYuGLQsYwHwYUA+KsQFR5OErLmjhW6yjoYdwDDqJ7BSsWPDoeMjiPnXImunCFlgKWCYNM2lWuaiArMdrTydwLe19H2usbyjrAyVmjmbcv8i0Lzt0UqU695BlxyrUAsVg5QT2a5qFL1WxjdMCIOtDWYyECsiMDFyBnR5muZpy8z5JPco0J0C28z7h1Ezl0GIZK1lwnGauqqn3U7nzhQLN5t0UQBbJpQAyczGV1EYtYFb7rpVCOyJFgRRSpzxmS16j4tLuk0ky6FoAmfkdfAcbZVFtnmoY0rOByTyGTKOO5e+sSgvXknikFuSArNxDpiiowg7IbP0hLqEsBt12KSAzdYw4FLhBkWpapdWj7QlEMuaktFhxizFUbjekXwmHKPbzrLnkOKdQHzHKAu5NUJM+S/YMyvUDZYzo/qxke3BoD6Lb5oerfkjVK48h0xTuzHOoZgfsN7AVcYVpvMy8e67WwImjOhg1pWYmriq5fdsCFGzrsFQBmebRsVMW5UJxDRSREkOmZM1UFWNbYWi17b0YMiE0KlxVBWQ+DPgDFIBVWIOoQ9stB2Si4hYMeBkgK1xPFufrdieZQ03lPLbEkNXcDMzqHrLf/O03p3fL2xGnxkFzKQ2d4lymGtbcNPa9L5g3syyalMUlxJCZ3qGKYkBS+5Mf5SyjuM+64abP4Ib5Wum1dOTpRVGh/1UH9TEqIp+FklqDZTFkjumlVgBumE7EVlBqiSFzY0kQuHQtRst6RYnZN/qRn+UQKANkYdUOtG1soEq5Iek/Wh4VBPXsZz+b66677tG41C+l1A1rgLk4mOKFIUGtRtsyuXsZFzkFTF0BFSWzmdpfM8VdTeqhylxcoVFxk4lOGbRx6CEUrCUsVrpqx0c4erlHIds4ssgOXhSQdRf3kEnFim8qNZmHzKQs9tplTPLqaxUaIEtpWRkgayxt4HrGMBrIfhrtjFKlxtF0rfwgT/EUFpJ6KKICMlHybXseMouVyrXQ9noFV/sCsmI/8DAB2VI9ZPYYsmJlqPKxEneU7IjVcg+ZSLNKlWUSE0pSHc0noNLTjBdSSOqhLLjhEgCZSVlshOAN22q4qUpstRhDpnjITECWeciqntu3TUvykPXGlgnI8t+qYajgIYsqIGOEEmel0uDKvOjVwE4bLoshswGyuj9Q8FYDyNgcuYn43a5m3dbFMO6EDo4l/boKyHoKW3eh0ApJVng872vuIqmaQ1lIfJe2zFAcSzxkpqh5LIKyLIvpelM5vI+B+2/nSPUINb88hkzrt71siDrEW4q4xoNmtLwQQawgk+HZ/X2vYxpBy2yA7XhpHrK4o74b5VjLmu1Xq8TNZjGGTKF7y66dsmgrDB1ZknqY2fsqCtBv+1DxivGnTlhFRh3arl8OyIJikhKvJCbTtbzTditLcGWMGwvwraa0XmEAsn/4x/+T/lB0lB4g058pdIu1DjVAFkXWNVEzkEmpfyuDDTFoGH7LsiyqUo1VD1l+8UCpFh73YVZ4PUCWv3uvpd/Di4uArDZY1979fOjTVE5TgU9ZDJkprrIuRmnNDJuHzAbIqjG9EBhTGkpJl0JMfPpuSmcb6VmNtzYPmffLnmXxPe95D3fddRdvfvObuemmmzh06BBHjx4t/PuvKg0jDbYZQ2ZKQlms07IoBV5PeUr2dYWkkilChmEnU9yF4j2Y23ta7+954SUeMkdoQcWy62qRw1ZAFvoIY6ISsmNdkPpRFoWMtTStZSKj8liDhZ6HrDzuQuWBq/RCzUOWpeJNj/WVwPp+8QquAUoaIpuI9HOyiVGLIdv2/Pw6ilLW8zb0zNnKOaHiLatYEkGwCGXRMlFmHjI/nVj7xZBp5xkxZEGJAl0QJfWu6iHzzT5fYoEHkK3c0FHwkKmGvzjpO17JuJMKZVEVT+uXiwAyRZZGWdSvV48kjqXMglgEkEWx6tHQ+0I2Yqq+vQByJn63OP5slMUkMUEfD1m20IoiZVHEPsgY/HwxbCv0wgD7+K4qcQUaWFabp1qfRdGLWCkr0h371kXcDzvElrnXpmDEXQfh2QBZE2mWiegW50Ep00K26n2MY4QQvPSh5P289Z4WIVY7DabGX+/FkPUXFZBVXCWGR/ZrVRJD1m989qTnIVu6upFR0spYN10BoVJnLRb9jXqB0GFVXAII25Z07C4RQ3IKgFfKTybtU8NLjRgys/8FtRpxq1UIXMuOk7E+/mL6e8hCWwwZegxZoACyji/SBCzKvSMvAYQpILMprpCEKxTYF26iOJst8+KiZ6NTUgvPltSj7rkgnJ7hEhKA+573vbv3jJnIjCpveo+dsNAlVaaDG0XJ3CbhqXf9jOGFWZ5+xw3a8YlhWw1x0PuWGXJSVodMlYpiPNAAWXdpzIre3KPoV6oeAOl6ZVIWB/QxOh8Getyn+ncf/UkV1fuXechsgMwWQ1aNJKLkPhobwviG7iIeMiiZ5yyGBs8rjvHHijwqMWRbt24F4NZbb+Vv//ZvS4+LStJg/rJLo+Ah678weWEXLwhoNYu9z8sywqUWy5DcQ2ZK7iHLvQf7b3olyxa+weyeM5mTh2ikQcOOqwIyB6lYbmwWjVroAZKuSheK21bKotcHHARxmzhcgocs7vZWAHPSzzxklRIPWeFaKiCyUBYzXr5tMbSJaWcftNerze+pUndWnAyTyd+uYlXreRus1jefjChfRln0+gAGd3gY9uiZP4OMsijKsyza0t67Us/nWKks0UOmBjArHjK/MLH3AWQKZdH0FKpnOVGHSDjlcTkLCmVR2ewrlsCioaF8ZViah8zIkBVJhIX6pn5/x6kVvrNqaRbSvtAsNi7MRBVQBGSO7xB1IorANJfMiCBsMWRRAFJqHrINSirm5/Jl4BWFdlRL+lMZZdFx9H5QdasF2lt+mn3580vS3ntxVEhikXjIiu9dpYz1YlystNHk3asA0ITPUkp+92cP8bodqxjvSK5qHbFiG5OaWImT9aGf8WBfN0bV63TatzaKCufW3JrmPfAXJmjXJnl41zb9QNc2R/X3kEkpiGVU8NxkymzsCOJO3m9j0X/MJZQ+9fr249pRcQwK4D38IQ/K43kcifKuDnFjpGCOEb9aQzabBYNJfgEjUQwOGbHes8SHnz86wETgcbgTcsmPvwXAkdY+BOO9YzQPmQeBG2jtEmmCqcRDNtjHQ+YWvIlaYiV1e2zJnZcCkXasP3tsM9ymlMWuGi4hXd7wptenP1RAlserardzi/1And8S0JK0adOhPWw6tCfdM5qfYHYOI87R9LbaY8iMYsqRzAG40mbVQxZRbpjOjYPK84bGmh8Xs1z6VV8bo4nRWQVk+Z+ipIyEqW+pQKvnIbPQHe2ADI1ure1TAJlTuGfyXS3dJm+ndZvl21jm68eKPGpZFo8l49F/NWnEekj54h6yLq7v02wVFaV6q43jb0E4I0BGWcwUIXAUTaXnIavmluiwOcqBm18JwMLYT5NAfCFwvHwykF0XqVi2hGVRqHWTNNhtldAuu1YPWT/xZKdvEcZMYm3R0vtaJ11ENWXCWGB0i5fdQpTHkGWAbGkWI9cAKvXs+5ZYjzXKovK3auHs0VDTA6TCjXcJyMr+ihL3u9dncrdZqDLKYlbuwEpZtGQg8/ENQLZED5ma2VABZF7BM9GHsqjFkJVTFp24S9v1CTz7tfySwuR6/RW7YmiTJcWQmUpbLEvm0LxtjlPDVIxj1UNWAjyqJUl/etddQgxnRlk0F+eyGDITkCHdxEOmFLYe6M7xx/7/YIoRzuBm631rStr7SKP3Kgcp84drALLADUDY1X8py2LI7IDMtQHXWOAGxTGoArLedwlbhfe3cuVv89BDv61t8y2Nbd/4N1TPej13duG02/+eQ+utT6Q/Rwzz9PeQ/WIhYjYKIY1dLesrUuRZdzOp+VU6igJc2XURt6+9jEMPfU87TriZMq62JLnW+PYXcXjzFy03dAhlWKhv1Ishcxyksj5GYnGWhfpFo5Iu37bENkGSMEVLmqJ6QBajLFYqyE6nDwbVGxMpQX02o2DFcbj+3BOZXFjgi584mF4h0gC56nEOfQfP0bMpi4zqvBhl0XeSkGqVceAGyZxvrNtuRPEZ0/fUMlRNs0A6ZIZqQRcdkF3/o+vYeuJmXbmWagblXEK3W2iE5ueNkkYWY4J1ymI/D1mlYCSwGE2NDlZRE2EoyZfUNaavhyy2sBhCfWwkMWSGN9Nz9MRlcaAZaLTjS/qAaYSyxZCZhlQhpTWpR6UseBOoKOEOBa9synIpsTkm59i2WTY6v+wesve+972PxmV+aWXAoCxWl+Ih83xaFhrG4+/fx0NbXtn7HQFVxQIuFE3FsXjIVFmQFepBQm4TvuIN6LpIJa7LsSwK1W6AQNJSudGyTbyEhVEVp4/1VpU4DnusGXOcZ9Y331PfQ7lHQ6UsHr73aaw49Urm54fzIPz0Bp76XvsYHEwPWb2n1JQBMnW74gFRHsz0kEllUnU0QFZCWVyEwmNKL+09xQD8XkstHgXPWFiXTAdQ6VsaZVG/h7pgmN4PlMXMjJPUikangMwvGXeeWiNG6VuqZbWwgPdJSrAUyqIZQxaULFRCBWRuzYiw0GPIyqS6CBUl63cbD+9j5/gq6s2DxCYdOXBT5Uf32HUVanM1sAMykSpAUsYIBXyLDhzvP9C/7Ura+1j7Nmrj8h9mHwncIB1vxf4spVewxEIC0G1p7704tl7H9QJMpbqiATKVsqiP16HBx3HXLRfDWcp9CpkYBfHsPvjBH7E+3XbEWV5oh9myxupG6nxXYouMftaSpIAskcSolR2jKKV4YNBKAzfQANld8SxWlaIPZXFs5zNZoMPC5q9p2yWCKO4WCqH3PGSuQ9hWPGTO4uuOapgvW3W6JYDMFDUdv5nUQ0rdE+plMYalhsd+gMw+dod9j7o698ukCE0mvvqtKsX1KANkMuzQSpN62FYM4TlJrJ7yWYUoWXMsHrLsdyGGzGLcSzxkTpKwpddOl7GxzHuleMjIax6q0hHFJDlaG8Oov5uldyfNoqftqxj9uFiqpRhDNrAwikxzvXaVOcBTgFtIH0CWrVFK2x2TshgXn831BI4yNsIwKFrVUhEW2iEU37HmIcsAmeFdc2Nb1G4SQ1Ym1Yqdnu7GUc9DZrVW9RFbXJxXkt7/sSCPSgzZr6S/DBgesupiRVrDLm7g03IssQkdw5ovcuVdSJ166KRzUzEDXSILVJKCkELguIryGbrIrkpZtHnIEstzS43fkB2u2fxp5BJBVnLOEgFZn+PCdHGpqAWXfXPSVP5WlPXW4RO46efP5rZbn0FvGuhRFpXn7kO3cY1hlLWjbOpQAVm5V6OXOi25lqN6SpQaP5UyymKfGDLLVJl7yPoo77YkMyW0r0VFpW8pSvpkWL6gum55ulozqYcqTtSh4/h4JcDE0YCX0iytDtnSGQBL8ZCZlMXyTKOKZ9St6Wn/sVuaTakuQlnM4h0uuP8XnPvgXZy081+LfbenzSpA163SUujGNcUQESkanJc9QxxqtExRHhaat11JhazOAeq6LD0lRsToIxW3gqBkLJYWhrY3zI0jq05toyyq1mvVQ6bdPhZ4nsfczKi23VsK28SiVJnUxLEXHZ+0T/WcWLqZqhurHjLVK4+l8GvgVRBKjaIjZf0+85Bpj5W0SUiP6qHTCqdIKYhkF6cwZpPzpOcRKWvUUgyBQqO8KdsV9kUYl9AKTVHGq5nUQ0aHtEMzilRZGnAzaYTqXOlLmxf6j1DxvPgKQ0IERfDSM65FHdpeHw+Z52A6hh0nu54utqQepWIBZLW0NIQKyJAua9asSe6njYu0DYbC3bQXuMjb2POQ6aKZSGWsFzo2AJlnvKuOJb7dM2LIBufHIL2z6gFUPWT9AFnvOMXQasbhuVIWPLSu5yDcvC8044re39RmlhgszW6rMgVCx5723i1xQVeX6CFTdSQ3inHS3Anq8HSdZG1Ydv8LSq9pMyy7liRMjxV5RIDstNNO45vf/OYxnzc9Pc1pp53GjTfe+Ehu+59WBg1Athi90wtDXM+naQFkgUVZyBUuafWQlSmr7WwCFwJHUWoIPS23rg2QVTp1KHjIOhwcfIhPn/2ekicrylIBmTqORUE5SN6nGitjS9Xfu5YxHS8sjBIpsQMitYSXLYYF8GNQFt1Klhwk36a6/bUMgCVdoacYpZahWFGOEupaer6FLgWPBJClWZxKs8tRkmXxEQKyrgrIcg/ZvQvT7NECwft4yBRxqsZ70DxkidJRmmWx5Jp6bNXSKYt5DFn5OBexvi8oWcDiOAeonlsxqLu6lOl7Vd/l8aseX3peZvEcbDc5a9d9+NFRCrQfIZLH0TyWFdqKUqwq86rS0UswE4cIvwSQlegitepY/kOZa7QYMrcckPmOn45Xy7eQHncNF/u0bY4Fe6wdgGOJ/fvFbZf2/u4Bsm5Tmwfi2MPzPJzGCCtkTocrtMgyScSuDZDpUqtl7VIBWfG8SLm+mmVR9conlEVdKm6Ao8xL3ViUANZ03JYwA+zeS5FQFg3Le8/j4rpE4bEBspbyCCo4Ulka4RINTCK2z1HWOFuvuB5o1zI9ZMqj9KXNGwAztBlBIKe1q4bAzEMWd+k45Uk9hO9g5twSKa3dKXhORCnojM0kRnPFREo1L6Esakk9EFx11VXZjZWj7YBsXtriNHPJAJkpmpcrlhogE4vUymtHRSOiY7yHivKJVQ+ZGqcc9unDvrMqua4aI2ermWcAMsdzNA/ZQ3i6wVCzJtjvXQCvis6WechMarEb2ymL1T6vsqqUzFHv6cURbhZDpky121a+nhvujRnf8bzSa9p0bdf/JfOQ3XHHHUxPTx/zeWEYcscddzA3N7f4wb9EMhiXZxm0iUDi+j4dq4esOPgrihVRjSHrURZLPGQtZWIQ6nmhsQhawI2QXuoh0ymLAAvBjPV+NpkOJpZ0nKo0uCW0ON8tB2RqnFofI012MOBpKYc19cGcfIxhlCudqvKlUA3UhbFkFuyB7NT6pipHapxMaQxZH8qiNU1vFkTeh05rBWSWbUuSEg9ZJB1+vmAHQqpnsNC2PmnvnTik4/j4i3imATrK4/erQ9ZPIgvf3xTzeqZFNRMpc3DgelXafbKNlknVd/nAEz9Qut9UHiIRMVFfseh1HSegXeIheyI/7G1/Et8HSLLJqUYTJXW4CO3v11P6RqzMNZ4KaBXTvOfVtXdbcSulRg9ZkmTBFiuWb7cs8BajyPx8DiRVD9lhlvW2x7GD67qI2qBG8bQn489F+D7+mO2hjPQS6X1V44FNIYqVcVHxHLJi37FW08lilPMCLSlSKAVxt6gQe2ndHzUGqCuV8WrxPkuZUBYxvI8ZeNm7YpZQ85AtTtFWu5iqgKsexNCS1MMqilLqGFkBTeklEShbdwxvZ6gsUF4fw2Ih5bsGyJRU75XieiSy2NMwiSErnd08BxmZ/cr+jmwlb153wXEALGvoY2TbXXcVzq/7HgXKonR5+9vfnrZeXTeTNtSHhrVrdGRopRBmUpb2vqulzYxxHZWjqX7rotgAmZnUQ/UMdZR5R83c2inJNAtQCS5ImqJ4u6SVrm6AZEfgKOfMxQEz3Qfzo9W4wrIsqH08ZD1AZhhyvRIDY6VPSY+KqzB/lEnbi2OcNIZMcQLjOgF/cKB/9nabOlOmPz4W5BFDxbe+9a28613vOqZz4jj+L5n8w6QsLkWSWJyi2bhisd5mCSBavofQKIsSEFoGutPrX+W2hefxhIF/5lPyaYDFAGvw6IvxWJlIWqonTR67srhUCdVsc5Y006CnvTfbrPa7WM0MabuQjEF4pZRFx8goZCpQWSa5slgfLe29Cs6UdvVAdgbINA9ZtXftshgyv09Sj37SD5DZaCaPnLKoJvVQs3aVp713LAaK3r4SowMkgKzreKVp77Vmqd+5b7KLfkk9Fn/3sQnIShYwqVgzPTcBZGWwtKxFVd+hHowDu637zbpXIZL3X/ABuNkwJAmhKUWOU6Fl85AJWM4B3i/fAUhWcCDZHodIJfhLTYxXBshUC7g6brVQAsVD5nl1UGhLSQyZ9dIQH9vC7EVxIcAdFl/gZTaWuy10I03iIUNKTZn2+6yR9ZM3suYT/8xD73l+YZ+ZZTFTajSiV/qt59RC5soLKqMsqh6yOAUQVa+qURY7UhA29eytAF5QS6+Xf8sQxahk9V46RDIkMgBZ9owLozGNYwRkGu7RcnKogOzYY8hUoNkPkJVTFvWfKhWzn4esUBRZTRahzP8VLwPERcqijDrEfWjqwneoDgSo/izh2nUTJxKFSejtl25h2+ohzlw1xc578u02SlvVTRKMRRpl0eE1r3kNV1xxhe7hKwGFbRnSz8/gRlG6W395oUrxlBJHoywqHmbLpW391wRklThvlprUw1cAWVeEhXb1jpMNQGrjzVZc29b/VA9ZK6rgq2UaVOBZUhjaJHiqCUvCMg9ZKWXRuhlIauXlDVOuFcdccWHIC6+Hw6OQQfB+Btr8Ov8Fsiy++tWv/nfddPXq1f+u8/+zycAivGablHUam/U2W0TnqwGONalHvvhdMPgpzh74IjVnlnbrWdZ7CENRKaX/CWirSmv86ACy1c1qYV4aPXofh1eksWI1+0D0lSx6JiBTLTi6wa84ASZ0FLfUOmnWxjHrkPVSe2v0JLu3Tf3lKqvZxGD6jLEFkMm8ylhZ2nu/n4esdE9iUSs979GkLKpp75WJWBRTGiht6+chMwCZ0i2dOKTjeqWURa1Zyqc1F9WlylJiyEIDHHol4E8qVlPXrT0yD9kSk3pkMr/vhZy3+mz2cL1+oDA8C4aHzIxVO44d+vlxCKriowKyaHGwrHrJ1SyLwvCQEeqALFGZi+9X9kvZZZGy/pCNwVPvvonbTzqbldOHtf1xVs9wZB1yUtkeu7iuizQAmdenXpe7divexATR6CY4csTYayr8GSDTQbMUcHtTLe6a308toVIWQ5alug7cQLO+dyVW74NXKVLmI6kCsuLzSgSRDIk9M2treu+gcswxZGVvVX0/0VL7hEZ5zK88sW6Yw3v1Qz0vNY+pFHa1ALWRWSZSEuX085BpM7lBWXTaDlTAmVQ8D+oaEesGv9I7eA5rThjjvu1Kc0UCyArp0C0eskbF48Vnr2V+vqMUudBBcCa1wIeoXahDdsUVVyRNVgrY9wdk5Ya7BJAVY8hUQIYZQ6ZIxWIseeLaJzLoD6JGDpp1yNT5SgXOgZp9UXRL254xKFTKYmyJd7QDsnyst+MAT/H4CQWEmRkre9uNGEcty2KW9t54X2Usg34eMrVWnjokvCjm+6dFfOssl3dVFT1ILA7IbA6gX7o6ZJ/85Ccf7Xb8UstA3J/XfN555/EJY1tZ4KEtE46a7l2jHnZSD1lFWfwE1ERixcwpiwZEMD1kJYuCQNJRvU2PgofMmz7K9MGH+Rq/gM1betur7aNAklnML6HpBZ6b2+0MQKZavMI+kwIAUiKEq09QqnXOsCSZXHoRFAe8VMCMFkOmnOs5gqdtW8Hpa4dZMZRaNaOs/oYyEUU5ICujLPp96vL0zRjZB7TYAJktS92SRFUEfFVhM+6hZdDr4yEz34Pquc08ZItkNwWd1mRmylqq9KPM9O5jLH7lST1yRcHzKrQjexHrftIPZEPRQxbJamkfkYq11XEqtEOLh6xwUnItGYdIJbZRA2QW76spHQWoaMkpNEBWU19Zj7Jo/ZZyifS03m3sSoaXGmAu+um3mUCy8ch+bf/4YDr/Pvuj8OmP5rdPKYsy1pXpwOintbPP7v09+rKXAhCNbgZ0QFZQcoX2HwADE3Vaz1nOwX/O3RWqcaCmeGSkVtMpn9MyQFb1qgilP8S4SEs/drMYMqUlEUH+yzJckhiyLpGRES07x3d8LYbMTE2uSpamXHuryj21GLIlUxZVlkX+zs6+9Diu0usM4/oZIFNuqqyx/epl90vqYY5RtQ81t59A/YjDwNUu1f+ZzY2qJy89NqNXl8UPeUkf1ba5AbBQOMWJnbIEfoW22ryFQSWAcFqnLOLwnOc8h6997WtaPG0ZIOssMme7UcTgcQuYs2ioxlxLWcju2WujZS4dr43zrRd9i60/zqmAdjJhcm5H85ApVEbRZfjoWTTre6nPbdDbnT6WUL3WWICFxYOvArJWFOAp+QI0D5niBEiKYwu2ydsLHkDHEkM229bfqFsSF+L1+Tw6ZTHvq24cEzldEAK1cs1SPGQ2kPlLF0P2Kzk2qfXhBgNceumlhW1eiYds07XfK2xTY6ccRUPOxq4NIAB0etOGOeCWSFkU0NGyLC7uGVhMqnt34IRdFsI8Dq0hK1qcQ5n3UPWACKPmlMrzj9Q2W66T0FHMdMvKtSzK6nP2JM/+nIfmezFkqh1OBWTq99KSTwD/51Xn8JtP3pzvT/npqiKsehOsxYRRPWTHhpicfgjLYn2zWbePWTzFu2VmERQqAChXlgrvQVEMHdml63haWYQyUelbppVTFfcRUkJ7zTOU7jLKop5lscpJy7aVHHesXzoX14whK9HOhBAF6mxXaXevdp5poMjounGE5iFTpkVnCYCs69gBmXAMQKZI4CRp720K4DF7yErS3icULqi1m2w5uJvAyIJQyRSAiS3a9li6yTuVUs9KaXq7ly9n4xe+wLq//3sa558PQGgBPiYgy8emSrlyEBVdIYmUebOugGonzMfltolz8+MdyebRzVR9HZBFjtBiq3rXCbKkHgr9VI1ftlIWkyyLkWHNzp4xcAMN3/TzkAUZdbOUMahQFpdKY1Vr3ynzom9ZmzJKq3Z/NSFDn67v9vNuqw4yKTQqXHR0gJHPe3hHBJV0TLRaD+en9pJ69Kd6uiOVApgqy7LoxP088frRwZD+vfxuFzcIIOoaMWQOX/taUhIhVhg4wpJkBqAr474JcUePm2P85CKt9mjnYH7tONZYL1oMZolRb1iplwjF1OqCWeRxCYBQSedqkp2uCAk6YwxPnYIfDurnp4epCUakBfbZPGTq/NiOfTy1DpmSNEcoffcTA//IK+Q/8dv8uaUOmQLIUn1hvq3T2x0ZW+dcSy6inlQVPUDNqOvGsldn0FMGkdtHH8jEFhdny4r7WJFfAbL/B7JYLgHTAgV9QMfoSGFbmYcsi8soeA/yI7T/evc2J50yr4mArjbolHo2zVsBeL38WMm9+7YIgKd2TmN9NM7TO2dotcO8EhCiTk/CoIQ5iqK/aB3cOC4AA62Nlu/1jrtbfPSmBd7+i6MKZTHfrwIy7XupFh/ba+5VqFcUWZX+mMaQHQtlsZ/0A2RiCUHEj0hUQGYAYR0A9AFkZm0RZaFLYsjcUg/Z2m2nJNcw9vfzkDl9PJC9NvXZFxsf2yu5VxTl8XWeN8C5q861Hle4/jHAM9foO1GZRiPA7eaZsEZHzqWrWEKDEsDbo0CbHjLFHSksGcNMUROfVJWkHuqc5/k1bSwEacp1a73DJdRwU8WJY2sWwXCRkggmxbl3+wyEGpTFwC22q3bKyQxceEF+blgEIEUaWOqZVHpiYDEmqUaIhgLWRnc+A6c5xMDASYwNXdTbPj6wnH96xj8hBFqSgRjX6h12LXXIYtW6b1EikzpkYV9AtvG08fwZRPlYzTyO6l3U76gl9YiXEJeC7uFRjX22GkeZRV4jyil9r6+H7JEm9egq41Kp79Q7N1uPLDUTB85fTbB+kOpJY1S3jCKNuckpAUMi7jfn6XuWG6DIjaKE7REZNQClwx/8wR8AEKmAzCkzMvdf3FefO41XiWgaNTcOdZT4Wik1fUGVyhJYFlA02tbdH8NJCf32Yq7J2zObe5a6fWrpZVdTDSDS6iXUTMfJFkUXaEeBnvBLedeOwspa4xzgMq5kkNn+ae/TuTc2DiozZnp9lqXAze8fKrF1bix7MaLH6iGztuFXgOxXcqxSGihuWVArbgkgyzxkKiBrWLIaCsHMA0la1TD0C4CsnOJmWGQVD9nQoY/y5/ItXEzRo7dU2RhPcGn3dMbkgAbIysCq6g4XBohUY8hCzUNms85KitQ55f4WOkM9ggsPR9S73R4gU4sHS6kqXMr3Uq5hHYwnvyA5XwVk0m7VUiXoU9Okn7h9TFg2QCaOoT5XqSgxZNLgouuAbOkTsJodPokh8wv1YzK57LfeweNf+DJe+YGPatvdPsjdrTZK9y1FTEDml3jIjhx5Kt1uwNTUCqrVjX2vqX657K2V1RdSxcwSaiYcUaU6u5GxB5/F4KHzWL/+N+iEqocsrb9nKHAZIJNxCMocoaofNjqsKWtmcq95TfGoqRZg3/SQuQHdKLbGrNgszP0kiSErvpvuImPA1eI0FAt3CkRkLImV+SnoVwswlahbHN9mKzIPmeo5sVGuhJIFuF5VlfohBr7zVs593NcYHMnXjYt/7TUMBoOA0J7n3DXn41XNmC9wMg+RWmha8U7a5uA4dghll7CQ9j4FZE7Axa/YypZzV3D1pn/ua0ALLJTFlXEeFKWC9QXUBEN9pCRBh9VDliV5UkGE6k3qQxN3+wIywbK16wHYetnTWc2e3r6aUjTbs4CX3GudjEJ1yDoNn+VvPoPxV5+McASHDl+tneuUgCFHLp2yyMRW7acXh0kJFyOmTUiHl7/85WkblVqcCihsnLsSSIBktyxxiiayYLAS89N5W+ZnSgFZdQmJocBGWQx77+CJ/ID/Jj/Bmyc/zlBXTeqxhMQ0iwCyNZvHlF/JM6hG1nYc4Km0c9W4qxi6x8ef0vu709Xvo8aQZR4yk6pcZsw02Riq+Eq/ahsesmyKUL9KZqAdcK8EYAcRYlafF0PLPPlYzrL4K0D2GBW3hGZow0ZqMgs17X2m8WiA7PIv8GDtFP5H9/W885kn9jYfuWkT2+97PLfcfFmpRXcxUQGZIGIl+/scfWyi6jylA0q1yhRiyOyURZsIuYiHTHk/plteKsVv1WBYqUwlGmVRmdxcm9I4kBTF1AGZfRJVpeYuHZD5Ul3o+gEy23t/lD1kZvrc9kjv79GR8lpaBVE8N04ccsey40uzLA6MLeOCl/06yzcer23vLSqWV+K+8erixmOQaIkxZO3WKDf89MXc/ounWa3vmVTndENL9vXLQKgqxdK7ZRTl5FoT21/K2vt/G9et0bFQFtVYD1A8unGIVGJidqzsn52ucHslgYhfQln0fV2hrrgVOmFcSFySPM6xLcxlWTe7ahzo7GRhvzqfOsqckCX6kUbbKoskYQEIw3x8R83k+u6kAYTT7xX2AWSR6LCgLA+mwimlRAhBUKtz+Z/8Bc/6zbdz4oUXpdfX27Rt4jRqE+sLbXVSg4ujeGNiW/yLet/YTSmLZp9P3tUJIyfQGKnwtNedzP0TN1nrpGWSZa1Um9u98HG9v7WkHlGFFe2kTuqL5Wf7NdB+L99nyz49ts/1fEZe8mKCbq70ux3FU9wPkHn9x+9L/tef8JL/9SesOv1kLuFqhuQ06+VOTtiTpwO3GRBzymIKyBTDikn3D0Pdm5WNG3Op6G+cM/Zd+LvaTy+KkrUs6vAcmcytbreOwOH2228HIFb1C0V5H3nuCUz899MZvuw4usglxPBKRqQ+T7jzM1T2P0Rl707c1nxpPc6lesjMs4XCDHCIeTLfZVP7Qc0Y1nGWwLpQ9QALIFu3dVw5uPgMrTjA1dg2yhysGBPWr3stGzf8d7ad9GG6RhkkdR6MncxDpo8Ht1E0zAB4S9QXOhogUyjpWox30q4h759oup/k91gg+LmeUCnq/AqQ/UoeBSnLBGPzVgUl6Up7HjJVaV99BuvfcT1veut7eeOTcgVUdj32799MqzWI67r4q4oegP91+zyrF2I+nKbDFjWDCqEBskdBUVdkKR4ybVExFrljAWTIWAvUBv29q3TIAhUqjnoTm6MoimWURakoKTawrT5T754KvcsJ7JTFmrv0BCtqPJTTz0Nm8WI8Kt9ZtYIbNJzq9Ca+vuNSdreewpo1r1jyJavr8/57r9flu+vPWRI4USVX4i2B0kuIR+snkdE/yymLUdp3hJXa/Do+T312A435zdr229JvupRn9g0lo5+HLJNsDGgeMj8DZKaVO2n3yMterNVVm6kpsTfD4ywmHaWPLxWQ+Y5PJ4oxi+8CCEuWro0H9xW2ZWJ6yA7fNZK0SzFsV/fs0IwsoHvI1AB7mSpDRUC2uOdOpSwe/dR6Gt93GP204U1Km9ovYUjohHSUIPeK0V9ipYTDyk1bOOmJl5QmPPD9eiFFNoDrZ4BM7ReKh8xGWZRJlsUhoz3Zr0Kh8z4GtOyZtKmtlveTleTfPJIu66c+xvvkO3keXyq9Zpl4nsdAW1cCXd9nxTvfycrffWO+rVu+VqniLOKRaYyMsv6U0xGOxwSH+Bi/wQd4u5a11cyABwrLIuur6ppo9BFpjOfMQ2a2TPTxkBXmUMPz6YUhTiWAsM3p3MXw0dMYOXqadow6r6hsCeE5VDYMIVyHzpKo2rIY5woEk4cI0gypahIwGSmU3yWuIWYJCih6v+LY0WLVOn0oi712qnXI3CIg042OxTHRjgOmR3MvWrA6N6CouQYcJ+CEE36PVateUKSsWmLITMpi/aSTGH7RC4vtW2LZKzXRkJp06kGlUGgWu+mINgvuLRxEIjp6W7udoh7kLmF+/Y+SXwGyx6gIx+EvT1hcSYE+sRvp2HUML4rrCI6fGMiVeCG0+dJ1XZa98iTq56xg/DdO7W1/zp4uV143z8WH0gs3JrSaOarSc/aKs1m16sUALI/y+INHKirFywSr21YN8cfPO9mw8unvRLV4+XVl4qlZFqtYQkFZU7yQikJSAGQyB2QqnSdWaIZDNV85XAFDNkXYkq1IVWDKPGTuIlx6VXyF3phx3ycOF4td2jxkAsH8fBLQfO+95y/5nnjFVNg2EQi+fP+z2d75rVKqjE2CiSpfarT5UqPNX538FGLHxV0i3SSTzDInhMPPK/pi6ShK1OrNI8d0XYCm8anL0t5HKpfeAsjWs5fG/AYc6dGR8GA7YtYVfJQks+tSKIujo/q3KANkMioqkRogS9tX9JAlfX/8LW9maOzJve13K7WogrV6VjGbtLUsi/9/e+cdJ0WR9vFf96SdzTmwyy6wS9xdsiSJogRhAUVWwADGw4CK4VQUjxPF89DXOxUxvOrdoXh6d+odespxQdBXDwwoQQRWRWBJC0vePNPvH7MzU51mumd6dtLz/XzQnZ7q6urpp6vqqScU43YsSuoh3v7AarLCpJLUIzM/TXbs1iM7Va+f2Oz6TbdtvRBHtmTh0CZX1tdWUWIjAaYm8TYnrIWMdWNubW1vq1QhU1lgY7EyCkXTsSSk/ckMS520lNxCJt3jzMk5RNYlqQXAIai7UTkki0Vmi03ROsG3K2Qmxh2NlbH3FJJBOQUT2pytmG0WX989xkgXoHxZyMwKFrIME4/RGclI5By4Gi97jrc5zdjb7EQZ9ihMql3s+6lSdcnCYrHILOpmiwV8UhKyxl/iOZbyDSPvJh7Zt94KAMheeKvqffjCvUDiHo9EacN5pTHOa7V2/Z99n8RlLdYs0Wd1y7L4V1lU4t1cXhrvJv39zA6HK8ufowUmOJDQkgResGLkrO6orHTNQdjFS7V44lZN831etFXBEctRWQlWYTux0+t94GuPQNEVpFkl3S6LorhyXpQQpoXX57KYYPX22ymNrlg00XuhEJzY5jTjXEaG57M51ftsOZXM3oJEmWRdFt3Nd0rGL7PdjpSLLpLVlZCvzSXYzORKSG309htrjlsBew+Uld0HjulPWlTcz9ua5X0LH68K2eHDh7FixQr86le/wjvvvIPvv/8+lJeLSPLrDwLMRHJ4unLsiXvD58oD3t/o8uIi7Di/QrXu/9pcwlZZ6JpYmDgeR79xrX442zhw7Ss7fLKy+dgDx4myvplNJpiz7Mi8rAcSytK9xaTdqNmEVyu7Ak4nbOe8exZ1SuqEB4c9iJ49fomBA9agrORuz3cm6aa5ghOlpaWu7xrk2Y/csBYy9oU6+1MX/P32UbhqeBfYunnbmjS0QHT+oQZvStreM8tgtplQOjAHtq7ySRkEASVmdWWY7Wx5k2Rwcjo9SlJjg9eC2NgwCMntAfM3jSn1FmcUMqWFUnOWa9KWtn+c55gl3ds2U3q6YhtNCitybmSDIZv5rv3LXnvOouveczj9o7fz5h2uiVVy+x5CJSUlMKcn4PtvpmLrNxNw3uCFqteUccVbQGI2MHKR6LDFsluxeHGmvCNP6OtaQbV27Sr7juM4fG9x4nvGlKKUHdMXbpdFq82M/9jFHTvPc5h0YwXKBufigqt7w5znat+Rxp801T25SGxdVnNZ7N+/v+fvdMmz7lRQLSu/tdGJT7ITcKh95NeyGbbdLpbh2UPEbmcpY4sAADwTX5Q0wrWX5NXDvRPL5Pbvs7IkCzDtFjLewqO44FK8fSoFL9TZcLzeq8Dbk7zXTGr/LaZbckXVzCwv8/x90WGXzLYd3orm7d73ISkpW9RPWXgLhnXLQmOiuC4AGHyxOOthJ5sFGe3vTc4Zr9UkqfE0MptPY8h3ybA0p6FtdzkObc6Fo8V1X70L5EkTWMSKdG+0tlohCBwOHHBlzJRayBJUJkYs4+bdALPFiiO2HPy+51Q4eRPa8tJFZbwxZOoWsESrHfYz//B8TpbIi9OHQmZPtuL4dxNd12hMg9liUvTgcMeQNaZ4ZeXN9pT9fIoFhaPlbo6Ck0dtQw2yEqwY9v125p7UUJ9kWRRiyDiex5v9SrG5vxldmB2yRnV3yfWOE+J3wunksW3rhdi7tx/27y9Xb4XZjLQZ00XH3OOVzZaHysrn0CXjBqTs9P4WnJlHzq23oPtnnyLnllvQbYBLAbAk+FfMPXVILIT+FTLXsU1FJ7DqioEQ2IU/iQyUlNworltlYYwTXEuKv3WkYmlpJ9xaLH/nmNKiT2aHA5zZAnQbB44DZmcvwkWXZaBiTCHeeOMNAEBO7mhP+S4lUxRrnZOuPl8CAGR0BY9z4DkHJrcMwFl7PWpSD8CSfAnMid64qS+OrwMAnG09icaTjHeO1jGE5zH+sGvMuPynFihZyASBRxu8i1e2bOCUzbWqcjZF+dmf/HGk5+++s67GhB2fIfNUPS7a+TkAICfbqwSbbQMBACd+9FqTBfA40ertR9MLhnv+Tp2ivC+t1EImja1OtiSjZ36p6BhvUlxeRlKZaz7RN7uvwrdeJqTlILXhLOwtTRj2nfd6xx087MVLUFJ8A5DpHfdfbJuqWE/n8lLZsUh2WQypqjhp0iTk5+ejZ8+e2LBhA7Zu3YrTp0+jvLwc//3vf0N56Yhg8vfrsSjhc8BkwVO9OuNvR09iWfdCxbKXbNmAAxm56H5kv+h4llX+iC69ZxAO7KqH2daGy3OSkJ/mmiBfcP1N+Oerz6DlrAWNdanoO28M7IMHyzPQKcAqZLzqCq1k1cfE4cKsVNg/3Yyk4hc8x9ddts7zd0bGUCADSPixFE2W77Fg/6v4T+dh+JarbK9RwKWXXoqn77oV5jMn/bYTACwJCdj1dhekFp2DqdGbBtySm4js6yshtDhgLRQroWOW3IS6dd+iqH9fZAzIxfV9s2Ey8fjzn3fJ6u+3/xx69tgrvldR9g3e07/yVjtE+363W8iuvexqfPj3D/HtjjGw2hpgT+iDv982CmeaW9Gnk3cC53CyFjI55iw7sq7sjaS6O3HoJI/sbpOQceMInP7gA5hzc5E0fHh7+yQumgFayNxYWwV029eI9/dnonfJSQBA2gHXgHhxywAcnWhDv379kMLZMbcmFyeTmlHWo0xWjypdRwP31Mj8NK9YdiXefuQVAAM8x3rmpeCKoXILStHTv8XJv/wFqZMna77snJ9a8EaJtr2G3AoZz/N462fD8fnjX3u/M3EoHZiL0oGuSUfS/HI0fFMHa04BSj46C+xXqtHLLRf2wpP/3oLG9vfOrBLsPGzYMHAch9zcXNjaY0H793sVx+s3okvJAiDxLVyetQhrTyxBg7PdFYXdIkKDhUzq8nzzOJeiknfHQDR9fxJJg1yDvCnFisy5vdB6pAHJQ1wLHndc2AOpdgsGFmd4rpWS0gfHvr0Y2X3+DsDrssiZeNjNdvx8/F9x4MwB9EmrwHfbd6O19RRKShZ4rr9mzG+xYccazDj/AVG7Rk+fihf/9AmEvWYUNLl+r8bNL6DL1w4c7TMF+Z1Hw2IRW8hMvAlWM4+xEybihx+3i77LLsrGY1k87t/tyrDGwascTV+7Bt9cMAz9D32OlM9P4NZen2Fj8uNoTB2D/Ue+EL0xA4sz8PjMShx4Qvn3ZS1kY8dejL/+9Th43oG2tvbFIEnsTYJK/DBLTklX3PS/r+P7+maU7DqGvCUzsPnEZ2B3p3VbJXrhW8+x2QWZwB5vZrckWxL+NvIy/PNMMoalp7oWLcpsQI1rouhLIUtItuDYjmloOZOHxmNl6HU1h+65KaLIYV5wtO9bBTSndcXClltRwB3Hq0Iv3Hf3YPB2MyY3/oRvtorrdgo8zrWdhMlqk4w68vdkzcVrcN/u/fhSxUvbxsmzLHI8B47jkJ3eT1T2ngmDkfbdNWipeQ2AN+brxIkCnDzp+ucLi8WClAvHA994NyNjJ4C5ORORmzMR38O7SOn25jC3Wy7GXdEL2UXJ6FKpzUPGVYmk/2fT8rcrazk5E1FX5xqb95j34svTv8Xqi9rwcWUBjm484q1KGt9qzhB95jgLcm7uB/vneyDGdV4fsxWVMmVM2fXU00aHA5zFDHSdCFQ9jQxLIjL6usaA5cuXAwD69b0Kn312EGZLEoqLlbPNXjf5RZjeWoSHFL5LTU0Frnob3Na3kFdYhP/b+QnW13+EnLMlMFlck3tH0+cQnKdxsKEG/PRMrH/6aSDNqzxodbnjOQ5LdjShqrYVg+sd4HiH3KorcDhsOQQIp8DbgSsWPoP/bNmAE1vTMGViGZ764UdZvfW7LkL/ch52FCKvoh9WFhTi4J7vcCRjALJzcpCekQdL0lQ4HXUw2VztHjD4UXz25Sr86ZBr4WNv44WYVczBYslEdslUmJY1wnHiJJLHjZNdDwCckrnEuCuvxcY/vIROFRW4se9EjC8ej6ytVmzcw8i8yhzS2r4o/Ztxv8G8N1/Ffn61Yrm8tCz87E/b4DA5kdQofg8s7kXw1E7A1X8FTu7HP99KV6ynS98eGDpzATb9xbvTLx/B+5CFtGX79u3DV199JRqQjh8/7gnSjHXuO/EaynNNgDkNcwqyMKcgS7VseuM5pDfKX0AlCkrTUFCahvMkxxOSUyC08Ti2PROWBDvynr5fU30cBwhsjJaKAifb3LHdpMM5/UedDB3/F5w5sxMfb3wPlxX9EQ9zbldIAUlJSbCekPnbeEjonYKSfzbhp2wB5gQ7ug4YjG3/WofGOjsKe4ktJ6xFjyW/Wxnyb/IqDL7c1/JOHAJvkaysqHTE0gQoguAAZ7WguKIbxljG4403XO4Q3bubUZwlt/I4GRcrk2Qy6cZekQ07snF11SGsXevyy+6+cQNgMslStXvapSPtudlHRsaWs1Z89yfXYNXr/FTgW6Dowt7oM9a7qp03uAvy1CrwhcJvmpSejKueuA0H7vvYc+zDO0Yprrxb8vORc8stylVLPl82qAjAQdyyuxm9TznwUF+Xu0eKDzlwrwTyPI8hXTPxOVu/NG19RgJSx3ZGKoDOTQKw33dCG47jcFlDG1YnuyarFrWsVCYTRowQu4JmZY1GVlb7anHnochueB/9ktbiszPzXHUzplZNMWSSwdPcnlTCkp8ES77Yop/YV5w8xG414ZZxckX83OFyr0LmzujW3q6S1BKUpLoU7GFDP4QgOEQuSN26XYhu3S6U1cnxPCYO6Ye6La7Zu9DaADhbYWkCxgx6EJZc1ySQDTB3WweU9qMxWxJQxLhqmTnOky0s4/QJjH33A+99C82YNOBzYMY1ePraL2V1XX5eMZ6UHW2/beb3NZvNaG11yZ7Fk0FP/K7aNbrUWBPs6N3Jjt6d0gEAbackmePa35nO2I97hEdx8Os7MXBcEmqYbXF5E4fKrB6oZIemRGaLEB8KGQDYk5Jx6sdRnrqGd8nCx8z3POcETN59q9Y6vbJsyXb9DkKDPHbGHV9ntlnB/j5K2TIrcyrR+3g6vpQk03BzUbZrAUyskCnfD89bcOfgOzH1nVb0G/MSeLOAkyfyUVMzVPkECRaLRSZrSmm2zflexY6TJHFJSLbgvClyq78vpBYy1kXX/Q5Yrd6J7dbkfVg71Ap3TymwMWQSVw3ZuM+ZYStORWJTDsAkD3G70puUQihEdSj05Y4213YyHAcMmif6zr0xNM/zOP9833Maa0IqJo9cjId+8nrbJNT+gD5Vl2Ho0KFAZh4w9j5YABw+83c4T4iTgFiSpqOtcQMqv/8cfK4VLUwGUkC7yyI4DsltrszLAACTPG5NEHg4TU4UPeK17swYNg1wG7R+UKhXMKP3RY97PqZkZaNn1ki4c1aeOHwOJmsPmOC1/pf264I39s/DN7td80uLyYzuZd7fMWPWLJ+3Ikj6gMGTq1BSXonMTkWeLYiOQOz9pja/clurcxJzkOkYo6qQcQASWjIVv2OzMaLbWFcb33pftf0jq6eKFDKzwrYikUJIWzZ37lxs3LgRY8eO9RzLysoSfY4LAsxaqBtWqdIQh8AidVnUhI6YHLM5BRkZQ1CWuwlnmDgKpdgON+tqX0WnxDJMmHk30ib9HV3rj8GWn4/jB/Z5yqhb8wKHdzqRPusy1e/ZAUqWkdLp9MSQsa5IKSnijR7dOIpHANtcbm5cSr7Pdrk3yASgmu7e873Pb8UoWchYmk+2x4CMKETerFLFuDujSRqSj3ObDyN5RCcf2y6ow57StygNKy7rC3y+GQlOYPKhNqwpceC7NBOe7SF3l3LjXmVWyjrK+wjE19peZqsgWDSla1bHyWbeZOMtfbTTjdXEiyQg0CyrangsZAq/C8eZZJNJ35V5/2Q3tWXfBzbuSSmhgRuT2QyupY0py4lciOUnuK4xsro7/vOqejFpYgu139PdR9vSxAt1iSpxof5wSN3BGfrjK4zsLl82UUwawTTf4cP1GQCc7H5/Jl72jE1wAgoucywWSzZamu2w2ryT36bmZADnXNYl5tXgIMDpkNfHpjt/omdnjMpIxt+OnsQPjc24oci1iCB1WVTCHR9Vfy4T21/rgTNlA+F0mpHGF6KFSSuvhnJfoXD/rFXUR2p7rcj3UHT9Hg1WNsui95puD8Vse7b4AOSLTTLrljsmT/o+u5MsKGSG5Jhfn+etCjFkbbJEH27YcU8LImcWpxOmxnOYNm2aQjl3SUaGzTmwplyGwpP/UeyvtLosSp8Hp7BJmyBwxve1orkJxxz3ltEyJrBIFTKO52UZiWUeOirzMvb3a3U40XhkDmx57+PC/HmK5ZWwSMNEdKL27kcCIW3ZkiVLsHDhQjz66KP46quv0KKQ8SQu8DMg+ePmzrmw8zx+V+F71YxdgdEXuCiOIVPLYig7S+eLDQDdcrJEq5xK2c/cnGw5im9PfgpTshWWvFxk9e6D5IxM2BK9q/bufVgCRanT7fTggzLzPfvbsmfINtEWHJ4Ysq5duyIlxZW1cuTIkVBCYGSD9yMn1dXymCFPmwJQWtyY4WMSysCbzB2ijAHtqYxv7oe0Kd38F1aAfV5pdos4SyaA/93cgHc3nsWEXIUYwnZ4xkIm+87HYoRmhYz5O2CFrP1aWWZv7Jo532tpZTfDXtGzCH1T7Hi6t/idsUr6CiMmCWxCG+UNxQOtmPltVRSyNsYNWCnltxvebBG/yxwHp8OHAtK+MpuW4ycwXaqUsPuQKSya5VWI+4aEhMA2PG1jkx5AvmfagIvkfaU/UXX6UPIAsWWFN3HKrtOe5FHKdaSnZ0MQ7sehg9VoaEhFY2MKjhxujytW2BhacMqfKauQJfAcSuw2LCzJw1O9imH3JLxg6lGxHLPxUc5mHrYfamA7Uodsiw6LlYbJqfOk193PWhj8+yG1yh1PAWozgWVzTMyihPc3mtD1YpxfeD6eG/+c6xsfFjK1Bycv5TqiaCFjx0/OIjvX5HDILIVufI17iu3iOEze9hmKjx/GJVs2QHHfEgalbP1cgrK3ip9dCERtEB9ot5CxC0oCb7hCxsIqxmx7LDqTW2nJpCwtoaaQsRZGh1NA25l+OFezGJVpEo8IH5e0qiR08YXZFlif2tGEdHY1c+ZMmM1mfPnll3jttdewd+9elJaWol+/fnj99ddDeenIIkiF7KGyTljcrcC/+xHzvS6FTJLUQ6vVidP5YnvOYxUyFVctX+R1K0P5mAtx6uhhjJx9VUBt8EXWnNnyg5zyB17q+yI4PDF7NpsNCxcuRGtrK5KSlJO5OJjfwp9++7vf/c53ASWU9l+S9HYiC5mPGZpeq2swcGYetmLfyRK0opTMI8EJFDUKqhMzwJ3mXFlB8TmR9WR18/1AWQuZWYeLqRJdbF/gvK7fAOUz8H0Os7jC3N9VnbJxVads1DQ0ic7NyMllnNiMec6cyr55wVfM/M30HaoKmdv6prTabRJviW3iAEebDwWkfT8tvwq35GtxlkW5dd2SkAQ0eIP7lTYX1gKrkLn2NBQ3xJrgdt9k2qbQ6bDJ4KT7C0lxShQyKY3wZoLz9T5cfPEVAIClS90uiu3ubxbx5J2D4EkSw9LCJBqwqClbbD0qQ5fbQua2cpobz4JrNsPUVU+CDclnhf7DeeYnNG56DoLTgYxL7pZ9rxfpb7s/R8DzF7ie94T2+YfAKNel6T3xfH9v3KY4y6LUIqZxnHe7LPqZF7jck8XXcCX1UJ6z6B73OA4l9UdQUt8eF6ey2OV+FwWFReEub/6RiSD0ojmpBwexZbc9y4pob1KB87utgV7YR8XWzbZar0KWZeuk4brSRSheFAbjOc5a35nnoqdNFh3Zlt1c8vNf4L3fPo6+4yfqPrcjCalCtnXrVtTV1XmC0ZuamrBjx464iSHzoMclRwUtsSBsp6zbZZF5k7X62Np6ZOi6hhvOT0yA3/M5DpNuviOgayvVxXLFFVdoOMf7tyyGzOkQDcBWqxVWHy5I4oVJ38/4ySefxJIlS/y2Ty/uGDLB6WcgjeB0sVLYn1JLYgslfFnIfE7KNV6ujd0/y9ngo6R/OA4YUrodmLoIP2z2uvQq9RvSIzaJfBptIYOCRcMQGFcadjKnFEOmBMfzYlcejhO5Qcpwu8r4fb7qFjItx22WwH4v1pplglOTpVZxQsjMT325QQIQZefTu62EMhzY388VfyUeLwQFi2vPpAS8V+eaQne1K6+Gs3nfVGNvFSd7XFBuTkrPQXA40Hboa9f3RiQZkG34LX8HBDaBlOQ+RRYyPy6LnqNSxbO9nJLLosBsbcDzVtm5lrY2QOV9CHrcC8D7IKFnT5z6UZ4VXHNSD94kTqzYrqCx8x1B4H1a8AODWfBhtR/mT4tOz6YUi3Isly94k3KeZ9ZC1sb0HXrcKANxWSyu6IubXnwNHMdhx44dus/vKELqsjh16lR8+603w1NCQgIGDRqE+fPnh/KykYfhL50y7CqFot+66okSl0UV1wGWpKH5sJerJynxebkgFbJQMWrUKHTv3l35S9H+HvJVbg86LX5saX9d0sSJAazuaBhALO0ui0quQCy6ZCrMcCp/68FXDJnPa2vd/NLmffpWxfVYTRfz/s3LLSBaBjqzNP7ECIWMY5QlAy1kot+WdVlkJnNaYsgOfe6KnREtYnEcnA4f7297tkC/LjxSlzUVC5maQiZ9HlppcTAWMvUdekUoWoid7KRRn4XMl+wH4lWtZCETBPkzvbk4F5Oz03B9UTYqk/3vcahuIVNaPON8LuoUFroyJ3ufp4YbdSi72waO+JoC8/65rcRsLBAnVTxFae+1KmSS44K6y6LZ7PV2KCu9V/a9yYeFTPe4J1MUVSxk7oQmKu+KkixrVchkMWS8gD0794j2IRQETsW9M3BEC5Fm1kIWuMuiltKy2FGVOST7+7UxfYdFFnPHLp5ILP0BuCwqtTESCalC1tLSghkzZuAPf/gDjh6Vb74XNwQZhKgdZrDXac0QWGVOgwKZdnE3xcHc5COIHgD6jp8YsQqZL6ui2iRMntTD/+aOLF3t3s5lUKqyW6Ob2lr1oHLVzkbD6qDXQmYWK5RDbxKVC0UClVAh1p8D64h9uSz6vrZGhYx5NtaAxwqR/1n7EaYfULLuSV1WpRMYAwYuzsS4LBppIWOapqYs+IshO/pNJo58JU/0YOIAh8+kHu3vqp/fR5rUQy2GjJWrEZ//CwBQeGiv7gmTm2am70lst1C6E6Z063qH4jm8okLG/hmcyyJLIFIljWdWs5AlmVx7Yj7SvUiT/Kq52yvH8XI+46Uvv/xyjBs3DgsWuFwAtVxfcChbdwOFk0zlWCXDbSFzslYqTmohY9x/ZS6LavejrLgpK2TJGDjgDfTsuQy5ufJtSszuLIsK+Br3NKEyBLrvixe0v29aPJUAhYUOHjh96rRoE3tXDJmxYyqbSIx9H9lHqLt/0fI+ST6rzRVYhczByJxs4VDkhSRxb/UTAtQzyRX/d12hjm0jIoSAe4KDBw+iUyffvqWjR49Geno6nn32Wdx8881ISUlBv3790K9fPzz++OM+z40p9LgsOtrQb4Lypod+L8MO9jqtGXotZGqjq8nPvSZnZgEak3p0BOwO874m3oKozV4HcaUYMj10s9uwsDgXx1rbsKA4x2fZEydO6KpbK54YMoEXK5SSwUKvkh9OBF8eOBrx5bLoE40KTQubZdGI4G6FwV0tnoZFc1yEDtqavFlFbWeCS7yjisq7xlrIPP0Rc0xwKk9UzBwHZ5uP97fCteWEf49FdQsZC6uoZe/aj+rDr8B+4gwsI0YrlveH2XkWvOMknKZ0TE12bWw9bOg6nDr9DXJzlPfqU1SiWPc1f5Y29j3zYyELBIvVKsuyqKSQ6UVNeXQrsCK3Lo5TVlzbSU1NxZgxY1S/V0JgFH9jFDKJhYxxGPO4LPqykAXgsigt5v6o5LIIABkZQ5CRobx/mK8YMr3jnmzxVC2GzO1iKbHgZxWJ9zAV2AzUGsVbbiGDy2VREkNm1vnsfcU8A4CTdSFWsb7pdVnUqIKKPqm5L4ssZCKXRfXxT/quWk2+LWT/W94F/zx+GpcX6He1DDcB9wQ9evTA7bffjnvvvde14Z4Ct912m+dvQRBQU1ODrVu3xl8MmYakHv3798fWrVsxrKISoy5W3nXcHyKFTItSxSDah0zD5FCtY/CnkAFwpbpvPz3cFjJWIfMZdyeIZgUepDEY/lx8pHAchwdK/QfNAq4FjlDgVsgEgQcY64JUbqPJQsZKlSeph87JIh+ghUwrnRNtnjiDon6VvgurITIFuhNYeA8puVpJj2h1w9FDw9HeOPnDSBQmn0XGvgmG1w9AdaLlcMono2x8FauQsfAc4FSzcI+6C8hsz/jJutMo+b5JqveXZVGAgI2ZI1F+Zid+zBiMuQFayFIsCUg/vBROcxbOL74WAJCY2BWJiV1Vz1Hsx5mfQIfxwG+CgkCUNd5klo8RBrjA+nulH7u0Ev99+h3PZ38TYRFairKKfygUMtZCxsmTevAS10x2bUNmDVR5bnLFR91CJj9XjNnRpvo76B73pJX7UchMEgV//NW9Xd+33zcbXx9o2nvwrjmwNIbMpjN+0NfCACBWyLIKvR43zgATaGhFll1VzWWRab/YZVFilWXrksijv6Qe3ZMS0D1JOUtmpBPwkxk1ahQee+wxlJaW4qmnnvKb0p7jOHTv3h0zZ87E0qVLA71sdKJhQjdjxgzcd999mHDZ5aK07rpgB3s9nTzPiRQyTckb2BeQyRtr0qB81n7m3Q8n3F692hUy75+i7QWkEzKdLot6WLlypep3eiY70qJmNoaMVcgkrrbRFEMmspAF2MsFHEOmcfK2aHAlClqaMOTUMQwZPcL/CcpX8/7pjiFjvlWKIZM9/5D41nM4/MU8FH19B3hnYD7/SoiSD6hYyNoEeZZFgclAWNSrL656/GkA4tAZl4VMxWWxjEnLLPJE8J3iG/CfZbHNIaDJZMeX6QNRb83SvU+Qm0vKLkEK14hc1GF051HqBUULSgrXYl4eQceCmeExZFyC3H0OTsUYMt34eae7ZLFWEt8WMila0oQLBseQyRcGmHGNd8eQMVY56Tjtw0ImdYdkvlA8oCm5i0QYzA6HauIUX+OecrNkGplaQQBihaxzn0zkFIv3DHWy+zoGHEPmmmuwLovJDjsSrPqevcmPiS4t1w57iqvOvuOKPMcdASbQALTN0aRlTCaT4nls89scrMui5Nmz64w6XRajmYAVsg8++AAbNmxAz549cdddd6FHjx5YvVp51+24R6MA+crGpwXjXBa1KGTKh7VYyM7VeoOueY3B56HCwQyMPl0WWcuXyL85uKQeenjqqadCUm9n/OT6QzABTGIAmYVMp9U1nLArgoG6UXlccEIUQ1acaMNXE4bir9PHG+MOquCyqCVBRIDz//DATBxNWS6XFHv//qIiyhYyr1yX9B3s2diUjeMzc5xogUYEsyor2pNQaRHHxz5kSsfZlWLAtVF3IHRO7Yz3L30ff7/070i1atsyQlHRCNhCZrC7YpLcU4QDIDiDV2D0KFj+YsgCwnCFTOqy6CfLoq8YMpn8aXVZbFfIpEGpSu2VfDb72P9P77gnq1ulb3XHW52y13mOlQ3KZSpqt5Ax/apmhUyqILf3LWxSj+LWbFjM+uZ8vB/ro9liwuUPDsHsh4agU/cMz3FfCTT8omGKJrOQqVxDLamHLyVR2q/IFsFjiKDubNSoUfjkk0+wdu1aZGRkYN68eRgwYAA+/PBDo9oXG3SQRi8O6NSzb4rEQqYh0FTNCqBl9YJjJ8tR4rIoqFnIgkzqoYeqqqqQ1DsO/wTQnvbeh8uiKYosZKxCprQPmR70K2T+9uERW0yCirtRzLLIrOhqcFk0JH6to2AGcWthJ+QvXYrC/3lSVEQUQ6ZgHWAno+xeODw4ONWSerB9omhBRt5nSJN6sM9bqb9pk2R29BVP4Y9sezaSrcn+C7rbpjAREq0p6RBN3sT7tpAxf2tJjmCyFMusHRwENNYH6N7L1qNTIdPVB4QhqYf0QSlnWWQtZDpiyNTuR3bc9VnL3loyi4oPhSzYcU+aGMaNO/nP6YTj4EfUYfCULug9vEDWRtGWQBrFRiovHA+kpaeJYsjg5JFmT9dWYTv2FP8KXFKaDVmdxH0AOx7q3gZGU3Fti1DipB4+siyK5ljRtGIYHIaMxFOmTMGWLVuwZs0anDt3DlOmTMEFF1yAL774wojqox8D9iHTAjuZ0J1lkXV3DGJfFLOWrEGs8hfmd01rUg9x9LoPl0WdST30sHbtWtXvAp3Upzedhrl9SVwQTIBT3UIWzF48HY0RST085xt838bWJ/LtkH2rZfDVOsmIBFiXRc5iRsbsy2GRJJdiXRY98TNOZXctViEz84BTbWLInCP2RFCykIk/pqene6/H1K9mIdOayS1QWIVLOcsi+/Jor1dPUg/NblOceAGv6UQRTu0PLMaaRe8kT4/1T1PJEGdZZF0W3TE3TpVFCUlxmTVQzQVT9qh1xJBJMfvIbupr3FNEuo2HWVkhYxduLAPOYGiVcuZocVIPjRYyqVJq4jBs5DCRhQwCr8v9zmzhMeG6PprLszg0WqMU0bBmLjSKn58WC1mryGVRu4VMiYenlyMv1YaXrh7st2wkY+hMY/bs2di5cyeef/55fP/99xg6dCiqq6uxZ88eIy8TfXSQhYzNEKbXZZFVyLggUrH6S3sPAE52BT/M5mftFjLWqudFaWPoUDFv3jzD6+Rbm70fZFkWJQpZFOzj4cap8rwCQb+FDGip+YeqLIQqSYjWGDIpyt7+xrCv2fV+pU4sMaZCn/sltRdxyi1krMsix/RRbZIYMkHNZVEUT+lPIfN+X1BQgOJib5ZJJRdph9Rl0eC9iaQ4Re5pSgoZ87dOhczn1iHMpfRk9mTHpqb6LuCkykQA6HsHOdU4wEAR2ozNssi+wk4HB4HzF0Pmw9KiMcuiWoJkf3FOSjWa1N47BD/uqT1rdnsMxf0KFZJ6BBxDZnLtwyu2kHGKi2hqXPfkKGQXpfgvqEAwFjJBw9Y5bYcbRJ+1KGQiC5mvtPcmHlf2vhIAkGxRtv5fPbwLNi2+EBf1yVP8PlowvOc3mUy44YYbsGfPHjzxxBPYsGEDKioqcPPNNxt9KZ+MHTvW4w4k/WdRMGH/7W9/w8CBA5GQkIDi4mL84he/QJtagLdeOmhjaHYPHU2JOdxIN4ZWsZBlXNYDAGDtoh6foMVCJjCdUG5SePeKCCzLImNNjMIYMtGEnXVRhMmny2I0IfbAcd9xYBOpQJJ6NG//Mxr+84gh9fm+mGjkkh1S3odMTChdFrc0OvBxi4CUsZ0Nqc+UbvP8nVCWoVhGKe29FpdF18bQWixkzGHF385bYMIEcYZJRZfFCLOQcaK099rr9W91YvtN7RYy6Ucj1vD8rhuKJt6c6D3yq5BpmbSz44khG0MzVTs4UcyzcpZF9Wtq3YeMt0kW7NwWMosWl0WJW68PhSzYGDK1/la0gbzCWOfJssjOjQKNIeNd7rxsiEZd40Fdyr3ZGvg8klV+9G5z4tRiIZMUMplMioY1UVIPtk3SZyRy/OBw28Db8Niox/D2tLc1tDh6CclIfOzYMWzatAnJycmYNm0anE4nXnjhhVBcSpUHHngAq1evFv17/vnnAcgHyQ8++AAzZsxAeno6nnnmGcyYMQOPPPIIFi5caExj0o2ZjPiDzRCmy2XR6RS7EaooJkmD85C3aCByrlP34bdomMSff8V8z982PylMQ43mfchEFhfWmthxLosvv/yy6ncBb37MKmCCNMtiNCtkwSf1cKNbIXN3q6z7ZxD1+UTkm+lOYOE9pLQPmfT3CHVSj0YD96ey5CUhbUpXJI8sRPJI5e0ilJJ6sFkW2fgZNqmHCfCR1IONIWPefz8WMumzVnJZdEiuaQm1hczB9nm+Y8j0JPXQ84z1pN4WxeQJeuO/lPH7DoqsAuKkHkYoZCmTJnmLG6GQMQ9NcHBQzrLIWmd9XFPWISj/VnLZ0e6yKP2JfFnIfI17KrWLP6nMZ/xtIO9GnNRDYwukSi3vahabZfFYY60hsqwFhz83ZR+IXgW1LQQkh3mely00Aepp730tQvE8B7vZjqndpqIguUC1XCwQ8IxLEAT8+OOP+O6777Bz507P/3ft2oX6+npPGavVit69e6NPn8B8XwPloosukh177bXXAABXXHGF6Pjdd9+Nvn374h//+IcnI09qaiqWL1+O22+/Hb169QqsERldgYRTwKi7AztfJyILmZ49oyRKhFoQLOCaEPlCi090QZ++wJYaV/kwe8EpTZAUUduHrAOTegwZorypZjDwzP23nisATOoxZFGFYgyZeIBo+vo1AD7Sg7vPD8Bl0cj6fCLK/imf4GsZfC0hdkU1etKRMqrI5/eiGDKFLIs8Yx5JYTKHpphNim6mmdYGsYXMV1IfwKdCxnpdeJN6iOUy1ElW2L2KlF0WtceQ8WYOzjYNS+iQWhY1Who8//F+zuiVrulcX/hz5BBn1eVgNjjDbP5DS2DOzEDSiBGGLFZYLGlobTDBkujA/o0FEEwKWRZZl0UdFjI1M6nCUk973f7vR7qdAu/Ds0TvuCe9vBYLmXJ2aH0WshGOBnxqSsSAbZ+BM0lcC008eI4XxZAJTgVLWohwCoFbyETJ4tTcF5UUMoWy6i6L0qQeTF1RlQY4OAKecSUmJnr2HhMEAXa7Hb169cKkSZM8ClifPn1QVlYWupgJnaxZswZJSUmYPn2659i3336Lb7/9FitXrhSlR7355pvx6KOP4s9//jMefPDBwC54+WtAeXmHWRpEFjI913SKXTN9KiZ+0KKQZVu9ZSpTEgO+lhFotpCxfyu6w7m/C53LYmNjYwBnyTtF1k2LaxFwYk8q7FnpOLX7SmDgX70Fo1ghU8yy+OPHAHp6jrfu3aipLt39l58Bz1iFjI35cytk3kMy33woxG+EWCHr6CxZohgyhX3IWAvZiPRkZFpMaHYKuLk4F2slK/WTO+1CUeIpsGnvxe402jNqAkB2ttdFOycnB4DcZVHpmRkJ617kNyOen6Fg2LRSfPp2DTIKlBfqOMZSw96VkuVWDdZCdoR3IrsyU/O5avh7B6VxM6IYMj91a9mHzJyZifyHHvJbTism3oLv3uoGa3IbGo/bIJQyVmIll0VfFjKNLotSRl/eA0XdNYYgCA4A3jb4clnUPe5J2qv2jipZ0pVgY8h8LV7d03QEf/rHP1BwtBb8qNmSNrhDZhhLptP3bzt0VxM2d7eh6vNzqmW0InJZDCKGjFNVyOQui0oKmdrvJ4t1FuU0IIXML7Nnz/YoXX369EGXLl0iOui/rq4O69evx+WXX46kJO/gsWXLFgDA4MHi7CydOnVCUVGR53s1jh49irq6OtGxmhqX9Qcmc4e6fVntXuUmIVl76mOphUwtK5EqHPuy+1fmutltuKpTFg40teDervn6rmUwmpN6sAOGLwtZCF0Wv//+e0PqYRe0eacTP/27EAkZdyIlK0GSZTG87qTBIFrkdz+iU/sDqktvv+bPXmCoQsbKJa9gIdPQdj2T40Do6BVOp+DHXYuxDqSYTfh0aG84BCDLaha58wFAn7Sj7Scx/biOLUKkfUrnzp3Rt29fOBwOnHfeeQDkae91p6XWCbtJrJKyzPdLgvOfpwAALVyz7HuWfhd2RmanJGR3Vh5vzFDuDzUr6RznTt4HADhscgYVS+O9vh+FjM3mCU7kceLfZTGopgWEiTPB0WxGY7NbTuUWMiebadRH5me51VSbhazP+YWK8fmKSOccPhQyveOefE8sDS6LSr9HezVa9yFLSrCj8IhrjLElSRYoTBw4cBILGedzQWfC1w0Ys70BNgNSGTgMSuqhppBJY8jULGRqi3++XRa1tDI2CPhWX331Vdxzzz2YMmUKunbtGtHKGAC8+eabaGtrk7krHjp0CIArG5aUgoICHDx40Ge9zz33HCoqKkT/ZsyYAQD45JNPsGHDBqxYsQL19fWebEHufTUWLVqEmpoavPLKK3jnnXewefNmLFu2DA0NDaiurhaVXbx4MbZt24Y1a9ZgzZo12LZtGxYvXiwq88unVyIpIwuCyQyuUwneeecdvPLKK6ipqcGiRYtEZefNm4f6+nqsWLEC3xwUr0D95re/EZVdsGABamtrsXLlSnz44YeyexJa0z3ntn7Z6veepk2bhhU9O6Prmy9j/3c7sWbNGtnv2tz+Lh8RzGhoaMCyZcuwefNmzfe0YcMGfPjhh1i5ciVqa2uxYMECxXs6ceKE55pvvvmm6nM6cuSIp9yZs94Vqw3/97G44c42v8+puro6oHvKy8tTvSe192/Lli2ye+pi92bYqtj1lefvkydPoLl0oufzLY+I4z5DcU9an5Oa7Emfk1v2vmIWUhwOh0v2ek0RP6pLL1W8Jynbtm3D5s2bYbK7Jg2dypN83tMXW74GACQ0NSnWd+zYsYDuSfF9YiY273+wDtu2bcOmz73bjWzetEn2nJokK85/fecd0WcjnhPL0aNH9N0T9PV7UtkrayjzXHvlr1YCAFav3uU51tqaLbqn1198AU11R7BgwQLVzJj/+miD5zmdOXPGc3z/gQOee1KipaVFdE88z+OLL75Ar1698Kc//Qlr1qxBF5s4QxnHcSF9n0wpXiXrtHBQJnu3Pf0A/nt0LdbX/gE5/Sp9Pqfp06ehpCILjz7+S89zYjHB6bn2Aw884H0GLc2K9yTlySeeEG0b4ASHp558UnZPWt6nt+Hy6KmHE395+y+ee5JSVVWF9HzvQqHJWo49B79mH5CovPQ5SeW/I/q9n/b+JLrmWbt4UaKqqgoC47b717++L3qfkkcWum7Nbsbcq68Q3dPate8p/kYipVoQ8Mknn2i+p6++Ei+OnW5X5JT6CJvNpquPkGb15nhe8X3aXbPbU8bMm2XP6ZVXXgEAlO3d6Sm39un/Ub2nA01tsGflQEhIRF7PcnEbek3EM888gyOHSz3HWhvsWPfVVtV7Si+0iJSxYMbcTZs+99Sza+dOXbLHN3v7O669f5Q+py2nvL8lALS2tuLVpUsgpWbXd57nxHLjDdeL7mn16j94vjt69Kih84hPPvlE1q5IgRO05LQMM06n0+Me6Q+bzaY4OR0xYgRqampw8OBBkWvismXL8NBDD+HIkSPIzc0VnTN69GicPn0aX3/9ter11CxkM2bMwPbt21FeXq5yZmhoa2kBx/O6knq0HjmKR1c95/l852WzkFqhvd1d7nsfJvuP4CynsPO+n3v2PdHDk5eL95aZ/z+rUPvdDvQcPgq2RN9xa8Hwm9/8BidPngQAXH/99SgqUo5P2f7RP7Fu1W8AAFnnjcTes67J9nnnnYehx7ui6dvjAABb15PI+VloNnBesGCBJzGNlMbGRjz++OOez0vRnpnqvOuBKU/Kyo9adSV67u+Mnj/sAC84kZBxJzLyEzH3ofOAnWuBhFSg9ALRc7nrTfnAHKms/mwvlvx1BwDgiqHFePSSSuDwdhz4jVcB7/TQIPCJYpfZ/P987fl7wYZ3AQADBw7EtGnTcPJIA2p3n0DpwFwkJKnL+Jd7DiGx6gIAwM5evbC1fz/R91lZWcYlDHp9FrDnH66/Jz0ODFuAlz/5Ecve+xYAcM35XfCLKvG7XNvUgkGffev5vHlwGV558gnP56VLlwbdrO0ba7FhjUsJyshPxNylw4KuUyutjlas+2kdCpMLMSB3AACXdaCu7kNYrFnIzBiueu7/zJ4mcju+q3f7gst9+13vBICDu7/DG0tcccHZxV0wb8WzALx92JneXm+LW2+9VeSmqITTKaDb4r97Pu/91RQfpY1h77ZjcLYJ6No/W3G8PLBzO84cP4Yew0bq3tOSlZ9ENOLnS1390jf7T2L6yv8DAHTLScK/7xrr89ycw6Nx83Pj8MzeQ1j+k8tSadp7Bn+7oAKDSjJ0tQkAyu97H+NgwVY48PrPx6Bzpuvdrzv2L+zf/ypKu92JtLSBnvL7dmzF3m/2obDPeSjokYJf//rXAACrxQLb1s8AuGK1F635q+g6+7Z/gz8t8yqfHdFvnmw6iZfnXen5/Ml52ajJ+RIA8Mepf0R5Vjk2fnweWltd8f2jRm6C1eqVS2dzGxq3HoO1cwos+eLx1uFoxEcbKjyfx1/gslhtrzuOC7e7FCtOEHBwXH/NC/MnW9vQ65Ptns/35qZgUXmpYllf454Sx44cxrOrvOW7NRzH1b9+Rlbuzo/uxPqf1gMAnhjzBCZ2mSj6vv7gAby6aAEEcPi+eyWqF92HcVnqGaYBrzWpec9JHHvFe38F9w7C/nNH8fuXX0F29k9obknEJdMXoWu3Hqp11R86hzd+ucnz+ZbnL/B5bV/c8IcvsP5b18LY81cOwqQK7Z5Jr733Hu5Ocs2L7G0t+PEieUxf26lmPPLUY57PN954Izp16iQaTwFg+/kVnpCVLve97zn+3/vHIz8twfP5wK4T+OtTrkXVwh7pmHHnQBjFjh07UFFREZb5uT+iIkhk48aNGDdunKayO3fulCXh+OGHH/DZZ5/h1ltvFSljAGC32wEAzc1y14ympibP92rk5ubKFLlwYrb638ldhjTjkVW/QuVo7Ao0IiBlTImsws7IKgx9dkrt+5Axvt+SoP3MWT1w9Lkt4EwOZF13cWgaCugalPyRcmY3en9/UnSMN/Eut7fyGYZdJ1woZnCSBFBLlTE13JOM9LxEpOf5P6eN8b7JbE9wJLquoS6LSjFkjEwrTJAckjW4UCSRSM7wpqfv6BgAi8mCqd3ECzw8b0Zenv8Nhdn3fEQ2Y3Vgk3ow9+PvzrQ8646OsQOALpW+lcSi3hU+v9eK2p1pjlvkJBmDhcBdOs8BeA8uKxH7m+dkj0dO9nhZ+eLyvigu7wtAnIxl6KCB+LpdIVN2OWODDDvm2UrlzGbxzgPcMWQF+Zdg335XxkKTSdyP8TYzks5Tm6Qz8q66X4AQlJeUxUeIRbDjnlqCM1EMmeJ9tScpgYBe+3b5VcYAH+6sZjM4joMg8Kir6woASE7zvahgTzYuZMAZRAwZe09qLoscx8EmWNDMud8v5X7PonJpeeQH4yZJMWSRRa9evfDqq69qKqvkeug2j0rdFdnyhw4dQufOYgXg0KFDIclsF+noytAY5Sht1KqIih2Z4zjwdjPy7hwccrfdqqoqrF27VrUdelC6nVjKZsRmrjO7Exdo+I1+V9EVT+49jOmtp3Gs/ZheBcqhHg4RUH0+8ZPUQ2myny7ZZzDkST2iVK76ZTDu6oxCJopJ0ZnUI97gmSQGoiyLOmTOKU2wYYA46ZV5s9mMm266CUePHkVBRjq+drfFTwxhRz1/aQyUg5NnGi0uuRHNLUeRnj5EppD5glXC2EUNXjRR19dePYmFfI17SkhlS+0ZibIsKpQRZwXVNyeSxlRxClt/WEx+FC4Du01xDJm+c0UZD9Uc6jiA95d9FuoxeGZJedG2NaSQRRb5+fmYP39+wOevWbMGpaWlGDZM7jbTv39/AMAXX3whUr4OHjyIAwcO4MYbbwz4utGCLAjW4I0q9TIy58cOu5Z2C5n6yhD7/1CiZ1AKBLOGDT2jhVbmuXozOPl/RpNy0jApJw2fffYZ1rUf0zupYpOmcAqqb6dOyvtnBQRrIWuflDn9BHCnSlJ4h2IQ4ERW5OgcUE3sLFMlC5u/jHpxr5Axf7O/ldZVeqV+VY8yp0YgjyUvLw95eXmoP1jrOaZkIWOb11Gx9VI5rEve5/nbrazZrNmoKP+N7rp53oyKimdx6uQX6NZNOdbPfyoj3/has9E97mnMsug3qQeD7vdYugeXgkLmr04t2Tq1wmZZ1Pv+sGOY6pmceCsDtbmUWvIOaX8gygQbpeNHIMT8aLFlyxbs3LkTc+fOVfy+vLwcvXr1wosvviiylqxatQocx+Gyyy7rqKZGDOGwkPW7aLLn76FzF3TYdbUqZGxaV0HDSlAocAeq+iPQ7iuvW1qAZ0YerIXM45KnZ1Xeya7s6/tFpS6BLCUlJbjwwgt11ecTdpuFdqVBlOJYQ9ulq5OGwE5Ko3RA5UUKmfc3YjOu+rs3rf3Dry6tBADMGVKso4WRDzuZ87dQoIYg+WBEFspgZF5sOfG9D53apsRGk2gRW7zOWk96/tayFY0/8nIno0ePJTCbva6F7FPQbSGTKic++imt456nbskIqBbGwe5XqJgdWpR6PTiFjONd+5CJq++4bJ2BvnuAuJ0mtW19OE6kkOm3kImPO8llMTZ5/fXXASi7K7pZsWIFpk2bhgkTJmD27NnYvn07nn32WVx//fXo3bt3RzU1fEhfEp1B3EYw5urr0akwB4VpbcDQ6g67ruZ9yFQm2R2pkC1ZIs9apATPg816rIzkkZcNzsWQqV0DalckUpKVqPA3BzP3E9qEEli57+BrU2jRZpi6XRYZWWH+TEtLwzXXXKOrLr8oxpDpW130lco5UERuLlHqsqhk3QQkaaAN2nNu9pBiXNQnD5lJAcQARzCsUusQAlv1lna9RihkQbnp6lC4wmUhZd3xjFDIlBApZEFbyNSfh9ZxT40LrlVW6PzFkIk2gNepWMvmC7zcQtaRmcn1LtKpoXYmxwFODQqZ2tsgs5CJ+lg9LYxuYtpC5nQ68cc//hEDBw5Ez549VctNnToVb7/9Nurr67Fw4UK8/fbbWLx4MVauXNmBrQ0v/dpTdWccr9e/GmQAFqsNfSZXI23E3A7du02zhQyshUz7hMxI3n33XdXv2GQ1/Qv1b7Y98foKWGyxEzs4pbIAVf064dKBhbh0YHvmTI5DjvVBpJufQZb1YZ/na1XUlWhTXUQMgawoWMjY1VBf+7t4yoRChEVWhOgcUXmVZX/xZMGP25GOZ56VrJwhOJrhWQuZUqIdDbD9LYTwuSwq16PgsihKghGeKZZoLz4/7niBEoysSs/09Sv5GvcU65bIllpyMNZl0Z/Sqt9CJvnMyy13fl0WI6QrECmmqjFkYpVcbS6lJjPS/kA0rEXpgl4gxLSFjOd5HGjfJ8YfM2bM8OwfFndwHHrs3o3M+nqknzwJPPzLcLeow9BuIWM/hcdlsbRUOS0w4FLIqqursW/fPoxN+QnwsweyEOSKZqRjNvF4Zs4AyVEOJu4Eks3rFM9hCUYh61GQCt/b6RoIm9SjffLXpjOjVqhlOFpdTtRaLVr9NshlMVZhFbK2AFfpxXNbQZcyp0YwVjaRwqXosgjf33cArELWIRayIHdP8iUPvsY9JbQqiq1O775sitmhjXRZ5AKwkBmokQUTj3buRD1gb497dqjsUi2JIdPb70nfR6cOt/BYIr5HC8IFx4EXBOTW1cHa2hq2QSQcsJMr7TFkXjpywuVvC4Y+ffpg0qRJSGCTc0T+NoMdRwfFkHXNYeMsQmxNFbkstlvIggjgNopoXeEsrvDuGaf20wlMrLE/C0jcK2TMbyiSSx0/SyhcFoN6L3RM1DtyLE1MS1c8HiqFjEXvrymzkPmowN+4F2hrRAqZUsZD1sVWr8uiNKkH5P2/v/HAyF4zmAXY77/4r+dvZ6vKfsASl0Xf3kYKp0t+C1Ha+0gxFXYA8T1aEMp0oMtgJOEzyyKUFbKO7Cw2b97cYdeKd1gX0ESN+5UpwmZcDLnLojyGzAhrQiCwk+9oWuGcfMudqBg3AdPvflC1TGaR1wVq4ORpPuuLd4UshW/y/O0QudL6/13G5WwFIM/fZ9Gbt1uBoJQ6f/Glkn0qO4pL71uKinEX4arHnxYdD5mFzECXRZMP9UPvuKe1v7m0+6Wev7MSsmTfO50at8RRQoNC5rdOA7tN9p2xmvXdC5vEiFe4LwCak3poRbR4E0ULesESnzNvQox05caAAS8a0WohY+nIAfe6664zrrL46eO86JhADBkyBF988QU4jsOAAVLXR3+XUb5OR8WQtelM6hGKdrErnNEUQ5acmYWJC25zfXhfuUxiahrmPvIkztQfQ/chI3zWF0+ru0pMTdnp+VuvXGbaGwDIY8jCndRD7E7lJ4asA8eHvG5lmLjgdteHDd7jypseB4/oJwzaZVH9O/3jnrZne0nZJThy7gh6ZPZATmKO7HtWEYHOWEClJGC6sywayENT+2DKM5+gMN2O/p3TdZ0rMIopp5JlkeOARFjRAJcFzT2XGpRix5dnGnW318R4+SRn2HSfH63E58yb8ElHpeqNBFjrh68O0sm4KSUw1pPMzMzQNEyBRYsWaSvo8LpiqO2fJLLyxc0qvvYBMCEhAbfffjtuu+02WFXSJkcECvuQtTETCUuYVhedMb6PTEH3nugx9HzDsizGKmkWb18k3opC+XeblJ6O1FOnMPLjjz3uoOyiPAdjZDoYmRRZDPxsGBwJfWvoYsgYxVP/ySJ8Kciaxz131Robk2hJxJ2D78TUblMVv2fH/GAsZElD89vbFb4si93zUrB58Xisu2M0zDoX3FndUj1WkMMFLRUwCTxKHDme3+up7oHtuVk6IBfZnZORmp2A/hfG1lYgvgh/b0FEHjrT3t84uhsAYOEFZaFoTUi59NJLYTKZ/G5vUNLXayUZf/EU9OjRA+Xl5T6zdxrN73//e20FS5hV+z7T/Rb3Ndi4fee7DRqiWiZq0DkAmkwm3b7wskvqSJEeEII87f0FvXI9h4Z3k7viSGHbVVRUZEizRFaEOHI5ISQwstUzL8Xz98xBynJWlmDH5A8+RGHtQdVAMyMsZMHAurIpJ/UIj8uiGh0x8Q82qYevFmoe9zx1GXO/Jot3Ia5Tj166zhXamH6/XQGSWsj8Z1k09rmlJ1p1uysC6lv+iOCAfCEDVzWPxoWtld5rmtXHzymVBQCU32eTmUf14vNw5cPDkZCkEN8Xo5DLIiFD76re/ZN74aphJSjK0Bt8G37Kysrw85//3K8VJLtzCWYteRRtrS3o1L0n5nbvOEXMTVVVFdauXeu/YKf+QPVqoLUR6HK+3+K+EhNcveJZfP/FJlSMu0hHSyOV8E7kQp/UwzX4jeuZixWX9UWSzYzuzCRYDZ7nMXbsWOzatcuwTLPR6rJIGI332RdnJeLleYNx5HQzJpXnqxRnZKVdbkROUga5LAaDs82baY5XWLxkbyFcFrIHhz6IRzY9ghy73BXPKIJJjCJVmnxZyDSPe97KDSGzUyH6T5yCo3t/xMjZV+s6l2MUHz7VNbfQn2VR1yVDhjaFzNVYM0ySw+o3sfySSgwoTsfoHsoyynFcxPwGHQUpZETQE0WO49A5M4jEB2HGZtPmo8xmYAsHugalPr6TDWh1Wcwq7Ky6j0vUEeZ4ntBbyMye68wa7PuZrenbDYu+24efdXZZ08aOHYuxY8ca1qxYd1kktCKezI3vneenOJsMxtR+yHusU1oC7JbwutRnFhbBkmBHa1MjLph3o8+ynB+XxlAxq+csdEvvhtJ0fSnj9SBKex/0xtDq3+ka92CsEjz+2psCOi+xXw5Offgj4BCQNNDVx4Yzy2JQaGlIAI1NS7Tg+lHd9J8Yw4Tfnk6EnzgPPI8W9PrSayUS4hw6hlhUyNjAc+2TvwuyUvH1iHLseeox49sEwMmmLY5Wl8Ux97n+P+Cq8LYjyrC0nAQAnI/PdSdDEMlzu6sXayGbO6Q47IlSLLYEzH/yOVyx/CkU9i5XKBF+l0We43Fe/nnITAhdjLNoUU+nPibLsmhkDFkEqDK83YyCn5+H/PuGwJQaYFKK8N8GAEBgno3VR9p7InjIQkYQUcItt9xiXGWsZ1C8KGSxuPDglGdZ1ArHccbKFAOrkJmiNWvrmHtdluYcffEj8c6c6suQ9O7VyMFxoOxuXecKDnkGQ3auH253RTep2TlIzfbhauX+O5b7VtGjCM5C5utXClUfFWr4RHHsk96FhEhQLAGg6NwppJ86htPJ6bho41+BufK4dPXMwqFuXWxBChlBb02UsHHjRpSVGZ84JaYnDSI6Xs47NqmH/ucYOpliVlXtUTrM8DyQp2QBIXzx0Ve7cW3VQ0DdLmC0PoVMvMDgdlk0sHEdTCz3rdLsl3rQYyHT3UfFynwmQm5j9OVXoukPz6LFYkVBqv+Y5MQBuX7LEMpE6UhJEPFHRkZGSOqN5UmDiFiMIXPKY8j0ECqZ6jksH19+sBeONicGTIiftMVEu0wNuiSgcwXRvnqu90W04Ww0TLbjxPuAdSXVm2VR+hh9GT719lGRGrOqu/+PkNsoKOsJs6MNZkcbeB/PIvu6CjT/cAopY7wZVCPFyhctkEJGhH2iSmijsLDQsLpoH7IwXD2CYsjcGClTLBarCVcuG+7KimeJF/lykXDge7R16Ynhw4eHuylhISiZUnBZFE38A68Zf7xxGO5/exuuHl4SRC3+EZxsYpIYln0DLZcmH09WvzxF5nxGv8tiZCCSYR/3kNA9AwndpQpbpNxFdBDDvQVBxBbr1q0LSb0xPWlgicWFB4Usi3oIlUwBrr1k4k0ZAwDLmRO4//77MX78+HA3JSwEJVMK2zggCNc4lmHdsvCfu8fimvO7BlGLf9iNo2O5bxXY9P56LWSSz76MWnrlKdxJXwwjAu9Dt1IZebcQ0cRub0Foh96aqOCuu+4yrjKOTUseL91Ax8s5m6EqJL+zQsyNHgyVKcJDsBuKRzPByJTIumSSJ/WIhpGKdbuM5b7VyNA+XzFkeuUpUhWyWLCQRepvGyvEbm9BEDHG/PnzQ1Jv3HSyYbhPViELfVIP/UpAqGSKiF+CkikHI8+cWyFjY8gCr7qjiBsLmchyqddCpn1jaN3yFAUyookIvA/9FrIIvIkIJnZ7C0IH9NJEA2+99VZI6o3lSYOYGFTIWBevAGLIQiVTRPwSjEwpJfUQZ/OL/LHK6YgPC1kqs0F3p5PHgqrLV8+lV544vXvfdRCxoMxEq5UvWohMySU6lAh87wkFqqqqDKtLnNQjTtyrwmwhC8nkLMgYMiNliiCAIGVKlBBD3i9Fw1jFKpWx3LdmWcw4f89W9Di8D8N/2KHrXOlj9DXR1ytPkajIRDOCyC2eVIZQQlkWCSJKWLt2rXGVxUlqZhFhWDkNvcticDFkhsoUQSBImXLK99WLtm3I4sVlEQAqD/5gSD0mH11jrPRRgfT/qdkJOH2sCeOuCt/m9EIQe2mSbqyP2O4tCG3QWxMVLF68OCT1xvqkIZx0qMtiABayUMkUEb8EI1MCm/ZeIalHNOB0xofLYjBIu0JfMWR65SlSLWSBtOuy+wbjkrsGovfwghC0SCMihYzkOZSQhYwgooQ5c+YYVpfIZTFCBzDDiUWXRfZJBmAhM1KmCAIIUqYUsoZGXZbFOLGQGTlu+PqV4rmPsidbYe9uDWsbnCJ51vfM+ah4YyOH2O0tCO3Ey4Q8ytm2bVtI6o3lSYOYGEzqwRKAhSxUMkXEL8HIlCCy+Mrfl2gYqUQKGVkUFJE+R18Wsljpo6J14TMYl0VxRU7/ZeIc6i0IIs6JG7eacAyIHRmrF0CWRYKIKERJPdpdFnVuOhxukrOyPH+XVPYPX0MiGLlCFpZmEBoQJakJYoGBi67XOCyQyyJBFrIoobKyMiT1xs8qbsfLuZPrwE01A7CQhUqmiPglKJliXRY5eQxZNFgZCsp64vzqK3Hu1AlUjp8Y7uaEDGNdFtXr0itPkSojkdouf5jM3nElOStb17nRes/hIl5mYgQR9bzxxhshqTduXBbDMDhkHT/u+fv8888P7cUCiCELlUzFI5c9+AjyupWhatF94W5KWAlGpkTufu1JPW4pzgXgmqzMyE0PpmkdxrCZszH+2ptEk1nCi3Si7is0KVb6qGhVTvJLe6Ck7wCk5uThgvk3BlETmcj8Qb0FQRayKGH58uWG1cU+8bhRyMJgIUtsbMT8adPQlpqKzp07h/ZiAbzHRspUvFNS2R8lj/0m3M0IO0HJlEJSjxK7DV8M7wMrxyHDQlOWWMRXDFkw8tSrV/jSxccKHMfhsgeWQRAESnsfYuJlJkb4gt6aqMDITXxZf26KIQsthXl5KCsrC03lg+a7/h9g/BhtDE0YTTAypZbUoyjBilybJZhmERGMrxgyvfLE8zx69+4Ns9mM4cOHB9ky44hWC5mbgNrPJrUiA5lfaLmJIKIEIzfI5ASmo4wXhSxcOdpC+ftOeBTI6AJ0GRXQ6bGy6SoROQQlU6J9yChJTSTTUTFkgchTdXU1WltbYbWGN2V8vMOJnitpZP6Il5kY4YPoXreJH6qrqw2ri12tihuFTDSB6ECpDyC2SzO2ZGDkIqBocECnGylTBAEEKVOCPKkHEfv4iiELRJ44jos4ZSzaLWTBEt93rw3q8QgiSvjd735nWF1xqZCJctB33Oq73s00OxIjZYoggOBkSnCyvtSR+94QxuLLQhYrfVS8K2SEf+JlJkb4gjqKqODJJ580rC7WZTEuY8iS8zvuuhHsemWkTBEEEKRMObwxZOSyGNkY6rLooyrqo2IDLsr2EwwHcTITI4joZ+JE4/a0EY1/8aKQm21A7yrAlgbMWdNx143g39dImSIIIDiZYjehDWnsJRE0rEJWUFAQVF2+sizGSh8VjxYygY0bI4XML5TUg4joCSPhpba21rC64jLLIgBc/hrgaAVMHZexLZJX+o2UKYIAgpQpNqlHPPVLUQjP8xg1ahR2796NmTNnBleXj+9ipY+KR4WM1cc4SurhF1LICFLIooQTJ04YVhcvclmMXIUhJHSgMgYgolf6jZQpggCClCmFfciIyGX8+PEYP3580PX4moJQHxW9MG8zuSxqIHJnCgRBiBg9erRhdXFsMrMItuDEApG80m+kTBEEEJxMsS6LkZwMhzAWX0k9qI+KXpJMPJLPnQYATP73X8LcmsgncmcKRMdBFrKoYOXKlYbVJbKQkUIWWiJYITNSpggCCFKmHBRDFo/40r2pj4peeI7DtW/+FvPfegY99u4Md3MiHurxCCJKeOqppwyr65y9zfN3Ue8Kw+ol5ESyhcxImSIIIDiZEpzeLIukkMUPvixk1EdFN7aWZuTUHwl3M6IC6vEIspBFCVVVVYbVNfuim1BTeBaWsnz0HjXWsHoJBSJ4YmmkTBEEEKRMMfuQkSt1/ODLQkZ9FBEvUFIPgogS1q5da1hd11Veh9mPz0aSJcmwOgkVInhiaaRMEQQQpEwx+5CBi9yFDMJYfD1p6qOIeIF6PCI+07FGIfPmzTO0PlLGOoZIfr+MlimCCEamBCYTGyX1iB989ZHURxHxAilkBBElkC89YTQkU4TRBCVTTkrqQYihPoqIF6jHI4go4eWXXw53E4gYg2SKMJpgZEqc1CNyXX2JjoP6KCJeiFmFbOzYseA4TvGfxSLeGLZLly6K5RYsWBCm1hOEnCFDhoS7CUSMQTJFGE1QMuUkl0VCDPVRRLwQs0k9HnjgAVx//fWiY+fOncOCBQswYcIEWfn+/fvjrrvuEh3r0aNHSNtIEHpobGwMdxOIGINkijCaoGSKXBYJCdRHEfFCzCpkF110kezYa6+9BgC44oorZN8VFhbiyiuvDHm7CCJQvv/++3A3gdBI8e9/j9o77kD6ZZeFuyk+IZkijCYYmaJ9yAgp1EcR8ULMKmRKrFmzBklJSZg+fbri9y0tLWhtbUVSEmWfIyKPGTNmhLsJhEaShg5B90//L6IzLAIkU4TxBCNTCX36oKXGNQE3paYa1CIimonFPiojIyPcTSAikLhZgqqrq8P69esxY8YMRYXr3//+NxITE5GcnIwuXbrgt7/9raZ6jx49ih07doj+1dTUGN18gsCyZcvC3QRCB5GujAEkU4TxBCNTefffj6Qxo5F9802w5Ocb2CoiWomlPmrGjBkoKysjbyxCkbhRyN588020tbUpuiv27dsXS5cuxV/+8he8/PLLKC4uxh133IF7773Xb73PPfccKioqRP/cKzqffPIJNmzYgBUrVqC+vt6zn4Z75/lFixahpqYGr7zyCt555x1s3rwZy5YtQ0NDA6qrq0VlFy9ejG3btmHNmjVYs2YNtm3bhsWLF4vKVFdXo6GhAcuWLcPmzZvxzjvv4JVXXkFNTQ0WLVokKjtv3jzU19djxYoV2LBhg+ie3MlM3GUXLFiA2tparFy5Eh9++GHU3NOHH36IlStXora2Nibuac6cOTF3T7H4nKLpniZOnBhz9xSLzyma7mn06NEB39MlV1+N4hdewN1ffhlR9xSLzync98Ti654mTpwYNffk7zklJyejpaUFGzdujJl78id7LJFwT5988omsXZECJ7A7MUYoTqcTLS0tmsrabDbFlekRI0agpqYGBw8ehNns21NTEARMnjwZ//rXv/Djjz+iqKhItezRo0dRV1cnOlZTU4MZM2Zg+/btKC8v19TucLN3zlw0btmCgkcfQfrMmeFuDqFAVVUV1q5dG+5mEDEEyRRhNCRThBby//O15+/D4/qrliN5im6evHyq5++73nwvjC1xsWPHDlRUVETk/DwqYsg2btyIcePGaSq7c+dO9OrVS3Tshx9+wGeffYZbb73VrzIGuFyNFi1ahHXr1uGjjz7yaV7Ozc1Fbm6uprZFMsWvvoKWn36CjTJLRiw0KBFGQzJFGA3JFGEkJE9EvBAVClmvXr3w6quvaipbUFAgO7ZmzRoAytkV1ejcuTMAoL6+XvM50QyfkICEnj3D3QzCBwsWLMDzzz8f7mYQMQTJFGE0JFOEkZA8EfFCVChk+fn5mD9/fsDnr1mzBqWlpRg2bJjmc3744QcAQE5OTsDXJQgjWbJkSbibQMQYJFOE0ZBMEUZC8kTECzGf1GPLli3YuXMn5s6dq/h9fX09HA6H6Fhrayt+9atfwWq1anaVJIhQ8+6774a7CUSMQTJFGA3JFGEkJE9EvBAVFrJgeP311wGouyv+7W9/wyOPPILLLrsMXbt2RX19PdasWYPt27dj+fLlyKfUu0SEUFpaGu4mEDEGyRRhNCRThJGQPBHxQkwrZE6nE3/84x8xcOBA9FSJj6qsrESfPn3w2muvoa6uDlarFf3798dbb72FWbNmdXCLCUIdu90e7iYQMQbJFGE0JFOEkZA8EfFCTLss8jyPAwcO4Msvv1QtM2jQIPztb3/DgQMH0NzcjDNnzuDjjz8mZYyIODZv3hzuJhAxBskUYTQkU4SRkDwR8UJMK2QEEUtcd9114W4CEWOQTBFGQzJFGAnJExEvkEJGEFGCe6d6gjAKkinCaEimCCMheSLiBVLICCJK+P3vfx/uJhAxBskUYTQkU4SRkDwR8QIpZAQRJVRVVYW7CUSMQTJFGA3JFGEkJE9EvEAKGUFECWvXrg13E4gYg2SKMBqSKcJISJ6IeIEUMoKIEsiXnjAakinCaEimCCMheSLiBVLICCJKuOWWW8LdBCLGIJkijIZkijASkiciXiCFjCCihI0bN4a7CUSMQTJFGA3JFGEkJE9EvEAKGUFECRkZGeFuAhFjkEwRRkMyRWjh/q4FAIBFJXk+y5E8EfGCOdwNIAhCG4WFheFuAhFjkEwRRkMyRWjh9i55mFOQiVybxWc5kiciXiALGUFECevWrQt3E4gYg2SKMBqSKUIr/pQxgOSJiB9IISOIKOGuu+4KdxOIGINkijAakinCSEieiHiBFDKCiBLmz58f7iYQMQbJFGE0JFOEkZA8EfECKWQEESW89dZb4W4CEWOQTBFGQzJFGAnJExEvkEJGEFFCVVVVuJtAxBgkU4TRkEwRRkLyRMQLpJARRJSwdu3acDeBiDFIpgijIZkijITkiYgXSCEjiChh8eLF4W4CEWOQTBFGQzJFGAnJExEvkEJGEFHCnDlzwt0EIsYgmSKMhmSKMBKSJyJeIIWMIKKEbdu2hbsJRIxBMkUYDckUYSQkT0S8QAoZQRAEQRAEQRBEmCCFjCCihMrKynA3gYgxSKYIoyGZIoyE5ImIF0ghI4go4Y033gh3E4gYg2SKMBqSKcJISJ6IeIEUMoKIEpYvXx7uJhAxBskUYTQkU4SRkDwR8QIpZAQRJdAGmYTRkEwRRkMyRRgJyRMRL5BCRhBRAm2QSRgNyRRhNCRThJGQPBHxAilkBBElVFdXh7sJRIxBMkUYDckUYSQkT0S8QAoZQUQJv/vd78LdBCLGIJkijIZkijASkiciXiCFjCCihCeffDLcTSBiDJIpwmhIpggjIXki4gVSyAgiSpg4cWK4m0DEGCRThNGQTBFGQvIU3RSU9QQAjL36hjC3JPIxh7sBBEFoo7a2NtxNIGIMkinCaEimCCMheYpuZi15FMdr9yOvW1m4mxLxkEJGEFHCiRMnwt0EIsYgmSKMhmSKMBKSp+jGkpCA/NLu4W5GVEAuiwQRJYwePTrcTSBiDJIpwmhIpggjIXki4gVSyAgiSli5cmW4m0DEGCRThNGQTBFGQvJExAucIAhCuBsRa+zYsQMVFRXYvn07ysvLw90cgiAIgiAIgohrInl+ThYygogSqqqqwt0EIsYgmSKMhmSKMBKSJyJeIIWMIKKEtWvXhrsJRIxBMkUYDckUYSQkT0S8QAoZQUQJ8+bNC3cTiBiDZIowGpIpwkhInoh4gRQygogSnnrqqXA3gYgxSKYIoyGZIoyE5ImIF0ghI4go4eWXXw53E4gYg2SKMBqSKcJISJ6IeIEUMoKIEoYMGRLuJhAxBskUYTQkU4SRkDwR8YI53A2IRZqbmwEANTU1YW4JEUt89913yM7ODncziBiCZIowGpIpwkhInggjcc/L3fP0SIIUshCwbds2AMCMGTPC2xCCIAiCIAiCIDxs27YNAwcODHczRJBCFgJ69OgBAHjrrbfQp0+fMLeGiAVqamowY8YMvPvuuygrKwt3c4gYgGSKMBqSKcJISJ4Io/n2229RXV3tmadHEqSQhYDU1FQAQJ8+fSJuJ3AiuikrKyOZIgyFZIowGpIpwkhIngijcc/TIwlK6kEQBEEQBEEQBBEmSCEjCIIgCIIgCIIIE6SQEQRBEARBEARBhAlSyEJATk4OfvGLXyAnJyfcTSFiBJIpwmhIpgijIZkijITkiTCaSJYpThAEIdyNIAiCIAiCIAiCiEfIQkYQBEEQBEEQBBEmSCEjCIIgCIIgCIIIE6SQEQRBEARBEARBhAlSyAiCIAiCIAiCIMIEKWQEQRAEQRAEQRBhghQyA2lubsa9996LTp06wW63Y+jQoVi/fn24m0WEic8//xy33norysvLkZSUhOLiYlRXV2P37t2ysjt37sSkSZOQnJyMzMxMXHXVVairq5OVczqd+PWvf42uXbsiISEBffv2xRtvvKF4fa11EtHNo48+Co7jUFFRIfvu008/xciRI5GYmIj8/HzcdtttOHv2rKycnr5La51EdPHVV19h2rRpyMzMRGJiIioqKvD000+LypA8EVrZs2cPZs+ejaKiIiQmJqJXr154+OGH0dDQICpHMkVIOXv2LH7xi19g0qRJyMzMBMdx+N3vfqdYNpxzJz11akIgDGP27NmC2WwW7r77buGFF14Qhg8fLpjNZuHjjz8Od9OIMDBz5kwhPz9fWLhwofDSSy8Jy5YtE/Ly8oSkpCRh27ZtnnL79+8XsrOzhdLSUuG3v/2t8OijjwoZGRlCv379hObmZlGd9913nwBAuOGGG4QXX3xRmDJligBAeOONN0Tl9NRJRC/79+8XEhMThaSkJKG8vFz03ZYtW4SEhARhwIABwqpVq4QHHnhAsNlswqRJk2T1aO279NRJRA/r1q0TrFarMHToUOF//ud/hBdffFG49957hXvuucdThuSJ0Mq+ffuE9PR0oaSkRHjssceEF154QZg/f74AQJg2bZqnHMkUocSPP/4oABCKi4uFsWPHCgCEV199VVYu3HMnrXVqhRQyg9i0aZMAQFixYoXnWGNjo1BaWioMHz48jC0jwsX//d//yV7g3bt3CzabTbjiiis8x2666SbBbrcLP/30k+fY+vXrBQDCCy+84Dl24MABwWKxCLfccovnmNPpFEaNGiUUFRUJbW1tuuskopvLL79cuOCCC4QxY8bIFLLJkycLBQUFwqlTpzzHXnrpJQGAsG7dOs8xPX2X1jqJ6OHUqVNCXl6ecMkllwgOh0O1HMkToZVHH31UACBs375ddPzqq68WAAj19fWCIJBMEco0NTUJhw4dEgRBED7//HNVhSyccyc9dWqFFDKDuOeeewSTySTqBARBEJYvXy4AEPbt2xemlhGRxsCBA4WBAwd6Pufm5gqzZs2SlevRo4cwfvx4z+eVK1cKAIQdO3aIyq1Zs0YAIFop1FonEb1s2LBBMJlMwtatW2UK2alTpwSz2SyycAiCIDQ3NwvJycnCdddd5zmmte/SUycRPaxatUoAIHz77beCIAjC2bNnZYoZyROhh3vvvVcAINTV1cmO8zwvnD17lmSK0IQvhSyccyc9dWqFYsgMYsuWLejRowdSU1NFx4cMGQIA+Prrr8PQKiLSEAQBR44cQXZ2NgCgtrYWR48exeDBg2VlhwwZgi1btng+b9myBUlJSejdu7esnPt7vXUS0YnD4cDChQtx/fXXo7KyUvb9tm3b0NbWJpMBq9WK/v37y+RKS9+lp04ievjnP/+J1NRU1NbWomfPnkhOTkZqaipuuukmNDU1ASB5IvQxduxYAMB1112Hr7/+Gvv378ebb76JVatW4bbbbkNSUhLJFBEU4Z47aa1TD6SQGcShQ4dQUFAgO+4+dvDgwY5uEhGBvP7666itrcXll18OwCU3AFRlp76+Hs3NzZ6yeXl54DhOVg7wypieOono5Pnnn8dPP/2EZcuWKX7vTwbY/khr36WnTiJ62LNnD9ra2jB9+nRMnDgRf/nLX3Dttdfi+eefxzXXXAOA5InQx6RJk7Bs2TKsX78eAwYMQHFxMWbPno2FCxfiqaeeAkAyRQRHuOdOWuvUg1n3GYQijY2NsNlssuMJCQme74n45rvvvsMtt9yC4cOHY968eQC8cuFPdmw2m2YZ01MnEX0cP34cDz30EJYsWYKcnBzFMv5kgO2PjJIr6uOik7Nnz6KhoQELFizwZFW89NJL0dLSghdeeAEPP/wwyROhmy5dumD06NGYOXMmsrKy8P7772P58uXIz8/HrbfeSjJFBEW4506hmPOTQmYQdrtd0ergdvmw2+0d3SQigjh8+DCmTJmCtLQ0/PnPf4bJZALglQstsqNVxvTUSUQfDz74IDIzM7Fw4ULVMv5kgH3+RskVyVR04n5uc+bMER2fO3cuXnjhBXz22WdITEwEQPJEaOOPf/wjbrzxRuzevRtFRUUAXEq+0+nEvffeizlz5lAfRQRFuOdOoZjzk8uiQRQUFHjMnSzuY506deroJhERwqlTpzB58mScPHkSH374oUgW3OZtNdnJzMz0rMIUFBTg8OHDEARBVg7wypieOonoYs+ePXjxxRdx22234eDBg9i7dy/27t2LpqYmtLa2Yu/evaivr/crA1IZ1NJ36amTiB7czy0vL090PDc3FwBw4sQJkidCF8899xwGDBjgUcbcTJs2DQ0NDdiyZQvJFBEU4Z47aa1TD6SQGUT//v2xe/dunD59WnR806ZNnu+J+KOpqQlVVVXYvXs33nvvPfTp00f0fWFhIXJycvDFF1/Izt28ebNIbvr374+Ghgbs3LlTVE4qY3rqJKKL2tpaOJ1O3Hbbbejatavn36ZNm7B792507doVDz/8MCoqKmA2m2Uy0NLSgq+//lomV1r6Lj11EtHDoEGDALhki8UdA5GTk0PyROjiyJEjcDgcsuOtra0AgLa2NpIpIijCPXfSWqcudOdlJBT573//K9sno6mpSSgrKxOGDh0axpYR4aKtrU2YNm2aYDabhffff1+13IIFCwS73S7aGuGf//ynAEBYtWqV59j+/ftV970oLCwU7XuhtU4iuqirqxPeeecd2b/y8nKhuLhYeOedd4StW7cKgiAIkyZNEgoKCoTTp097zv/f//1fAYDwwQcfeI7p6bu01klED1999ZUAQJg7d67o+Jw5cwSz2SzU1tYKgkDyRGhn6tSpgtVqFXbt2iU6PmPGDIHneZIpQjO+0t6Hc+6kp06tkEJmILNmzfLsgfHCCy8II0aMEMxms7Bhw4ZwN40IA7fffrsAQKiqqhJWr14t++dm3759QlZWllBaWio8/fTTwvLly4WMjAyhsrJSaGpqEtV5zz33CACEG2+8UXjppZc8O8O//vrronJ66iSiH6WNob/88kvBZrMJAwYMEFatWiU88MADQkJCgjBhwgTZ+Vr7Lj11EtHDtddeKwAQqqurhZUrVwqzZs0SAAj333+/pwzJE6EV9x6Jubm5wsMPPyysXLlSmDx5sgBAuP766z3lSKYINZ555hlh2bJlwk033SQAEC699FJh2bJlwrJly4STJ08KghD+uZPWOrVCCpmBNDY2CnfffbeQn58v2Gw24bzzzhM+/PDDcDeLCBNjxowRAKj+Y9m+fbswYcIEITExUUhPTxeuuOIK4fDhw7I6HQ6HsHz5cqGkpESwWq1CeXm58NprryleX2udRPSjpJAJgiB8/PHHwogRI4SEhAQhJydHuOWWW0Qrx2709F1a6ySih5aWFmHp0qVCSUmJYLFYhLKyMuGpp56SlSN5IrSyadMmYfLkyUJ+fr5gsViEHj16CI8++qjQ2toqKkcyRShRUlKiOnf68ccfPeXCOXfSU6cWOEGQRKQRBEEQBEEQBEEQHQIl9SAIgiAIgiAIgggTpJARBEEQBEEQBEGECVLICIIgCIIgCIIgwgQpZARBEARBEARBEGGCFDKCIAiCIAiCIIgwQQoZQRAEQRAEQRBEmCCFjCAIgiAIgiAIIkyQQkYQBEEQBEEQBBEmSCEjCIIgCIIgCIIIE6SQEQRBEARBEARBhAlSyAiCIIiIZ/78+ejSpUu4m+Fh6dKl4DgOHMchOTm5w6/fv39/z/WnTp3a4dcnCIIgjMMc7gYQBEEQ8QnHcZrK/ec//wlxSwJn9erVsFgsHX7d5cuXo76+HosWLerwaxMEQRDGQgoZQRAEERZWr14t+vyHP/wB69evlx3v3bs3XnrpJTidzo5sniauvPLKsFz34osvBgA8+OCDYbk+QRAEYRykkBEEQRBhQarM/Pe//8X69evDpuQQBEEQRDigGDKCIAgi4pHGkO3duxccx+GJJ57AypUr0a1bNyQmJmLChAnYv38/BEHAsmXLUFRUBLvdjunTp6O+vl5W7wcffIBRo0YhKSkJKSkpmDJlCnbs2BFUW7t06YKpU6fio48+wuDBg2G321FZWYmPPvoIAPD222+jsrISCQkJGDRoELZs2SI6//Dhw7jmmmtQVFQEm82GgoICTJ8+HXv37g2qXQRBEERkQhYygiAIImp5/fXX0dLSgoULF6K+vh6//vWvUV1djQsuuAAfffQR7r33XtTU1OCZZ57B3XffjVdeecVz7urVqzFv3jxMnDgRjz/+OBoaGrBq1SqMHDkSW7ZsCSqJSE1NDebOnYuf/exnuPLKK/HEE0+gqqoKzz//PBYvXoybb74ZAPDYY4+huroau3btAs+71khnzpyJHTt2YOHChejSpQuOHj2K9evXY9++fRGV2IQgCIIwBlLICIIgiKiltrYWe/bsQVpaGgDA4XDgscceQ2NjI7744guYza5hrq6uDq+//jpWrVoFm82Gs2fP4rbbbsP111+PF1980VPfvHnz0LNnTyxfvlx0XC+7du3Cp59+iuHDhwMA+vTpg4kTJ+KGG27Ad999h+LiYgBARkYGfvazn2Hjxo0YO3YsTp48iU8//RQrVqzA3Xff7anv/vvvD7gtBEEQRGRDLosEQRBE1DJr1iyPMgYAQ4cOBeCKT3MrY+7jLS0tqK2tBQCsX78eJ0+exJw5c3Ds2DHPP5PJhKFDhwad2bFPnz4eZYxt1wUXXOBRxtjjP/zwAwDAbrfDarXio48+wokTJ4JqA0EQBBEdkIWMIAiCiFpY5QaARznr3Lmz4nG3krNnzx4ALgVJidTU1LC0y2az4fHHH8ddd92FvLw8DBs2DFOnTsXVV1+N/Pz8oNpEEARBRCakkBEEQRBRi8lk0nVcEAQA8KTQX716taKiw1rXOrJdAHDHHXegqqoK7777LtatW4clS5bgsccew7///W8MGDAgqHYRBEEQkQcpZARBEETcUVpaCgDIzc3FhRdeGObWyCktLcVdd92Fu+66C3v27EH//v3x5JNP4rXXXgt30wiCIAiDoRgygiAIIu6YOHEiUlNTsXz5crS2tsq+r6urC0OrgIaGBjQ1NYmOlZaWIiUlBc3NzWFpE0EQBBFayEJGEARBxB2pqalYtWoVrrrqKgwcOBCzZ89GTk4O9u3bh/fffx/nn38+nn322Q5v1+7duzF+/HhUV1ejT58+MJvNeOedd3DkyBHMnj27w9tDEARBhB5SyAiCIIi4ZO7cuejUqRN+9atfYcWKFWhubkZhYSFGjRqFa665Jixt6ty5M+bMmYN//etfWL16NcxmM3r16oW33noLM2fODEubCIIgiNDCCWwkMUEQBEEQflm6dCl++ctfoq6uDhzHISsrq0Ovf/LkSbS1tWHgwIHo27cv3nvvvQ69PkEQBGEcFENGEARBEAGSk5ODkpKSDr/u2LFjkZOTg/3793f4tQmCIAhjIQsZQRAEQejkhx9+8GzmbDabMXbs2A69/qZNm3DmzBkALqWwX79+HXp9giAIwjhIISMIgiAIgiAIgggT5LJIEARBEARBEAQRJkghIwiCIAiCIAiCCBOkkBEEQRAEQRAEQYQJUsgIgiAIgiAIgiDCBClkBEEQBEEQBEEQYYIUMoIgCIIgCIIgiDBBChlBEARBEARBEESYIIWMIAiCIAiCIAgiTJBCRhAEQRAEQRAEESZIISMIgiAIgiAIgggTpJARBEEQBEEQBEGEif8HHI48KbR8EcIAAAAASUVORK5CYII=\n", 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" ] @@ -8606,7 +8643,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -8619,12 +8655,12 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 25, "metadata": {}, "outputs": [ { "data": { - "image/png": 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DwUBiYiIZGa6jrHU/i8Zk79OnT4PjlI2Nu3v37h7GaWvG1FJUKlWDz69fv34AHuOvrq5uVf8CQWOIeS90adLv2umAk3up2PgczqpiUGQc/S52G20T1L8wcc+dHHlpGlZLYOaijk7XzF4nEHRirr/++mCLIGgjEiLD6JcS5fVa78RI4iPtpMbo3WUOp8ynvxzDoSj0TopkWI8Ydhwp5eWaMMqpMXr6pUQRY9A26K/2PhmpsQGR/bbbbmP58uXMnTuXM888k5iYGCRJ4sorr0SWPVdgp0+fzmOPPUZRURFRUVF8+umnXHXVVWg0nWPKmjZtGj/88APz589n+PDhREZGIssyF110UYPPwl/82YlozNfO6XS2uk+AhIQEv9oLBPUR815oU9/vWpIdzIrfhfrgWpTSbDQnDmJVZJyGeH7avJkdppGMykhkMAlUHHMtRlZXlBFm8D7/dSX8mgXrOhs3hghOIhC0L/PmzfMalU/Q8RnXN4Fxfb2/9M4+r4/H77XRI7MKqrhydHqD4CTgClhyyVDvEf7uuWgAANnZ2QGRfeXKlcyYMYOnnnrKXWaxWCgrK2tQd/r06Tz88MN8+OGHJCcnU1FRwZVXXum+npSUhF6vJysrq0Fbb2X1qc1HevDgQfcuHriOcGZnZ3Paaad51N21axeyLHvsUO3bt8+jr1oOHjzY4H4HDhygV69eAJSWlvLNN9/w8MMP8+CDDzbZrjHZf/vtNxRF8TCsWjJuX8cUG+sy2uv/jRrbkZNlmcOHD7t32cA1dsA9foC8vDz3DqNAEAjEvBf61BpvkuwgddfzlDi2kqA2YZe0rmcRMrKlgsxDy5nVLZcR4xaSvTsXh0aFWiWhWBqeNOmK+GW4PfTQQ41ekyTJPbEIw00gaD/E5CVoKuS/L0m6gYC9YKvV6gZh4Z977jmvuzcDBw5k6NChrFixguTkZFJTUzn33HM9+rrwwgtZtWoVx44dc/u5ZWVlsWbNmmZlGTVqFImJiSxdupRrr73WfZTwtddea2CkXHLJJXz11VesWLHC7RPmcDh47rnniIyMbOAOsGrVKvLz891+blu3bmXLli3MnTvXLTvQ4LN45plnmpUbYOLEiXz99dd8+umnXHbZZYDLAH755Zdb1N6XMfXs2RO1Ws2mTZuYMmWKu/2SJUsa7fv555/nv//9L+Aa4/PPP49Wq+WCCy5w1xFGmyDQiHmvY6BRq5gVv4sSx1ZsVjNHotJJj4/Aok+ipOg4JepE0tXF9LT8iLR/NZlpQyA12tVYaw2u8CGCX4abtyMdsixz5MgRXnjhBTZt2tSiSVQgEASOyZMns3r16mCLIQgSzeVpayxVQGPG28GDB736bfnKn/70J958801iYmIYNGgQP/74I+vWrSM+Pt5r/enTp/Pggw+i1+u5/vrrG/hjPfTQQ3z11VeMGzeOm2++GafTyfPPP8+QIUP45ZdfmpRFq9Xy6KOPctNNNzFhwgSmT59OdnY2y5cvb+CjdeONN/LSSy8xc+ZMfv75Z3r16sXKlSv5/vvveeaZZ4iK8jy607dvX84++2xuvvlmrFYrzzzzDPHx8dx9990AREdHc+655/Kf//wHu91O9+7d+eqrr1q8s3nTTTfx/PPPc9VVV3HHHXeQmprK22+/jV7vOiLbkhx2LR1TTEwMU6dO5bnnnkOSJPr06cNnn31GQUGB1371ej1r165lxowZjB07ljVr1vD5559z//33e6RpCJROCQS1iHmvg+B0oD64lgS1iSNR6ZSZHSjFJkBDuTYFY7gWY2wfpKL9sH8NdB91qq1V+LhBG/i4qVQqMjIyePLJJ/nb3/7GbbfdxjvvvBPo2wgEgkYQk1fXpaXJtX0x3gL1gv3ss8+iVqt5++23sVgsjBs3jnXr1rnzstVn+vTp/OMf/8BkMrmjSdZl5MiRrFmzhrvuuosFCxaQlpbGI488wu+//+4+8tcUN954I06nk0WLFjF//nyGDh3Kp59+2uCEiMFgYMOGDdx77728/vrrVFRU0L9/f5YvX87MmTMb9HvNNdegUql45plnKCgoYMyYMTz//PMeSaffeecdbrvtNl544QUUReGPf/wja9as8YiQ2RiRkZF8++233HbbbTz77LNERkZyzTXXcNZZZ3H55Ze7Dbim8GVMzz33HHa7naVLlxIWFsa0adNYtGgRQ4YMadCvWq1m7dq13HzzzcyfP5+oqCj++c9/ehwJhcDplEBQi5j3OghF+6E0B8kQS3pUBEqxiXKzHYAYg5b0uHBUkgT6WCjJhsoTp9rahOEGbRyc5Nxzz+Wee+5py1sIBIJ6zJs3j8WLFwdbDEE701KjrZaWGm95eXkeCalbi9Fo5NVXX21QXjfaYF369u3b4DhhfSZMmNAgfP6UKVPo0aNHi2S6+eabufnmmz3KNmzY0KBeUlKSV9kb4//+7//4v//7v0avd+/e3SPdQS3NjbeWjIwMPvvsM4+y2qOWdcfubSy1tHRMCQkJrFy5ssWy9u7dmy+//LLJPgOlUwJBLWLe6yBYq0C2gyYMAIlGnnkaHThtoMgogNMp46gqo/llqc5PmyZT2b59u8jXIhC0M3PmzAm2CIIgsDOvrMVGWy31wzTvzCtrUKfuEbdQw2w2e/x+8OBBvvjiC8aPHx8cgdqJ+uO2WCy89NJLZGZmeuSQC1VCWacEHRMx73UQwiJBpUV2WMgtMaEvPUAv636SnccpN9vJLTEhKwo4bKDSgj6an4/b2HOsgl2H84MtfUjg147bG2+84bW8rKyMTZs28dFHH3HDDTf4cwuBQOAjmzZtalEuK0HnYnSvOBjvSnbaEqOtllPGW6yrj3pUVVW16PhdMOjduzczZ86kd+/eHDlyhBdffBGdTuf2J+us/OUvfyE9PZ3hw4dTXl7OW2+9xb59+3j77beDLVqLCGWdEnRMxLzXQUjoj2zsSdWhHyjDQHdJRkIhTKPGaNBSZrKDUk1PZylS+lhI6I9TE4HGYUKxNJ3jsqvgl+Hm7Xx/LQkJCdx7770NzrYLBIK2pTaEt6Dr4c3wagkatarRtrVREEORiy66iHfffZcTJ04QFhbGmWeeyeOPP97pfagmTpzI//73P95++22cTieDBg3ivffe8+oLGIqEsk4JOiZi3usYOFCxXh5FpryLdE0hOjWgSEgaDelx4aBUo63Io0gfTlzmRajVGqQzZmNSJBKSmvcB7gr4Zbh5i4IlSRKxsbENIm0JBIL2oSMclRJ0HGpD5Yciy5cvD7YIbnr16tViHzV/mTt3rju9QKjw2muv8dprr7WobijrlKBjIua90KfWD3uHaQSzuh1xhfwvOg5qDajtUHmCns5SivThfK8Zy4miodzglBkz9uxgix5S+OWA1rNnzwb/0tPTA2a0Wa1W7rnnHrp164bBYGDs2LF8/fXXLWqbn5/PtGnTMBqNREdHc9lll3H48OEG9V588UWmTp1Keno6kiQ1uYtYVlbGjTfeSGJiIhEREZx//vkNHOMFgmDTXGAAgcAXysvF8RRBYBE6JQg0Yt4LbeoGzxqRkciIvy1EOnMOGIwgqUCRQa1FSh9L3B/nc2LYHLblVvDy5mwczoapx7oybRpV0l9mzpzJypUrmTt3LpmZmbz22mtccsklrF+/nrPPbtwCr6qq4vzzz6e8vJz7778frVbL4sWLOe+88/jll1888gY98cQTVFZWMmbMGI4fP95on7IsM2nSJH799Vfmz59PQkICS5YsYfz48fz888+d/miOoONw5513BlsEQSciOTk52CIIOhlCpwSBRsx7oUujEY/7XwR7VoKtGvpdBH0vgIT+qNUabnDKKDVtoOlco12NNvsU8vLymDBhAhdccEGr2m/dupX33nuPf/3rXyxatIgbb7yRb7/9lp49ezbreL5kyRIOHjzIZ599xt133828efP46quvOH78OE899ZRH3Y0bN1JUVMSaNWsICwtrtM+VK1fyww8/8Nprr/HPf/6TOXPmsGHDBtRqNf/85z9bNUaBoC1oatdYIPCVxsL1CwStReiUINCIeS90aSzisd1SjcWhYNdE4EweBsmDXccm8Yx4XLBnPbtem8vh127CYbMGcyghQZsZbiaTiQ0bNjSZR6YpVq5ciVqt5sYbb3SX6fV6rr/+en788Ufy8vKabDt69GhGjx7tLhswYAAXXHAB77//vkfdnj17IklSi+RJTk7mL3/5i7ssMTGRadOm8cknn2C1CmUShAb1dVzQkG05Ja06fuFwymyrWQHsKvTp0yfYIgg6GUKnBIFGzHuhy+heccwe36fBrllhaTn7TlSy91gFB0ocDdq5jbduWlRF+6k4mYOpUhyzbjPDrX///siyjNPpbFX7nTt30q9fP6Kjoz3Kx4wZA8Avv/zitZ0sy+zatYtRo0Y1uDZmzBgOHTpEZWVlq+QZMWJEg7x0Y8aMwWQyceDAAZ/7FAjagsmTJwdbhJBmW04JSzcc8vnsfO1xj6UbDnUp4+3gwYPBFkHQyRA6JQg0Yt4LbUb3imtw1NFhqXL/rNWHe22nUavoleo6Wi0B5qrSNpOxoxCyPm7Hjx8nNTW1QXlt2bFjx7y2KykpwWq1Ntu2f//+Pstz7rnnNtnn0KFDG21fUFBAYWGhR1lWVpZPMggELWH16tXBFiGkOT3N6E44DfXOzjsdULQfrFWuRKEJ/UGtaXBG//Q0Y/AG0M4I/11BoBE6JQg0Yt7reBh79KP0Dw9jt5qITxvQaL3M9G6oukWjVklIYfZ2lDA0CVlPP7PZ7NXnrDZpp9lsbrQd0Kq2bSFPLUuWLGHIkCEe/6ZMmQLAd999x8aNG1m0aBElJSXMmDEDOLWCNG/ePLKysnj11Vf5+OOP2bp1KwsXLsRkMjFt2jSPuvfffz+7d+/mnXfe4Z133mH37t3cf//9HnWmTZuGyWRi4cKFbN26lY8//phXX32VrKws5s2b51F3xowZlJSUsGjRIjZu3MjatWt54YUXyM/PZ/bs2R51Z8+eTX5+Pi+88AJr164VYwrSmK6++upON6ZA/p3m33UnE7rJUHSI1T/9xoPvbOKRhx/G+vM7fHfnYPj0drKe+zN8eju/PHQGOZ8/zW3//YBPvt9ND72NI1++gkatarMx1Z4IOHLkCDabjYKCAsrLy6msrOTEiRM4HA53KpbanYu8vDwsFgtFRUWUlpZSXV3NsWPHcDqdHDp0yKPu0aNHMZlMFBcXU1xcjMlk4ujRox51Dh06hNPp5NixY2RnZ1NaWkpRUREWi8V9TL22bnZ2Ng6HgxMnTlBZWUl5eTkFBQXYbDaOHDniUTdUxlRdXS3GFMQxZWVlhcyYZFlm69atQOd+7nX2MV1++eWdbkyd8e9Ud0watZbH/v00o86cwDXXzGh0TM++sAyNWsW2bdvAVtUuY/ruu+8IVSTFz8QzJ06c4JVXXmHHjh2Ul5cjy55HjyRJ4ptvvvG53yFDhpCcnNyg7W+//cbgwYNZunQpN910U4N2RUVFJCYm8sgjj7BgwQKPa0uWLGHOnDns27fP645bZGQkV1xxhddcNJGRkUyfPp1XXnnFo/yLL75g0qRJrF27lokTJzY6nsZ23KZMmcKePXsYPHhwo20FAl/YvXt3k7u/AhfunDLZhdwofcQoy09IllLQx4ImDBxWFHMpRc6anDLD5nDDeZltGtmqNmVJ79692+wevmIymQgP936MpTMyfvx4gFb7ZwuaJ5R0KhS/cwLfEfNeJ6a6GD65xfXz6FmQeWGb33Lv3r0MGTIkJN/P/ToquWvXLsaPH4/ZbKZ///7s3r2bQYMGUVZWRn5+Pn369CEtLa1VfaemppKfn9+gvDZkf7du3jOox8XFERYW5jW0f3Ntm5PHnz6TkpJISkry+b4Cga+ICaxl1Do+rz/5JYmHvqVU48TYrT8qlRoAWVHItUWhNeUxji3EJZyLWu3bEevOgNlsDpmXbEHnQOiUINCIea8TE1YnN7S1InhyhAh+LR3fe++9REZGsn//ftatW4eiKDz77LPk5eWxYsUKSktL+fe//92qvocPH86BAweoqPD8I23ZssV93RsqlYqhQ4eyffv2Bte2bNlC7969W5UgfPjw4ezYsaPBjuKWLVsIDw+nX79+PvcpEAiCiwaZC1TbiVNVkSsnkltqQVYUl9FWYqLM7MAelUaC2oT64FqXD1xHxOmAk3shd4vr/446DoFAIBB0CnJ++oQDb87l4Ir7UeQmAoVpdOwvtPD78Qp2Zh1tPwFDFL8Mt++//56bbrqJ9PR0d7TFWsNm6tSp/O1vf2P+/Pmt6vuKK67A6XSybNkyd5nVamX58uWMHTvWvZOXm5vLvn37GrTdtm2bh/G2f/9+vv32W6ZOndpqeU6ePMlHH33kLisqKuKDDz5g8uTJTeaAEwjaE7Hq6ANF+1GVHSHSmIgxQkeZyc6RYhNHik2UmewYw7Wkx0cgGWKhJNsVuKQj4XTA7pXw8U3w6e2wZr7r/1WzXeUtMOAMBkM7CCroClRXVwNCpwSBR8x7HY/CY9mYjv1ORe5uJFXT5ki5rMfqkLFVl7WPcCGMX4abLMskJ7vCdBqNRtRqNSUlp8JkDx06lJ9//rlVfY8dO5apU6dy3333cffdd7Ns2TImTJhATk4O//nPf9z1rrnmGgYOHOjR9pZbbqFPnz5MmjSJRYsW8cwzz/CHP/yB5ORk7rzzTo+6q1ev5tFHH+XRRx/Fbreza9cu9++7du1y17viiis444wzuPbaa3nkkUdYsmQJ48ePx+l08vDDD7dqjAJBW/Duu+8GW4SOg7UKZDsqjZ70uHBiDFrKzXbKzXZiDFrS48JRSRJodCDbXfU7Ck4HbH4SfvgvHN0KTjuow1z/521xlW9+qlnjre4z3R+OHDnCLbfcQv/+/TEYDMTHxzN16lSPZMzbt29HkiRef/31Bu2//PJLJEnis88+c5dt2LCBUaNGodfr6dOnDy+99BIPPfRQi3JzAixbtow+ffpgMBgYM2YMmzdv9lqvoKCA66+/nuTkZPR6PaeddloDGXNycpAkiSeffJLFixfTs2dPDAYD5513Hnv27PGou2vXLmbOnEnv3r3R6/WkpKRw3XXXUVxc3KzMGzZsQJIk3n//fR577DF69OiBXq/nggsu8Bqp+IMPPmDkyJEYDAYSEhK4+uqrG7ghzJw5k8jISPLz85kyZQqRkZEkJiZy1113NUjpU1xczN///neio6MxGo3MmDGDX3/9FUmSPPzDa/s8dOgQl1xyCVFRUfztb38DXEFK7rzzTtLS0ggLC6N///48+eST1HW5r/08vfmcS5LEQw895P699m++b98+pk2bRnR0NPHx8dxxxx1YLJZmP1NBx0fMex0PlcOCBMhqfbN1q3pfwsm+01D3Pb/tBQtx/PJxy8jIcEeYUqlUZGRksG7dOnfkmx9++AGj0djq/t944w0WLFjAm2++SWlpKcOGDeOzzz7zGpa/LlFRUWzYsIF58+bx6KOPIssy48ePZ/HixSQmJnrU/fDDDz0m4J07d7Jz504AevTowbBhwwBQq9V88cUXzJ8/n//+97+YzWZGjx7Na6+95nNqAYGgLXn88ceDLULHISwSVFpwWN1FUc4yFCQ0ciRQ44fjsIFa66rfUfhtFez/wjW2xAEg1Vmni0qGslzY/zkk9IUhlzfaTY8ePQIizrZt2/jhhx+48sor6dGjBzk5Obz44ouMHz+e3377jfDwcEaNGkXv3r15//333ZHJalmxYgWxsbHuIFA7d+7koosuIjU1lYcffhin08kjjzzS4BnfGK+88go33XQTZ511FnPnzuXw4cNceumlxMXFefhmm81mxo8fT1ZWFrfeeisZGRl88MEHzJw5k7KyMu644w6Pft944w0qKyuZM2cOFouFZ599lgkTJrB79273QufXX3/N4cOHufbaa0lJSWHv3r0sW7aMvXv38tNPP7XI8Pz3v/+NSqXirrvuory8nP/85z/87W9/c7sTALz22mtce+21jB49mn/961+cPHmSZ599lu+//56dO3d6zM9Op5OJEycyduxYnnzySdatW8dTTz1Fnz59uPnmmwHXYu3kyZPZunUrN998MwMGDOCTTz5p8LeqxeFwMHHiRM4++2yefPJJwsPDURSFm2++mfXr13P99dczfPhwvvzyS+bPn09+fj6LFy9u0d/PG9OmTaNXr17861//4qeffuK///0vpaWlvPHGG63uU9AxEPNex2NkNz2KIwY5IqXZuhMu8/6M6ZIofnDnnXcqmZmZ7t+ffvppRZIk5YILLlAmTJigqFQqZf78+f7colOzZ88eBVD27NkTbFEEnYg//elPwRah4+CwK8oH1yny00OU7GcvUXb++w9K6cPpSulD6crBR05Xsv87SXG+ebmiLB6iKCuvd9VvQw4dOqQcOnTI/45qxqUsHqIob12hKG9Pa/jvrStaNK4DBw74L4+iKCaTqUHZjz/+qADKG2+84S677777FK1Wq5SUlLjLrFarYjQaleuuu85dNnnyZCU8PFzJz893lx08eFDRaDRKc1ObzWZTkpKSlOHDhytWq9VdvmzZMgVQzjvvPHfZM888owDKW2+95dH+zDPPVCIjI5WKigpFURQlOztbARSDwaAcPXrUXXfLli0KoMybN6/Jz+Ldd99VAGXTpk1Nyr5+/XoFUAYOHOgh+7PPPqsAyu7duz3GOGTIEMVsNrvrffbZZwqgPPjgg+6yGTNmKIDyyCOPeNzr9NNPV0aOHOn+/cMPP1QA5ZlnnnGXOZ1OZcKECQqgLF++vEGf9957r0efq1atUgDl0Ucf9Si/4oorFEmSlKysLEVRTn2edfusBVD++c9/un//5z//qQDKpZde6lHvlltuUQDl119/bdBHLQH7zgmCipj3OiDr/+Wai764J9iSNCCU38/9Oir5wAMP8O6772K3uxLizZ07l0ceeYTi4mLKy8tZsGABjz76qD+3EAgEPiISkfqAWoMz8yKKnOFoK/MwhqmQAEmCOGcRZdU2yo5loehjof/FoPbrkIL/HN4A6x5q+t/Pr7l88UpzXKkN7BYo3N/wX9FBsJshezN8NrfhvWr6yzzytmf/hze0SvS6fk12u53i4mL69u2L0Whkx44d7mvTp0/Hbrd7+BN/9dVXlJWVMX36dMC1O7Ru3TqmTJniEdG3b9++XHzxxc3Ksn37dgoKCpg9ezY6nc5dPnPmTGJiYjzqfvHFF6SkpHDVVVe5y7RaLbfffjtVVVVs3LjRo/6UKVPo3r27+/cxY8YwduxYvvjiC6+fRW0OtDPOOAPA47NoimuvvdZD9nPOOQc4Fd6+doy33HKLO98owKRJkxgwYACff/55gz5r8xrV7bO2P4C1a9ei1WqZNWuWu0ylUjFnzpxG5azdravliy++QK1Wc/vtt3uU33nnnSiKwpo1axrtqznqy3Hbbbe57yno3Ih5rwNir8l/rBU+r77gl+EWGxvLyJEj0Wq1gOvc+T/+8Q927tzJ9u3beeihhzwmFoFA0PbUHlUWNI/DKfNy8TC+14xFF2Yg3ZmLVrGhVuzoJTu9yaXCoWGb/kwc/ScHW1yoKoSC35v+V5rj9t1DEwaKE2xV3v85bWA3QdGBhveq6a86e7tn/1WFDeu2ALPZzIMPPuj2a0pISCAxMZGysjLKy8vd9U477TQGDBjAihUr3GUrVqwgISGBCRMmuEQrKMBsNtO3b98G9/FWVp/a5MyZmZke5VqttkE+ryNHjpCZmekOwFVLrW91bV+11O8ToF+/fh6+fCUlJdxxxx0kJydjMBhITEwkIyMDwOOzaIr09HSP32NjYwEoLS31kMvbUf4BAwY0kFuv1zc4ZhobG+vur7bP1NTUBqH8G/vMNRpNg6O2R44cISkpqUF058Y+T1+o/9n36dMHlUrl8dkLOidi3uuAOGr8T1tguFXl7eLkhpfJX/MUiuxstn5nJsjLxwKBINB4c+YXNKQ2Aff23ApGD5tDXMK5qPZ+RFj2ZhRFBkmNvvcZ/MQYPqgewYjv85h1TkabJuBulshESBrYdJ3YXp6+exo96BrxzbNVgaSGBC/pTGruY5AVUNXxuYpsmQ9ZfW677TaWL1/O3LlzOfPMM4mJiUGSJK688soGaVamT5/OY489RlFREVFRUXz66adcddVVaDSdY8qaNm0aP/zwA/Pnz2f48OFERkYiyzIXXXRRg8+iMdRqtddypU6AD19orD9/CAsLa2DwAi36Ozbm51c/WEpr+hB0PsS81/HYceg4eksFdpWF05qpe3DfbqQdKwEwjruOiOjYthcwRPFpFnz66aeZNGmSz8E4LBYLS5YsYdq0aQFzdBcIBN556qmnWLBgQbDFCGncRltOCaN6xXHDORmu5NqpQ1F/Ng9kB6g0cNG/mBCRzKGaukBwjbfe413/msPpcBlwR7e6ApEkenlmKzIU7oO0sfCnZxpev/AhAE4cO+ZxHLG1rFy5khkzZvDUU0+5yywWC2VlZQ3qTp8+nYcffpgPP/yQ5ORkKioquPLKK93Xk5KS0Ov1XqMoeiurT8+ePQE4ePCgexcPXEc4s7OzOe200zzq7tq1C1mWPYyQ2jQ0tX3VcvDgwQb3O3DgAL169QJcO2LffPMNDz/8MA8++GCT7fyhVq79+/d7jLG2rL7cLe1z/fr1mEwmj123lnzmdftYt24dlZWVHrtu9T/P2h3E+vrR1I7cwYMH3TuXtXLJsuz+7AWdFzHvdTwUmwmbU8ZC8yfztIZoauMfmyvLurTh5tPbx/z581sV3r+6upr58+dz4ICX4zgCgSCg1EbdE3invtHmYYg57RAWBYZY1/+2ajRqFbPOyWBUrzi255Tw8uZsHM6W7YoEDbXG5ZNniHVFj1TqyavIUHbEdb0Z3736Pl+tFkmtbrAb9Nxzz3ndQRk4cCBDhw5lxYoVrFixgtTUVI9owmq1mgsvvJBVq1Zx7Ngxd3lWVlaLfKRGjRpFYmIiS5cuxWazuctfe+21BobCJZdcwokTJzyObjocDp577jkiIyM577zzPOqvWrXKI9z+1q1b2bJli9v3rnZnq/5n8cwzzzQrty+MGjWKpKQkli5ditV6KmrqmjVr+P3335k0aZLPfU6cOBG73c7LL7/sLpNlmRdeeKHFfVxyySU4nU6ef/55j/LFixcjSZL7c4qOjiYhIYFNmzZ51FuyZEmjfdeX47nnngNokd+joGMj5r2Oh6n/ZZT2uRRDr9HN1k1LTaF3QgSZyZFEq63N1u/M+LTjpigKH330kU+rawAmk8mn+gKBoPXUz9Ek8GRnXpl3ow2wW01IThmVSkKSQLK6/I1qjTegpm0so3vFBUX+FjNoChQfcoX8L9znClSi0blSG1hKa4y2STDwsia7sdlsRERE+C3On/70J958801iYmIYNGgQP/74I+vWrSM+Pt5r/enTp/Pggw+i1+u5/vrrGxy5e+ihh/jqq68YN24cN998s9sYGDJkCL/88kuTsmi1Wh599FFuuukmJkyYwPTp08nOzmb58uUNfNxuvPFGXnrpJWbOnMnPP/9Mr169WLlyJd9//z3PPPNMA1+tvn37cvbZZ3PzzTdjtVp55plniI+P5+677wZcBsm5557Lf/7zH+x2O927d+err75yp9YJFFqtlieeeIJrr72W8847j6uuusqdDqBXr17MmzfP5z6nTJnCmDFjuPPOO8nKymLAgAF8+umn7lx/LTmaOHnyZM455xweeOABcnJyOO200/jqq6/45JNPmDt3Ln369HHXveGGG/j3v//NDTfcwKhRo9i0aVOTC8DZ2dlceumlXHTRRfz444+89dZb/PWvf/XYQRV0TsS81/E4Z9LfW1w3JiYWDK54Gjir20iijoHPDgMfffSRR7QvgUAQWtQNJiBoyOhecTAeTk8zNjjyeDC/ENuxCgCi9Rq0x06QVhMg8NTOWwcw2sC1i3bOna48bfvXQEm2KxiJWus6Htn/YpfR1kykTF98ipri2WefRa1W8/bbb2OxWBg3bhzr1q1rdKV8+vTp/OMf/8BkMrmjSdZl5MiRrFmzhrvuuosFCxaQlpbGI488wu+//+4+dtcUN954I06nk0WLFjF//nyGDh3Kp59+2uC4lcFgYMOGDdx77728/vrrVFRU0L9/f5YvX87MmTMb9HvNNdegUql45plnKCgoYMyYMTz//POkpqa667zzzjvcdtttvPDCCyiKwh//+EfWrFkTkCOpdZk5cybh4eH8+9//5p577iEiIoI///nPPPHEE63KsapWq/n888+54447eP3111GpVPz5z3/mn//8J+PGjfOIXtkYKpWKN954g//+97+sWLGC5cuX06tXLxYtWsSdd97pUffBBx+ksLCQlStX8v7773PxxRezZs0akpKSvPa9YsUKHnzwQe699140Gg233norixYt8nmcgo6HmPc6OXVzqForgydHCCAprfVkFvjN3r17GTJkCHv27GHw4MHBFkfQScjKympRZD1BQ3Z8twbzj68QIbsmBmXYlZx+8bXtdv/a0Ov1d338xulwpQiwVrkmwIT+LU5tYLFYWvRCHipMmTKFvXv3BtxnrDlycnLIyMhg0aJF3HXXXe1672CzatUq/vznP/Pdd98xbty4ZusHWqceeughHn74YQoLC0lISPCpbZt95wTtipj3Ojm2alh5nevn0/8OA//UprcL5ffzIIZHEwgEbYEv/iYCT5IGn4d50gs4JB0SoLJVBFukwKDWQPJgSB/r+t+HfHSFha0L/98emM1mj98PHjzIF198wfjx44MjUBeg/mfudDp57rnniI6OZsSIES3qI5R1StAxEfNex8JUVsCRdS+Rv/kNqotym2+gDedomYWc4moO5B1rvn4npnPEVhYIBG4WL14cbBE6LD1iw+kRG46dm9BqwyBOrMKnpaUFW4RG6d27NzNnzqR3794cOXKEF198EZ1O5/YnEwSe2267DbPZzJlnnonVauWjjz7ihx9+4PHHH/dILN4UoaxTgo6JmPc6FsUFxyj92eV2VR2ZQb+E9KYbSBInLBo0dgvW0pJ2kDB0ETtuAkEnY/LkEEgU3cHRDvoTZP4B4vs0X7mT095HDn3hoosu4t133+W2227jueeeY/To0WzatMlrEmxBYJgwYQL79u3jgQce4P7776esrIznnnuO++67r8V9hLJOhRLbckpaFcHW4ZTZltO1Xm7FvNexsFtOBS3U6lsW/KrYOJTjMcOxRWc0X7kTI3zcgkgon6EVCLok1cUg20FrAH1gwuD7gvC3EQjal1D9zm3LKWHphkNeo982Rd10J7PH9+kYgZQEXQ7r4e9xbnoapwyaPy3CkBRa379Qfj8XO24CQSdjxowZwRahw3J0/TIK3plNwUeuo3ZiXYuAh6kXCIRONc/paUafc0fWz1F5epqx7QUNEcS817EIU2yE6zRE6TUYwiObbyBwI3zcBIJOhjjr33qOFpSiLzNDWQ4blz6E2lbFn2/9D5Kq/da4Qs1YFP5IgkATSjqlKEqL8s+1N/VzRwKndt68RIl1oPIw2nzZpesMiHmvg+GwnPpZ03GiFocCwnATCDoZr7zyCvPnzw+2GB0Tx6mIeZnlPwJgqiojIrp9jhupVCpsNltIvUwWFRWRkpISbDEEnYhQ0SlFUXA6neh0umCL4pX6xpskO5gVvwv1wbVQmuM61q3SIsf2Yr1zJDtMIxiVkdjljDYQ816Hw14nOq22ZUGNqDiOsyQba3UZhoEXteuCaijhl+GmKArLli3jlVde4fDhw14TIEqShMPh8Oc2AoHAB8aMGRNsETosY9LCUcJjqLTaqTQ70KglVLZKoH0Mt7CwMMxmMwUFBSQlJYWE8RYR0TLHcYGgpYSCTimKQkFBAU6nk7CwsGCL0yi1xpskO0jd9Twljq0kqE1IhljQhCE7LFRlfU+m/Cuzuh1hxLiFXc5oAzHvdTQO5BeiLapGrdGQrta2qM0vP34Fv7wDwIDe56E3BP85Egz8Mtzuvvtunn76aYYPH87VV19NbGxsoOQSCAStpH6eJUHLUTmsoJIwGhMwGmpyuDkq2+3+ycnJWK1WSkpKKC8vR61WB914s9vtaLUtm1gFgpYQbJ2q3WlzOp0YDAaSk5ODJktL0KhVzIrfRYljKzarmSNR6aRHuV5ac0tMlGEgXVNIT8uPSPtXw5DLgyxx+yPmvY5FWXk5OrMdh0ZHM4kA3Kj00dR6epoqSoXh1hpef/11Lr/8ct5///1AySMQCPzk0KFDwRah41J77j4yCaw1hpu1/ZJwq1Qq0tPTOXnyJFarFVn2PRR4oDly5Ah9+/YNthiCTkSwdUqSJHQ6HWFhYSQnJ6MK9SNXTgfqg2tJUJs4EpVOmdmBUuwKp15utmOM0GGM7YNUtB/2r4GBl4G6a3nCiHmvY6FEd6ckeiCSpuW73ckJCSjRetQqCb3SdQ11v77ZZrOZCy+8MFCyCASCADBlypRgi9BxsdfklolMhuIs18+W8nYVQaVSkZqa2q73bIqwsDC6d+8ebDEEnQihUz5StB9Kc5AMsaRHRaAUmyg32wGIMWhJjwtHJUmgj4WSbFf95NAKYd7WiHmvYzH2or8Bf/OpTXJiAsTUBDLpwoabX8tMF1xwAdu2bQuULAKBIAAsXLgw2CJ0SBRZ5re8IvafqOT3Kj2VVgelJhsnCwuCLVpQEfokCDRCp3zEWuUKRNLc7oRG56pnrWofuUIIoVNdgLCoUz9b28+FIdTwy3BbsmQJP/30E48//jjFxcWBkkkgEPjB0qVLgy1Ch8RqNWNzODHbnZiUMPaVwJFiEzn5J4ItWlAR+iQINEKnfCQs0hU90mEht8SEraKQdOt+0qxZVJlM5JaYkBUFHDZQaV31uxhCp7oAujp6bet6ixO1+GW49e/fn8OHD7NgwQKSkpKIiIggOjra419MTEygZBUIBC1g8uTJwRahY6IOY+foRWwf9giazAk4a1b3FHNZcOUKMkKfBIFG6JSPJPRHNvakqqyQsmobBg2oUdDgIDJMQ5nJTm5xNYq5FOIyIKF/sCVud4ROdSxMOdux5+1AKc9veSNdJCXVNgorreSf7LonYfzycbv88suDHvFMIBB4snr16mCLEDC25ZRweprR5/DWDqfMzrwyRvdqeRh/vU7DtROGuX8vHj4eta0cfXI/n+7d2ehM+iQIDYRO+YYDFevlUWTKu0jXFBIWZsBhc10zOkuRDEloK/Io0ocTl3kR6i4WmASETnU0fvv4P2hs5VjSzuWMvz7QskZqDdnlMmqnBeuJArqql6xf3+7XXnstQGIIBIJAMXv27E5xbGRbTglLNxxiVK84nxLKOpwyL2/OZntOCYzHJ+OtLvFnz2xVu85GZ9EnQeggdKrl1D7PdphGMKvbEVfI//I8zIodJ6C2l9FTbaFIH873mrGcKBrKDU65y+VyEzrVsVA5XRGcJV24T+3MunhkmwmH0nVT1HS9ZRmBoJOzYMGCYIsQEE5PMzKqV5zLAIMWGW91jbZRveI4Pc3YDpJ2bjqLPglCB6FTLcPjeZaRyIhxC1152n54DnVhFhpFQVFLSOljicu8iBNFQ9mWW4GyOdunxa7OgNCpDoSikB6twinrsSX6lv950PVL0WlUROjUbSRc6OP3t7qiooKHH36YMWPGkJycTHJyMmPGjOGRRx6hoqL98h8JBAIXq1atCrYIAUGjVjHrnAy38fby5mwczpq8Zk4HnNwLuVtc/zsdDYw2X19cqnK2Ufn2NVS9PxtbUU7bDKoD0ln0SRA6CJ1qHq/PM63OlVx70J/RdRuGNnUwut7nwJSlqIddwQ3nZXp/XnYBhE51IBwWEiLDSI7Wk5bo24mYuAgdkWGaLu2m5deO27FjxzjnnHPIzs5mwIABjBs3DoD9+/fz0EMP8cYbb7B58+aQykkkEHR2+vTpE2wRAkat8QawPacESXYwK34X6oNroTTHFfpapUWO7cV650h2mEYwKiOxVavNeceLsB49CUCK2UFV9hF27/gep7mMP0y6kpjY1h257Oh0Jn0ShAZCp5pnZ15Zo4tQlaZqNKpwNBoJrSS5k23Xf16O6hXb6qPiHQ2hUx0Ie50cbFpD8OTooPhluN1zzz2cOHGCzz77jEsuucTj2po1a5g6dSr33nsvr7/+ul9CCgSClmMwdK4HYe3LiCQ7SN31PCWOrSSoTUiGWNCEITssVGV9T6b8K7O6HWHEuIWtOiLksJrcP+vCwrGf3EdGluvZVVVyTpc13DqbPgmCj9Cp5hndKw7G4zU4054jJzGUVBIRpiZTrXKdQKhnvHUlow2ETnUoHJZTP/tquDmsYKlwpQOIywisXB0Ev45Krl27lrlz5zYw2gAuvvhibr/9dr744gt/biEQCHxk69atwRYh4GjUKmbF7+Isx1ZsVjNH1OnIUSnIhlhy7TEcJp1ojZPRlh/R7G9ddLHesWp6J0bQKz6cyMgoomLiMGjVROk1qG1dN9lnZ9QnQXAROtUyRveK87oIJdW8+FZbnZyssFBV4ZlHV6NWdSmjDYROdSQqKsopqLRSVGWl3OHb/tH+De9w4OUZ/Lb8Fhx2WxtJGNr4ZbhVV1eTnJzc6PWUlBSqq6v9uYVAIPCR66+/PtgiBB6nA/XBtSSoTdij0igzO8g7fpK84ycoM9kxRugwduuDZCmF/WtcK9A+EqFyEK3XYgzXodOH0yMlhf4pUfRJjCQlrGtOENBJ9UkQVIRO+Ufy+Tdj6nE2AMfLLZQWd92cVrUIneo4lJRXcKzMzNFSM0UW33zVLCoDJpsTm0Omuqq8jSQMbfwy3AYNGsS7776LzdbwpcZut/Puu+8yaNAgf24hEAh8ZN68ecEWIfAU7YfSHCRDLOnxERh1MpFV2URW5WDU2EiPC0elUoM+FkqyXfV9pfbcvVoLKjXoY05ds3TNCQI6qT4JgorQKf/IGDCctDGXun8319tx64oIneo42Gx2bJIeBQmdPsKnttExcUTrNcRF6JBsVW0kYWjjl+F2zz33sGXLFsaMGcOyZcvYsGEDGzZs4KWXXmLMmDFs3bqVe++9t9X9W61W7rnnHrp164bBYGDs2LF8/fXXLWqbn5/PtGnTMBqNREdHc9lll3H48GGvdV955RUGDhyIXq8nMzOT5557zmu9devWcf7555OQkIDRaGTMmDG8+eabrR6fQNAWdEqfUmuVKxCJJgwAjf3U0UWdteRUPY3OVc/aigd67bl7Tc2Ze43eZcSB60x9F6VT6pMgqAid8p/kHn1Ju/wxBl63lH7Dzgy2OEFH6FTHIXP4OIbO/Yhecz4hpddAn9pmdEuhd2Ik6XHhRGNuvkEnxC/DberUqbz66qucOHGC2bNnc8EFF3DBBRdw8803c/z4cV599VWuuOKKVvc/c+ZMnn76af72t7/x7LPPolarueSSS/juu++abFdVVcX555/Pxo0buf/++3n44YfZuXMn5513HsXFnitTL730EjfccAODBw/mueee48wzz+T222/niSee8Kj36aef8sc//hGbzcZDDz3EY489hsFg4JprrmHx4sWtHqNAEGgmT54cbBECT1ikK3qkw0JuiQmLA9SShEYlITud5JaYkBUFHDZQaV31fSTrWBF5pSZyK2pCaEsSDl00VodMZXnXXdHulPokCCpCp/xHZ4ggvu8owhIz3AtaXRmhUx0HSZIw6NTERoah1fiYj63u3N5Fd9wkRVEUfztxOBxs376dI0eOANCzZ09GjRqFRtP6oJVbt25l7NixLFq0iLvuugsAi8XCkCFDSEpK4ocffmi07X/+8x/uuecetm7dyujRowHYt28fQ4YM4e677+bxxx8HwGw2k5aWxhlnnMFnn33mbn/11VezatUq8vLyiI11JQf84x//yN69ezl8+DBhYWHucQ8YMICIiAh+/fVXn8e4d+9ehgwZwp49exg8eLDP7QWCLoPTgfzRjVQd+oHDpJOiM5PsPA7AcXUPCuxhGA0aejpzkdLHwpSl7ihrLeXH5fdgKPgFa0R3xt76KgA/LbkJfWUOlvjBnHHD0wEflkAgEPiCzWJi//sLQGvAOOQi0oaeHWyRBIL2o7oIPpnj+nnMjdD3gja5TSi/n/udgBtAo9FwxhlnMH36dKZPn84ZZ5zhl9EGsHLlStRqNTfeeKO7TK/Xc/311/Pjjz+Sl5fXZNvRo0e7jTaAAQMGcMEFF/D++++7y9avX09xcTG33HKLR/s5c+ZQXV3N559/7i6rqKggNjbWbbTVjjshIUGEoRWEFJ3xrL8DFd/IoyiRI0lXFZIcoUECJCAlwYjRoEFbkUeRMxxn5kU+G20AR1MnsinxrxxImeQuk8OiAZBsXfeoZGfUJ0FwETrVeszVlTiP78GZu42SouPBFidkEDrVgbCZwFYNsu8J4hVdBBa7k2qrg/KykuYbdEJ8ervZtGkTAOeee67H781RW98Xdu7cSb9+/YiOjvYoHzNmDAC//PILaWlpDdrJssyuXbu47rrrGlwbM2YMX331FZWVlURFRbFz504ARo0a5VFv5MiRqFQqdu7cydVXXw3A+PHjeeKJJ1iwYAEzZsxAkiTeeecdtm/f7mEMCgTBZs6cOcEWIaA4nDIvb85mh2kEs7odoaflR5xlR1DsVpBUqKsK6OmspEgfzveasZwoGsoNTtnnXG5TL5rQoCytZ2/U+irUsT0DNZwOR2fTJ0HwETrVeuxWk+uIuKJg+fUjfvrtSxRDHGde959gixZUhE51HHatWUbYoa9Aa6D/bR/61lgdxu8FZiTZgS3vOGNGNd+ks+GT4TZ+/HgkScJsNqPT6dy/N4aiKEiShNPp9Fmw48ePk5qa2qC8tuzYsWNe25WUlGC1Wptt279/f44fP45arSYpKcmjnk6nIz4+3uMeCxYsIDs7m8cee4xHH30UgPDwcD788EMuu+yyZsdTUFBAYWGhR1lWVlaz7QQCX9m0aRN9+/YNthgBodZo255TwqiMREaMW4i0fzXl3z6P3rIfCScOtBjSxxKXeREnioayLbcCZXM2s87JaFUi7rqkXXhzgEbScelM+iQIDYROtZ6EMJmE7q6It4fKHFRW5mGzi7RLQqc6DiZTNbLdiU3y/WSMpFLh0ESgtZUjm7vmSRif3mrWr1/Pt99+i06n8/i9sX+111uD2Wz2OJZYi16vd19vrB3Qora1Bqg39Hq9xz3CwsLo168fV1xxBe+++y5vvfUWo0aN4uqrr+ann35qdjxLlixhyJAhHv+mTJkCwHfffcfGjRtZtGgRJSUlzJgxAzjlbDtv3jyysrJ49dVX+fjjj9m6dSsLFy7EZDIxbdo0j7r3338/u3fv5p133uGdd95h9+7d3H///R51pk2bhslkYuHChWzdupWPP/6YV199laysLPdxg9q6M2bMoKSkhEWLFrFx40bWrl3LCy+8QH5+PrNnz/aoO3v2bPLz83nhhRdYu3atGFOQxnTs2LFOMaZrZszkv1/tZcU324iXy0g3HeClZS+TH3sGDxwaztaI89lnjWe7uRs3fy1xIv5M7L+tI9pWyJc/H+Tvj71GQVFxSI2pI+peUVFRpxtTZ/w7daQx1Y6rM42p3f5OdrM72fTeI4WEa0FTcZS1a9Z03DEF4O+0f//+Tjemzvh3+vjjj6HiJA5TORHh4a0a09O/RuCcvIRPDqjbbEzNBUEMJgEJTtIWDBkyhOTkZL755huP8t9++43BgwezdOlSbrrppgbtioqKSExM5JFHHmHBggUe15YsWcKcOXPYt28f/fv359Zbb2Xp0qU4HA2T9SYlJXHBBRfw7rvvAq4/6E8//cSOHTtQqVz2rt1uZ/DgwcTGxrJly5Ymx9PYjtuUKVNC0vlR0HHZunWr+0hxR2ZbTglLNxxiVK+4BrtnDqfM1rVvEb7nbQD63fIe4VGx7mu1u3Szx/dhdK+4Ft1P3vQ0KpUEPcZAr3GBH1AHpbPokyB0EDrlB0e3w6ZFrp97nQ05NS+Yl/8PwqKCJ1eQETrVgVj/OBz/FeL6wEWPB1sar3Ta4CQTJkxoYFjVZf369UyY0NBvpCWkpqZy/HhDx9vasm7dunltFxcXR1hYWIvapqam4nQ6KSgo8Khns9koLi5217PZbLzyyitMmjTJbbQBaLVaLr74YrZv3+41CXldkpKSGDx4sMc/sa0vaAu+/PLLYIsQEEb3imP2+D5ejzxq1Cr69UojPS6cPomRaG3lHtdmnZPhk9GmyDK7fvqaXT+sZeeeXe7ykkoT637awefrvuFEwcnADKyD0Vn0SRA6CJ3yA7vp1M9RdVxCLOUN63YhhE51IOw1p9m0+uDK0UHxy3DbsGEDJ082/jJTUFDAxo0bW9X38OHDOXDgABUVnmdYa3e2hg8f7rWdSqVi6NChbN++vcG1LVu20Lt3b6Kiojz6qF93+/btyLLsvl5cXIzD4fDqq2e325FluVV+fAJBW3DnnXcGW4SAMbpXXKN+agmJKcRF6IjSazwMN3AZby012gDsdhsoMrICsvrUZGIuzCVh4310//k/lOXsbt0gOjidSZ8EoYHQqdazK+cEu/PL2HusnOqwxFMXzKXBEyoEEDrVgXAbbn5GZA/NA4Ntjt/pAJoKTpKVleU2knzliiuuwOl0smzZMneZ1Wpl+fLljB071h1RMjc3l3379jVou23bNg+DbP/+/Xz77bdMnTrVXTZhwgTi4uJ48cUXPdq/+OKLhIeHM2mSKyx4UlISRqORjz/+2GNnraqqitWrVzNgwACREkAQMsycOTPYIrQ9+76AvatO/W7yMyyw3UxKjJ6kqDCSYmPcxRExLuNPrZJQLGX+3aOD0iX0SdCuCJ1qPQ6rCacMdqeCKjoVi91JldVBeUlB8407MUKnOg6VVZWYbU7MivcYE82R+8MHHH7prxx+4c8orUgp0NHxOaTL66+/zuuvv+7+/dFHH+Xll19uUK+srIxdu3ZxySWXtEqwsWPHMnXqVO677z4KCgro27cvr7/+Ojk5Obzyyivuetdccw0bN26krqveLbfcwssvv8ykSZO466670Gq1PP300yQnJ3usyhgMBhYuXMicOXOYOnUqEydOZPPmzbz11ls89thjxMXVvLSp1dx111384x//4IwzzuCaa67B6XTyyiuvcPToUd56661WjVEgaAu6QnqKX3/6Gn3pfiJ0anrEhvu92qxTbKRE1+y0JZ3aqYsxxjGsRwwqSQJj11zd6wr6JGhfhE61HmPaIArNf0K2mVEik9l/ohIAOe8YIwYFWbggInSq43AgvxC1vRqrwcrYVrQvrrIilRUDYKquJCIqppkWnQufDTeTyeQRZKOystLD7wtcu3ARERHMnj2bBx98sNXCvfHGGyxYsIA333yT0tJShg0bxmeffdZsXrioqCg2bNjAvHnzePTRR5FlmfHjx7N48WISExM96t5yyy1otVqeeuopPv30U9LS0li8eDF33HGHR70HHniAjIwMnn32WR5++GGsVivDhg1j5cqVXH755a0eo0AQaCZPnszq1auDLUabYjabUGxOzDbXEWVTzhH6DfGjQ0edKLWaU7vnklqDFBYFtiqwdk0fkq6gT4L2RehU6+k9eAy9B7uCcCiyjKzSopLtOKqKgyxZcBE61UFQFNQ1862kC29VF7rwKBSVhFolYTOVdznDza+okrWGzKWXXhpImboMoRy1RiAIZbJenYWq8jgVFjsAluQRnDHzX63vsGAfrPun6+fz74fU005d++z/oCIf0sbAOcKPQiAQhA5Zmz9AG6Ynpnt/jN37BVscgaBJFFnmwKGD2M1VxMYl0r1Huu+d5P8MG2sSzv/xMUgIfKC/UH4/98vHLTs7WxhtAkGIUZvzpDPTN05L78QIovQaNCqJcKd/iThLKyooqbZRZrJhVrSeF/XRACiWrpnssyvok6B9EToVOPqeM5WeYyZ3eaNN6FTHQFKp6J/ZnyHDRrbOaAPQ1YmdYe1687LvacsbobKykvLycmQvjoLp6a384wgEAp+56qqrgi1C2+OwANA7MQppwCSI6e5XdyeLS7GUuMJsJ9nU1A019Euhgia/HFNxNmP+4NdtOiRdQp8E7YrQqdaTs+1znKZS9LHd6T7s/GCLEzIInepChEWe+tlWFTw5goTfUSVffPFFMjMzMRqN9OzZk4yMjAb/BAJB+7F7dxcIW++wAiANuhRG/B36tC5fZC3VugR+CT+LvYaR6CI90whY1JE4ZAW1rdKve3RUuoQ+CdoVoVOt58TPn1P505vkblkVbFFCCqFTXYiaRPOyomA3iR03n1i6dClz5sxh4sSJXHfddTzwwAPMmzcPvV7Pa6+9RnJyMrfffnugZBUIBAIUpx2TxYJKkpAUDYFI4Tlk6HB6Zg7BbHNijPHsMSEhibBCHSqNBsVpR1JrG+nFxbacEk5PMzaaf64xHE6ZnXllPuWfEwgEXQup5rQBGtdzKvu37RTsXodsKmXkXx9GFyaSGgtCl8Kc3yhZ9xRo9SSMn0N8T99DoSraCPbkV+CUZeyReYwOLRe0Nscvw+25555j4sSJrFmzhuLiYh544AEmTZrEhAkTuPvuuxk1ahTFxV070pFA0N4MHTo02CK0KWaziYMnXccjlFQbpwM2h4xKwmdjqZYwjZqwSLXXa33PmQbnTAdt8y9E23JKWLrhEKN6xTHrnIwWy+Nwyry8OZvtOSUwnpAy3jq7PgnaH6FTree0lDCUqijs6akAVBXlEZazHoDKsiLik3sEU7ygIXSqY1BWVoy5+CgAVRYb8a3oQ1KpsKkNqOVqZEvXOwnj11HJQ4cOMXnyZAC0WtcqdG2C6piYGG644QaWLFnip4gCgcAX3n333WCL0KbYHDIH9MPIDhtAoU3HSy8/z1svPk7W/j1tc0OtoUVGG8DpaUZG9Ypje04JL2/OxuFsPjloXaNtVK84Tk8z+ilwYOns+iRof4ROtR49Ngw6NdFRLj8fQ1Q8GpWEQavGWV0SZOmCh9CpjoHKYUGrllCrQKdvXToAAPOIGygfeycxp18WQOk6Bn7tuMXExOBwOACIjo4mPDycvLw89/WoqChOnDjhn4QCgcAnHn/88WCL0KaER8Yw4PIHsDpkYuRykvbOBsBWMAAGDWtdp8d2QsUxCIuGjHNaLZtGrWLWOS6/3u05rpco986b0wFF+8Fa5XKuTuiPA5WH0ebLLl170dn1SdD+CJ3yg9qjklrXS2/fnj2ge00eK60lSEIFH6FTHYM+RhV0q9HXhNafLDl7/CUBkqjj4ZfhNmTIEH799Vf372eccQYvvvgil1xyCbIs89JLL9GvX9cOUSsQtDedPRGpTqNiWA8jAHZ7JCcjdWjVKtS61r+07PlxDfq875HDE+h3o6fhZnfKHDhZSVW1ibS4cLrFN53ss77xJskOZsXvQn1wLZTmgGwHlRY5thfrnSPZYRrBqIzEkDTaoPPrk6D9ETrVSpx2kF2L5bU+buiNp66by9pbopBB6FQHwVFnntYIf8zW4JfhdvXVV7N06VKsVithYWE8/PDDXHjhhe7w/1qtlg8//DAgggoEgpbRlSYvrVZHj5QUVy4XtanV/VRVVuGwOrBoGhpONnM11W/9nTDFysnTr6bbH//ebH+1xpskO0jd9Twljq0kqE1IhljQhCE7LFRlfU+m/Cuzuh1hxLiFIWm0QdfSJ0H7IHSqdZhMlRwrrEItSagqZHoC6GMACVDAUhZU+YKJ0KkOgt186metofF6gkbx603h2muvZcuWLYSFhQEwbtw49u7dy9NPP82zzz7Lrl27mDRpUkAEFQgELWPatGnBFqFtqS6G7M2Qtw1s1WCIdZWbS1vdpVHnICJMTXh4RINr4eERaHGtcjtMZS3uU6NWMSt+F2c5tmKzmjmiTkeOSkE2xJJrj+Ew6URrnIy2/Ihmf+i+dHR6fRK0O63VqW05JS3yG62PwymzLafj+3+ZqqupsjgoN9upcNREt1WpISwKp6JgqSgKroBBRDynOgaKvWaBVa116W4rKdrzLbkf/ZPD792NoigBkq5j0OodN4vFwrJlyxg+fDjnnnuuu7x3797ccccdARFOIBD4zmuvvRZsEdqUY4d3IW96GpUkEfWXxUSFx0HZETC3/sVsQLwWiIKUlAbXJJWKPund0VlLUSVILe/U6UB9cC0JahNHotIpN9s5efIEdrWBMgsYI3QYY/sgFe2H/Wtg4GWg9usQRJvQ2fVJ4J22TGvRGp3qjBFbfUaSMBn7IznMJESfise3vUBBU1GO2ZrDmWcHUb4gIp5THYOtB4+hP1qGrIvm9BbUb+w5lJt3BNXBnwCwWi3o9Z67d505vU6rd9z0ej333HMP+/fvD6Q8AoHAT5566qlgi9CmlJRVUFRlo6DSilXRUqpEUFJt49jxY63vtF5upPpEx8Sj16rR2X0IPVy0H0pzkAyxpMdHkKouJ7zqCOEVh4kxaEmPC0elUoM+FkqyXfVDkM6uT4KG1BpJLY2MWkutkbR0w6Emd7hao1OdMWKrryQk9+Csm/7LmXNeJnP4KQvNrjMCIHXho5LiOdVBsJlRFLBJYc1Wbeo5pDFEuX82VXietmnpc6ij4ndwkpycnACJIhAIAsHEiRODLUKbonbaQCUhKwpafQQHKrVoS0wgmUl22FFrmk6Q7RV7baS2Rs7c62sCklgrWt6ntcoViETjmqAirQXYAa1iQ6LO0Q6NDpw2V/0QpLPrk6AhdY0koEU7XL4YSa3Rqc4YsTVQxPYZjSMuifi4tGCLEjTEc6rtCcQufMTgP1Ial4lG17zh1tRzKDOtG6rcKDQqFSqN1eNenWmxxht+GW6PPfYYf/3rXzn//PO58MILAyWTQCDwg/z8/GCL0KYMTNKdCn8dGYEuKsFlBikKlaVFGBNTfe7TbK5G7ZSRJB1ezb5aw81S3vJOwyJd0SMdFnJLTETbnagkCUmCKpOZXEly7bo5bK7z/mGRPsvdHnR2fRI0pK2NpNbqVGeL2BooBoyfHmwRgo54TrUtATuqPGIcMK5FbZt6DhnCI8BpArsDjv8KMWldZrHGL8Pt+eefJy4ujokTJ5KRkUFGRgYGg+eKtSRJfPLJJ34JKRAIWk5paeuDdHQIHKdW19CEkdk3E6V6JLqoBLThrdhtA/blFSApTmyRVsZ4uX64Ug2F1dgx00+WkVQtmAwS+iMbe1J16AfKMBAjgVTjIhetkykx2UGppqezFCl9LCT0b5XsbU2n1yeBV9rSSPJHpzpTxFZfMZWewFF2HJ0hgrDEDCR16553nRHxnGpb2noXvjEafQ7t/RBO7gFFgfX/Qv59dZdZrPHLcNu1axeSJJGeno7T6SQrKytQcgkEglZSN1hQp8TtjxYGkkR42mmQdlrru7PbOanphlaxERnu3ZG5TDagstgBsJqr0EdEN98vKtbLo8iUd5GuKcQc3oMIs2tV2KhTkDUatBV5FOnDicu8CHUIBiaBLqBPgkZpKyPJX52qjdhaUhuxNSqd9ChXRNjcEhNlGEjXFNLT8iPS/tUw5HK/7hcqHNj+Lex4HYC+N79HZHRskCUKHcRzqm0J5lFlr88hVSWSIoOkQnF23sUab/j1piD82wSC0OOFF15g8eLFwRaj7ajdcVM3f0a+RajUxE55AotDJiU+3GuV8Jg4JK0ajVrCbipr1nCrXWncYRrBrG5H6Gn5EcVUgkWxISOhMhXSU1tCkT6c7zVjOVE0lBucckhONp1enwRN0hZGkt86VS9ia5nZAccL0FpLqFLFYYyM7BARW33FYat2v7TpDadSl1RXlnF450ZsVUV0H3oeKWl9gyNgEBHPqbYnELvwh9Y8h1qC8PTTSBrUcmO7/nMoN7InCc7fUYAys44ikjvlYo03/HqSbdq0iYEDB5KYmOj1elFREb/99ptYCREI2pHOPnltOZBP+PEyHAZdi8IJN4dGrWJs7/gm6ww47SzI6AX6aIhq2ofO43hIRiIjxi1E2r8aaf8atDk/oVKBKiwaKXkQcZkXcaJoKNtyK1A2Z4fk8Y7Ork+CZvBiJOlPHEPrNFEpx2GM0PtsJPmtU3UjtkZFoBSbiCr5HYBkVTXxcSNRSZJnxNbkwf7dMwTIiFajxBpwSho0Wp273FxZjvPHJaiBoqiELmm4iedU++DvLnz53q9QOW2crJZ9Mty8PYcinSApMjbZhjG2Y6TXCQR+vSGcf/75fP31141e/+abbzj//PP9uYVAIPCRyZMnB1uENsWClioiMalOrTiv+GoT/3vnPdaua/x55BfhcZAyBIzprkAijVD/TP+sczJcL1hDLocpS9FevQL15a8gXf4yTFmKetgV3HBeps9hztuTzq5Pgmaol9YiVq/CUJ2HxlJMirq8VWkt/NapehFb66KmzvdHo3PVC9GIrb4SH+YkITKM5DjPI5KRsQnun+3VXdPXSzyn2o/a3a+zanfh1enIUSnIhlhy7TEcJp1ojZPRlh/R7F/tbqfITlROGwDqsEYiODdGvedQjEFLiWSkWBUH+ugOk14nEPhljjaXrdxqtaJWtz4zukAg8J3Vq1c3X6kDoznjJo6UmIg2nDKgema9jb4yB4tpMPAH3zq0VUP5UVcOt6gUry+DLWVnXpnXM/1lh3/G/utKtBGxRJ55LZqoU6cU6h8/GdUrNqSShnZ2fRI0Qz0jSeesqoniClpbnSirPqS18Fun6kVsrTDbSNS4vmuFUiwVJaYOEbHVZ2r9e7We+Sb1hggGpCWiVWyoE5p+L+usiOdUO+Jl90tVVI5T0lJutmOMaGT3y25mUGo0TkVBTkvy7Z5eFmuqw5IBiNHXWUwN8fQ6gcBnwy03N9fDt23fvn1s2rSpQb2ysjJeeuklevbs6ZeAAoHAN2bMmMHrr78ebDHajHF9ExqUhRsTiHLkE6Mz+9xf4ZHfsK9biFqSMFzyKNHpQ73WM9ucVFrsaNQq4iJ0XuuM7hUH42mQ6+bIkcMoB3YA0GvEDIxRnu1qjbdQM9qg8+uToBnqGUlaczkoICsKZodEWSuMJL91ql7E1jiDRITK9TpTrTJwvJ0jtgYiv1WLqM03qWm4W6GPiofKE9BFk3CL51Q7Uu+osv5EPobyo1Spo4mJ6ul6Hng5qiw5rOhqFliI8HExpd5zqNxsJ6Zm8bbcbCe3sy7WeMFnw2358uU8/PDDSJKEJEk89thjPPbYYw3qKYqCWq3mpZdeCoigAoGgZXTFs/7DMjOALNDZfG5bXFqGpcIV8CTRoaWxsCNfLbubSGshhoyxnPWXOY325+0lzFFVTO3Zg2++WAHmUib+dS6RUTHuOhq1KuSMNuia+iSoQz0jKV2uRpJALUnocFLYCiPJX52qH7HVGJWKVOy6lmiMxFzdfhFbA5bfqgXf/dyTRYRVWFB0kFL/ot7oMtzMZT6OoHMgnlPtSL3dr2jLMexApLOCkrr16u9+OeosrHpZfGiSes8hY4SO9DhXMLHcEhNlHSS9TiDw+Wk2bdo0hgwZgqIoTJs2jdtvv51zzjnHo44kSURERDB8+HCSk5MDJqxAIGieV155hfnz5wdbjLajughUatBGuCYGAEONz4etChy2U+UtQLGbkSRXOpgwg/eokgApciFhjpNYqk74LPLAWAU5KZLiKit9jn8OQHnhNA/DLVTp9PokaBIPI0nKRy3bQZJQ6/TEJfSi2uS7keSPTnmL2CqVZCHbLTgUCcfJg3TXainTG9slYmt75rc6VlSKvtKCWSs3NNwMNX100R038ZxqR+rufhWbMDplJFxzaKXJQq6E990vex3DTeub4dZgsSa2DzisOKtLSJYtSLpYNB0gvU4g8HlkAwcOZODAgYBr9+3cc88lIyMj4IIJBILWMWaMtxTSnYeiD+9EY6+EvhdgPK9m58tQx1nfXApRLV8wGpgYBj2MyIqCZGw8zH+P1GQMZZVIRt+Dh4Q7qyBMg1qSsDsVdBoVOmuxz/0Eg86uT4LGqW8kJZevR7aXoyigi0pC7TDT01nqc1qL1upUYxFbK79bhqZgD4oio+CkMqYPcefc1C4RW9szv5UiO1w/eHnp3VemRjpRifWEhWGBGVqHQjyn2pE6u1+VioY4QAEkCaK1cqO7X/mFJZgLqlBJEpEWiZZ6uXldrCnaj0XR4ag4jgqFbvoyyvRxIZ9eJxD4ZZLOmDEjUHIIBIIAYTb77ufVkcgtKEHltGEz2qmdqh1hsTjsTuxOBam8kEgfDLfaVUCVJIG28R237ikpYM8FVSs+35pVcENSBn11ua4yVaXv/QSBzq5PAu94M5I0+1ej7F+DreAQWskJai1S+lif01q0Rqe8RmxVq2DI5RzILiSi1IRKcYJKjS39T8QNu4IbnDJK7XFEWrYb1hoCkd+qJZwx5xXsdgdyrQFXB5M6CpXdCTixmKs98rx1BcRzqv2ou/vVneOuQIWShAQkR6rB6n0XvqqqErPVpbthUsuCgDW2WMP+NahP7kMGFCSqovsQN+6GkE+vEwj83kv8/fffWb58OYcPH6a0tLRBpElJkvjmm2/8vY1AIGghhw4dalW7dnOw9wNFllHJdgBUdSKrFTjCKTjhMoT0+fkM6DGk5Z3WRmqTVE2G+iesZjfOUt54ncao9TsxpkPFMZAdUF3oez9BoLX6JOi4NGUkSQMvI6zeLpJarfHJSGqNTjUWsRVAiepOftxYUir3MLhbDBidQPtGbPU3v1VLkCQJnU4LNHxORSf2oNqYDgYjTpsVupjhJp5T7UP93a/Ek6vR2Mw40RCWMgC1YqWn84TXXXhNZDwlSWPBZiItKrbF9/L2HGLgZUjHd+NYdScarRbDyL+70uu002JNMPHLcHvzzTe59tpr0Wq19O/fn9jYhn+I5lIGCASCwDJlyhSf27Sng71fOK0MTIlElsHZ41R0yajYRApqfrZUFPnWZ+25e43eddajMfQ1/mi2KpBdK/stQZFlDucdRSvJqFL09IhIcAURqPZRziDRGn0SdGyaMpJQa3DED2Dj+4tRqgqJ63cGI8b/2ScjqTU61VjEVoBR4yfD+Mnw7aNwYrfHd6s9I7bW5rcqqc1vFZVOepTLgMotMbmCu2gKXUe99q92vYAGiL6j/gCjfEyF0okQz6m2x9vul+3X4Zh//RBNeTZqmt6F7zPwdPoMPL3F92vuOaTpcTrR3fu53CPsrgXVUE+vEwj8MtweeughTj/9dNasWUNCQsMQ3QKBoP1ZuHAhS5cu9alNezrY+4PktBGmqTGYIk/F1I+MMtIjKQ6NPgptSuN+at7YfugYhmPlyAY13hMBuChy6HFUWHA4ZWIrSokwtuyZZ6quoNLk2tWTHQYSw+JwFB/FUnCMeJ8kDQ6t0SdBx8abkXRi28dEUU1Er9FoEvsTc/wHNI5qrCdPLdi21EhqrU41+wIWUZMfsd5udrtFbPWS30opNgE0nd+qJSgKOO2uUwFNLTB1UcRzqm1pbPdLM+oqwk+f2sCX09ddeG80tVjjJiLRZbhVF7iLQjm9TiDwy3A7duwYd911lzDaBIIQojWTV5MO9l5o9AhDW1Obxwg8EnFKKhUJM99p1QuN3WpB41Swyk0ckwQK7Xqs5a77q8uLW2y4WZ2wr9sUFHMZg5P688vvOYSdrMJRktMhDDfxMtQ1qf/Ck7vlE3TVx5GStnHatc+ijU4iypSHJFV41GuJkdRmOlVjuMmWcrCZUel8DDnuL/XyWynFrnxTADEGbaP5rVpCeclJ8pdfi6RSoT5zNv3OnNyWI+lwiOdU29Lc7peSNIiyahuVFcWk1yxGBGL3q/nFmgQoOhC8xZog4JfhNmzYMI4dOxYoWQQCQQCYPHkyq1ev9rldo8YbssdqmiMuk5e/z2t/ow1O+aOB62hjXVq5Cm0dcysHCsswNpNBICzKiBVQqyTs1aUt7j/OaOTKv9/s/n370Z0AaOyV2KwWdGH6xpqGBK3VJ0HnoazwOLrq4wDYEl370qcNyIS8UjCYfO4vkDqlyDLle78mIiaeY6VmKvPLccgKqQX5JPfoG5B7tJh6+a1wWDDYK1wpFAzdTtWrn9+qBVjM1dicMjhltIr3Y9on8g5RXVaEPiKG7r0H+DOSDod4TrUtXne/nHZQaUCS+GHVMgwHPwGVmrT/+wRJ5apTd/drgHSU8t92EBYRg77n6IDIddwZjaPUhK0ol552Oxpt0wuwnQG/DLenn36aqVOncvHFF3PWWWcFSiaBQOAH/kxedY23HdmFrD/5JReotqMqOwKyHUWl5bA9AZU8ktGDLuOGdnb8PVlaTlWhK5ywwaQ0zGXUCsYPSIYBnlEovQVq6dkzE+WS2WjCYyAl02tfLQnU0rP3QJz2UYRFJ6FR7EBoG27iZUgQXfYbmcmRVJodKIPOcBXWHks0FbmO8fmwcBJInTKbKsj54mkALMkj0csuv/qKouPtb7jVzW9VYsJuKifRcRKAo9Wx5EqS9/xWLUAnW4mL0CErCproKK918lbeh9ZWTmHa2XTvvSAgQ+ooiOdU21N/Xvtt4/tof/sYJbYn4bGDkBQnOJ1UVZYRFXOqbu3u109vP4/+6PdYw+IYO/fdgMhUrEThqLIBUFpygsTktID0G8r49cb1xBNPEBMTwznnnMPQoUOZNGkSl156qce/yy67rNX9W61W7rnnHrp164bBYGDs2LF8/fXXLWqbn5/PtGnTMBqNREdHc9lll3H48GGvdV955RUGDhyIXq8nMzOT5557rtF+V6xYwZlnnklERARGo5GzzjqLb7/9tlXjEwjagtmzZ/vVXqNWMWtcGjdKH5F56FWqDv2A7LQhq3QUlVcSV7yTv1g+ZJb0sWs3rh2pqqqm0uKg3GzHLHuuO+3OLeG9jb/y1uf+fR9rA7W8vDkbh/PU+NQRsWiG/hn6TICIhocca4+PLt1wiG01O5beSBx0Dil/fozYC+5Apff+AhZK+KtPgo6P6sSvROg0pCQmkNprkKuw1nBz2n1O+hxInaooPRWIRJc6EE1iJrreZ2GMMQbsHi2mNr9VWSFl1TZ0YXrUKgm1SiJGp1BmspNbXI1iLoW4DHd+q5YQq3OSHhdOr/gIeiR6XxhyhhkBUMytiHzbwRHPqfan4thBqqsrqTh5hG49+9Ij1kDvhAjCGstRWuPqoNQ/LeMH+oQMToT3Iz9hHDZ71wiG6NeO265du5AkifT0dKqqqvjtt98a1JH8cKKdOXMmK1euZO7cuWRmZvLaa69xySWXsH79es4+++xG21VVVXH++edTXl7O/fffj1arZfHixZx33nn88ssvxMefeul66aWXmD17Npdffjn/93//x+bNm7n99tsxmUzcc889Hv0+9NBDPPLII1xxxRXMnDkTu93Onj17yM/Pb/UYBYJAs2CB/yutmn2fMsryE6UaJ4fldGJsrnOE5U41xphE0lWFqA58AYmZAY2M1hxKYj82DHgQ2WZmWmIfj2v2vZ8wYNd7AFjOH4M+vIWr2fV2C5oM1OIloS5qTZOBWkwHNqIuz0EXnYTU/+LWDz5IBEKfBB0Y2emK1AiQOgxqjkA5DQk4HDI2h4xUcpzI7s2H964lkDoVTTXaOAMOp4K6zyASJv49YH37St38VumaQsKsJaCW0KnVREerUcze81u1iLr+vV4ScAP0Te+BvrAYVVzXeIGti3hOtT8JtmPYNSosMT1JTk2HyJojwpZioOGplL5xGiS7AWtM4Ly7+wwaQd/BIwPWX0fAL8MtJycnQGI0ZOvWrbz33nssWrSIu+66C4BrrrmGIUOGcPfdd/PDDz802nbJkiUcPHiQrVu3Mnq06xztxRdfzJAhQ3jqqad4/PHHAVfCxgceeIBJkyaxcuVKAGbNmoUsyyxcuJAbb7zRneLgp59+4pFHHuGpp55i3rx5bTbultIRcm4JgsOqVauYM2dO6ztwOmD/GiRLKcZu/SktNlNdVoBTpSMm2kh6fDgqwqFwn++R0fykb2o8cy8b5/WaLjoBVBJatQpLRXGLDbfSt65FLVuh30Siz5zp3ddvXBqafZ+6xluag+K0I6m1EJeBs+9E/lc8jO25FV59/nZt24D+6A849HGM6oCGm9/6JOjQKMVZSPYaP7bU09zlJ5zRFB53BSYJO5rLwO6DWtxnIHUq3FlJeETNC2NictOV25D6+a16VH+H03QUp6RBQYNUdZKe4DW/VctuUCfBtMa74ZaQmAwVGnBW+j+gDoZ4TrUzDit99RWQGo08cMSpHXiAqgKvTRLCnBARBgktX+RpDn82hzoqIZuVbuXKlajVam688UZ3mV6v5/rrr+fHH38kLy+vybajR492G20AAwYM4IILLuD99993l61fv57i4mJuueUWj/Zz5syhurqazz//3F32zDPPkJKSwh133IGiKFRVtdypONA0dpSrOVp6lEvQsenTp0/zlZqiJjIa+lhXUmpTManyCXo4ckFxJbZFUnlGRgsBhvTJYEj3GPqnRGGk5S8u2SeKOHyihH3HT0XHO+VQHceO7EJ2vv0PlO//i2n/N5ScyKGsrBScdpTcLZR8/SQpu15gdHq010AtSk3ybYcuxl22/vvv+eTj99i84Uv/Bt0O+K1Pgg7Nzq0bOXiykhPlFuTkYe7y2MRTHqaW0uM+9RlQnTLXCRRkCNwLoS/U3XEfkZHIiL8txDLsb1g00SCpUCEDiiu/1R/nc2LYHLblVvg0h5dXVlJpcWCyOXCqGzlqVjt+S4Vrp7QLIZ5T7UxZLuDa2VXF9XadQNGGu65Vezfc3DlTtaHt1x3q+G24OZ1O3nvvPW666Sb+/Oc/s3u360hFeXk5H330ESdPnmxVvzt37qRfv35ER3vmZBozZgwAv/zyi9d2siyza9cuRo0a1eDamDFjOHToEJWVle57AA3qjhw5EpVK5b4O8M033zB69Gj++9//kpiYSFRUFKmpqTz//PMtGk9BQQF79+71+JeVldWitvWpe5SrpQ/+YOTcEgQHg8HPENg1kdFktY7cEhMRtmIkQCVBldlObokJWVFckdFku0+R0dqUui9t5pZFfZQdDlSyK1x3/dDhtcbbtPAdJB77ltKKSiyqCNSKA2QHclQKR9Tp2Kxmxjm2MCtht9fV88woB92MelKST73oGna9Sc8Dy9FmrWnFQNsXv/VJ0KGx5+2k2uYk2xmPKuLUSY3wyBiiB11Iwtip9B3o21GlgOpUzcIIKg1owyk4nsfun77h52/eb7JZoPCaGkWrIzLzHGIyRhCedhqalMEovc6BKUtRD7uCG87L9HkOP5xfwKHCKg6crMKuaiQErt5Y84MClq7l5yaeU+1Mac6pn2N7AXDCGUV+mZn9h7K9t6mNCl1r4AWKksPYDnxL+d6WxcDo6PhluJWVlTFu3Dj++te/8u677/Lpp59SWOjKpRAZGcntt9/Os88+26q+jx8/TmpqaoPy2rLG0hCUlJRgtVpb1Pb48eOo1WqSkpI86ul0OuLj4931SktLKSoq4vvvv2fBggXce++9rFixguHDh3Pbbbfx0ksvNTueJUuWMGTIEI9/U6ZMAeC7775j48aNLFq0iJKSEmbMmAG4wtsCzJs3j6ysLF599VU+/vhjdvy8nYJN73Ba90he+vBrXt6czZ8mXwrAP+6/lwPfreKrVxby+fJF7P51J/fedz8vb85myQdrGdUrjm+X3I/NamHhwoVs3bqVjz/+mFdffZWsrCz3MdDae8+YMYOSkhIWLVrExo0bWbt2LS+88AL5+fluZ+DaurNnzyY/P58XXniBtWvX+jSmrVu3snDhQkwmE9OmTfOoe//997N7927eeecd3nnnHXbv3s3999/vUWfatGmYTCYxpkWLePfdd/0bU1gk+w4epri8gqMnS1Cr1WgkGUWlQ6OC/MIyjhRVcejgPlBpufXO+9rt7/TJU7dS9uZM1t89GmTZY0zHysxk5+S4Fkl+/q5Ff6fVq1aSYlDQmovpmRjT4O/00IL7GVX5DZH2Eg6YojA7JBSnHb1a5odf91NmdpBToSJeVcVvHz3J1p9+bDCmBI2ZnN930atHd/eYsgsqUJw2KMkNed1buXJll/4+deYx3ff0/ziSd7TRMT3//Av8rBrODu1ItpREu8fkcMpMmD6L3pPn89QnezlpD/dpTC+99FLAxrTvUDa7Dh5hf4GZtV9+yWfL/4N9/b8wrV+M3WZp87/T7H88wbe7c9CUHSEyfwu//7bXNSZzKVu3bafApmVzVinbs4tY+Pi/2Lp1K6s//QTtoY1kRMm8/vlmduaVNat7FaVFVFZWgCRxxbTpXse04ddD7DiQS9bJCm6/47aQ1r1Af59effXVTjemUP47vb70KcqrTBzMOcra739h48aNbNxXSEGFmb2/bPE6ph1797Ev9wQ/H8wP6JhWv/pvfn7nIXZ/sSxgf6fvvvuOUEVSFKXVXqyzZ8/m7bff5qOPPuL0008nKSmJdevWMWHCBADmzp3Lhg0bGt0da4o+ffrQv39/vvjiC4/yw4cP06dPHxYvXszcuXMbtMvLyyM9PZ0nnniCu+++2+Paq6++yvXXX8/OnTsZPnw4119/Pe+++y4mU8M8NOnp6YwYMYJVq1a5+wR47733mD7d9dCUZZmhQ4dSUVHR5NFNcO241Rq1tWRlZTFlyhT27NnD4MEtS8JZl7orfaPTo5kVvwv1wbWulRDZ7gpLHNuLb5wjed80ghEZicw6J4OdeWXCP64TU1JSQlxc6/9GDruN7Jf/TmzxTqqiM+lpz3KF+Q1PQDamk1tioqzaRm9yiew7DtWfX2o3H7dtq55Hu381iqTm9Ls9nw0oCnwwA6fNgj3zYvRjr22+w+pi+KTmqPSYWdD3Qs/rJ/fCp7cjO23k2mNQVeSTQBkKEgc1mRjDa5LqVp5whfe+9L+eCXWdDljxN9fPQ66AYVNdP+94E/Z95tolmP5Wq3PQtQf+6pMgNKk9ct/SXIyyrKBSSR7zzuzxfVo1HwRSp37631z0xb9jic7gjJuXsnvzJzh/WAJAj7+/REK3XgG5T1N49Tn/fTXsfIsT5RZOVLh2GgbN/cQjb6Mvc2pJ4XFKC4/hsFnoP9y7n++R/b9QusoVVC38D/fTb8R5foyqYyGeU+3Ljy/OxlCRjT02k9E3uk6ebV35NPrDX6LR6Rl0xyqPeU2RZX598hJQFOz9L2P0lFsa6dl3tq96Hs3+1SiSimF3foZa7T3PoS/s3buXIUOGtPr9vC3xa8dt1apV3HbbbfzhD3/w6iDYr1+/VgcwMRgMWK3WBuUWi8V9vbF2QIvaGgwGbDab134sFotHPQCtVssVV1zhrqNSqZg+fTpHjx4lNze3yfEkJSUxePBgj399+/qXY6b2KNfo9GhSdz1PyddPouRtdYVnVochO21UZX1P5qFXmSV9zKxxaezMKxP+cZ0cf4LnOJwyL3+fx7fySBRDLOnSCSTZgawoWNBhsjlJj9WTriqgRI5knTwSRzu6yso1kdVkdVjDi5LE9gLYnV/Ozv3eU380oDmH/5pjoyqNnvS4cPRhYdidMg6nk1i9ymW0SVLjx0atp/zmMBhP/RyRUDMgR8gfaQqFYEyCwOPrkfv6Rps/R+6vu/sxn+afWhxOucH8Y1L0mFWRyAbXS3ufXhkMSIliaPcYEqQKb90EnNG94hoYvtbKYmRFIVynRhXXE3X6GBxWz0Xi2vxWLSEuMZU+g0Y2arQBRBoT0KgkNPoI1LL3d5vOinhOtR9Oh4OwqqMAyLEZ7vLhE6Yx9NrnGHTTaw3a2O02yjXxVKuikAzRDa77Q0q3NFJj9PSM1aOYOv/7qV/L5OXl5WRkZDR63W6343A4WtV3amqq1zD7x4+7nKC7devmtV1cXBxhYWHuek21TU1Nxel0UlBQ4HFc0mazUVxc7K4XFxeHXq/HaDQ2sORr25WWlrp35doTjVrFrPhdlDi2YrOaORKVTnpUBIBrZwQD6ZpCelp+RNq/mtMH/rnxUOeNIPzjOhavv/56q9p57OAOuow4SUa190OwVWFT1JgsR6G8gMhwLbHRsWTpz+SD6hEc2pzdIj0KBL2NaqRYA/aafEX1seti0FSfRDI3kkemQYO6Iba9OEzXJNTF4VoIctbxLVErdV6MGkmoW1J8Elu5BY1aIkyKwJ21rW4ELlOxp1EXYrRWnwShjdfoqbXfY6fDFTXWVgVhUZDQHweqBr5cx4/mcOiXTTgqCzjj0llERjcfHGRbTgnxZ1/Jyz4+N+o+nxh/KhnwhFn/xmJ3ug3B8NgU0NbM09WFjfTW9uw8kI0+vxxneAIjb1vWLveMT+pO/LxPQONlYauTI55T7YekUmOcvpTiowdITjoVyVUX16PRNrowPef939s4nDKBTlbRo0c6ZNXM3+YiiEpsukEHxy/DrU+fPuzYsaPR61999RWDBrU8RHBdhg8fzvr166moqPAIULJlyxb3dW+oVCqGDh3K9u3bG1zbsmULvXv3JioqyqOP7du3c8kll7jrbd++HVmW3ddVKhXDhw9n27Zt2Gw2dLpTL2+1fnCJiUFSFKcD9cG1JKhNHIlKp8zsQCl2reqVm+0YI3QYY/sgFe2H/WvQDLys6cm6Xo4qb5N1e7ygC1rP5MmTWb16tU9t6hvnN5yTgZq7OFFYQEzVahSbCb1iwelwoKT9Ean/xYzoP5kR3+f5tAjgL4kGXLlioo1er6ckpxIu56KKatlq/vGiUixF1ahVEuFWFQn1KyT0h9heKHlbybVFYbJKRKkkFAWqq6vJVRtIj9WjspRC2tgGCXWLCgsw1RyTipPDTxlu4fEoioJdVnCUnSA8PnQjorVGnwQdg/rGmyQ73Efu7Sf3oZQfRRUWharbMNarzmaHaQSjao7ca9QqqguyMe57F4DSkxe1yHA7Pc3I3o2fAi6/7EAsHuq16lPGmiEOkAAlqIZbbTRZmzam6YqBRJK6pNEGnes5FerpnlQqid7pPeid3rih1hht8o5QdyG0uhAYGPh7hBB+GW433HAD99xzD+PHj+eCCy4AXDkVrFYrjzzyCGvXrmXZstatNF1xxRU8+eSTLFu2zJ3HzWq1snz5csaOHUtaWhoAubm5mEwmBgwY4NH23nvvZfv27e6Ikfv37+fbb7919wUwYcIE4uLiePHFFz0MtxdffJHw8HAmTZrkLps+fTo//fQTr7/+OrNmzQJcxynffvttBg0a1OgOYJtTE7pdMsSSHhWBUmyi3OyKkhdj0J46ylUndLsmeXCjk3V9/7j1zpENJmtBaNOayWtnXpkX41zFQXMUUWSg15rpEaNFp9XC5GdBF4EGPPRoVK/Ytvd/rN0h03gPJ5zxh9kg3QxhLXtZqqiqwFzzfVEpXiK1qTU4My+iJGcPWlMehojuOCtc64XhKgfF1TaizUeJjY51Jdeu5+tXrejJ0g8lXK4kLfbUymS1xkhWfjmKAsqhbE7v0/jxp2DTWV6GBN6pNd4k2eE6cu/YSoLahN0hI9sdqOzFOLK3kckBZnU7wohxC93zQFR8KnaVhE6tQjK1zEjSqFV897+HT+2eEeDFQ7UGwuNcO9lBNNyiR19JVWEeekNU85VbwK4PHoWqAjQpAxl08c0B6bMz0VmeU776ntbS2I50MHA4ZewOGUNY+/i+tySHXGfCr0/1jjvuYO/evVx11VUYjUYA/vrXv1JcXIzD4eCmm27i+uuvb1XfY8eOZerUqdx3330UFBTQt29fXn/9dXJycnjllVfc9a655ho2btxI3Rgrt9xyCy+//DKTJk3irrvuQqvV8vTTT5OcnMydd97prmcwGFi4cCFz5sxh6tSpTJw4kc2bN/PWW2/x2GOPeTi63nTTTfzvf/9jzpw5HDhwgPT0dN58802OHDkS3AdGjQ9Os6tsGh04bW4fnMYma8kQC5owZIfF5R8n/9pgshaENvPmzWPx4sU+tRndKw7G02CVT2UpAUkiLDyGSKPrCC7mUtC5fj6V76wdjDYAZ43vamP6Hu6bDM74/nzf82Zkm5npxpQG1x1Omf8VDyNFM5ZxbKGbchQTThRFJpZyYqiixBFJlv5MRvSf3OCBevrIsQwdPpoKiwOjQXtKzMgYHJIOtWLDXhHaE01r9EnQsfB25D7WlguSBjMa8lUZpKtOHblnyOUAdOueTvfuNYsk2uoW32/+XXey6MmnAD8XD23VUF3kSgUSFuUOhrC/Sg8FlVSZDjDyrIB8RD4zePiZwJkAFB7Ppfh4DpIi03/k+Fb1Zz55iLDqY5RLzYdSt5irMVdVEJvYMLp2Z6WzPKfq+p5CiLqzOB2NBiT79qW70FXmokkfxRnT6gQItJtd7w4aPehjQOV/ABE3mjCKHWHYTeVU5+TQZ2jgug5F/DLcJEni5ZdfZsaMGaxcuZKDBw8iyzJ9+vRh2rRpnHvuuX4J98Ybb7BgwQLefPNNSktLGTZsGJ999lmz/UZFRbFhwwbmzZvHo48+iizLjB8/nsWLFzc40njLLbeg1Wp56qmn+PTTT0lLS2Px4sXccccdHvUMBgPffvstd999N6+++irV1dUMHz6czz//nIkTJ/o1Tr+o8cGRHRZyS0xYK4tI0CjI2ghKzC4/t/S4cFRefHB89Y+rnawFoc2cOXNa1c6b4TXuxv9SWVaIfOxX+PV/rsLKkxBz6oiELw72/pJXUIKuwoISAQ3NLN8ZlNGDQRnej3u4J8PcCkYPm0NcwrlIB9eiPbIFtexApY9CSRnKT/JIPqgewYjv87xOshq1irgIz908SaUivltvtIoVbTfPdCShRmv1SdCBqHfkvtxsI9FRDSqJciIaHLln4GWg1iDVJt21mxpPuuuFOXPmBGTx8ODurVi/fQKtWkXcX54ksZfLNaOUGPR2J3JV8Hbc6pK19gUMBb9gjegGrTTcwlV21GoVjjCX4dbYcbqf3lmIPu87bPp4xtzxToN+Omt06M7ynGrW9zTI7iyKLLPvxatQG2IwDL2UtDGXelwPd5Shd5ZjrvR8HhzasxXLN/9CJUnE/WURyRlDAirXwepw9BUnMauPErqOB4EhIPuYZ599NmeffXYguvJAr9ezaNEiFi1a1GidDRs2eC3v0aMHH3zwQYvuM2vWLPfxx6ZISkritddea1Gf7UZCf2RjT6oO/UAZBpLlcsKtJpw2DfaI3pSZ7KBU09NZipRezwfHi3+cpqAYWVJTZpUanawFoc2mTZv8jljqRpKIik0Cw5hThlvVicD03QqOFZcRZrJgDnd6NdyqrA525pZSWm1jVHo03eJad0zJq8+fuj8MnoKuzsQpJfRnAioOeTv21Qy9/ta6HJftTUD1SRCa1Dtyf/xkNQ6rEwBtpJFkL0fu3WkvIhKgLNeVWqOF1OqUv4uH5opiZFnBITvRRJzyr4uM74ZUEY8mIhlFlpFUwT0too5KhgLQmQtbLc/QJB3YoqFvtyaP06nCXM88ja2iwb1C6ThdoOlMz6mmfE+D7c5SUngMa3UFVFdgqjSRVu96fHIPIlUFaMI9I6hazdXYnQqgoHiL4OwnzqjuFJtM2NSdR6cbw6+38OzsbPbs2eNOXlef1atXM3ToUHr16uXPbQRN4EDFenkUmfIu0jWFqBSXD5BacRBrzUcdkYG2Io8ifThxmRehrmt41ZusNQXFRFVmoaBCiRlAWlOTtSBkiY1tPkCAz4RFc6xawWo2Uf7bPoYPmNR8mzZgS/TF2DXl9Ens6fW6uawA6ZO5pDkrKTlrNt3Ouczne9Q32jwmQ7WmwXegvq8f1DHecl3BlIhOBWP7R50NBG2iT4LQot6Re5186qXLpo44Va/ekXsAIpKQS49gLTtOS1/H3DrlY3Ct+ouH8RoTcqQOh1MhyhjvLh9y0Q0gNb8Y21YUHz1I0Q9voomII2nMX8js3QddVSQ6tcqV/iPcx++Uopzy79WGN3mcrltqKtpCPVq1CsVmQtK7Ttl09ujQne05FaruLI6ibCJ0asx2J9Hd+zW4npmRAbbfQVXh0tua48tGnRNnhA5ZUYiIjGzQzl9Om3ofOrUKnabzu/T4ZbjdddddVFRUNGq4vfDCCxiNRt577z1/biNohNoH8Q7TCGZ1O0LP6k1gM2FxqnECGnsFPZ25FOnD+V4zlhNFQ7nBKZ/6ctebrMOtrq1tCRmdsxpqY+B5m6wFIUv37t0D0o+tsgSdIdL195ck8h0xaM3lVBU1TNPRXtx2zZXYnQqy4j2gcFS0kUinKy+ao6r5HQDbntWoju1AHW5EOtt1PNp7oJamqb9CWuvz9/OnzxNuK0JOO4vBUxe0dJghRaD0SRDC1Dtyr7WaiVCrcEpaSi0yShNH7n8uVqM+Wo6stnB6C3eT3DrVSHAtSXESE673Glyr7sJJ9zArxIaDLhK0dY4jBzmhfeHxI1iyXYs2YQP+QI/kHqCred2qLvDdcHPaQXHtgKLRN3mcrkdyMoTZXTki87dBr3O6RHTozvicCkV3lmTncZKTo1AAJWNAwwqRNUf/nXawlLn8T4Fu4QrE1fhnRgQmYI/HbdsrEEoI4NdIf/zxR+bOndvo9QsuuIBnnnnGn1sIGsFj9SwjkRHjFiJtXgQ730RnrQZFQVJJ0GMkcf3/xImioWzLrUCpmzun3mStsdkJlxUkCcwWS5P+cYLQ5csvv2TMmDF+97P1/X9jLN2NM3kYp/39CdTRKYSZj6KnNABStg5JktBpGn8p0xvCGZCegk42o0poPiXAjt270ef+gF0Xw+gaw62xQC21lJZXsv7rT3GUH2Pw6PEMHjYa8BKoRVGQLGVYnTI2VcPvTnFFNXsOZmMqPc7YkSOJiw3NIx6B0idBCFPvyH2qbMOJAmE6jAZtk0fupQjXi5rKaaW6qrxFKQHcOlVv8VBVfZLuVpdfWlV4nZ3txhYPa0Luh1oeRFvVqSTAUcYE0NhPXaw6CYn9vbRqHMVuQlYUVBJIWte+ZqPH6Xa/Byf3uHY7vnwAOWlgl4gO3SmfU37uSLcJpTkASFEpSGFeAuVE1PHZrg0cBOComzM18EcluxJ+/YVLS0vdOdG8ERkZSXFxy8+9C1pGo0e5olIgZShqW7VrtU2lgfH3oU7szw1OGaW+H069yTpFUlCrJNQqiSiNk/ym/OMEIUvdyKn+oK7Ic4X1rXlMjBgxFk6EQ3SQUl+0EH1UPFTkuyJYNYfdDICs9kwv0JTvh14j0fvQGwBYj8ZDjeEGnoFanDYzSQawO7XYYhvmeaw4+hsx6/5BDFCSuIC42MD7CQeCQOmTIHRpeOTehoyCLOlIjwsHpbrRI/fJaX0wFQ1BE5WEBmeL7ufWqXqLhzaHQhSuBZfKajO5ktT04qGlzPW/oaGxWFRUSFnRMQz6cLr3yvT5M/GHYXEKzu4xOGQFbUw81P1cWhGuvLi8gqNHy5EATbqdwTVTsdfjdFIFkiKDpEJ2mLtMdOhO+ZzysiNtqy4j2lmGNjKFbnEx7e/OUmO4EdvL62WbPh6T2YbNoeDMzyU1oea7VzPXoglrmx1xWXYtilQXIocnoorpvBFV/foGp6en8/333zd6ffPmzfTo4XuCPkHTNHaUSynOAknlchavDY9cXQTU3Q1wnYvfmVeGAxXfyKMokSNJVxUSVeM35JQV1LIVo0Hjmqyd4TgzLxKBSToIM2fO9LsP2WqiT7iZuAgdMak1MZoG/gnOvw9GzvC7/1ZhN8N3z8BPS+Hk3sbr1aYEqF2Nb4JeRg3dYvR0SzC2WAxDRCSaiFhiDFoSlJJG66mt5fSIDScjIYL+veq7cEN0vGtiUUngqAiN6HfeCIQ+CUKX2oXA900jKOh2AcaoKMJ0GpSwKLRaLarKE/R05qLTG/heM5aXi4bicJ7aze4+6Ewy//YUGZfegz66QQp7r7h1qnbxsKyQsmobekM4Bp2ayDANcWEyZSY7ucXVKOZSiMtomOC+6CSVFgcmVcMF5Ow351D1yd3k/RAEVw1LGWqVRFhkLCqNBjRh5FTryCqoYufvB3zuzmZ27bIogFrnuVtRe5zurJrjdLnqntjQYZE1HLfoOEw60Ronoy0/otnfOXKdeaNTPqe8pHtKtB1F76xAZ6kzZ2h0rnpt7M5iqSqluuwkTkWB2AyvdeTwBHKKTBwrM3MsP9ddXlJeTqXFTpXsJV9qAHA6rOz/3/Xsfutudnz3RZvcI1Tw6038qquuYuHChYwZM4Zbb70VVc3ZdqfTyfPPP8+KFSt44IEHAiKo4BTejnJZLGb2795FhBYMg8bRvajGoK487m5X9yjX6WlGT/84y49IluNUaTRgN6OxlzftHycIWd5//32/+1BV5pMUVTNZ9AuNgDTl5WXk//QlKhWo5RTKzKnejzMaag037ztudcNhp4QrEK2HJN+OKQ7p3w8K94O2vPFKtbsB4PUoV1xCMtHdY9CoQIq2+nT/9iQQ+iQITbwduVftX41h/xoMJdnu6HVS+ljiMi/yfuS+FdTqlMdOn+o4eksl1Jz66B4p4bBoGt3pU2SZvGPHkGQnNqNE/UNyDkM8Wlt5cJJw1y4a6Y3uohPOKPTWAiylx702aYqImHgcw/+ObK0mtXu9YOdejtNF2ZygKFgcVoyxXSM6dDCeU42lZGiOFqdkqLcjXW62E4WESoFqm4Kpnd1Zjv4/e+cdJllZ5f/PDZVjV+c8OTEzzADDiCg5CIjiTwwYEBVYFUUQV11cWXdhXRWRNeMqKOoaEEVBURQVxCUMYWAGJs/0TOdYOdcNvz9uxwrdVV3VPT1Df59nnu6puuGt6ve+5z3nfM/3HNpNdCCKAHg21rEkzzFWuxNFdiArMdRJLQH2dQ9hHYqRsjnZOgdjk8w2ItiQtSjKAu+NWi7Kenr/5V/+hX/84x/ccMMN/Od//ierVxvRsL179zI0NMRZZ5216LjNEbIf+N7De9E1hWgKVM8qenqeJx0ZIbx7DydOakYoS+K40zalPm7vQ7D3D0id29ElE4LJhtB2ckWN9SLmB5deemn5TeGDRyZ+905ki1RNxx9LIwhQ45yh6XuFkUzGSasaqNDvV/jlvvxy2HvDMvRHSGsR1s8khz1O3yiRc+9qNBy36EDhYyZn/CZt4MYgSCZMzhqIj4xnxhciKjKfFrHgUJByv/6txuY+q1+UJMn5KfezsAeXXnopD/zmt1OCh43Bv0CwH1WQ0XUZITZIO2LB4GE8FkbQxloW5G6Al7Uvxd43gOzO5Lw358hD4TR7G5Ezwzhc7pIv5/HVcsqF78n/Zj46XULGRAabpNLwKlGHnu91arqWDNOhpJYMWeUsXruMOaWhCwKSyYy/wuUsMzmi4d59iBiZX1/rxL2yHdElF3wYu92BrWZC/VkftbW6PLUsoZJw+hpxxo4gWo5vIb2yHDeLxcKf/vQn7r33Xn79619z8OBBAE499VTe+ta3cuWVV45n4RYxt7Da7AwtORuG97Nk6Qb27PgD1kQ/yeGuKcfNZKxtc2isFzE/qIjxCo7OG8kEzomOabf/5LeYY32sXtrGJW+Y35YAFjL4RuWEfW21nOLML4edkNyQMTZ0kbAft9egb+WVw945JrFdojFx1hs/kyFIx8GcW6Q9MjKIKZHBJIlYrR7ysvrt1YbjFl+4jtui03Z8Ylr11DxtL6Cweuru3Tvx9x3GYpY55XUXzXjvMadtcvDQ/wcrlh0/QdYSiIIOmoaw5LSCwUOrw0Pd1fcRDfmp9uY6Q/WNLRAwQSYEmgqiNPsvq0S8uK8DmxJBswmsHX3tpLffPDdjyEOn85ub0EUZh33SunScq0PP9zo1XUuGQii1JUN27anX04qYMqHr4PS40FKFM9KlohhHdNnpb6Or6USiQ4dxj7bfyOeI1mw4P+fc5ZfdTDQSxjuHgq9rli+FriEwxebuJgsAZefLRVHk/e9/P+9///srMZ5FzBJN7atoav/M+P9lTxOWyD4cwlQqVyFj/cqf70Ud2oelZjmrL/jAlHMKGetFLEzcfPPNfOELXyjrGh0HduGJpbHUteGYFHw5L/Jb5Ggv0Z4Tgfl13LwmDe+YnHBdNdeckF8O21tVjWxKYxZVxO5nwXV+QTnsvuEApkwKPSmSKx9SGKqzgUxGJaVoCCM9uBtzxQ86urqRh2PogsiJZnd+x81RA8P70KND+d9fAKjEfFrEwkMh9dTOR+/CFOnC2riWqtfkZnly1FOB4FM/wjG0g5SzBWZw3BRV4/J//Q7Vq0+d8izWLd8MkV0kYmGCqTRxk4+Wy+6aNnjYVO2Bak/+G42p2+mqQZt2FFd/Vy50TYNkiISukRYm1d7NleOYh07ncRrfSTCRgVeJOvR8r1PTtWRAVXIy1qW2ZMhp95R8CmF4H3omSUYXUEY6aTbJBK3eipSzFOOIel0OvBs3A5unjLEYR7Su2kdd9RzvG8ee+djQlB5yxxuOP6LzIgA45eIPAO8H+1RjVchYhzt3YBt+mWCgH7IcN8hvrLMx53zvRRSFK664oqzzdU1juPsAITVOxuVhy6T36pvasA8FkDzJgufPGSbLCcuWgnLYSw48CJYEoMOTX0bbc39BOey+kQCimiYdVEty3PpUL8P9EQCsnYfyOm6RjIQseTHJEmKBZ2J32ILeGyatRdioqojS/GUFikW582kRCxf51tze/S9iDXeQGIpyWh7HDaaqpwIIzjoYAmvaP+OGaXtXEFPTmtzNa8IPgkhAtTAYB4QYDaqKLMmzCx46JhpyExuaN8ctk8kQWXYJajxATdPamU8oAj27nyHa8Syi2c7SM9+DPLlnXTadzjGqBMpor69XiTr00VinCrZk2P9HQ31xtEZUq1pSUkuGvO2e9j4E2/8Xup9DySjoJAg7V+M767qKlLPMtSM6L3CMWnFNMYI19uNzT1m24/bII49w9913c+jQIQKBAHpWY1xBEMYplIuYRzgLb0PzGTx3agBVAN3VxL5tfyTWtw/JWcvGcycWw2xjPRnzwvdeRFHYuXMnGzZsmPnAAggG/Zg0g49urZ2qHNXatgwSe0CdeYNWcSiTBDxGefJ55bClOIKtCmQLmpIsKIet6zpP287CrCdZUVXaBsvX0MoYuTHuz9+QfNNFH2Ak9m5SSuF+cmmLD31UoS/sH8Rbu/AkjMudT4s4tmCKG3WborthhiMncOKalZjTzyKJAqRj02Z1tizxsdk6zDWvP3uqnYgbrYOsshG8kAQID/fga1oG5AkeaqqholxgDYqZfAQCRosBraODFXWVcaJmgtli4fWXfzTndV3XicWiBAa7sdkc1DS2FX3NvkM7kF82qIDCWVdOeS+HTle13KhpA9qq7KBFKkanW8g4WutUOTYoH6YtZzG7EJT/pn8whIpIqulcqjdeXrFylukd0Q7DgZNmdkR7jhxkz5/vRowPs+wN19G+6sSSxzIbpKzVpJMKaVVFHOqlqv343E+W9QTffvvtfOYzn6G+vp5TTz110bgfJfQceInw/qeoal1H3eqtiKYSRSMySU7wZtC9HjJrN/D8tt9jC+4j7lkO5xYXxZoPvvci5gdVvhqcN/yGoe5DOKuyotRjtV1qZt4jWuFoFDGlIApgFs3ji9eYHLZ/VA77iKuNNpcDGI04Y6NNHjKoJnsfMgzgKD5w7Q2kMhqmaZp654Pd4aJ22SYsDhf2lfl7RFU5zFQ5ppc+rq5rQnOYEU1WJPX4rD1ZxDGEVIRN9SZSipPkiuJ7n9m8DUZfCzCyWzPQ8ZY41Bz7kIoMY9Z13A3LWHH+u3DUtCI4pgYgJwcPdz18F6aOR9EdNaz6wPdy7iE5axmOpgFQh3tn/AxzzhjRdfZ95wpELUN6xUXUvPWGou+hp4x2AJpoQpIntm356XR70cxuYv5eJDVFo9lC2Fq3qA49hyjHBmVjutrTFw52Yx7WkGQ3axpcCK7ExP0rVM5SyBFNqaAlQ4iSTHq4m5V6YUdUEjSqR54HIDrcA6tOZO933oUgSkhrL2b5GXOTHQ3ipm/IsKNyTxdV7evn5D5HG2U5bl/72tc455xzePjhhzGZTJUa0yJKRPcrT2HZ8wADOx7Au/SXWEcdN03TGY4m0TMJ6qfjFo+2DBAQMPtaENyNENyHI1W8pOpxkWY/TlCJAIrJbKVp2brcN1z1E79H+ufVcevoG0YfNBblZbqJcTmCPHLYylAMVdOJphSqnfnlsAVBwGqSsJpmR09sftuXyv5MLWtOhVU/B5N9wfLxFwNyryJE+pFEAbtZxl7fPvPxY5jsYMWGjJ5r0yDfnNqxrwNzOoSyZBMnLzl55qEGh7DE46QLBDysNju6xYVNT6CSnvZa88EYEUSRjLUaS7wfNdxf1PXHsLnJih5zo5omauYK0un2/gHB34GopdGBiKUR33mfOO7VoY/qOpXHBtHdhaBmCEo+vI7iWzIUKmcByET9iJqOjsFmI9w7znwpppylWORzRN1KH5ImkFF1ui3ttEmFHVFvbRNRi4xZFpH1IEomTSJsZNSVyNwJh3hqm+gDUqKNZOz4DYSW5bgFAgEuv/zyRaftKEMf3g9A2l6P1TGhrvXYd2/EE9lPqn4z9e+7rfAFwpOoXu5mTly3DrP2IpIgQDIM1uLki+eK7/1qQ7mR3wd+9rM5M2KKvY5AJEVKUUkeOsCK+jzO3RwhbGmg03YyJj3NOusktbQ8cthKoAu7nsAuW2n2rZl/OWxdB/8how2A1VO4b5JsBuamIWml8LM5nE+LWGCY1PdzSpBmJkyqH9Oig8y0cmXPKVXJYMqE0QHNVtym000M0SShOqoKHrP5n74HFveMwiCVZIwM7nuW9OB+rO5qqtefP6UdSWvbUuzDYUxVpfVtlNUkSCImuzPvvbPVoYXhvQw98O9YU8PQsgWpgnS6hYqjuk5l26CBAK7RfZVulWnztZVkgwo5XraVZzJkrqV98C9ACjJxo/XEaNuJ6cpZSkIeR9SRiSHoOknMMzqiVpuDFa1NkAqDHCGZimMzSai6jmR1lD++ArDaXdjf9WOaPG58M7BdjmWU5bideuqp7N27t1JjWcRsoOts9QRIyS4iTZumvGU3y0i6ghidvuFnfKQTq64jCiK4GrFVD01E/yN9RTtuUHm+96sNlYj8fujaT5Y1Bi0RRrS68maAJFcdvaEkuq6T6O9iRVl3Kg0nnHQ6NStOJqVomMyT6MB55LDNZLCTRBvt8wTkymHHhmH/n43zlrwOnHUVG2s07GfgJ9djkkTkUz9A06lvqdi15xuLipKvIkQm9SV0Fl/jhsXNnqEUSjpJ3LyPU2coJ8ueUxoC6bP/jURoiOa2iQbT6YyKuUBGfK1XBdEFLdNk92yFnbrJqCRj5PCOv2M++Cc0yUzNxgun3KepuR1iuyE9UlqNcGasbYnRb7KYVg5LTjwTOv4OQiDvZzze1KGP6jqVbYPUid6BLjUIjNYzltmSYeOmLbBpC/RuhMe+iKLpKCPdWFuKm+dFI8sRZSSGKZVCEAQsVidNxfQGdNQajltsCCsZVjeMZouXlBAQmgVWtVbOji9UlOW4ffvb3+aiiy7ilFNO4V3velelxrSIUhDpR0jHDMpXFp+3qXUpdvUAFmt8WiPx0iu7sPeFEFx1bJTN4G6aeDPcC7WlqVBVku/9akMlIr///rGr+N1DD87q/plMhle+eQWS2YZ589tZfcbbp7wvSCYUWzXm5AjWRPFU2krA5zDnj6LlkcOutzqwZOKomkLXSJTWameOHHZXVwexv/4ISRBwXtxG4+rSFvy+ET/PPfsMqWAvrzvjAhqaJhqVh/1DRJKKMTzdQVOhiwDdgTj9/jCyGmfTqmUljWE+sNiA+9WD51/ZhXswguysYalcQsRaEAiJHixaAm2y81cA2XPKJMucuuW08f8/96efkdr9MGY1yZZP/DL/RZKjrW6KdM5mQqUYI1o8CEDG7M29yVhwSEkZm1prgVYG2VASo4M0RJmmo9ONY8yOJ0PjTmcl6XQLDUd1ncq2QZoFn9mGpKWI6iKdFW7JEDbX09UbIqPqCPv3cmJLhTONWY6oqCsIGMKDqjQpaDqdI+qsBf9BiA4amcHxc2yVHeurEGU5bu94xztQFIX3vve9fPjDH6alpQUpS85aEAReeumlsga5iGkwsn/i9+rlU95qa18Ow38HtGmFJIRwDzoQt45GWB11IEjoukIm2FM6kStPml0fCiOoKYLKzGn2VzMqEfn98Fmzc9oAhnqPgKagJiMoQv6//Mb1JyLHBxGaVs36PhVFHjnsepsXIRAgkVaJx6N0IuTIYSfiMZIZQ9HRKpUo6AOowT5aX/pvAIJdLVMcNyEZxG6WUFQdu6e6wBUMdPz2i7gGniHlaIZV95Q8jrnGotP26kEm2EcspZKwVzF9lVouXLWtmCIirtqZM3UzzSlBS+NIGoGhaNiP051lu9QMpEc3i1bvtNdKZ1QC/kGqvD7Mlumf80owRjbW6KiKk2RVS+4NnJOyDdHBoh23HYf7sUUjKEJmvKH3jI6Xe9L9I31gWTn+GY83pw2O8jqVxwa5cUFSRVdU+ivcksHlayCly4hkSI50VehDTEKWI5pIJKgZneeDaUgW4YimLD6UlEIq0Yc3HZ+gT5uslR9vNjJJiA+Du3nB1o6Xg7J2yz6fj+rqalYWUFVbxNxDHT6ABCDK4M0qJndPkhYP9xZ03NynvIPYwCHcvmbjBUnm5bAVPdxDLL2L18xcJz4VOTVHMWz+PZjIgL2VNl/z/NccHUMoN/L79re/nfvuu29W97bFe6h1WUhmVJwt+YmQprM/NduPVh56t0PcDzYvNE9Myrxy2KphJmxmiSpRRc0jh+0QM5hsJjRdx24vPQLqa2glIApYZBFTVvax0ZKksX6UGtLcPO11zKP3llP+kscwHyhnPi3i2EJ4+aX0Dx3GV106nWndO24tepM005yqaVyCcMCMWRYRIn2Q5bilowF0RUUWRSSbt+B19u94msgf/wNRV0m++Yu0r9k849jKZYzY1QhYZVy1uRn8hKWaYChBWtFQD3ewrKa4vVMiHkNLqSQzxQspqa5G4kmFlKKS7txPU5H3OlZxNNepfDZIiNogGcQpq1SZReQyWzJk0kl6/3gnZmcVrtVn4GpYjgkFS3MJlOZikeWI1poFrIqIgIDdZGWoCEd0T8Q2LiYmDHbi1nREEQSTPefYSqJ7229JP/U/pFWNxqvuxeM7/qiTZTlujz32WIWGsYjZ4plnn8GXDGOuX8Oy7MXANclxi/RDQ35p1HWveUPOaxFTDTatB6IzyyjnIJvvrWmG0wa4E93A6Ea2TL738YxyIr8//OEPZ33fqswAVV4bIEABx+1oYf8/fo1l8EU0TxtL3ms4boXksLF6Qc0g6Cr1Yi/DeeSwmx0C1IwWSnuLpCxNgt3hZsOyVoPyZIlMfTMRnPh9hozAmmXLMMe3YZJFSMfBPLeGrVSUM58WcWzhggsumf3JJUS2s+dUx+P/i967HZOnkdaLb6J96Up4ZfQ5SA4AUwN7A4N9jPQZz5w9LFMo9+9wVxHTjTrXmL8PmNlxy8sYGTGoXqFEZmbGSMKoKctH4RScdQyEDWESZaCLYonRWt064tE6zLXLZz54FLqjjoPDcdA10kcO0nRS0acekzha61ReGzS0B1U0oaZToKk0c4iA1VtWS4agf5DA7scAGJEbWP+e/56zbFK2IyrJLiJRg/pfU+MgE9Vm7A1o9zUyph+5b+8rWHoManNdDJoKtxkuGwnJTWy0TCE41HtcOm6LqhDHMJLJJNZoF8mMRsCWp5mnvYahuEp3IM6e/aWJyDjbN6G1vgbXqjNLH1g23zulockOTJJIWrTS6Y+j6TooaRDL53sfrxiL/L52LPIrtaG5GtBsVXRmPByiDbessiX5FPLeCZrIHXfcMfubBo8YP511M1IaUopKSlGnPaaSGAmF8cfS9McMrv3k2r6TltZy0rtvRXjdx6F1K0hmUppAUtHxiz58F/wz/Ruv49nOMN97ogNF1SbqRmCKsElJcI1GO6NZ8t5j9TeyZcbv0VPTiM0sIYuCQe9YYChrPi1iEXmQPacGjuwh3LmTvgPbjRdG6foAhHPFteKhkfHfbe7CVGRfXTMNbittPjstliJlyCczRqodeGwmQokMoUQGj81kUMREaSpjZAyZpFG/BnkDNlabA9XsxixLWNTiZdFPe+e/8Nqr7+CUi64q+hzZZCZlMzateqi76POOVRyNdaqQDfJrNlKhQRRFJaNB1LUsvw0qAZPnvNXlmzunbfQz3Rc/icGmc6lyu7BGOzHpaSQ9gynpp13txGy18X/yVr43vCHvZ2lsX0X1Kf+PlvM+gtPlHX/dbJs7VUkAd00jNpOEx2bCskBZLOWi7MIiVVX5yU9+wu9//3uOHDE2fe3t7bzxjW/k3e9+d07N2yIqB1VJo615E6mh/dQuydOZXhTpSDoxxyIk+jtLuvaGc8sQm8nD964RPRDPIGWUivO9j1vkifyKXUYNWlCqKRj5vfDCC2e+diEER/ny3jyBgLFDYim+9psnEKL9nL/1RE7bND8SzFZRxSyJZMy2GeWwGd7Lvt/eiWlkLxG5iS155LCv9cYZX51mWzDtaoThfVPV+IBEeASTpiNZvcxoXidJqRMbmva7Pxooaz4t4lWDdEblcE830ZE+mptbqW8oTBHOnlNi0ngmVesoJVKSjeBRpM+g+WehdvkmDvNvpCJ+qhoK95uz2p001NYY9XBqsLgPkkelNi/yMEYC/kECQzFMkoA5YyMf4XTz1d9GtHuN2qA5Rtt5H8JqteJtKLVi8djDfK9T09mgvU/8iaq0FVFXQZJQWi9hXZktGZosKeobXGRUHbGxceYTyv1Mk3oDqtvvRxvaD2oK0WSF+rX4Vr5h2t6Azqp6nOf+EwDpnk46LXWoqURuvWqFUd/YSv2YgqUUntN7HS2U5biFQiEuvPBCnn32WVwuF8uWGYn/P//5z/zqV7/iO9/5Do888ghud/Fy8osoHg6nm1Pe9KFpj9GcDUiJflyZobzv7/rLT9Aj/TgaV7Nk66UVGVdevnfc2BjbTQLVJh2xTL73qwI5vWFGcIxGn3WridYCvWF6enpmuHB+JBMxwn2d2EwSZmczhbYtLpPOZT23o+uQPBKDeXLcNjVYwOaGlkaeLUIOW2l5DeZoL/WmOHo6hmx2TKkdfH3NEMvSCqJswSrOknzgakDVdFLhYUzJGKbRHjUv7j+MLRAiGavjNZMOz9ujb0rz4hHyYaxH39EQFZjtfFrEsYXBF/+IMLQLR00r9k2XlxzRT0QCxH9xLSLQd/JV1DdcUfDY7Dm1pU5HtXtIt0xQAaOWOjIDR4h1HiRb5sNX5cN3ymuLG5hj1HGL5beBOchijGjhPpqJoSLgV3x0ChQUZogEBgknjbIAB468jpvomkOeWBYa154280HHCeZ7nZquJUONnAarC7Ms0XbppxGqJ4RhZtuSwZSJYDJJWE2Au5p0RuWlPXuJDh5hydJlLF1WXgB8OkfUPhoMnSyMJkly0Y5oU3MbTc3zFJA0O8BkN5QsFyCDpRIoa8f82c9+lueff55vfOMbXHPNNeONuDOZDN///ve5/vrr+exnP8s3vvGNigx2EaXjpIs/gAkNwZ0/QhPa/yS20EH6Bw5XxHHLx/fW+l9GlSyIahpB12gRDjNsrSqL7/2qQHbkV5pQeZS0SQ1csyK/gUBgVrcb6DpAIGjQB21qDYXMgGS24qmqw6qEEa3F033KhjLay0i2FiWHvfk158CyRvC0jn93k+WwY8/8hX0DURQTnDLLIe2N2UmMcff7Omlaami+iSnjNX2SalzBHn1WL4f9STKZDPF9Bzhx1QVTP/Ykg8pZRajJVRiznU+LOLZw6OWnsPY8TcZSxZbNbyv5fLfXhyaaELUMmVD/tMdOmVO6jpAIIosCsnfCqdkVdWAeiaMLnTQpCqI8y+2Ko9YQdSrWcctijLSpw0ijPqxLtjESdxZkjKiCiZB7NWIqRF1VZfpVZVJx/HufxmS142hcgcVVM/NJr0LM9zo1nQ1a6VbA4YLVFxs9Qidh1i0ZJtdNW9xo6SSmh2+kChhJXF6241ZMb8BsLNjegM4645mPFvnMH2Moy3F74IEH+MhHPsJHPvKRKa+bTCY+/OEPs3v3bu6///5Fx22WyBudLwKTo/Pmumkk23Ude7IfHRA8ubSWzl1PE+47iMlZxeqtFxd133xpdv/DX8Ae60PAeNBTnlZ8r/vwtGn2RZBbK5jUcEkWzHqapJou2BvmjDPOyHu5meZTqL9j/PfqpglhknzZniVLlsHQnvHmrvMCJW38HHVkZzQQvmXGvyyMyWH/+fkaUuZlyNbZc+7tNa2MVcqFhyYcN/nSOxgJBqhxTCyxBXv0iSJDigNTeoRkYOqGNzsKurnVO+uxzhaF5tMijjNEjLmnOGbncAiiyPL2diyJAeSa6Wtfp8ypZBBGBUSwTTzTFl+LYZt0lcBwL9UNs4vYD+tu1HCSZOgIbZqGMEN2fQpjROxHMkYBgMekoFrkgsIMS1efyNLVX59xTLqmEQr5sdkdWCzT07RHBnvp/8OXADCfcQPrTrtoxuvnvaeuIxyH0uhjOBrrVF4blEkagVQo2O5hVi0ZkkHjp8UFkozVJpOxVGFOBZAisxCRy0JRvQHzYDpHdMe2xxk+8ByimuKs995c9hiLhWKrRhk8SGKolwq3Jl8QKMtxGxkZYfXqwl7+mjVr8PuPz+LAuUbB6PwowiE/nY9+F2fTGhrWvQ6rx4hUlhSdT4U5sc6EonlIrV2X83bvY/dgjRwh6lsDMzhu06XZD/3tQTyqHVFX0QSJoPM0XlMm3/tVgTy1gtV2DySDCIrCwQK1gt/61re48847p1xqpvkEsOF1byK8dgvD3QeobjQ2SQXnk6vBcNyiMzfbrRS0TAIBHUGuTB+YNWe/i+HoWw266SxR29iGWF2F5G7C4XONv37ykhpgamR8uh59JncNvmAvYuoADLxSsEff0Xg+8s2nRRx/ONGbJG12EG8rXrkwG57aZugbnpGiNGVOxSftEewTQiPLNryGuNeJt6EdS81UyfO9v7oVMRXG3LKJ9jPePf56vuBUV9qBEDKy9VXhAG5vrpjJWHBqc6t3CmOkLfJXyKRQBRlRFJG0MC61k2GrfdaMka4DOxl84GYkLY3jws+xctPrpj0+k5xgNciW0hRnVUVh249uRoz0Iq88h5Mv/kBJ5x9LWDDr1JiDBeOOWzytIAoCVtPsNR92HjyCczgGnokeiyesWYt15BVEb3zac4tFof3i3l98FkmScaw4ncZNF+S8X8gRTfXuxNf1JwD2/yqD7Gli6XnXVGSs0+GFYRlzfwRNTOEtIlhzrKEsx23FihU8+OCDORm3MTz44IMsXz57I/BqRsHo/Ch6DryMcuAxggceA1cDSzy100bnU4pKRtFwWicVRIcMTrgsCsi1eaKZ7kaIHEGOz7w5ny7NvtqtkDFX0zNKw5OTRpZmwabZFwjy94axz9gbJp/xmmk+gREx99Q2G5svZsj2jDWSTYYgkwDTLMU9ioSuaew4MoQAqJ4ExSpbZ1SN/lCSaEphbePUWttWn51WX3nS+1a7i+arf1708YV69G2yDoBdAaUTHry+YI++o4EFsRlaxNwiFcGmJ7HZTHialxR1yrT1mtPQEhVV410f/9z4//cfPkK6N4xZEvBpDsbcKld1M67q/AInoa5dmFN+RnQnY9IkhYJT1qpGUhh2LhHoy3Hcxta5bR0jNHlt9IeS44wR8TE77PgZYiYOug66htB8Mr41b5w1Y8TlqWFEMzIycf/MdVnVFg1XjR1NA8nnLeoeY5BkGTl0GFM6RMJfmkDZsYaFsk4lIiOQUTGJAvGMwKN3/Ru2eC9NW9/CiafPzFwqhFhwGDWRIWm3jjtu9po28O8yBHx0fU6UJjVVJXHkedB1guYGGjcVf66tqhHJJJLKaMQOPEnK0Vxxxy3fOmTx1KMDopYmHA7i8ebuK49m3Xi5KMtx+8hHPsJHP/pRLr74Ym644QZWrTJoeXv37uXrX/86f/7zn/nmN79ZkYG+2jBddB5VgY7HsKsRdEGioX1V4YwX8Oe7Pok12oWp/VRe87abJm4yWa3LnWsg165ag1XbhVnSjPT/NLLmBdPs6RhekwImC/a15yGd+Has7ok6hlnzvY9z5KsVTHc+h6akQRCwyQJtQgfDVk9O5PfSSy/loYcemnK9GedTVuHxTNmehLWWZDxNWtEQ+zupbZ1bZdBUOsWIXI9JT2M3Fy929Pvf/wb10BN45RRrP/rtORzhJGgqCGJBI1pOj76jgXzzaRHHGSKTKLqumRXrCmbwxxRS09G8AZ2xde3bv/wj9/zzFWxZ4iMRHERTNTIq1BVRv6VrGlYljAaIk3qlFQpOLV97Mnrzf2Px1Of0VpvstGk69AYTnLq0euIzVS+Dhg2QjoGmgCjD6z+B1LgxL2Mk3vUSFlnC4m0w6mzywFNdR43bjkXSkS0z9zC1CxnsttH65lkIvVmq23CH9lAtHt/sp4WyTh3p6SPZb/QYrJGqWBbeBrpGamB/WdeN1m4mKNdgr5mkoupuMn6qaSNz7SjcGmPW940EEXQdHZDt3oLH5XOg1q9cDj1uDgxFiSYVtDwB3nIcqELrUMPG8+iq34inphH7pFYEk+95NOvGy0XZjtvg4CBf/OIXeeSRR6a8ZzKZuOWWW/jwhz9c1gBfzSgUnZf2/5G1R55EJ4IqWBAf+RR/mSY679ZCWNQgieDU6J4S6jYmgGQCe67B9NS3w4HR60T6wDe9pHDeyT8p8upoPwk8ucZsVnzv4xiFagUjj9yOLdOJoOukNZGMawm+067OifwWMl7TzScCHaBmQDIXle0JSz76RpvSSt2H59xxE2ULyfO/REhR2dBcfLPsFimAnNoFKYhHQ9idk87t3wkIxmbT1VDwGqWif9f/of/jq2D14n3jv2ObbGhHMdajzz/Wo8/VRpvLqLXr9McNUQR5yGjmuvcho83BUcJC2AwtYo4RmdQrzTVzjVshJ6lPcZMYipFRNbx9XdS3TdRYT17XPvK2N4xn8C3N6+kMvQMtNsJGz8yOm5CJsbHJiabrKKsmbFKh4JTZ4QGrwwhODe/PG5xq8tpynbax70UQjTVCSaFoOsmhTpyNG/MyRrTffxNLtJtU3Ylsff+X849flGhpaTeurQVn/LxkJvWbnAWzYePatbC/C6TAnGVlFgIWyjqVikzUfbt89SRrW3GmBjCby6sHP+/yf8p9cdRx09FRgt2Y5sBxc+tRNrZ6UFUddWn+OtOCgZzR4MWyGgeqpqPWTw0KletAFVqH6uvrqa/Pv44thLrxclG2DvvnP/95PvrRj/Loo49O6eN23nnnUVOzqH5ULvJH52MImTiCKCKZTERmiM5XN7ThFAYxOaZG9559cSeuQAjRt4R1+TjAkyOvRThueTFZ3twxfzLIxyqmqxUM732J5JEniCdTaIJEyHMWW/PUCj71g1v50b0/zHv9QtmeFCbUyCCCKKEMdbKS6bM9VfWt9AM6kAnlNsitNMyyyCUbS+9d07Z0FXKv3WhxEOuDSY5bx+9ux5wOoi49i7aLPjHrsXUNBdm9fx/xkR7ecP4bGBjsRw8lIJTAhoW8W608PfrU4RiqphNLKVQV6NF3NPC+972Pe++996jcexHzg1379mEbjmE1iTQ462fsPVjISUpbfYQTaax6gtS+v4IlkzeD/9QPbuXDZ/0QgNVr1rN6zfq899n++G+J7v4LkhLntR/9vvHiaHN7URAwO6du9KYPTh02VHpFU97g1FiN2+T1bs++vTjTcaTWExg+9CJqKkbK9DJbN75xyv3GGCPPj6vJeqf/Ap31hk2NDs7wTTOhpgswm/pez2gzhTnMyiwELJR1qmnTeXTXrCIZ8eNwV+NZuRY6Q6BUXuEwbq2nqz9CSlHRdu9iU3Oefr7lIhVGQECWBGRnfqmPgqUYowkBURAQJQGTfUIIrBIOVKWZRMcKKrITqKmp4Z3vfGclLrWIPMiOznc7GmmRjMV8EB99OKeNzq9YvhKSLwPh0ayKUecmRnuNCKKpgEM1yXHTw70zNxLOgyOdhzEFE5hlEa/VhwzoaoZUPIrVdTzq/ZSH6WoFl3lEaKhj/2CEZEpFiBoOU/bi9b6bPj/tPfJle7xaEAEJVdHptrTQIgWnzfaY7W5WtjViMclIrcVnwOYbdS0rwDFKM4p0Q/2a8ff8wRCSmiIVg3I6zEQOPEXdE/9tXHP9WvREEAHQBQGnp0AEMatHnzYYxBLYh4kMFlsjrb7WvD36jgYWSu3IIuYO4aEu0okMw1oVjTM1nh5FPifp3dbnqVIOYtLTSDvugo5f5nWS3rHxq0XdQ40O4wrtBSAZj2C1uyAxKXORR7VvOiqyJplBTeWlImdH+1VFIRnoJalrpNUqVFsjttQB9MCRnPttWeIDTWWpSyOjWkk2zBBkco7a3OjAjFmwIwMjyMEEkiBQJ1kpeZs5RqcDCHcft47bQlmnan1V1Pom7W08rcDThmBPhevBbe4aYpqMqKsk/d0Vu+4UjAZKgGlVMvM6ULIZzeJGDXShqQqWRBBUpaIO1IzBGjVdNJPoWEFZjtujjz7KX//6V77whS/kff+zn/0s5557Luecc045t1lEVnQ+Ex0hMSqf7JdkvDNF58cdMN0wFJ4WdE3DtPYikiNdOFryRzsxWdkfNaNEhgnrL7N1w+UlD32wvxtTJIUuSFTbq3j23s9gHtxBono9r/lAfirJqxnTSvKmDN58U3Mb6hk3466daEs7OfL72C/v5tyN/1z4JnmyPTYtihVQkXA7HHh91TNme+xv++5Ej7m5RiZhRKdNNqNORTLNfA4YkW3JZAQsQhOGTdc0rEIaTRSQzeUZUldtKyOAWRJRgr1sqhXQWjwoJheyyZz/pKwefYIkYyGNgI6oTKJGZfXoOxq4++67+ed/nmY+LeKYR7RmM30JGZu9tNYY2U5SUtlGjd2KYG8C2VqwXrPYOeWtb0M4IGORRZRgD9jXoCcCE0FEW/7gX3ZwqgsZZ6wXBJmwe0VRVORYPMpw1SakWD++mnbMLhd6sIGqxjV57ggkQ/gcJsAEzflFVcYQknxkoilSSgJPJIjTXTiIOegPYoqkQBColwusJ9NAdzeTyqgkFY1k9yEaGucgK7MAsGDXKU/rxO+hbqhZWfIlEv5eUkeeweauwdKyyWgJgCEoZqtpw5r24/M5p7/IbDHFcStcY1nIgQrsfwZbarQXYmIQLdRdcQcqX7DGm+pF03RUkwOrt25B1Y2Xi7Ict1tvvZW2tsKx6p6eHm677bZZO26pVIpbbrmFH//4xwQCATZu3Mhtt93G+eefP+O5PT093HjjjfzpT39C0zTOPvts7rzzTpYty+3rdPfdd/OVr3yFjo4OWltbuf766/nYxz427fXPP/98Hn30Ua677rq5F2DJis73RHpIZFRDpMLlMnp5TRedn0J57AdPC4IoctKFV858a8GHTRlED8+ODqdnkiAIZKw+BFFEQcSkqYjhrlld79WAgjzvtCEL7WjdBPW5z91Y5Dd+6qnT3yBrPukjccRRuWyT1UFb9QzzafyG8+S0AYHOV1D/chuiIGC5+FYczQWCDdkQRUN4J3B4iuMmaBlOGFOZXF46BXMymlqW0NziMb4zcxjCwbw0rinI7tGXUHGbbFj0JIqWLNij72jg1Jnm0yKOeZz3hsuAy9B1veRzczP4S2as1xybU7qm0fWHO7A4q3Atfw32rCDiiuWrYN/o3E8NAWt4cf8RTD0hZElkiewiL3kwKzilBbtBS6MLCsF4ZuZgJ+B2eznvmv9C13U0HSRxBs7JZBl4m3f813yiDf2am0TACNCoA115Hbcx0QZdEMlIdnRBnJ2sudXLrqE0opoidWgfDVtKv8SxgIW6TimuJqLxNMmMRurQXtpn4bgd3r+T1GN3AVD/zq/T2D5RU772PV81AnxzhBf2HcbaF0aWTawyT2+H8jlQrowfDR1FF0lmFNJz5EBlr0NDmguHHkNTYTDjWVB14+WirG9s586dbN26teD7W7ZsYceOHbO+/lVXXcVXv/pV3v3ud/O1r30NSZK4+OKL+cc//jHtedFolLPPPpvHH3+cm2++mX//939n+/btnHnmmYyMjEw59rvf/S5XX301J5xwAt/4xjc47bTTuP766/nSl75U8Pq//vWveeqpp2b9uUpGVnReGpUSTutm9MkERtlsHJcVndddDQTjafrDSTo6DpR0a2vjGrSa1dga185q6Ke+49Ns/MRDrH2vQY2palpBtdPMMnsCPV2Z3iOvBuiaRjgUIJ5WSErTS9gnEolp38+eTwAm3ZhTijTJABSYT3nHN4sNXykYDATpDiSMjWCqtF44PXoNnf44u3a/MvHilIL/8loCSFYn4hiFJNI/QeUqQCsBJnr0BYcIxtJ47SZ8Xi8Oi4xTyhCMZ+gciaEnAkZtac3cir9Mhxnn0yKOG8yqQfMkJynjaiWYUDgyEufISHzCSWpajpAMGE6SqozPqVg0hP/lR+l7+pfs2fVi7rVdjYw1vx4TUFGifhRNJ66KWGwFNpKTg1PVDswWC4IAIhpeq2AERURpanBqmu9kRqcNsiicXmBCtOF7T3SgqNrEx6o22BKiAKlAblB0rP7nrscOImx8O1s++QBbPnH/zGPIN35RJO0w6JJaaOb2AzPh2cP+KZ+lWCiqxrOH507ZcqGsU3t/fAMH7r2Ozid+CoDoaqQjkKI/nGSgq7T91xhSkYnvzZEt4DOHThtAOhogrWiENFtRwjZjDtRrRx2oYVMjGcGMKsgMqk4O0YZbVtmSfAp5bwUFZbLWoaRuQtN1dDVVcB06VlFWxi2VSpFOp6d9Px6f3eZ827Zt/PznP+f222/nk5/8JABXXnkl69ev51Of+hRPPvlkwXO//e1vs3//frZt28aWLUZ46aKLLmL9+vXccccd49TORCLBZz/7WS655BLuv99YFK+55ho0TePWW2/l2muvpapqaiQsmUxy00038elPf5pbbrllVp+tZGRF59OCA81kQhdkQonMjNF5wermUAhEJUmyu2O8B0gx2PzG8lVBRdmEq8pQF1qz+gQYGlUgDXVD7appzlzEGFKpBIcGggBo9arRx0zXUZJRZJtryrEHDx6c/mJZ8ykaT1IvAYj4MxLRIrM9B4ei3PfUPpL+Xq5+w2tobZg7MaJMasIom62lURv7hRqkWBrwE48EsLuqsgr+K5A5dDVAKgzR/onIewEaFxTo0ZewQxzsJoFqk4aYp0ff0cCM82kRr27kyeAH4ylkNYWnACNkbE6FRyZ6hNo8eWqtZbNRkxUbhrDhdDhWvJZB0YmgpgtnoLKCU6LJhpgyNp0mLTX1+hWiIvf0DyCHk8iSgMvswUxh0Ya65iU43vEl3DXNCPapNWeFRBtm5VSPoum170BCxddUXl/dguqBM2A+5NcXyjoVGziIqKZJO5bTBoiyTNreiCXajRydneO8xKGg+exkNHBNQ6udC1iWvIaANA3tPxtZ2e5QPI0mZUDXiKgmvO45Et7KWoeG0jbEeBDQqbIKtM7ETDuGUFbGbf369TzwwAN539N1nV//+tesW7duVte+//77kSSJa6+9dvw1q9XKBz/4QZ566im6ugpT7e6//362bNky7rQBrFmzhnPPPZf77rtv/LW//e1vjIyM5DQQv+6664jFYvz+97/PufaXv/xlNE0bdybnBVnRebOnnqYlq2luX47XbioqOp9xGHLnY8209zz2C/b9+R7698xj5hDAO4niFzq+G4JWEoloePx32ebmuZ98jpe++maeve+/co697LLLpr9Y1nzymDVkScAii1istrzzKV+U1Ro6yEW7/4W3DHyDSPfOvLeqVJR1dbWZdU1u1jS4qHK7Zj5hEpx1SzBJAk6rTHLYmHN6JoHRmYbKFIu7GtDRSQd62HHgCLv7wuwO5F9exzYx98VPYrDpXKrcLsQx9Ss1jaAkackcxmy18X/yVr43vGFWEe5KYcb5tIhjGpEjO4g8fS/a/r+Ckpr5hGxkZ/ATAVqT+2jKHAZlUmB3UgZ/bE7VyTFW17tYVuOguakl59IAKVs90ZTCQE8HAOs2buGsyz7ImW+dJqiYFZzyp2VMkohJEkknonT642i6boxPzB+cCux+nHTnsxCdUAPcu+MZnv7d3Tz/p5/mHN8/0EtfKEmXPzGebZ+oPTact7HMm2y24mldjxAbhO5nYeAVQ7Rhmn6s5aDtxLNpPvE8bLWzUIaehMmOaHYWsRDmS359IaxT6WQCCxkEQHZMOFhrXv9W1l38EU56w/tndV2vEMPnMFNfV58TrFBUjd2dgzz17DYOHzlcxujzY/Nrz+Psd3yc1/+/IoP4Wdlut92CX67Hb2rE7qoqKdtdErLWIUWaIFGb1Ky68SKZRAsVZbm5H/vYx7jyyit529vexi233MLatQadbteuXfzHf/wHTz31FPfcc8+srr19+3ZWrVqFO6vh5BiP+cUXX6S1tTXnPE3T2LFjBx/4wAdy3jv11FP505/+RCQSweVysX37dgBOOeWUKcedfPLJiKLI9u3bec973jP+emdnJ1/84he55557sNlK2+wNDg4yNDRVDvbAgeLS5vmi8+Jo9K3NZwc9hmmG6Pyac6/EKmlYqo2eUsGX/4g11ou/ayMNa04r6bMUCy2TQlCTCBb3RIp9slhEcLHOrVg4XB58F32WVDxM9ZIN7O3YhqykkPI4v7feeit33XVXwWtlzyfZ5CERNcRuqqqdpOPClPn0Qlc4b5S1qraZpFXGLIvIWm6PmkpGWU16GiQRJKBEMZFVazYiiO8xZLEbjPnfOTBCsDuEKAi4wxq5ndZKwysRO1pPCFUzCrlTgC7nOpiFevSx9w/gP0Q6qKHpOnF7A76zP57To+9oFFTPNJ8WcWxj70tPIu9+AFGAdTf8tvRNQZaTFFdFPKNBkVQiQqffkpPBv/XfjDklJwPIZgkbEvjy91J8MeTAMhhFFw9Rp2nF1XmNBacOPkkQG16HDVvaCloGj56mM54BPUa7GkBo25o32Hngke9gSgVQ2k7nlCsMdo3/ufuxDe0gba+HC9415fh0WkUSLEiSiNkysWksp0WBLIkGBVOUQbYdtZYghT4LLBz59enWqXx1hsWg1ObQZiXCCU0edF1HXTERpPZsvLik++ZgjMWRh36vqxlSP78Sm64ztOYylrQf5d7JeUox8qLSwltZ61AkJVM1+vfOJKJ0+l0Lpm68XJT1BL3nPe/h3/7t33jggQfYtGkTNpsNm83G5s2b+c1vfsO//uu/8r73vW9W1+7r66OxMVc0YOy13t7evOf5/X5SqVRR5/b19SFJEnV1U5tCm81mqqurc+5x0003sXnz5lm1Pvj2t7/N+vXrp/wbixD94x//4PHHH+f222/H7/ePf2eXXnopiqrx5k9/nR8MreZF1iBoKpmeHfTtewE1OsThHU/SrnYSicX5P3krb/tZLy++tIOf/vSn/PSnP2Xnzp3cfPPNeFaexuUf/yJ4Wnj729+GJT5ALBbDnzHzwAMPcM8993DgwAFuvPHG8XuD0Rvl0MvP8q3bbuLhX3yPP/7xj3zrW9+ip6eHD33oQ1OO/dCHPkRPTw/f+ta3+OMf/8jDv/4JT/3XJbx0x6XccO27jWPf/GYilgZeeGUfO196lnvuuYcHHniAbdu2ceuttxKPx3n7298+5bo333wzO3fuzPlMk495+9vfTjwe59Zbb2Xbtm0zfia/38/tt9/O448/XtJnKvR3Arjxxhs5cODAnHymF3e8zPMHR3hi1yD+aIbn93RRZTeR6dyOnklM+UxXXHFFwc+kqBoXf+IOfuRfx/PqKiR0pOBBJDWJpGcYOPjylPl02Y+O4EgOw/BBHnp6F7f89O/8+38Yn+mqaz7M8sZq+va/TKMYmvKZfvy/P+XWXz7Fj//4JKcs8fHvH7uqrL/Trp3bGRwcpOPwYXoGR0r6O131kU/A5vdw6cfvAJuXG2+8kc6uTkJxhXgiyf5DnWX/nRSLj3AkRiaT4a/yGfyOswhaWqZ8JkXVOP9jX+LJ/QPEO3eyWu/i0b/8lW893k/PqZ/jP16qY7/rFHYmathj3cR1336Ui1Y6yPTt4eFn93DzvX/hS1+e/7n3gQ984Lh7no7HNWK2nyk60EEkEiZlruItb31byZ/ppi/+D2G5Gv9ADwP+CJJkQtIVXFYZKTZMMJ7hyZf2oCcCvNgZYmd/mjPOOIOf/vSndO17id179gACb37n+/J+po7BCIlEAi2T5FOf/HhRn+lIbz9ffEbDrzlxh/fRVmWlPxAllVEgHsSkphADHXSENEJNr+d9H/jg1M904/WI8WESiQQHBxPjfyfd00IoFMKVGeayN10y5e/UEXexp+mdJF/32Zy/07uueCfvPqWeyMHn8G77Cj0P3kZk919IxiMc6upFU9P0b3+ElQfv4bWv3Mpb1zm586t38Pjjj/PX/76GZ/7rYp78wWcWxNx7y2Vv5prXL2Xv//2BZw4O8a7Pf5d9D3yRrm9cwuDdV5B84HoOf+PNaA/8E5+//gpe6Bji0LZHeet67/hnmovn6cILL8z7mc55xzXc9dhBLv/X7+TdGxV6np56+hluuOshbv7xYzzwjx1FPU//e/e3SCST7Ny5E9leVbG/09OP/wlVVfnl7/6c83fas3cfwykTyWSSUPeeo77uhZIqBzo60ZQkT760l1AiQyrixy7r9PvDvHJkAH8gQF/3EVQkbvrs54uee9N9ph/87knCcjVDvZ0EY2lC/iFsNjuZZAyHkKJ3OMieziHi/l72DmfoSTun/UwzaWkcTQh6BVQFDh48yAMPPMChQ4cAWL58OZdddhnLl8+eT718+XJWr17Nww8/POX1Q4cOsXz5cu68805uuOGGnPO6urpoa2vjS1/6Ep/61KemvHfPPffwwQ9+kO3bt7Np0yY++MEP8rOf/SxvHV5bWxsnnXQSv/nNbwCDVnnuuefyzDPPjFMwBUEoWlWyUMbtsssu4+WXX+aEE3K5tjm0idNb0XbcR+qZH2JO+5FNFiSzHXxLUVe+ge+NRudnjGxF+tEevJ6UopE++Wo8698w7dif+cb7sMT7SdSeyGklSPjv/PtvUZ/6NgAt7/0fapqMvMbTP70Va9c/UGQHJ994/+yUsl7t6HwG/jHaC+mC26ZIDF966aU89FBu0W+++STvfQjl5d+iDu1DzySxuqrzzqf3v7adHzx5JDdy+vubYHA3VC2F0z4yd1HW7T+B3Q8ZkbJ3/KS8awG9wQRPHhwhlclw0fomfM7i69zyRW+Hjuwm9btPIThqcJ99I672jTnnPX1wmNv/tI/z1tYX/E62/fw/cfX+A6vdxdJ/+gUIwpS/24fOWj4n9SHTodB8WsTxgdAD/0xmaD9R7xqWvP2LJZ+vqBp/u/8uVh68B7es4m1ajji8DzJxdLOTI0IzpnAXZqsN3wX/jLTx8ok59fR34NBjRj3oW/JnS/y9B4kcfAZXXSuu1o10/+V/MLmq8Cx/La7W3FKMseflhY4hrhEeYEvyKYRkgFhKRU8GEdGxOqsY0V38n7yV/o3XcfWZK6c8j+mhDmK//QSpjIZy2kdp2WQoWSf2/x3ztm8iCQJc+AWoLm2Po770S/x//grpVAJFsuNS/YhqmqB3HcG4Qps4RJXbhfC6j4+r3m377yswp/wkWl7Hae/+XEn3m4xn7vsyWuAIppaTOOWSD876OmNQVI3vP76fxh3f5LWTeuUhW4w2EMEh/JqTwaZzOendtxZfIzVLFG33irBHs6asdj0LT3zF+D3P/NB1nbSqYZFLE9g6cveVWDMhWHYW9RfcmPN+8OFbsY/swORrR7jkKyVdezqkEzH6//EjzE4v7mVbsdfnqrLnQFXQfn0t0YNPcog2vA6zwQxjVGU2nsFrk2lXO41s92V3VSSTnG8divQdhIQfTZQJudfkrEPT4ZVXXmH9+vUF9+dHExXJuy9fvrziNV82m41UKpdvn0wmx98vdB5Q1Lk2m62guEoymRw/TlEUrr/+et773vdOqZsrBXV1dTmZvelQaOHo8W1hKPwjrLoD29q30b7pXKhZjSTJXK1q6GPUNMi72Oi6jhbsQRIEbCYJW92SGceiu5oh3o8YLa0lQJ0URnVZSKsanpoJGoy5eil0/QOzGiMWCRZuUryIwphcKxg4MsVxK8l4rX8r8to3I2dRXPLNp/e/1nC8p9B9Op8yRGYGd8PQnjlrcrnzyCDWwQiYXZQupmwgnMwwEEqyst5Fk9fG5Sfnr6mZDoWK82tbV8E/3V+QHmJQbkKg62xuK0zZ2XL+FQjpN0LVknF68eQeffPttEH++bSI4wcedQScFmqWlB5oHXeS4idxTdMRQ2p7eK9Bm1PTCHE/7VaFYavDcJKGN3C1qo3PqZcPHMLhjyFUN7CkwD18TcvHRTX8gz2Edj1q/E4VG7Mct+moyGL3DvRkEF0QSFatwnfKewpSkc3xfsz2UUejbeJ7sdUtm6D9h7pKc9yyRBtS4SFcShINiMQSeJ2OvKINTU7AZCZVNY1KbTEYeAVbvJ+EqTIUsdw2EG0ztoGYSxRap+aT3qklghM0tlFl0TH85n+/Bf5D+NpO4Iw355byFIKuafhHhhB0jUzcRH2eY7z1bRB82VBe1TSjDU4FEPQP4n/hNwAMa07WF+G4VaK0p1QUWodMaGh6BpOapiXdQcDqmrIOHau93I4uYXoaNDY20tOTq8DT12c4D01NTXnP8/l8WCyW8eOmO7exsRFVVRkcHJziVKXTaUZGRsaP+9GPfsTevXv57ne/y+HDh6dcMxKJcPjwYerq6rDby5MVn4ztXcG8C0ciGgBBICnYsbZsnaKKM7ZAdQfibOsYmbLRU1WVv/zg80ixfla60rSNUfDdE99jIT738uUrset7MZvSxkJX5INWL0bAazMWMPPEhnbFKeeRWr2Z6qZliGU2P361YM9TDxPd/wSixcWmt34K0VkP0ihHPHhkyrEf+tCHcrj+heYTYPw986grZRu8U5ZU5fRoqVYH0VUNTQApk5qzJpexWBQ1pZKeJbv7iWeepeOZh6hWB2n84BdwumfnABVSiUOUjH95MHkzed66Bk5pL6wKJlTnN4xjPfrmAjPVf+SbT1B6/cciFiBSkfH+kLjy15gVwrT1mr0vQjoKgoDQeCK+dW+Z4iRt//lX+J+7vkMsMIiSyJDI2As6bpMRC06wVizuqSq20wWnWPtmxK7niXU8i6f1BKSlrwPJVDjYGZm0f5jcB9XZYNSbaYoRMBuDrkN0wLB1pryd5XJU77rSUTC+IrxmjeZ8qnd162hxAHY7NOVR3SwBclULDnUIjzAy88HFIMsRDSYU9BGDvRRKFNcrr5IotE5BBeoMi8QL+w5j7g5ikkRWW9xTrFVjaDuWeBeJwdKEpuKJOEOWdsyZCB5XPrcNo1cpGPMyNgSFjisRsdDw+O/W6fqSjqJgIMdaBbIZUUnTrgYYttor5kBNtw7JA3tICWawOhEaVuFbddGCqBsvFwvWcdu0aRN/+9vfCIfDUwRKnnnmmfH380EURTZs2MBzzz2X894zzzzDsmXLcLlcU67x3HPPcfHFE8Wjzz33HJqmjb/f2dlJJpPh9NNPz7nmj370I370ox/xwAMPVFTVaMsSH5xFzoaqzaGiNrhQVB25Nnch394VpDeYoMlrm6LeJEkSVZG9mNIhdNEMVjtYXGA1vtvphCRqm5dC1+hUiQ1OcfamRXz0oXdMNbDu6gaoLm2T8GpHpG8/pr4X0EQTomz8LeL2JlID+wgf2kP7pETw5z6XS6cpNJ9mQr5sz+Qoa7dUh0ftB8CfshGibU6irIH172O/9xI8Zp3ZtFmtM8VxJYy1Y7j7IM5VRmQYyVxUb5oxzBS9Hfnr1xD6XkRyN+C59L/mtTh/NihG3jvffJoPee9FzAMi/RO/u3LrwgthJicpsefPRP/8ReIKJFvfweqNb5riJK26+BoUVSNUcxJauBdnzZqi7ttoTVPX6CKj6giNU23ITMEpy5KtWJZM7TubLzi1ZYlvwnGzVU1VnZVk8LSg+ztIDR8eb/6diEU4eNdVyJKIePKVrDozTx18tmiDyTbeH86iF2hRoBoy6sbxBRzCInHy+vWw6wAwel3JVNb18rWBsIUPYdbTSO7ltMyz/Hq+dWoy8jWHzqF3lhl4VGMBNB1i2BDlqd+vu34pLn0AsyVXyGs6OBxOLvj4XaQVbUIJORuT92Thnoo5bk3WNPX1TjKqjtww/Z5teuGtDmNOSyaEtq34Vr6hIg7UTOuQeXgv5knZVIpkpi10LFjH7fLLL+crX/kK//M//zNOw0ylUvzgBz9g69at44qSnZ2dxONx1qxZM+Xcz3zmMzz33HPjipF79+7lr3/96xRK5znnnIPP5+M73/nOFMftO9/5Dna7nUsuMYqP3/nOd+Z1FN/ylrdw8cUXc80110zbiHy2yLcZMisxMElgAly5kfvNrV5OXVo9Ltc7eVI6alpwhROMRNMkMypifTMrmTr5GzxWNjRNVfKcYtDDvXkdt7zR91h+x20RpcOqJ5AkcQrNZWfMi2UkjhLaT9sktbXf/OY3XHfddTnXyDefhvsO0/Orf0V31lF3+pU0rdyUc8yUbE9WlDUeDeLUDGOSiMfxuqvmJMp60YntXHTi7LUfG1tXkvRascoSZoYZfPInmPb9DlG24Lnq5yVdq1D0NrXrdwgH/oFVi6OJJjTFP6vora7rDIRTBCJR1rbM7bNTMIM4Cdnzab7kvRcx9zhy+CBSII5FlnBZaynWNZjJSTKtOpfu338DQVdJ9xnqyZOfm/sfe4FzNi7hgis+XtT9dj71CIG9T9Iceo7ltU4sMpCVcatkcOrAwf04o0lku4/sJ3Bn1I3eEyI9sJNTLjRei4RGUDQdRVORZUf+G2Wp3gWTOj6TBUnLEE9G8vdjVSbLmJfJTvGMZmXQDYfdm6vKXRKyHFFZS2HTjOytK9kLjFI7K60eWACF7N5kzDW907H2PIadrYjkZtXWrlkHqR1AYoKaWQLMcuE5nXY00j0UJalopF7Zxebmk0q6diFYlCiYR+13nv3mGGZyoLLpqMWW9syESjGJjrXA44J13LZu3crb3vY2/uVf/oXBwUFWrFjBvffey+HDh7n77rvHj7vyyit5/PHHmayx8pGPfITvfe97XHLJJXzyk5/EZDLx1a9+lfr6em666abx42w2G7feeivXXXcdb3vb27jwwgt54okn+MlPfsJ//ud/4vMZf8w1a9ZMcQwnY+nSpfPbPyQ10c8Lc67c+HQZgXUrVqDv2U06EiWTEvGL1TlOW28wwQ+ePDL1IZgSzclV88wXfdc1jaGBHiyijiR7KbREKYlITgPpReRiQ40EKfcUY2utXYp+5DFMSoLQSD/eWuPvVIooUGCgCz02BLEhUpnMzCdk0320DKIiIABVVoH6Bdrk0l3TiLvKY/SpivXwUr/fcHplkVNmPj0H+aK3rvQAVi2FNkqQmW309tHf/hjTgUdwCEn0G385p+I9xdR/nFynGH2m5lneexFzj6Hew8jRNAgC60qI0s/kJMkmMxlPO95EJ3ZxwvkYm29q/76Cm6V81N3kUAfugaeJApquj64xU2u+xnqKFTMfU+k0kiAgm0zj50weT3Cgk6iSJOlx5ThuGVcrog5yJkI4OILbW40pHaTGaSaj6piqClAac1oUmHEKHkgE0DIpBvK0KIiH+knH04iCgKiZCtrRojBGpwPDjpfruGU5oqlEHJ8kICCQTkXzO6JziKLs3hzTO9dvPAk2FnCaPJO+71A31BWXZS4GJruHgGJCUhKk/BVss5QMjf6S+7xNxtFyoEoK1qTjRvZcEI563Xi5WLCOGxg0xM997nP8+Mc/JhAIsHHjRn73u99xxhlnTHuey+Xiscce48Ybb+S2225D0zTOOuss7rzzTmqz6IUf+chHMJlM3HHHHTz44IO0trZy55138vGPFxcJnHekIsZPk73gglKQz737tzCwm1ZVJS1YqA8+wd/urxrPCExWDoRJGziLiyNRkUw8TOSVXWxe96bxexWKvocDQ/T6RyNsURubssb4yt9+QWrHrxDScU78xG8RpdJUll51SI/+3c0T0dylJ55FrGUF1S0rMDu846+X0mPQkhxBsMikFBVvbRFiHVlRVk0002NehiKYcE9WDZunKGvREATDcI4cgFA3esagKGnS7JXOsqO3A3ITXsWoy9VFM4dnSRutdcigGtlq/3A/1XVFUpNniZnqP04IBeDBB+dMeGYRc4eZ6hej1gZC9vXYRWVK77Fi6hdn2vBsueJzCFYvmKfWfsuSyIbG/PXghai7rto2OCBikSVUTUe0u6fYv2Kpu/3dHRx48MtYo114L/g0Kza9PueYZDJByFyPXRvE4mvOeb92yVpCAydgqmlHFgxnsUqIU1U1+pmacs+B/KINesyBGvUjo+E1qZjCfVNEGwLBCEOjjoU1olPWVt/dhKrpJBWVRO8hatrKZAllOaI+QUVRdRil8wWL6JVXSRRl9/LQO0MJI2DpsZkMR3OuAo+eSfa1BMdND/chpMJG/aSzDgQh57kWRBFzVSuu2GE0W2Gh+JLrksccN4uzYA03VDbbXSpmOi9w4DmC//gueqgX1zvvora+dfzex6LTBhVy3FKpFC+88AKDg4Ocfvrp1NRUht5jtVq5/fbbuf322wse89hjj+V9vaWlhV/+8pdF3eeaa67hmmuuKXl8FeikUDJePtSFYzgGLidLpzkuL5+bAAIaZllCdtYQDR1mZeCeiYyASS4Yfe9V3VQlupH7txcVfQ+NTBR326pyI7kqEuLoouAf6KKmaUllvqDjFWMOkGUiO+muacBdk8s737ZtG2eeeWZRl20zR6DOaRTc57lWDrKirKFEBo/dcCZDicycRVljv/kEUjKIsPR0LFtnKWXtaTEct2AXmxtWoisuMiUKMkxBNm00FqFGFBAEgaSm4XXPLnrbsnwdQocNm1nCnOwG5tZxg+nrP0LxJA5nes6EZxYxNyimfvGsCy5DP//NxNPq+GuVql8UpqmF3rZtGyevrEcb2ofdU4vcegpIpoLU3TWrVkOHm55ggi5/HLQaxmR8SqHuOj1VOCNG26Jwzx7I47hZrTbO/dh3SGZUdC3Xxreu2ULrmix16bEGyQC23PsXEm1IC1bSqQQiOo1iB2FrzRTRhnQyNn4Nk7VM8TOTjReGBUypKAlpLzWvKe9y2Y6oIMowKtItAF5ZyXFE5xJF2b2swKOopTHpGVQha2xzEXh01hNVRJLJBNFDe1iy8ryiTnv2L7/EfuBhZJOJNR9/sOBzveGd/27sDwrULs7mud51qBP7SAzBU8VMhQqzXSfm2oGKajKhgU4AEodeGXfcjmWU/SR9/etf5/Of/zyhkLEJ//Of/8w555zD8PAwa9as4ctf/jIf+EDx0qeLmB7hkB8lkSFlNk/ruEFuRqDb3kqjchhN1xlMmBjOkxEoFH1flXgJq9qPEO2HB6+fMfreunw93g/8gNBIH76mXKW8mpaVJHeYsJlFzNFuKEpT7NULJRlFQkcwz+wIffCDJTg20QHjp6O2OJGOPHSf7B4tcxFl3dXRjSkdIqn385pZBopH5DpSoQTJdIwWsxeLScLqLFCPUgyyaaO6hhIyIs6CxTnr6G1N62oY6ysXPAxts5FjKR2F6j9qrdV0RjLzLu+9iPJQTP0iGP1IHRZjKzBf9Ysf/OAH2fvUr5Bevh8BWHvDbzFLpsLUXVcj6BpKPISSzpAw14CqlEzddbq8WKoa8ah+LMLAtGO0mkpggSSCxk9Rhqw1ejrRBtPIIZQQ6LpAzNaI7+wbpog2XHnqWqzvvot0MkZtY1vufadBvmyr6mzElAoihHMVuyePd6asTD5HVI0MkJJN6Jk4ogDNSidBq2/e5NeLsntZgUch3EOjFkEVTfSwoqzAYzqVpOf3X0K2e3GvPRtPdi9PQeCVqBNLxE9C2F/0jkeLB1A0nQROEITCz7V95r9Xqc91ODhCOp4hYbXM6LgtVDQsWcOIIGKRwRw5MvMJxwDKctx+8IMfcMMNN/DOd76TCy64YIqDVlNTwznnnMPPf/7zRcetghBd9aRSYfRilB2zMgKheBpH0qAFJDNxvFX5hSTyR99jCDVtRasvCZKMu7YJd23+cTa1r4Ta0U1zqj/vMYswoGsaOw91I+oqqlMhH4NezyQRRlXHbrzxRu69997iLj7muBWZecpH91E0nd5AglQyjkMS5yTKKqqG6ppYhrKaX64jFjaukx45jNkil1fwn00bFSRCUjU2PUbC2sh4RUCp0VuTzRAEivQZDt98oUD9R19fH3ZvzbzLey+iPMxn/6pCSCsa3QMD6Ikwy1dMBHFuvPFGPnLxWiQgIzun0DQLUneH9tKQ9KNrGulIBO2Bf5oVdXftuk3Q+RSkusv6bJMxPNSPJZlBcnqxTwqAzSTaIAzvJbb777jrluJYdTbIloqINhTKytRtuhgt/hpaGlfkPa+YrEwhR1Te+wck/yG0ZBTJ6gTfsoqpBxaDouxeVuCxXtCQRAEJBa8yRDBeO+vAYyg4RGj/k8bv9vZcxw0Mun6kE3M0VyugEJqtaXCaibuMMp/5fK4T3uXENRmTN3+bmmMBJrOV9evWI4c7QZo+WHOsoCyre8cdd/DmN7+Zn/70p4yM5PYGOfnkk/n6179ezi0WkYXXvPNfij84KyNwBAHd6EGOU0xRN01GIDf63l7Z5ppmu6E2GRuGYGdp577KkEolEHTVqBwwT80Q7X36YWLP/RwpMcSaj/0Ki9VetNOmaxqxkR4saMiOOmbKtxWi+8hmN9XBTiRdQZQtRKz1lY2y6jrLq2Q0zU6moXrWl/E1LScOWEwi2hgFqhyJ7Xy0UVcTUQzaqFYObdS31HDcAvPouBWo/7B7a+a+/mMRc4Lp6he14f2QDCGabGi1a/ibfmrF6xf/797PUjX8Akn3Epav+O746/feey+Bh/8DtcpGwpEb3MsbPMwEMAmgWhw43d7ZU3erlxuOWyIAcX9OpiLV+wpmiw3B3Ti1FcAkDA300L3neeJDhzntLdexv7Mb20iMZKqOyQzEYkQbarOeoUqINhTKyiw75YKC5xSTlSnGEZXmQD2wGBRj97IDj3aLTmp0T+TVgmBtnHVz6HhwYg9sKaDAuOqks5CWNuOqW2r0/iuC5dJqS0OVHZonKH75nuurq18i/crv0UcOYhJUzBZ72XXJZ7/zppkPOgYg166AcCf4DxX9vS9klOW4HThwgOuvv77g+z6fL69Dt4h5QnbfGCAsenFrQRRx0oY1X0ZgPppretoWHbciIa5/C2oySnXb2imva4KIGBtABwa7D9K6YgOXXnopDz300IzXjIQDHOodfT4bLDkCMpMxHd1H9HcgiQKiLqE56vCd88+VjbKqGby20bnldU9/7DTw1TTgPeMyJHcDh/96N8PRFIpDYdVsLziHtNFhUxOJQJzEQIR6/yAeX91sR1k8ctYLHbOeZCQcx2ObVKe60IRnFjEtCtUvJjURLTqMhE4mNMJKXq54/aLdUwvDYIl2oWTSyKMCRpdeeikPfXitQQluyi+KlB087NGrcGkhdE0lmPbMPnjom5Q98HfkOG4vPvBV7PEe9MbNbHzPf+W9RP+eZxCe/i4OYLj/UsTRGjc9S3nvaIk2zFVWZiHLr89k9/IGHkf6kCWJjAoSGdyZg4xYPbMKPDbb0jQ2ulE0LafH4Biq1p4BTC+ul4MxGm7W3Mp9rp/BHTuChkjKVo0sy4t1yWPwLYeDf4VMwgiIFtuLeIGiLMfN6/UyPDxc8P1du3bRMEPTvkXMIfJlBLytRJU6AhkJZbqMQJ7oezSeQNJSeC0m2nyeaaPvz/3PR5CUGFL7aWy85EN5h5d0NpNKPEMycpiqVHIKXWYRE7DaHAW/w9qWVQQtMjazhC3eC2woymkDCA5OyAbbqgo33y2mR4v9+R/BwE6jVm7DW7la0ysXZVUnNactEAHPh3zKW9JpHwZg5I/3GtLJqdw6lmKVt/LRRsXRSF6bzw56bNbR27C9lXDUqPQfOLxnfhy3rPUiGovTmj5MsxUGIwKdQt28ynsvonLIV7/o0UcQBZm0ptMltNMqjVS8frF9xQaswSewmSWkcJeR7QJjjbp/tCapUG1OVvAwHRrArumAQjiewOuwzS54WLWUSFIhnlaI7dvBspaTx9/SNQ1zfABV00lZCz9znqbl+AFJFIgPHmLpFV8hEhjGJ+euJ8U6KZqqkUhEcTiN4JQsiTg7/sjOP/wJTFbWf+DbJbUGmUktFi1jPO8lZGUKOaIjA510//1/MXnqad58Ie7qRob6ujBbrHhr6udFfr0Yp21K4HHXA/DovyFn4sjiaBamZgW+k66aVeBRToVBFjEjgssQ6JtJ1XW68W7vCrKlzTOhJJ5H9Gbqc50kjBOLoKBqIp2ZMoIbxxt8S9HRSWU0Et27qVp3bDtuZbnfF198Mf/zP/9DMBjMee+VV17he9/7Hm9605tyT1zErJBOxgl0bCc5fAQ9k5j5hLGMQHCIYCyN126ivdpBa70Pr91EMJ6hcySGnggY1KzJGYE82bqa5GHq051Y4pN4wrLZOC4r+i5EehEi/SRiYQrhYKaajuEYfcEEQz3zSAk7jlDT2M6KxiqavTZ8aYM3f+ONNxZ1bnVDO/Zz/hk2vYu69rUFjysqyrrqfEPRSklCsHOSoTboOtu7grP/kMokx23SfJwOYzUe33uiY7y/02S8sOpGnlz2cZLLzp96q1EDf9djB3l21OnMO6TR4+6Ln8Rg07lUuV2Iw3sh3AfxEcRIP+1qJ2arjf+Tt/K94Q15x1EIDe2rkUQBp0XGGp2nguqs9cJlMvYyiqIgSCaCsWTh9WIRCxuTnKCMq5VgQkFJJxAEAUUw4XFa8TYtR0gGDCdIVSpy24ZlJ+C1m7HIEsKkes1P3ng9pEdthr0A/Xly8LDagdnuIixV4TfV47YZ2W1RlKYGD4uB2c6uqIO+UJKBw7unvKVGh2l2y1Q7zdQ0FpZjaGpbydomD+ub3SyRRqirrmb5itW0LclfOzYTnvrfW3nhzrfy0q++POX1aGAINdxHJtAzq36OY+vwlja3kZX581dI7fsr0aHDRMJBNHVULfbgPVwjPMA1p7fO6GRsWeLLOWa4+yD6ocdIb/8FIwPdPP/fb6P3J9dy4OnfThnLXKoHFrJ7eQOPJjMsOxMaNkD9eqhba/xceSHSxsu5+syV47arkA3JwWRlUat7RhtUSJV8sg16elcH/liKSDJDXMoTKMt6rjOiFUkUkLUUwfgoM2qWz3UqMkx07+OovTuMHmjHMHRvGzt7Y+zpj7Bv146jPZyyUVbG7bbbbmPr1q2sX7+eSy+9FEEQuPfee7nnnnv41a9+RWNjI7fcckulxvqqR3/XAfy//gwAjvM+w8qTz572+LIyAnmydSaTEyETQFbjdI7EaKt25I2+K4kINWaFtCQh+yYyrtnRp6rGZQyOvhfuO0DzsvzOQ8m9R15NECWj4Nl/aJxyet111xV1qsNdxaotM0sSF0X3qZ3Uk2Z4P1S1VyzKGopEiAYTRsPcpJDTEDcfplPU0zSdS8/YSpXDhGVShLxY5a3paKP4OwwaoWRCaNs66+J8u6uK9W/7VwR389TGrXOI7PXCZveiJgV0SaI23Y3ZVI8UTs6bvPciKog8DArCSXRdx2yxUTNX9Yuu0TqxTMJoxTEqgX7lu95Bz7NfwiSJmHCStyIoK3iomxyEzAbV0iNMymzNgrqrVS2DxACO6JEpNS9yrJ8612hwaPnKgufLFjuyp8EQdwqWH1gRlASyGkfz70fXdYTR8ThEBckkkTbNvhVAdrY1oJiwCSlUQa1YVkYJDyBgdHCrbl7GkMmBnImS6S/Sma4ACtm9QoHHkaF+1GgGk2TBZXUhi8DIfmCW9M6xnmcm+7StLf766MMEO17AZjVz0Xs/NeUS2TaoyWrsvwCsMXNuH7+s53okZUdNREFL4XXKZdUlH963k8SjX0QAat56O80r8oitHCMQJBMJRwuW8GHUkUNHezhloyzL29TUxPPPP8/NN9/ML37xC3Rd58c//jEul4srrriCL37xixXr6bYISEZD478XKn4dQyEhCaxVIJsRlTTtaoBhqz0/nztP/U617EMKRcioGsPxCJ2Qt35HTvpprx4V0VhhUGPyqVzVNS8lc+G/UNO6AkeeRqeTP0e5PYWOZfTsf5FAx3Zkm5vlWy/BZM6ilHrbJhw3Xefvf/87K1bMLvJbCDN+7+5m0qKVeCyMf/fzLBvdoFUiyhqORhmJGFk3e0osynErVOPR2dvHXx76X9qSezhhy9m0rDqppBqPYmijVKg4X1jyuiK/ofKRd70Id6JLClFFRQLqlF4ituZ5k/deRAWRh0Eh64bCsCpOakJf6fpFQTBqygZeMdaoUTz71N85OWE80y6tgOOWj+pvM3pUldszcvWZ78CkvglX08qpQgWRSQrHrhnoVN62Uceta/rjioC37QQckZ3YLSn0mB/BaWQh19XKEHeBM7cXatHIopxmgkew6ClQkhNZmTLr1U9wp9BbPKSRMXuqqW5fj7c/jN02NG9iEIXsXqHAY/9AP5mgwVxasvk0zL3PEOvrxBwcweOtLjnw+NL+IziGouB2s4LCNsg++Dy+kSeQRQG98wwEi6ugDep4eRuaICHqKjZ3njFkPdeqOFGfLGtJYHQfNovnOhUNjF4JbK5jf99l3foBErpEa/usq9oXDMoOmdbV1fH973+f73//+wwNDaFpGrW1tYizSOsvYnrUW9IoPhuKqmOvKrJnxywzAnmzdboJol2YJJFqUmTCwfzR9/ikukeHIWGbN/pkMtO+6aziPscc9hRa6Ojf/zzSzvtQAP3US3LeT7taSacUEpERrIEBqqqmd+rnBILAS8l6TMP9JCI7WDopalwuUtZaHql+LyhJLqtaUvR5+Wo83mX5O5cP34VZTyI8vQ321JdU47GQi/Nni4LrxVPfRBg5iElQkE0mRJsH3zmfpH9k47zIey+igshygsKJNPWiDogEMwKRchRQZ0Cf1ExqZBvx/ldYca5Ry2xyuBjU2rErQRp8Berg51D8x9dWgBo+1t9MMk2pvctbq+Rth+5nCQ91M/D1N6PY62h847/ibZigWBbLFllzwknQ96DxH/8BGHXcyIxKHpZQ25uDrKzMcNqBGI+ArlBlFWitRLY1NoggCFjc9SCKrFh7EkSfB1LGd+rJL0BTSUxn9/J9/+mof1xJebhqM9HtfwHAvO9FPKeeC5QWeIxHRtCTCkmblTH3MZ8NukQYoUo7hFlJwu9vAtla0Aa1n3Aq/vZfEY6EqK/L8/mynutYxsTS0TmaiYfp9Ntm/Vy32NJoVcZ+0+k99hMwJ540ywawCxAV5brU1tZW8nKLyIJHSIBjNKKSL/pCZTIC739tOz948kj+bJ2uI6gpaull2NqUP/oem+y4GQ/8QugpdKxCS0aRAF00YbZYczYRvdQSHDQiafbD+2huLpy9nLyJ2P6TmxHNdjwrX8uSzeeUPU5L41q0gZewp4cJ+YfxVldmPVjR0sCnr35PwZqA6ZCtvJVStlFFFE2UETNhtKStJOWt+VaJS2ZUOkdi+OwSNe4ymoUXwLTrxdABkB8nHQ5idXuNVhRLT+fq9Q3zIu+9iAoiywmqsoKkCQgCmGULA2U4QTMhaGshFTeye/1H9tC2ahNrNpzKli3XkcioU+jKkzGX4j+FcOTIQZyxFKbqJtyj9yrUE61bryHSFyaljNYvJTrRpYnsZUlsEd8yEETQNYOu1za6yVRGa9nLcdyysjIZyc5YXsasxoBRpd5ysq3RIeOnY1TQpWYSzXR437w4boXsXiFsOvedxF9zCZHgEL6aRnb9zfj+4z2vAOeWfP9UwxYiplrs1VM/a7YNcqb+jkOLIEhG9ni8zjCPDTLLIg1eGw3eAn//7OCG3YGQMKNmUlj1WFnPtU9MGKqvshUWheMWFMpe6QKBAD/72c84dOgQgUAgZ3MlCAJ33313ubdZBEyoCwliTj+vMZSbEdjWMUJ3IE5/KJk/WzcmRmJ2UnXOJ+j3b8qJvvuHerGmFUwmMyZbVd77ZKtc6YEOUDMIkrns3iPHG05qkNFibjIWX95NRE3rSoKjx8YGDvLIc92ceuqpU66RvYnY1ORA6H0BXdcZttZUxHFrX70Zqfd32Nw1SHoQqGwgZ7YZvOwaj6RgQzXE6QgkbQSpKqnGY7bZslJpo7F4nMe+exO1mV6iGy6j5qL3z+q+02G69SIcHMAqOTgUCLCp1mW8OLgbeUXTgs4gLiIX2U6Q1VZLMqwC4PLYSWXkijtBY6hpX8ugJGK22pCThrP/yCOPcOqpp2I3579P2VT/IqHrOrFEAqfdyOQN9HQQSCSImx28dvSYQrVK5polpDIqVj2BqKuIkoTL7Zky/qLZIrLFyOAFOgxHZxSpRBRJ0xEkK/nd2yKQTTlNy3glCQEdNRGm0+8pK9uq6zrEhozslXN0zfe0Ght+JQlD+2B5+fZlJozNqWIhiCIOlweHy/ib1Zz4BtyeKlzLir/GZJz15qsKvjfZBiUzCgls2GQZJDOdKces6wxzghu+5YT67IhaEpuQwGsVZ/9cj9XsZbUhOOah65COHdOqyGWtzo888giXX345sVgMt9udN1VdKbrUIphw3CyugpzxcjIC739t+4TTViBbF979N6Lbf0VAMeOyr+bqDStzou/7Dh7COhAlba3h1Kxx5vQeSf0Dd6ofVRcQq9oxm1nsPZIFKRNHkkRMTnfeTYTT7cN93ifxNS7FU9/O6jMzU87Pt4mIDnVhkQTSqo51mlYApcDTegK87S4jy7qQnvusGo9kMIaoGd9RLKPjdVWgJ+EcwGG3Uyf4MelJEkNzU1A93Xqx79ARZCVKfMVFYOqATBx9cBfCinPnRd57EZVBPicoEzxMBhDQMWfCtKuJsp2gQqitb6X2mu8ZNWOjJRQ33VS4se98iP8APP/oL0i//CBmLcFJN9yPpuskFQEzAibPRH1bXrbI6a3UDD+LiT4cagBZBBET/O561BUX8v2RjTzXGS6JLRJzLyPZtYdI8GVazjJ63r3U0Y85ESKpx6c09i4JOZRTC3bNg5YK48gkOFJmtjUWDXGooxeTLGJqths0QVFk2NpGsutFAjueZcNr8rezqSSmm1PFoOXCj1doJHkwxQYtIR3aBWmVeChEUDMXrjNMx0Cy5LVHhYIbVlEEFERRwq0cZsTqnt1zfRw6bl2P3oVy4G9EzTVs+MC3jvZwZo2ydic33XQTDQ0N/PrXv2bDhg2VGtMiCuBwbx+2cBJBrGG6rk6z3Ujt7A3nOm1jGM3WKUIVg88Y/VJGDm6nbdWmnOg7MYM2odryyzxPjj5l0ilimowkiqBL9C/2HslFarSlgtlZkHK67OTzxymnX/jUDdz25f+elnLq1fx4G93ouo5SKSETyTQRca0kurbBoceNqPSp14KpRNpGVo1HMG5HTIXRAbdVpnmuFPUqgPr2dXj8L2FxBubsHvnWi1QqgazEAPjLUy+y5IKNJHufIzj8NJtP+yiCIMy5vPciykchJ8i09w9II4dQlTSyyYLg21iWEzQtBCGHKve5f3ord/z3N40aaKs7/3jnWPxHRMeWMmj9/qEequtbOf2GHzMSjiGjTjl28rr7QscQ2w9/l1OST1NlBRTHKKVRQO98Bn/HThrkrWzZeB1Xl/AdHhGaSAcMaqR0ZB+tK9YjKEaNm1AGVTIf5TQyYkNP+hFR8Ni0srKtwcEeNB1SGQ3BNlELdZhm5Og2oJtoJITTNbcOwFVXXcV9991X/AmaaqgyzweybFA4biWdjpNR43i8poLqjzt+fgvOwB7UhhNZ+Y4vjF9uuuCGbeQg2OyGuqVv6ayf687ePqyJFKLXVpQg2LGAvmAccyiILkTIZNKYTOaZT1qAKMtxO3DgALfffvui0zZP6BscxBZKkhTFaR232aKYbJ2vrolDzkZEiwtXlTGK7Oh73xs+RniwC5elgITx5OiTeynmwCtI6CQSMYKCoyIqV8cV0sYGeiy1P1Nj1dtem4EHr5+echo1GjEIgoDJU5mM22SM9a2pxMbvxZdfRn75L4iiwKot15a+aGXVeERtjbjTUTRBQpUnzdFKK+pVAG0rToCduyA5ZMyDAhTpSkOSLUhX/C+R4BBX1XgY2PlnhORTiAzjH+yhun7ua1YWUR6mc4KEtW9GGt6LVCEnqFRccZKLV35wHdqys9nw/z49/vp8iv/ULVmLstuE3SxjjRyB+lYkUaDOm59CNXafvw08Qu3BvxKQVbxNqxFH9oOuoptdHBGaMMW7OJ1n8NWcgSQVn72qW7qB7ieMpt6JwYOwYj3W13wQJRGmuq5wT7npUDArI1hJ6xlEdJrShwhba2adbbXaHKjLz0ONDNLYsGT8dU/bCST2PIBg95Hw982541aS0wa89PW3I4kC4pqLWXfBB6a8l1E1TCV8B/FAH/F9T2B1+3AsOQUhu1l2tg3SLNj0GCY9QVKfFCTIskHx0DBaUiGRhLGqwfkKbgwODSIrCVJV0nHjuDmbVqN2PILNJBAf6MDTcmz2Ii1rN7xy5UoikUilxrKIGSCMNSK2zN0CWIzBO+XD94xTXsYwOfreuPQEGpdOk7HIij5FEnZIxxCVBB534ejTqxUvd/RgUSKoDn28j0sO5VTZRo0UR7B52b2/g9Url05POR2TvZZMYMulOM8W/aEkP/rHfhL9e3n7mSexdsWysq+ZSSdB09F1AUmeRYQsq8YjmBTQvGsBgWBCgTlU1CsVOep1VUsn3gwcLvgcVLrXoSyJbGirhrZqLr30Ur7z1dsIv/wznBbZ6Fu16LgteCw0BdRgLEn3kYPU+rxEBo8ge70o8lRbNp/iP81L1kKNyxAEiXYWdx80zhWfIypGOaS1EQ4kac2kEXSdYEonqCt4Xa00qZ0I+/8IJ1xWdNCxur4V7U23UNO2FtFhfIYNr72oqHPzYbqsjMl/CDXpRrK6MDWuw7fm0llnW2uallBz+T/nvL503RZY9mNkV+28UOcvvfRSHnrooaKOTaUS6KkoCqBlJhynv/35d0QObcNut3Peez9T9L27Du4m8Zih5VD91q/QusI79YAsG5TAjh0/AjrJaIhOUcprg6qlBJpJQndOzOn5eK5VVSOGDZugINuOH6rkqrUnInV4jBKuRBfwKnTcbrvtNq677jre9a53sWTJkgoNaRGF8Jrrvk86lUTJpI7uQMpt9ZAVfVJEKzIxzFqKONrEcQswAzLf0DUNJRFG0TUy+lSK4BTKaTLKgKZii/XQvGQ5nRnXtJTTVKgPMzqCo66iRtVJnPNe+TSirhLZ+06ogONWb9MRnWYyohVhNnNvGllxypQVryTyqtf5Jjlu/o68Rnmuex0+9NBD6GqGlnfcCrWrjRrbRSx4TOsEDe83RK4cNTk1LHNRvxgI+Dn4vfch62n6V1/EmrZ6MqqOUpeb7Z8v8R9ks0HhDHbCyEH0UI9BSbRVFV4Th/ciBo/g9NbizZgJxlK4kwYjIiak8PqMwKMQKT3oKIgidWtPL37802CmrIwwvBfbHGdbZbMVsnuOziGKddoA1HgQn8NMRtXQfRM98hwDz1IVfIZM1IGuaUXbm2R0gsru9OQpEcm2QU4vdjWOye4hmrLiz2eD1AwrvQLgglVLxi9VTHBD03QODwbpPrCDZW3ttLQtKem5liSRMz7xE2JpFZHS1ZwXKmRvs6HQqiTBfxA472gPaVYoy3H7y1/+Qm1tLWvXruX888+ntbUVSZrKGRYEga997WtlDXIREzBbrJiPdWnWrOiTolpoGl2AUrEwnYK4YDIgRxuqkkGpXYeQjuLwNWa/OanguR1n4BVUTcc/NEjUYZ2Wcvrirn1Y4yG0hmVsruB4nR4fNnc1LjWIme6KXLPNLUGVfdaZwaMhKz4b5FWvs1XRlzSTjAYIvrSdzWvfOOWcOet1OPbsCQI333wzX/jCF6DllMpcexHzhkIbtO2//C8cyX705i2sfvu/57xfbv1idubY6/Gim6yQTmPtf45g3xHWrlkDbW1Tzqt05ni6MQHgW244bv5DPHvfF3FHDqDXncDa93wl/5hGg46ibKXNZUdXMuijrdZ0k22CLXKUg44LLds6Hxhfp4qAXQlPBO/aJtgD7rb1mEeew2FRyQR7MfuKYxYsdSpo1XYyqo7Lk/ud5dig6uWIohEgbNF1tJE8Nig2MnGBLOrlTH+XWCyM/0fvxa1n6Au8hZY2QxymlOdaEASDYXEMI+eZFwSj9cbgLvAXFvxSVI2dPaF5GmXpKOuv8s1vfnP899/97nd5j1l03I5PRP399Ox7nnQsxIZz3zX++sHn/0L4pYcQnbWsuug6bC5v7snZPYXsXiypQRRVxyXEGYw7FkQGZCFANls45f135H9zCuXUyXDYgqgmsUkqkq0w5VTXNEzJIUMV11Z5MZG1G06BI09CstOQ3i03o6eOZphly/TH5cF8yYpXAoWEZ47o9VjjA0h9z0PnM/PS63Dfw1/H2vMUVC3hiiuuqsg1F7FwoMX9xBWVFJWvmcyXORZEkaZlJ+Dx78RmShNrGlVttE1sIucyc1yoF1vC1U4yniaeTmCO9JIEEsJEBjJnTDYj6MhY2YJkYliux6wlwT6RuaHMoGM8HiU81M3ws79GNFupO+kSakqoxymVcqqpGqIkzirbuvuxn2G2OKhqXYOvZVXO+6lUgt5Du/HVt+HxzV211BVXXFH8wYngxO+TAoJr1p8C3fcb/wnshyIdNzcxsJsNQZCsLOOsbVBy0hitpQUtXS4PmqMOoj1Ig7tLOvd4QaFnnurlqP2vEB/owJJK5iRCxv5ef362OPr00UBZjpumaTMftIjKQFONf7Op8ZkDvPzH72PtegJNsqCe+XYk2ZhKwb5DSEO70Yd2I5nzy/Pmiz4FuyxImRg2KYrX1bggMiALHlmUU9HqQkqksGkJlGkKnjVNQ978LlLBfnxLNlV+XDWrDcctFTZq6dxlip9kRkPacmmZ5vmSFa8k8gnPnCeGqVUOYsmk0B++CUGyzHmvw5HBPmzhKEk9wqGdO9mwYQO6rjMSS3Ogq49Gl0x7y2Kd27EILZOi1qKSkWXMVZWXuSrU96x52XqIGZvISCSC2+0Gu0Erm7PM8QxjGjI34x+JA2CWRGxmCVNd6zRjckPVEvSubXSmXYQSCh634bCFEhk6/XHaqqyIyQC0lh50VJUM2777YWyxbhJVa7D5je8r0HpKSY4bFOf4bn/kR6QO/R+arYbXXvWfQGlZGV3TSDz7v6S0DCPLL+TUyz8x5f3h3iN0/eTDCLpKeOu1nHjW3ClE7xxdp4pCYpJK7+RslrfNsKdKCob2wvKzi7xe0PiZRTsuxgZpkgmlaQu+tRdPsUHvaR3CrKjIoohodVNq+HPZCVtxdz6K2TxsfJ5SAp/JMGTiYPWWruK8QFDomT+o1hPtCaEDVYf30L560/g5k/9eJzR5eODoDH1GLO6IjxEc2fsikd99FmQL3otvoWX1yUd1PM7WDShdTyBpKYa79lI/KkZiS/tBFkmIzryUzkLRJ4sEejqDScnQlulgxOo66hmQBY8symlKsdEqiaBrZOJBOv35C54lWWbjuSVEJ0tF7aQNxvDesh23kVAEUyIDLgn3zIcD8ysrXmlkC89UZZ7DbZUQ7G0gW9GU1Jz3OnSoQQQRdPvUjMiL3/swNeke+pZdQPvbyuubtIijAzEZnKCJLZudWuF0KJQ5ln3LQNeIR8No6TjxeBS7bCn8rM7DmBraVjOCiF2PUmeRqXLaYOXKacYkoq58A/7DL2OKd+F1tdJWbXyXnf44wVgad6KbKncVwuqLSlZDlmQToq6Cro87bQAmawGF5jKRHjqENXwYJT6Aqqo5pS4zIRz0j/fENHsact6vbmjliGhCUlXivXsqMuZKYGS4H2tKQZZlLJPF3kQJalZB/07DRhSLPD3PirFBT/31tyT79iCbW3j9xsun2CC5YydbBg3xv3bdQamFAjXLT4Lev4KmGE5o48aiz33x77/FvOOnyJLAkn/6BWb7sVfXXOiZ97auJqLrWPUEqV1/AK8pL4PltT4rtx3NDzANFh23YwSJaBBF0yGdRCyjp0ul0L5uC+x3YrdISImDgOG4rfOkodGN7luec8500SfL4F40iw2TzY1QvXzBZECONsLD/USGjmB1ePA2LUeSTRNvZlNOHR5s6UFMoo5PStB5tEQ3vG3ENZl4PIb/5edYteyssi63v3cYazhGghSnFXnOsV7jMVl4JplWOOJaSZvHoLV1+uNz2+tQ19lYlUF3eVBXrsJpNaLYJlnCabdDGsShVyf95rjAlGxD5RRlJyNvyxL3TqT+HYjxGD5VRe0bQXvgQ3OaOZ5xTNU7WFMrYw2HEaJ+iAloT36Dv0kv5R2Tomp8f2QjDfJWTucZQz0yYlDe2kwpfAzhV5wcsJ7GSasvLWqDlV2H42ldh6d3BKdFxmGR0XSgNk/dVAXqAZ3tmzANbcNp0cgMHURqyKU6Tge36ueEJjdpRUNZsjTnfUEUqW4/AW94Nzb70KzHWQxKaUu173AXtsEoitnDKVkCJOmqlSQ6XiAeOogj5Medp2YtGwe7e7El/GbohgAAe05JREFUEwgeC2NhymJskKjdT1VmAHUoiJIxmq6PzVH/swMoo0HrvIInM6HOUE4GHQZeLslxy0T9oGqkdBmTdX5a0MwF8j3zV/teQnVJODQda//D8OCjeRkse/csXBtXkuMmiiKiKBKPxzGbzYiiaMhqTgNBEFAUpaxBLgK8UpKM04yi6jg9c2NsS4GrugmqGyA2bBR6rnuT8cZo823BMZXLPlP0SV7AGZCjiY4df0d/1pAZlq/+EZ7qiTqKHMqpbzl6wE080oPFGsVrbzo6lFNR4uVUHebALuLJnZS2FcjFAfuJqEo91Z7cjUEhzKes+JxgivBMG8GEgj5K6QolMnPb6zATByWFgIDsrOVnP/7Z+KZo6bqTcR3sw2aOTDyvizi2MA+OG+RvWVKVCKNpoOo6oiDOeea4mDHVSHGDhiYI6LpG9MiLrNQP5Ixp3IZ1htmy8Tp8NWcYkv+jlDdRMuNccTpPayfzy9hJnPR/XTParHx1OGvWnwyx58aPEQUgqydqpeoBT9h8OnT9zPjPyC4o0XETYkOYJNHoeVbTNP6ZJq+7S1ZvhpcPQrxv2jWjXEf0Zz/7WQlUyaBxT4s3561eUzvBYUMp1LL/JdynzEyXDIwMEVFTpOPmccetGBtUvWIL5oDBqGDkADSsG5+jf/VcgSBcQiIWxGQuvb4bixN8S9H9B0l278C26V0znzOKOnMKwWEmYaqanZLzAkL2Mx9QtlErxRFsVSBb0JTkvK9D5aIkS3/LLbcgCALyaD3T2P8XMfdosGQMZT2AIiJA84K6E6DjcRjcbdTfCSLER5WQHFNFL471DMjRgpKMMEZesTlzaRjZlNO4KiCJAkI6RrN0gKC1Kodyuvfvv0SJDOGoX86SUy6syDizjbW5YS0M78KdGiAeCWB35d8gFmOsz73sKuJpFaupNBrPvMmKzwWyeh3qI3GC8TSoGbwu+9z2OowNT/xur56i1Fa/fDN0/XFijM1Hl7K9iNIRGOnHlFIwSQJmm7fk2plSMDlznE4lGMSHQ4iiyDJBx0oiKW3uMsdFjumIq416tR8ZEwld4pDYRps0dUzZgcerX7/UaK59wmVTaNdizWrOQeRgkQHHvHU41StzD5zEsqloPaCzFpz1EB0wsjInXFba+bHBSdeqyy8IUTPp84zsh6ZcHeNKOKLFKkoCLL/oo4SGenCJYo7talx+AkFBQNB1Mv27gfyO25jt2tziJmBtQUqHcbnqpxwz0+dYsfG1cPBe4z8DO6FhHWDM0Qs257KWSkWHtIRE74uku19k1Vkh7M7ierK1OxTw2YsWZ1noyPfMt7nmicEyByjJcfv85z8/7f8XMYdIhY2fkmlW6npzgvp10PE4WiZh0CwcNeiZNLIk5GTcSsmAhAc70RDx1rUsnAzIUcJKL+g1DhTBNF4zOB3l1Dy0n3ioH0E2EXMuwfe6a3Mop/49f8cW2Ed/V2Uct3zGevnakzD5H8VSswxBi0Eehn6xxrrRc/SpwfOOLOEZNRWlLtmDlRThzEoYUwOcA9nxTGQISdcNx9BePbWxbe1qxuk3g3sWHbdjEPuPdGEejKILEpvMc1y7kpU5zoT6sOtR0pkM0ZSK12GZu8xxkWMKJhSsqQhmLUNCkPD6pmazldWX8r3/68ofeMwTdJQhf41fHruXtw7ndUuQTTZIx4x/mjLaw3H93CjJNmyAAwMwtAfUjLHHKBbRUfqj2QkmG5tbLbmO6GTHbTjXcauUI1pKA+665qXUNS/Na7ssNheNW9+Gt6YBS8uJec+fPOYPnbWc8z/6TXRdR9VK7Hlm80LVEggchr6X4MR3lHb+DFBr15FWfw1A197trD75rOJOzFOzd0yjAINFQCMcz+RfhxYwFmvcjhWkjCJVLAvnQUr61tA9FCWeUlBefIbapRsY6Q0jCOBcayM7XjST46UpCtu/ew1StJfUsgvYOip+sCAyIEcJbiEFNlNB9bV8lNPE7ifxLd2Io+VkyEM53ZIYNbZZ0cHZIl/U2NW+CVp/VFCRaq5V5I55ZAnPJBQBH4YEuRoP0Om3zVmvw10HDkF3CFkSaJM8UzdDJpvRB8d/EHVgF6XlQBexEJBOxDEjkDF75p4GlZU57tLr6Ur4UK0SnmlalsznmPSRGKZEEh0QBSlnTHtefo7nDptKcpRKYYvkq8N5TyJB5sjzmLUkkgDW3980Z0qyWt0JJHf9kUgyiXrgJZpWF9+vcfvuvbhCUURfHcvyfBYw7MEw1SSGjpB4+g+s87bPSUuTUhpwj6GQ8mD9mR8seE4h2yUIArI0i/x144mG4+Y/ZKg5WouV4JoZLas20/OEDcnXTpW7FFXJ48xxy3rmGY5gDe7FrKURrfW0+JbkrkMLGBVx3P7+979z6NAhAoEAuj414iAIAjfeeGMlbvOqxtDIMNZkBtFhm4POO7OD1duAX3dj1v2kenYS9RrS0roOVk/pToEoy6RNLmyA0Le9wqM9RpEezaSYjY15MZTTj33s37nvvmvGX55sTLd3DPBORxqnz01qVbnVZ7nXn2IATVZQlRwFx5KMtabB7t8arQBq14Cv+Dq3YxpZwjNepwOr5MSsp5D1BIfmUHgmHR7CBKQ1AYenlove+1Ee+uHXx/9GXXIbiYEXiXe/wJozY1ht+VekuWymvIjZY9Ubb2AwdC1SOjb3N8vKHGuChCpohEIhPLZJrIz5bFidNSYQGJbqsWsRFGdzzpjWV0t86Kzlc1ovm12Hk4xux6VGUAUZRRfR1PSc1eHEq9ZwcCCKDqT3PFuS45YJDxBNKiQ1D8uyPgtMOKLnhEPUhnZTG3oJ/eEDCJK54o7o29/+du67776SzilouySxfNtVJDK16wnH7iOSVEi99CSrt74BgP13X41otmFbewFNp1w6q2tb7U6Wf+jnJUn665pGKDCMSdARJQfHBd8l65nXBQk0DR0dcyY8cdyUdWjh1m+X5bi9+OKLvOMd7+DAgQM5DtsYFh23yuBgZy/WSIykpvGaoziObD64vGQremyE2mVb8Lasovek95AOD+Gra55yXrGbuKqVW/HsOYzbmkAP9yK4m+bssxwTGM+0GotIMZTTH/7whzmvjRmol2uTVL1kUGFM1ZX7bgsptkn7/4ji70DSFATJVLKxTiZj9D56N6IIwub30v66V4fjliM8U7Uc0VQDkV5cZKg2aYhzJDzj2fxmuqrWo6dCPN8Vov6s9/C9ScquyarVxNNGn8Du/TtYsTFX63MumykvojzUua3Uua3APPxNsjLHoUQGj82E2+qb6Hs2R5njksbkqUehvuCYttTPfb3s5DocRYMYViRBRJOtdGY8c1aH4/T4SDpbsES7kYZLlOyvWkpGtmKumdpWIqelSXw7Dj2KIttRkRDnwBHNZ/fyof/IHgb+dCfYqmg+8/3UtK4uaLv0wGE0JY0kF3Y01XA/YnzIELtwNUGJWWyhbg1HQhqimiFx4FnY+gaSiRix4S4AQjUnUZalLrEPWzQS5PDQ6L4jKLKpnHsvFOR55mWzB0tmGIsWp3s4REuNZ+o6FDnagy6Msqz91VdfzeDgIHfddRdbt27F4zlO0qoLEGLGmEVCBdPopSIfH/yky26YckxNc+7GupRN3JrNr4e+B43/9L4Ir3LH7WBPP9ZEAt0pMVYmPNNG4I477uBzn/scyUiAoSO7aF1/OmAY003e1MSBzspQJceQbawH089gTQdIYsZb5cNC6cY6lYgTThp9gsTMq4OYV0h4BpMD1DSCrtGiH2TYWjsnvQ5Xtbewqr1lfCzRwzt4TjLqUq55/VKaVm6i9+8SVrsDWx7rtkiDXcQ4sjPHDjNtPjv79+/HW91M8Gi0LCkwJhgVKjhabVQm1+G4l+FPxLA7XOiIhOJzqyTbcvbV2G1WqtrWl3Teqe+9teB7UwQhNIk+78m01hg1lXMhCDFm92ZCYKgX3X8YOEwy9e6JsWapjTpSg6Q1QLbgrqotaLu2P/F7zK/chyyJrPrYA8jm0hwl2WQm7VuDY2QHdbF9oOvEwyNIooCq6ZidpQUNsoPrxWIsuN4q+cdfK/XeCxZ5nvlGRyPSSJhEWiUY89MpyFOf+QVMlyzrqX/llVf4j//4D6655pqZD15EWWh/663Ew34stqPXCLEQH3w6lLyJ87Qa9VzxEejdDmsurtDoj00EAn7kTIpUYsJxmwkXXnghO/90L9qLP0NDpHbZfVjtRiRbjw5MqMg56yo+3snGOpOKoqtJ7GKaZMbLgFZVsrHWlBQ2k4SGjmg7Lkgb02I64Rn8HSDKoClo1ip8Z/3znPc6lCWRmy45kReTU5/7lVd9G5wN4D8Inc/MKZVoERWEpkE6AhY3zIMidN7MsSBQV1eHx2MHPTbvLUsKjQkwHLijMCYgqw7HzZERmWAiA6gVrwfM3tw3ryuuQ2ZJ9OcpjqghCKHNYUuTCy8sTmjLlAoimEQyqo6rakL9Olt5MKPZcehRNCVDZ7pwxlOJB5F1SOjmkp22MWw4953YlEsQm04EQcAnJvA1e9B0HXVpa9HXyavqCbxyqIu+fc/jMIucds6bcs6bbHc+ePoSWq/8CdGwn8b6yu8RjgbyPvOiCJIZmzmNT4kSDafm/5mfJcoa3cqVKxfbAcwT6luWQ47cx/xiXvjggmCoTh141OgPl0mWnOo/XqBrGrJoyPuLluId9p6eHjYsWUpU1xFQOfzyU6w59XwAnnt5D47eMCaLhZVz0cNpirFeiim4G1nQUJMRgoKzZGNdZVKpahj97M21BY87HjCT8AzDexne9guiex8nGLfQ2nAaV5/QOOe9Dvv7ernmTVuAXCoRgcNG7YBYOg12EfMP/2AXofuuQ5JNWM64nvr1M/eomi0KZo6tVWjRKKKYoF0NMGy1z0nmuNQxIZsRlfS8j2kcObV3BVBmPWChzf1MKJn+nKelSShhsCfmQpimp6enqONWuBRocAMCTHLcchRQw4M49CgyKtF4DK/Dkdd2tdpSCC4LCevs7ZOj/aSpL4z2mRMFAdFevJ0uFFyP/OV2avx7SdobIMtxy7Y7py6rNuZE4/Fhb6d95iUzQiqMW42QsbTyj0nP/EJGWY7b5z//eW666SauuOIKmpubZz5hEcc88tUyvUv+K+qOX2Ie2YNo8yDZPMiNJ8x6E5es3UDohd8ZFLmXn2Hl5jPn8iMtWAiiyKYb7gdNRdeKb2IfCARou/gi+p524jXr2DN7AcNxU8L9pFWNCJ65ibhnGetg0oWeCiJmYng8szDWyiRqp3x8O/DFCM+kT3gnwV3PgACdLz3G5vPfXdFeh7HQCCMPfBrJVYv7pMtxLT2ZQCBQuHHxMdzE9NWIkH9wdPOcwaVZqCxZegIzZY71TAqkKoS2rfhWvmHOM8fFjAnVqG+ZzzFNQYF6QKCi9YDTMWd0TcM/3Ed1nhr1bObM4OFXUBNhPLXN2Gvacm+UxxEVdBWrEgLZCYz2pa2QME0gEJj5IJhoQG9xgTiJfp9lu3pVN0QG0XSdGlOGugK2q9maBq8NaitY1jGm6gglKTsWCq6bmjYg+PfQmD5MZs+fMFU1vyoYEjM+87IVDZG07CbVdib9tdeOP/Ov9S1c560sx+3//b//RzKZZPXq1Zx77rm0tLQgSVPrUARB4Gtf+9qsrp9Kpbjlllv48Y9/TCAQYOPGjdx2222cf/75M57b09PDjTfeyJ/+9Cc0TePss8/mzjvvZNmyZTnH3n333XzlK1+ho6OD1tZWrr/+ej72sY9NOebXv/41v/jFL3j22Wfp7++ntbWVN77xjXzuc5/D6/XO6vMdq8jexKXif8GdHkIVZNREGA2RZDmbuIYN9IYzCLpKav8z8Cp13MYhSghi8fVdZ5xxBmaLlfZ1r4Ge56D/JYMiJYo42jaRkM2I9jnirmcZ64zsQEoFkXQFsxqjZGOtJCd+Xyj9C+cIxQjPNC5Zg99dh1fO4PAay3clex2ODPbgH+iCgS6i7eexeqkxn8bvM4lKtN/WQpWqYdYFAsrciScsonIQEgGsozQxh3duIurFZI6Th/bAsjVQsxopT8uSSm8gixnTZLbIfIwpB/NUe1doc39w+18JPfE93MleLG/6HM6a6Tf3h578Ndauf9Bt9rDlxjxqjlmOaDieoiV1AEHXCMWSdPodFRWmGVunZsSY45ZtA7NslyJZ0ZAQUbEoIRiTCMm2XaPZMazeksabrxYtmlLYfbiPE6ODmAEQchy3meiq+YLr73NEsUhHEDMJ+NNnwFZVmCGh6/NCo55rFPfMR9j1qy+gpJIk/DGuvnzl+DPf2zF8tD9CQZTluD3++ON8+MMfJh6PF+yhUY7jdtVVV3H//fdzww03sHLlSn74wx9y8cUX87e//Y3Xve51Bc+LRqOcffbZhEIhbr75ZkwmE3feeSdnnnkmL774ItXV1ePHfve73+VDH/oQb33rW/nEJz7BE088wfXXX088HufTn/70+HHXXnstTU1NvOc976GtrY2dO3fyzW9+k4cffpgXXngB2xzW33TtfQH/Y98Gi4uW8z9GdXOu8znfmFLLpE4oYAEE8RLAUdImbvIiZrU5SPpWY431YLVPTxFclBzPxbe+9S3uvPNOaN5sOG6psFGLVLOSjedeMbc3zzLWkYydZZKEgA7xkZKNdSaVQNB0RAHE49xxg5npR4Iosv7dXwJH3RSKaaV6HcYDg+O/O30NwKT5lEUlcvj3I5EkJjkJmlvnVDxhEZXBEntqlCYG1DfOyT2KyRzf8cXvc+edEzahlL5nczWmbMz1mLIxn7V3+Tb3b0k9R13kWcx6EvGP/wzummnpz3rUWCvUyW0dJiPHEbUgCG6kVAgPEbriKTp1vWIiMOPr1AxIRUYw6TpitqOVZbuCCQWX1YslEyCTitA9HKalxp1ru2bR8ywfXfXggX3sf+jLNKS72W7xYs+EEKxu1k8K2hZLV80OrkeVZ7AmQ8ZcVzPTtpfY9duvIPc+i+5uZfV77ij6My00FPvMp5ZfBHt+R0B3kc6kx5+LP//fwaMx7KJQllX92Mc+htvt5v7772fr1q243ZVTPNy2bRs///nPuf322/nkJz8JwJVXXsn69ev51Kc+xZNPPlnw3G9/+9vs37+fbdu2sWWLUZtx0UUXsX79eu644w6+8IUvAJBIJPjsZz/LJZdcwv333w/ANddcg6Zp3HrrrVx77bVUVf3/9u47Tqrqbvz4597pM9v7LrALLgIKGECKXaJRMIhiVGI31qBEEx5rNJ1oYkjC70mCotjrE2PEaFTsIDaK0qUtsIVlly2zdfq99/z+GHbZ2Tqzhd2F8369eAFzy5zZOXvvKd/7PeH44tdee43p06dHvM/JJ5/M9ddfz0svvcTNN9/ca5+9tQb3QURtODWsput99j4xafUsk6tuKxaTikDg1VWS4qJvxLWbrfLKX2Nzdh7Od7SnHDdCARSho1gcMY2ANd+8cg7HzYv961HSju/tIrbV5mZtxyZS0BqrcYTqqfL4Y7pZ7yytRCsN3xiH+hTS+uCxvEGnDzOtjkkIoA9JJKgbmDLC79Ncn1qFEpU1OBAhP1bdS5K97cLFR2QxZSk2TbMDJgtY+2ZF0GhmjttrYPfmzHF3ytSevixTS/3x7F3rxr0aWkMcHjCZURSjy7XjxicF0VQn3py8ds/fXkc0aMnAXOfBpCoEVR96/cFeSwgRTacNYPPuQiyhenQLnNxyQzsznslx2WgHawnpBoH6SooVU8S9KxT0U1dTg8WkYlLiol75q71w1SHZWTSESgGBLVCDDgSUw2eMNdFbZISEnzpzGokmPwij0+Ul6txVOBrqCIj+S4TXG6L9nR9x5g+pmXw5k7JTm3N23HLmCJKDB1l+hMoaqx7N+xcUFHDPPfdw3nnn9WqnDcIdJZPJxK233tr8mt1u56abbuLLL7+kpKSk02OnTJnS3GkDGDNmDOeee27EAo2ffPIJ1dXV3H777RHHz58/H4/Hw9tvv938WutOG8All1wCwPbt22P+fLGw6h4cFhMWk4ojYYB0Tlo24tJcmE0qId1A0wUupzPciFNNUa1E3/Iitmz1PjTdwOZKirrTdrSmHN/x9SdsXnwJm/8yi8rSvVEds67QzYWzDz187EyhwpLDvioPX3/xYafHabrBukJ3p/tEQ0PlI2MybiOOXLWS3GQ7IVsyAc3ApAgSRUN41Fh3oh8/s8sZmYBi56BlKDXmdCzOgbsg5lHDU4VJVXDY7VhdSQDMnn1o8dfWiylb4zGrChZVYNdaLWJqhI7MYspSbHyHfscdyX0aDjVleEqnjaXmOtVKb80cd6dMHenLMkHkvWzSiHQmXb0Q5YyfwrBp4Q52y2fvzr+H8pPms664vvle2RNNjfvTtLUEg3481jTMNgcmwo37veSSYNaZ4v8S884WUVW6RpxWR5LTSs6Qth23ps/0qncSFTnnkpwQj1q1Ezt+zBgomp/MYBFWu4PPzdNYVjW+x5+lozrVkq5pWLTwEiai1Yxbe/cu1ebCq4efM0w06trcu+prq9lf42NflYd9jdE/znB4QOBwu8dsjyM5byz5aU7y4nS03NOxDpsAutZx2F/nH7Z5cD0UP4xaw44vqOPxemjweMIREjn5KP6a8OC6Hn6OPkHxYLOoqI7Bv7xXNL/zKckp5OekRSRaNJtUxg8ZuJ+/R0McY8eOpa6urusdu2HDhg2MGjWqTYdw6tSpQHjx72HD2qZJNQyDzZs3c+ONN7bZNnXqVN5//30aGhqIj49nw4YNAEyePDliv5NPPhlVVdmwYQPXXHNNh2UsLy8HIC2tg1CBFioqKqisrIx4raCgoMvjAEYmCGjKrJeQFNUxfa5VI67OkYursZCQYkVXWlSrKJ5lOiLZKgehkLceAQhdxxrFMhBNM5ez7lqMdmg0tthxAmbft5jZz55vPkI0VuJKHULGqGmYLOEo+t6auexo1NhuT0JXBGahMdTYT419aNSjxhknnEF10kl4dANHnJxua+JuDPDN1q3U7/qM8+dcR1xCL/1svNXhv52pzQ375jD41skTDCfJZiuq0Aj4qih2Jx35xZSlmPgbqrEKgdoXGWVj0NGjFceafn/2rlX4c23jQay6F/DSGPSS5HK2HznjrQZE+ByuyGclu0wIYXFCsAHF4iTl7Nsprz+lV5LARFOnDGGgTrmZoMdN6nET25S5vRlPs82O6mnAqfiptSZG3Ls8DfWEFCsWEcQWn9rJO7fVXrjqrXEK6v5vIeRjsuqFRgfG8k3dS/TWKkKiREvAVx8Ob02w+BmWkt5uhMTYFBFeLmR42zV5pYGhR63dP//5zzz++OOsXbu2t8rTrKysjOzstjH4Ta8dOHCg3ePcbjeBQCCqY8vKyjCZTGRkRK5VYbVaSU1N7fA9mjzyyCOYTCYuu+yyLj/Po48+yrhx4yL+zJkzB4DPPvuMVatWsWjRItxuN9dffz1weATpXy89jcfjYe/+gyz/z5usXbuWhQsX4vV6mTt3bsS+DzzwAFu2bOHll1/m5ZdfZsuWLTzwwAMR+8ydOxev18vChQtZu3Yty5cv5+mnn6agoIAFCxZE7Hv99dfjdrtZtGgRq1atYsWKFSxZsoSDdV72Fu3H0Px8sWknFSE7BYFkap3DKXfXs724kqqqaspLSwgZCg/+7g8R512wYAEFBQU8/fTTLF++nG++Xk/Fpy/znSFxPP7vD3hy1W7+dN00fC/8kPIls/C+djtVz1zFvsUzWf7UH3l5xWomD0/h7b8swGxSe+UzlZaWMm/evIh9582bR2lpKUuWLGHFihWdfk+tP1NPv6cV/3yK9DgrhreW7Tt2dfmZ8uIE3uIt/OOf73LPUyv4+z+WYEofhbveg55zMu8+u4jGL5+h4JV7Kd5fwpIlS3j7nXd54LmP+OdH6xibaefvv/6fbn0mTTe47BeP8fGWQtS6/ewyj6Mk9wdsrLahmKw0egPY4xLZWmPDdfadvFx9Au9vLuZnS9/iyac6/kwu/Gx65wXia3bz8YfvD8jvqT/q3m/uuoW0VQ+Qsv1l9m36tNc+0/KXngLg9RWfNn+mWbNmsXz5cp757xfUm1OpPFBMrSdIQ/VBXMkZhPweXPiprqpkR3ElXvcBdlaFKA3GHfPf00D7TBu2F/DVrgOs+LaqXz/TmWeeKb+np5/mrS+38tzbkfey5s/018Ws2lHFim9rWPLaSkrLDzJv3jzMJpW3/7KAycNTePqtlbz/ze5uf6bHH/of9Oq97CuvITfVRVWdj5Bu4A+GSKQRs7+WsrJyvMJO8aZPoWpn+HyeCr7++mt0XeeJl99o/kxPPvU0f3xjXeRnsli5ftGbuM9+mGfck/h26BVUW3LY40ugoDrIN6/+PyYPT+HRf61g2ep93Drvtm59T9/97ne7/J527NjJ1rIgu+rjaNTtPPDAA2i6wRk3/5r1hW62f/E+Y37wc14/OIwq50jc9Q34A0FM8els8WeTMvPnLNoUz7ries674xEs8em8K75Lwdi72F7aGHPdq6+r5ctnFjIlNwH93Z9Tu+1DgvWV6LpGTXUV7uoKand8Su62R7nJeI2Vj96P2aRGVffu+eltYITYubcQXdeprPOioyKEQPVV4/V42bZtG5itFOzaAYFGrr/+OoL1VRTs2cPOovJB9/vUo2uEp4p//Oxitn38fyxZsoTPPvuMgUoRQojuHnzRRRexe/dudu3axYknnkhubm67WSX/85//xHzu/Px8Ro8ezTvvvBPx+t69e8nPz2fx4sX87Gc/a3NcSUkJubm5PPLII9x7770R255++mluuukmNmzYwIQJE7jpppt45ZVX8Hq9bc6Tm5vLpEmTeOONN9ot38svv8zVV1/NvffeyyOPPNLl5+loxm3OnDls3bqVsWM7eRbks8VQ/BXEZ8Hs7iV66XW6hvH6rTTu+YK95LabASvJYSZPLw7Hg89ZGlWiAk03eHLVbrI3/4PTfKtICJSFZ/ASh2K322msrcRtxFGRcy6Trl6I+dCs0VHp6+dg5zvhWc25z0d1iKYb/O39bWw76Gfy8BRuPj0Ps6KjKCY2Pf8/OMrWE7QmMm7BW702c9lpGEfzjGlDOP1y2mgwmbsX+nGMa5nAx9A0NvxtLnH4cY2YwtBLftvhcbEk8Nn4tytw6vUw4mxGzQknZ3K73aSkpKDpBp+8tpTj9zxNglknKScf1dDg4FY0Q1BpJGDoOla7g5Tz78F0UtcDWtKRIwyDDX+9GFUPEsyfwdTL/qffytJUp6T2swtGo1cScxWvgXfvAZMNw5FMUbWHxNrtKEIjoDrJOO6k8KyMtzocOXPBIsidxp4v38S8fhlWs0LyFUuxJ+c0f5Yu14gTgl1P3Yyvej8+1xCmzX8K3RDN94N50/O79Zm6U6eiu3cdnvHsq3uXvulfuD/4M8GAl0S8uKwKwp5EMVnUeoLkqpUkJ8SHQ2ijzdZ7cBu8eSeGHgw/0+YNkWFUYBEBapQkrHEp4QiJhvJwhMRFf4OU4+BfPwof/50rYeycHn2uwWT7kzcTqC7BHzeMU+Y/ybZt2xg3blzX7fN+0KNQyc2bN6MoCrm5uTQ2NvLtt9+22ae7C3Q7HA4CgUCb1/1+f/P2jo4DojrW4XAQDAbbPY/f7+/wPVavXs1NN93EjBkzeOihh7r4JGEZGRltZvai5W+sxWIIVFsCAyVJa19lwIp4oFYXNOLErIDQdCo6eaD2qBQ8FF5qjT7kzGxSCW1ZweSpP2izWPL46tUIvBiGA2P5j3ttseQ+zdhWfwCCXrA6+zQpx0DXpkFkNjN26rnYiz+FQAGEfGBpe72KJQxWCwXBX4tXCDT1cHz/U089xYL/uavDUCKvpkDQQwqN1DnzjvzCxVLUAucvwltfzZCMrsP7+9JTTz3FPffc069lGCi62/HqlWfv2qwdp2E2J+EKVmHRvRSVV5KXld4m/NldsR+LNwiKQkb84VDJqBJCKAqNOaejVv8Tu6eUssKd5IwY0+MkMN2pUwMi22ircNXG2gKCHh94KvDYXCTFxXcvW287yVayUsIJyjwdLC8RaqhA6AZmVUF1JHX/Mw0SLQdNvFlTMVWXYG8soaK0sL+L1qkeddwKCwt7qRhtZWdnU1pa2ub1srIyAHJy2m/EpaSkYLPZmvfr7Njs7Gx0XaeioiKiUxUMBqmurm73PTZt2sRFF13EuHHjeO211zCb+z7d9caCEuyeOvxaiFP6/N261qcZsCKyVeZC3T4SFS8EG6jVQ8dWyvGm5wJtsWV3OmXaVE4/o+1iyaoeBFVFNZlo6MXFkmPJ2Fbi9vJ5QRVjs5yMz03r8ma9/7OXsJV8DnHppF+9rNtlHOzay0JmP+40KP4UDA1Kv4Hhp0ccE2sCn5AuOHDiLYQaKhmZdzgj6cmTp3T6zIpqi0MPevAoLoyR51GeeN2RXbhYioqiqpx60pj+LgZw+Fl1qZ+107jPjBuGr8RNEAv+QJDi6rZrx5lUFd0aj1AtmMyWiFNG04kZMWUmJe6dpI8/n6xh4U5QTzui0dSpPes/wL9/C5b4VEadc11M9y5/SGfTzj14SjZzzgWXccuZI5g6xMLJQ3uYnbXVs2ilnjgsAR8AcSadYd3M1tudwfUD5eXUHAgnmopvMJHfs082oLUeDM2beC7B4v+S5LTgqPmGSqVny1P0pQHb4p0wYQKffPIJ9fX1EQlK1qxZ07y9PaqqMn78eNavX99m25o1azjuuOOIj4+POMf69ev5/ve/37zf+vXrMQyjzXvs2bOHmTNnkpGRwTvvvENc3JF5+N4UCjfglRgb8H2hywePW2bAOn4m5VXjY2vEtbqIVYYS0T0eMIKkOXVyUhKPmZTj5VVV2LxBlHgrSTEc5/P52iyWXOLIIMvwIFCpF4mUktirM5fR3HCDmsHyf7/E6IavqEvNgesXdnmz3l9Rg73WRyCk0TfLBQ8O7SbwOe1EzBYHBD2w/U1QzT1K4OOw2/j+hZH1QNMN3trtpd7acfIEi7cW90f/IOGEc0g5aTY3OzOO7MLF0qDj8/n6uwgSHTTuVRPK0HHE25x4qtuPnJk0ex4wDyPUfsRSV5LTc0i+putHTGIRTZ2qLPgae9En+C0uODf8HFa0ncX1H/yTuC3PYwMqJ04jPWsYpvVPUfD2evSkPEb/6NHuFbz1wt/ODPzBcOZLw9YiOV8Uid6aRDO4nqu5qbDaIwbXfQ2HM0s74o7uUOb2BkPNeaOgrgSKv4S8Y6Dj1tDQQF1dHYbRNqVrbm5uzOe77LLL+POf/8wTTzzRvI5bIBDgmWeeYdq0ac0ZJYuLi/F6vYwZMybi2Pvvv5/169c3Z4zcuXMnH3/8cfO5AM455xxSUlJ47LHHIjpujz32GE6nk1mzZjW/Vl5ezvnnn4+qqrz33nukpx+5ZqRj6rWEGt2kZvRvlp8jkgGr1UUsYI7HfmiTI+gGDl1MYriIDVZFZQexeb34LAanxnDcnj172oRfOGp20Cg0FAXqhEJS/JGfubSaVU5zHcDi3o+zrgrD34Bq73wwQmjh8GZhOvoX3+5Ku1nIFDPiwGb0wjWYCz9HNds6XTQ3VhtKatl8wMNl00d3GEpkAnJuOq05C6UZjujCxdLgs2fPwF3c9ljRWePeYrZCQ32XkTNqjM+Y9+XzfFHVKX9t+HzW2FO9Hz92EmVbnsOsKvh2roSsa8MdnYCGL9CDh1hah6v6DRKTRwFQ5wtR7PbGlK03msH1eq+XRp9Koy2R8pNuax5cn3PiOBrOup9go5uEjKHd/0yDQHuDobcOnYaprgRqCkFZ04+l61yPW2qPPfYYf/3rX9m7t+N1pvRuLBo9bdo0Lr/8cn7+859TUVHByJEjee655ygsLOSpp55q3u+6665j1apVtMyxcvvtt7Ns2TJmzZrF3XffjcVi4a9//SuZmZncddddzfs5HA4WLlzI/Pnzufzyy5kxYwarV6/mxRdf5KGHHop40HXmzJns3buXe++9l88++ywi40xmZibnnXdezJ8xWuNO73p9kiPhiMSDt7qI1foV4m0J2LRGDL+b4so6ctMTj4mU46aQB6DLzk1rc+bMaRt+0ZiIOViFEGC12Rl6BBdLbnmzzj9lFi5tK1azCiVfwfEd/95oukFegkqGPRE9o22W2GNR60Vzq31rSAi40RUzWiCIXVE6XTQ3VlOGp3DXrJM4f1IXnb9WzzIfqYWLpeiVfPlv2PkuqjOJnB88hGLuv8GQpozKUv/o88iZdnSWuKS+zk1CYvvXiWif042mTk3LUjDMiQTTh8dU7onDksjMG4Ml/0SSAqWotWtAXEOa2Y9iM0M7SwFEnTymnXDV1oneWj+L1pFoB9cPrP8Y/65PQFc4N60Ooaa3GFw/+5iJkGjdPo3zZXF1/QFUTwXGli39XLqO9ajjtnTpUubPn8+MGTO48cYbefDBB1mwYAF2u51nn32WzMxM7rzzzm6f//nnn+eXv/wlL7zwAjU1NZx00kn897//5ayzzur0uPj4eFauXMmCBQv4/e9/j2EYTJ8+ncWLF7eZKbv99tuxWCz85S9/4c0332TYsGEsXryYn/70pxH7bdq0CYA//elPbd7v7LPP7tOO20ARSzx4SzE14tq5iMU7h+Ev+xZhGBj15RSr5qguYoPd6GsX42usxRJjx23hwoUsfeCGVuEXmXhDXgQquqVFTH4fz1y2vlknD58Em9PDWcr2ruyw49Z0Azq+pBJnYogkm7NPyjcYRSbwoTmBD6EQFaaMbifwObjudRT3Phypw4ifPLf59TefWsz3pyxt95jWI+hCCHaUuhmRHofdZuvw971XMuJJMSk7UIz1YAmG6SA5qqXrA/rQwoULWbq0/Tol9a1oG/fC4qS4NkDZ+jc5Pd+FGD4qPNMf8vLDE20kpQ9BsUb/fFd7oWnF29dx8PPnsdUXMea2l3DGRc6ExfKcbjR1SvHVYlIVHAnRRUy1vn+ljD8fvn4WPJVQ8S3HJ+hgj4PjI6PKYkoK1YuJ3qIdXB+WNIqy0jWkO1Xiaz9nxJnhFPrHYoREy8HQhM3P420oxmb48HuiX1D9SOtRx+3vf/87M2bM4N1336W6upoHH3yQWbNmcc4553DvvfcyefJkqquru31+u93OokWLWLRoUYf7rFy5st3Xhw4dyr/+9a+o3ueWW27hlltu6XSfHqyacFTp6wxYHcXcB00uTEYjiUYd/nqdKrsrpmyVg1F8ei7x6bGHGS9dujScCrhl+EXAIDF5JNC98IvuajeOfMTZsO11qC6Auv2QGBmS0fKmd3acQoLDEu5gSmGtEvhodftxWk0EzeGUz91N4LN3y1c4KjcRcA1hWouOW0eNodaNGnddLZ++/jhDa9aw65QbOenMi9o9rrcWfJdi5A3/DmrWRBS1f0fUZaet/0TbuNdDQSpfuQp7qIHGxgpuvmUJAPu2fMaedS9iNaukzHmEoaMmRPW+7YWmnZsUwlFbAEKwf9VzjBo/rdvP6XZZp4QAf13431FmTGxz/5p6GuYNL4YTQhV8GH6+GMB++HyxdDZ7O9FbtIPrroRkRk6ZER483b8O1e8+piMkWg6G+gwTQWFDF1p/F6tDPbp679mzp3mRO4slPILXlF4/MTGRm2++mUcf7eYDmxIA5Xu3suX1R9j+7lIaayu7PmAQa7qIveqdREXOuSQnxKNW7YT6MhzOeCxWO0nxDqx2F5+bp7Gsajya3vaZymPd7NmzD89c1lZS6wmS5LSQl+okL9VJktNCrTdEcbUH4auBlBF9NnN5eLY1fPNbtnofWt6ZCASN/iAlHy8LryV0cBvoWpub3pg0a3j00dz+0hzHpJZhsKkujMRhlJJOZdBKosMS7pCrpsgw2CgovvAgm3BGhv00XeNba9moWbZ6H4kuF8MbvsZu+PB+u6LdY2LNdCn1nqlZCuOHJDJ+ZP8+Kw0d1ymp700ZnsK86fmddoTWFbpBNaMc/z0UBXK0UkT1bm45cwRnDwlf1w0BruTMiOM03Qgf24HW94OPqlNINvkYxV7yv/1HeE25N+8ML1fz2lK+2VcZdXKlLutUoB7Eocd2HMmd79tBeZetrULPnhhet3LrR+i+evDVgK+u3ftXZ+Vuue+kEelMunpheJ22YdPCg6ktw1XPv4fyk+azrrg+fA/tpN0zZXhKpz+rdYXu8PGjZhx6RUDBh5hNKgmbn2b3qw9SvPrldsvb2Xc7qLUYDPXEH0edkkCNJau/S9WhHk1XJCYmomnhXmlCQgJOp5OSkpLm7fHx8ZSXl/eshMe4qtI96Ls/Rgf8Ey4gLqm/S9Q3uoq5d9gB51BIGdFrMfdHq7feeiu8WHIfrLPXHW2TaiRwQbWPhJptJO//GuPgx6gma7tJNbb/vQKzEURPCHBin5VwkGmVwKdDMYbBfidFJ+Rw4c+LnOV966232j99OyPoZ43+HhklK0h2VoRHpK3xPcp0KfUiX004TCyxf9dwg47rlHRkdDar0nIm/arTLsFZtxKLKqDgfcgcw6mZOlqlg4ChkJR6eBmlaGfSWz+nmxyqwKE3oAgLoGDowW49p9tVnTpQdoCaA3WYTSouv41oU2+0vs45nblML3qFBL0GTQ2iqKD4n0AUfxF1UqgjkuitHW2eM0wbBVW7CO54H8bMobZwMzbfQar8Krlntl/eozJKIiInQApFZjveupr+LlWHetRaGzduXPOzXwCnnHJKc4ZGwzB4/PHHGTVqVI8LeSzTfPXN/3bFRzdKNNj010VsICvevo7Kj5cgrHHkXrCAjKHRr6hy67zbmHjF3X2zzl43tb5Zu7x7cRoN6IqZUDCAxUqbm7VJgVDQT0gINGPgxpsfcW0WzQ2R6AhHPNQ0+jECjYzIyYgtDDbkxyF8OOwWEjKHRGyaN29eh2FIbRo1WSdxrXgJtaIC/vs/4ZAk1dKrmS6lbhAiPDMAUc829KXO6pTUv1qHB96adwqUfAnFX8HEa0g2aiHeBnGZoIavy7HOpLcMTfPqKmYcOMxmEAbFocRuPafbVZ3y1FUR0gUhXcdu67x87Zb30P0radOnJGvl2EQQXZgJ6SoWTScQQ2ezvxb+bv3dXpN3Lu6dG6j11aKsfR+LFl6GQHUcftbwmIiSiHYwdIDoUcftmmuuYenSpQQCAWw2G7/97W/53ve+15z+32Kx8O9//7tXCnqsmpBhwhiaiIYJi/PozKAYzUVsXaGbiWnhuG09FGDPmnf40bSZQOcXscGaBKGxtgpTY3jBeCOG5ys13SD/+7cc0Wxh0Wp5sw4YChbVRZzDimqPoyjgbHOz1k64hK+m/h0t4GfqcW2zdh2zOshCVllRTlxoPyIoKKq0M1zEkMDH2+JZZFfkjMwvf/nLTg+NaNRs/gc+TylO4UEx2cCV3u0RdKkXhbygh8L/HgAdt67qlNR/WncQkjLG80PxBSo67HoPKneEBwHis8Lhgd2ZSY94TncEproCCAbRayqoVZ3dek63qzrliE+hOvcshLeGvNTYsxQ337/0dYQUGwJTczbdKiOZWlKi7mwekURvnRwP4e9WGJlMDdkxixD+TcuZmuzH0Ay0DLX73+1g1M5gaJxt4OZP6FHJbrjhBm644Ybm/59++uls27aNN998E7PZzPnnny9n3HrKX4+qKFgdidDPD5T3la4uYi2n9+eM0Ch7/UHUYAMFmsEtZ17SaadtsE7vO/Fjs5vRDYEzPimqY5o+7/vf7OGy6ZMG3sxlxM06jzJPA3ZbHMKvUudrm1TDfMLFzJt+fN+UZRDrKAuZy2pCV3QMYZBQv4sqZ3r0YbDeqsP/dkZ23N544w3mz5/f6eERI+iGGUVx4DCZCRmCA90cQZd6T/nBMqoP1GFWVRw+O7GnPOpd0dQpqf+0bOB/WAgnhFI43r8Z/d3fEq/4UYQO9WXhZ9G6M5PearmaikAyAW8ZQvhIcnnJTcmOebmarurU0PyxDM3vwZI3Le9fSSdQ6w0QZzJAaDQGlJg7m32d6K2z41t23hKckznP8yZJxrdwsAyTEJj8NRiV246dKIl2BkMHcoxPr3cpjzvuOH72s5/19mmPXYHw1DW22FLCDzadXYhaTu8LI47JmLAC2rb/YD5rTpedtsE4vT88Tof0QzOsUXbcmmYuT8pxHdHwi6i1ulkXoVDrCwH64aQaR2htucGqsyxkLquVoFnFavgJCMGHponsjzIMtqCwCFOVB6tJJcWSRMtUMPn5UYTpRnTKR6LU7iDgCxLwH6DWltftTJdS7/DUVDSHiVlbZMDrL1HVKalftZxJd6+tRPj3YUPDp1iwmE0oArzdnUlvFZrmsyRiEuWoCJy+MoSRCSZTTM/p9nmdanX/EijU+UKAhUTn4Lp/RYZ+FqEaIayhBhRhgKJiII6pKIn2BkO3+wZuVsleuXNu3bqVd955h8LCQgBGjBjBzJkzGT9+fG+c/tgWOPSM21HecetM686FK2k63w++R2qcHwo/B1dqxEzSUTG935Rm2GyLuoHbNHPZsM9zRMMvotZJHLknoOELarhslhY364bwszmtFnc+VnWWwKexbDcugtiSssBXg9WVTnz8cV2GwTaFEitVZZh94VC6jLjIsFSHI4qMnhGNmjhKPUk4g1VYhJcki0ZuSuKgadQcjaxpIygd+2O0xmrOyBze38WJrk5J/a5pJr3aXIIAPNgxKSohHWq1BGpwdW8mvXVoWgBM9gziAhU0qgn4arwMS42L6TndPq9TfZQUqr8cDv38hmAwQJk9k2xzuLNSpiVSSeoxESXR4WBo48BdgqhHHbdAIMCPf/xjXnjhBYQQqIdC+QzD4P777+fqq6/mySefxGoduD+Age6b3cU4A/XoZsGx3Mxp2Xn7Yt9JnKp9QmpDGfz3Z+FnNozQ0ZUEIXjooh9jh33K8BQW/Wsd53x3ekzH9TT8IiodJNWoafRi91VQ79OwH3cSpkM3a399Jfpzl6OYbZin34N16IS+Ld8A1lkCn3XOM3mr+hMmZFq4aMrxmL/9N2rFds5UNrIv57us7iAMtuU5z0/JwZZ2FmbNxwRrZMNk7dq1nH322Z0XsFWjRrOnQrCKkOrA1DLEe5A0ao42w3KyGZbzg/4uRrOo6pTU/w7NpKebfJS4RhII+EnVKgBBo6aSFN/NmfR2QtOGJOchtCzqGwxqvCFEtYc8PfrndLuqU4Xr3sakqMRnDSdp6Akx/BAO6SQp1JFcG7XXtIySiM8lUF+JQw8CCm6bOCaiJDrNZl63pb+L16EetWjvu+8+nn/+eW677Ta2b9+O3+8nEAiwfft25s2bx4svvsi9997bW2U9Jhn+Bvwhg0bkCGVT521iXhp1Hh+hyj2I+lLw14LJdjgJwp6nuUVZzi2nDxucnTagob6WgKYTMjljPvamm27qgxL1gg7WlhthbySFemyGl4Nl+5vXljtgpLL7YAO7SqsorQ/1d+n7VWcJfCbmpZE9ajJv1wxj2S4n2vgrEUJQ2+jjO7UfNIcZbyipbT6mdUfw0lmzmHPTg1z449+3ee+o6lPrRk1IxZ9wHP6kkVQHVIrd3nCSHS0I6iBo1Eh9asBeo6RILWbSh+ZkY07IpMQxmlJbPk5XfLfXjNRQ+ciYjNuII1etJDfZToNfQ7XYyU1xkuQwh5er0Z3ox8/stMPQtL5YV3Wq4vMXqf7o/7Fj1asx/QiaDZC1UXtNq/VAbaqBIcLJ0OIc9m5/t4NFu4OhFmt4ZnHOUpj+QH8XsUM9atW++OKLXHvttfzjH/9g9OjRmM1mTCYTo0ePZsmSJVx99dW8+OKLvVXWY44wDPRhp+DLmowre4BfBI6Qpun94Uo5uiHw4cAXCGDYkykOJbKXXBLMOlP8X2LeOXjXCtq2r5TtZQ2sL4u9w7JgwYI+KFHPtXezVhUF4rJw2O3YzSpJ3n1Ua3b042cSCvqbj7VY2w5cHNULgrbS2aK5bRaJ3W5mszKaYrcXZd8q5iTs4O4Ta5niKIt5kViIsj6106jJzswgN9U1OBs1Up8aqNcoqZV2wgMFCrpqBaXVTLoRimomven686p3EhU555KcEE+o7FtqDxZTcfAANJSRpxdjsVpZL0azrGp8hwtON51r6co93HjvQx2+pzAMLME6AEzO7mVV7ej+pSpKzJ3NAaHVd6sc+tuv2EFpkZojhu92MOkym3nayP4rXBd6VLNCoRCnnHJKh9tPO+00udBmDyiqyrS5csYyQtP0vtlPuS0Hq78SpbGeg+UHqdXtR830vhLqXqgkwHPPPdfLpem5juLIPWo81Y0GqSYbSdQRVE2U6Qm8VjWeq3LKIM2FIQS2pPh2zzcYM4Z2V2efsc0i50nfZYb2LsnCjfPje8mOT4VN3QsljqY+dZTpstYbZFiyE11vxFazmypXclSZLgfrMh4DVemHS7BoHhxDxhE//vv9XZwBeY2S2tHL4YEdhaZZdryDvWgHfr+fCmHD6simwd+AWTTydWElQjV3Guo9eXgKt1y7qOM3DjYyJtNJSDfQcofF/GPoLClUf62N2mOtvttaEYdIHI1QLYMz9DNG3V2SYSDoUWlnzJjBe++91+H2FStWcP755/fkLSQpUovp/dSsYaCoCED31R3OTHgUTO+nn34dtqk/IvOk78V87OzZs/ugRN3X8gY7aUQ6k65eiHLGT2HYNJwOB4lWgVt3Um0bhiUtn3inndLdG/j02xLi7GaSnFYcjrh2zzcYM4b2labO25TcBLILl5NEPQlWBWtcSqehxJqvgfqvnkPfsQIaytuct6v61N4Iulq1E09VCVUVZVSW7iG7biPxooEtoZxOR9Bbnm/pyj3HzIxqXyvd+hkHNn3Etk1r+7sowMC7Rkkd6MXwwM5C09RLHiftyqV8M/YBHo2/k+W2i2lQE0g3eThf/4yyXet5879voB3Y0mHUwCVzLu7wvRVfDQ6LiQS7hZS0zJh+BJ3dvzBZItdGPf8eyk+az7riepat3tfpda7ftfPd5mYkk5cWd8xESUwZnjLoOm3Qwxm3hQsXMnfuXH7wgx8wf/58Ro4MTy3u3r2bJUuWUFRUxD//+U/c7sibb0qKHEWVuqnF9L7ZYsVrScGngdeSRmLL/aJIgjCQR/WPmxR7h63JQJrl7iypBidcjFK1k2RfPR9vrWNNueB2/xM4zDqn17zB3uAkyrRKsuPNqO69YE88OjKG9qGI9dSwU2cfRm68CyA8qtrOemoHy/ZTueplAJzfvYtRU7MiztlZfers4W6nex+JwUYaAipCicNvjiferPPtvhKWtTOC3uZ8slPeK1qGiamugXGtG0jXKKljHc2kA+SmOEF4wuGBdmeXM+ldhaaZc8Zz0YVjObh6H1/sq2KYaS1n2HbznfrnmC4S8FRp+EvicGaNbDdqoNM65a89/O8YlsPo6v7V72uj9kBvfrfSkdWjb+KEE8KZebZs2cJ//vOfiG1CCABOPPHENsfput6Ttz1m1JTto65oM/a4RNKOn4rZFnuiiqNOq+n9KlIJKQI7sYVuHM2hdgsWLGDx4sX9XQwgijjyzLGYgUuHGbhX7+Nf35zG9MYVjDaVMq12HVbDh+FVUFfch5E84ujIGNqXWmUKq/VpiGovALXeIMnthBI31hyeZbMnZbQ5ZUf1KZZO+ea9pVyn/ZtJGXaE9gHL9s7h3427uXRcImZHwtGzjMdAFGzkhENhYqFuhIn1hYF0jZLa19vhgdGEprVcX0x1g6m2CBSNNJuGPXEITpPe4fpindYpX83hfzuif8YtmvtXR58BjsDaqN10VIZ+HkN61HH71a9+hSLXWOozJTu+xli7DAD7jc+SlC47bq3TCKfGhR+orfOFEAJqPUEIBchTOk4jfLSP6s+fP7+/i9As2jjyppvdk/oFJH72TzJCB7CpOppiRhcqqh46phYE7bbWi8RWh59L0QI+cignJX10m1DibLOHUIqDkCaIyxgScTpNNzjr0hvafatYO+UbN+3C5t7KZMsX5AS+JlDeSGCvCbPDfvQs4zEAKb4a7BYTdosJYgwT6ysD6RoltdVpmnT3vsjwwONnUl41vss1IyG6AdLmqAGxA5+woCsWHAhcNgvFvrh2owag8zq1s7AEa5UHi0khx54U9TNC3X0O6oitjdoNffXdSkdOjzpuv/nNb3qpGFJ7Qr46mnL7OBO6lwnpaNNmej8lH5RwuvH6Ri+pgRLi/R4qXUNIzT8PU6tQhsEwql9Vuo+i1S+h2uPJnXoxqTnDYzr+008/bQ5bHgiivXGZTSq3pG2nxq5hBEy4lQRswo8QJspCiR3esKUW2skCp4eCDNWLsSgG/vKd2HLHo7QIJU4Q9eCyhTOJJRxefLvpBv/66gKGDh3a5nuMtVP+XOiHmNa+T8g4yBBF4IkbhssZj6H5Zae8L3VztqEvDbRrlHRYv4cHtogaKEkYQ3zDLkRAI1C2lzrLCJJc9nYTkHVWp2qrK7D5QhgmG0PbyVDcme52vI7I2qgx6vfvVuoVvRq06vP5gCOwgv0x4oRkBSMjjpBixWqz93dx+l1n0/u5divu+gO4qEVDxev1Uff5a4y0PoEyyBbnrq0qxVS0GoDGMWfG3HFLTh4YjbOYHbphp1p1iuzfwd3QiIUQqgIhb+ioyRjap9rJApeS4MJTm0SiXg16AFFdgGKPB5MtvL+nKnysMxkOLZbd8gY/OsXU4ax0LJ3yH2Xsod6sY/h16rBh+P0YacMprmn/2TuplwzAjtugvUYdA/o9PLDl2nHxCZSFsjA8+wGdVKWCnOQxqKoSmYAsc2yHdUrTDao0G6mubDAd2+2ofv9upV7R41ZrcXExN9xwA5mZmcTFxREXF0dmZiY33ngjRUVFvVHGY5ZTeImzmUlOlr8kXWV2Uo0gKek5VJiHEMBBOtVkVq+hqq4BQ7UOqsW5hb8BkxoOQba5EmI+fsiQIV3vNBC1DPNLc5GcEI9ujSdkiT+qMob2qQ6ywA0fcTwBSyK6IWioq0HUFoczhaXkQ+WOcONe0G7GtqtPzur578qhTnmSVVBjSkMXgL+W4gOl1DZ1ynPyUfw14U65rnV4qmNp/b7esKOwmH1VHvbXeBExJGboS4P2GnUM6GzNyM40NfDnTc/vWcO+VdRA0JaMDztCgGYIBOLQG0auL9ZenWqOGghMw3ThXznltqXdL9dRoN+/W6lX9Gi4eseOHZxxxhnU1tZy3nnnNScr2bFjB88//zxvvfUWn332GaNHH31pRI+IQEP4b1ti5/sd5aKd3ldtcWQVrcd4/1egG2gCKv1mGi12UOzUxTCq358ZJ49PUmBIYjjBT1pq1we08t577zF16tQ+KFkfayfMr11RZAw9VnWYKcykkJU3hqrCrdj1Gnx+FXNdGZb/3E5g18eYjBDUlGBa/uM2s9J/ePhlTj1lWs8K1qJTnp6SSu2+jRhC4ParJCcd6pQrbUfR23y+ozipUF+pra7A7guhmx0MtQyMGYdBe406RvRreGCbqAGNxMTh+BurOKAnUbO/npOGJmJqlYCsdZ062p9l766jKfTzWNWjjtv999+Pqqps2LCB8ePHR2zbunUr5557Lvfffz/Lly/vUSGPWYH68N/dWIT5aBL19L6uYVv9V4TDiddvQmg6adoB9tSYMFvtpMfbogq16/fGYTDcIVEUBayxf/d33XVXb5foyOjlxV6PNV1lCjNpQdJdJhobrOjCQC/+GsPqwAgF0VBAFxjtPGvWK/WpRafcZLYQjB9GpUen0bCgeIPh9NMKnXbKZUOse4JpYylv1LAMoAiDQXuNkvpeqwRkSS4ruSlORHoSDfvraPCH2FxSy3dsbpTcaSgp+XBwG/dccRYc3DZonmWXpO7qUU1etWoVd955Z5tOG8C4ceP4yU9+wsqVK3vyFse0ncUHKHZ7KfIc2xecqKf3m0b1Xek4MvOxmhXMGAwTZVgVnWHJXYfaDYjG4aGOG2Z7t57h+tGPftS75TlSenGx12NNtIvEqnmnYh9/ESqgCANPUCOkWPGqcVSRzF5ySTDrTPF/iXlneF2kXqlPrTrllZqDxKRk4u1mGvwam/fXUtvQiNACoJih8SAUrwk3xDpYcFc2xKJz1jnfZ86NP2fW9ff1d1GaDdprlNTnNFQ+MibjNuLIVSvJTbajKgomVeGkoYnE28wkBvbjrm+gbP8+xBu30/iv2znw5DXw5p0Yy3/MJ68t5Zt9lUwensIN07JpKN5I0F0CWjDyvWTYtTQI9WjGLRQKdZqIxOl0EgqFevIWx7TGOjc+I0gwYCWvvwvTz6Ka9WoZaudIplZNwUYVdgKkBPZT7HaQl+pCNVtBC0DZlgGZcVIEGlCg2zNKr776aq+W50iRC4J2T0yZwlLysf5nPoorjlqPDw0zZZZcHE4XDX6NJJelzax0r9SnDkbRc1OcbN5fS8hXj+YvJWTSsMSlonz+//D4AjgddkSMSYX6M8xZis5gvUZJfSuaqIHv2N1UBvyohkZ87bf4G3dTpWTgyMzD0IJtMtRWlRdT/urPAbCd9VNOOPX7Ee8lw66lwaZHrdKJEyfy5JNPUldX12ZbfX09Tz31FJMmTerJWxyztFCQkCuLoC0Fc1xafxdncGg1ql+hpOG3JKKqKpVqBuV1AYqqPBgNB6GuBL74G543/gfRzihdNI3DvhqpW7OjmK2ldWw82L2F6mfPnt3LJep7TTfRV72TqMg5l+SEeNSqnVBfBt5q1IZy8vRirHYHn5unsaxqPJpu9HexB4SoQolzp4X/du+BmkIs8ZkkDT2RSvtw3AGVGk+wwwQwvVGfOhtFPzEnnmHKQeKFB5PuQ3jdeHw+DjQaVNY20Lg7+qRCTfVo6co9ciR9ABuM1yipb0UdNZB7CnHjL0BRFRRhENQV4iyCnZUhNtU520QNeOuqm9/DFp/a5r1k2LU02PRoyPq3v/0tM2fOZMyYMdxwww2MGjUKgJ07d/Lcc89RXV3NkiVLeqWgxxqzxcopty/r72IMLu2M6mcnn0Ao4CXZA+W1Psy1exFUIExWvJrgQKMgMdCAvepzjhfRrSPV5yN1gQY0Q+BTu7esxltvvdW75eljckHQnolpkdiWz5o5Eoh3egkagbbHtXjWrKf1qatRdJsWJMNmIAICHRWfZiaOIJa4TPbUBUHEM8rujkgqtK7Q3ebzRtMYO9Zm4zRfA96N/8aRmI5l6CRIyO7vIgGD7xol9a1YowZc/5mPLS6BGm8Q1Qhi8VeT70qkyO/EZbeSmJ2PUr0TdrxNZs5ppLqChISKJTVVhl1Lg16POm7nnHMO77zzDvfccw9//OMfI7ZNmDCBF154ge9+97s9KqAkRavdUDtVweZwkWcXuAIVJHoq0RE0aiYszhTMKOyp8w+oxqFrxFSCNVm4UoZ36/gHHniAhx9+uFvHHmlyQdDeEXVdaycBTGpcOItnRwlgelKfouqUq2ZM9niEqlITMKMaARprq0i0+qkUqWiKlXpbDim+Ytj5Luvsp/LWx6spybRw0ZTjMWeeEFWY87EYGnWwbD+Vn74CgOOcuxk9ZWB03AbTNUrqezGtL3ZwG9QUYo5LIyU9hZribWh6AKfuZpTqoVrPoKTGTK4Adc/HuErWgr8OFAXj04V8xLQBv5arJHWmxw+JfO9732PDhg2Ul5c3r9uWl5dHVlZWjwsnSdHqalRfDQVID5ZgIPALMyEUtNJtWOOGATZQlJgbhxOHtV2mIZrGYVcdu/Ezb+zRz+LKK6/s0fFHklwQ9Ajr4FkzgGK3l1pvCISHPL0GJXcapI3udn2KulPeeBA+/38oukaKM42qou2ge1D8DeTTiMeSQo0vlSqTnbT9X3Oy9w6GNZTjr/JTVWAnfdhoPhGTmxtjXf1eHkuzcd66yuZ/2+NjX1qkrwyma5TU97obNaCYrXjij8NWX4jN8KGIEJmh/VBThq74UNBRVDMoCkJA4941HC+2RRVZI0kDVa893Z+VlSU7a73IX1+N8NVgj0tCcabCoSQNUltRjeoLDcVsR3Gm4fZZcAQqUYRBnKeY0bYkvLY0qvwaVWr0jcNlq/exoaSuuUHashxZiXbG57RdPLtpnw+/LeeemWM45bjUNts7azxG07jcsmVLu5leB6KYbtgtNHXeZKctNt1JANPd+hR1p7x4DRhauCFmMuNNGAF1xcTrdagKJBo1WGwOVJ8bzdeAOdhIRnwWBxUHfp8P987POF7dzC1DijCy7+Cdjz7iQDcHXDr6vWzap6PfvYHa6cu0+gmlOAjpAlf6wLk/D6ZrlHRkdDdqoDYAiUkjaagpJUnU4iCAVdEQhk5AtWGzhAemGjUTe5Vcck3RreUqSQNVtztugUCAF198kffff589e/bQ0NBAfHw8I0eOZObMmVx11VVYrdbeLOsxZcfa9+HrZ1EUyJ/3CnEJhy9qA7WR0B+iHtWv2QdfLkE128lJT2ZXkY20UBkYBnatnmTFgy1kxax70Hy+ThuHk079NVTv4UByCRt37eVJQ+NHZ+TzzBdFzZ22A7U+nvmiKKLB2rJxWOsL8XWRm8l5yW22dzRbd7SGeskFQY+MLmeltSB5eg1Vdiefm6dRXjWem3uQACbqTnnr8E2/TmLScNy+Blz+chwqZLhUdG8DhiE4YBpCdnwGGXGweX8dxaEEjqOKyTXvwOpvGN7g7daAS0e/ly1/du117KLt9L28tpirpua2G8LZ0TaAr/ZUgaJ067yVB8vIdx1a0D4pvc12eR+RBp0OogYOBOLwmDOx1X+LIgKgKPgUGw2eEFY9hE8xk5RkjWotV0kayLpVY7ds2cLFF19MUVERQggSExOJi4ujoqKCb775hn/961889NBDvPnmm5xwwgm9XeajTnvZ8TRvHWZAoOB0JUbsezQ23rsr6lF9WxyYrBian5IaLwFzAuWqnfhgJYreiEDDpXuwCR+GUDttHKovbgBD5xI9xGkenX3r03l626l87TqLycdlcMMpQ/jPhyvZs+Nb/t24m0tnnAOqufl7O2dMJiiCb4pqWXYowQbAstX72FRQwpmmnSRVuKlPnEhCcgYQWxYsOZIttdaTBDCnjh3X7feN6vrUYfimk+LqeNweL9aaIlxCw2NJptKro+7dQsCWioqDeJsFk64j6g+ieqvISMnv1oBLe7+XXXXsou30/frNbby3tZyd5Q389qKxEYM1HW2DcKftwTe2AvDQJePbdBg7O++y1fuI37qbVGeQpKSU8DOL7dSH/riPyGuU1F0dRQ0kxMcTZ4Vgo4HQDYTJSsiejslThgboZnP4+V1FiVzLtZ1wfEkayGLuuDU2NnLRRRdRUVHBQw89xLXXXsuQIUOat5eWlvL888/z+9//ntmzZ7Np0yZcLlevFvpo89rX+xk7NvKGnRevI5IcBE1OVJMJkCls2xP1qH47jcNhyYnU+5No8Hgx6svIFgdQEARVF1UhK8FqLwAqOvE2c3PjUHirUFJHopjtZDj9mKq+JclbRHaomFkJZ2D974fMrSmkqrGR+s0Ke4qfoTDlLL7xncyUvGRuHuODYCP/9tTx4T6dx4UBQuGb4hqmJHk5ZfeLiDIdt/fHJJx5dczry73yyiuyYSQ162kCmPfeW8tr48b12fMgnYZvpjop0xqx1tejKWZsydmkVlVhNTzYvB7SrBacNguapxZdKIR0Fastnoz4+JgHXG45fRhU7uTN+rYdu2/2VXLZsHqsuodNuw/ypDBi6vQdqPUxdkgiB2p9bQZr2tvWdOzXRbXNP6f2OoydnXd9oZtbE3QSLBZwJHdYH/rjPiKvUVJ3dBY1UHOgnIS0eGwiQEg14VaSOagnkEUVFkLo5hZZmltkzZWkwSbmjtszzzxDcXExH330EdOnT2+zfciQIfz85z9n2rRpnHfeeTz77LPMnz+/N8p61Np2oC7iho2uke4vBrMX4hNA1wbM4tADUTSjxR1lnEx2Wkl0WCjTAyj1BzAw40gfTkLISp0vvHh8TrAIJ36swo8hQNMVLNY4sMVT7PNSa3GQRhnTG9/B9/7HWGxmFEcyqYnxiNp69MpvGFG5i3tTPyK/KhH17WIwQsxVLUwIpfGvNWNZbTqF/xm2m1NrVmAK7kFBYNryGEbVpzEtPgzIbG1ShB4ngGFqn4XURRO+maOXo6kK9UoCdaEELCYPhuHFooBq6CjeBiwihI6CMAIcrDiI36GgKETMxnU14GL+z8NQUxjRsXtm6zRUBe41bWRkeRXoIU7vRqdvZnotc05M4I1v6/lwnxExWDMtL5EbRgV4++sCNu7aF3HsxqIqbh7la7fD2NV5p+QmkLNvP7X1FQhzGqkD6D4ir1FSrLqKGsgbkgV6CMUWj9kax8FANvV+DWzDSTRr1Bk2jHay5krSYKMIIUQsB8ycORNFUXj33Xej2hdgxYoV3SpcIBDgV7/6FS+88AI1NTWcdNJJ/P73v+e8887r8tjS0lIWLFjA+++/j2EYfPe732Xx4sUcd9xxbfZ96qmn+POf/8y+ffsYNmwYd955J3fccUePzhmNbdu2MW7cOH7x9DscUNKYkpvALambMe1eAYWfQcgLFgfG8DP5SD+ZV72TmCRT2MasuXG4r5JblOVM8X+J4q9pbhyiBREN5Wi+WuqVBBoSRyNQqPOFMIkgQ/wFxOHDjIZAQaDgs6bRaEmhJmjC4Yonz9qIqNxOACsVSRPJTQvfEIqqvZTXeBkjdhOnBjDb41AShoLZhqH5aayppDzowKM6GeIIkSZqIOjDUFSUhGw8jXW4jTgqcs5l0tULMVu6fm509uzZcp0kKUJ7S1tEQ9MNzr/qx3z8z95fU7LNTODpwzC3DN80QqBawJmCqCqgKmihwB9O+JOVYMGmNWLxHiRFr0JVQAgwgEYcVFqHYY5LI89SR6hqD4oexFBtWIeeFB5wcXup9QRJC5XhEo2oVjsJhwZcMNswQn6qK8vBCGFWFRLjXKjOlMPbqg5SpbvYkXAas6afgXXvh1BTiNBDHPTo7NPT2WgPd/rOMW1kpKUKxQghVAu7Qmn8q/7wYM15pq9Ra4s6PZZunte7/UNUEUK3JeIaefqAuY/Ia5QUi07XXtM1qNrJPT+9jUWL/46x+v/RuPdL9pKLIDyAk+gIhwnX+UIkOczk6cXhrLlzlspn3KR2NbXPt27dytixAyucNuaO25AhQ7jzzju57777utz3T3/6E//7v/9LaWlptwp35ZVX8tprr/Gzn/2M448/nmeffZZ169bxySefcMYZZ3R4XGNjI5MmTaKuro677roLi8XC4sWLEUKwceNGUlMPPyfw+OOPM2/ePC699FJmzJjB6tWreeGFF/jjH/8Y8RljOWe0mirGxk2b+bLKSvbmf3CatpY0kxcl6AGhIcx2GjQ15sa7FNajxmGiHQwNtX4/2UY5ZsVAUcAwwKc6CQkVIcCkQLzThuKrIYCNIstxWK0WUC3UBSFHrSHRvx+T7sdvScaZNwkUpbnxmG/sw67V0aDEE3KkkyGqACixjsTtM8hVK0lOiEc546cyC5Z0VIimIdZywV3jjdtpLPiCbaEhoChkJdrJTXFSUVFOYsNuTIrAbATRUPHgpMyej9PhZHioAPy1BDUNFYHHnIJmS6I+pGJ3OMkwe1Hce9oMuBS7vVBfRk6oCFCoc40gNWd487Zud/raGaxJN/mi7zDGdF4vdY0+BAYWqxND6PI+Ig1K6wrdLF25p8tZYk03+OS1pRy/52kSzDqJ2fmU1Pqp9YbIS3VS5w1iqS/BaneQcv49mE667Ah/EmmwGMgdt5iHGtxud9Rp/zMzM3G73TEXCmDt2rX83//9H4sWLeLuu+8G4LrrrmPcuHHce++9fPHFFx0e++ijj7J7927Wrl3LlClTALjgggsYN24cf/nLX5rDNHw+Hw8++CCzZs3itddeA+CWW27BMAwWLlzIrbfeSnJyckzn7A6zSeWW1M24tbUEAz6K4nPJFLtRBdRrLkpJJ9csU9jGKqZne1LyEW/cjq3gCxDxzcsv5KYlUGGkoDVUY6gqNoJoJitBbOFOH6CqoOoBMJmxqSoJNrDWFwCQoigkmPxghEO5LKF6DhbvJGhyUSdcJDltxAVVCGlYTYKGQBAfOgA1hkGSK/YsWHPnzuXVV1/tw5+sdCzpi/oUS/imphvhMGexmVF2N/W2HOp8IRr8ITKTXAQ9KooeIKDYqTRnYbY5cVpdBDx1BDQPZtWMifDvqkn3o/gqyTKpOEIqen09itCx4IfGgxQp4XLUeYPkG1WYVQXDMLD6KthflYShmKn16SS5rOSYEhGVBwgE/BQ5JpIbf6jT5/OCyUuOUQSGQrWeTmp8+J5Z7PZSqzjIt+zDrpXS4IunKHEMufGuro/tznmPc2EYgpIaH3Xe4IC5j8hrlBSLaJ5lv3zuDznn9ocjw66rd5JrTyLNZSJO85HUTtZcGb0kDTYx19hAIIDFYul6R8BsNhMMBmMuFMBrr72GyWTi1ltvbX7Nbrdz00038eWXX1JSUtLpsVOmTGnuYAGMGTOGc889N+Jm8cknn1BdXc3tt98ecfz8+fPxeDy8/fbbMZ+zW3QN0+4VpJm8hOKHUevT8AUCeAIa9UERbrzn5IfD+3a+Gx6RlroUVeMwdxpkjkVTrXxkTMYt4hhld5OVYItoHKqqiqoH8BkWytQs6hJPoC5xDOWWoXjMKQhhAEp4oU9DP/w2igGGhgKYVDCj4wxWEecrJdGmkBtnoGg+FJMVu1ZPUuggQd0goEOCI5xdT1VNkVmwuvDss8/2+s9SOnb1RX2aMjyFedPzuwzXaxp8edU7iYqcc0lJiGe4UczxjgaSaEANNGJTdRQEFSKBGlMaWVk55KU6SbQpGIZOyABFVQkqdvyqEzi0JqbQUYSOAFQUXFaVOl+IOl+INGsIm+7BMMIzdXFGPSl135Jcu4384E6SaraiVe5ERaAqKgFvA0XVXvYVl6BU7yVTO4BFFZjQcXr3U1W6l/3Fe9FqD5Bu8hBnVTELDasK9Y0eSvaXULJ/P1p9JZmiCotJQcXA6i2juLSU/WXl4Vk+pQ6L2YSigNVbTvGBcg4crCDQWEe6NUicycAsQljR8DbWUlzVGO60+UID6j4ir1FSrKYMT+l0pu3MW37D+kI3k0akM+nqheEIlWHTUE1W4izG4ay5599D+UnzWVdcz7LV+9rN6i1JA1m3gnsLCwv55ptvutxv37593Tk9ABs2bGDUqFEkJEQuYjx16lQANm7cyLBhw9ocZxgGmzdv5sYbb2yzberUqbz//vvNa85t2LABgMmTJ0fsd/LJJ6OqKhs2bOCaa66J6ZwdqaiooLKyMuK1goLwrAw1hVBTiOJIJjfehahsQPjCEawWq5WhMoVtt0SbcbK9BAkpvmK8jnhc6BAIYFN1ND3cOKw1pTI+xYmiOCl2W6ltNJGkVWITITyKiyrNQYIzF9UIEQzVYzf8mFQFhIFAIJoajqopvPCwEKCqKJqBiiBkCIJqq8GRGLJg/eUvf+GXv/xlD35yknRYX9WnrpKddJaMwHVoCQNhtlLuGIXZOIhFCf/OlNSEExA0zcapeoCAYqXCnI2IzwYEHq+PTLWRFJMfYegoioJmsocfkgMQGgqCpsEYhAj/UUAAJqGhCh1MJmxmlQSbwkFfCFfQSxJ1WEUAhfBsvN3wY/jKMQmVOMBJHIrmA5MVlylEotFAnC98b3CaBXbDiyIEJhVchgfhLURXLKjxI3AFgigmC4oicIUaEZ49KKqZFJOKIyRQAg0YQmDXGxhqFFHqO46A4iDRYRlQqdDlNUrqLU3XiX+t3MBV502LOWsuIPMGSINKt2rqL3/5y+bZp87+/OpXv+p2wcrKysjOzm7zetNrBw4caPc4t9tNIBCI6tiysjJMJhMZGRkR+1mtVlJTU5v3i+WcHXn00UcZN25cxJ85c+YAsOnrL2moq2F/RRWhUIiygxWU2MewPZiBbk/l22+/xePxcLC6lhp3Jd9uXMvChQvxer3MnTsXCD/sDfDAAw+wZcsWXn75ZV5++WW2bNnCAw88ELHP3Llz8Xq9LFy4kLVr17J8+XKefvppCgoKWLBgQcS+119/PW63m0WLFrFq1SpWrFjBkiVLKC0tZd68eRH7zps3j9LSUpYsWcKKFStYtWoVixYtwu12c/3110fsu2DBAgoKCnj66adZvnw5a9f2zWdK1tzcc/ddHX6mjz9ZyT1PreC1ld8wMtXK01/VopzxU1bt9eFyOCjaV0DAgF1aNtUkoygqXq+HwqoGNm3aRG6Kk6qaWgzDIKQbVGhxGKEAVpNKXHwibs1GAAuekIGGSrXuoiZpPEV6OlWNQQrKagmEQhiaRlCYqFWTqAw58LmGUlxeRVFVIzt37aKxvgZ3XQPL3/mgy+8pPT190H1PR2PdO1o+09ChQ4/4Z9J0g4vv+xurtpVA1R7S3Zv5ZsNGFi7/Fu+Mv3LXp1a0GY9wzbpR/CbpD3wQGEuSy87QQAGh6mL2lxRRVrgTm6qDMKgQCRR5zAxJshF0H8CkqpR5Ffw6qBjUaFYqQg4aqg+S6LBQ7m5AV21oqASFmQAW3CTgtWVQGnTiM8WjGQAqXp+PoA4+nxdNKGiYwgM0ito8mq8fmt0yhIGuhQgGAoT08L9D/vCyI8IwUIRA1zRQFAzdAASKEOHjgj78fh8oKj5/ABBgGAggGAyihUIYhnGo7ykQenjmv7a2FoBNmzYRDAYpraiioa6Grz79sN/qHnDM/j7Jz9S7n+mtL7fy+upNDLH6mWCv4g8PP3T4M5nMzL75fsidxgP/+xJbvt3Oyy+/zKv//D9OTfZQvXMt6wvdnH/VjwfUZzoav6fB9pk+++wzBqqYk5M899xzMb9J05cYi/z8fEaPHs0777wT8frevXvJz89n8eLF/OxnP2tzXElJCbm5uTzyyCPce++9EduefvppbrrpJjZs2MCECRO46aabeOWVV/B6vW3Ok5uby6RJk3jjjTdiOmdHOppxmzNnDltXvsHYXX/D0IMUhxKp9YYisyA5D42WNpSHU9he9Dc549YLokmQoPnq+ffWOj6uiOcm9U0m+76ksa4Ct+7C7nCQ4VTAV0NVYwhFDxA0x5OVNxrTobX3DEPHW7QBW6iGAFa8cXmkZecBh5McjNT34AzVUKcmUpd0IrmprsPbvbFnwVq+fDmXXHJJ3/3gpGNKf9SnrpIRdJR0yNjxDhVFO/AHAqQmuGgMCsyegwQVK5Xm7BaLe0NxVSMZtRuwiCCl5jxIzDm8rdpDYu12nEYDIAhZk3DmTmxOKuRvrGO4thebCOAxJ7HHdBwJjnCyj4CnjuHaPmwmCOoGmqFQmzCKoMlJnTdEujVATmAf6AECwkKhKQ+bwwkCdH8Dw/RirCqEdIEmoMY5HM3kxBcIRpxXNwxqHHkIsxNPQCPJEiIjWILQgwSFmQOmHExxGRiKacDdR+Q1SupN6wrdFH2zist+EFud0nSjz5Y6kQa3oyo5SXc6Yd3hcDgIBAJtXvf7/c3bOzoOiOpYh8PR4TN4fr8/Yr9oz9mRjIyMNjN7zZKHt1kcurkBcajxjvCQp9eEG+9pozt9Lyk6XT0Dp6WdEG4cVpmZfFwKk05fiLrzLeJ2vIO3aAd+vx+P1UWZbSwfmyeSGdrPRN9XeEq3EpeUjmq2gRZAFRo6JkJY8FrC2UdVRSE3xYkwBL4agRkTZrOZ3BTH4cWHU5wgPFjqS6iyO0k5fiamKFIX19TU9MnPSzo29Ud96izMubOkQ+oJF5N2cDs7istYU2WEB1xSwgMu8XXFuOtdVITCAy65Rg1VagKKHsBCiKwke/Pv3rAUF8X1yTiMelQUnElZqGq4HLkpTooNA6PWQBOCKiOBxPgW12wEvlorSjDc6RPWJLLT08KdPsVLpQcSDQtOrRGf6sQel3R4sKbaire2AkLhYw1rEtnZQ8PHVnsizmtYk8jOyW3uTJZ5griEHafuw6fGocZnMazVINBAuY/Ia5TUm6YMT2HLx7HXKbNJlZ02adAZsAtYZGdnt7uMQFlZGQA5OTntHpeSkoLNZmver7Njs7Oz0XWdioqKiE5VMBikurq6eb9YztkdGioftV4cuoeNd6lrvdU4/LAyiUkj0rnglCF8+ubTJBR9wHBPBRnOIBVeg0LrBNKSTCT49hNXX0B1KInUxATQA6R6KylXEtmv5jDEEiSucic4Di8+nNeNLFhnnXVWH/7UpGNNf9WnjhpU0SQdWr3Lyfoqd7cGXDDZcNfVE2fU41PDzy2b6qqIUxVUsw1VC5JruLvd6etssKazY3ty3oF2H5HXKKm3yTolHSsGbA9gwoQJfPLJJ9TX10ckKFmzZk3z9vaoqsr48eNZv359m21r1qzhuOOOa04i0nSO9evX8/3vf795v/Xr12MYRvP2WM7ZHa99vZ9yWqSwrdrZvDh0dxvvUnR6pXE44vA+51w6jydXncvbuzcy1KVTajKRM3ICN585AmX7m+z57F+YaosQdQ0YiplC8wnUHfc99qaejbLzHc5RvuZ4UxWKHjycBev4mZRXjWddcT1i9b4uH6ResmQJixcv7u0flXSMGmj1qa8HXFTRQENQRU+bxPBTLmHVririSz5iuKeCTFf497Kgm50+tI4HawyTtcNje3LegXgfGWh1Shr8ZJ2SjhUxP+N2pKxZs4ZTTjklYh23QCDAuHHjSE1N5auvvgKguLgYr9fLmDFjmo995JFHuP/++1m3bl1zxsidO3cyduxY7r77bv74xz8C4XXchg4dymmnncZbb73VfPy1117L66+/TklJCSkpKTGdMxZNMbSX/P4Vzjt9SseLQ6eMQD9+JssONd67WoRS6h3rCt0dZqTs7Bkcf1Bj4dvbKa/zt9muhYL8a8VHfLG9ELM9gdHjJnPz2ccDhDNb7qvke+m1XDouEbMjIRzOZDJ3/jyeJElAN56NO7SPphs8sXIX33z9FRk2je/kD+XSGedgtljRdIMnV+3mQMFGvpNuJmh28nFVMpNGpHNDy06fWoEqNBqCCnpSXmSnT60gw2miwqtTaGRQlxs5WDPSXEl1vYf6Do7t7nmPt1ShyPuIJElSTAbyM24DtuMG4cwxy5cvZ8GCBYwcOZLnnnuOtWvX8tFHHzVPi0+fPp1Vq1bR8mM0NDQwceJEGhoauPvuu7FYLPz1r39F13U2btxIenp6876PPvoo8+fP57LLLmPGjBmsXr2a559/noceeqg5k02s54xWU8X4xdPv8OvrZrRJjNEyha1svA88HXXsumo8frWnikXv7+J7J2RGdupafL/zpue3mQ3sanuT2bNnRwxESFJPDLb61N0Bl45+LyH8u/f4qr28vmE/SU5rxD7RdPpKd2/EangJqk6GHD8hYrBm/d4KsoLFOIWXkcOyI45tOq8DH6edMJzLZ54b9XkH8iDQYKtT0sAn65TUmwZyxw0xgPl8PnH33XeLrKwsYbPZxJQpU8SKFSsi9jn77LNFex+jpKREXHbZZSIhIUHExcWJCy+8UOzevbvd93niiSfE6NGjhdVqFfn5+WLx4sXCMIwenTMaW7duFYDYuGlz1MeENF08+kmBuPGZtWLtvupuv7fUt9buqxYhTY95e0jTO/1eu9ouSVLnOvvd7GzblwWV4gePfi4e/aSgzT6dbQtpunjg9c3i5N+9Lx54fXPE9s62NZ33nD9/Is758yfiyz1VMZ23s/uEvI9IkiR1rKl9vnXr1v4uShsDesbtaNfdHr1MYSt15vrrr+/Wsh2S1B5Znw7rajavo22abvDy2mKumprbbvhmR9sgPBOIonDKcakxn7ez+0R/3kdknZJ6m6xTUm8ayDNusuPWjwZyxZAGL7fb3fxspiT1lKxPUm+TdUrqbbJOSb1pILfP5QNSknSUeeqpp/q7CNJRRNYnqbfJOiX1NlmnpGOF7LhJ0lFm6tSp/V0E6Sgi65PU22SdknqbrFPSsWLAruN2LAgEAgAUFBT0c0mko8mOHTtIS0vr72JIRwlZn6TeJuuU1NtknZJ6U1O7vKmdPpDIjls/2rJlCwBz5szp34JIkiRJkiRJktRsy5YtTJo0qb+LEUF23PrRqFGjAHj11Vc58cQT+7k00tGgoKCAOXPm8MYbbzBy5Mj+Lo40yMn6JPU2Waek3ibrlNTbvv32W+bOndvcTh9IZMetHyUkJABw4oknDrisNdLgNnLkSFmnpF4j65PU22SdknqbrFNSb2tqpw8kMjmJJEmSJEmSJEnSACc7bpIkSZIkSZIkSQOc7LhJkiRJkiRJkiQNcLLj1o/S09P59a9/TXp6en8XRTpKyDol9SZZn6TeJuuU1NtknZJ620CuU4oQQvR3ISRJkiRJkiRJkqSOyRk3SZIkSZIkSZKkAU523CRJkiRJkiRJkgY42XGTJEmSJEmSJEka4GTHTZIkSZIkSZIkaYCTHTdJkiRJkiRJkqQBTnbc+kEgEOC+++4jJycHh8PBtGnT+OCDD/q7WFI/WbduHT/5yU8YO3YsLpeL3Nxc5s6dy65du9rsu337dmbOnElcXBwpKSlce+21VFZWttnPMAz+9Kc/MWLECOx2OyeddBKvvPJKu+8f7Tmlweuhhx5CURTGjRvXZtsXX3zBGWecgdPpJCsrizvvvJPGxsY2+8Vy3Yr2nNLg8s0333DRRReRkpKC0+lk3Lhx/O1vf4vYR9YnKVq7d+/miiuuYOjQoTidTsaMGcPvfvc7vF5vxH6yTkmtNTY28utf/5qZM2eSkpKCoig8++yz7e7bn+2mWM4ZNSEdcVdccYUwm83i7rvvFo8//rg49dRThdlsFqtXr+7vokn94NJLLxVZWVnijjvuEMuWLRMLFy4UmZmZwuVyiS1btjTvV1JSItLS0kR+fr743//9X/HQQw+J5ORk8Z3vfEcEAoGIc95///0CELfccot44oknxKxZswQgXnnllYj9YjmnNDiVlJQIp9MpXC6XGDt2bMS2DRs2CLvdLiZOnCgee+wx8eCDDwqbzSZmzpzZ5jzRXrdiOac0eLz33nvCarWKadOmib/+9a/iiSeeEPfdd5+45557mveR9UmKVnFxsUhKShJ5eXniD3/4g3j88cfFj370IwGIiy66qHk/Waek9uzbt08AIjc3V0yfPl0A4plnnmmzX3+3m6I9Zyxkx+0IW7NmjQDEokWLml/z+XwiPz9fnHrqqf1YMqm/fP75521+2Xft2iVsNpu4+uqrm1+77bbbhMPhEEVFRc2vffDBBwIQjz/+ePNr+/fvFxaLRcyfP7/5NcMwxJlnnimGDh0qNE2L+ZzS4PXDH/5QnHPOOeLss89u03G74IILRHZ2tqirq2t+bdmyZQIQ7733XvNrsVy3oj2nNHjU1dWJzMxMcckllwhd1zvcT9YnKVoPPfSQAMTWrVsjXr/uuusEINxutxBC1impfX6/X5SVlQkhhFi3bl2HHbf+bDfFcs5YyI7bEXbPPfcIk8kUccEQQoiHH35YAKK4uLifSiYNNJMmTRKTJk1q/n9GRoa4/PLL2+w3atQoce655zb/f8mSJQIQ27Zti9jv5ZdfFkDE6GO055QGp1WrVgmTySQ2b97cpuNWV1cnzGZzxIyJEEIEAgERFxcnbrrppubXor1uxXJOafB47LHHBCC+/fZbIYQQjY2NbTpwsj5JsbjvvvsEICorK9u8rqqqaGxslHVKikpnHbf+bDfFcs5YyGfcjrANGzYwatQoEhISIl6fOnUqABs3buyHUkkDjRCCgwcPkpaWBkBpaSkVFRVMnjy5zb5Tp05lw4YNzf/fsGEDLpeLE044oc1+TdtjPac0+Oi6zh133MHNN9/M+PHj22zfsmULmqa1+f6tVisTJkxoU6eiuW7Fck5p8Pjwww9JSEigtLSU0aNHExcXR0JCArfddht+vx+Q9UmKzfTp0wG46aab2LhxIyUlJfzzn//kscce484778Tlcsk6JfVIf7eboj1nrGTH7QgrKysjOzu7zetNrx04cOBIF0kagF566SVKS0v54Q9/CITrDdBh3XG73QQCgeZ9MzMzURSlzX5wuI7Fck5p8Fm6dClFRUUsXLiw3e1dff8tr0XRXrdiOac0eOzevRtN07j44ouZMWMG//73v7nxxhtZunQpN9xwAyDrkxSbmTNnsnDhQj744AMmTpxIbm4uV1xxBXfccQeLFy8GZJ2Seqa/203RnjNW5m4dJXWbz+fDZrO1ed1utzdvl45tO3bsYP78+Zx66qlcf/31wOF60VXdsdlsUdexWM4pDS7V1dX86le/4pe//CXp6ent7tPV99/yWtRbdUpe3wanxsZGvF4v8+bNa84i+YMf/IBgMMjjjz/O7373O1mfpJgNHz6cs846i0svvZTU1FTefvttHn74YbKysvjJT34i65TUI/3dbuqr9r7suB1hDoej3VmMpnATh8NxpIskDSDl5eXMmjWLxMREXnvtNUwmE3C4XkRTd6KtY7GcUxpcfvGLX5CSksIdd9zR4T5dff8tv/veqlOyPg1OTd/blVdeGfH6VVddxeOPP86XX36J0+kEZH2SovN///d/3HrrrezatYuhQ4cC4cEAwzC47777uPLKK+U1SuqR/m439VV7X4ZKHmHZ2dnNU60tNb2Wk5NzpIskDRB1dXVccMEF1NbWsmLFioi60DS13lHdSUlJaR7Zyc7Opry8HCFEm/3gcB2L5ZzS4LF7926eeOIJ7rzzTg4cOEBhYSGFhYX4/X5CoRCFhYW43e4uv//W9S+a61Ys55QGj6bvLTMzM+L1jIwMAGpqamR9kmLy6KOPMnHixOZOW5OLLroIr9fLhg0bZJ2SeqS/203RnjNWsuN2hE2YMIFdu3ZRX18f8fqaNWuat0vHHr/fz+zZs9m1axf//e9/OfHEEyO2DxkyhPT0dNavX9/m2LVr10bUmwkTJuD1etm+fXvEfq3rWCznlAaP0tJSDMPgzjvvZMSIEc1/1qxZw65duxgxYgS/+93vGDduHGazuc33HwwG2bhxY5s6Fc11K5ZzSoPHySefDITrVktNz2ikp6fL+iTF5ODBg+i63ub1UCgEgKZpsk5JPdLf7aZozxmzbuWilLrtq6++arPWiN/vFyNHjhTTpk3rx5JJ/UXTNHHRRRcJs9ks3n777Q73mzdvnnA4HBFLRnz44YcCEI899ljzayUlJR2uHTJkyJCItUOiPac0eFRWVorly5e3+TN27FiRm5srli9fLjZv3iyEEGLmzJkiOztb1NfXNx//5JNPCkC8++67za/Fct2K9pzS4PHNN98IQFx11VURr1955ZXCbDaL0tJSIYSsT1L0LrzwQmG1WsXOnTsjXp8zZ45QVVXWKSlqnS0H0J/tpljOGQvZcesHl19+efM6Io8//rg47bTThNlsFqtWrervokn94Kc//akAxOzZs8ULL7zQ5k+T4uJikZqaKvLz88Xf/vY38fDDD4vk5GQxfvx44ff7I855zz33CEDceuutYtmyZWLWrFkCEC+99FLEfrGcUxrc2luA++uvvxY2m01MnDhRPPbYY+LBBx8UdrtdnH/++W2Oj/a6Fcs5pcHjxhtvFICYO3euWLJkibj88ssFIH7+85837yPrkxStpjUmMzIyxO9+9zuxZMkSccEFFwhA3Hzzzc37yToldeTvf/+7WLhwobjtttsEIH7wgx+IhQsXioULF4ra2lohRP+3m6I9Zyxkx60f+Hw+cffdd4usrCxhs9nElClTxIoVK/q7WFI/OfvsswXQ4Z+Wtm7dKs4//3zhdDpFUlKSuPrqq0V5eXmbc+q6Lh5++GGRl5cnrFarGDt2rHjxxRfbff9ozykNbu113IQQYvXq1eK0004TdrtdpKeni/nz50eMRDeJ5boV7TmlwSMYDIrf/OY3Ii8vT1gsFjFy5EixePHiNvvJ+iRFa82aNeKCCy4QWVlZwmKxiFGjRomHHnpIhEKhiP1knZLak5eX12G7ad++fc379We7KZZzRksRotVTc5IkSZIkSZIkSdKAIpOTSJIkSZIkSZIkDXCy4yZJkiRJkiRJkjTAyY6bJEmSJEmSJEnSACc7bpIkSZIkSZIkSQOc7LhJkiRJkiRJkiQNcLLjJkmSJEmSJEmSNMDJjpskSZIkSZIkSdIAJztukiRJkiRJkiRJA5zsuEmSJEmSJEmSJA1wsuMmSZIkSZIkSZI0wMmOmyRJknTU+NGPfsTw4cP7uxjNfvOb36AoCoqiEBcXd8Tff8KECc3vf+GFFx7x95ckSZJ6j7m/CyBJkiRJnVEUJar9Pvnkkz4uSfe98MILWCyWI/6+Dz/8MG63mwULFhzx95YkSZJ6l+y4SZIkSQPaCy+8EPH/559/ng8++KDN6yeccALLli3DMIwjWbyoXHPNNf3yvt///vcB+MUvftEv7y9JkiT1HtlxkyRJkga01p2er776ig8++KDfOkOSJEmS1B/kM26SJEnSUaP1M26FhYUoisKf//xnlixZwnHHHYfT6eT888+npKQEIQQLFy5k6NChOBwOLr74Ytxud5vzvvvuu5x55pm4XC7i4+OZNWsW27Zt61FZhw8fzoUXXsjKlSuZPHkyDoeD8ePHs3LlSgBef/11xo8fj91u5+STT2bDhg0Rx5eXl3PDDTcwdOhQbDYb2dnZXHzxxRQWFvaoXJIkSdLAJGfcJEmSpKPeSy+9RDAY5I477sDtdvOnP/2JuXPncs4557By5Uruu+8+CgoK+Pvf/87dd9/N008/3XzsCy+8wPXXX8+MGTN45JFH8Hq9PPbYY5xxxhls2LChR8lQCgoKuOqqq/jxj3/MNddcw5///Gdmz57N0qVLeeCBB7j99tsB+MMf/sDcuXPZuXMnqhoec7300kvZtm0bd9xxB8OHD6eiooIPPviA4uLiAZWgRZIkSeodsuMmSZIkHfVKS0vZvXs3iYmJAOi6zh/+8Ad8Ph/r16/HbA7fDisrK3nppZd47LHHsNlsNDY2cuedd3LzzTfzxBNPNJ/v+uuvZ/To0Tz88MMRr8dq586dfPHFF5x66qkAnHjiicyYMYNbbrmFHTt2kJubC0BycjI//vGP+fTTT5k+fTq1tbV88cUXLFq0iLvvvrv5fD//+c+7XRZJkiRpYJOhkpIkSdJR7/LLL2/utAFMmzYNCD8/19Rpa3o9GAxSWloKwAcffEBtbS1XXnklVVVVzX9MJhPTpk3rcSbLE088sbnT1rJc55xzTnOnreXre/fuBcDhcGC1Wlm5ciU1NTU9KoMkSZI0OMgZN0mSJOmo17ITBDR34oYNG9bu602dod27dwPhjlR7EhIS+qVcNpuNRx55hLvuuovMzExOOeUULrzwQq677jqysrJ6VCZJkiRpYJIdN0mSJOmoZzKZYnpdCAHQvLTACy+80G6HqOVs3ZEsF8DPfvYzZs+ezRtvvMF7773HL3/5S/7whz/w8ccfM3HixB6VS5IkSRp4ZMdNkiRJkjqQn58PQEZGBt/73vf6uTRt5efnc9ddd3HXXXexe/duJkyYwF/+8hdefPHF/i6aJEmS1MvkM26SJEmS1IEZM2aQkJDAww8/TCgUarO9srKyH0oFXq8Xv98f8Vp+fj7x8fEEAoF+KZMkSZLUt+SMmyRJkiR1ICEhgccee4xrr72WSZMmccUVV5Cenk5xcTFvv/02p59+Ov/4xz+OeLl27drFueeey9y5cznxxBMxm80sX76cgwcPcsUVVxzx8kiSJEl9T3bcJEmSJKkTV111FTk5Ofzxj39k0aJFBAIBhgwZwplnnskNN9zQL2UaNmwYV155JR999BEvvPACZrOZMWPG8Oqrr3LppZf2S5kkSZKkvqWIlk86S5IkSZLUa37zm9/w29/+lsrKShRFITU19Yi+f21tLZqmMWnSJE466ST++9//HtH3lyRJknqPfMZNkiRJkvpYeno6eXl5R/x9p0+fTnp6OiUlJUf8vSVJkqTeJWfcJEmSJKmP7N27t3nRbLPZzPTp04/o+69Zs4aGhgYg3Hn8zne+c0TfX5IkSeo9suMmSZIkSZIkSZI0wMlQSUmSJEmSJEmSpAFOdtwkSZIkSZIkSZIGONlxkyRJkiRJkiRJGuBkx02SJEmSJEmSJGmAkx03SZIkSZIkSZKkAU523CRJkiRJkiRJkgY42XGTJEmSJEmSJEka4GTHTZIkSZIkSZIkaYCTHTdJkiRJkiRJkqQBTnbcJEmSJEmSJEmSBjjZcZMkSZIkSZIkSRrg/j+2HHV6EbaxSQAAAABJRU5ErkJggg==\n", 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gkHHalTF1FI1G0+L9O+aYYwCCxi+IbDZs2BBuEQT9jL6uU2WFO0hz7mbggU/RSk0Sj3ha/nYKeoe+rlMCQUcR1SH7MInRRo4ZYG313JCkaBKivaTGmgLHfLLChz8fxKeqDEmO5rhBsfxUWMmz9SmLU2NNHDPASqxZ3+J6DfdJjDaGRParr76aF198keuuu46TTjqJ2NhYJEniggsuQFGCM3DNnTuX++67j7KyMqxWKx9++CEXXnghOl3/UN85c+bw7bffcuONNzJmzBiio6NRFIWZM2e2eC86QmJiYpvnurMq2dZeO1mWu3xNQeRz6aWXhlsEQT+jr+tUkucAnigDLq+CLWsc7HnXf8ItDLdw0dd1SiDoKN2a+XYkwYBITtJzTB6ayOShrU/SF07JDvq7IXvknpJaLpiQ0SI5CfgTlpwxOrXV6908c3gIJYfly5czb948HnzwwcAxl8uF3W5v0Xbu3LncfffdvPvuu6SkpFBdXc0FF1wQOJ+cnIzJZGLPnj0t+rZ2rDkNtQlzc3MDXjzwh3Dm5+dz/PHHB7XdsmULiqIEeah27twZdK0GcnNzW9xv9+7dZGZmAlBZWcnq1au5++67ueOOO9rt15bsO3bsQFXVgGG1b9++Do27s2OKi4sDaPEZteWRUxSFvXv3Brxs4B87EBi/IPJZvHhxq5ldBYKu0td1aoB8EOItEJuOGp1IjcuHrCh4y0pJygy3dEcnfV2nBIKO0i3D7a677mrznCRJgcmkMNzCS3sp/ztTpDuUaLXaFmnhH3vssVa9NyNGjGD06NG89dZbpKSkkJqayqmnnhp0rdNOO40PPviAgwcPBva57dmzh5UrVx5RlvHjx5OUlMSyZcu4+OKLA6GEL730Ugsj5YwzzuCzzz7jrbfeCuwJ8/l8PPbYY0RHR7cIDf7ggw84cOBAYJ/bhg0b+OGHH7juuusCsgMt3ouHH374iHIDzJgxg88//5wPP/yQs88+G4DU1FSeffbZDvXvzJgGDx6MVqtl/fr1zJ49O9D/ySefbPPajz/+OI8++ijgH+Pjjz+OXq9n+vTpHZZPEF7EZEgQavq0TqkqVOz1v44fAoZo9pbVoqrgOVBM0vjwine00qd1SiDoBN0y3FoL41IUhcLCQp544gnWr1/foYmzoOc4Up22tkoF9LTx9vvf/55XX32V2NhYjj32WL777ju++OILEhISWm0/d+5c7rjjDkwmE5deemmL/Vh33XUXn332GZMnT+aKK65AlmUef/xxRo0axc8//9yuLHq9nnvvvZfLL7+cadOmMXfuXPLz83nxxRdb7NH6y1/+wtNPP838+fP58ccfyczMZPny5XzzzTc8/PDDWK3BoatDhw7lN7/5DVdccQVut5uHH36YhIQEbrrpJgBiYmI49dRT+c9//oPX62XgwIF89tln5Ofnd+h9vPzyy3n88ce58MILufbaa0lNTeX555/HZPKHyHakhl1HxxQbG8v555/PY489hiRJZGdn89FHH1FSUtLqdU0mE6tWrWLevHlMmjSJlStX8vHHH3Pbbbd1uEyDIPzMmjWLFStWhFsMQT+iT+tUbQl46vyvE7KRtDpkrRmNz4nsbrnfXNA79GmdEgg6Q0+mrPzjH/+oXnjhhT15iz5NT5cDaJr+/0gp/zvTNhRUVlaqF198sZqYmKhGR0erM2bMUHfu3KkOHjxYnTdvXov2ubm5KqAC6tdff93qNVevXq2OHTtWNRgManZ2tvrcc8+p119/vWoymTok05NPPqlmZWWpRqNRHT9+vLp+/Xp1ypQpQeUAVFVVDx8+HJDdYDCoo0ePDkqFr6qNKfLvv/9+9cEHH1TT09NVo9GonnLKKeovv/wS1Hb//v3qOeeco9psNjU2NlY9//zz1YMHD6qAeueddx5R7r1796pnnnmmajab1aSkJPX6669X3333XRVQv//++0C7KVOmqCNHjmz1Gh0Zk6qqamlpqXruueeqFotFjYuLUy+//PKAHjcvBxAVFaXm5eWpv/vd71SLxaKmpKSod955pyrLvVt6orOIcgACgaAtDvyyWi1/ZrbqePFcVSnZpaqqqpZ+9qBa+dl/1LpfPw+zdH2XDfnlXZp3eH2yuiG/vAckEhzNRHI5AElVm8VohZCnn36am2++udV9SwLYvn07o0aNYtu2bYwcObLF+b17/eEYzb0+HeFInrZQ9Yl0Zs+ezfbt2zu8ZyxUFBQUkJWVxf33388NN9zQq/fet28f7777LosXL2b//v1B5Qh6i/nz57N8+XJqa/veZv3ufO/6I4sXL+ahhx4KtxiCfkRf1qkf3nsUY+7HIGkYdd376AymI3cStMvGggqWrc3r9Lyj6ZzFs+VjXl16V88KKuhTbCyoYGy6rdPzWJ+ssHz191w4Y3Kb8/Nw0qOz8k2bNrUIaRP0Dpv32TttgDWETY7PjGdTQQWb99l7XtAQ4nQ6g/7Ozc3lk08+YerUqeERqJdoPm6r1crTTz/NsGHDwmK0CfoXixYtCrcIgn5GX9Yptdxf59QTPVAYbSFibLotMO949qt8fPKRsyk3X2j++8I/9YKkgr5Cw2JAR/WpgQa9entjUQ9K1z26tcftlVdeafW43W5n/fr1vPfee1x22WXduYWgi0zIjIepdHq1odF4i/Nfow8xZMgQ5s+fz5AhQygsLOSpp57CYDAE9pP1V/7whz+QkZHBmDFjqKqq4uWXX2bnzp28/vrr4RZN0A9Yv359h+ohCgQdpS/r1ITT51NVtAW3NjrcovQb2t1rL/ugbJe/1IIxGhJz8KFpER30yssvkXNMy7qpgqOTposB0LHcDU0XA0amxfJ+bwjaBbpluM2fP7/Nc4mJidxyyy1BKc4FvUtXDS+dVtPnjDaAmTNn8uabb1JcXIzRaOSkk07iH//4R6tFsPsTM2bM4LnnnuP1119HlmVycnL473//y9y5c8MtmqAf0FAGQiAIFX1Zp7SDxhI/aGzQsV+27yB313ZUTy3nzZ3foaRQgmCaG2+S4mNBwha0uaugsgAUL2j0KHGZrJFP4CfHOMZnJQUm5H1ZpwShp7uLASfHm7g3nANoh24Zbq1lvpMkibi4uBbZ9QSCnubFF18MtwgBMjMzW6T47ymuu+66QHkBgLq6OqKionrl3m3x0ksv8dJLL4VVBkFoEOG2glDT33RKKfyOoblvA+B2XxjI6ivoHA2TbUnxkbrlcSp8G0jUOpDMcaAzovhc1O75hmHKLyxIK2Tc5CUBL0p/0ylB9+nOYsCunb+GV/h26Jbh1rzYsEAgCD9VVVVhN9wE/YdPP/2UiRMnhlsMQT+ir+qUWl+btjkWqw30WrQaCY+zWhhu3UCn1bAgYQsVvg143E4KrRlkWP2/Z0UVDuyYydCVMtj1HdKuFTDqXKDv6pSgZ+nOYkCk0i3DTSAQRB4pKSnhFkHQj7j++uvDLYKgn9FXdWr1K/fi9vqIGTKRU6adGTiek5EG+xqijJytdxZ0DNmHNncViVoHhdYM7E4flNWi8Tmp8umxRRmwxWUjle2CXSthxNmg1fVZnRL0PF1dDIhUesys3LdvH9OmTWP69Ok9dQuBQNAKBQUF4RZB0I9oby+zQNAV+qJOqYpCXOlGBpZ/j6FkS/BJY5OtIaIId/co2wWVBUjmODISoog166FqH1E1eSTKJWTEW9BotGCKg4p8f3v6pk4JeokmiwFeazp2p4/Ccgf7ymqwO7z+xYC0bCRXpX8xQPaFW+J26TGPm8PhYO3atWKTrkDQy2RnZ4dbBEE/4u233w63CIJ+Rl/UKXflAVKjwOnRYUzLCT5pbJJh0tP3aldGFO5a/94jnTFwyKpUAWD2VDS20xlA9vjb0zd1StBLNF0MsEahljswV+/FrDjQWTNJjY9FI0ktFgMilR7zuOXk5KAoCrIs99QtBAJBK/R2sXFB/2bWrFnhFkHQz+iLOmWqKSQt1kx2UjQjRh4fdE41RCMrKh6fQl2tPTwC9heM0f6EET4XRRUOqpxevIZYdBoJn8ZAUYUDRVXB5wGNPmA090WdEvQSzRYDNKoPk1KHqqpEOQ42ttMZ/O3ckb34Etk78AQCQafp7+UPBL3LihUrwi2CoJ/RJ3WqvvA2Gh3YMoJOKQYrWw9UseNQNTvy94dBuH5EYg6KbTC19lLsdR5sFj0ptmhizHosOhW7w0tReR2qsxLisyDR7/3skzol6B2aLQa4HLWoqoqiqnh93jYXAyIVYbgJBP2M/fvFxEEQOm677bZwiyDoZ0SiTm0sqMAnK203qKwvf2TLAK0+cNgnK/x0oA5VawBAdoo9bt3Bh4bVyngqlGgyNKVkxJmQNHokIEovYTNp0Vfvo0y2IA+bCVr/jp9I1ClBhNBsMSBO70Ov1fizwGqj2lwMiFS6vcetuLiY559/np9++omqqioUJfjBJ0kSq1ev7u5tBIKwMHXqVADWrl0bVjk6Q3x83yueLohcLrzwwnCLIOhnRJpObSyoYNnaPMZnxjcW6W2Cqsgczt9BlNaHMWYwhvrjPlkJFO39a2wK8SbQpib2/gD6CQ3v50+OcSxIK/Rn+SvbBV4XyB4kVWGwtoAyk5VvdJMoLhvNZbKCTquJOJ0SRA4+NKxRxjNM2UKGrhSzRkKj1WA06rEMGIG30uFfDDBZiB82E602shPud0u6LVu2MHXqVJxOJzk5OWzdupVjjz0Wu93OgQMHyM7OJj09PVSyCgSCDuB0OrFYLOEWQ9BP2Lp1K6NHjw63GIJ+RKTp1Nh0G+Mz49lU4E9+0dx4Kz1YQHGFP0GGNCSJ4wk22sZnxpNzyjMRX/8pkgl6P7OSGDd5iT81+66V1G3/BEn1OwK06aOJP+58istGs7GoGvWrfBackhVxOiWIDFpbDPCU5CKr4FY0xNQdZrBcSZnJErQYEMl0y3C75ZZbiI6O5ueff8ZisZCcnMwjjzzCtGnTeOedd7jiiit4/fXXQyWrIFTIPn/WHHetP5Y3MScQbiAQCAQCwdFEQ5FeoKXxJvuo+/UzLHINiqQlauCwFkZba146Qcdp8/0cdS5Kzu/Zt/s0NKqMImnRj7qa7ON+w2WyglrfByBaDfMgBBFHa4sByvb3qFvxN4yqE61WD1o9UsYk4ofNDFoMODk+co23bs3Wv/nmG2666SYyMjKoqPB/eRpCJc8//3y+/vprbrzxRtatW9d9SQXdR/bBjg/8dSoqC/zZczR6f0zvMTPh2NnCgOsHmM3mcIvQIerq6oiKigq3GIIjIFaxBaEmEnWqufEmKT4WJGxBm7uKrLJcZEsdsteLZvNDrPlpAj85xjE+K0kYbSFg8z57m0awosjoLDHUuvy1tRSH3/PZ/PP6v3SRlEvQSFuLAeqoc9CbUqjJ/QqjNZ6otGMg61S0elPQYsDB/LJwD6FNuvW0URSFlJQUAGw2G1qtNmDAgf/h/OOPP3ZPQkFokH3w1QPw7aOwfwPIXtAa/f/v+8F//KsHe63wYGFhIVdeeSU5OTmYzWYSEhI4//zzg4pHb9q0CUmSePnll1v0//TTT5EkiY8++ihwbO3atYwfPx6TyUR2djZPP/00d911V4drCT7zzDNkZ2djNpuZOHEiX331VavtSkpKuPTSS0lJScFkMnH88ce3kLGgoABJknjggQd46KGHGDx4MGazmSlTprBt27agtlu2bGH+/PkMGTIEk8nEgAEDuOSSSygvLz+izA21Et9++23uu+8+Bg0aRHx8PNOnT2fPnj0t2r/zzjuccMIJmM1mEhMTueiiizhw4EBQm/nz5xMdHc2BAweYPXs20dHRJCUlccMNN7Qo71FeXs7/+3//j5iYGGw2G/PmzeOXX35BkiReeumlFtfMy8vjjDPOwGq18qc//QnwG3DXX3896enpGI1GcnJyeOCBB1DVxiXUhvez6TUbkCSJu+66K/B3w2e+c+dO5syZQ0xMDAkJCVx77bW4XK4jvqeCYN58881wiyDoZ0SqTjUYAxMyYkjd8jgVnz+Aum8DANroZHTWBBx7v2NY3gsskN5nweT0gJGx51AZn23Yysr134VzCH2SCZnxLJya3aoRrFN9DEmMYlhKNMeMGs+w0RMbz9V/XgunZrNl9fu9LbYggmlrMUDSGbEO/y2+tAlU/rKS3R8/TEX5YaBRn8ZnxrP9YFU4xW+XbhluWVlZ5Of7My1pNBqysrL44osvAue//fZbbDZbl6/vdru5+eabSUtLw2w2M2nSJD7//PMO9T1w4ABz5szBZrMRExPD2Wefzd69e1tt+/zzzzNixAhMJhPDhg3jsccea7XdF198wW9/+1sSExOx2WxMnDiRV199tcvj61V2fAC7PgGfG5KGQ0wqWOL9/ycN9x/f9TH8+r9eEWfjxo18++23XHDBBTz66KMsXLiQ1atXM3XqVBwOBwDjx49nyJAhrRbWfOutt4iLi2PGjBkAbN68mZkzZ1JeXs7dd9/NpZdeyj333MMHH3zQIXmef/55Lr/8cgYMGMB//vMfJk+ezFlnncW+ffuC2jmdTqZOncqrr77Kn/70J+6//35iY2OZP38+jzzySIvrvvLKKzz66KMsWrSIW2+9lW3btjFt2jQOHz4caPP555+zd+9eLr74Yh577DEuuOAC/vvf/3LGGWcEGS/t8a9//Yv333+fG264gVtvvZXvv/8+YBg18NJLLzFnzhy0Wi3//Oc/WbBgAe+99x6/+c1vsNvtQW1lWWbGjBkkJCTwwAMPMGXKFB588EGeeeaZQBtFUZg1axZvvvkm8+bN47777uPQoUPMmzevVRl9Ph8zZswgOTmZBx54gHPPPRdVVTnrrLN46KGHmDlzJkuXLiUnJ4cbb7yRv/71rx0ae1vMmTMHl8vFP//5T8444wweffRR/vKXv3Trmkcj//jHP8ItgqCfEck6pdNqWJCwhZN9G/C4nRRqM1CsA1DMcRR5Y9lLBjE6mQmu79DtakxBX/XjuySvuYHU7+7G6+udBdD+xITM+NY9l7IXjSQRZdBhyfktemtS0GmdVsOEzPiI1ilB79PeYgCAQxNNtcuHwyNTW9XocGow3uZMyGjRJ2JQu8H111+vDhs2LPD30qVLVUmS1OnTp6vTpk1TNRqNeuONN3b5+hdccIGq0+nUG264QX366afVk046SdXpdOpXX33Vbr+amhp12LBhanJysvrvf/9bXbp0qZqenq4OGjRILSsrC2q7bNkyFVDPPfdc9ZlnnlH/3//7fyqg/utf/wpq97///U+VJEk9+eST1ccee0x9/PHH1VNPPVUF1KVLl3ZpfNu2bVMBddu2ba2ez8vLU/Py8rp07SB8XlV95xJVfWiUqr52nqq+Pqflv9fO859ffqm/fQ/jcDhaHPvuu+9UQH3llVcCx2699VZVr9erFRUVgWNut1u12WzqJZdcEjg2a9Ys1WKxqAcOHAgcy83NVXU6nXokNfd4PGpycrI6ZswY1e12B44/88wzKqBOmTIlcOzhhx9WAfW1114L6n/SSSep0dHRanV1taqqqpqfn68CqtlsVvfv3x9o+8MPP6iAunjx4nbfizfffFMF1PXr17cr+5o1a1RAHTFiRED23bt3q4888ogKqFu3bg0a46hRo1Sn0xno/9FHH6mAescddwSOzZs3TwXUe+65J+heY8eOVU844YTA3++++64KqA8//HDgmCzL6rRp01RAffHFF1tc85Zbbgm65gcffKAC6r333ht0/LzzzlMlSVL37Nmjqmrj+9n0mg0A6p133hn4+84771QB9ayzzgpqd+WVV6qA+ssvv7S4RlNC9r3rJ/z+978PtwiCfkZE61T976WydJSa/8gZ6uZ//U7d+8iZ6t5HzlQ3/+t3av6jZ6ryq+e2+L385Ys31M3/+p36y79/p9ory8M8iH5E1cHGecredW02i2idEkQcB/O2qjsfPF3d8/AZ6qFtLW2KI83Pw0m3PG5/+9vfePPNN/F6vQBcd9113HPPPZSXl1NVVcXtt9/Ovffe26Vrb9iwgf/+97/885//5P777+cvf/kLX375JYMHD+amm25qt++TTz5Jbm4uH330ETfddBOLFy/ms88+49ChQzz44IOBdk6nk7/97W+ceeaZLF++nAULFvDKK6/wpz/9iSVLllBZWRlo+/jjj5OamsqXX37JVVddxaJFi1i9ejXZ2dmthm/1CnvXwhd3tf/vx5f8iUgqC8AU50+rW7qr5b+yXPA6If8r+Oi6lvdq6/p713ZJ9Kb7sLxeL+Xl5QwdOhSbzcZPP/0UODd37ly8Xi/vvfde4Nhnn32G3W5n7ty5gN879MUXXzB79mzS0tIC7YYOHcrpp59+RFk2bdpESUkJCxcuxGAwBI7Pnz+f2NjYoLaffPIJAwYMCEo9rNfrueaaa6itrW2xn3P27NkMHDgw8PfEiROZNGkSn3zySavvhcvloqysjBNPPBEg6L1oj4svvjgg+7BhwzjllFMAAl7mhjFeeeWVmEymQL8zzzyT4cOH8/HHH7e45sKFC4P+PuWUU4K81qtWrUKv17NgwYLAMY1Gw6JFi9qU84orrgj6+5NPPkGr1XLNNdcEHb/++utRVZWVK1e2O+72aC7H1VdfHbinoOOIwraCUBPROlX/eymZ48hIiMIm1SJV5OG1HyDGqCEj3oJGo/X/nlbk+9sDIwanMXpQLMcNshGrESHZocLpclLl9FLj8lIna9tsF9E6JWiXI9ZQbAOfrLCxoOLIDetRFYV1T13Nl6/cS83hAnIGWMlOimaAsW99X7tluMXFxXHCCSeg1/uLUUqSxN///nc2b97Mpk2buOuuu4Imwp1h+fLlaLXaoNAmk8nEpZdeynfffdcihK153wkTJjBhwoTAseHDhzN9+vSgsLs1a9ZQXl7OlVdeGdR/0aJF1NXVBU1mq6uriYuLw2g0Bo7pdDoSExPDlwyithRKfm3/X2WBP3uk4gWdEVQZPLWt/5M94HVA2e6W92rr+rWlXRLd6XRyxx13BPY1JSYmkpSUhN1up6qqMbb4+OOPZ/jw4bz11luBY2+99RaJiYlMmzbNL1pJCU6nk6FDh7a4T2vHmlNYWAj4DZ6m6PV6hgwZ0qLtsGHD0GiCvzojRowIulYDza8JcMwxxwTt5auoqODaa68lJSUFs9lMUlISWVn+TddN34v2yMhodOvn5eURFxcHEFh8aJArJ6dlYcnhw4e3kNtkMpGUFBySEhcXF7SYUVhYSGpqaovSA2295zqdjkGDBgUdKywsJC0tDavVGnS8rfezMzR/77Ozs9FoNEHvveDIzJkzJ9wiCPoZEa1TTX8vAZ23Dit1xCsVwfuldQZ/O3ctAHpLDNqG825RhDtUlNmryS+rI6+0jh3v/Yuv/3t/q+0iWqcEbdJQQ/HZr/I7Zbw1JB9Ztjavw8abvewgsdW7iT/0Fc6axrkMrurOih1WIjaF4ObNmznmmGOIiYkJOj5xon9j6s8//9xqjThFUdiyZQuXXHJJi3MTJ07ks88+o6amBqvVyubNmwH/XqqmnHDCCWg0GjZv3sxFF10E+Asx//vf/+b2229n3rx5SJLEG2+8waZNm1rdg9UrRCdB8oj228Rl+lP+a/T+fWw6ExiiW2/rqQVJC4nHtDzX1n2ik1o/fgSuvvpqXnzxRa677jpOOukkYmNjkSSJCy64oEUR97lz53LfffdRVlaG1Wrlww8/5MILL0Sni1j17RRz5szh22+/5cYbb2TMmDFER0ejKAozZ85s8V60hVbbuBKZmZkZWNhQO7hHrr3rhQqj0djC4O0obSWYaZ4spSvXELRP2CIKBP2WiNap+t9LxeeiqMKBWXag00g4JQtVLpmiCoff6+bzgFbvbw9gbDJXEYZbyPAq4NREYVbq0Kse1JJfWm0X0TolaJMj1VBsjeYZI8em2zp0L7UinziLHqdXxpQxEuyf++fFfez72qmZ79KlSznzzDNbXbVvD5fLxZNPPsmcOXNarLi3xaFDh0hNTW1xvOHYwYMHW+1XUVGB2+0+Yt+cnBwOHTqEVqslOTk5qJ3BYCAhISHoHrfffjv5+fncd999gfBPi8XCu+++y9lnn33E8ZSUlFBaGuydai3rX6cYMtX/70jIPr8Bt38DWFMgqZXPT1WgdCekT4LfP9zy/Gl3dUvU5ixfvpx58+YFha66XK4WSTLAb7jdfffdvPvuu6SkpFBdXc0FF1wQOJ+cnIzJZGr1/ezIezx48GAAcnNzA1488Idw5ufnc/zxxwe13bJlC4qiBBkhO3fuDLpWA7m5uS3ut3v3bjIzMwG/R2z16tXcfffd3HHHHe326yhNE580lRtg165dQWNsONZc7o4wePBg1qxZg8PhCPK6dUavBw8ezBdffBFYTGmg+fvZ4EFsrh/teeRyc3MDnssGuRRFCbz3go7x4IMPcvvtt4dbDEE/IqJ1KjEHxTaY2rxvqVaNJGu9mA16YqLjcfn02B1eUOsYLFciZUzy10GF4AXRPjYRjGTSskcjXfwquZ88SkbZeqw6d6vtIlqnBG1ypBqKzWsO+9B0uYZivOcQ8QlRgATZI/D9akV2OfBUlWM9Yu/IoVPL3zfeeGOX0vvX1dVx4403snt3KyF4beB0OoPCEhto2J/jdDrb7Ad0qK/T6WwzlNNkMgXdw2g0cswxx3Deeefx5ptv8tprrzF+/Hguuugivv/++yOO58knn2TUqFFB/2bPng3A119/zbp167j//vupqKgIZOX7+uuvAdi3b19g71NlZSV1dXUcPHgQWZbJy8sDGif6+/fvx+FwUF5eTnl5OQ6Hg/2HiiHndFySBexF1NXWoqoqLpcLn+zD43HjK9uLYrRRljgRtLrA9fLz8/H5fBQXF1NTU0NVVRUlJSV4PJ7ApLmhbWFhIR6Ph5KSEqqqqqipqaG4uBifzxfIPtrQVpIkfD5f0Jjuu+8+ZFmmpqYmqK3VamXkyJG89tprvPLKKwwYMCAQwpibm4tWq+Wkk07igw8+4KeffqKuro7Kyko2bNgQtEeqrTENGzaMhIQEnnrqqUCb3NxcXnrpJex2O6qqBsY0bdo0iouLeeONNwJj+vXXX3nssceIiopi0qRJlJWVBUIc33//fYqKigKf0/Lly/nhhx/4zW9+g8PhCLTzeDzs378/cO+HH34Y8HuQDx48GBhTWVkZLpcr4FFr6HP48OHAmHQ6HdXVfte/z+ejsLCQ8ePHk5CQwLJly9i9e3fgc1q+fDm//vorU6ZMCfqcGjx1TXWv4fvQoHvHH388Xq83kM1r//791NbWBmR3u90B+RrkycvLQ5blwJhOPfVUZFnm4YcfDowpNzeXhx56CEmS+L//+z+Ki4uRJImEhAQ+//zzIN277777AL9B1zCmhpT/S5cuDRrTkiVLABg7duwRv08N373bbruNrVu38sYbb/DGG2+wdetWbrvtNgBmzZoF+D2mDoeDJUuWsGHDBt5//31eeOEF9uzZw+LFi4Pazps3j4qKCu6//37WrVvHqlWreOKJJzhw4EBgT2FD24ULF3LgwAGeeOIJVq1a1eozoqHt4sWL2bNnDy+88ALvv/8+GzZsYMmSJTgcjkAIUUPbzo5p0KBB/W5M/fFz6ktjAiJ2TD403P+jRJnXwgBPPhrZi9frZd/hSgbGGqmrOIy+eh+7SpzIw2Zy2+13sHXrVt784BN+zDvEz4VlPPzC6xE1pr6sez98+zXLX3ySk49Jw1mcR7ZNw9mzft9iTEajsc+MqT9+Tt0Zk06r4eMHFzM+M55XV33LfW9/zVfLFlPw8Awc/72MA8/9ET68hjXXjWDN8mU89+4qjh8YTcn6N/jpx00dHlP+5rWUlJSwvaiMAyUVvPvDXn49VMPbK1a1GFPDHCASkdROxFJpNBr+8Ic/cNxxx3XqJg6Hg/vvv5/PP/+8xWp/W4waNYqUlBRWr14ddHzHjh2MHDmSZcuWcfnll7foV1ZWRlJSEvfcc0+L1Zcnn3ySRYsWsXPnTnJycrjqqqtYtmwZvlZS9yYnJzN9+vRAvZmFCxfy/fff89NPPwU8LV6vl5EjRxIXF8cPP/zQ7nja8rjNnj2bbdu2MXLkyBZ9GhJBNN9n1SVkn79O266PwVnp31itM4DPA65KMMdBzplwyvW9UoR73rx5vP7661x11VUce+yxfPfdd3zxxRc4nU5+//vftwh7uO+++7jjjjsC+xwfffTRoPM//vgjJ598MmlpaVxxxRXIsszjjz9OcnIyP//88xFDBp955hkuv/xyJk+ezNy5c8nPz+fFF18kPj6e9PR01q5dC/iN/RNOOIG8vDyuvvpqMjMzWb58OevWrePhhx/m2muvBfx1x7Kyshg9ejQ1NTVcccUVuN1uHn74YSRJYuvWrQEP8JQpU9i0aROLFy9m4MCBfPbZZ+Tn5/PLL79w5513BtUoa87atWv57W9/yzvvvMN5550H+L14VVVVZGVl8eKLLzJ//nzAH0py8cUXM2nSJC688EIOHz7MI488QnJyMps3bw6U7pg/fz7Lly+ntrY26F533XUXd999d+C9lGWZk08+mR9//JErrriC4cOH8+GHH1JSUsLPP//MSy+9FHiAt3VNRVE47bTTWLt2LQsWLOD444/ns88+43//+x/XXXcdDz30UKDtrbfeyr/+9S8uvfRSxo8fz/r169m9ezc//vhj0PvUIOfo0aPJzMxk5syZfPfdd7z22mv88Y9/5PXXX29XF0L6vesHvP/++5xzzjnhFkPQj4hUnWoIwfopv5QF0vtMqPwEqa7EHxKZMAwUGdVZSZls4RvdJIqPW8RlU4b5V/xVlZ/vPxNUGfcxv2fSOVeHezj9i92fwabn/a9nP+UvZ9SESNUpQcfxyQrPrcsldcvjnOzbQKLWgWSOA50Rxeei1l5KhRJNSdp0xv1pCTp9J3No/G8R1JX5I8tO+SvfvXAj5tItuKMHMWnR80FNt2/fzqhRo9qcn4eTTs/Q33vvvaAMfz1Fampqi8LA4A+hBIKyBzYlPj4eo9EYaNde39TUVGRZpqSkJChc0uPxUF5eHmjn8Xh4/vnnuemmm4LC4/R6PaeffjqPP/44Ho+n3UQsycnJLUIyexWtzm+UJQ6FXSv92bDk+hj99EmQczqMOLtXjDaARx55BK1Wy+uvv47L5WLy5Ml88cUXgbpszZk7dy5///vfcTgcgWySTTnhhBNYuXIlN9xwA7fffjvp6encc889/Prrr4Gwu/b4y1/+gizL3H///dx4442MHj2aDz/8sIXxbzabWbt2Lbfccgsvv/wy1dXV5OTkBBlITfnzn/+MRqPh4YcfpqSkhIkTJwYylDbwxhtvcPXVV/PEE0+gqiq/+93vWLlyZZs6fiTa2vc1f/58LBYL//rXv7j55puJiorinHPO4d///neX6i1qtVo+/vhjrr32Wl5++WU0Gg3nnHMOd955J5MnTw7KXtkWGo2GDz/8kDvuuIO33nqLF198kczMTO6//36uv/76oLZ33HEHpaWlLF++nLfffpvTTz+dlStXtvm9euutt7jjjju45ZZb0Ol0XHXVVdx/f+sb2wVt0zQhjUAQCiJRp4L2zWQlMW7yEkpfySfW40aHjFaVQatHyphE/LCZFJeNZmNRNepX+YFwLWusDYO3BsXkDfdw+g9eF8hu/1ylAVdVC8MtEnVK0DkaaihWNNRQtGaQYY0CoKjCgR0zGbpSBru+Q9q1Akad2+Fru+qqcJYexKzXYrBlogFiT72SGrdCbP1WjL5Cp2bpHU2UEArGjBnDmjVrqK6uDkpQ0uDZGjNmTKv9NBoNo0ePZtOmTS3O/fDDDwwZMiSwl6bhGps2beKMM84ItNu0aROKogTOl5eX4/P5Wp0Qe71eFEXpVJKEsKHV+RV9xNkt4oZ7y2BrwGaz8cILL7Q43lbGv6FDhx7RazZt2rQW6fNnz57d4X2VV1xxRYt09Q2etqYkJye3Kntb/PWvf223mPTAgQNbXQzpiDN86tSpLdpFR0eTmJjYav85c+YcMfvWSy+91OpG77vuuquF9y8xMbGFB6uh6HnT972tazbIu3TpUpYuXdquXGazmeeee47nnnsu6Hhb71NSUhLvvPNOu9cUHJlTTz013CII+hmRplPNkx0sOCULrQT77R4OqpmQlMOY/7so8Hup1eq4TFZQ6/uAf19O9h8fAn07CcAEnWbvho+RfnwRjQQDYk0oKlBrxxxst0WcTgm6gOxDm7uKRK2DQmsGdqcP7eFSkCTsHj22KAO2uGyksl1+B0QnnA2HC3dTWe4AwOSJZzhw7NCs9jtFKN0qB9CTnHfeeciyzDPPPBM45na7efHFF5k0aVIgo2RRUVELj8p5553Hxo0bg4y3Xbt28eWXX3L++ecHjk2bNo34+HieeuqpoP5PPfUUFouFM888E/BP1G02G++//z4ejyfQrra2lhUrVjB8+PDwlQToClodpIyEjEn+/3vZaOspmu97zM3N5ZNPPmHq1KnhEShMNA/J7Umav+eyLPPYY48RExPDuHHjek0OQc/xxBNPhFsEQT8j0nRq8z57i2QH1SUF6GQnSBJq5qktfi8bkio0ZMTbvM/uT/5ligVN6LPyHq3Yax1UOb1UOrz8eqiGXcU15O9vGVEVaTol6ALNaijG6X1YqvOwVO0hzqi2WUOxI1Qdakz4lpTeSub0PkTEztgnTZrE+eefz6233kpJSQlDhw7l5ZdfpqCggOefb4xF/fOf/8y6deuCVt2vvPJKnn32Wc4880xuuOEG9Ho9S5cuJSUlJSj8ymw2s2TJEhYtWsT555/PjBkz+Oqrr3jttde47777iI/3L+lotVpuuOEG/v73v3PiiSfy5z//GVmWef7559m/fz+vvfZa770xgjYZMmQI8+fPZ8iQIRQWFvLUU09hMBiOWLC9v9FamYye4uqrr8bpdHLSSSfhdrt57733+Pbbb/nHP/7RtxYzBG3SdJ+hQBAKIk2nJmTGw1R/avKGDHWx8QM4ds6dVBZuwzB8Uqv9Go23OP81BCHHrJGR9Bq8skJDmS9Pnb1Fu0jTKUEXaFZDUXI11rGVvU2yieoM/q0+7trmV2iT4WN+Q6XVSE1pEfGJA4JPNtgPfaRkUMQabgCvvPIKt99+O6+++iqVlZUcd9xxfPTRR0d0iVutVtauXcvixYu59957URSFqVOn8tBDD7UoKnzllVei1+t58MEH+fDDD0lPT+ehhx4KJJlo4G9/+xtZWVk88sgj3H333bjdbo477jiWL1/Oued2PM5W0HPMnDmTN998k+LiYoxGIyeddBL/+Mc/Wi2C3Z/Jzc3ttTFPmzaNBx98kI8++giXy8XQoUN57LHHuOqqq3rl/oKeZ9asWaxYsSLcYgj6EZGoUy0ML4MFXebJJGWe3G4/nVYT6FtR56G4yoXT4+WEzISeEvWoYkSyCQbEoAK55rHoomzEZresKxuJOiXoJM1qKHpUDTEaCVSo82narqHYAQwJGaQkZJDS5Ji9cCs1X9yP6q7BPPNukoZ0LvFiuOhUVklBaDlS1hqR3U4g6H3E904gEHSF7z95GXX7/9CrHsZd/yGaDtaXErTDjy/Drk/8Xpg5r4RbGkFPIvtQ3vsLtXnfspcM0vQ1JCn+rR/7DMOocCnYzDoGy0X+Goqzl3Vrq8++Pdsof9cfhWeefhM546cHzkVyVknxVBEI+hkNdcsEglDQUNJBIAgVka5TPlnB7et8wjGTToNZqUOnenE4Ox7GJWgHpT5Dp7Zlbd6mRLpOCY6MDw2rlfFUKNFkaEpJsuiQAAkYlBCNzaxDX72PMtmCPGxmt/MzWGLqt0NpJHBVd38AvUREh0oKOpZZUCBoSm/uceuPqKqK1Edi3XsDsXdEEGoiXacKtn5N/pcv4YnLZtzpl5I6YMCROwFDBqagORCNViNhUJxAzBH7CNrH63GhUVQ0Wv8kvi0iXacE7ROooegYx4K0Qn/K/6r9qIoHFQmldDeDUSgz1ddQLBvNZbIS2JPaHr9uWs2hzZ+hjc/khBkXER3tzywfH59A3KBYNJIEtr4z1xYetwhGo9Egy7Iw3gSdoqysLNwi9FlUVUWWZWG4NaFpMiiBIBREuk5VF20lyXuAgSVfYY22dLhfTGw80UYdZr0WrVd43ELBj3mH2Xqgig1FdezauoHvPn6F7z9+qUW7SNcpQds0LccxLiuJcX9agvSba/HZMnB6VVweGaezzl9D8Xc3UnzcIjYWVfPsV/n45COXKasr2kJ8xc/E5K3AYGj03Eo6Ixp9fRI191HicVNVlWeeeYbnn3+evXv3tloAUZIkfD5fd25z1GI0GnE6nYEC4WIyKegIUVFR4RahT+Lz+SgpKUGWZeL6WEHOnmTixInhFkHQz4h0ncpUD+CyGinXpxId3QmvmdHa+LoPTQQjGVX2l2BStXoqf12HOf8LZJ0Zzpwf1C7SdUrQOq3VUNRpNTDqXH78ZRuxFTIaVcYdPZDRs5e1WUOxPc9bou8wPqOOSmMaBoMh+KQpBmpd/qLufYRuGW433XQTS5cuZcyYMVx00UVishNiUlJScLvdVFRUUFVVhVarFcab4Ih4vV70en24xegzqKqKoiiBBSaLxSKeZU1oXqtPIOguEa1Tso94VxHYzKQNm9C5vk0Lb3ciVbmgbaJ+s5Cy8nKijHq0BzYgASbVheLzotE1/s5FtE4J2qS1GooNqD4vLo3f452ZEN2ihiJQ37edchyqSqamFJKjIWtsy/PGGKgtQXVVtxuKG0l0y3B7+eWXOffcc3n77bdDJY+gCRqNhoyMDA4fPozb7UZRjuwSFggKCwsZOnRouMXoM0iShE6nw2w2ExMTg9VqFQskTcjLywu3CIJ+RkTrlL0Q5PqEGImdK9Tr1UdxqMKBrKh4ig6Rk9UD8h1lHDcsC4b530jZfAhNdSwSEnhqQNc4WY9onRK0SWs1FBtIHncG0Rv2oFPc2DQuUBTQ+Nt0uIaiowI89YsocZktTm8uVdAdqsJZWcDE6S1ORyTdMtycTiennXZaqGQRtIJGoyE1NTXcYgj6EEajkYEDB4ZbDEE/Yfbs2eEWQdDPiGidKt3V+Doxp1NddSYrFQ4vqCoee0WIBRNoLTZo8Iu4q8HSOGGPaJ0StEtbhteQ0SeDoQp+fAlUxW+sm2ID55vWUGwTe0Hj61YMN5cmGrOiInlqOi94mOhWcpLp06ezcePGUMkiEAhCwJIlS8ItgqAfIfRJEGoiWadyt/9ISY2bWikKopM71VfSaNEaozDrtURJInQv5Bib7Ddslr49knVK0A1MtsbXTnunu5cU7aLW7UNWVLBltLz8iBkcOv4qaide23UZe5luedyefPJJZsyYwT/+8Q8uv/xyEhISQiWXQCDoIsuWLQu3CIJ+hNAnQaiJZJ2q2r+dOpeTOkMKk7sQMj36nJv8e3GsaT0g3dFH0Tu3oHFXo82YSOrxjRFeqqsqaE9SJOuUoOvUEIWz2oVXUdGXlpAcN7hT/fNzd2AsqcVtjGeSMbrF+bFjx4dK1F6jWx63nJwc9u7dy+23305ycjJRUVHExMQE/YuNjT3yhQQCQciYNWtWuEUQ9COEPglCTaTqlKuqBIvXn13OOGB41y6SMQkGngAxYotDKDi8fy9lB/IoPHCAOsnCjkPVbNlv55c9+4LaRapOCbrO1g8fIXfNKxysclFa46a8rKRFm40FFe2WBNDUh0rKMcHeNp+ssLGgb4Yzd8vjdu6554pN/AJBhLFixYpwiyDoRwh9EoSaSNUpU3Q8x/75IWr2b0cdeEK4xREAGsWfKEbSGjFH2fDIKqggO4PTt0eqTgm6jnf3ajSyG4DdlnFk621B5zcWVLBsbV6rGSkbOOa0S7AfzCWuSZhk0xIETG17j12k0i3D7aWXXgqRGAKBIFQsXLhQhI0IQobQJ0GoiVid0uogeTjW5C562/CXF3H7FOrcPhKijUfuIGiX49MsqD4dclYSGq0GfXIOGo2EOWlAULuI1SlBl1AVBa3iRgUcx8zm/NkLWziKxqbbGJ8Z3249t9hjpxF77LTA383rxh0b66F4xb3ITjvmcRcQPzTyQye7ZbgJBILI4/bbbw+3CIJ+hNAnQajpzzq17vP/Yd/xJQY8nH7tUyIqqTuoKjrVB1oNeqMZgJHzH2m1aX/WqaMRSXZz3KBYVBXkYWmtfo+a13ODJsab7IOyXf56isZoSMzBh6ZFse+aisMU7/gKAE3yiX3CcOvWHjeA6upq7r77biZOnEhKSgopKSlMnDiRe+65h+rq6iNfQCAQhJQPPvgg3CII+hFCnwShJhw6daS9MD6fTEWtu+XxTu6FiZUryHTvIs2dj9vt6pKsgnoa6ukBaPVtt0M8p/odXicSEhpJQm+0tNmssZ6b3/P23Lpc5F/egfcvhw+vgZU3wofXoLx/OWuWL+On/NKg0MqomMYwSa/D3gsD6z7d8rgdPHiQU045hfz8fIYPH87kyZMB2LVrF3fddRevvPIKX331lahDJhD0ItnZ2eEWQdCPEPokCDW9rVMd2QtzaM9milb8G3tUFsee/heysoZ2aS9ManIymlgTWq2ExlMHJnMPjOgoQfY0vtYa2m0qnlP9DF+TRZSaYshfj6ooSNlTWzRtMN4kxUfqlsep8G0gUeug1uVCRo/eYEQuP8Aw5RcWpBUybvKSwDPAYDSSnZaEXnGhTegb3vFuGW4333wzxcXFfPTRR5xxxhlB51auXMn555/PLbfcwssvv9wtIQUCQccxm8VEQRA6hD4JQk1v61RH9sJUFG4jSqkmquYXYqKjW+yFGZtu69C9BiQlQozJ/4dcBySGcCRHF9UOB4eKa5Ak0Ja7yQZKSw5TWlyE11HD8Sc27l0Sz6l+hq/RW73vp5VU2ytwaa2csHhqq811Wg0LErZQ4duAx+2kMDqdON+vSKqHCsVAuTaDDF0pg13fIe1aAaPODfS1xsZD7WHw1fbwoEJDt0IlV61axXXXXdfCaAM4/fTTueaaa/jkk0+6cwuBQNBJNmzYEG4RBP0IoU+CUNPbOtU8nOrZr/IbwyZlHxzeztCaDaRHyZhtKcTEJbXYC9Oal65VDE1qRblrQj+YowiP24XTK+PwyDgVLQAFP3yIZ+XfUdf9G5+30SMnnlP9i30lFew4WM3O4moOybF4ZRWdtwZVkVvvIPvQ5q4iUevAa02nzuEAVUFRwaEasEUZsKVlI7kqYddK//e+AVN9YXdX39je1S2PW11dHSkpKW2eHzBgAHV1dd25hUAg6CSXXnppuEUQ9COEPglCTTh0qnkiA0nxsSBhC9rcVVBZQFT5HqJQibO5Wf3u0/zkGMf4rKTOGW0ARmvja2G4dQut0Uph9p9QfR5G1tfVM0TFoNafd1TbiUlIBsRzqr/hdjnwyArIYLClEe/dj14rITur0UXFtexQtgsqC5DMcWRYozjsqwYvaCSwRFkZGG9BI0lgioOKfH/7lJH+vsb6etPuvmG4dcvjduyxx/Lmm2/i8XhanPN6vbz55psce+yx3bmFQCDoJIsXLw63CIJ+hNAnQagJl041GG8TMmL8e2E+fwB13wbw1gEqqqrgKt/PsLwXWCC9z4LJ6Z0z2gCfLoqyWjeHq13sP9yyYLCg48TFxXH2eX9m9gWXMWxYDgBDBqVxTEo0x6bGEE2jY0A8p/oXFms87kEn4U4ZS9bQEWTEW0iNNaPztGFcuWtB8YLOX4JDqzTaJbK2SVkOncHfzt0YFrmnWiKvtJYd+ft7ZCyhptt73ObOncvEiRO58sorOeaYYwB/cpJly5axZcsW3nrrrZAIKhAIOobYUyoIJUKfBKEmnDrVYi+MNYPBehdoDTg9MgWadAZoa1rdC9MRJJOV/ZVOALylpQzqiUEcxVhjE8BQP3X1NHo0xXOqf5GWPZK07HqP2OEdsKv+hKuq9Q7GaNDoUXwuiioc6N0uorUaFEmH3SlDhYOMeAsan8efodTYGNJcIZsxuHwg2f0JUDTdTrjfo3RLuvPPP58XXniB4uJiFi5cyPTp05k+fTpXXHEFhw4d4oUXXuC8884LlawCgaADzJo1K9wiCPoRQp8EoSasOtVsL4zd6eNQaRk1Ti8uWcUSZW17L0wH0OqNKPUr/KpLhEqGnIb9SBAU2iaeU/0Ys63xtcveepvEHBTbYGrtpdjrPJg1Pow6DRaLBZtFj93hpai8DtVZCfFZkJgT6KpLHUXBgN9RmPEHvL7Ofd/DQbcLcM+fP5+LLrqITZs2UVhYCMDgwYMZP348Op2o7y0Q9DYrVqwItwiCfoTQJ0GoCatONdsLo5Y7kCrq8KLi0VrISIhqey9MBxk+dS4GrRbdgBE9NIijA0dxLq4dq9DqDVjG/AG9NQmMTQy3JskkxHOq/6IaY6hz+/DKCr7SEpKyWrbxoWGNMp5hyhYydKVIHje1Xh8ykDHIAmod+up9lJksxA+biVbbaJ+MmzSFcZOm9N6AuklI/IE6nY4TTzyRuXPnMnfuXE488URhtAkEYULE+gtCidAnQagJq0412wsjqTJG/PthvNomhX5b2QvTUSzj/4Ru7AWQenxIRD5aKSzMo2jjR+R/+x7llXYAVEM0BeUO9pTUsiN/X6CteE71L0oLtlP406cc3P4N6C3sLnVRWO6g8MDBFm0bSne87RhHSdp0bDHRWORq9KoHPTKammIGy0UYTGa+0U3i2bLRjVll+yCdsq7Wr18PwKmnnhr095FoaC8QCHqeRYsWhVsEQT9C6JMg1IRVp5rthbG7FDS24ejlOmo8Oora2Qsj6F0UT2MRZp2+3tDWaCjzGtB5a3FXVQTOi+dU/yJ/0yoMeZ/h05lJG/kBdaZkfF4PqhJciD2o3mJWEuMmL4Ed7yN/+wya2oPo9AbQ6pEyJhE/bCbFZaPZWFSN+lV+5zPGRgidMtymTp2KJEk4nU4MBkPg77ZQVRVJkpDlNuouCASCkLN+/XqGDh0abjEE/QShT4JQE1adatgLk/ctdszYogwMircANtwVDuwOL6h1DJYrkTImBe2FEfQuGTY9cmIUqqpijmr0huqjbJhcXgyGxkm3eE71L1SPAwBF4zfY0y58DKNOQ5yl0XALMtqa1ls8fi6WUef6w5zdtf7Fl8QctFodl8kKan0fgAWnZKFVvbi2fYSnthLNoPFYM8f0+ng7Q6cMtzVr1gBgMBiC/hYIBJFDXFwrNU4Egi4i9EkQasKpU833wtjisv172oCM+Pb3wnSU7777msJfNyHJbuYuuDnUQzhqsOpVMOv9f5jMgePHX/okaA3QxHEgnlP9i5HJRlRXNL7oRACyk1p6vjfvs7c02hrQ6lrdm9q8nuP4zDiOT41i16fPAKCMUhnXnwy3KVOmtPu3QCAIPwMHDgy3CIJ+hNAnQagJl041rND/5BjHgrRCMpzfIhf/CtHxaHRGND4Pg+VKykwWvtFNorhsNJfJSqfDqYzl2xleuhIAr/ev6PX6nhhO/0duUiNY0+Q91BlbNBXPqf5FtFYGkw5iYttsMyEzHqbC2HRbp76jDcbb+Mw4/zUAWWtCK7vwOiK/CHe3gjunTZvG6tWr2zy/Zs0apk2b1p1bCASCTvLpp5+GWwRBP0LokyDUhEOnmoZVjctKYtyfllA59ByqnW6qSw/gqqtq3AvzuxspPm4RG4uqefar/E4nMoi1xRNr1pMQbUB2dT65iaAe2Vv/QvLvN2wH8ZzqZ/j8tRDRm+r/dkP1ISj5FZTG7+OEzPgWRttP6/7H+vefYeNXq9q8vE6rCRhtAGkDUsiIt5Bji/ykJd1K/bh27Vouu+yyNs+XlJSwbt267txCIBB0kuuvvz7cIgj6EUKfBKGmt3Wqrb0w+5V4VP0QTKqT1N/egikls929MB1d1c8elApFUf4/FAcgwvi6QsHhSvR2J5LWQFqTsEifrFDrdFFXXUlqSioarUY8p/obvvrENDq/4Va08WPkjS/gkxVSL3mV6NiENrt6ctcSU74D56HBcMrMDt0uNTkZyqpA4+y26D1Nt9OptJecZM+ePVit1u7eQiAQdIL58+eHWwRBP0LokyDU9LZOtbUX5hjNQTISojAkDyVm9Bn+PTH1e9oaw6ni2VRQweZ99o7f0NBkP45HeNy6ymF7DaU1bg7WBntBtq1/n4InzqH01UuorSoDxHOqv7HnYClFFQ4K7P6C2DVYqHJ6qfPI1NpL2+0bLVeh1UhgSez4DY31IZmuyA+V7LTH7eWXX+bll18O/H3vvffy7LPPtmhnt9vZsmULZ5xxRvckFAgEneLtt98OtwiCfoTQp8hmY0FFp/d4gN9rsXmfPShcqLfobZ1qdS+MqmKu2oM5ykB85glBiS4aaG0vTIcwNlmwdtd0T/ijGEdUBgejjkejMzC+yXGjxUpDoYDaqgpi4pMj8jnVF7+bkUJldQ16jwenUyITsMYl4tBr0WslNO52jCtVZVSsG6yxyMd0IiOsqb6we3vXjhA6bbg5HA5KSxut3ZqaGjSaYKWUJImoqCgWLlzIHXfc0X0pBQJBh5k1axYrVqwItxiCfoLQp8hlY0EFy9bmtZ5VrR2ahg4ylV6fIIZDp1qMsWo/eOr8r5OGt9mv+V6YjqDoo3F5fMiKiq+ynLhBnZVWAPDbM+YAc1ocT0lORokzo9NIGLX+0LZIe0711e9mxGCMQQZ09QZVRloaDKhfENG72u7nsoPi99Jprckdvt1hjxG1yoXX7mKQEtn73DptuF1xxRVcccUVAGRlZfHII49w1llnhVwwgUDQNSLpx0vQ9xH6FLmMTbcFQvmgY/uwmk4MB8SaGJ0W0+n7dtcjEBE6Vbqz8XVy24ZbV/Dpo9l92B8i6dt/iPGjQ3r5o574+ESIrs8sqfjrfUWETjWh3e+m7GtRYwytrsVezLHptvANIMxMuPL54AOmJtklnfa2O9aVNb6OSurw/Q46dUjVfoMwrraqw/3CQbf2uOXn5wujTSCIMG677bZwiyDoRwh9ilya78MKyoAo++Dwdij6wf+/7GthtB20O3nx28JOZU1suMaytXlsrJ+UdpZI0Kktm3+gsNxBqUcPMaFNJW8wWUCjBUB2iVDJkGNsstjg8k+yI0GnmtLqd9Prga3L4f3L4cNrYOWN/v8/WIj8yzs8ty637bpkRzt6S2NmUVfbhpW76jCyqvr/6IThprENZJ8hm4LoMbg8vu5I2uN0K6tkU2pqaqiqqkJpxcWYkZERqtsIBIIjcOGFF4ZbBEE/QuhTZNO8oKyk+FiQsAVt7iqoLADFCxo9Slwma+QT+MkxjvFZSVx88mBe/Lawy9667ngEIkGn3Id2UOnycCAqjaR2kqx1CUki9ZgJ6LQS+sxjQnvto4mDm8HjAEs8JI9oPG60AhKgBvYkRYJONafpd/On/FI2FzzNeNf3SK5KMMX569H53KhFP1CRv5UBuklMOG4RlwmjrSWShGyIRa4pwV1VRltpD3fk5iHtr0KnkRhqiMPUwcuPPGEKo8ZP9Sc1AQ4fLgmJ2D1Btw23p556iqVLl7J3794228iy3N3bCASCDrJ161ZGjxaxOYLQIPQp8mmYIEqKj9Qtj1Ph20Ci1oFk9k8OFZ+L2j3fMEz5hQVphYybvASdXhdk8EET462VUC4fmlZT6neFcOuUr66SBKkah0bCkHpsj9wj5ey7e+S6RxMbVjyDuTofT+JITrj4wcYTkkSxW4/iqsK1/xBDjg+/TrVFw3dzzeFPScr7kkqdjC0tB029R1ZRVYo8VvSOfUzmB+ITT0Wr7URSjX6I4vXgqy1DbzIjGayBTK8bimXM1dW4PEWc+NvW+3qrD2MAXJIJo6XjWe37kqHcLcNt2bJlLFq0iBkzZnDJJZfwt7/9jcWLF2MymXjppZdISUnhmmuuCZWsAoFAIBAIWkGn1bAgYQsVvg143E4KrRlkWP21xIoqHNgxk6ErZbDrO6RdK2DUuV321vX1MC5dVBxDFr6FWrYbb1RauMURtIHq8yArKp5WpqoFdVpMdW5cpaUMCYNsnUGHwnTNJmo1texVMqiudJERbwHqv5tOHzZrOmlyEVLuKhg5O2CsHI0U78+j5O3rkADT9BvJGX8aAGp9yn61IalQK6RmDMUhVyBL+nbLlfVluqUZjz32GDNmzGDlypWUl5fzt7/9jTPPPJNp06Zx0003MX78eMrLy0Mlq0Ag6ACRuOoo6LsIfeojyD60uatI1DootGZgd/pQy/2JG6qcXmxRBmxx2Uhlu2DXShhxNmh1XfPWddNoiwidMkQhpY3FEG45BG2SatWiwYDb1tJzohpikByHMPj8ewgjQqfaomwXGnsh0bYkbF4DdocXVW3y3bToyYi3INXEQUW+39udMjLMQocPr9v/3qiA1mAJHLdOWUS1B+JiYtvoCekn/gFO/EPXbly8DdzVqJ3YGxcOumW45eXlsWjRIgD0ev+mQY/HA0BsbCyXXXYZTz75pKhoLxD0Im+++WZk/4gJ+hRCn/oIZbugsgDJHEeGNQq1rAZ95R58ko5Y22Ay4i1oJMm/t6bZ5LAr3rrucDTo1C87d7M3LxdkN+ec1cWJ5FFORowOdBYY0DJ76Ql/+Ct6jYpktgERrlPuWlC8aHQmMqwWVNVBldMLQKxZ3/jd1BlA9vjbH8XE6mRMsSYUVcUQ02i0j87u2XwZ2966A9XjwJl5GlHHnt6j9+oO3Vo2i42NxefzZ1+JiYnBYrGwb9++wHmr1UpxcXGXr+92u7n55ptJS0vDbDYzadIkPv/88w71PXDgAHPmzMFmsxETE8PZZ5/d5j68559/nhEjRmAymRg2bBiPPfZYm9d96623OOmkk4iKisJms3HyySfz5Zdfdml8AkFP8I9//CPcIgj6EUKf+gj1k0N0/jTpkqsKg+pCr7j9e9Ya0Bn87ZpODpt467zWdOxOH0XldRSWO7A76r11adn+pAq7VgZfrwuEU6dcLidbcguodfds5jjfrs/J2vYomTufRelE1k5BE2S/IyCQTbAJhsRMpPgsMMcBEf6cMkaDRg8+d/vtfB5/O2N078gVodgMCikxJlJjzSTEdr5cSVepk6KQFRXF2Y/LAYwaNYpffvkl8PeJJ57IU089xYEDB9i3bx9PP/00xxzT9YxK8+fPZ+nSpfzpT3/ikUceQavVcsYZZ/D111+326+2tpbf/va3rFu3jttuu427776bzZs3M2XKlBahm08//TSXXXYZI0eO5LHHHuOkk07immuu4d///neL6951111ceOGFpKens3TpUu69916OO+44Dhw40OUxCgShZtasWeEWQdCPEPrUR6ifHCo+F0UVDnweFzoUzLipdisUVThQVLX1yWFTb11CFIlGmVj7DszV+Y0eAY022FvXDcKpUwd3/Yjy3uVseuzP7N61rcfuY4iKxaDVYNFJuJ1HtwelywQMtyMHtEb0cyoxB+IyUZ2VFJXXYa7cxWDXTga591DtcPu/m4oMrkqIz/K3P5rxOhtf6y0tz8veVhePyksO8t0X7/Lzpm+oru18GY74+ESSoo0Msng73bc36Vao5EUXXcSyZctwu90YjUbuvvtuTjvttED6f71ez7vvvtula2/YsIH//ve/3H///dxwww0A/PnPf2bUqFHcdNNNfPvtt232ffLJJ8nNzWXDhg1MmDABgNNPP51Ro0bx4IMPBlZmnE5nYF/e8uXLAViwYAGKorBkyRL+8pe/EBfnX835/vvvueeee3jwwQdZvHhxl8YkEPQGkVaIVNC3EfrUR0jMQbENpjbvW+yYGaBTMEoaZElLbJQRu8MLah2D5UqkjEnBk8Nm3jqr6wCgYFZqcavNvHUhCOUKp05VFm5FC9jkClJTB/XYfUYPGQQl9d4C1Qn0nuegv1BZU4cGFcmrafPdU+trdkX0c0qrQx42k4qCbegd+zCoLjQaDRp8xBpU7HUeYpz7iYuJQ8o5/ahOTAKAz9X4uv6ZBFBzYBc1K+9C9dShnXYrA4afFNStrHA75h+fAaAq7iFiojuXMXZYRhrsPwhmL5Hsc+uWx+3iiy/mhx9+wGj0v7GTJ09m+/btLF26lEceeYQtW7Zw5plndunay5cvR6vV8pe//CVwzGQycemll/Ldd98FhWS21nfChAkBow1g+PDhTJ8+nbfffjtwbM2aNZSXl3PllVcG9V+0aBF1dXV8/PHHgWMPP/wwAwYM4Nprr0VVVWprxQqaIDKZM2dOuEUQ9COEPvUNfGhYrYynQokmQ1NKikUiyqgjJiqKjHgLNrMOffU+ymQL8rCZwZPDZt46xeMKZGSrdTja99Z1gXDq1PGmYrKTokkYmI01xhaSa24sqGhZxNzQJKGGu/XVf5+sdLmIeX9H9nkpLKslv6yO3eWuFuf3bN/I+kcv5bulczlUuDuin1M+WeHZ8uP4RjcJg9FEFC70qget6mWAVMEQiqj26dhoOglfTgR7DnuJwxV2ymrdVDo8qE0MtzrVQEl5BaU1bsrLSlv081QdDryOTRzQ+RvXZ63EVd35vr1Ilw03l8vFo48+yvr164OODxkyhGuvvZarrrqqW2GSmzdv5phjjiEmJnidZeLEiQD8/PPPrfZTFIUtW7Ywfvz4FucmTpxIXl4eNTU1gXsALdqecMIJaDSawHmA1atXM2HCBB599FGSkpKwWq2kpqby+OOPd3mMAkFP8NJLL4VbBEE/QuhT5NNQGPttxzhK0qYTF2NFqivB53HhqavEc3Abg+UiDCYz3+gm8WzZ6GBDo8FbZy/FXudBo5ECnoxonYLd4aWovA7VGZpQrrDplOxDV5mH1aQjPWdsSC65saCCZWvzePar/OD3tKlx62lpuDV8ZsvW5gnjrRW8Xg81WhtOTRSSPqrFeQ0qMc79WHxVuGorI/Y51fA5byyqpvi4RcT/9ir00QkY9Toseg1GvZbooZPZPfQSnlXP4dlv9rVcBDjK2Fdayf5KJwUVTv9CUT3RtgQAtBr/Ht7mjLZ5GD0wlpxBSVitts7f2FRvb7hroP75F4l02XAzmUzcfPPN7NrVvVj3tjh06BCpqaktjjccO3jwYKv9KioqcLvdHep76NAhtFotycnJQe0MBgMJCQmBdpWVlZSVlfHNN99w++23c8stt/DWW28xZswYrr76ap5++ukjjqekpITt27cH/duzZ88R+wkEneXBBx88ciOBoIMIfYpsGiaGmwoqGJeVxLg/LUGafC2YYvEqKj6fjNfjRsqYRPzvbqT4uEVsLKoOMjSae+tUpXHiaLMY2/fWdYGw6VRlvn9/DEDSiJBccmy6jfGZ8WwqqAg23oxWVFR/HbK64Elm089sfGY8Y9NtIZGlP2EwWhhy2UsMuPhVsn9zXovztrhE4qMMJFuNxEqOiHxONf+cL5syDO3QaWhSR6NNHY0m5VikMX9Cc87TTDt3IeOyklrq0VGI6vHvcZM1JiRNo5kSZYlmdEYiowfaODaulfenrgytRsJsGxDUr6PUYaHa6aWizo3bGblet24nJykoKAiRKME4nc5ACGZTTCZT4Hxb/YAO9XU6nRgMrW96NZlMgXYNYZHl5eU899xz3HDDDcyZM4ePP/6YY489lnvvvfeI43nyyScZNWpU0L/Zs2cD8PXXX7Nu3Truv/9+KioqmDdvHtC42Xbx4sXs2bOHF154gffff58NGzawZMkSHA5HIDygoe1tt93G1q1beeONN3jjjTfYunUrt912W1CbOXPm4HA4WLJkCRs2bOD999/nhRdeYM+ePYH9ew1t582bR0VFBffffz/r1q1j1apVPPHEExw4cICFCxcGtV24cCEHDhzgiSeeYNWqVWJMYRpTUlJSvxtTf/yc+sqYlPgslr/X+TEV7tvP3EW3ReSY+svndP6cuTz55S7e+PwHUrR1JFVs4ZVXX2OXlM0v5TpKLcPY6U6gyDyCiz90UzVoGlWbPiRBsfPJxp1c8p/XySvcxxl/fZC3HeP4rCQemzUao1yLXnXjVrRQV0ZK3W7cPpn10nh+t2wXPlnp1piAHvmcHv/vSh57vO3PqXznt+QXFFBSUsI3uRWBz+nP8+azsaCiS2O64/a/c1JcHTp7If/7ZitL3vmOW269DadkYf3WfHL3HeLlx+7FWfgj995zN999/wPXLVvBe1/9QpZVYef/nkCn1fQ53evp79NTTz3J1u/XUbR9E88+8UiLMcXHJ1JzKJ9YvcJPaz7CaDRG1Jh8ssJvLruTTQUV7Nu8ljOyjTy97Cm+Wr2K8opK9uwvwaON4rW3loNWxzmzz2bBKVkUb/uGddv3cflDb7P8vcj/nHpC93SZp7At+Q/8Gvd/QWM66+yz0Vps/Pjjj3hqylqMyX5wD9u3b4eopC6N6d8vvseekmp2HSjjm/XriFQkVe26P/Czzz7jj3/8I//973857bTTQikXo0aNIiUlhdWrVwcd37FjByNHjmTZsmVcfvnlLfqVlZWRlJTEPffcw+233x507sknn2TRokXs3LmTnJwcrrrqKpYtWxYoadCU5ORkpk+fzptvvhm4pl6vx+l0otVqA+3uuece7rzzTgoLCwNJWVqjpKSE0tLgmNw9e/Ywe/Zstm3bxsiRR2+xRUFoef/99znnnHPCLYagH7CxoII7//sNs048lgWnZHW48HLTleaFU7OZkNmyDpOg+zSE6Y3PjA/6fA7m/0rJ29cBMDDOTGKMBWnOa1C/Ct3w+WzILyfNZqa4yuW/xuR0NNvfxf3Vo2jrSsEYjSE6AeKzkIfN5Nmy0Wwsqm5xv87SE8+ott6Lpvz4ym3YKn/BHJtC2vwXgNDpatPrTMiI4bL4n6lZcSsGxQWmWKLi01DiMlktn8DbjnGMy0rq1nt41KOq8OaFgAojz+H9vcaI+t1rSx/VfRuRvnqgseGA42Da3wJ/imfnEfj0b1C+B1JGwfQmc3xVheUX+zNSDvsdTLi005fO2/ItFav+iUMTjXPEXE7//TkROT/vVrzD448/Tnx8PDNmzCArK4usrCzMZnNQG0mS+N///tfpa6empraaZv/QoUMApKWltdovPj4eo9EYaNde39TUVGRZpqSkJChc0uPxUF5eHmgXHx+PyWTCZrMFGW1AoF9lZWW7hltycnKLkEyBoCeorKwMtwiCfsLYdBupujo21e/BCZpoyj5/Wnh3rX8/T2IOaHUiDKwXmZAZD1P9n1NTA6CmvPH3z2LQIikyuOxg8U8CdVoNF588mP2VjkajreGzHXMh5tHnt/hstVodl8kKav1nC3TZ8OiJZ1TTkEVoKZuqKFC2kxqvj8Nx6aQR2pBFnVbDglOykBQfqVsep9K3gTgcKDo9qsGAInuo3fMNw5RfWJBWyLjJS4TR1h4+D7iq/DXcDNEtw3MlCYxWcFeDu4bKSkd45GyDtr6b2/MPoOy3o6hg0GnwVOUxZlpjvwY9Gp8Z16bRtrGgosV1O4JPVti8z963jUGTDQDVaUdqcthZV82egmIMWg26QRayu3Dp1JwJkPomg406DhXkhkLaHqFbhtuWLVuQJImMjAxkWQ7pnq0xY8awZs0aqqurgxKU/PDDD4HzraHRaBg9ejSbNm1qce6HH35gyJAhWK3WoGts2rSJM844I9Bu06ZNKIoSOK/RaBgzZgwbN27E4/EEhVc27INLSkrq8lgFglBy6qmnhlsEQT9Bp9Vw01kn8OVBTeOEeHI6up0f+gsxVxb408hr9H6vzNAZPFd+HJtC4JURdIzWJmFpGdlUnHgRxr2fY9LVZ+RzlAcMN4CtB6tbGm0NaHUQmw41h/DW2dHXT5obJpVAvbHT9uSyPXriGdVcNmhivMk+vAXfkaarwSW7IS2nhdEWCl3VaTUsSNhChW8DHreT/TEnkJHoT6xRVOHAjpkMXSmDXd8h7VoBo87t3qD7MSVFO6ldcSuSJGH+3d9apH4HqMGM7CzDXVLCqafODYOU7dPad8PrqEKqj3Pz+BSUOv+e0qZ7snRaTbtG25E8y63RVN+Z2rpsfYFfykB7oAp3sY8TmhyvLD2IrKg4FRm9Pq5L17YY9WQn+ZOhlEbw71a3JCsoKCA/P/+I/7rCeeedhyzLPPPMM4FjbrebF198kUmTJpGeng5AUVERO3fubNF348aNQcbbrl27+PLLLzn//PMDx6ZNm0Z8fDxPPfVUUP+nnnoKi8USVMpg7ty5yLLMyy+/HDjmcrl4/fXXOfbYY9v0AAoEvc0TTzwRbhEE/YhlTz1ZvwIcz0/5pWx+/e+o3zwK+zf4Ez1ojSB7UYt+oOLzBxiw5QkmZMQIoy2MWJMHM3jK/2PA2Xej1dSvSzvKg9pMyIxn4dTsNj+nHeveYttL17L97Tvxej2B4w0GUnfCuHrqGdXorfB73p5bl4v8yzvw/uUYvryLVIObrGiF48pWsWb5Mn7KLw3tAoPsQ5u7ikStA681HbvLR2G5g8JyB3aHF1uUAVtaNpKr0r/w0UoRYYGfWoeTapePKqcXh6Jttc22cigoc5B/4GCf+d2LyRpL7cg/4ZUMaKMS0MUNRvZ5jtyxnjaT4bRDX4uC+OnFv/LL4xex+b2WCWc8eis+RUXrq0PxNRbKNkoypsTBWCxRxKf0XH3GSKBbHrf169czYsSINr1NZWVl7Nixo0ura5MmTeL888/n1ltvpaSkhKFDh/Lyyy9TUFDA888/H2j35z//mXXr1tF0q96VV17Js88+y5lnnskNN9yAXq9n6dKlpKSkcP311wfamc1mlixZwqJFizj//POZMWMGX331Fa+99hr33Xcf8fGNP0qXX345zz33HIsWLWL37t1kZGTw6quvUlhYGNmFHwVHHQ899FC4RRD0Ixr0acEpWaw5/ClJeV9SqZOxpeWg0fgnVIqqUuSxonfsYzI/EJ94Klpt91LGC7qP22ijqKQGr0/Fu2sPx2ecGHS+NcNrw/dfU1ZZgfdgCYMV/++qvayYpNTGrQDteQQ6Qk8+o5qHLFb4NpCodSCZ40BnRPG5qC3YwDBlR+hDFst2QWUBkjmODGsUarmDKqd/chlr1pMRb0EjSWCKg4p8f/uUyNo/EykYJB8WgxZFVTEZTK22UY3+aCzJU8NDD73Sm+J1meyc48jOOQ5+/+cu9T+SZ7l5iLMPTcg9yz2Nr6YUjbMUV23LlP+WY6aSZ8jEZI3Hp2poiH9LyBxFwqXPdD+Nv9flD791RG6Jjm4Zbr/97W959dVX+eMf/9jq+dWrV/PHP/4RWZa7dP1XXnmF22+/nVdffZXKykqOO+44PvrooyMaglarlbVr17J48WLuvfdeFEVh6tSpPPTQQy2MzCuvvBK9Xs+DDz7Ihx9+SHp6Og899BDXXnttUDuz2cyXX37JTTfdxAsvvEBdXR1jxozh448/ZsaMGV0an0DQE8yaNUssJghCRoM+6VCYrtlEraaWvUoG1ZUuMuItQH0YmNOHzZpOmlyElLsKRs7udtp4QfcwmGOp8WrQKF481S0L1raG/OsK0kp+BiAh2oBBq8HktQNt7+HuLD39jGoeslhozSDD2gshi+5af+hwfdFgn6Lg83nRqj4wN9ajQmcA2eNvL2iVQVYdpNQXMU+IbbXNsBN/j1p3IubY5KPqd6+58SYpPhYkbEGbuyoofF2Jy2SNfAI/OcYxvg8lw4k3KkiqDp01usW5kcOHM3L48LY7S1Lb5zpA3qtXQc0hdnsHd+s6PUm3flWPlJDS7Xa3SObRGUwmE/fffz/3339/m23Wrl3b6vFBgwbxzjvvdOg+CxYsYMGCBUdsl5ycHLFFHgWCBo6WHy9B7xDQp7JdaOyFRNuSsHkN1NQ5OFyVj1dvxU4sNovfoyDVCG9CuPn2nYfAYCEpexw16dNQJS3xGR0rOB0tVyFpJIhOJj3W7T8o20MqX48/o5qELBZaM6hyuNnjciDpzdR5ZH/IYlw2Utkuf8jiiLNDs8hgjPZPmH0uiiocSDXFDJHLAChy5FAk4fe6+Tz+pBvGlhNTQT2yu/G1tvWyTUk5jR7ko+13r0Oe5T6aDGdonA580ZCR0uv3LvEaMbt8OJ32Xr93R+n0k6qoqCiodtvOnTtZv359i3Z2u52nn36awYMj12oVCPoj8+bNC9qLKRB0h4A+1XsTNDoTGVYLh6vyMfhqMPhqkOPiG8PAhDchrPi8Hiz5n4KqUiUpTLngr53qP9rmBUssyuAJUPi1/2BdWUhl7PFnVLOQxSKXHatjHwoatNFDyIiP7ZmQxcQcFNtgavO+xY6ZeIMRrdvvAYg1gN3hBbWOwXIlUsYkfyZWQevIjfuX2jLcmtJXfvfyv3gWSfUSNXAUhtSRVJUdxGAyMyB9aKevFTbPck+iquCrN9r15vbbNmHHlo3oLbEkpQzEVv8edAVTdBxRDi0x7o7vO+xtOm24vfjii9x9991IkoQkSdx3333cd999LdqpqopWq+Xpp58OiaACgaBjiD1uglAS0Kd6b0LDj6pJrqVhW7xWbZJkQXgTwoqzugyjTsLrUzHEdLIEjdcFHr/BrbENgkPR/r+bJTbpLj3+jGoWsqj1+TNralCQ9E32S4V4kcGHhjXKeIYpW8jQlRITn4ymogRJkrDadBTVatBX76PMZCF+2Ey0IpS4TTxuFxpZQZIkNFodRwqA6yu/e+VbP0XnqaG4zI72syfRuytxDTqZAX+6s/MXa+ZZtjt9qOX+sghVTm/PeZZ7EtkD1Efz1X9/m6LKXso+vhefw45m6HRSxp8FgPPzf+DxOSgb/FtOuuCWLt9+7LDBIOXikbq2xas36PQnOGfOHEaNGoWqqsyZM4drrrmGU045JaiNJElERUUxZswYUlJ639UpEBzNPP/889x4443hFkPQTwjoU2IOxGWi7ttAkceKrEshWSkBoMzpoKjCQEacCY2rEtKFNyFcWH12RgyIQUVFHjqkc50dTTxrlkSqNLHIdRXUHdhHeghl7PFnVLOQRaPiwqjT4JUMVLlkiiocIQ9ZbMjc95NjHAvSCv1ejup9/pA/SYNUU8xgxUeZycI3ukkUl43mMlnpM+Frvc32faVIB6sBGK7qaC09Scmhffy6+lVwV7PxsIEbbrund4XsJKqioPPWAaAxxSCb4tG7K1G76tFu5lnWlFURVbUTr2SEmKw+mQzH53bg9choNCBJRlr4WiUt+3b9iEbx4tVnkjIeXI4atD6/wWqI7abNUZ/wBk9d967Tg3TacBsxYgQjRowA/N63U089laysrJALJhAIusbEiRPDLYKgHxHQJ60OedhMKgq2oXfsQxuVQrTXn3krVqNSXOchxrmfuJg4pJzTI39lt79Sb3xJSOisSbgqD1K1+1tcVcUkTpxLlK3tmqPuqsPoFNVfQiAqkR1VeswVDlzu0BpuPf6MahayOFTrJUqnA1MsVehDHrIYlG49K4lxk5f4Q9N2fgJ7Pq/PdKciZUwifthMistGs7GoGvWr/D6TMKK3UXxeGjIk6NvIKqn43MQeWAfAMem/7yXJuoHPybEDopEVFW9mGg5jLeZDxehiu+jdaeZZjnKXoFO96FQvPtkB+JNH9aXw9arqGvYdrgFAV+5hVLPzkkaDVx+D0V2OUr8PzeguZ0SqFY9PwTc4s3sCmBrqRnczO2UP0q1f1nnz5oVKDoFAECKcTme4RRD0Ixr0yScrPFd+HAN0k5jMDySqh5B8LpA0pOiqsFBOhS+aPaaTGJczq3s/LoKuUxfsNdu/40dq1z4LgDJoElntGG478/JRD1Sh00hkSLFoo5OQS3U4fBKqqiJ1M2NbAz39jGoasjhYe5gojYyEBAYzGdEWUOtCFrLYZiHvUef6Q9Pe/n/gKEcdNAHptLvRanVcJiuoDcWQQRhvrZBwwmyKUk9Ckf1J7jYWVDA23Rb0PkVZ4zDpNeg0Ggyelqnjwf/5bN5nj4iC05KnDoPOL785Jo4YdSDY9eCr8hv3nf1+NfMsmzwu9JL/u1rrcPWIZ7mncbscgdc6Q+t73IZnDsJY5UGb7H+/pLpyjDotRp0WkgZ26/6q0YosK7h9R66PFy66/dv666+/8uKLL7J3714qKytbZJqUJInVq1d39zYCgaCD5OXlhVsEQT8iLy+vcXJaVM2E4xYRn3gqUu4q3Lu+AJ8HHz6ih07me+UE3qkbx7hv9onJaJjwVJegV1UkoxX0JqLjB9Cwzl5XWdx+36oS9IBPhai4ZLJ/dzledRGjog0hM9qgZ59RLUIWa79Estf6J66yB01NMYPlypCFLG7eZ2+7RpZWx05fKqrdTpWvihPrDcTm6dzHZ8ZFhGERSWSmJpGZ6l9k2FhQwbK1eS3eY2tMHMMHxAIq+YcKWlyjqVHN1NbrFvYq7prG10YrRCX6Xys+cFWB2da56zXzLGfodKge/xzcopWpCLFnuTXjuSN0xni2JaZQM/U6fG4XyYNHtNomNi4JHIXgrX8/65qUOml4TztAa+PJq9FRe7Ca/LJ+FCrZlFdffZWLL74YvV5PTk4OcXFxLdocqWSAQCAILbNnzw63CIJ+xO/POjvIo3DZKVls+/hzVLsJk5SORivjis7kuHOeZhoa8oQnIaz89OsezGVVKDYbY4H4pFTMiVHotRK6aHe7fdOTYvBWpOJTJbQ6HQmx1h6RsaeeUa2FLO5710es/QNMshs9GjRafUhDFidkxsNU2pzQVmttGHwKkiO4jl6D8SaMtiMzNt3G+Mz4ls8VjcZvALmrmTA62Chp7gkdm24Lg+TNaG64qU28Oo7yThtuzZPhoDQursQaJRStLmSe5baM5yPK2Enj2WKNI2fS6e1ftOF9akjZ32C4aXRgbmmHtEZb47FY44j0gNJuGW533XUXY8eOZeXKlSQmdtzKFQgEPceSJUtYtmxZuMUQ9AN8ssKCB94kfezUoB8416EdGO15uDQWqmOOQZc4BLQ6dBDkSQBhvPU2krMcFXAZ/BMYg8mCIdbm32zvrmy374DJF8Hki0Dp2TChnnhGtRWyWKzGU6HLRq9ROfbMe/x7WBJzQhqy2N5kNCYxFVO5Hr3OjSp7kbSNhbh1Wo0w2jpAcw8lNPmsDFFQfYAtn7/JqcefAYk5+NC0Hr4aZvYeOIxSUotWI5GgmJB0UGN34pEVpH1FDE7I7vC1WkuG4y7dg6KqyDozVrOBGGdRyDzLbRrPHZAx5Mazqb4gu6cWZB9bd+8hqrQOTewAMjsYGdDWeGwpGeyZ/h+8xSXw0O9CI2+I6ZbhdvDgQW644QZhtAkEEYQw2gShYvM+ewujDVUl0XcYt1ZD1aApnNos9bIIAwsv8UMn4q3chyl5eONBS6LfcHNUdOwimiYTMtkHzkp/spkOrmYfiZ54RrUVspioc6Ca9dijhyENPimoT2/o6vDfnAsn/h4sCf5wTUGHKFr1MFLxVogdRPo5d7f4rCTFx4KELUiF30JNMZOTDPDhNShxmayRT+AnxzjGZyVFjNEGUF1VAW5/6ZQEYzQK0ZTU1HvBSw/R0arHbSXDca59En3tfrQaHYTYs9yu8Sz7/Bkr3bX+fXQ9bDwXOQ34SuvwKQoDqitwVBYju7w4LNFkdnM8FrOZU8eOZPvXBSGRtSfoluF23HHHcfDgwVDJIhAIQsCsWbNYsWJFp/v1Rvy6oG8xITOem1fezNNvPN2oF3WlZMfpIC4GeezYVvuJMLDwMWzmFS0PWhLAXhic7r8DqIrM3ifPxef14hg2i7GzWrl2F+jqM6o92gpZHHL+ff4QtTbSe/e4rlqE/neFAwcPYi7dj6tOCmQ0bfisJMVH6pbHqfBtwOo8iKLIOLxe4mM81O75hmHKLyxIK2Tc5CURY7QB6GIGUJI4HslTS1R0LBqNBrR6DJKCqrg6dI32kuHEjTi7hQEVSs9yW8azNncVVBb4M1xq9N0yngu2rMe+Yw0avYmcM6/CaGpZTLtOisLt8hdor60sI1bnQ9Jr8cV0rhRAu+PZvq1T1+pNumW4LV26lPPPP5/TTz+dk08+OVQyCQSCbtBVo6034tcFfY8v33o2+IC9KPBSG9f2GrEIA4scitxmlPI6XOX5DG+jTU1tDRt+2UpUXCo5GWnERRuRNFoqZAt6bwWuqpKQyRNqo62BNvXNaPX/awOhq5GHpHj8L7TBlbx0Wg0LErZQ4duAx+2kTErAKtnRGbUUeWPrk3SU+uvo7Vrhz+4ZIYya+FuY+NugY8df+QqSKRY02jZ6BXOkZDgNddpcdVXoVdASWs9ya8ZzotaBZI4DnRHF5+qW8VxxIA9N4bcogMo1rbYxJw9ha8oZaC02kizxDF/wPHgcfsMxRONBblFBLmLoluH273//m9jYWE455RSOPfZYMjIy0GqDlU+SJP73v/91S0iBQNBxFi5c2OlQpIiKXxdEFC30yV7Y+Dp2IJ7iHVSXHUIXl45t4DG9L6DgiJQpVjQOL+DF5azDZG65il2+fw8JX9/tf/27vxE39lQAjLHJRFfXEKML3Zb9rjyj+jL7Kx2UVruwGmBoqjAQO8LE9GhUUyxycnLwCdmHNncViVoHhdYM3DXlaHVQ43TjcHixRRmwxWUjle2CXSv9JRkiuKak1EmP7JGS4ez55WuqvngArc9J8pxHSMvyL9WE0rPc3HgutGaQYfU/U4oqHN0ynjWyG60GfKoGo8HYapvMzGwy518bfNBgCdl4SiQJZ03pkTuGiW5p85YtW5AkiYyMDGpra9mxY0eLNqFMISwQCI7M7bff3uk+kRS/LogsmuuT/WAeUbKCzpqErDGy45W/gqriG3E244XhFlYKd/9C6f49mGNTyDluEjq9f0+VKXEwh6OHolgScblcrRpuzqrDgdfR8Y0hR8cdkw2FxWAOXe21rjyjusLewkLckomByfHEmMK3v2zXGzcRW1dISdp4hl50Z9jk6EtoFB9oJLTNa3mV7YLKAiRzHBnWKAqROOz0olhk4sx6f90ySQJTHFTk+9vXe6H6C60ZXtWVJRT/8iWuqsNoff7vanX5gYDhBiH0LDcznu0OL7iLUfUWqtxqt4znMakmqLah6i1Iml6aUzQbj1yZj8fdee9db9Etw62goCBEYggEglDxwQcfsGjRok736434dUHfo7k+7d69HUNdNe7kLCbpDbgNcRjdFcjVoQulE3SNkh1fod+1Ao+kQTPmo8DxYydM49gJ09rtO8LqQRkUi8enoEtOazzRUBfJWenPNhmCyVRXn1GdpWT145hKt7AxZgTTr3i4x+/XFtE6FZ3qwVPXuT2GRzVyQ6hkM4PbXev/LdIFe2PcbjdEmRoP6Az+a7gjJ7l7xa/r0EkqpoQMDElDAscVWaGmqgxrbCKaLv6Wlu7bg+OHFwEw6jXEWwwYNNUhkbsFzYxnTd1eoupKcEpmYuOGdc949vr3+kk60xEa+qmsrMStSMTHxgSKm3d3PAdr9ERyIbPI9R8LBIIukZ3d8ZTCzenp+HVB36OpPvk8LgyOes9MXAYAAwdmYLG70MW0XyNM0PMo9YaB12BDo+3YnpkAdaVoJAmTxQrmJvvBLE2LBNtDkmyjO8+ozqCt9u/HtETF9Mr92mJoZiamQ8XorXJY5ehTyK3vccMY7V9A9LkoqnBQ5fQSa9ajU3RUOb0UVTj8hoPP4zf6jNG9L3sb7Pl0GQZ3Ba5BJ3Pin/ye123ffIT3myeRVJmMi18gPnlgl67tqrUHXmclRGHSa0Gxt9m+WzQznqM9JaiAWXUS5KfqivFc7y1sbpg3x7P9Y9zlhVRu+YzqOif5WisTF7+NtivzkWbj8UanUWyKAoo7f61eoNuGmyzLvPPOO6xZs4aSkhLuueceRo8eTVVVFatXr2by5MmkpHQu04tAIOg6ZrP5yI3aoSfj1wV9jyB9kjTEzPg71cV5DMg8DoBBgwaDtwDk9muECXqeiUkKshqLyzbkyI2b4yj3/x8VXN7HZ47H55XxyipUFGMNgeHW3WdUh3DXMCZBwemJom7YsT1/v3ZISBkE5TrwVIIidzgRxdHM1qIyDN4avGYno5qeSMxBsQ2mNu9b7JixWQzEUotRrcKjicbusIBax2C5EiljEiTmtHWLXkfn82c21TRJlGO0xOBT/QZ9TcXhLhtuw2JklAFWfIqKPjoB3PbGwtShppnxHAtoJAlJgjqHgyKJrhvPvvoFQH37z4gf13+EuXpv4G+NztA1ow1aLga4FKKNkVu6o1tL5Xa7ncmTJ/PHP/6RN998kw8//JDSUr+iREdHc8011/DII4+ERFCBQNAxNmzY0L0LNIn39lrTsTt9FJbXUVjuwN6w+TstG8lV6Y9fl32hEVwQkTTVJ53ewJDjf8OYGfMYnFNfCiAqyf+/sxLkyN0XcDQgOcrRaSSi4we0OKeW7aFm11oqcr9vvXNDGJ8l2HAr8UWzs7iGvNJa9u3fFxI5u/2M6giVhei1GmLMelIHh3ny3vAdUZWO19I7yvF4XDi9MnW+4GmqDw2rlfFUKNFkaErJiDchVe3D5C4lljpsZh366n2UyRbkYTMjJzGJ7GOITcugODPpqY3OjMTkVJJjjAyKMxNP10MbDb5aTHot0SYD2oT6hZvaHgpfbzCe7aXY6zw4Y4YQa9ETY9YTZ1SxO7wUldehOishPqtTxvOG3INsO1DFTwfb31OrNhThxm8kpg3M6PJwmo/HZtGTZutYqGY46Jbhdsstt7B9+3Y+/fRT9u7di6o2RoVqtVrOO+88Pvnkk24LKRAIOs6ll17avQs0jfdOiCJWr2Cp+BVt5V5izTr/SppGGxy/Lui3HFGfopMaX4s9POFDkcFZbxQ0M74ANix/gLwP/smutf9ttfvPu/awq7iGXTXBoWm2pEYjMFQlAbr9jOoITbOf2jpa2riHaOrF7CkvSD+j+JiLKMy+CG1WY6mphkzGbzvGUZI2nbgYK5qyXeiQMWgUjB47g+UiDCYz3+gm8WzZaHyyEsZRNMFdjc1iIDHaSGpS4zMzLimNtFgzidFGrEpV16/vqu9rjKFaF0dFnYeDB4pQldCPv7nxPCDOigRIQFq0plvGs+p14lNU3Pg9XhsLKlr9DAcPHEhGvIXspGjiowykDwo23HyywsaCji2StFgMiDP59+hFKN0y3D744AOuvvpq/u///q/V7JHHHHOMSGAiEPQyixcv7t4FmsV7GxyH0OEjSq0NbBwG/PHrijeiNn8LQs+R9KlGF0dxtT/E5ODBonbbCnoQp93v0YEW4Y4Aqtl/TOMsb3HOUecvUO30yjh0tqBzZksM8ox/Yr7gBbJPmRsSUbv9jOoIlfWGmyEazHE9f792cBoTKKpwsKeklp15eWGVpa9w5qzzOPu8/8f48ScBweVnxmUlMe5PS5B+cy2kT8ISFYXG58aiByljEvG/u5Hi4xaxsaiaZ7/KjwzjzdPkd7JpTUFDFDQk4nC0/G52GHe9t84UQ57DQlGFg5LKKmqqQxvC3qrxXJmPz+PC43bhth/slvFszDoJ7+ApWDLGBurLtvYZDhwwgPgoA1ZTvVEY3Vg2okHGZWvzjmi8tbUYQG3kLrB0y4dcVVVFVlZWm+e9Xi8+nwijEgh6k5dffrl7F2gW721UZP9qmgR1Hl9Eb/4WhJ6m+rT5hWvRWOKwjfgtg4+fAoDLGE9xld+g1x3eR9rwSWGR82incF8RtQerMegkrN4omgdLDhw4ELN7G3qDF1TV/4WuR3VWkmA14/X6ICktqJ+k0XDCmHEhlbXbz6gO8PPWX4hx1qJNy2JwmFfP9dYkKus8qICn7GBYZemLNK8ZGshkPOpcGHE2mm8fxbJ7FWj0cNZjaPVmLpMV1Po+0LHapD1K0wXO5r+ZlgSoPgB1XTfctu3dh6W6DlWrxZI9gIZAw5ryg8TYErp83aYEfQ5ZSYybvAR1x//wbnkHX/43oKrIPhnTkMnED5tJcdloNhZVo36V3+H3f8zplwTdr836skYruGv8SZM0usDiTGfqy7Y2HmnXCv8WkKqtXX+jephuGW7Z2dn89NNPbZ7/7LPPOPbY8G4KFgiONmbNmsWKFSu6foFmm78HmaOIwwuShiqj1V+zJUI3fwtCT4M+1VZVIJXuRAXKYrMChltc/AAKJQNuQyxRqsgwGi7qKovxygpeGaIsLSdq6YMyoMQIqP7V+SZ7RKISM4ha+J4/a2QH03B3h24/o46A7PNC1T6qFRm3lEKYAyXRGUxozDZMSg1Rqj3M0vQ9Nu+zt10zVKuDgSew4d3HmDhxon8PYezAFuVtQlF4ujsUl5ag2J1oNRLRmGlaSbECK3KNG8e+wi7rqqO6HJ/Li8tr4vicE6iz/YOYxDQMMclH7twB2jKeqwadSv7KZzHph6BRZby2IYycvQytVtdt47nV+rKT09Ht/BA2v4Z8aCuyLINGg/Ttk2jqKniu/Dg2FVUfsb7skRYDSPwYmN2t96yn6Jbhdtlll3HzzTczdepUpk+fDvgLbrvdbu655x5WrVrFM888ExJBBQJBx+juhMiHhjXKeIYpW8jQlRJn1iM5AY2WjHh/xi599T7KTBbih81EGymbvwU9QoM+uUrzMeu1uHwy1gGNWQt1ej2jF7+PUS/0IJxYzUaqE7PQOEqxJbZMThK0781RHmS4Af76bEfKGCn7QpLsoSeNNgB39WFizQbcHje6lC5k2OwBRp97k98otqaGW5SIx1NXRfXXz6DRGzHlTGdC5kiYCmPTba1PxK0DmDhxIoqq4qs6iCHWn5mxYeIfbqMNoKSsHKXGnzExQ2MJMtxya00Y7U58dYe6vshgTcOn1WOITcFsjcNsPaG7IgfRlvHsqLWDJOGSLJhOuoyRp5wX8OaHwnhueo2f8kvZXPA0413fo9YexuOVkZHQKDKGkh1UfP4AA3STmHDcIi47gpF4xMWAxKGdkrM36dYT+Nprr2X79u1ceOGF2Gw2AP74xz9SXl6Oz+fj8ssv751NyAKBIMDixYt56KGHutS3YRXqJ8c4FqQV+lP+2wuhPl2xpqaYwXIlZSYL3+gmUVw2mstkRdRy68c06FOir5jEAVYUVUVpll5dGG3hJ33MNBjTTpHtpl44RwXEd9ygOfDjx7h+fBNcdgZd/g5GY/fS+XfnGdURLPGDyLpiuT/8LATlC0LCwNBOpPsz1VV29v/8BQA6YxajBo5sd8Jfq09gy45CoqyxqLtyGZMxIXBOp9WE3WgD8KoaHLp4jLIDi9UWdE5r9S+qGHy1eD0u9IbOe70nXvJAKMRskwmZ8a0az1aNG32cGVlR0aZmBYVgQ+eMZ5/XQ/5376MzWLBljCQubUjQNdYc/pSkvC+p1MlYEobhcfjDGWXgsD4TQ+0BJvMD8YmnotW2HwnU1nj6At36tZUkiWeffZZ58+axfPlycnNzURSF7Oxs5syZw6mnnhoqOQUCQQdZtGhRl/q1Fe9d9ek/MDqKkXwOFL0Tc8akLsevC/oeAX2y+xOPaIxWNFHhnwgJOofPFE9ljRuvrOApLCBz0PjAuV37ivFpTCTHmEmytix8a3f48Fb6N+tXlR0meWBmt2Tp6jOqU2h1EBfuIElBV/A2SYKl1RnaaeknKiYebVQcKgqeqkM9KVqXOeG356BOnY3bp2DUBf9Wjjjp96hjJhNlS0HSt194Opy0ZnhF4yI6ul7mhNb30nXUeHbW1VD33QsA2E+4OGC4AehQmK7ZRK2mlr1KBrG1CmZNFBpJxa2JosqlYLOmkyYXIeWugpGzjxgdEAkGfVcIyTLpb37zG37zm9+E4lICgaCbrF+/nqFDO+fmby/e+9f1n2Lz/IpGlZFdenLOegKt3hh5m78FPUJAn+oNN2zpLVZVUWRwVOCyF2MYMByNLnKLlx6taC029ld5kFQZz+GDZDY5V/7JfZiq8tieMIapl/6jRV9L/ADqNBJ6rQa5phSCeneerjyj+jqqqlLr9lFe62FArAmTXhThbot4I0QlRflz6CTYjthe0mgoI57s9IHED8rueQG7iCRJrX7uUfGpQGhDaH9a+QK+vPWoGj2Trnw2pNcOomm2TEM0iteNz+fDYI5qu08buF11gdf65l79sl1o7IVE25KweQ3YHV5U6xAkCaqcXmwWPRnxFqSaJmWKUkZ2dVQRTbcMt/z8fLZt28asWbNaPb9ixQpGjx5NZmZmd24jEAg6QVxc51NftxvvHZ2Cq6axJlJlRSkJKYMibvO3oGeIi4tDVWScpQWYNCqaVmpi5W5Yheurx5AVlUEXLSNxYNvZhgU9w46fvsby/9k77/A4qnNxvzOzvasXW5J7twHjQgs1CQRCIAlwQwqkYCA4EAikwSXlOje/JA7hhgCBUBLIvZAQggmkQAgYQrcBg43Bwk2WLKtv0/ad8vtj1FZaSdtsyfK+z6PH65k5M2d2z3xzvu98xV1BefV0HPaRkyZBFIlZKkjKSUQx1RVLinYjagpWc/rVjRl19QjT+mLijPmX/8hFRmXDO427qKispcptRRInRz2mXTt38P7fbsel+FHOvp7ZiwqbqXMqYRYUzJY+44/DllGbxIILWPDJTx7EXk1ewv5uYr4D2N1lmN2VCJIRJdqLKdyGJkhoqoogHiSjal+2TFXT2HbvFZCIkFz8aVacsybrU3mMKvY+d3xqhpU06StTJBos1DttaFqEQDQJgNuqK22iIOhlipTElC5TlJfidsMNNxAMBkdV3O644w48Hg9/+EP6gp9FihQpPNOmTcu6zVj+3sddsg7fnjcRNv43ZoOIUe4BpgOTK/i7yMFh2rRpeNtbaDngRRDAXO9hwbBjJGcFiqoBEOhpLSpuh5hYJETimXUkgJ6ln+HYs7+U9rijrrgXq8mQWndVVTm6TCEpO4iPYmQV7MMSm+RJLjIqU0IBL9rja9kvWGhe8SWOO/38g3atbCixm6hP7AIg3LMfKCpuo6IkBj9L47tKwsEdUwUh0Kqnrbe4wVjYzK17tr6M8uqdAEy/9B7Kq+txl9diaDFiMggkwl7MzpG1HQtBS3sn5mAMyWgkoRkwahqyPzd3VYMax9C/ImkbZnzqK1OEHB/7JEdAmaK8VPBXX32Vj3zkI6PuP+OMM3jxxRfzuUSRIkWy5Omnn86p3coZpaO6OpZUNeCxGrEaJQzhjpR9kyX4u8jB4emnn6andSegl/+yVo5UysqqplPuMFHjtlCmBQ91F494/D3tA58t7tHTf9vMxlSlDSDqwywJOMwGyqpGmfxKxsEslOHufLubs4zKhK6WDwAwaTHKSgtTv6oQeMprqfVYmVFuY5YtOn6DIxklOfhZyszt+mCOqULwxu9vZPvdl/LOoyNdkQFe+e13eP1/Lua1R9Znfe5keLDItMOtj/l5s2cxq8LO9BIb5lj+xpbRONDZxYFAjL0BcFVMo9JpZqYlx9Wu5JDnwjjMVbJ8PpTMQIv6aO4JE4gmcVuNuK1GAtEkzd4IqqpAzAelM6d0maK8Vtx8Ph9Op3PU/Q6Hg56egzdgihQpMpLrr7++8Ce1lenWQlWGUPv4xxeZMlx//fUkIwH2n/BVop17qaybO+IYd2kV7lKnnn20WKfqkFMmBHFXOUkoKkyvy65xZIgilqb+2+C+cpSIn0Sgg/xySh4kGdVHndBFVZWDaFLB1DB5Jm8Gs5XK8gq9hp7sn+juTGpavQFUXwRREHDJIqPPMge5au1VbH/7VcLdB5ixcAWV0yZZYppEiKSiERfTu36KkW7McS/R3o60+8dillNFLbWRwIDF0nd+R9XgAaEOqDg4z4LW55KoGO3Mnz0X9h4AIZDbyYaupg2vJykZUOaehbfpXYyRFjzOOurL9Htt9kbwhxO4ovspcZUgzP9YQcqWTFbyWnGrr6/n5ZdfHnX/iy++yPTp0/O5RJEiRbLki1/8YsHOpcpJQgd2kAwcAItH35jDi6XI4csXv/hF3OU1LP7Q+az49HVYh7uwAIjSYNr1cNeh7WARjFEvVpOkW6DLxkhyoMgQ6kJtfw810WfdHrqCZh/dnWpzl8i21gBbP9iTd38LKaOGYwg2YzMZKCutwOmpOGjXyQl7X3+Kz8iYeANhekIJunrjxLXMJuDXX3MVyad/gOnN39Cx642D3MMs0TRqrTKldhOlo6wCO8uqKbWbmG4Kp90/Fh4xSqndRHVl5WDiKPuQsR/qzKXXGbH6C//FgrV/ZOFnfwrOPmUx5ochmUEzZW97N3u6wuzrCdOrpCZxkRWVe3qW8bJhNSazlQalGbG3HTHqpd4YYBbNBGUDmy3HI89PH741VchLcbv44ot5+OGHue2221BVdWC7oij88pe/5I9//COf/exn8+5kkSJFMueRRx4p2Ln83i52/f7rbL/7y+ze10RTT5htjTsKdv4ik5+Mx5Ojz0XvIE4SiozCwKqZANbRE3+0vPca7911CdseuI6WPe8D8P7u3ezpCtHii6BaR19x0/pW44wxL9qQ930uFFJGjcDXl0ippGFk9tOJxtE3mS4+I2Mi2yvY41rJXvtRGM2ZZSe897f/iyboU9pkjjFWB41EmFq3hfpSG3PratMesnj2TOpLbdSZI9mfP9a3wmV2D24zmIlJdnpjSTra9+fQ6cwQRAmLw4OrrBoc1YM7QtkbeHtDIYKxJL5IEtUwuK7fn/V6c3OQ9mVrKf3oNxHqV+tutEoCUTLhmHMiH8z5Mvdon+Sel1uQlfxk1GQmr7XE7373u7z00ktce+21/Pd//zfz5+tLsY2NjXR1dXHqqady0003FaSjRYoUyYxzzz2XJ598siDnikd7Bz57NSfGiA8t2oaqKIhSMZ31kUCm4ykgelDCCaKxZiZ5moCpR/+qma10TBchg6tCd6cEwj59YhXsbscck1EMVurGmCSXLP4wHWULsXqqUDXI5+kvpIxKQZH1otsAabKfTjRdqhM5ECXmbaZOVjAYijI0HcccewLHHHtCVm0++alP8fAlM7HEuzGUjpPA4lAzLGV+WvpXu+UYJMJgyiKdfrwvrtjiTtn8tteEJRgmKu+lKk2zQpOwVhCNJknIKkrrPqqzrKNotNjpdUxDkGOY+1w+h5cquuxDM/Xi2ovP11P+x0NgdiCWz+d0RHYfASWK8lLczGYz//znP3nggQd47LHH2L17NwCrVq3i05/+NJdccgniwUpBWqRIkbQUckLklGQMJVZUVaPTPQex7W1kazmxSACbs5iQ5Ejg3tvXs+V312Msm0HdcZ/CXZFeLdsZtmLwRoAIFfEYJnNhM6cVGZ13d+7BEQwjiNMZa6pUUl5NwmbCaBAwSrpLlpsAglEiZB0769zcBUuZu2BpQfp7UJQ2oLN1N/42HxajhM1YzcHJo5c77YoLJagrFS5fF2UV1eO0KJIpTz75JGz8MbT1TL4VzfigAXTUbIe2YZlbs1Dc9h1ow5yMIZSbUhU0RyUE9yJFDuL3oWkDK9sJawV7u3W5orY2Ub3k5KxOtfCEj8MJHx/4/6j1ZUE3UA2r02aAlBJFMDWVt7yj90RR5Etf+hJf+lL69MNFihQ5tNx44438+MfpM1dli0NM4HCYAag6/WKo+KEez1RkyrC5yZu2DEQ//3v3rZzhbkLueJfIMefQb9OVFZUtLf6BjKIWTzUyIAsmgt5OymvqD80NFCHib0eOJYkl7WMqbhabi4aqEj0JgKhPJhec9y19oqvKh6az5C6jxhurPft3Ek8oRBIKon0wvn74WJ0obCXVhACjQSTub4ei4lYwbrzxRn78yVn6f3rbUxSKicbv90IkgUESMRnspCtwkLSUkEjIJGUVrbudEk9m8lNTVbw93QiaQjJiTFHc6laeixw6AdcoxrZ8SSZifHDbJ1GMdgzH/AeLPnQBisGKJEdzLgkwlDHry47CkVBfduqmXSlS5Ajl4osvLtzJhqbnNbuKStsUY3OTl7ue3z3mi/G4+dUYOveR0AxUVOuTiaGWUE7VS0nMPOY0IvOPw1NSirHoAnbo0DQcRhAUEdU1eikAQJ/I2sp1d8L+uDiLe4SL1cEmFxmVyVi1xrswmg1EZI3K6bOB9GN1opgxZxGCdAWisxKqi7UOR6WrUR+jBis0HJ9Rk4svvhgMffGNckx3HyzAuB7PWDAaQ40F+zs6kXv02LVpioV0KXN6BRfNHbpLpdjSTMmcVRldJx4LIwoCmgYGmydl37QFK7Pqc7ZEegMkFRWUXpIyIAjUnnMTdk8pzrL0sXzZMFZ92bGY6vVl81bcnn76ae677z727NmDz+dD07SU/YIgDLhQFilS5OCzbds2li4tjEsTySGB0sb0aYyLHL4cU+dhxYzSMd1KPP73WTTNRdI9E4PBMMJ95Zg6DwB2uwO7feoWPZ20CAKLrnpIz+KmKeMfbyvrU9y84x87jH1P/gTZfwBt+grmnHZJDp3VyUVGZTJWZ5z6RVh9HlpvO4LJNOpYnSgkRzks/dSE9uFw4PWNf8Ha9CyqycHR1/45ozbbtm2jbFkd4c5e4kkVT0sT0+celVc/MjEWpGO4scAQDtC/9md1pFcm3WVVumFF04gHM886arE5OeqGv5KMhdDyyzeYNUIyTKndhKJqCB49KVJNHspiuGc/KEnMVieGvoLhuSpeU7m+bF6K2/r16/nOd75DVVUVq1atKtxksUiRIpOCtm4vUm8cSQCPwYKoqvh72omGe6mdMXlqJBXJjeFuJTBkQqzI0LWD0vg+hHgZppK6sWMOikwsxsxiCnslD0o0QaxtP+6Egi+SoNRuwmIcf5W0Y+82TNFuopqbOfn2N0vGHatDEhUI5fOLY/VwRkmgapAks+LbAzgqCcd140Wwaz/kqbhlYiwYTjpjQaLmIrzLPko05MM+iuImGYx4Tv4qFrsb17Qsny5BwGjNpNpdYXEJMVylfQbdmnFW+zNg219uw9L1DjFHPcetvSfv801V8lLcfvnLX3L66afz97//HaMxywesSJEiB4VCGlBaO70Y/FEQBEqNVl5/8CYsHW8Rs9dQ+7XfFew6RSaO4RNiQZVZU7YVaedT0LOLykQLdLShahobW0TeiixnxcyK0ScxSlLPimb1HNobKZIRH4RMSN16EhnvO8/T88JveFt0s/hT36JhxtgTRtVaBtFujLHsV+uGkquMGnOs+ppATYJoRC2ZwUbl2PHH6gShaRqRhILdXIxWScc0p4ToNJOwZa6MLF26lNKqOoJWG5q9AqctXSRZdmRjLKB8PjJiWmOBQTJhq64ExlZuZhx3Xt59Hoqmqmz+03q03nbMM1Zx9IcLGEYBqdkyzWl+q2zjDGU9NEMbXny7SAp5SQ2fz8cFF1xQVNqKFJlEPPzwwwVT3tSE7iqpiGYEUURyVkIHmKLdaKqKUMwaOyXon6AIqkzN1tvxypsolyJokol4MolVEom072Qu97Omdh/LT1yXdiK87Y8/wNi6iZBjBisuv3MC7uTIw+/zogoibpcbSRx/kmR2VSIDimAg2PIeTsWPU/HjcYyfxe6o+XMwt7Qj2vKrkZSPjBptrComJwnBhEmJE9n1MnPVd8YcqxPFv556HO/O17EaRc698r8P2nUKEZs1UUx3GcBjBY8n4zYPP/wwP/7xj1lw9WMFTUoy2Y0FmhxHEKS0ZUAEUURo24Ip7iNm8RT+4mnKHHTu30PT39ZjiHTiOu1a5hz9oYxPN6vEgKBZiVeOXouySJ4FuFetWkVjY2Oh+jKCeDzOt7/9bWpra7FaraxevZpnnnkmo7atra1cdNFFeDweXC4X5513Hnv27El77H333cfChQuxWCzMnTuXX/3qV+Oe/yMf+QiCIPC1r30tq3sqUuRgU6iMkgArP/V15q/9E3O+eBcA0+pnMr3EypwyE2oOMTJFJi8GSWRN2VZOkDeRiEfZJ9XTq5pJSjb8CZE9Qj0ug8LK2KsYGtOncw8pRmJJBcKTLB33FKbxX7+l+e7/YPP/fGZEjHk66o85ndJLHmTu1RtYVOOivtRGtceGs2R8VyeruwpRECDq01ccciRfGZVurIaTAsnuvXR3tbNHmzbuWJ0oPNF9zIu8RW3wHdSDVCS4Pzbrnhf3ZlWIuN/N767nd7O5aQLlu5LU/5UyXzUbGFMHIZNkv/K2st6lGwue+Tlayya9n5IZVUkQ2vUyc3ffzxphA2tOrEtV2jJ4LnPlzacf5N1ffJx3/ufTqPLIZ1JwVGI1SpRqvoJf2+fzEYrLRBMKWl/5ApPFhsm/BzERIuxtzep8lRaNCqeZ6RVFxW0s8lLc7rzzTh577DEeeuihQvUnhS9+8Yv84he/4HOf+xy//OUvkSSJs88+m5deemnMdqFQiNNOO40XXniBG2+8kR/+8Ids2bKFU045hZ6enpRj7777bi677DIWL17Mr371K44//niuueYafvrTn456/scee4xXX321IPdYpEihOffccwt2LkGUsDpcuMtrAKidPpNyhxmXxYgUai/YdYpMAhQZaedTlEsRks46/FGZULiXpKyQ1CRcDhue2tkIMR80/iPtxN1dXoPbaqTGnECTJ1kR3CmKGtYTGQhGC0IGk1aXw0l9TRUuqwmXGqDUbqK6uhZRyiATqK2s74OmK285kreMSjtWgyiqhqgpeBzWccfqRFFRNY1Kp5l6twEl6j8o1xgam5Wp8japErkoCf1fKXNvrkK+99KRzligOqtRrSU0J93sYXTD1vbfXkXjHf/Bjid+MeY19r3/Jq8++D1evXstvYHMFGclHEBWNWRFQTSMXHVbsXg+86udzHPEMr/ZDNm1v41dnSF2dIahz73RXVqJ1WqhxGaiTPVnd8L+d4bBWtiOTjHycpX8j//4D2RZ5gtf+AJf/epXmT59OtIw4S8IAu+8807W5960aRN/+MMfWL9+PTfccAMAl1xyCUuWLOFb3/oWr7zyyqht77zzTnbu3MmmTZtYuVLPcPOxj32MJUuWcMsttwxYZqLRKDfddBPnnHMOjz76KABr1qxBVVXWrVvH5ZdfTklJquYfi8W4/vrr+fa3v833vve9rO+rSJGDzcEqbguAs2bwc287VC85eNcqcmjpbgRfE4K1hHqnHa0nQiDkxmQ0YjKI1Jfa9NUWSwl49+rHDyuAumjuHOjuc7kLd4P74NQPOpIYz+VtoSuBnLASKUut+5SRy1t/SQBbhqWq7WUDH7VwF4IjXWLz8clbRqUZq8ZAHFEQEIy2jMbqRNFQPxOa+iamsR5wFN4lsVCxWRNFly+IIZJAi0Gm307/mIrG4rS3tRDs2s/Co47DZC5QvNQQY8E+Zz294QhtvS0kTW78qg2P3YSnZDZCd6NuLFh43oD7YiTowxj3EwuFx7xEtNeLte11AALdbTjd4999rTWB4DARsYzyDNv7VtKjvr4VwsKFNqkxvRakYrANhE0Iosj8WbP1zLXGYHYn7Itxw2AuWB+nInk9maWlpcydO5eTTz6Z5cuXU1lZSVlZWcpfaWluQunRRx9FkiQuv/zygW0Wi4WvfOUrvPrqq7S0tIzZduXKlQNKG8CCBQs444wzeOSRRwa2bdy4kZ6eHq666qqU9mvXriUcDvO3v/1txLl/9rOfoarqgDJZpMhk46KLLircyYa7eNjKQOyz9xRX3KYW8ZAerzHkpZmQ7LRGTSj2IYWCDSb9uHho5DnsQybyRXfJvMnE5c2jBSl3mKmfXjewrX/15Cd/f5/X9vSkbYci6zE6APbUSZ+sqGld5fyCh8b2Xra1Bnhv196c7gkKIKPSjFUDCoIAomGIe91YY3WiGPpdhzNP+54tg7Ws9JW3e1/YifLOn2DDFfDENfCPb8IT16BuuIKNj97FW3u7JoXSBrCnw8++ngiN3ZmvEvWPqd1vPUfgkbVoG/8fPe37CtepocaCMjtOwhiTQRzhZtxWg24sEKVUY0EfHimGxShhsQ9mlNzc5B3xTDvLqjEbRBxmA1I0/XM7/NmssyaZXmJjXv0oddOGGlcKPN7mnPJZ3B+7Gc+p16TucPa9L3oznyNoqkp7j5+u3jhdsckTkzoZyWvF7fnnny9QN0ayZcsW5s2bh8vlStm+apVelPDtt9+mrq5uRDtVVdm6dStf/vKXR+xbtWoV//znP+nt7cXpdLJlyxYAVqxYkXLcscceiyiKbNmyhc9//vMD25ubm/nJT37C/fffj9VaXMotMjn53e9+V7BzvX3XVzAk/Cj1J3LUJ68HUaJDdSL7DxDcuZOFxxTsUkUmGrNDD7KXYzR7IwSiSdxWIy5LKYFokmZvRJ+cyAndamtOU7PNPiROKnTwJqVHCuOmI5fjENet3v2rYf1K27/ea8cfTfLmPi8rGkpS2r3/0LeROrYRSShUuy0YVSf9a2lD23/zrAUcN2twlc3iriCa1NOtJ4LpFfNMVvryllFpxmqlqCEgEkgK9GYyVieKoYpb6OAaN0ZL5CJYS8BgRpVjemzWJEvk0iu6SEhhMHkybtM/plwVtfSrNcGuFmoaClS2ZpixQBBAok/xGuqKazDprp79xgI5wdwyM2CG2dOB0evDTaudzrSavjmvceTqXNpi8rGAvnO0YuP2ShRVI6moyN4DOFz5F8bup6ymgbKahpE7HFX6v+HOjDNLJpMJ2gP6ipvSq6YtUl5EZ+Kf0FFoa2ujpqZmxPb+bQcOHEjbzuv1Eo/HM2rb1taGJElUVqYGZZtMJsrKykZc4/rrr+eYY47hM5/5TNb309nZyfbt21P+du3alfV5JjPpLEiZMJp1t0hu3HLLLQU7VzIWQo6FicYG45X2xFx09cYJdDYX7DpFJgHl81E9DYT8XfjDCTw2Iw1lNpK+Njw2I/5IkuaeMFrUB6UzoTzNhMhaQkwRCMaSdLaP7hVRJDOGr5qkrLwpMux7VXeBiveCpSRlYnf6gio+tXwab+3zj1ixCyQEIgldAWsPxGiVdcUmndI3tJ3F5qB7xrn0LPoCjpkjC+1mmtwibxk1bKyWWCVsJhGrScJiNmU2VicKk52AYqI7FKeppYArQqOQT2zWRHHMJT9l9mW/Y+Enrsu4Tf+YqqxpYGa5nQXVTmZbI4Xr1DBjQVgxIgpgEAXi0RDN3giqpoGcAHGIsaDfsAJg1pWyUWMQLZ5Bj5ZI6orbqDGI8WDKuYfjEz1saw2wo72X3Xub8v8eMiBpqySSkPH3hokEMjNOxKODiqpkLC6MjEXeipuiKDzwwANcdNFFrF69mtWrV3PRRRfx4IMPoihKzueNRqOYzSP9XC0Wy8D+0doBGbWNRqOYTOmzFlkslpRrbNy4kT//+c/8z//8T+Y3MYQ777yTJUuWpPydf/75ALz00ku88MILrF+/Hq/Xy6WXXgoMBtted9117Nq1i/vvv58NGzawadMm1q1bRyQSGXAP6D/2xhtvZNu2bTz00EM89NBDbNu2jRtvvDHlmIsuuohIJMK6devYtGkTGzZs4P7772fXrl1cd911KcdeeumleL1e1q9fzwsvvMBTTz3FHXfcQWtrK1deeeXAsZubvFz1qw3c8re3+dXtd/DUU09ldE/33nc/1971JP/v8TdZ+4NfTKp7ArjyyitpbW3ljjsyv6eJ/p0qKioKdk+J7haskkbr/v0D97S9qRMB8LV8gKaqxd9pityTjMj3ng/jVR24gzuptkLrB2/jlBIYoz0QDyEF9rHLm0SZexbnnv/Jkff04ou80hJne3MX7+3YMeH3NBV+p0f++Accra8z3ZLg90+9wr0v7ORnlxwHG66g6d4vkDjwLuGmN+n+x4/5/f/cxOP/fouZTpUPnryTK06ezfYXnuCNJi8fufqndHb3sH79eoIRGUM8gBTtwiT38siGvyIrKidd9n3eaPISbHyFD89x8dgLb/PN+57iuY3PD9zT7/++mTPO/Tw3fPO7KffUL8ufeXsPgd1bmF9uGvWegLx+p4+f/ymeVVewPyQynQ6SvgOEognC0TiJaAiHAdSunXQrNn76l3dBMkyqsfd6S4ydB7zs3tl40Mfeeed+HGnnU4jB/YTNVbR5e2nc08QHLe20dvlxWw3s6QgixHw8f/e3QZEn/HmKBbrZ8H/388ZLGzP+ncxmM5s2bWL9L27DbnewfevbGMIdBZMR1//kN6ieBtpb9uIPJwiFwrgsBgxqErsWpdMf4p1d+0mGunh9VxeUz9fPGw+ydetWorEYf/7bP3nqqad4+aUXCW56jMVVFu55/DnueXEvHz/3EyAIvLa1kYi/k/eefYhnH7qNTa+9yg//ax13PtfI3X9+hhUzSvnbLddhkES++93vsH//fnY3t7Jx8/a093TF2q+jIhIOh9m/a9shkXvf/eX/8UFHiLd3H6DjQHNGz9Nnv3ApS67dwJ/9R6GWzJ5wWT5eEsSJRNAyyR88CoFAgDPPPJPNmzfjdDqZNWsWAHv37iUYDLJq1SqefvrpEe6OmbBkyRKqqqp49tlnU7a/9957LF68mLvuuosrrrhiRLvu7m4qKir4r//6L26++eaUfXfeeSdr165lx44dzJ8/n6997WvcddddyGlSqFZWVnLGGWfw8MMPI8syxxxzDMuXL+eBBx4YOEYQBNauXcvtt98+7v10dnbS1ZXqOrRr1y7OP/983n33XRYvnhyB07ky3BqUiZ98Lm2KjM+GDRv45Cc/mf+JVAX+8Fn989ILYekFACR6vRgNIoLFfVBSLxc59PQ/i2/t7WKNsIGVsVeReztIRoIoGhjdNZhJ0q3YeNmwmvZla7nslLlpn9dX77kWq/d9Yq6ZHPfVuybgbqYmsqJy7ws7qdl6Oyf0ubxFFVDDXkRUZKMDL246a89g+efWYTCaBtr1y9mV9S69BtWb90Ln+6BpaLYy1MolPCeewCOR5Szvq0EFpJfPBUhukY+MSjdWld4OEpEgKgIGZxVmQc5orE4Urz/wXcztbxG3VbP66gfGb5APHdv1mDYlieqspvlAG87wPhREwiWLaCh36Ilcgm26W+knbps0iVyyIWVMPfVd8O6B6qVw+n8W5PyyorLx0buYu/t+XAYFm82BKXJAz+RqLWOfWo4x2ILJYqX0o99EWqa/L+P730HY+CMkUUD68PdTvtt0z6b4ol4wWxONSKUzUEtm8KxybMqz2T+WA75u9v7mcwAIK77EUWek9wZ79+93Y7TYKJl5FJUzlxXk+wDYcv+1YDDjXHAac1adNbC960ATrb/X5+fS8Vey9OQCzEcOMdu3b2fJkiWTcn6eV4zbTTfdxJtvvsmvfvUr1qxZM1CIO5lMcu+993LNNddw0003ZVQXbTg1NTW0to6sAdHW1gZAbW16P93S0lLMZvPAcWO1rampQVEUOjs7U9wlE4kEPT09A8c9+OCDNDY2cvfdd9PU1JRyzt7eXpqamqisrMRms416P5WVlSNcMqcSh3sWq6mEz1egei3JIavaQ1wXTM6JK8xapPCkGFBmVrD8xHUIjU8Se/UBxMgbCKgIBjNC7XJK555Fe/dSNjcH0V7cm/a5rTltDYoqUF9ZuFiKIoMub95+lzdnPaVCDwhBEqpGi9BAndRDQ+xVhMYnYcmnB9sNj3PSvAiaCoKIJpkJ73uDueqOEXFOB6vwcK4yarSxGn/9QYToG0hoYDQj1B6b0VidKBYeewqGwEysZdMP/sWGxWZZorrrmoSKKEeAPpe+4bFZE4Wm6RkJJROYnSnvnrFIGVOOSl1xyyI5xlgMGAsiy1lTu4+6yEvInTuICQYMBgMmrZsGY4RuS5+xoHsplykqBklkT2s78QO6O2Nl1MBQqZju2XTG2lAVGUUUsPfXhxslBjEcGHSnNDlGr3225OyRixz5kojHELreByBQPi9lX0lFLf4T1uAon0bJ9AUFv/aRTl6K24YNG7jqqqtGZGU0Go189atf5f333+fRRx/NSXE7+uij2bhxI8FgMGXF7vXXXx/Ynw5RFFm6dClvvPHGiH2vv/46s2bNwul0ppzjjTfe4Oyzzx447o033kBV1YH9zc3NJJNJTjzxxBHnfPDBB3nwwQfZsGHDgOvjkcpw5a2QL/oimXPyyScX5kSjKG5Fpg6jrnov+TROiwf13z8nEg4hfmwdzDwJSTJwmaKi9QfIMzJhxow5k8s6OWUYlo7cH5XBWorochKOxnA7LKOmIx+u9B2wTqcWPQaxPWGlEzf1hq6MlL4yAsiagKppGB1lhHNIbpGLjBprrNrnfhSaXoZwF1rFAqg9JqOxOlG4lpw1/kGFYlhslkk0YhbjaEAgaUSbZIlc5GSCpt9docfxHPUfzDr1kozaDR1TLUkXcneYeEeIuXISyZB7Cvx0xoLeV+5F7f45Zi2GoKnIchJp1ipK531shLEgEQkMnMvu9Iw4//Bns0soxyV4QRNoTrjwY037bAJU1jZg/Mwvifb68Eyfk/M95kIi2ovFKKKoGpI11avOYDQx90MXHNL+HEnkJcF6enqYP3/0oN8FCxbg9eaWdOKCCy5AURR+85vfDGyLx+P89re/ZfXq1QMZJZubm9mxY8eItps3b05R3hobG3nuuee48MILB7adfvrplJaW8utf/zql/a9//WtsNhvnnHMOAJ/5zGfYsGHDiD+As88+mw0bNrB69eqc7nOq0f+iX1nv0l/0z/wcrWVTX/0QM2q/BWn3/awRNrDmxLpJ8SKdStxxxx0FOU8sEiIUl4kmFOLCyJhROREnFCwmlTmc2dLiH33VW44hWlzsa/dhrDs2VQkYkjBjS4t/Yjp/pDEsHbnbasQfVfDGRSx295jpyIcXrPYlBCJxmXBcJhKN6DWoRilYPTy5RYtSQjQaIR6L0hKz5pTcIhcZNeZYNTth/lmw/AsIdSsn1Vid8KRdwxK5WI0SdrMBh82Oy26edIlcEokYoZhMMCYTSGQ+Nxg6pnyingk3lpDxdaVPZJcJaY0FRhPm2Sci1i6jyz6XvWIDu4QGulZ/B2nZBVx2ytyUxCPl849HOeU7xFZcid2VZlVs2LMZEmyEjGX0mqsIRBJjP5smCxUNC6hfcjwuz6HNw+ggyoJqF4tr3Sydlf/K8a63NrLt1vN457aL6GrdXYAeTl3yWnGbM2cOTzzxxIgVt36eeOIJZs+endO5V69ezYUXXsh3v/tdOjs7mTNnDg888ABNTU3cd999A8ddcsklvPDCCwwN1bvqqqu45557OOecc7jhhhswGo384he/oKqqiuuvv37gOKvVyrp161i7di0XXnghZ555Ji+++CL/+7//y3//938P1KBbsGABCxakX+6dOXPmEb/SNpx0Lj31Tr0ob7M3MqYFqUj+3HrrrQU5T0ePF1+n7jbjDAkMfZJfu+frWHyNRCuXc/wXf1yQ6xU59KycUQqnkr7Ac0LP8rV48WIw2lN2DU6IS8Yu8JxhKugiGZCmdlla0rm8DStYvQ+IeXVlwiV0U146Y/SC1cNW+iKhAE5Vf99GohE8rtJRV/pGIxcZNeZYHYOMx+pBYLS07+ORNu17jsiIbFRXMFfdSr2hC48JhCQgGakvtYEWxhhsodtio3TuWUjj/HYHG01O4jAbUDUNLYuyS0PHlLN8GjGDiGB2osWyLAI9hNGMBVa5F6vNjNFQzs4O/TnztjVRWTd3hOfRihmzWXncaaNfZMSzKdAV1Vc93TZjQYrJ93Q007T5H8iBDmaffinl6VL4Z8tQ+WKyj35chsQivSiJGBBDECZ2DE528vp2rrrqKr72ta9x9tlnc+211zJvnu7n2tjYyG233cYzzzyTUeKO0XjwwQe5+eab+f3vf4/P52PZsmX89a9/HdfNwul08vzzz3Pdddfxox/9CFVVOfXUU7n11lupqEi1Slx11VUYjUZuueUWnnjiCerq6rj11lv5+te/nnO/j3jSuPRoPXpa3kA0qVuQsnzRF8mcc889lyefzD+tcyI2mJ7XaBkWvykaQdMQikW4D3tGnRQm9Bfzv197k5M/O3LC2T+JkftiOfqJhYPseeS7COEuhGUXseDkkS4zmdT6KjKMUersAePX2Ruh9AmoSIgoJI1D3JwyUPpa1CSiLCAApWaozGFimauMGm28JGQVoyToiSLSYJDECRlro9Xhk2WFDX/+PUqwk/r5R3PCyR8daDNq2vccGB6b1RB7FcG7GwQBTTIh+w7QoPjptthHxGZNFHaDypzKvrE7rWzsg4cwdEzNXHAMzH00b4ViVGNB1A+AxSDhnnksptrFlM4aXKnMyliQj0EmQ0K+HqTtjyEB3raTC6O4JYbUmUvjXtv8/ibaN21ACHWw8Au34Ei32jgEt1FFtRlRVLDYJ1HdxUlI3opbZ2cnP/nJT3j66adT9hmNRr73ve/x1a9+NefzWywW1q9fz/r160c9ZrQi4NOnT+dPf/pTRtdZs2YNa9asybp/eSTknNoMe9FrPfokA8BtLYwFqcjoFEJpA6ietYSOs25GjoUpq5mRsq+itgFb4gNM5nBxVWWK8tbO/djag5QvOiHt/tFWE0wWB/GuvQiaQrJnpJtSIVcTjij6Xd52v4IfKx6bCVdgBwgioqEUX8QNWpgGxYdQvzrV5S2N0ie4ZiMlQ/g0B8kslD5NNKKrbRoGLTF4XBYTy0LJqH5eeeTnxNs/QCtp4Kwv3Tx+g0PEqEm7DBKz9z+OKEeJtgHoilshMy2Plsgl+OSNSMlehISfpBBGnX0ipUs/NXkSuShDxpSYeWxaypiSjPpfAUgrn6J6IhTJYGTmhf+d9v2XsbEgD4PM20/eiXrgHQT3NI75zPcAXS4PVzRLKqbhA4ySMGrR92yNacloEEnT9LmcyTlif6Q3iKn9LQC8HS3jKm51TgHK+hRtW/4reFOZvJc5fvCDH/C1r32Nf/3rX+zbpxeTbGho4MMf/jDl5eV5d7DIYcghsCAVGZ1LL700pWxFrjjdpTiPOintvtmz5oCvr85J1Ae24uR7qpGIBBGTKo17O1iUZv9oqwmiJKLZyrEnu0H1p7Qp5GrCkcZwlzeXewZhfxI0cFtENNEwusvbcKXPbqK+1A2Uongj+CPJjJU+f1Sm1GTFoMSIxcNjr/SNQqFkVD+W8H48yRaiiXHeORPAaMqb2VVBSWgXYuID6NiOXDqXe15uKbzSNuRcyXkfZ49wNxZjFFFTUAUJYd6Xmb/sw5MnkctQxW28OcQQCj2mxmJXSys2fxTRWUH1OEbLxsfXI8T9mGuX0PChi0cekObZLDfESUT8GOUk3ZGqUZ/NaPc+rP4m4kndMD6aMc1ZUs7ShnIkVQb7yBrIuRjT3t27H2F/AFGAeaIVy7D9rorpqJKIyShiiGRQhFuO930Qsvrdj0QK4p9WXl7OZz6Tvn5EkSOQYS/6UDjMNLkVVZDwyqU0C0yqLFZTjULFuI2Js3rwc297UXGbgphrFhKXDEyrS28pHasEyPKFc6C5G9S9eh2pYgmQvEjn8qb1NGIVkmiIoIZxa71p05FDmjinktm6pRzGj3NKM7F0Ci6IJlGTSdrGUvpGodAyaoZDRZPNRMsPbYKGTBn6rLy1t4uNHU9zRuJdxHgrtO1De2Ive5LliOqxrFx0Hpfl+WyMFpsVTyZpqjkTsfcAs6LbqfVYMUveEX3U2x76mECARCIOiooAiIIBKcN2w8eUqmp4g0FCvk5mzJxb0D52dbZj7Y0TE4xUj3NsoPkdTNEuvHGRhg+N3J/u2Qx0tCOFu3AgIDtqR302PWIM0SSh2j3A6MY0QRSRHJUQPADhVCUqV2OaHO3FCCiImIeHUgC102dQW9vnhi1lEGfYn8XaYC568IxDXorbv/71L5577jl+/OP0yQluuukmzjjjDE4//fR8LlPkcGP4i96oYUrGQYMqNUxL2EazpmX1oi+SOffddx/f/OY3D+5FnDWDn0PtUJVuTabI4cwxZ38FgPXr15N+3XWMEiC7ngVfn9Lmby6WAMmD0VzehK1/wtT8iu6qbLZC9ZK0tcuAkXFO3Y26q7rBhCgnaFB8WSl98aAZNaGgqRoei5p1cotCy6hqiwxuK0wbbxo9cRgkkTUn1rGl6W4qdj9HXO3EIqmgqXT7eymNtfApaxOlgorEDeST9Hu02CyH3cH5l/YlaHv8Koj0QGSwXu5EJnLpp7nLT6iv7pk7IDNzWmbtho+p1/9yJ9YPnkATjTRc/wSCWDh5EzN6kA1liLZKujrb2PHq35G9+5h/+heobUhVEo1yXyyYxTXiPGljELsbMSOgakkMAtQl9+C1uNM+mwtLNDA6oUGPWRuznq6tHLoaoW1bQYxpFXNX4jOaUeVk+u/WaAGLG2KBjOrp+Xt7MSZkRMlEsfjQ2OSluK1bt476+vpR97e2tvKjH/2oqLgdYQx/0VtsJST13CRIooBbSmIMdkyaLFZTjVWrVhXkPO9vfJjE/rcRrCUsu+A7qTtt5fhjMomETHjvbmbOLj7jU5XxxlPaAs9q10CBZ1WOj1lEtsjojFW7jJKZ8M//BFWGE66GeR8bUbtMVTUQNN7a509R+mj8hx5frOheD0L96qyUPlEwIctxJDRqk3sJWMqySm5RKBkF6IprvFf/nGZyPJkw7HiCFbHX8BkU2pOVVKk9oEK75MLprqBe7EL84O9QMTfvbMvjKl6eBl1x8+1L7eMEJXLpR00OukoaTJm7zA0fU1anfg+CmqTX142rrLIwHQRO++IP0DSNpKLR07oL545HAPC2rEhV3FSFY6pNKJoRZU5dyjlGM8jQ+A8sne8jJHx6sp3K+ZQe/YX0MYixvhpxFvfAeUc3pj0D3j1oAMFWtDyNaTMWr2bG4nHKYDmq9D6GOsY9346WTiwdIeJWG8XiWmOT14x527ZtKXXRhrNy5Ur++te/5nOJIocZaS1Ivc2oBoWEAqKg4VBb8FrKJ00Wq6lGNDrShz0XAgd2YjnwNnFzmpe4ZOCDkBVTtIto615mFuSKRSYjmYyn4SVAOiy1VNKGpkFrzIKX+mIJkBwYs3ZZMqrXLwOoPWZE7TJV1Xhsy348NhMfXliVqvQtPE9PChUP6a7q5fOzUvoM3buISn5kgxWlajGlyy/MKrlFoWTUwPeg9tW2Mo9MkjBpUGRo/AdCzIendj6xjk6S4S40DdxWlelldkRs0LXj0GRbLmmAA2/pqyFyfNLEFZXNWUGP6XbkZIJZw5JijcXwMTWtbgbCHitmg4gl0QUUTnEDEAQBk0GgonYGnaIBq0HDEBmWjKkvM68kCEj2QeVqTIPMwvMQO7bDU98GQYTFn9Lrww2PQTxhGgY5pp/QPKwAdhpjmjvZiZyQURGwJKJEDoExTXNUInfsINq9n/FMKlpfjJsmTY5xOJnJSyrE43ESicSY+yORSD6XKHIYMaoF6fV7ELvewyJouiDyTKf0+KsnTxarKcbu3YUpXmkmjlESSJhG+q8DqPZqiHZhjIxvTStyeCEnYux/51nMNjd7G7fBWWeN3WB4CZBQEFNCD5gPy7nV+ioydu2ybm8PhkgCSRSxGe0psUAGSeTYBg/PNXamKm39SIa0mXwzVfrE7kbcQ5Q+hil9MHZyi0LJKIBwr49IbxyDJGDQrExa1a0v2zKWEhBEEkiY++rhqcm+CbggHtRsy5GWdxC9uzE7Sghba4j0xoklFYzNO6mZtaSg18qVMped45dkH5M2fExV1DSAo08JiHYVomtpMRhNLFu0ECHQAsZhBdNTap0NxvKPaZCRDFB7FFQvBX8zBFr06wxbSTu2XGZZUsEoiYgWN8OjwoYb09oMNXgE3S12f8yC/xAY07b4LIgHgkCQBdEIFmv6uQRAwymXEvF/DJfRVPB+TDXyenMuWbKEDRs28I1vfGPEPk3TeOyxx1i0qBj7ciQwpgUp1gvbHtGtoqI+YUhrQSoqbwWhUAXhj6k2g+CG8tq0+xecdTkmg4StNMMghCKHDUFfN/7nbgNg6aI0mdCGM7yIrCLTnyneLilML5YAyZnR3Naa2jow9NXHXGIcmT77uNnlfOdjYk4Fq/NR+mD85BaFklEAXm8PPX59tcUaMzJpI6b7si2rkklP+5404BIE0DSUeGQwO+dBzLb87qbnMO16Ck0yMe0zv+RA3/cmtkwexS0XNjd5+fgnzkvdaK+AvrIV9KY3LuZST1KNBhF6DyDYSsFaCpIBwVOnK1j+ltSDE0N+wyFJ2DIqJl8yA9W3j2j7LmyqiiCKKTGI1fIBdrTrLsJWvzBy3A8zpoXCYcyiA0Uy0ZvQ8Djyq6e7/al7EEQJd91ipi1cnbYMgaWklv6lHW9HC7UzRj6dA7/BrEWQNn9xkeHkNUu++uqrefnll7nwwgvZtm0bsiwjyzJbt27lwgsv5NVXX+Xqq68uVF+LTGLGsiDFY2EUowPN6tFdWYIHQJGHCCE9C9KWFv+E9X8qsW7dusKcqD/LkzG9lcwzbR62qtl6EHKRKUUs0jvw+al/vTB+g+ElQCQDPVIF7cY6ZMuQrJQGk35csQRI3igRPYGDIlkwjGKlXjmjNCdjmK70LcjamNYv0688dfaYk+GCySggHvIPfLYMcUebdJgdaKKRnkAQfySJ227G6izB4SnH5nDij+g1u1Q5rtcvOwjZlpWIH4Ck0Ul5dT2aaMQgChiDzQW/1qGiPwX+mp8/jKyogzskI9j6CniHRibH6Dc23/X8bjY3eUfsH42d299g6+++zva7LqWjuVHf6OnL9RD1psi2nS0H2H4gwI72XjoTqc/oeM/m+/FStrUG2NnSht87mAmyPwYxFvINbLO60jxrQ41pZXbsdgftxul0iZU47HbdSCBKqca0LIhve4LElj/S+t6rA7/BPS/uTfkNqmYsxrD0UzhPuZqSNDGGuf4GRzp5rbh9/vOfZ/fu3axbt47HHnsMsS+zjKqqCILAf/7nf3LppZcWpKNFJjdjWZDe2tmMtTOA2ShS47YSS8QwtO6ivH7BpMhiNdW46667CnOi/owyo7hKFpm6lBmTuCodKKrGtz7z9fEbjCgiK+N212Bk/CKyRXJjyYfOIzxvGUk5eVDOP5481mJBAtv/RbBtJ9bF51AxU1+xySS5RcFkFDBrzgJixquJhwLYpo2eLG2ikUvnsjdZTkm0BY+7Qn8eBH0FokrTiHsj+MMJSunCMedExIOQbXmOS0WLWIm5qhANBhaceRkWuwehYl7Br5Ur+1/7M2zfAJKJms/dhTSO61x/Cnw4lXuGhV20qS4UXzOh5C4WnDjYJp96kvHeHjQNkoqKydE3zt31qJpGPKkit+/B2bAMgFgoiKJoJBUFwZKdE6+lYjZx3ZOWzuZGSspTM6aWT5tN8vjLSYT9lFTWjTzBQaynm4jHEFV9LU2yOjlqlDIEZbUzKKu9Iu05ijU9cyfvIIPvf//7fP7zn2fDhg3s2bMHgNmzZ3P++ecze/bsvDtY5PBhtJe10JfxKyQ4aOrWrcRS0/uU1y8AJj6L1VTj3HPP5cknn8z7PGoioi/JG21p3SBSjlUURGlkxZ1cXFGKTDxmNYrZrL8evvKNb3Lfn58Zu0HaAs+6wt88XoHnIjlhr56DvXrOhF2/N5ag6V93A6AYqgcUt0wolIwCEJ2V2JZ8nMlsXpIVlXtebkFUj+VT1iY9eyQ26ItMEgWB+hILruh+vLKD19RjOR2xMIV2h1BhjIHTDLW6+7t12fkFvkL+tHd1Y+jWY9KmZeC612/8feCB3wGfAAYVh30xB56gH8LbC1ZPssoUQ3GZkRUNp0df0fOZqmneH0ADhN07OKpPcbNXz6Z59nlo8V4WuMuy+RqoaphHqH4VlsrZVE0bmf6rpKKWkoox4tJGGNOSuK1GIH9jmlGJsHSaG0XVUBpqxy5DoMgjEiGl+w22PfyfCIKAffYJzD3unCy+qSOPgsiF2bNnc8MNNxTiVEWmIJ7lnyTSsx+ro5Tka/cgqkmUnr0T3a0pS6EmRG/vacOgJWlT/Tzy3u4RLzlNVXn9nmswhNtQZ53OqvPXprQfalHj1AzSUxeZPCQGXSXve/AP4x4+boFndYwCz0UOS1yecpImN8ZEgERXdslGCiWjDgeGysGVi86jVFD1lP9dOwZq6SEnEGM+Slwl7LIcz5/Cy9l9MJJ2Rf36v5bJ61KqKfpKjiYaMq69ZpBEXrr3hwPfc38K/Hk9/8KS3I2QBPXxr0HZrLzrSVYZY3rNQLMT+lYDPeU17JVMiEqCWPfg3GbWvCXMmpdb7KDN4WHpxXm4FKcxptU6JWK9PkxygO5wZc71dIVECEkUkEQBHB5gjDIEO5/Sk/KoSV2RTFOGQBJAOLAFNBW/vRgzPx7Ft2eRg86CVR8Z+NxRXoGnvAZzaZql/SIF4corr8zbFUlOJhDVJCpQ4ilhhWOkG4QgiohxP4ZkiEigLbV90Q3i8CYRHvj4teu/w+133TPqoaMVkdXMbmLBbkhGqJUkApbKYgmQKUbd7EU4vduwuINZtSuEjDocGC4HL/vQTL24dsXcgVp6Ab+XZDJB0l5LzUlXsHz+uSx/uaXwSbtUdUi9u1TFLRTXyyk4zBM/JVw53YEWdqOOEls9Gl9bexW333FnSgr8MrEXoawewWRHVRKFqSfZr/xaB2N3BVHEPv90TAYR96wV2Z/zIJDOmBYJetF8+3AASZMn93q6KdkyBxMjpStD4FG8JDQRFRG7pzztbyAnYpgkUFUBzVIsvz0eE/+UFjmiqFp4wkR3Ycpz8803530OTdOQl1yAFo9Q1rCENYvSu0E4Smso6T6AQdlVMFeUIhPPzv3tmL0RRMnAd//z+6MeN1YRWbx7UeNh0BTC5ipKP/rNYgmQAvLib28CyYhn7gksPf6jE9KH6oYFEHpfT/6QjGWcqKgQMqqfF574HeGeA5jLGzjj3M8V7LyFIH3SrtRaeq1//D5isgOvYRY1Sz6NATLOzpkNkZCPYCA6UDbBAySSMo/f/2PskQNULPoQq86cBN+fkkAQBKQsk17dfPPNI1LgNztnUu+xo9Hnso01/xT4Mb/+7zDld/6512V/rjx495+/RQl7sVbOYt6Jn0zZN5oxzWKwE9OSiGjUyi0ELBW5GdOGGPaGu1gO/w3aceBSvIBAc8KZ9jcwqAkW1fRVepuZGstXZCRFxa1IkSnG448/ztq1a8c/cAyMJjMrzlmTsi2dG8SiyGaI7YHYLnjimrRuEMXJ+eGH1+vFHE6QNJrZ9Je/pB1P4xWRFbob2fPYz7AF96J5ZlJeLAFSMBRZxtn5BgDxkpqJ60hJf+yNptecyjDJRSFkVD+m9jdx+z4gkpgHTALFYwhjpn3vK6uQmH48jubnqJe6QVVAlA5K0i6/t5vOoF4vzhw34wFMRgMzo+9hTPiIdlQU5Dp5o/Ql2xGzm54+/vjjrL3yitR6klEZra9kRiCaxGPPLwU+QEdHG+ZEAhHHuEWl97/2Z4RkGGvFTEoXfCir6wAE/T3s2vQP4p17mH78p6mbPViGI7TrFSy9zfT4lsEQxW0sY5rk3YvVZEREQyippfSEa3Mypu1oPoDQ3oskClRpltTaicPKEMSDXdhVDUGA3nAUj8M+8jfoK74NgLG44jYeRcWtyEEl6O2g+YUHkCwuqo/6KCW1swA9PiqRiGG2TOaQ8sOTg5UUKJ0bRLnajaCpIIioyWhhXFGKTDii0YJscqOaXcyelX48jVtEtmoxC0/8BIZ3HwFiEAtisLgOymrCkUYy2ovDbNCTAzg9E9eRkhmDn31NGStuhZRRFcYEgsWA6PIU7JyFZLzxffRRyyG2Sf9PYD+UNACFT9oVTqjsN83CqoaZ5RpMze6pnYPLuw2z1V+wa+WF0jeJl7IrxDx79uwR9SS1Hj0pB5qGy0xfJs/c60lqqsqB9nYETSFRJrFqnONb3/gr5vABolXHcHwOipscjyJu+T1WoGfvvBTFzSTr7oqCZVB9zMSYJr1+N/TsgpIZOdfTjYYCCEkFgGnDs2UO+w0OyBGkkB7vXGrWqEn3G5iHnMNQLC80HkXFrchBxdd1APmDZ5GB7prFeKpn8Np938AU2IMy+yOs+mSxzl+hsVoPnsVquBtEm2UaNcIBANriFrqoz98VpciEs/LT1wG6688LL6Sv45ZJEVlDxZCsh97dUHtMsQRIAbCoEeZU9rkozZjAYH5HJS0hgVg4iH/Lm6ycl5nLZiFl1By3prtrzTpM46bLhiix3j0DiluhmTtvIbPm3ElvLInNZBiyfTG8txOSXSAn9GQpE8hbezuxdgVJRkpZlkU7q9WaNgW+I96JW/WhJQxQuVzfmGOR83C4V88cCRjtJSn7VEVl0/N/Id69j9L6hSw9/kzEZJ9yZc6uFEA/JRW17DVYsWgxxNCQWnuaxvJKEVVxo8ybMbA5E2Mas06FUAdEeiAWwGBxZ21Ms5ZUEahcBokIFqs9deew30CRBn8LoxodPG7Ib6CJRkBDQBi/fEGRwihu8Xict956i87OTk488UTKy8sLcdoiU4B4eDBo3WJ39SW0CCIpcRI9eyawZ1OXTZs2ccopp+R1ju7WXXRvfwGD2c605Wdidfa9pIa5QYQjEVyyjKZBWAzjcVXk7YpSZHIx1ngaV/EqnTX4uUdX3KBYAiRvEumTAxxyBIFWKrAkfMhZZAouhIwCQNMGE27kODmecFzT9NUlJaEbN2afdtAuJYkCHtswxay/eDQaBFpSFckJIB6PIcoqMVnIqt2mTZs4ZcHZI1LglxolpLiKpiZo7gpSX+HKuZ6k3eFi9tcepzcYwNGXWr8fURIxvPN/WJK9hOUAHPdRlpSLyEkHibrarK7TjyCKLF1yFKaeHWAeUqA6GQFVRhQERLtnYHMmxjTKdGOaomkkOz7A0rAya2PaglVnwqoz0+8cVobAH9MoNVqQ1ATRWG/aMgR72rrpbQkgieDu1Zi81RgnB3n7Md12223U1NRw0kkn8alPfYqtW7cC0N3dTXl5Offff3/enSxy+DLPo7FsuptFtS6qK3X3DEftXMocJuYYuvQXb5GC8pWvfCXvc3Q07SC25RFCr/2W3qB/cMdQN4gyOzarlbisklBUrEJSF8iilOoGUeSwJq/xZHaiOapIKCrelvcL16kjnfhguQbM40XaHGTqVtNReRKxGR/OuEkhZBSgT2A1Vf98uCpuooTsbiAUl2ndvf3QX3/oCp+/efTjDhHywk/SsuArxBacn1W7r3zlK4Mp8P1d+MMJPDYjFaWlWE0SZoNIIhqkuSeMFvVB6cys60kKgoDbZmJ6dQUet2fE/qSrDqMk4E60gxzDKoHTYqCsNHcjlam8z/gVaNFrogHEhmRxHfb8r5xROqaro+yZSWN7L+/uD/Du1rcGthfMmJbmN3A43ViNEnYhjj+SHPEbyAk9DlFRQSrGuI1LXorbb3/7W6699lrOOuss7rvvPrQhk/Dy8nJOP/10/vCH8WsAFZnCxHsRBQGTJGK06gJm8aKjqCuxUWFKQsQ7zgmKZMt11+Wf3UqORwY+m61DJkTDXVEEkTj6Z6My2AaDST8uS1eUIpODWE+L/mJV5LzH0xu9Jbx3IMjuxq1FQ02BiIb8JGQVRdXQJnLFDTjuY5/nzC/dzGlnX5Rxm0LIKIBYyE84IROXFZKG7FZPJhPvRMrY1Rmio7mReCI+foNc6N4J7e9C8EDqdmcNvphGWyBK4453D861s+BDJ53KueddxKmnZpcp9brrrkNG5Fl1BV7VQb3YRX2JBavdpSsNZgOlUkKvJ6nYUOaeVXBvkJVHHcXiWjcLrUGIBQZ35GNU6I8jVWUItuqf40MUN0t2hhuD1YnfWI4GJDt35t6vUUj3G0Sw0BtLoioyHoM84jfwVNShLDgPefZHcJQUPfbGI69Re8stt3Deeefx0EMP0dPTM2L/sccey2233ZbPJYoc7vRbhgUJ+uuypAS07wV72SHv1lTmgQceyPsciyoMaDUuFFXD5Bzy0hnmBhGIJim1VyMLAn7ZRCyNG0SRwwtVltlx72UIAqhLLsh7PEnlc2H/axgTQQI97bjLJzAL4hTh/X1tiG365G2eYOVwS/FUCBkF0NndhbdDNw7ZekUyS40y+XDUzCe68ylETaG9eScNc3Ir2jwWm5/8DQ7vu6glM1n85TsHd4gSH8TcmHsDRFp3Ffy6h4r77v9t2hT4WEoAEUGOUEY73ZZpudeTlON6tktRSrvbUNrn5KfKegKQfvJZFe+bLyUVlXj7LhwlDezYt59kawCDJFCetJJtPlDLzOMg3EVVwzE5dal1+8tIkoi9bBrOikHHxtHKEBglK1pfGYKaxF6Cw8oQVDXMp6ohu9XPI5m8FLddu3ZxzTXXjLq/tLQ0rUJX5Aiif8XF7AChz2d9eCay6ZOjYOVU4dxzz+XJJ5/M6xxGJQ4GUVe4hwar97tB7H4FP1Y8dhPTS/WJuOqN4I8kQQvToPgQ6ldn7YpSZOKJRHSFQNMAkyPv8VSz+AT2G6yU1S/E5pkkKccPc5RoABHQBBGr7fBzESyEjAKIhwdXNSyOCXYZzYNpc5YQ2b8Ye818bBWeg3INJeInLqtEtTRqvqceobcZd+yA/uAL2cWXTTSyonLSZd9n8SmfSFtPEskAiohgclB6xjdo7zk6p3qSW//+G6x7nkK1ljH/igdHHuAZdDvt3rOF3u4wkijglE2UjDw6IzRXLdvbwshyksR7W1m18AwSvT5UVUNRNQw29/gnGcZRH78qx97oHHjmVxjjPmJ1J3HcZ/WajGOVITB69yCb7AgmO0L1QkqXfrpY0zMP8lLcPB4P3d3do+5/7733qK4uFtM7knlz5z7snUFUp5NF/RtNNkLGMmK+AwQ/2MaspRdMZBenHIWYEJHsK7BptKa8xGVENqormKtupd7Qhadktp7aFz3VMlpYd4Ow2CidexZSMTHJYYchGabWY0VRVdSy0rzHU830WdRMnzX+gUUypm7uMfQaFRRZRhAnfsITb3kb/963iMYTzPjIleMeXxAZBdRUVRFY+mGUaJDSisN3JddRUY/jwl8c1GvUWhKoqhFTGle0JSechTm4CEPZjIPah0zo/OetiFoSY92xuBedMe7x/QrD4lM+kTYFPt2NRHb+m+iWRwmqFiyORVy2ZG5O9SQjgS7UuExCkNMf4JoGCCQVhXDzVr0UAWCScl8TFyQjIWsNlt5m5J4m/TJVdXTPOAU1GsDhPvRJnqS++YHU51GTSRkCWzykG/DL54NkKNb0zIO8ZlVnn302v/nNb7jqqpHa+/bt27nnnnv48pe/nM8lihzmJCJBpKRKVEsNON0WLcPq200y0khxSldYrrvuOm699db8TpLUC7UOLYY5mhsElhIwmBDlBPVyDz0WR+6uKEUmHIsWw+Lsi2GsrCjMeCpSUKoXn0j14hMnuhsDvP3yPzDvex5FMtNwxuXjKpOFGlOO2gU4ahfkfZ4pj6ZRb5fBaodZI3P22WesBFYe+n6lYf/WjYhKnHjIyOoMFLf+FPjt777Mmi9ckzYFflh10vry44BMcM9WamYvzameZJkhhmAxEHaMcqzRwlteE2K4g6QQI+RehJAIMcuVn3LlmnsiWng+ddP1Om4zFq1mxqLVeZ0zVzQ5ztwyE4pmQJ6mG0syKkMwjP5MlgAt777Ev3v+RUNtFbOPP/9Q3MZhTV6K249+9CNWr17NkiVLOPfccxEEgQceeID777+fP//5z9TU1PC9732vUH0tchhinLaMqNmJsST1ZWEqnwVtm7AkfUR7/VgnsojsFGPt2rV5n2NrUxu2zhCKu5T5jO0GgXcv0UAXciRAQjBR8vEbaPcuK7pBHK6kpJp3FGQ8DdCfnOQwc8UqMjaWqtlo+55HUuJ0t7dQUTt2LbKCjqkpiKZpCIV8RhIhPe4KwJK9a92hRFD1VSpRMo5zpE5/CnzXCaOnwC+vmk6T0YVdCyHGOgFyqic515kEzQF1usKxuck7IvV+3F6DNdyBZnFz2pXpjROyorKlxZ/xdRd95IsZHZcN+3dupWvXGyjxCCvO/1rG7YREGKelT3Xoy5aZURmCNPT/Bs/s+V9Kd72Cb58TiorbuOSluNXW1vLmm29y44038sc//hFN0/j973+P0+nk4osv5ic/+UmxptsRzopz1qTdPmfFGSTnLKJs+jwEm+fQdmqK8+9//5s5c+aMf+AYhENB1LhMNGEY1w2C7kYOvP5Xktv/SkywEnMv47KlubmiFJkExFNrhP3730/nPZ66m96l88XfIvj2UnHBLZTXzsyzk0UmE/WzFyPssWE1GjAlW4GxFbdCyKipRkePjxdf+Bdy925WnnY+s+cWcCVxjPTxQ1FVjWAsObLW26FCVZhbYUPVNNTazJOWrZxRyv33P878eXPT7hdEkSUX/xdWTw1YPQPbs06BH/Xr/1rcbG7yctfzu0esMlXMORbVYaW8ambaeMGh71NOzaAW5kGidcvTmPf+C1E0Iicvx2DM8DdPhAc/D0k+lsl9bHv2/4i1vouhcgHHnHUpoP8GJUYFANVgyfwGjmDyDkCprKzk3nvv5d5776WrqwtVVamoqECcBH73RSYv7sp6qCyWWTwYlJTkGgY9iFQ6g5imIpU2ZOQG4T7Wgn/vv6k2GbD27sYgzc/JFaXIxNPe3YMhFNeD6g22goynSFIlcUBPNd7Z9F5RccuT1//+AIJkpKxhEbMXHD3R3aGkdg5YzYAGvn3QcMLYxxdgTAG89uI/CfX24iyvYfWqsa852THLIebsvBcA/94GKKDiFvR3o0WTGCUBo9FFurWsZ55+gsAHL+M0qpx55fqCXTsrlCQOc9+01JFdmYvxxpS1ZmGuvdKRE3rdQABrCcfUeVgxo3SEcXLOh0YvizHcCHpMnSenrux89QkkUcJdM5uy+tzGib12PvLef2ERFIIdeymdnmEisaE1JE3ZZY2O7HgOc2g/0WgIuHRg+/JaG5rmRHZVZXW+I5WCZg6oqChmDCtSZKKZNm1a3udYdcH1qRtOHdsNorx2FuXTqnWXnNBuIDdXlCITz/7OLgy+KABLTPaCjKeaGQvwihJWA5hDTXmf70hGU1VM2x9BUGV6IudMCsUNgxlctXqdKV/TuIcXYkwBaO89Sbn/A6Il8+AwV9zcFdMwWJ04hBhG5cD4DbJgf1s7iW59paRKsbA/jYtfSbSZisjbaIJAPB7DbB65+pGti1/WKENq2GXoKtlPocbUaMRCXpSEjFESkUzulBitEZ4likxk218wJEMYS6YjzDwFGTG950qG7Hz7RXxN7yAYLAgf/ANDMkTXjNMoq/9OTvcze8HRGPa6MEoiRFuAzBS3/Z1dqN4IBlHAqVnIKqdtxXwMkVaq5P1oShKh7zc2kQCDhNk+sTUpDxfyVtx8Ph8PP/wwe/bswefzpRThBr3S/H333ZfvZYochsTCAdq3/xuLzY2nfjEWV3rXh3g8itlsTbuvSPY8/fTTrFq1qqDnHPdFLQhQsQBa34CuHQObs3ZFKTLhqDHdVVKVTBiMpoKMJ6PRxLIlRyH69gDtBejlkUsyEUPSZFTAYJlEpQBKZvQpbnvHPbRQMsqq6unW8ypwPEkQRJElS46B9q2gtBb03NFoFFUwYdQS7Aoa+N2baVz86uZiaDVjMYkQaIXK2SnnOCQufsqQbI1Sdu6amYwpTdPo8fuJBrzUzZg95rHD6exsH6wZGDIyD0Yob4Iqs6ZsK9LOp1B2PAdKjLjRjn3eKWxUjuWtyHJWzKzIKXSg551/YGl/k4SpBKPcl9XRmnu8orWsDix2SEb1mnNzP5xRO5/PixJOAGDOMlvmMctXY5TfQEAAfzOU9f0G/cnQDMV5YCbkpbg9/fTTXHDBBYTDYVwuV9ql6oIG2BY5rOg8sA//xtsBCH7ku8xbfmrK/vdff5rgpocwRTtZePWjWKxFa0shuP7668c/6GBQMV9X3MLdEO4pFlY/TFl+7leJBC8mFtMnB4UaT2L5bPDt0Sf2qjJqEdsiY2NSIiyb7kHVNORZB3eVIRvaDTVEu8PEkkFqezpwl43u9lSoMXV0pQRuN9rsGQU534RTNltX3IIH9MmssTAxP/NP+DgdSz5MbyjM6mllvNszcpWoYfYiaOybOIdaUhS3Qrn4jUcgFCLgjSAIYAipZFPgIZMx9eKDP8TV/hoxVwN1X707q75Fg4Olr2zuwdwN/cqboMrUbL0dr7wJt+pDUmKoiAhAaNfLzFXfYU3tPpafuG5cpS1d0hNjxSyE9jdxaUEaKh2omkayvjalXVYrooIApbOh413w7s7sSwAEQDE6MMhh7FkmlTNVL+w7A9DVOKi4ybqHBwZzVuc7UskrEO3666+nurqad955B7/fz969e0f87dmzp1B9LXKYMbQ4qtnmYnOTF1lRB7YJgoQ50o6gqXTsaxz1PLKisrnvJVNkfL74xS/m1V6VZTobX8W/bxuJkC/jdkr5fHpjMu3BGHt3vJlXH4pMHAaTBVd5NZXT9ZdqvuNpgLK+ZBRKEgIthTnnkUhfjIkoCJjysLjny3B5HrHXEYgmicvjy/NPX/Gt/DugaQPfhWA5fItvp1DaryxpGa1cZorDbGB2hYOjZ1ZhMhn6XNj1+Kx7Xtyr/47OGhBE/Tvd8zx0bAdFHj051UEgHIniDSfoCSUIJLJrm4mcsjhLAA1zbzOJWDSr81fPX43p4+uRT/42pTWpyXcMksiasq2cIG8iEY/SlTCRFEwogoGQ6GIP9bgMCitjr2JoHLuGYX/Sk4HfpY/Fi45i6XQ3C6qdWE0SdrMBT8lgeFL/73TX87szny+VzUFDI9Gzj2Q8klGTJSd/kmO/8WeW3fB3zJYs69PZK8Di0T93D8qI91q62N0VorEnmd35jlDyWnHbtWsX69evZ+nSpYXqT5EpRJ1NRq50IKsqO2JG7nkt1T2jasYCfBYjVpOINbYfWD7iHJMlA9PhxCOPPJJX+1AowIHHf6D/Z8WXOPqMz2TUTvPMYFdPHEFNEtv9NjOP/Whe/SgyOch3PA1QOhtV04glFaIt71NWMqMw5z3SGJocYIJcBNNl1Kuqn89Ox2KE0hnMcadfbeuX57VnXMrmJm9+8jwRAvpCM6aAqyQApbOIyyrRhEzv7nepq8wzocYojOri1/0BhLugeyfsfRG1ZEbeLn7ZoBlt7Ck5EUFJsDjLRBWZyKnaOcswd23EZpaQ/HugemR9sdFwO524Fy9Lv1ORkXY+RbkUYZ+zHjnQhlXVEAWBpKLicZnwlMzW6542/kPPxiyln36PlvTEUjl7ZBmVvgyhua6I7pdqCRwIklQ03Lu3M3NR5rX8xqvVmL6RABXzSDa9Ru++bZScoCKIItFIiIQsE08WvTAyIS/Fbe7cufT29o5/YJEjEosahb4MUSvm1bHF35MijEoqplFSW6FnaoqNDMY+VO4ZU41zzz2XJ58c26o3FonIYDp4gzlzi5rBZCbunonF9wGmwL6cr19kcpHveOpHc9XyTlsMQYkTf38rZcs+VoDeHYEMrbNnzi6rW6FIN7m0u0o4c+0vRm0zVJ5vf+EJjvnCD/PqgxoNIvTXO5sqiputlHd7QEpEiOzcRt3xFxbmvBEvGG0prpfpXPxKk92oioKiJDDJiaxd/PJl2vR6PnV5brV/M5FT0+ccBe/2ueP17MxKcRuT7kbwNSFYS6h32ulIWJEiupJlN2h4Sm2IggCWEvDu1Y9PU5QaRirV0Ke8WUvAZIfedr0mn2gAkz2vFVFn7Xy6Fd344WvZkZXilivbEzUkDwSBIFp3G2WV05A9s1ASYSyebJxjj1zyLsC9du1aPvvZzzJjxowCdanIlGHAMixgsLhY8yHdOpQijEpnQvs2PTaq+XV9IlI+P+8MTEcy+U6yHVKShjIbqqohVGQXpzb7w2uwWC04q7IL/C4yeXj7zksRVBlxzuksPesrBVHaAARRIupswOb/QA+GL5IT2/a0Ih4IIIkC07EyEarbeBn16G7U6wGOIs/v/sIP85bnLR1d+Pfr34MjJDEj35uaDAgCsmcmUuc7SP7CuUo2/v5aLAkf2syTmfHxbw5s73fx8/a5+LWKlbhVvUB1W9xGgHrqDV00xF5FaHxSr905SclITtlKdXe9cBd0f1C4i8dDoCYHYrSSxsGnMmoqwdP/H4MJlERqrcw0jLoi2rGdpP8AsqIgiiLi09/jefH4nFdE3WXVaNOOxeSuoWLuKKuJw0j2dmMwmhBMDshh1c1ZtwjvG/rnjt1bKaucxuqvjG7wKTKSvBS3Z599loqKChYuXMhHPvIR6urqkKTUpU5BEPjlL3+ZVyeLHKYk+hQ3kx1EEQOMEEaXh7oR27fqgdhdjSCZDrl7xlTjxhtv5Mc//nHO7S1aDEt/AVZ3djE0FbMyE/5FJimaBuEuNFUhGtGTk+Q7noZSsuoikokkM2YuKcj5jkTiET8GRSOpaFjsExfjNlZGPXxN+kRWNKaV59+7+T/zHlPxsB8NkFUNyXr4xrgNT0QxY8lxGLucuGrnpy3g3E+miSg0VSUc9BJVkyTjhlQFd5iLX6TXj0PVEASIhUN4XCUZu/hNNBnLqfJ5uuLW1Tjm9zuc9x6+ESkewFh3LLPO+HLqTrNDH+tyjGZvBH8MJOdsRC1JV8JM0huhvtSGKCf0MgcZrJSnTXqSaEeWZVRENEUh3rSZudr7ea2IHvP57J7Dtx78NtbwfhLVx7Dikp9kfb3aGQvxzf8Y7rpFVM87+Ct8U5G8nsDbb7994PNf//rXtMcUFbcjl8Z9B7B6IwhOF3V924YLo0BsI+6kH1kwICgaEofePWOqcfHFF+d3Ajk2+NmUZfBxkcMaNRnHYxFRVIGEW88SnM94Gj4pXXjMhzJqd9DrRR3GlJZWEK2cgyYnMRizS5leaEZMLpOvUap6UQQDgr0cSdLSyvO8ZRRQYjNhrKqHeC9u9+E5TtLGCq78FPCpMdtlE/stJ2M4DCqyKiI4hmX+Hubi16wqhMIlJAULdruD6Vm4+BUC1deC0PkugmSC+uOzev9kOqb89pmE/f8iEu/Fc6CJimkzM2oX7tiDMe7DZ6pm1vCd5fNRPQ2Edr+CHyseu4maUt2oEvdG8EeSoIVpUHwI9auhPLOaacNXRNsMtXhkPawkoWo0C/XUS4d2RVRMhlE1kA25ZQE3mMwcdf61he3UEUZeipuqquMfVOSIxefrIRpOEDMYBxQ3SBVGsaSCppiQRBFUEZ/qwo/1sHHPmIxs27Ytv4RBySHZpYy5KW6aquLtOkBZ1fTc+1HkkCMmw8wo63sh1+vxBrmOp3ST0kwoJiQam1nHnw/Hnz/R3RhgqDxPxiIElASSKKOZwa+608rzvGUUULHgBCoWHN5Ft0dLRDEW2cZ+GxNB5lX1xQDOSc2GONzFTxMNeA3VALiFIQWwM3Txy5ft295AefUuRAHqvvRbSioyf/9kOqbCrjl09eqFvuN7tmakuGmqil0NIQsg2UaWvZIR2aiuYK66lXpDF56S2brCC9SX2kALYwy20G2xUTr3LKRMVy2HrYj2hsOYJQeKZMGLC48986Qn/aQrNZAJ/ca0OoeKajITKy8fv1EGJKIhgq2NmCw2bOV1GCwTE7d7ODE517yLTAk0s4ukyYNmHSbohgoj10yMvu2gakR7g/gla07CqEjhaOnsRvJHkUSBEsFMtjb9bc8/SvzNhxCVOM6vP4bJXKzNctgwNPGFKb+6iuNOShV5xHNdTEh0GJIiz2dg8G0HVSUa6sVvcKSX50WA8WMFta4dCIlwfrHfscGyPFiGudYOc/ELRJO4rbrCFogmac7BxS8f1KSuUKkaSMaD896orp9Lp2TGagCDkllyPSHRy6JqOxoa6vxURa9fZr0VWc6a2n26gaK7UV+lNJgQ5QQNio9ui42XDatp717KZYqameI0bEV0HwLtUf17cVuN+m+TxYroaMa091/7B6HW97BUzGTpySNXe/vvccveTn5GEo/HCrXZZf0cjfaWXXg33AiA/aM3MfeYkwty3qlMcTZc5KBx/CXr0u9IEUYO9ifqCckCSdGckzAqkkq+luzOHh9Sn0WyNAdXSaPVgSLr8VGte7Yzc+HIMg9FJimJ8ODnPsUt1/E02qS0+eU/EtvxDFKil/mfuKGYkOhwZ9jk0hu2I8ohTGpsVHleLCE0SLpYwTMif8O04y844h2UlVeOGiuY0fMxluKWxsWvvlSX+Xu7w3jDCdC0rF38cqXKIYHLgoqGxZxd8fFMx5RkMLDsK3cguap1ZTQTon4ABAQk26AHQIqhaWYFy09cp68qN/5DH+uKrvAK9aspnXsW7d1L2dwcRHtxb2a/37AV0VHJcEV0NGNacPMfMEfaCfmXwDDFbeg9njjdjKuz7zsz5a7Ea6rCliduR+nYgWKw0v9LZ5PF+kgmK8VNFEVEUSQSiWAymRBFUU/FOwaCICDLcl6dLDLFGCaMFLObhJqm8OIhcs+Yajz88MN5TYw0VQFBREPAaMre6lk7+2h8m4zYzQassb2kq89XZHISDgUQEjKSKGAwOpDIbzylnZTu20hN+/OYiKP+7RuIBksxIVEW7Ni6CclooqS8lvKKyonuzkh3O6MNQQ5h0uJI2hC5PkSeP/zwX/JW3rbv2EE0qVJSWsbsaYWx/k8Uw2MFS8LP4Ez2oAgGZK0aUck99jsW8mJQVCRJQOgvftzHaC5+ba37cMT9WDQjBIXsXfxypNomgLtvGp+l4jaWnBruHiiV1KU9bjgDsbZm/+DGPuV31DT8Sz6tryoPy6wqSQYuU1S0fjdwMnCNLfCK6GjGNK1sDkKkjere7dD8ml5eI40x7ZJlBsSn+ub8eZTgEEQJuXkzpmgXLqNEZZkNRdUwlUxcsqXDiayewu9973sIgoDBYEj5/8EiHo/zve99j9///vf4fD6WLVvGj370Iz7ykY+M27a1tZXrrruOf/7zn6iqymmnncatt97KrFkjwkq57777+PnPf87evXupq6vjmmuu4eqrr0455rHHHuOPf/wjmzdvpr29nbq6Oj7+8Y9z88034/F4CnXLRwaTzD1jqpFvtrYVH78czllDss9tJVtc5dW46hsg3A3B3Xn1pcihZe+BDuQO3VAyXTZSTv7jafik1BN9FbvWiyoa9TjpPCalRyLhZ/4fkhzBO/PDlF/0zfEbHGyGyfOoYqWh7/eTw36aReMIeV6ILKW9L9yGxb+bztIFzF5z+CdAGxorKCsaUcGK2SihSib2x0w5x36/u7sFw4EgggCLTc6BSd9YLn4O2Yuk9CKhErA3ZO/ilytKn6IvSCBmV4x5tDFViFhb25w2FvXXDOwL/djS4h/dO0AypPUSGq44rZhRMnYM7xgros05Jj1JZ0y71BPDcmAfQiwKf70OjLa0xrRQ81bkUByDKGASLGSzPjZceVbL5mHt8OK0GCjpz2JtHznXKyaqGklWitsPfvCDMf9faL74xS/y6KOPcu211zJ37lx+97vfcfbZZ7Nx40ZOOumkUduFQiFOO+00AoEAN954I0ajkVtvvZVTTjmFt99+m7KywdpUd999N1deeSWf/vSn+cY3vsGLL77INddcQyQS4dvf/vbAcZdffjm1tbV8/vOfp76+nm3btnH77bfz97//nbfeegur1XpQv4vDDSUZJ+k7gNnhRjC7UmNZRhFGmqrRLMfwR8gpA1MRnYIUTBYEjKbMLZ4jAp4rFkL4xXFTLheF8uQiGe2l/5eyOfQU64UYTykJLBQVWbJjNRvAYGJfwllMSJQhqqIgKVEAJMskKTo9XJ7bXFiTFlCTlChh9kU8I+R5IcaU0B+PaT58SwGkMCRWsMU1E2vwfTQN/IEAfsWTc+y3EvFhAGTJOpCFdDwXP5PZiqBEEM0uSld/lvbkx7Jz8cv5O0jo/2bqwjiE0cbUaO6BSVmhdf8+kOPMmLMwpc3w1bRY8F227g9gkATmGJ2Y6UuadCpZJ/roV5zGVdo4eElPhhvToomXsCT8+veuqaijGNPae3qI+XT5UyGbMlbc0inPq1cdj7B5+7COpXr4FBNVpWfSxrht2rSJP/zhD6xfv54bbrgBgEsuuYQlS5bwrW99i1deeWXUtnfeeSc7d+5k06ZNrFyp14n42Mc+xpIlS7jlllsGLDPRaJSbbrqJc845h0cffRSANWvWoKoq69at4/LLL6ekRLeuPProo5x66qkp1zn22GO59NJL+b//+z8uu+yyQn8FhzXtLXvo+tO1CALYTv8mc1d8eGBfOmHU29OGFmilBBBc83PLwFQEyL8Ad7aktWhWLICmF/VkF8FWcI/MLlkUypOP+mWn0FNSTTIaxGrTFYOCjKdhCSxigR2QUIj5/fixFBMSZYiQDDG/yoGiash11RPdHSCNPC+dTbzHidzbiaiGcLuEEfK8EGNqeZUBJeokOXNaAe5iEjAkVnC600U4aiGZjKHGQrhdFTnHfped8EUOzPoogqxnC87Exc/c2w4v/kJPx+8o57Jlc7Nz8cuRDl8vxnACLBayfRuMNqZGcw987Z6v4wx8gOCuAdNVY8bavvX4E0hATDNisgwmbcr1nWWQxPGVtoOZ9IRUY1o0KWPGhs0ggSDRnEyfDTYZCQ60z6aGZFrluSKNQd44uABSTFQ1OgV5M/773/9mz549+Hw+NE1L2ScIAtddd13W53z00UeRJInLL798YJvFYuErX/kKN954Iy0tLdTVpfdTfvTRR1m5cuWA0gawYMECzjjjDB555JEBxW3jxo309PRw1VVXpbRfu3Yt//d//8ff/vY3Pv/5zwOMUNoAPvnJT3LppZfy/vvvZ31/U51YyAfoiy0G2+ADPpowMikiihpDRGNabBd+S+mhc8+YYlx00UU88sgjuZ8gGQXRmPHEOZ1QFsrnEQgniCRkwts2M/+kVMWtKJQnJ2XV9ZRV16dsy3s8wYgEFoGonWQ8AGoIt7uYkChThEQYq7HPhcwz8YaOUSeXmhGUBEY0amM7CVrKU+T5Zy/+TH5jSlUxyhGMRgnLYVrDbQTDYgUTkg1DMoZFDRPThpReyjL2e870SuZMH4yFzMjFr2ox7NkI3Tuh9U0Mx3w+Oxe/HNnb6cPijZAwW1iVZdux5FQ698DTBR8ViV0Yu95D+/seBMk0aqytZ+FpdNmqQUkc1PCgfg560hMYUWogHNyNkIgTl/34RWdaY9qC4z5GaP4KYuEA7tLM42vTKs8nzcBgtBIM+IlHgkiolHTvQqhcWExUNQ55KW5vv/02//Ef/8GuXbtGKGz95Kq4bdmyhXnz5uFypbpBrFq1auDa6RQ3VVXZunUrX/7yl0fsW7VqFf/85z/p7e3F6XSyZcsWAFasWJFy3LHHHosoimzZsmVAcUtHe3s7AOUFqmcxlSg1JnB6LMiqhq1Ed00dSxiZunchR7oRRQnRU0vp8VfnJoyK8Lvf/S6v9pvvvRpbeD+JmpUc87lRMoMOIZ1QvuzEBvYGQUrGYcezUF9bzB54mJLveAJGTkoNDizxAKIqIyZD0O90U0xINDbxIenL80gOUAjGkufmnj0kIkEUkxNql1C69LwUeX7v/ffnd/FECOibc0zw91AwhsUKJhQb00QfigbxkJdmUSxI7HfGLn61y3XFLXgALdiGwVWTsYtfrkREJ1FDBZhG1kobj/Hk1HD3wLLo27iEMEKfW+Zo7oEA8xYdzbxFR2fdp1w4JElPYIQxrS1kJZqIoBHGXSKmNaYZqxZTUlUHZJbcZSjplOfL5SRCxzZschRBAOGv1xYTVWVAXorbZZddRmdnJ3fddRerV6/G7S5cRpi2tjZqampGbO/fduDAgbTtvF4v8Xh83Lbz58+nra0NSZKorEy1HJhMJsrKyka9Rj8//elPkSSJCy64YNz76ezspKurK2Xbrl27xm13uFIixcHZFyPlKRlXGEndjUiv3gG+Jt2tbumnuUzVDol7xlTjlltu4eabb865vRYPk1Q04lmIh7QWTRNURHZh6twN/9iaX0rrIhNGvuMJGDEpDSatTNcATUMNe2n2OooJiTIhpc7exCks48lzobsR15DJJcMml88++yx/+MFluT/7Kd/DFBkrI2K/PSQDbQiaglPtpTPiLljsdyaKl1yznO6XHiAYTRJ67VmWf/TzGbn45cPqT36NaFJBHWUhYCwykVOpsbYaccGK1WgA0UBz3D4pYm0PSdITGGFMSxodWBI9CGgIsQDQJ18KaEwbrjx7w2/gTAZRBAOqJo6pPBcZJK9vZPv27dx4442sWbOGZcuW0dDQkPYvF6LRKOY0hXstFsvA/tHaARm1jUajmEzpywtbLJZRrwHw0EMPcd9993H99dczd+7cMe5E584772TJkiUpf+effz4AL730Ei+88ALr16/H6/Vy6aWXAnqwLcB1113Hrl27uP/++9mwYQObNm1i3bp1RCIRLrroopRjb7zxRrZt28ZDDz3EQw89xLZt27jxxhtTjrnooouIRCKsW7eOTZs2sWHDBu6//3527do1sDraf+yll16K1+tl/fr1vPDCCzz11FPccccdtLa2cuWVV6Yce+WVV9La2sodd9zB25teoqenh127d+MNJ7ngim/yRpOX7S88wZoPzeSbN1w/eE9PPMmmfWEe2hpDMdh48+XnoHsnnzz/PNZ8aCY9jZt4blsTP7v/TxN6T0899dRh8TtVVFTkdU81doFQTxtlHk9W9/S9m/+T40vCmHx7sL/0Y5y9uyEZx146jfc/2IOqJOh4+5/M2XUfZ+y9haNNHTz5xF+O2N9pMt7TLVedxdsPf5/vX3n+wD1Nnz4973s677Jvo3oa6Gzdh7c3ipKIkRTMCGgYlTC+cJzX3t2JFvXx/NZ9UD6/+Duluadb77ibvd1hXnp7B2HBMmH3tKXFz51/eooVM0rZ8Zc7aNq7Z/Ce3nyLdb95jEj5Ui66+ocgGTj33HMxSCL7nr6P6ZYEHaqDn93/p5x/p69ccSUfdPTyyrZd7OqJTbrfKZd7+vj5n+JZdQX7QyLT6UD2tRMXbaiqilUJ4jAoqF076VZs/PQv74JkGPeekokYT1+/nJbff5VbbvhCVvf03v4A73UpeINhvO+9cEieJ7vZwH/e8HWSwZ6sfyez2Tz+7/TOFlr+dRfWWBcBUy3hpEo0obC3qQl/JEnY14Wzagb+9r10v/K/PP7Yo4dcRjz0y3V8fI4Z4+4XePKJv2Q89h754x84viSM0PgvVs4oHfd3au7w0tRyAFWO8co7jfgVKyHFSNhSTUdEY0dLNx2dnXS2tZKQNf7rZ7cW5Hl68om/cHpgA0t8zyIr0KuaSAommsJmmpNutoZLsRFndtvfeO3+70yYLH/ppZeYrAjaaD6OGbBs2TIuueSSgeQhhWTJkiVUVVXx7LPPpmx/7733WLx4MXfddRdXXHHFiHbd3d1UVFTwX//1XyOsL3feeSdr165lx44dzJ8/n6997WvcddddaevMVVZWcsYZZ/Dwww+P2Pfiiy/y0Y9+lFNOOYW//vWvA+URxmK0Fbfzzz+fd999l8WLp1g8xxu/hQ+e0oNNL/wdkCbz4HCiPtjwVUBDW/BxhOVfAIqZB7Nlw4YNfPKTn8ytsabBHz4HmgKLzoejL876FMo7f8L7zM9JxKMknXXUl+nB3M3eCP5wgnqxixKXE+GkrxezB04yNt32OUzRbmK1qznuC/8F5Dme+pAVlY2P3sXc3ffjMih4amcTjYTQNLDanbR4IxiDLZgsVko/+k2kZeN7MRyJvPX0/yK+/XsA5q19BJtj4uoejSvPhyLHByz7sqLyy/97gusvOT/naze+8RzRZ38KQPmnb2H6nCU5n2syMBAruLeLNcIGVsZeRYj5kEUTJKMYTFY0OU63YtdjBZet5bJT5o773fd0ttLyWz1sRFy9hmWnZvdcbX7057ian8PudDHtSw8gjFcIegLJSE51bIcnrgElieqsJrD/fcR4EFkwEXTPp6Gszz0w2Kav/H/iNhKe2ex78qcY7SW4F55KyYxlh+aGDjaKjPrY5YR2v8Ie6tOWGvBYDTQozfoK7/l38eZD30MK7kerWswxF3x7nAuMfl02XIHWsol9wjTk3k5MNieqwY4/puCxGakvsSB2N0Kdft2JSFS1fft2lixZMinn53l9Gz/4wQ+4/vrrufjii5k2rbCZnWpqamhtbR2xva2tDYDa2tq07UpLSzGbzQPHjdW2pqYGRVHo7OxMcZdMJBL09PSkvcY777zDJz7xCZYsWcKjjz6akdIGuiI43CVzKrO/oxNLKI7o8AxkhxpX8bKW4LU2EGp9j+5XnuGYoz+HIIoH3T1jquHz+XJvrCR0pQ1SMjxl3j414NkfldF69GxmgWiymD1wkmPVYrofxpC4obzGE6MnsLD3ZUcj1JFXdrQjCasoI5oMyKo2kPVzoshEJgd2vor3jUeJefcz74r/QzIYMEgiJbI3r2tbtQgGiwFF1bC7so+HmkyMFSto8O4Fsx1EI0LpzKwTUcR7fQjo0YBmR/bv0OWnX4gUPQ2qlurP6sEm0ApoYLIP1EvLlIzk1DD3wJhgxawGEIiDHCNdrG3Q10l4t57FPGSvnzKKWy6lBuRgB1Kog5htZChSxqTE1rnYJxrwRpMgK7itxURVmZDXjOlTn/oUsViM+fPnc8YZZzB9+nQkKbVooiAI/PKX2RfHPProo9m4cSPBYDAlQcnrr78+sD8doiiydOlS3njjjRH7Xn/9dWbNmoXT6Uw5xxtvvMHZZ589cNwbb7yBqqojrrF7927OOussKisr+fvf/47DMUV86w8CLe2dWH1RYgocl0W7ffYlCOG3EemgrXkntTOKNdyy5eSTT869cTIy+NmYTXnNPoYFPGs9EYKROAY1htvhLgrlyYymsbTCCHjQ5g8Gn+czng5JdrQjiIUf+SKccQkkwyBO/u+mpb0TufldAJob32Tm4tVAnjIKqF9xDhx1mj4Rtx++ycEOdiKKWkucmuluZFVDq0tv7B4LqbQByC3cJRe2P/J9zOE2ktNWsvDCH2TVNqMxNSzWtlex0b/koIa6aTZaRsTahn3dg81dZenPe5iRSamBermHHosjxZhWZkyA2YDozGOlf5jyPCrFRFWjkpfkf+GFF/jqV79KJBLhySef5Ne//jW33377iL9cuOCCC1AUhd/85jcD2+LxOL/97W9ZvXr1QEbJ5uZmduzYMaLt5s2bU5S3xsZGnnvuOS688MKBbaeffjqlpaX8+te/Tmn/61//GpvNxjnnnDOwrb29nY9+9KOIosjTTz9NRUVFTvd1pNBfHFXLMoC+btkpiAKIJQ2IyfDB6NqU54477si5bTTSiz+apDcmEyUHC+swoSxFupkea6Q6sa/PotmHwaQfVxTKk4dEmP5MfcKQFbdcx1PaSanRpE9Kz78LPnEbfGw9fPx/iKxcS2/5MVx2ytyB0hL3vLgXWVHHv9CRhigeNpkUZxz1IRAEzAYR6cCbA9vzkVEACIK+KuOsAlEa//hJSkaJKOpXQ9ViWnuT7O3wDSngrD8nW1r8o18gFkAQBIySiMk++b1WwpEoobhMIJ5924zGVH8CGH8X/nACp8OBYHZgNJmxWMz4I0mae8JoUR+UzoTy+dTbEiypdTG/2kldTfbK72RjqFxePrOC5Z9bp4ct1K0GyUgiEqTX24Y/HMd8/OW0L1vL5uYg97y4l1lugTmVDpblUztxmPIciCZxW424rUYC0STN3oienEZO6GWJiomqRpDXitvVV1+Ny+Xi0UcfZfXq1SNS9+fD6tWrufDCC/nud79LZ2cnc+bM4YEHHqCpqYn77rtv4LhLLrmEF154IaUcwVVXXcU999zDOeecww033IDRaOQXv/gFVVVVXH/99QPHWa1W1q1bx9q1a7nwwgs588wzefHFF/nf//1f/vu//5vS0kFBd9ZZZ7Fnzx6+9a1v8dJLL6UELlZVVfGRj3ykYPc+FTj2K7cR6fWjqtlNvMqr63Fd8XtM7iPHrbTQ3HrrrTm37fYF6OnWFWZbSGBeticYJpRDmoV+sauGu2n2jrRoFpkkJIYYSkyDRWZzHU+ZTEo1Rea9e76CHGwnNv0kVn/25kNSL6rIocHhKmXukpXY/I0I4e16DK0g5CWjphKZpuZ/7I/349r/b2zuMmZedssQ5W2c5yMWGPxszm1+pmkarf4oO3buYl6Nh/q6+vEb5YjHDKJmwGDP3tsjkzGVzj1Q8MxHEI3YgWTPSPdAIRbAIIkYJMB1eMuiTFZ4fbu34HvhbmJGK1rYzGVn6MXXt+ztpDnk1d/f+by3R2RPHRlbV6jsqVOVvBS3Xbt28ZOf/OSgKS0PPvggN998M7///e/x+XwsW7aMv/71r+MuiTudTp5//nmuu+46fvSjH6GqKqeeeiq33nrriJWyq666CqPRyC233MITTzxBXV0dt956K1//+tdTjnvnnXcA+NnPfjbieqecckpRcRuG0WTGXVaVU9ui0pYf5557Lk8++WRObRPRwcm70ZKDq+RwoexwYJKcmNUYJjXM7kiCZk0rCuVJiBbvBTQEhJQU67mOp0wmpYJkIGiuwaq1Y2h7EzkRx2AyH/R6UYcr/kAAs8WOxSQdkkLAhcA++wR48wOIdINvL5TOyktGAbT7owiigNNiwGY6vGNkMxnjdUIXRrkNzdtBKOjD4SrJLPa7X3EzmMFoybhPQxPPhKMxPrj/CsrlTtrmfZz6uqtHbZdvIrF55WZIOKAue4+m8cZUJu6BaWNto/2xcwKYJy4ZUCHIxJhWWbGQ/W8+TYXgxxl+B4OkF19/MBnA/1YSjzWJJ49SJLnE1hVJJa9vZPHixQQCgfEPzBGLxcL69etZv379qMc8//zzabdPnz6dP/3pTxldZ82aNaxZs2bMY/JIvlmkyCElnwnRtDlL6bnwf0hEe6mqz3q9Lb1QtlSDfx8GSaNSjKEG24tCeRKy50AnoZYAkijgiUhM79uez3jKZAJXtvhUrJHteKwSYsc2qFtRTEg0Cjvv+ND46QAAZD9JREFUvxxjIkB4xhmc+B/fnOjuZMb0lfDm7/TPLZuhdFZeYwqg6Q/XI/QeIFx+FKd/6Yf593GSM/2oMxC9r+CxGTF3bQHX6Rm127xjL/b2IDiqWJThtTY3ebnr+d0Dk3uHzYrd7oBAJ5aOLaO2G7qaw6mZPfsjUBL6v31FsbMhE6Utl1jby80+JACL+7CIKx2LjIxposjyD52N8N7jEG2G3nYMzmr+Y1kJod0WbCYDstGWk/KQs/JcjHVOIa9v4+c//zl33303mzZtKlR/ikwFNE3/y4LNTd6UeJZYLMr7bzzLG3+7b4xWuiDY3JRfhrKpRn8NlVywWO1Mm7WQmYtXZZ1qvF8oPxJZTmftGZS4nHpKXzkOiowgx6hONmGyWHnZsJp7upcWY5gmEYloEA2QVQ3JPOgqmc94yoR5x5xKXbkHp8WA2PzKQb3W4Y4k63GIJuMhyPCXByny3F4OpbOIyyoHtv8bGH1MZSrPxUQvZjWKVToy5EfN3OVUVVRiNkiw79WM28kRPwlZJahl7j1xTJ1nRJzpzKNOZmGNk6NcYejtGHmdYS54x9R5Mr7eAJoGSlL/LGU/vscaU+PF2qpn/pS9i6/ihdhs3u+1pcTa/vX19/igo5cPgodvLOVQVs4oHVcREmacNPiffS8D0OXtoS0Q4722IPt6s1cdxoutS1GeP/rNlNi64jwhlbzM3bfccgtOp5Pjjz+eRYsWUV9fnzar5F/+8pe8Olnk8KKz5QO6/nwDitGB59SrqV9ywpjHD7fwGSSRbX//Dcadf8cgCAROPB+3Z2Q2p4JY+KYgExE/Mq5F02SFRBjNYMN+0pW0R04oZg+cZLgrG2ib/3HUWBBnyaCr0kEfT0YLTFsOza9B6xt6UPqhSD1+mKElYzR4DCiqRLJq8ibHSifPt4vzSLa9BQQxHtiXdkxlI8/nl4BitRGfVn3wbmQyIYp6kpKdz0DHuxALgmX8mDV50QXs72zB6crcCNcfPwcMZq5cchyGvY+DpsJ7j0PN0QOZLmXE9HFTWaLKCRJJpc9tTso6NdZociqjBDCKQveGi3EnAvSG9mM48eyB7yDxYg9BKUnSlUPowOGKpw489eBvhqaXYfGniIWDA7stORp1D1b21CONvBS3rVu3IggC9fX1hEIh3nvvvRHHHC5++EUKR7jXTzKRgISXpDa+lWqohQ/0B7Ry0Un4dv4dEQ1f4yu4V5+b0qYgFr4pyn333cc3v3no3KgyEcqJA+/S9fxddCeMJH0Cl310blEoTzJqZy6kdubCEdsP1nhKKeDccKKuuMlxtANvIdSPXkQk3ziawxUhEabM3pdCexLXBE0nz8sXnETblj+gCAb27Xmfja9uSxlTWclzVcEtJcFugorJ+z0UgpRnpP4E2PkMmqYQ3/saloUfHbVd/zPyoRM/lNN1hytvgurk8lgQ0bcH2reBo1JPQlUyg43KsbwVWc6KmRV5yfFoLMrO9l4AtOoox2RZLm00OZWJe6AoSTDzZMQPnmRashkl0IbBXcOaD83kLy0nElS6sVXOzPaWDmuS048jdGAX/u4PMO/7gJqZi2g/9VoSkRAlldlllcxIeR7G8DFYjHkeJC/FrampqUDdKDKVsGoxBJsRWdVwuT3jHp/OwnfZictw1VbjFsKIXRuhubLgFr6pyqpVq3Ju++6/HkTe+wqCxc1RX/hpRm0yEcrGioW0vvwPTIk25J3PIZ15SVEoHybkM55GY8SqTM3R9MRF/MEgXc//jeMuSa+4HdGr7Inewc+TuBxAenk+kz0nfpPpc45iOh1I3ibo2J6bPE+E6C9bMZWz0o54RioWcCBuJuDtwhf+OyeMorgV6hnp/x0FVaZm6+2Eo7txKAE00YjmrEVQEoR2vcxc9R3W1O5j+Ynr8noPy4nBGgBSFolU+hlLTmXyHSw68VwsoX8jiQLsexGWXYRBEvn0F9Zm3ZfDlaGGgkDlKvb36OW4km8/w8rzv4a77GNp241nTMs0e+pwMs6eeoRRzAxQpOBUm5NQ1hcjU5ZZcdSRFj6Zyx1WxD2vwf7N0LIJDOaCWvimKtFoNOe24Z4DmL17SRoznxhmGvBsW/hR5OZNTDvqLEDDIElFoXwYkM94Go10qzI7jQuwxF7B1LGFWDSMxWpPaXPEr7IPrXk4yRWWdPJ8TZkP6aXvgK+JWb4e6PhTbvI8PlSBLVwJoslGumfkgPMoDJ3/xObbgd/Xjack9f1a6GfEIImsKduKV95ERBaQFTOiKCAkNLyaGz9W6g1depKJxid1L4scMTvLSJ5/L0k5wczq7N8H+cope0UDVMyFnl2w5wVYeqFeL/AIYbihoLy6jl3uWdh6mzAro9fUzdRQkI8BoTg/SKVgiltvby+BQCBt3a76+oNX96PIJCQ+6AudjWV4uIXPH3+VkqQfQTKCmkRVhIJa+KYqu3fvzrmtXUhgNEpELfbxDx5CJoJ1yekXg/DZlG1FoTx52LPpKeSIF2tpLXXLTh3Yns94Go10qzKnLjgFX/cutLpVyAe2glEsrrIPoaOrCy0YwyAK2AUr1onu0DgMl+deeRPlUgTBWkIkoeDMccWmq7uLuC+CQRSxqGY8B/9WJoR0z8jZi08l3vIsDqcbc/OL0Fs76jNy8QKJrr+tw2jz4Dj6PCzlM7LvhCIj7XyKcinCPtcsRN/7SKpK1N+N32jCYzfptdC6G/V45oXn6V4WOWAxGVg5vy6ntpC7nEpxR515iq64Rbr1FeHqJaO2m2ou2+kMBfPO/QZOTzlGe0naNke8MW2CyFtx+/Wvf80vfvEL9uzZM+oxiqLke5kihxOJPsuwZMo6ycBQC19UVjELdqySQDIp06ZWFNTCN1U5//zzc267pMIIshNKawvWn5QXYxZMtRfjZKfz7b9h8X1Aj2deiuKWz3gaixET07oq1pxyLobdT8Nzj4OaLHgczeFMe1c3WiAGwEzJPukVN0iV54l4lH3OeuqtBlweaE66cpLnXl8P0ZCeNr4C25RV3CB9rNma5Wcgdb4Lm24f8xlpevcVQu/rWVpLpp1IQy6KW3cj+JoQrCXUO510hhyIcpiYYMFtNerFmAVBT+fu3asfnyZe6VCQi5wa4Y7acDzqm78jEI7S8epfqT3BSWTva1hd5ThmrUay6CvdU9FlO21Smg/N1mWtIrPziZ+Bbx9iaQOzz/1W0Zg2geSluN11112sXbuWM888ky9/+cvcdNNNXHfddVgsFn73u99RVVXFNddcU6i+FjlM8Pt6MCVkJIcHc7aNh1r4nPX0+PfhkINo0R4C5lI8dnPBLHxTlXXr1nHXXXfl1jgZ0f81FmZamC7D3MClEjGMpvSxDFPxxTjZERJ97jCm1OxpeY2ncRi+KuMbsiqDwYwqx4qr7H0o8d6B+j0252FSCHiYPFeDbQR9PSQVlYBtPh67JXt5HutFEgUUVcPq8ByS25hIxlq5HOsZifX6Bs5hc43MypwR8ZCuHBr0N3nSXkNnDFRBJGUEGkx6Oveh7ryHmFzkVLpVprfk2Zh6NqH6X2avawbaG78FYPoXfkN5rWNKrzKld3HeirTzKaobn0eSIyhtVlR5d9GYNoHkNeP91a9+xZlnnsk//vEPenp6uOmmmzjnnHM4/fTT+da3vsWKFSvo6ekpVF+LHCa8v68Na1eIWLiE0XPDjUKKhc9OS8yNFgkCKh4pRl1pyaSx8E1W8ppky7pFv1CKW7oXY9PWl+h+489ocpzjvzqyr1P5xTiZOabGhBpykmxIXW09WEpbP2lXZZy6q26zN1JcZe9j+WmfJnnsScRCgVENHpOOYfK8Oe5ACXcjigIeQtSVlmYtz+cvPwVmz0aJBRFLM4uhPtzJ5RmZ61aQqxzIioa1JMfvyezQV/TkmH6duIjbphfHDkSTNHsj+qqbrNfgyif2snvXm0Sf+xlIRlxn3oR7+sgMt2ORi5xKt8p02sIziB3YhFFNYGj8C5LSiypIONye0TMoTyHSGQrKxF4kOYKKiABFY9oEk9e3vXv3bs49V0/TbjTqD3MiobswuN1uLrvsMu688848u1jkcEPoi3HTcsl8NszCp5pdJAUTXmMV6tDzGUz6cRNo4Zus9D+TuZCIhlFUDc1QGMVtMCvUYEFXX8t7WLw7sAb20PHW36D5dT2eQJGPiBfjZMWkRLAYJZyu1HiGfMZTRgxZlUk664iGA3Tsa6Sj6X38kaQeR1M7GyHm01dlFPng9meyYnFjrJyHc9bKie5J5gyT55rJgYwRTVUoVXv0umCQnTy3lULNMqSZJyEcKfX+hj0j3nCSxpZO9uzbN+ozYk72YjcZcNutmKw5KlTl81E9DYT8XfjDCTw2Iw1lNhrKbLitRryhOM09YbSoD0pnQvn8nG+xxx+gx+enp7uL3lj24TW5yqnh76iNgXJq6ueweLqHebF3ma01M1vbh+kf32Djo3fx1t6uKf9u6jcUnCBvIhGL4AuGSQomJIOJhNHNHupxGRRWxl7F0PjkRHf3iCOvFTe3240s6y9Rl8uFzWajpaVlYL/T6aS9vT2/HhY57Jj+ka8R9nfiyjLBBTDCwheIqVCyAAOFt/BNVZ58MndBuq3pAJIcJWGOUagk8CPcL8oWc7Z6L+X4Mb/wHbCVFGOZJholCXJfOm5T6nObz3jKiGGrMgd692NK+tAAt33apIqjKZIlI+S5gtVZjS12gKScoLujlfLquqI8H49hz4gQ3oMj1gmA5HKlf0ZiAb2txZ1zdkQZkY3qCuaqW6k3dOEpmY0oCARCEUzhA0yP+0kqNrotdkrnnoWUT9iCkkAQQNPAYM5+RTkfOTV8lUmU30CQIohaAiQRUZDoPZJWmVKS0tSj+PbiUEPENJUwGh5X4ZLSFMmevEbekiVLeOeddwb+f9xxx/HrX/+a1tZWWlpauPvuu5k3b17enSxyeDF9zhLmrzidWUtWZ994DAufx2bEH0kWzMI3VbnyyitzaqepKpKiu0oKw+Kc8qX/xbiy3kXN7kcoU71YlV6keFCf2PVnmNt9P2uEDaw5sW5qvxgnG4khKx2m1MlzruMpY4atyshmD6C/nKyJIa72xVX2w4808ryyqpZoLIZREjFEOmnp7s1Knmuadgg6PskYsXKpl0EQAGeic/C4oc/IgOLmyemS/d4Pj0SW01l7BiUuJ2J3IwTbMIUPUJJow00vZkHhZcNq7uleiqyMzCqeKfMrLBw13cNR091UebL31slXTqWsMsWj7JPq0QxWNMlEULMfWatMQw0FZXYEmwdRFBAFsBs03VAgSqmGgiKHjLxmRp///Od59913icd1S+0Pf/hD3n//ferr65kxYwaNjY386Ec/KkhHixwZyIg8q67AqzqoF7uoL7EgCgKiIFBfasNjVLD4d9Gt2FDmnlW08qTh5ptvzqmdpmmIK7+CdtRnqJhbeHesoS/GiGogihVNMqIKIs3JovvFRNLt9bKzs5c9XSH2R6SUfbmOp4wZHkejWMBow2KUsMS62N8dQNU0kBMgHrmrMi/95lpevOMKNv3t/onuSsakleeiiKNmHlaThEVQcAQas5Lnz9z/ff5+29X869G7D8EdTBKGPyOyEc3iwWKUMCb8tHX1jHhG3mvaz76eME3h7N+RQ13Wl8+sYPnn1iGc9HWoWw2SUa+xaDCDtYTS6gY6l17O5uYg97y4N3flTUkCIAiCXgIoS/KWU8PcUf1Rmd5whFBMJixzZLlsDzMUKGYPqqCPo5hxiCt90Zg2IeSluH3pS1/i9ddfx2zWf9wTTzyR7du3c8stt/DLX/6SrVu3cs455xSko0WmPmNZ+Ij0EN2/jZrgVmxqmJelFXlb+KYqjz/+eE7tREli2WkXcsxZX2LGooMQRzPkxRhxzSGuiUQTCsHutmIs0wQT7g0QjisEYzKxYblgcx1PGZNmVaakdhZWk4RJEpBCB4qr7ICltxlnqAkt3D3RXcmIseS5t6cHWVYwKGFMaoxXxOUZy3NPeA+10Q9wRFsPwV1MEtI8I6U1M7GaDPrKZegAzd2pz0g40IMvkqQjkV0cYNo4Y6NJTwp0/l28u2Idylk/xXbWDzBPPwrR6uYrtc0pcczpfkdZUdnclwAkLUpi8LMh63zU+cupYatMbjFOMhEjoagYBfnIWmUabiiIKoRcc+h1zqEzaabZGyka0yaQgi9XzJo1i2uvvbbQpy1ymODr3M++v/0c0eyk6riLqJq1NKN2KS+LmRUsP3Gdnh2r8R/g3Us4EkUwWgjHHQSlEiIlC9ncHER7ce+YsVBHYi2w2bNnT3QX0jPkxVjndNATL0GIdqMmg7hdNcVYpglEMhiJl8xHSIaxuVMz0B3s8ZQ2jkaUwFqCFR/Ee+kN7qHb4so/juZwRVWpssgoqpG4Z/LLsvHkuWQwIFvLiSYFgoYS9ruW81aG8twjxbA5TMTKKw7xXU0coz4jjgqsoU6IRxGCO+m2llA69yxEUaK14mT4/+3dd5hcVcH48e8t02d7yW6y2SRseoEkJISqkRqEAIpGQAGRIoqg/IAXXhRRIlhQeUVDB6WJIgqC9BqRkkISkmB6siWb7bMzu9Pv3Ht+f0x2s5ttsyXbcj7PkyfJ3HvP3N1T7in3nBNpIC+v602kO7O+wt/l4lBrKpp44FNb8tgJC9ArP4FgLdrWl7jyrFMA9l+b1e6Zm9L2Li1zbCG5B2wv9bucOmiUCduBxmNYy6B1Q4VhsPXBIdfSUbDrQ/y4yPTYKcpOTp9I+ML4wwaIEBPMRpTiRYdtZ9pQGZAn4ObNm3nllVcoLS0FYNKkSSxZsoQ5c1KrtEujR8BXC7VbsIDmWWcwJoVrulxJcPb5MONcNm9czYurtlMyKY+51X+j2BbkAu8Gglkns6rNMvMHP+wP173AXK5hujXvQQ/GoJ5BuqgDwB6uAva/gnE4PBiHmaLJcyiafG+nxw5lemrJo+vC87lybFlyOfP6bcnGu82NaK7GbsVwIHhXO5Wa+jlcYVqH3/xHI8T4rP3xUFw4tPfSg1TK8yffXMP8kqnkN23GM/0LXD5nLuqHZe22DemsPH9k5Q6ODTaTn+OmqGh4/x4GSld5JKSm4XI6IBHHZkZxYPKudjrV9XO4whKc943vdRled52ZCydmw+LkVi4Hx8HB27tcNeM8tDUPkQg1ULfxda486exuG23dbe+yoawe274AiqIyQ9Ho7XIq/S6nDl5IJwZ4JqIlwvhJRxxGC6N1tSgNQHG2G0QIW1MF9U734duZNoT69fSLxWJ885vf5KijjuKWW27hoYce4qGHHuLmm29m7ty5XHLJJa3bA0iHiVgzdk1FVcDhSW2T2O56+NB0ph95LFnTT+KNhny25J2Fw6aixpu5PG9L60NkfYW/XZiH815gq1ev7tN1dRXb2fzCb9jy6gM0+w7BarAHPxgNGzE9HUVRiWKnvEG+fjEc9TU99aSneTShWIKwmk4TXvxaLvW5C1OaR9PjK1kjUdtOjL5sszKIUinPy6NpvNGQy9ZxX2b+3Pk47Xq7Jdm7Ks8379lHpttGuss27H8PA6GrPNKQPY/qoEVDU5iILYtmxUujnk9d2oxu80hLeA+8t6vbPLJwYnannSMdtnepKKLS8LClqony959CVG1kobqjT9u7GLEIhimIWhqK2vuqab/Lqc4WRhtbQFHxEWR4HIfNwmg9TVlRm6uZYJZjd7oGZFEaqff61Uy++eabeeKJJ/jud7/LtddeS0lJCYqisHPnTu69917uv/9+srOz+b//+78Bul1puJvoNWFscsUrUZDKeFv3PXzQfjn5l/YIjkhkMdvdiLbtX1z5xS9wUkYNs9UdUOOF3GkkUA/rvcAuv/zyPl3XUFVKYtsbJIDmGV8gLbtgYG+sk9cvctMmowiTpqBIvn7RIF+/GG76mp66k+oo+xHj05m863FCmdM5/aTjSZQqPY7KjMpR9m5W/RxuUinPf/fdc/n7Zn+HuLzyhPHdlueLx9kobtj/SvUob7h1l0cypi3lrdffYdfeakrG5jBpz58ZowVZNtNJIp7daR4ZqM7Mts/jNaU+7OIYTo4/TFFkO4lnL8PmSevT9i72aadQ4ZiApvRt1dD+llNylKnnV5wxk6ONSvEisqcsobp+TkpTVqSB1a+U99RTT3HxxRfzhz/8od3n06ZNY8WKFTQ1NfHUU0/JhtvhpE3PsNKLB2tPFay2D4t/bjuR9Ia/UKBWEn/sS8x26slX8OReYABcf/31PP74472+LhENt/7b4erDHnw9hd/FPA1/OM74LFuvH4yH4/zFQ8W/bydmrBl3Wjau3AntjvU1PXUnlVGZ9wNjeLPUR93M27j69HnYdI0rxyd7dnuaRzPaRtmbAz5E1EBXFXTdw3DfdrqnPHnTDf+PRx/7I7B/b0fL4JuJZzF2vMdsu9Jlef7FCU3430r+Hmyqm2H6UviA6C6P6DY75595Og+/v4c3Sn2cPOkS5h8/HT13ElcaccbWriSxbh0VkSlMOvlbJHTPgHZmtt33LOfTTeSYtbg0C82ug+bASkST27v0Yt+zo2bN5qhZvZuP11Z/yqluX9nW7aiJOBPMRuqdbj7QFyVfRx1lr2z31JlG/bZk/c6R7FDRNJ0rTAvR0lFG551p0sDrV8PNMAyOPfbYLo8ff/zxh37zVml4iTUn/1Z10Hu/iWZ3Wh4Wj1gGoQ9XkEiU4VBMEjkl6E5vnx4Wo1FfH16z8nSsogwsS6BlpPaaa6q6m6dRH7Qw7BbFWpgGu4M1YiblPTwYR+3IyhDZ9s5TOCo/Iu7M4Zjv/7ndsYFutEHvRtnXlvp45D+lKY/KjMZR9rKqGhJ1IQDGmU5G+rIcLWmqpfJ/9MffIxHfjB0TI2cSNld6p+X5zvUrifqSHUz5Ceeobrj1Jo+8UwrNG+NcmfM39B2vcUr5WpRgLaxWiPvXslI9bsA7M1u2d/GZawmq6TR4J1Kc5UFAciVCXBTrdcmyfttLyQbAIdTfRtvhPsrUU2daZwuFHVxOH9yZJh0a/Wq4nXHGGbz++ut85zvf6fT4a6+9xumnn96fr5BGmESkCQ2RHG1Teju9uGfJh8UmfHoEJWEREg7swobblTUkD4vhaOnSpX3qMFESUTRFQdMUGMANuLt7MLp9e8iIB2mKqwT0XFQzgkKUNaU+hNr5g3E0j6wMFbF/pNyydRxp7Wt66klvRtmTozIJrszegPXpX5kdDxxWo+xGuKl1sQZX2sB2qgyFljTVWvnX6lGwCOFAjxlo2Z2X5/HQgdfoXGmZQ/cDDJJU84hiJSjc+Ad8idXkaiHMuIGmqKgIoqVrmCK2DHxnZpvtXcrSJ+KPJBANyUZ1ILJ/e5eskuTI1bZXk6M2h/D1wr6UU3KU6YCeOgq6cmDeo2y0DZZ+5aLly5ezbNkyvvzlL3PNNdcwefJkAHbs2MGKFSsoKyvjr3/9Kz5f+0mw2dkyckerNdvKcNcFSKSlcfSh+IKWh4XDYp81loDixSXSoSE8JA+L4ajPlWxj/6uSugNUrftzU9TTg1Gp30ZWpIl3Ngco27KGkxIrKbA1cKqyinf2HMvfgzs4f3YGuiv9sBhZGSpTs1Ww3MRy8zscG8q3JtpWTEvW/YxQeCUOESGePQm7K+OwGWUvmXMszRlujHATHk/6UN9Ov7WmqZby3J6gxsjDaTWjxxqprPPhj2kdyvNpJ9xI1HsZsXATaelZ3X/JYaK18ZtYTSwaZgduxlg1qLqduFApVYop1g5BZ2bbfc/SPIj9z2DLsshQoxRnF/Zqe5ea/zwO/gr0rPHknHBpr2+nL+WUHGVqr68/h66po+Z3MBL0q0Y7Y8YMADZt2sQ///nPdseESPaMzZw5s8N1pmn252ul4SzejBAQ1wZ+jhTQ7mFRmF9AfP/DAiDDZZN7gZF81/+ee+7p/YVGJPm3beBG21J5MOrA+eMtHnJPoOaj/zLD5udrsec51ngXq6qG2G4N3eU8LEZWhkq2HgePHfJyOxzrc3oaIAdeydqMZsUI4YRQhMzsiYfNKHt64WTSCycP9W0MmNY01aY8z8/OJLp3E4ZpYQ9Wkpl+RIfy3KGYOBZeMNS3P7y0HflyF5DdtB0TAVgYiu3QdWYevO8ZIEyD3PhevEQJBeykZeamvL3Lrs/WYm/YipEzneP60HDrSzklR5mkkahfuffHP/4xyiF4HU4audJmnk6kYSbujI499wOik4dFomUulGkcOC+Fh8VoXdzimmuu6dN163btw13dhOn1MFBN3VQfjLqmctXnp/Fc5DLS11+PEW5koqYS9hbjcbsPm5GVIRNPzp/qbMXCvqanAdNmVKbSGIM74ceRaKaqthZ/3CFH2Ueg1jTVtjzXnURsmWgJH04rjBatAjEZFA7r8rxH7Ua+stgXzcZjNADgVk1yDlVn5sHbu0QM3LrAGYthIbB8e7DcnpT2PUuYFvWBIJlxk5jR5Wnd6ms5JUeZpJGmX0+3n/zkJwN0G9JoMfukcw/tFxz0sGgIxjBMgdtqxhuppCI+jvFFRT0+LEbz4hb//ve/W19b7o1YJIhqWERN24DeT6q/W11T+WpRgPDGBFbcJKLYcTudWHL+4qElxIHl5u0dR8r7mp4GTNtR9pwcohUbMRIJXMEKstNLKOpFxfSwrdwPM61p6uDyPJHNWIK4iKOG69m7V6do/MTDujzv0UGdmaanADWQnJ4SsWccWMAlxZGvlHWyvcv4rAz2VhmkhcoxEwlC+7biddpQJhzX5fYuLXF3hJKgIMNJbklq2wgdbMjLKUkaJAPaZR2JRIhEIgMZpCS1d9AmmTleBwXpNnITVagIPJG9VFbXdrtJ5mhf3CIrq29zP+yFM4iOORqtYIheLd0/suJ12DBt6RiWwFe1h9JaP/7w/vmLY0tQoo3JkRUz0WVQo3IT5kMkFg1R2RiiuilKbaxjo72v6WnAtKmYKpoNn56HKQSYBlnhUkQinjxPtyfP66Jimurmw8PRh/9Ywft/uZtP//PyUN/KgGhNUweV59leF0bmEcQtDQF4otXsqWpoLc/f/vdKXnn6d3y48rXWsEZ7ed6jgxq/jVGL5rTJGK48qs1Myn1hLCEgEQe1+5Gv3kig8ra1AJ/lpVitozjLiaYqjB87loS3ABBo8QDhSARz8v5F6mo+g/JVnW7QXZSuMznfS3Za3+5vyMspSRok/X6fpLy8nNtvv51XXnmF+vp6AHJzcznrrLO4/fbbmTBhQg8hSFLqOuwFll0CikqFUYwnWIqOICe4DZ97LJklp6EdtCrU4bC4xbhx4/p03dFfvGKA76SXWkZW3NnY05wEK7ciRAI9UEZGVknK8xcP6973Pgg1+alrjgGgRTUOfsm5r+lpwBxUMfWTgWWLk2bUY8Si1Jd9RvaE2di6GZUZ6ZV7W/n7uGONRKwocNZQ306/taSpzstzN+XmJNxNu6lT8siM1iX3diw5jfx3nsIRbSASnQcnnnpYlOc96mTka2x2BpBD0BfGHzZAhJhgNqIUL+py5Ks3utv3TNXt5HodxCOChKnSaNipfPefHLP9NVR/WZerwc5odKJGwqD1bZfCIS+nJGmQ9KvhtnXrVk488UT8fj+nnXZa62IlW7du5YknnuCll17iP//5D9Om9b+gkIa/YKCBig/+gu7KIH/m58gYUzyg4Xf3sBifYSeQSMMVrcEUOla0mdL/PMMRjmaUw2jZcIDXX3+dY445Zqhvo/fajKzorkwiejoOI0AMG8FIgmJBj/NdRnoFfSjEY2GEakOxDGyutA7Hhzw9dVIxLcoqoW6vhR5pQDOj1JVtozBNQxm/EEwz2as/ijpr0pQIlqZiukb+ipKQTFPzj17QZXlenGanLpFLfsxPkDQqzTz8HzzH5PAGFMvEbAhgPf/tw6I870mHxm9WSbKDCyjOdoMIYWuqSDZ+pyxB6+f8z1T2PVM1O/Zpp7JvbyVqUzkzG98m2OzEmzceVXd2OmdZfXH/5Da9bw23IS+nJGmQ9CsH33LLLaiqyvr165kzZ067Y5s3b+aUU07hlltu4fnnn+/XTUojg6+mgtimF4kBNRnjB7Th1tPDQrXiZOaMobopC2doLx6rGU/DKvbZx1KQm4Vixnq1uMVIngtzww03DPUt9M3Bk931QrJ1F0GyaI4m2Lg3wJFFGWiJeHKD92DNqKugD4WC4qkU3PQvEvEoKB1/X0OdnjqtmKoq+UVTqCpNoBohEpZFU1SQ5q9Affn60bXHWyLO9Dwn4IQp44f6bgbE96+/vsfyPD8rnR3xiQRCEfKNKtJ8AVRM7HYdbCrNcrGibjsz0e2oiTgTzEbqnW4+0BdRXT+HK1oW8+rH96Wy75maO43cDx+Ft+9AxSJiWlQFnZSMyWRvJNJhzvLu6kZ0EcdsNJjUyff29Dwe6nJKkgZLvxpuK1eu5IYbbujQaAOYPXs23/ve9/jtb3/bn6+QRpBosKn1307vwG0Sm+rDQnF4yd+3icirt6EYFmFhJxoNs7Ehh0x3OoEUF7cY6a/affOb3+TZZ5/t1TXCsij/5DXsTg9phSV4c4sO0d11o8PIioNx2ZMYK2Dj3gDNUYNN5Q3MUcvRHF6C7/wajw6K1rsK+khulB9Kut3Z6ed9SU8DpadXsgqzM2lujGEkohgxCNZVoLqzcbvdMFo6a+JtRpYdHUdER5qEafHF63/LtBPO7LE8L6najO+t32KKMIoZJ4SOqao0W2lU4T2sFytKZeQLzYZSvIjsKUuorp/DmvImxPt7+tyB0at9z8wE6TWrMdweQlGDSjGGxuYEgZgfu652WA22KZhM50ZEtGu4pfo8HspySpIGU78aboZh4HK5ujzudrsxjD6u7SqNOCUZFtbYdBKWQO1kP6i+SvlhYSbQ3v8tHpeDWjML3QyTQZBwpI7KeDbjMl1kZne/bPhoeNWuLw+vaCRE4zu/A6Bq7jeYf8bFA31bPerylR8FjizKYFN5A1NjGxFKgpglqA87aHa5GOOKp1xBH+mN8qEw1I22bl/JsjlIGzOJ5voKGmMqe+NjcBlxsnGA4hwdnTWx5gP/7mS7hpFmfYW/Y6OtRSflea4WpkbREftPiRgWjVhkph++20D0ZuSL3Gloms4VpoVoSePQp8Zbr/Y92z9n2ZZeQHphHum+KMFAlKhhYtMUxme5UdXknGXh20N9+lEEtGyKcqZ0+XN29zyWjTbpcNGvdwvmzZvHI488QiAQ6HCsqamJRx99lPnz5/fnK6QRRDNC2DQVl03D4c4csHAXTszm6sUlPT9oWpcNzya7eAamaiemeghqGWgt+w0qavI1kobdsO0Vtqx+k8S+TR1WuOrpVbvhvGrh0qVLe31NNHygV193DNwG3Klq+d0/G55P7dhTyEpPQ63fBk1VEG5AC1Yzy9qKQzEwhUIgrqJ6sqkxPHwacLObYtJ1k4XRj9C3vdTtd4zkRvkhkYi13wPxIH1JT/3VaV602ZMV0/MegHPuhTPvhrN/i5oxjnSHjsicSKYSpNgsJ+aroDoQIcPd80qkwz1dGOEApiUQiFEx4rZwYjZ7Xn2oF+V5FrnFU1FUDQVQFYU0tyu5WJGqtV+s6DCRUmdm8aLk3/sbswc2jc5mbamP9RX+Pn33wonZqTX42m5ToGooioLXoWPTVIj62bu3HMsSoNtRzDinHncM5y85jUVTxvb6eQxDU05J0lDoV/fUT3/6U5YsWcL06dO57LLLmDp1KgDbtm3j8ccfp6GhgRUrVgzIjUojQGvPsNLpflD9kVIPeJsHhabbCKeXEIgJXCgIIQhEDMrrmymmGTXiI/L6HbgignqHk7zx03hXLEj5Vbth2zsPvPRS5w2X7njUOJPzvckKYsHAjZamIqVXflQd3ZNFImgRMnU0TLxNu2myFeGLaaQ5bWQUlqA0bIOtL0P2FLbsrWFKUQH6mBm9mv82bF+ZO0TW/uthnDv+hbC5mfP9v0NLJ8d+fUlP/ZXyKHvNZ+AvR3FlMcHroiHgQ0GQQyNeM4qwJoDibt9ZE3SNqHSxa2810coACpAf1Skc1G8/NN7568M9n9SmPFdVjUDaVNyhcgQKhtamc2mg9ycbAXo18tXGgcZb1qFPx51s0J3hsuFQEmSHatEiJrVlQfJdAtUIwYf3JvN2H+emDkU5JUlDoV8Nt5NPPplXXnmFm266iV/84hftjs2dO5cnn3ySL3zhC/26QWkEaWm4OdI6VP4GxcHLhscgw5VcoSoQMRCWRVbjZiwiKJqGw6PgcDqJRiL4tv2HKepGrhx34FW7NaW+Dg/GVHrnh7rif+utt3LXXXf16hq7FcPu2F8cpA/eynUpv/ITrEH54P/QXVlkWBbB+r0kLIOCeBlOWx5BsqhojFAsQN31DuHKzbhC5qhrlB8KZrSZhCVIWEqn+bYv6am/Uq6Ytu3VV1SC3km4mnZjxyBNjSGadlBvjCHXHk+ps2Z9hb/T7+wpXRzKPB8PJ+cOC8DpGbi5w0MppTR1cMU/DqSXAMnyHF84OerWw+bco1Vf05quqYNTrnWyGmxxtptIyCQcUUEkSDdqwYgjdAeKqoHm6HTFyVQap0NRTknSUOj3C+Gnnnoq69evp7q6mrKyMgAmTJhAQUFBv29OGlk27KrAU9uMlZbGkGwA0cWDAqDcF8bh24GHMCoWcVPH5s0n3+Zh494A5UY6RygNLIh8hLrtJda4T+Klt96lYoyNcxZO6bR3ft74jpWoVCr+h7phd+GFF/b+IiN04N+2wXtVMuWRlfJVYCVQdCeKK4to2MQW3AfCIjdRS1qiESWuYNKEgonTlYPD6Rp1jfJDodBlonrtRFyd/0x9Sk8DIKXf8cGVe0OFrKlosVq0aD2KsEgPlyJCBpaq4vDkd9lZs77CzwPv7eqQFtumi4IMJ3PGtu/YONR5Pn9sMf4pi7GiTXjSR8cmwymlqR7K80OxP5k0cLqas+zxpmOfeBTR8g04zCACMCwVW6gevGOojLlooLjXC88MVTklSYNtwNbPLSgoYNGiRSxatEg22g5TkWY/oZiJL+EYku9PoPK2tQCf5aVYraM4y4mqKKiKQnGWkzQtjorAQsFUNCL7/ktDdRkKgjSnnXq9gKC/BuvjBzl67c18t/le5n92J/XPXI3596t497kHWLenrrXR9vD7e3j4/T0kTCv5/T1U8Nqe84tXtvDx7oZOj3c3dy6VuXWbNm3q5W8OMKIH/j2IDbeU5y8eVEGvMjOIpE9E0R2YQuARQbKsBoRlEsMB3nzy88fSqOWyxRyHLuIsiCTnv63ZXctLb7zJi/96ocv5jd01yruKu5Zzuoqf4TovstgrKMpyM6VoTKfH+5SeBktL5d5fhz8UJ9NtY0JuGjnjSgimlaAgsIk4CiaGJQgktC7TxbxxXk7PbaBx6/v8/dU3SBjxDnl6nz/CHz8sG9Q8nzt5Ac3zv83Mi36O3dH5yp8jTSppqtvyPNtNpktP7k9mujGnLDlsFiYZCXqas2wL1+NVIyioxLETsmz4m0P4q3YTDDYnV5zsYW7qwYZ1OSVJA6jPDbdYLMajjz7K1772NRYsWMC0adNYsGABF1xwAX/605+Ix+MDeZ+HpTWlvtYKQlsJ0+KJj0o7PQbw8a76biuWXV3bU7g9XdvoHE8kewZa7uROjx/KSmtPDwq1sQyPFcRU7DSrWcQVOwnTwhGu5ghrDxMdTWQ6FEwjjrnvU5TyD8n3qMlRm2g02Tu/8zGuVJ7nyuMKWeCq4qysCqq2r+WRlTuIxhPdVvDa3uNb/63GHzH4pMzX6fHuKng9HX/io1JM0eEQ0H262FNVz7bqZir9ESK0b3gf6rhLabJ7JxX0wjEFZEw4ipA9H50EiqKiKAoRxUF5UKXcF0ZRGNBGeVdx1/aczuIn1UZfX/Nmf/J8TX198j/2jgtfJEyL0pDWabjDQXeV+8K8bDTdDvs7a+LYCERFl+lCf+HbLKu6myuD97Ng40/Y9fDFvP23+1m3p46Fxen8eKFgafbeIcnzD7y3q9M8OFw7A/qrx/K8uZoJZjl2p4sP9EU8XD+ny7whDa62nRnzJ+Ux/+vLUU78PoxflHyl1YyDSKDoLpSMcfgyZiFQsIRAAC6H/bBeeEaSetKnLqpNmzZx7rnnUlZWhhCCjIwMvF4vtbW1rFu3jr/97W/ceeedvPjii8yYMWOg73nU6eyBs6bU1+VrO7e/+Bmvb65mW3UzPz1nVrtK78e76vnhC5sBuPNLczj2iJx239PVtT2F29O1D7+/h7XWYq4+raTT+R+Hct5QSotbKCqK3Y3uziFAIY3+AIWiGpdigGmgNu8jX5RhI4EQgmolnzFpheR7OfAqJfUsaHwF9an1YJl8yTQ4PmSyZ20ej312HJ94PseCI/K57Nhx/POt99i19b/8PbiD8884GVS99R5Pnj4GFMG6Mj8P799TB+hQwVswIavD77i74y3xs6BwLBcetMlqT+ni3U17mNwUpTmqkaU72h0bDnO+utwqQNMoKsgjXrkPy4wjNBuGMw9/JEFGrIps3UbemEJqQgLTn2yU6/4y8r351CidvEp53O3QsIt9WRVs2L6bR6wE3zyxhD9+WNZl3Oma2m389BR3Lb/nvubN/uT5h9/fw+yKahyZcTIPWlCo5fj6aC5rSn3D7vXQHjcfjgRwm00kFDs+JZOwsBNQMmD/IgnF2W6q9pZiGdFkZ42/DMU7hpyMNIS/CbNuHZPqtvM/OW9TUp+Buqt8SPJ8V6/uDpe82Red7f3aYij2J5MGRspzlhv3wEcrUHQnBc4sNkVVXNEaNBRUW5u5ir1YeKa7NCVJo0mvG27BYJBzzjmH2tpa7rzzTi6++GLGjRvXeryyspInnniCn/3sZyxdupRPP/0Uj2dgVxgcbZ77ZC+zZrWvjM0bn9m6bC/Q7kG/zx9h1rgM9vkjHSqPn5T5W8PorPLY2bWphNvTtalULg7FUtu9WdyCD/4PYRqIuEJUcVKqFJOrBvEmfNhFDJdioCuCmOKgKQ7RhjAgkr3zDhuaaSKaahDhepScySi6k3x3FK3+v2SGyyg0yjkr/UTs/3qLZY2l1AeDNG1U2FX+R0qzP8e6yNEsnJDFFdMjEA/y91CAt/aYPCgsEArryhs5ZVoOWeE97Nn2AX8P7epVBbAlfjZu39brdNHQZFDsyMRjS+B0pQ1K3KWqxwp6uBGHiGOoGj4lixozHZsZIt3yo8RBqfExQVcwRTOWoF+N8itPGA9123ixqWPDbt2eOr4yvgm7GeLTHTU8IqxeNfr6mjf7k+fXlvo4QYujKArNwkHaQb/ztaU+jH1bmTd+eC0y1dvOmgiFVAdiYFi47MkRRGGEyY5V4BBRBOCz3GR580FRCUWcVIe9TBc78PoqUcJeSC9C0R2DnucXKNtYSBqlO4JMnn5Ux59/GG5h0JNnnnmm04r2UO1PJg2MlOcsO7yg2bESUSoaw6DqhF1jiRoWtlAcVVV6vfBMV2lKkkYbRQjRxYtVnfv973/PD37wA95++20WL17c5XnvvPMOp512Gvfeey/XXHNNf+9zVPrss8+YPXs2X/rZM5x2wsIDBZ2ZgPptJCJN/H1zgLfqMpk7Maf1Qb+wOJ3LpsZ4+ZOdbKgxGDt5brvK48m5jcnKY63Z4dipeX7Om5nOC/9t6nW4PV17xfQ4eiLc+lDtzVLbfdXVyGQHZgLrH1cR3PUhuykmw31gtUmHrmKP1FJkVWInAZ5cymwlNIfCjIntIaF5yPWoEKwHy8BSHdiLjgRHWnKSfChOrlGFRwRR7U7SHTqKKwtLs1Pvb8IMN9KMFyVnEiX5GaiBcrAMhGpju5HL35pm8b52LP9v/A5O0z5B8ZdRHwjSFFdIZE6gNPtzPBc5mqMnZHHF9HiyAngI0sX5szPQXemDFnep6FCRO2F8cp+2lgq6lRwxpbkay+5lY6yQpmiCXFuUHLMe3Yri1BTcRMCMY6HgU7MJ2/OwHBkE4iAsQYG5l3yzBlW3o+RMBt2JZURpqK+h3vSwNf14zlp8Ivbdb0FjKcI0qAmZ7DHz2OBchKrAydoGJtvqoc2x9a5OGn1rdvQpfx2SPD/ezeLVV6MKE2PyGcw6/4fDJu670u3+TvvLzradNZZpUBbPoDqQnMfptCVfqc0TjeRFd6OTQKAQUT2gO4npaTQYDjL1OBnxajQzStSWhXvCfFCUQc/zx224GVe0lkjekRz1rT8M+/jpj5TL84O0TRNXL+741oc0eDpb+KmDg57HmR4747PcNEUNAhEDf9gg06UzwSxPLjxz3gNyDqM0qFrq55s3b2bWrFlDfTvt9LrhtmTJEhRF4dVXX03pXIDXXnutTzcXi8X48Y9/zJNPPkljYyNHHnkkP/vZzzjttNN6vLayspLrr7+eN954A8uy+MIXvsA999zDEUcc0eHcRx99lF//+tfs2bOH8ePHc91113Httdf2K8xUtCSMHz32CvuUXBYWp3Nlzka0Ha9BY2m3D3rVX5Zy5fHgY0o/wu3q2pNZhajZgqoIVIcXckp42zyaZ8PzmZ/iPix9lcqDImFavPvcA0zZ9Rjpuknm2BJQVJoiBukuGzXVVeQ0bwFVQ8+bSpmRgfBXkGE1oiDI0qJgJbCEgomK3zmOkD2PgKGS6bZTrPkRdVuIYac2cx7FuckewrKGMNWN4WTPvRpDd3pR0otA37/scWMd1XEXIdXNOJdBnhbpVwVQ9Zexc/tWvAUT+5QuWvbQGay4607KFXSbE+v9/yO4+yN2U4xAQVEgw2VDSUSxh6sZY1ahChM0OwHLiSnAUOxEsqYzwRbAqN+FYsaxVDv2oqN6bJSjO5INu7pqsAx0VSHD60F1Zx841odGX3/yZl/y/GLrIxI73kFBIDz5uCYu6BD3Xzrv3GG1R9JAdNY4bSrEgkw0dmG3Iii6nYjiwtg/QVQIgVuE0bBIqA4SQsWfPpW45iEQMch02wYtz4e3voUqEpiOTDyTjx8WebO/li5d2mWaSqni34nRuOLraNXZ81hVkyPhlhCUN4SwNVVgd7rIPv0mtCO/0mOY3aUpSeqtUdVwGzduHNdddx0333xzj+f+6le/4ne/+x2VlZV9urkLL7yQ5557jh/84AdMmTKFP/3pT6xZs4Z3332XE088scvrgsEg8+fPJxAIcMMNN2Cz2bjnnnsQQrBhwwZycg7MAXnwwQe5+uqrOf/88znjjDN4//33efLJJ/nFL37R7mfsTZipakkYGz7dyEf1dgo3/oHjE6vJ1cIHKofdPOhTqjx2daw/4XZybZYIYISbsFDR0vIx4hF8lpfasacw/+vL0W32Xv9+Bkrrq3Z76rhSeZ6F0Y+Sq1Xtf9WORBwRrCER9hPETZl9CigKmUoImxHAaQTIJIiqAApYFgRxkUDD0NPInzgDtWYTItRADDt7tXFo3lxQNAIRg7FqIxnRvV323JdYe3AmAjQraTRlTKc4J/lqcV8rgP1OF/66YRF3qVbQD64EZBSWUOGP4g8bTMhxEw3Uk9O8BUVRUb25+IIxVGHQrGYgMoqZaOyEqJ+YqaCLGE1KBqYjk5Cl43S6yLdFEQ27iSp26tpU0Mt9YWiqYqxRBigEPJPIGTux9VifG32DmOdztTCm7sZCQ1UEkaB/WMR9Twa+s2YKNREFJdyA04qgWHE8REDR0RxO4kaCcn0iwjJJN/3YHS4yLR9KPERcsVNmOwKbJ7lU/4DmeYcXrDgCFeFIIxQ3R0T8SFJXUnoeRxqpN918oC+i+shruOLzU0ZkB4U0cg3nhluvx559Pl/Ky/2PGTMGn69vK16tXr2av/zlL9x9993ceOONAFxyySXMnj2b//mf/+HDDz/s8tr77ruPHTt2sHr1ahYuXAjAmWeeyezZs/nNb37TukljJBLhhz/8IWeddRbPPfccAFdeeSWWZbF8+XKuuuoqsrKyehVmX+iaypU5G/ElVhOPRShLK6Y4LfkgL/eF8SsuSmx7cCYqaY6kUZYx/cDxSBi0MGOtMrAUGsw8ctIKej7Wn3A7ubbSMZYsJfkqUr2VgZ+8Xu/DciikPNF94gmojRUkqktpihqkOe2MHzcWRRlLTXU18eB2NAVsGFiKRkIkHyKmZod4CIwIiqZjsyzyjUqMxhoUVSdHt5GWaAYRw0BFM5qpriwl5hrT2nPviSsoRgK7lqz0lTWEgeS/S9xB3FETxUwQMhTc3jEHKoBdxN+6devInTi9V+ki25WNoihUhG004hoWcZfKJsydzn9r2EaxM5Ncj4Y3EUGIWhKqlmyUG0XggEw9DqpGLNxELBHCodvQrTgIBVUYaPFGPJqKK6GihJqxMLGLKE7/DsqU5H5RgXCcyTSiK2AKC3ukhsq6DCxFJxA1yfTYGatlIOr2EYtFKXPNozhtf6PvUOXNXoZbnjGd4mwPWstx0jvE/bJly3j22WcPYUz3Xk+jKt3Ni8zU7dAcp6Btugi4QVHISM8ggoVoqsFlVqDqNhAWAhULDYcVwm5FsEVDKERQsLATpzhRTnNjFXGhk23zkucIgWISVx2oiQhVlWXEdS8hQ5DtdOBNKJBKnk+Ax+ZAURTqRTr7SBsWebO/hmOakg69Q7nwjExT0uGi1w23WCyGzWZLLXBd7/O2AM899xyapnHVVVe1fuZ0Orn88su59dZbqaioYPz48V1eu3DhwtYGFsD06dM55ZRTePbZZ1sbWe+++y4NDQ1897vfbXf9Nddcw9NPP83LL7/MN77xjV6F2SdmAm3Ha+RqYcrSivFHEoiGMCSihKIGWQ4NrynASOBUTapDzZQZEQCa4wpHKAFsukbCtNAjtZRVe0BRicQMJuLDpqmYpoVt/zFFteGPK2S6bXjjarICoZiEgs1UmjFQIByJMxEfeptryxvyECjJBodLwxW10AwDh2oijDCaqiAEhAzI9NrJzCpJVpa2vZqcWD7I76j3ZqJ7InsK7/7jEabUPsYRSgP1FFDRGKY4282YLA/xsAZmjIjioFYvRDgzUI0wIcuG6g9RICwUFISwECgAaJjYLAOsGIoQaAhUTGyRemrJTq5s5zURVSEQFk6jkRKxnVjchoVCtq7hjvtRzRgmCkoiQlVdfevrWjlmHXYRQbfiuLUYgeYa6uI2CsfkEvRXUyRqsWkqCUugR+spb8iDWJBILEaxqMemKZimhSNSTUOZD92KoyluMrMnD3ncteiugt5dJUD17cGrJF/97LRRXpCPokBNTTVW3CSWULEjiKguQiINtxIHBAgThIkAVBRsqqA6YgCQazdwRaJYwkQFvFYzWtMWTDTyNBWaIGEE0TFRVZVYuJmyBhWEhda4h1zFj64IhLBwh/fSsM8iYSkk4ibZmopHp12DvrxyH4owiRkmxbSPv/JKGygqzYbGpDblgS1SS/k+B6ASS1jkOTS8hgmGgV1JEG72U56IIXRnMl97OubbP/3pT4MQ0wOnP501xdluFAWqzAhGk45uCYRpEFG8ODzpaJE44agLD8mFi1oIBTSRwEkCw1L2d+TYsOsqRjyGN7KXBDq5mopXASXWDAhcCT/jE9sJRl34nMVkOHXyjAAoJgYKNqOJsOlC0XSaFEFm2tCXqwNhpKUpqf8O9cIzMk1Jh4s+lfilpaWsW7eux/P27NnTl+ABWL9+PVOnTiU9vf2GpscccwwAGzZs6LThZlkWGzdu5Fvf+laHY8cccwxvvPEGzc3NpKWlsX79egAWLFjQ7ryjjz4aVVVZv3493/jGN3oVZldqa2upq6tr99nOnTuT/2gshcZSFFcWxWkeREOYQMSgILKHDAxclkCxwoCFy2pmothDJJZsHLicOXiIo2g2dA3csRBK83YsNAp0gdMKJxsNKnitJmjeTpOaRUbmRIq9JkptBAsVp9lEkbkLEskkkataOK0wliVQEXisZmpCTURUNxkuG+OcEWhsRCBwmc0UaCZxK1mget1Oxme7k8u1t92HZczgDjenusJVu975cWUsiHxEeqAcX5OHsJKGVzNxqCYJU1Ar0vFrOcwZk4miJEcpAsEAWQmBQxhEtXSq1Dw8molbszBiTdhFBFVVwTQBBVNpk+2sBAiLZLMvWfnT97+9bDctVDOGQKACugrhaIyQaifDqZHpr0MTYQTgEBEKRA3xsErCNPEqAgcRhM2Jrqu4EnFqQ0144zVkiRBOIigKaCp4rCBi/6ufqqYnV/Ma4rjryYA1yjM9xEMqqhlLvgqpFyDSCokDzeEYBVoTeVoMSCBQMWwH8rgqzOR7sygISDbXhdj/D1BEAhUTgYLDppLuUKiJGKjCZAJN2EWyk0RVwWlFEZFqDKHhEAKbZaEAimbHoxnk2g3UQA12YmQrFk4l0pqvPVYQK1yKiYbTkdWuPHDFwxDajYlGvk3DZYgDjQazmXFmKQEzA59jfOsS+QfH/W8e+ge33XbbIMdw3wxUuijMyyEcdqEajcSwY3jz9r/O6KHcl0dNMIA7sRu7FSWqeakhF5vNQLUSGEIhnkhgt+kgklu9tHTmKArJNLI/xShCoBPHRnJ+j80MJxt9qo6KAVjELRMLFbfXScEIyJup+M1vfjNi0pQ0MFJecbINXVNbV8FNXpvVZWeeTFPS4aJPLw3fdtttraNP3f358Y9/3Ocbq6qqorCwsMPnLZ/t27ev0+t8Ph+xWCyla6uqqtA0jfz8/Hbn2e12cnJyWs/rTZhdue+++5g9e3a7P+eddx4An37yEc2BRvbW1mMYBlVVVQCYVvKhb8TjCCEwBQjLQlgmLVMTQ81NgEVzKAyKihBWcqEBITATyT3JEi2VSyFQEBhGHCEsKspLSSQMEgKSVQtBImECEI9FAbF/U0wFhMA0osTjMfz+xuRxkdzY1rJMFAGJRAIDGz5/M3V1dTQ0NFBZW08iHmX5bcn5gkuXLgXg+uuvZ+fOnTz22GM8//zzrF69muXLlxMOh1m2bFm7c2+99VY2bdrEn//8Z/785z+zadMmbr311nbnLFu2jHA4zPLly1m9ejXPP/88m955gbMnO9j6zxXomtp67qWXXorP5+Puu+/mnXff46ZHX+O599YxOcfOYx/7UU/6Pp9UmuRmeGmoKiVmwfZEIQ1koSgq4XCI0vpmPv30U4qz3dQ3+rEsC8O0qDXTiQobmt2N4smlJuElip2QIbBUHZ/pJpoxiXjQT0NzhJ1V/v37+CnEhUqANHxRJbniYUzBQsUUycl1piUIxwxM06SurpZkHTA5FmSZZjKOTHN/E9BKxo+AcCSKgkWo2Q8k0xAITCEQVrISqeyvYPqiyXS1evVq0O1UlO9h7+6thzSeHnvsMXbu3Mn111/f7ty28bRy5Upee+01VqxYQWVlJV+/7kesLfXx2coXufKkSXzvmu9SWVnJihUreO3Nt1i5tZ67//pvarUCTvv+b3g2PJ836rIZm5NJYXgblr+SvXu2EaitwCaSjedakUZZKNlwrdv9GekeB3sDCaKmApZJs3BSaWYRD/rJcNmobAhgoBE3wVTtRIVOk55Do5LFXiONJuFJxp2iEQqFsBSNpqYAwrKICxUBWAIsK/k7b8l7lpXMw9FoBBOFeDRKLBxEYCXjW4hkfCsK5v5rkg0EgRGLYhgxDFMQjcVRhNjfuIRINNKaRiyhIEiGJYQgGEzuk7R2zRoAtu0uxUzE+OODv6eoqKjP8XT11Ve3O/fqq68+EE+vvcbKlSu5++678fl8XHrppf0uI3712N/45webKHLGKXv90Xb5ftmFFxFOm8Tyx9/goz1BfvDQq/x6Wx5lWcdhxYIcQTnh6l2EG2sp+2w1qmWQECpxdOriDspKy4jFYgQqd+F0pxE3kmVnadRDwpVHHBdq2hgMPZ14wiIWTxCLRAjhZlcsi2b3ePbEMqgVGRiWmlwgB42A5cKwpRFqrE12zIQjydJ4f9lroBK0HDSbGtu2Jjci3rJzN1gGP/qfHwxIfhrseAIOeRkx2D/TYJR7I/lnKkmH9H2rmCYqeOvNN1L+mT74z/s0rf4HF83P4w+3X9/lz+RwOGQ8yZ9pwH6m//znPwxXvV6c5PHHH+/1l7REYm+UlJQwbdo0XnnllXaf7969m5KSEu655x5+8IMfdLiuoqKC4uJifvnLX/I///M/7Y499thjXH755axfv565c+dy+eWX88wzzxAOhzuEU1xczPz583nhhRd6FWZXuhpxO++889j83gvM2n4vlhmn3MjAH05uEKvEmojEDbJ0gzHmPjANDKGzTysEmxuAeCJBsbkXhwZx08K0BI2OcSQ0J8TDFJpV2DQwTAvTAp9zPIYtDX/CTp49ztjoLkQiiiFUKtVCHK40FAWMSJBCswpdERhCYAkFX/qM1tf08mxRCsI7UMw4hqJTrY3F5vJiaB4ao1Zy1bVsN2pzdXIflnPuHXY9w6msWtiyJcM7tWlcrr7IgshHBAO1+EwPTpeLfLcCkUbqgwaKGSOup1EwYRqatn+FLMskXLYex/6e+7B3ArmFE4ADC1hMNnfhNhoJqBkEMme2LlRQVVtHZtM2dBVUkSCoeAlkzGh9XbUl/kjEiKNTpk/E4U6nOdiMHZNiswyHrhI3k6/g+dOnEhc6iXCAYmsvdg0MM9khEPBMIKJ6CRjaiIg76HmBiq62ErC2vkK4eidem0CoNqqbDfRQDXHFTp1eSKYn+cocQHl9kHz/emwiTqU+ATLGHjjWECLDvwW3lRzBMuyZuIvntc5BjAYDTEzsxiFihPRMdmlHkO5KLiYRCwWYmNjTmm9b40fzEIjEybPFGBvbA2aMmLBRpk/C7nQDFka4mQlWOXY1GX8JAY3uicRVJ0YsSrFZ0b48cBVjqE5ihkWmzSA/XgGmQVxo7FXHorkzEbrrwGqJB8X98x9u50tf+tJgROmA6G+68OiCmpBJqZlLrlsjPbIXNepHuDLJyUhHNeNYEd+Q5PmRkjd78vzzz4+oNCUNfzJNSQNpVC1O0pdGWF+4XC5isViHz6PRaOvxrq4DUrrW5XJ1OQcvGo22Oy/VMLuSn5/fYWSvVdZErMwJBHd9iB9Xm4qjm3JfmOpQHK9oxG1GCaleSCtsfdCXN4SI+GtR4snKo2XPpLBoUrLy2BAi5PfjNpLHzDbH8IWpCwkyLBtuM0hYzUBNH0thm3BDfj9us821ebmtldK6kCBDceEWUcKKC5FWSMH+a4UvjD9sgAgxwWxM7sOSO63b389Q6OnVjUTujGQFr15nwRHZzD9hOeq2l/BufYVw2Vai0Sghu4cqxyze0ecxxtjLvMjHhCo3483MQ9UdkIgll/JGw8BG2JZcfVRVkhuMCksQaRToaOi6TnG2K/kqFHTzuhYH4qA1/tzYPZmMz/GwN+LHcmcT8de0pgvRNv4a7IT99dAmXeQXjD+w6MkIiDvoxfy3g16ZU2eci7dto1xL4/LsZKM8bf8rsrVGslFebDVSr6ajmDFsGBRkOlvjZ3y2h/KmLFxWEyoK7syC5CuxQHG2m3LLwvJbJISg3konI61NgxBBxG/vPH58UBciGbeJIBHVjcOT3ibP2wn7a1vjz7JnUlhY1Jrn28a7Zc+kcGxxa9xWheJ4hBO3GSGsetDSC9qlqc7ivrFx1SGLw0OhP+nCWbOF59vss3fFSZNQtrzIrv/8Dc1fBoFmctI97ByiPD9S8mZPGhsbh/oWpFFGpinpcDFsZzUXFhZ2uo1Ay2uEY8eO7fS67OxsHA5H63ndXVtYWIhpmtTW1rZrVMXjcRoaGlrP602YfZFA5W1rAVOsjRTrdWRmlbQ+yHt60HdXeeypYtnXcHu6tjjbDSK5D0u90032lCVow3ACfXerFvZUwcut2cLW8ipW1Vu8VZfJ/El5nHnsOP794mOkl73JxFAt+e44tWGLUvtccjOTPffepp00GMmee8wYOeE6qpUM9qpjGWeL463bBq6WZZH7VgHMycnB6XL3OV2MhLjryaFulKM58AWa8FpNRNTkvDctUI9XVVB1B2oiTrHl63OjbyjyfFdx/7nPfW5Q4mwwdJcuEqg8vN3N2sbxLJiazRUtx4/8CkfMOIe/v/4OOyuqSPNmsSlWMCR5fjTkTWBUpSlpeJBpSjpcDNtSf+7cubz77rs0NTW1W6Bk1apVrcc7o6oqc+bMYe3atR2OrVq1iiOOOKJ1EZGWMNauXcsXv/jF1vPWrl2LZVmtx3sTZl8898lequm4bHXLg7yrB72l2busPPZUsexruD1di25HTcSZYDZS79y/D0v9HK4wrWG5D0tXvfOpTKR+f7ubtfU+Fkw6cM7J51/NIytP4eUdGyjymFRqWqc99yLQjKXolOozCBxxKrtzPo+y7RVOVj5hilYPiTi1ob5VAGv37sObmd2ndDGS4q47h7pRropmmuMqZu58Jh77JVZuryet4m0mhmoZ40muWtjVqMyhypv9Cbe7fLtixQruueeeQY2/Q6W7dNFdntdtds49/VSWv7yF3YHokOR51RwdeRMYVWlKGh5kmpIOF72e4zZYVq1axbHHHttuH7dYLMbs2bPJycnh448/BqC8vJxwOMz06dNbr/3lL3/JLbfcwpo1a1pXjNy2bRuzZs3ixhtv5Be/+AWQ3MetqKiI448/npdeeqn1+osvvph//OMfVFRUkJ2d3aswe6PlHdov/ewZTjthYetci5Zlq4VpJOdaWPkEits/6CfrdTQ0hWiKK5iZE9pXHtVaVJGguYtj+W6N2nDfwu3u2im2ehQruQQ72ZMwpyzh4f37sPS0ifJw1N1cme42h47GEyx/eQvVgWiH4wkjzt9ee5sPt5SiO9OZNnsBV3x+CkDrpqQn5zZiN0N8Wmt2WgFMs4tkBXCA08UYj4aijY64605PG3t31bBLmBYPvbeddZ98TL4jwVElRZx/xsnoNjsJ0+KRlTvYt3MDR+XpxHU379RnMX9SHpe1bfQdwrzZ13BHW77tj+Ga59PtgtwML8phHj+SJEmDYTjPcRu2DTdIrhzz/PPPc/311zN58mQef/xxVq9ezdtvv906LL548WJWrlxJ2x+jubmZefPm0dzczI033ojNZuO3v/0tpmmyYcMG8vLyWs+97777uOaaa/jKV77CGWecwfvvv88TTzzBnXfe2bqSTW/DTFVLwvjRY69w+yVntFsYI1GzhRfbzrVo86Bfu7uWgng5bhFm8vjCdpXHloqliwjHz5jIV5ec0q5iWbljA3YrTFx1M25K6uH2dO26PXWcmufn/NkZ6K705NwLTe9+AZARrqtKXk8Ng4931XP3G9s5dcaY9hU80+LBlbv5x/q9ZLrtHY/3UAFsib+yLetYetoXepUu9u3cwNwxNs5ZOAV9zIzDNu5ajnUVf13FHXQff6k0+vqaN/uT51PJt5+tfJH/PPLTURP3/TEUef7vr7/Drr3VnLNoKrOPPGZU5M2lS5e26yyVpP6SaUoaSMO54YYYxiKRiLjxxhtFQUGBcDgcYuHCheK1115rd87nP/950dmPUVFRIb7yla+I9PR04fV6xdlnny127NjR6fc89NBDYtq0acJut4uSkhJxzz33CMuy+hVmKjZv3iwAseHTjR2Ord7TIL71x9Xivnd3CiNhtn5uJExx6z82iqPveEPc+o+N7Y4JIcRHO+vEyb9+V5z863fFR7vq2x3r7tqewu3p2vve3Sm+9cfVYvWehg4/S0/HR6PVexo6/A5TOf7Rzjrx5fs+6BDvPR3vb7roKn4Ox7gTovv46+5Yd/HX3bH+5M3+5HmZbwfOocrzRsKU8SNJkjSIWurnmzdvHupb6WBYN9xGu54SRlcPeiNhisc/3NNt5fHgClwq1/YUbk/Xdld56Om4dEBfK4At8XPxJZd2el1P6aKr+JFx1zt9bfT1J2/2J8/3lG/Pvfz/dXlcGhg95fmujNS8eckllwz1LUijjExT0kAazg23Yf2q5Gg3rIdipRHL5/O1zs2UpP6S6UkaaDJNSQNNpilpIA3n+vnIeSlekqSUPProo0N9C9IoItOTNNBkmpIGmkxT0uFCNtwkaZQ55phjhvoWpFFEpidpoMk0JQ00maakw8Ww3cftcBCLxQDYuXPnEN+JNJps3bqV3Nzcob4NaZSQ6UkaaDJNSQNNpilpILXUy1vq6cOJbLgNoU2bNgFw3nnnDe2NSJIkSZIkSZLUatOmTcyfP3+ob6Md2XAbQlOnTgXg2WefZebMmUN8N9JosHPnTs477zxeeOEFJk+ePNS3I41wMj1JA02mKWmgyTQlDbT//ve/LFu2rLWePpzIhtsQSk9PB2DmzJnDbtUaaWSbPHmyTFPSgJHpSRpoMk1JA02mKWmgtdTThxO5OIkkSZIkSZIkSdIwJxtukiRJkiRJkiRJw5xsuEmSJEmSJEmSJA1zsuE2hPLy8rj99tvJy8sb6luRRgmZpqSBJNOTNNBkmpIGmkxT0kAbzmlKEUKIob4JSZIkSZIkSZIkqWtyxE2SJEmSJEmSJGmYkw03SZIkSZIkSZKkYU423CRJkiRJkiRJkoY52XCTJEmSJEmSJEka5mTDTZIkSZIkSZIkaZiTDbchEIvFuPnmmxk7diwul4tFixbx5ptvDvVtSUNkzZo1fO9732PWrFl4PB6Ki4tZtmwZ27dv73Duli1bWLJkCV6vl+zsbC6++GLq6uo6nGdZFr/61a+YNGkSTqeTI488kmeeeabT7081TGnkuvPOO1EUhdmzZ3c49uGHH3LiiSfidrspKCjguuuuIxgMdjivN+VWqmFKI8u6des455xzyM7Oxu12M3v2bO69995258j0JKVqx44dXHDBBRQVFeF2u5k+fTp33HEH4XC43XkyTUkHCwaD3H777SxZsoTs7GwUReFPf/pTp+cOZb2pN2GmTEiD7oILLhC6rosbb7xRPPjgg+K4444Tuq6L999/f6hvTRoC559/vigoKBDXXnutePjhh8Xy5cvFmDFjhMfjEZs2bWo9r6KiQuTm5oqSkhLxu9/9Ttx5550iKytLHHXUUSIWi7UL85ZbbhGAuPLKK8VDDz0kzjrrLAGIZ555pt15vQlTGpkqKiqE2+0WHo9HzJo1q92x9evXC6fTKebNmyfuv/9+8cMf/lA4HA6xZMmSDuGkWm71Jkxp5Hj99deF3W4XixYtEr/97W/FQw89JG6++WZx0003tZ4j05OUqvLycpGZmSkmTJggfv7zn4sHH3xQfPOb3xSAOOecc1rPk2lK6syePXsEIIqLi8XixYsFIP74xz92OG+o602phtkbsuE2yFatWiUAcffdd7d+FolERElJiTjuuOOG8M6kofLBBx90yOzbt28XDodDfP3rX2/97Dvf+Y5wuVyirKys9bM333xTAOLBBx9s/Wzv3r3CZrOJa665pvUzy7LESSedJIqKikQikeh1mNLI9bWvfU2cfPLJ4vOf/3yHhtuZZ54pCgsLRSAQaP3s4YcfFoB4/fXXWz/rTbmVapjSyBEIBMSYMWPEl770JWGaZpfnyfQkperOO+8UgNi8eXO7zy+55BIBCJ/PJ4SQaUrqXDQaFVVVVUIIIdasWdNlw20o6029CbM3ZMNtkN10001C07R2BYYQQtx1110CEOXl5UN0Z9JwM3/+fDF//vzW/+fn54uvfvWrHc6bOnWqOOWUU1r/v2LFCgGIzz77rN15f/7znwXQrvcx1TClkWnlypVC0zSxcePGDg23QCAgdF1vN2IihBCxWEx4vV5x+eWXt36WarnVmzClkeP+++8XgPjvf/8rhBAiGAx2aMDJ9CT1xs033ywAUVdX1+FzVVVFMBiUaUpKSXcNt6GsN/UmzN6Qc9wG2fr165k6dSrp6entPj/mmGMA2LBhwxDclTTcCCGoqakhNzcXgMrKSmpra1mwYEGHc4855hjWr1/f+v/169fj8XiYMWNGh/Najvc2TGnkMU2Ta6+9liuuuII5c+Z0OL5p0yYSiUSH+Lfb7cydO7dDmkql3OpNmNLI8dZbb5Genk5lZSXTpk3D6/WSnp7Od77zHaLRKCDTk9Q7ixcvBuDyyy9nw4YNVFRU8Ne//pX777+f6667Do/HI9OU1C9DXW9KNczekg23QVZVVUVhYWGHz1s+27dv32DfkjQMPf3001RWVvK1r30NSKYboMu04/P5iMVireeOGTMGRVE6nAcH0lhvwpRGngceeICysjKWL1/e6fGe4r9tWZRqudWbMKWRY8eOHSQSCc4991zOOOMM/v73v/Otb32LBx54gMsuuwyQ6UnqnSVLlrB8+XLefPNN5s2bR3FxMRdccAHXXnst99xzDyDTlNQ/Q11vSjXM3tL7dJXUZ5FIBIfD0eFzp9PZelw6vG3dupVrrrmG4447jksvvRQ4kC56SjsOhyPlNNabMKWRpaGhgR//+Mfcdttt5OXldXpOT/HftiwaqDQly7eRKRgMEg6Hufrqq1tXkfzyl79MPB7nwQcf5I477pDpSeq1iRMn8rnPfY7zzz+fnJwcXn75Ze666y4KCgr43ve+J9OU1C9DXW86VPV92XAbZC6Xq9NRjJbXTVwu12DfkjSMVFdXc9ZZZ5GRkcFzzz2HpmnAgXSRStpJNY31JkxpZPnRj35EdnY21157bZfn9BT/beN+oNKUTE8jU0u8XXjhhe0+v+iii3jwwQf56KOPcLvdgExPUmr+8pe/cNVVV7F9+3aKioqAZGeAZVncfPPNXHjhhbKMkvplqOtNh6q+L1+VHGSFhYWtQ61ttXw2duzYwb4laZgIBAKceeaZ+P1+XnvttXZpoWVovau0k52d3dqzU1hYSHV1NUKIDufBgTTWmzClkWPHjh089NBDXHfddezbt4/S0lJKS0uJRqMYhkFpaSk+n6/H+D84/aVSbvUmTGnkaIm3MWPGtPs8Pz8fgMbGRpmepF657777mDdvXmujrcU555xDOBxm/fr1Mk1J/TLU9aZUw+wt2XAbZHPnzmX79u00NTW1+3zVqlWtx6XDTzQaZenSpWzfvp1//etfzJw5s93xcePGkZeXx9q1aztcu3r16nbpZu7cuYTDYbZs2dLuvIPTWG/ClEaOyspKLMviuuuuY9KkSa1/Vq1axfbt25k0aRJ33HEHs2fPRtf1DvEfj8fZsGFDhzSVSrnVmzClkePoo48GkmmrrZY5Gnl5eTI9Sb1SU1ODaZodPjcMA4BEIiHTlNQvQ11vSjXMXuvTWpRSn3388ccd9hqJRqNi8uTJYtGiRUN4Z9JQSSQS4pxzzhG6rouXX365y/Ouvvpq4XK52m0Z8dZbbwlA3H///a2fVVRUdLl3yLhx49rtHZJqmNLIUVdXJ55//vkOf2bNmiWKi4vF888/LzZu3CiEEGLJkiWisLBQNDU1tV7/yCOPCEC8+uqrrZ/1ptxKNUxp5Fi3bp0AxEUXXdTu8wsvvFDoui4qKyuFEDI9Sak7++yzhd1uF9u2bWv3+XnnnSdUVZVpSkpZd9sBDGW9qTdh9oZsuA2Br371q637iDz44IPi+OOPF7qui5UrVw71rUlD4Pvf/74AxNKlS8WTTz7Z4U+L8vJykZOTI0pKSsS9994r7rrrLpGVlSXmzJkjotFouzBvuukmAYirrrpKPPzww+Kss84SgHj66afbndebMKWRrbMNuD/55BPhcDjEvHnzxP333y9++MMfCqfTKU4//fQO16dabvUmTGnk+Na3viUAsWzZMrFixQrx1a9+VQDif//3f1vPkelJSlXLHpP5+fnijjvuECtWrBBnnnmmAMQVV1zRep5MU1JXfv/734vly5eL73znOwIQX/7yl8Xy5cvF8uXLhd/vF0IMfb0p1TB7QzbchkAkEhE33nijKCgoEA6HQyxcuFC89tprQ31b0hD5/Oc/L4Au/7S1efNmcfrppwu32y0yMzPF17/+dVFdXd0hTNM0xV133SUmTJgg7Ha7mDVrlnjqqac6/f5Uw5RGts4abkII8f7774vjjz9eOJ1OkZeXJ6655pp2PdEtelNupRqmNHLE43Hxk5/8REyYMEHYbDYxefJkcc8993Q4T6YnKVWrVq0SZ555pigoKBA2m01MnTpV3HnnncIwjHbnyTQldWbChAld1pv27NnTet5Q1pt6E2aqFCEOmjUnSZIkSZIkSZIkDStycRJJkiRJkiRJkqRhTjbcJEmSJEmSJEmShjnZcJMkSZIkSZIkSRrmZMNNkiRJkiRJkiRpmJMNN0mSJEmSJEmSpGFONtwkSZIkSZIkSZKGOdlwkyRJkiRJkiRJGuZkw02SJEmSJEmSJGmYkw03SZIkSZIkSZKkYU423CRJkiRJkiRJkoY52XCTJEmSRo1vfvObTJw4cahvo9VPfvITFEVBURS8Xu+gf//cuXNbv//ss88e9O+XJEmSBo4+1DcgSZIkSd1RFCWl8959991DfCd99+STT2Kz2Qb9e++66y58Ph/XX3/9oH+3JEmSNLBkw02SJEka1p588sl2/3/iiSd48803O3w+Y8YMHn74YSzLGszbS8k3vvGNIfneL37xiwD86Ec/GpLvlyRJkgaObLhJkiRJw9rBjZ6PP/6YN998c8gaQ5IkSZI0FOQcN0mSJGnUOHiOW2lpKYqi8Otf/5oVK1ZwxBFH4Ha7Of3006moqEAIwfLlyykqKsLlcnHuuefi8/k6hPvqq69y0kkn4fF4SEtL46yzzuKzzz7r171OnDiRs88+m/fee48FCxbgcrmYM2cO7733HgD/+Mc/mDNnDk6nk6OPPpr169e3u766uprLLruMoqIiHA4HhYWFnHvuuZSWlvbrviRJkqThSY64SZIkSaPe008/TTwe59prr8Xn8/GrX/2KZcuWcfLJJ/Pee+9x8803s3PnTn7/+99z44038thjj7Ve++STT3LppZdyxhln8Mtf/pJwOMz999/PiSeeyPr16/u1GMrOnTu56KKL+Pa3v803vvENfv3rX7N06VIeeOABbr31Vr773e8C8POf/5xly5axbds2VDXZ53r++efz2Wefce211zJx4kRqa2t58803KS8vH1YLtEiSJEkDQzbcJEmSpFGvsrKSHTt2kJGRAYBpmvz85z8nEomwdu1adD35OKyrq+Ppp5/m/vvvx+FwEAwGue6667jiiit46KGHWsO79NJLmTZtGnfddVe7z3tr27ZtfPjhhxx33HEAzJw5kzPOOIMrr7ySrVu3UlxcDEBWVhbf/va3+fe//83ixYvx+/18+OGH3H333dx4442t4f3v//5vn+9FkiRJGt7kq5KSJEnSqPfVr361tdEGsGjRIiA5f66l0dbyeTwep7KyEoA333wTv9/PhRdeSH19fesfTdNYtGhRv1eynDlzZmujre19nXzyya2Ntraf7969GwCXy4Xdbue9996jsbGxX/cgSZIkjQxyxE2SJEka9do2goDWRtz48eM7/bylMbRjxw4g2ZDqTHp6+pDcl8Ph4Je//CU33HADY8aM4dhjj+Xss8/mkksuoaCgoF/3JEmSJA1PsuEmSZIkjXqapvXqcyEEQOvWAk8++WSnDaK2o3WDeV8AP/jBD1i6dCkvvPACr7/+Orfddhs///nPeeedd5g3b16/7kuSJEkafmTDTZIkSZK6UFJSAkB+fj6nnnrqEN9NRyUlJdxwww3ccMMN7Nixg7lz5/Kb3/yGp556aqhvTZIkSRpgco6bJEmSJHXhjDPOID09nbvuugvDMDocr6urG4K7gnA4TDQabfdZSUkJaWlpxGKxIbknSZIk6dCSI26SJEmS1IX09HTuv/9+Lr74YubPn88FF1xAXl4e5eXlvPzyy5xwwgn84Q9/GPT72r59O6eccgrLli1j5syZ6LrO888/T01NDRdccMGg348kSZJ06MmGmyRJkiR146KLLmLs2LH84he/4O677yYWizFu3DhOOukkLrvssiG5p/Hjx3PhhRfy9ttv8+STT6LrOtOnT+fZZ5/l/PPPH5J7kiRJkg4tRbSd6SxJkiRJ0oD5yU9+wk9/+lPq6upQFIWcnJxB/X6/308ikWD+/PkceeSR/Otf/xrU75ckSZIGjpzjJkmSJEmHWF5eHhMmTBj07128eDF5eXlUVFQM+ndLkiRJA0uOuEmSJEnSIbJ79+7WTbN1XWfx4sWD+v2rVq2iubkZSDYejzrqqEH9fkmSJGngyIabJEmSJEmSJEnSMCdflZQkSZIkSZIkSRrmZMNNkiRJkiRJkiRpmJMNN0mSJEmSJEmSpGFONtwkSZIkSZIkSZKGOdlwkyRJkiRJkiRJGuZkw02SJEmSJEmSJGmYkw03SZIkSZIkSZKkYU423CRJkiRJkiRJkoY52XCTJEmSJEmSJEka5mTDTZIkSZIkSZIkaZiTDTdJkiRJkiRJkqRh7v8DMLCZOsx6jLMAAAAASUVORK5CYII=\n", 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" ] @@ -8648,7 +8684,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -8659,12 +8694,12 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 26, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -8688,12 +8723,12 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 27, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -8722,7 +8757,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -8731,12 +8765,12 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 28, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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8efMwm8387W9/Izk5mT179jBhwgR27tzJ/Pnzeeyxxzh8+DCTJk1iy5YtJz2vgwcPYjabueKKK3j22Wfx8/Pjuuuu49tvvz2Fu+1ddPQZCATHInQi8AahE4E3CJ2cGSQlaYGR/2HNUKK5GW9XHPuOhy/qRPSZOlswGsFsRl6+XAuYLBYwm8FkahtIybK2/Th/Fegu/vrXvyLLMj/88AMJCQkAzJ49myFDhrQbe+DAATIzMxk6dGjLtlmzZtHY2MimTZtaXOxuuukmBg8ezPz589mwYcNJzctqtfLJJ59w9dVXA3Dbbbdxzjnn8PDDD3PZZZed1Dl7G6mpqT09BUEvQOhE4A1CJwJvEDo5M5BluCTJyuBaCxXNbn5pmpufzWhiaKYFZ0EpV4Ra6BNn5qefTFRVQUQEpKdrWS0OHoRO1vj7ok5EZupswmTCfc01mtKbA6qvvmofSJl+fStKRVH473//y8yZM1sCKYCBAwdyxRVXtBt/0UUXtQmkFEVhzZo1zJw5s40deHx8PL/73e/YtGkTNTU1JzW3hIQEZs2a1fI6LCyMm266ie3bt1NcXHxS5+xtGDrqlCcQHIPQicAbhE4E3iB0coZgszE628KgFM3i/CPVzLbao4595XkNjC76P+KqDnDwGQt/vtXG/ffD7bfDVVfByru+QbnjLnj11Q5P74s6EcHUWUZdQoIWMDUHVFu3nvZACqC0tJSGhgYGDhzYbl9H21JSUtq8Lisrw263M3jw4HZjhwwZgsfjIS8v76TmNnDgwHZrrExN70vr9VVnMhkZGT09BUEvQOhE4A1CJwJvEDo5QzAa0V00gWEjtF5RA6eZCAjQHPv6NhwknS3U60JIyvuRQ0UBHKk34nJBTQ2E/PQNcctf4MieWpTPv9QyVMfgizoRZX5nGdHR0dCnD4wcqQVSzYwcedoCqZPhVP4S0ZH5BGjZLUHH3HbbbT09BUEvQOhE4A1CJwJvEDo5g5g0Cd3w4YwxGjlf0ezSGxrAYBhE9Q0D6Z/zC0VqPBc7v+GXsnP5rzyVS5VvuNfzAmGeMiJdeexxzmZEB6V+vqgTkZk6y8jLy9PWSG1v667C9u2du/z9CsTGxhIYGEhWVla7fR1tO5aYmBiCgoI4cOBAu3379+9Hp9OR1LSqMTIyEoCqqqo243Jzczs8d1ZWFqqqttlmbXpvkpOTTzi3M4F58+b19BQEvQChE4E3CJ0IvEHo5Ayjae29LGuGFEOGQEL9QZQDWRR64olTi4hUynjA/QJ/cT3OA+4XiFTKSFDzKPTEo+zPwrWnfWbKF3UigqmzjJTGxrZrpEaPbruG6jQFVLIsc+mll/LZZ59RWFjYsj0rK4uvv/7aq+OnTJnC559/3qb0rqSkhA8//JDx48cTFhYGHF2s+P3337eMq6+vZ/ny5R2eu7CwkJUrV7a8rqmp4d133+W8886jT58+XbrP3kpn741A0BqhE4E3CJ0IvEHo5Mwno3IQX7qmEoiDUmLpSx5GtYzxnu8xqmX0JY9SYgnEwReuqWRUts9M+aJORDB1NmG1YluypO0aqenT266hOo0B1RNPPIHb7eY3v/kNL7zwAs8++ywXXXQRaWlpXh3/zDPP4Ofnx/jx41m4cCEvvPACF154IU6nkxdeeKFl3JQpU+jXrx+33XYbL7zwAi+99BLp6enExMR0eF6TycRtt93Go48+yquvvsr48eMpKSnhueee65b77g3MmDGjp6cg6AUInQi8QehE4A1CJ2cYTeudXC7YtEnzO8v42gZOJz9wIUHYacBAEkdI5jBJHKEBA3oa+YELkZxOqg+1b9PjizoRwdTZgs0GFgvGiIj2ZhMmU/uA6jT0mRo1ahRff/01kZGRPPbYYyxdupSnnnqKSy65hMDAwBMeP2zYMDZu3EhaWhrPPvssTz75JP3792fdunWMHTu2ZZy/vz8rV64kNTWVxx57jL///e/88Y9/5J577unwvIMGDcJisbBq1SoeeeQRGhsbsVgsTJ06tdvu3df58ssve3oKgl6A0InAG4ROBN4gdOJjNH0PVBTIyYF9+7TfLcvNj/c98dVXUe64i5V3fcOMGZpT3/33w/NvGfnAbUZBRwh1xFCGjEI41cgoRFLJIZKxMph/e8zk1LZv0+OLOhEGFGcLRiNMmED1V18Rfscd7c0mmgMqiwUmTDgtfaYALr74Yn755Zc222bOnEnfvn1bXh+7fqk1I0eOZPXq1Se8zvnnn8/mzZvbbb/55ps7HD9lyhSmTJlywvOeqcybN49XXnmlp6ch8HGETgTeIHQi8AahEx/i88/x7NjFlmQzK/eYyMkBjwciIyE1FS4L38LI0jXoLpoAkya1PfbgQZTPvyRnn4O4zS8Qpgd7xFT8/bVALJnDjOFnDDQgoaLHRQ3hhFKDkwAGkMMHJJClMxEX135qvqgTEUydTUyaRMCgQZCY2PF+kwnuvvu0BVIADQ0NbZz6Dh48yKpVq5gzZ85pm4OgPXPnzu3pKQh6AUInAm8QOhF4g9CJj/D55yiv/p2M2qHsKLSwRTVTEGxCrweDAQwbvyGw+gVyBiWRDOiGD2/7vXHQIH4IncqA8iUEEsv96gu8WgXr/Kcy3v4Nj/MwfSlAxo2KRDURODCgIhFKDS78+QMfUib1RVXbVwT5ok58tsxvz549XHfddQwYMICgoCCio6OZOHFih+m9ffv2cfnllxMSEkJUVBQ33ngjZWVlbcbs37+f+fPnc9555xEaGkp8fDxXXnklW1vbgx+H9evXI0lShz8dZTx8lbqAgOMPOI2BFMCAAQN49NFH+de//sVf/vIXxo0bh16vZ/78+ad1HoK2tDbrEAg6Q+hE4A1CJwJvEDrxAWw2PDt2kVE7FHXPXvRVpcxWLYwItKLXw/Cib/h9/gs46xUaDuaxI25Ku++NriIb9m37qfYEE+spQu+s5e7aF5hX+TgPNzxBKocw0IAOFScBOAgkh/7UE0QJccRSSgxlPCy9QFpAezc/X9SJz2amcnNzqa2tZc6cOSQkJGC32/nkk0+46qqreOONN7jjjjsAyM/PZ+LEiYSHh7Nw4ULq6up48cUXyczMJCMjA71eD8Bbb73F0qVLueaaa7j77ruprq7mjTfeYNy4caxevZpLL73Uq3ndd999jBkzps22jprM+iqyLPf0FNpw+eWX8+9//5vi4mICAgK44IILWLhwIYM66C0gOH0028kLBMdD6ETgDUInAm8QOvEBjEa2JJvZUWhBL8G5+r0ckeHKeguV/rFMtq9A8Sg0IvNO+HwSq8dybpOnWTO//AJKRTVBqp1agomjCFWF8er3yCjoUNDhwYMOCZUtpLNfGsYANYsL+ZFSYkkij+yIC0ga0f67oC/qxGeDqWnTpjFt2rQ22+655x5GjRrFyy+/3BJMLVy4kPr6erZt20a/fv0ASE9P57LLLuOdd95pGXfDDTfwxBNPEBIS0nK+W2+9lSFDhvDEE094HUxNmDCBa6+9tjtusUdoDi59hWXLlvX0FNrQ2mb9bCaxs1JQgaAVQicCbxA6EXiD0EnPoyiwco+JLaqZ2WEWjsjQ376XsEYbI13foUMFvcw/guaTGTyVUdlaQ97WLTgrKyFX6YuRAmIpQYeHBAqoIgojpfjjbgqndByhL7nyQHbrR6NTZHRuuIAfKZKSOC8kiyTHQaBtQOWLOvHZMr+OkGWZpKSkNs1XP/nkE6ZPn94SSAFceumlmEwmVqxY0bJt1KhRbQIpAKPRyIQJE9i3b1+X5lFbW4vb7T65m+hhqqure3oKgl7AN99809NTEPQChE4E3iB0IvAGoZOeJy9Pc+wrCDaxNtpMpT6WSv84ol2F6FDxILEudjY7Yqdit0NFBTQ0tD1HtZ+RxepcNjMWJwEYqSCMWmIpIZgGZBQk4DDJrOFyPgy4hf8GTufLIDMl4YPZG34h0YF1yBeMRT6nfWbKF3Xi88FUfX095eXlZGdn88orr/D1119zySWXAFBQUEBpaSmjR49ud1x6ejrbt28/4fmLi4uJjo72ej633HILYWFhBAYGMnnyZK/XXPkKcR1ZowgEx/Dggw/29BQEvQChE4E3CJ0IvEHo5FeiCxbnDQ2aa59eD4f8TFT5xxLlKmrZX6GPJ7KxlAFuK42NoNNpphStCQ4GKyZ2MoJg6lHQ4Y8LAH9ceNDhJIADDGEJc9GdY2LcOIgaZ2JPmhln8mAqL7ySvoMMHdqv+6JOfLbMr5kHH3yQN954AwCdTsfVV1/Na6+9BkBRkfYBx8fHtzsuPj6eiooKnE4nAZ2YLmzcuJGffvqJv/zlLyech16v55prrmHatGlER0ezd+9eXnzxRSZMmMCPP/7IyJEjj3t8aWlpO1OMrKysE163u8nJySE1NfW0X1fQu7j55pvbZHYFgo4QOhF4g9CJwBuETroJmw2MRhQFyv6zHmnTRrammtnZYCI3F/xrbDSGGUlJgYv7WhmdbWmxODcYNPtzg0Ezm5hkX9GSkdICqRJqXEYuabBgk8ykpJhISmp7+epqmMI3/IEPqSSSSCqpIbyNY189wcRRQqp0GEeYZoGu18OAASaS+poZlNU0pw5M0XxRJz6fmbr//vv59ttvWb58OVdccQWKouByaRFuQ1NusaNgqbnpa8Ox+ccmSktL+d3vfkdKSopXznEXXnghH3/8MbfeeitXXXUVjzzyCJs3b0aSJB599NETHr9kyRLS0tLa/MycOROATZs2sWHDBhYtWkRFRUWLLfimTZsAyMvLw+FwUF5eTmVlJfX19RQWFqIoCtnZ2YBmKQ6aIYfdbsdms2Gz2bDb7eTn57eMSU1NJTs7G0VRKCwspL6+nsrKSsrLy3E4HOTl5bU53+HDh3G73RQXF1NbW0t1dTWlpaW4XC5yc3PbjM3NzcXlclFaWkp1dTW1tbUUFxfjdrs5fPhwm7HdeU/AWX9P9fX1uFwuFi1axIYNG1i9ejWLFy+moKCAu+66CzjaNfyuu+6ioKCAxYsXs3r16g611/zvZt68eWRlZfH222+zcuVKMjIyePrpp7Hb7cyePbvNeRcsWEBmZiYffvghH374IZmZmSxYsKDNmNmzZ2O323n66afJyMhg5cqVvP3222RlZTFv3rw2Y+fMmUNFRUW33VPzWHFP3XdPK1asOOPu6Uz8nHr6npqfJ2fSPZ2Jn1NP39OKFSvOuHs63Z/Tv37/ezyvLcE8cjL/eMLGh/9zD1997mDX//sf1rz2McXfL2bkT38kdu8HrHntZvJftvCvf76HZ8NG7jabCQ6uID9/ESNLF3F75cM47UdoVN18pCrkBg9hmz2bfvV70ZVbuM7zL0KLHufbb9ve05olM5nPC4SwjUgqKUWHHX9qaMSOShGRuGlAppE/cyP3Xn6QnJwZPPooVFYuIHCEk0/7xPJhYWGHnxPwq39Ozd+/vUVSj9cR1QeZMmUKVVVVbNmyhW3btjFmzBjeffddbrzxxjbj5s+fz6JFi3A4HO2Crfr6eiZPnozVamXTpk2kpaWd9HxuuOEGPv30U+x2+3Gd8jrLTM2cOZPdu3czbNiwdsccOnQI0OzDu4uDBw8Kp7wzkO7WyowZM3yyy7jAtxA6EXiD0InAG4ROThGbDc9rS9i9UyErR+brUDMeD4zYZ0F1K4SrlfjrwT86kqTQStz+QZRUBSAHyCQ9aGbM700A/PL6FgKeWoCzXqHRI/N62Hx2xE5lgNvKJeUWAmtKGaLuRZc2lPTpsejuadufNDsbvh2zgCsr36OeYAJwUkIchxlACoeIowQnAQRTz/9F3shlPy+kKwVTp0Mne/bsIS0trdPv58fi85mpY7n22mv5+eefsVqtLeV9zeV+rSkqKiIqKqpdIOVyubj66qvZtWsXn3/++SkFUgBJSUm4XC7q6+uPOy42NpZhw4a1+ekJS3URSAm8QfwHTeANQicCbxA6EXiD0MkpYjSyNdVMVo6M4lQwY8GtwFfBZhKDKzlX2sUg+y6Ci7OoqwOPfwBRMVrQ9V2+SVtDZbNxXukaDIOSCAiW+TBpPpnxU3G5YJfDxArJjCsyFmnYUMaE7EV33oh2pXjJoTZS4+uplKIIlJyU6+LYoR/L58G/Y4d+LOW6OAIlJ5VSFAMT6kkObb8u6nj4ok56XTDVXC5QXV1NYmIiMTExHZpAZGRkcN5557XZ5vF4uOmmm1i7di0ffvghF1100SnP59ChQwQGBrZzCvRVmkvJBILj0ZxWFwiOh9CJwBuETgTeIHRyaigKrM0z8XWomagYGbdTYVyOhXNkK0jaGH9/qPBEUuyIREFm73AzjSkmDh3SnPwwGtFdNIHkS1Jx/nUhCTdP5fzzYehQOP98GHeTiZHPmhk7Ixb5/vvgt79tNw9ZhnOj8onW12CT49jmP5a3DXP5NmA6bxvmss1/LDY5jmh9DSOi8ulq+1Nf1InPGlCUlpYSGxvbZltjYyPvvvsuBoOBoUOHAnDNNdewfPly8vLySGpaBbd27VqsVmtL7WQz9957LxaLhTfeeIOrr76602uXl5dTXl5Ov379CAoKAqCsrIyYmJg243bu3MkXX3zBFVdcgU7XO+LSqKionp6CoBdwww039PQUBL0AoROBNwidCLxB6OTUaLY1b0wxsTfUTHKGBcmjMNyxlXp9JOUBidT5RWJXjEgNkB02EpvRhMENDkcri/NJk9ANH875RiPnKtp5Gxo0U4qkJJBlE9ju7tAcopno1HDKSxI54hzFSt1cyiUTYSqUSyZWqnOJ80BSwDaiB4R3+T59USc+G0zdeeed1NTUMHHiRBITEykuLuaDDz5g//79vPTSSy2ZoAULFvCf//yHyZMn86c//Ym6ujoWLVrE8OHDueWWW1rO9+qrr7JkyRIuuOACgoKCeP/999tcb9asWQQHBwPw2muv8eSTT7Ju3TomTZoEgNlsxmAwcOGFFxIbG8vevXt58803CQoK4rnnnjs9b0o30NDQ0BIgCgSdkZmZyfDhw3t6GgIfR+hE4A1CJwJvEDo5NRoawOXSgh6b0URA3EikI1vxeCCs0YYE1Pgb0ama/XlCyXacNhM5DSYCAo6xOG8KlGS5bUPeY/d3iNGI7uabiI77hr4jbmHSERPGzKMB2fDhJvr2m0v0rmXorph6/HN1gC/qxGeDKbPZzNKlS3n99dex2WyEhoYyatQonn/+ea666qqWcUlJSWzYsIEHHniARx55BL1ez5VXXslLL73UZr3Ujh07APjpp5/46aef2l3v8OHDLcFUR8ycOZMPPviAl19+mZqaGmJiYrj66qv561//2iNrnwQCgUAgEAgEAtACFb1eC1qMNiupNdspMAA2G8nSbgCq/Y1sCLyMoY7t+EsKQzMt7FLNDJjW3uK8tcV6++zU0f0d0pTdGmM0cn5n2a3LH+pyIOWr9Do3vzOJE7mF/Bpufna7naCgoM7/cQiOi6qqOBwODMd2qethulsrvviXH4HvIXQi8AahE4E3CJ2cGooCL7wAh1ZbuV6yIKPgKqnEVWwjxlWAvz9kB4/gTb+5JCTCjf4WKsuVdm5+AHz+OZ4du9iSbGblHhM5OVo2KzISUlPhsvAtjCxd09Kf6nRyOnRyxrv5CU6NsrIKNmzQ/sE9++zR34sWwYYNrTpinwaeeOIJJEkiKyuLm2++mYiICMLDw7nllluw2+0t49xuN08//TSpqakEBASQnJzMggULcDqdbc6XnJzM9OnT2bRpE+np6QQGBjJgwADefffddtfetWsXF110EQaDgb59+/LMM8+wbNkyJEkiJyen3Tm/+eYbRo8ejcFgaGkifejQIa677jqioqIICgpi3Lhx/N///V+b67zzzjvtzgmwfv16JEli/fr1LdsmTZpEWloa27Zt48ILL8RgMJCSksI///nPk3yHT55///vfp/2agt6H0InAG4ROBN4gdHJqyDJckmTliloLFWUKUqOT0DCo7zOQrKAR7GIEBfWRTK+34O8HFszIATKDUhRGZVm0TBPA55+jLHqJnf+xsv1RCz8ss7JhA/zwg/Y9sWDZNwT/9c/kf7kdz4aNR487TfiiTny2zE/Q/SgKbNrUl//+F0pLISZGy0o1NMDGjXDgABQUgNl8erNUs2fPJiUlhWeffZZffvmFt956i9jYWJ5//nkA/vjHP7J8+XKuvfZaHnzwQbZs2cKzzz7Lvn37WLlyZZtzZWVlce2113LbbbcxZ84c3n77bW6++WZGjRrV8teFgoICJk+e3NJwOTg4mLfeeqvD5s8ABw4c4IYbbuDOO+/k9ttvZ/DgwZSUlHDhhRdit9u57777MBqNLF++nKuuuoqPP/6YWbNmndR7UVlZybRp05g9ezY33HADK1as4H/+53/Q6/XceuutJ3XOk2HhwoWn7VqC3ovQicAbhE4E3nDG6uRUyuW6eJ3R2RYMKQoHD8u873cLqaGFDPFs5IvouRQUwBU1FsKCFWbYLeRMu5ukwWaGZVm0DFPTOZRPP6d6xyFS63eQxyQukaBcNWPDSErxVn4vPUE0WQRXNFCQ0p+k01yq54s6EcHUWcSmTfDpp9X4+YUzahS0NiDs108Lpr79Fvr2hYkTT9+8Ro4cydKlS1te22w2li5dyvPPP8/OnTtZvnw5f/zjH/nXv/4FwN13301sbCwvvvgi69atY/LkyS3HHjhwgO+//54JE7QHw+zZs0lKSmLZsmW8+OKLADz//PNUVlbyyy+/tNjn33LLLZ324MrKymL16tVMnTq1Zdu8efMoKSlh48aNjB8/HoDbb7+dESNG8MADD/Db3/72pBweCwsLeemll3jggQcAzYhl7NixPProo9x44434+/t3+Zwng2ieKPAGoROBNwidCLzhjNTJ+vV4Nmxka6qZtXlauZzLpa1tSkmBi/taGZ1t6Z5yuSZb82FsxHG1mYH5Jg4dMpEfORy/MCMXTYOBgWZGZ1tQx09g+nVGZNmoOfNlZuJ5bQk7Yqfg920+g+tLAZjEOjwqRFFOCocZSBaxainhVNGo+KHfuBZl/0Hkc05fD1Nf1Iko8ztLUBT48UdwOMIZPLhtIAXa68GDtYzVTz+d3nK/u+66q83rCRMmYLPZqKmpYdWqVQAtwUUzDz74IEC7srqhQ4e2BFIAMTExDB48uGVNEcDq1au54IIL2vQhi4qK4ve//32H80tJSWkTSAGsWrWK9PT0lkAKICQkhDvuuIOcnBz27t17otvuED8/P+68886W13q9njvvvJPS0lK2bdt2Uuc8GXztQSXwTYROBN4gdCLwhjNOJzYbng0b2b1TIf9lC4dWW3E6ITAQnE7I/tpK/ssW9uxSuq9cbtIkdPfczZjfm3joIXj0UZj7uJFHH4X58+HKeSbinrybPtdPalOB5NmwkX0ZtRQs+Yzq8kYa8UOHhwCcXMparuILxvAzyeQQSSXgQUXHrsZzKGg4vS13fFEnIpg6S2juPxAYWNMukGpGp9NK/1qat50m+vXr1+Z1ZGQkoJW85ebmotPp2jkm9unTh4iICHJzc497rubzVVZWtrzOzc3t0IGxM1fGlJSUdttyc3MZPHhwu+1Dhgxp2X8yJCQktHOVNJm0RaHHrrv6NZk9e/Zpu5ag9yJ0IvAGoROBN5xxOjEa2ZpqJitHRnEqXC9ZGBVqJS4ORoVqJhGKUyvJ2zbQ3H3OdsfYmg8Zov1uCZ6OvY7RyAFXMvLWzSjFZfg1OqgkChUJGQUDDSSRRyylBOIAVDz4UUcQq+yTqNSd3jI/X9SJCKbOEpr7D0RHhxx3nMGgjWtp3nYakDtZoNXaaFKSpG47V1c5Fee+zuatnM7U30nwzjvv9PQUBL0AoROBNwidCLzhTNOJosDaPBNfh5qJipGRURi224LJ+hXDdmtue1ExMl+Hmvku3/TrVQQ1ZbwURfuj+r592u/m6yn7D+JcvQ5XrZO+1XtwoCeUGhowAB4kVPxQkPGgQwUk3OjYyUjCXTayM06vAYUv6kQEU2cJzf0HKisdxx3X0KCN8xXn7/79++PxeDh48GCb7SUlJVRVVdG/f/+TOmdWVla77R1tO945Dhw40G77/v37W/bD0SxbVVVVm3GdZa4KCwupr69vs81qtQKas+Dp4qWXXjpt1xL0XoROBN4gdCLwhl6lkxMEKNhsLRVBjSkm9g4345FkdKpCQuFWdKqCR5LZO9xMY4qpeyuCWs2t+KP1lD38Iv/3ipVnn4UFC+DZh2wsWKC5OWe8b6X2ucXUFVRT4w5CanSRyiGKiEfGjYRE6z8Jq03/W0M4IdTxtWcKNk5vZsoXdSKCqbOEpCQtzVtdrcfj6XiMxwNlZTBgAO2bt/UQ06ZNA+DVV19ts/3ll18G4Morr+zyOadOncpPP/3U0sgZoKKigg8++KBL88rIyGjTALq+vp4333yT5ORkhg4dCkBqaioA33//fcs4RVF48803Ozyv2+1usV4HcLlcvPHGG8TExDBq1Civ53eqHLtGTCDoCKETgTcInQi8odfoZP16PK8tIeN9a4dtZjLet+J5bQnShvW4XNofp21GE8XxI9ucpjh+JDajqXsrgtavx7PoRTLet/L3v9rYt+Bd8j/aSOFfFvPly1Zyv7UybtOLqOvWs/5NK4V/WUztuq3U1sF+zyDqdGHYCcKIDT8UdKg01/VoOSntR0bhIIOoliLR67th3l3AF3Ui3PzOEmQZLrwQMjMVDhzwa2dC4fFobn6xsXDBBb7TwPfcc89lzpw5vPnmm1RVVXHRRReRkZHB8uXLmTlzZhsnP2+ZP38+77//Ppdddhn33ntvizV6v379qKio8Kqk8JFHHuHf//43V1xxBffddx9RUVEsX76cw4cP88knn7Q4+Q0bNoxx48bx6KOPUlFRQVRUFB999BFut7vD8yYkJPD888+Tk5ODyWTCYrGwY8cO3nzzzdPm5AeafbxAcCKETgTeIHQi8IZeoZPWphKfWzgUqmWWmtvMZH9txVSr2ZMnVm0k0jOcigYjRpuVPkXb25yqT9F2bEYTOQ0mAgK6oSLIZsOz/F3KfrBS+JGdH5TfMai0mgGuPIbTyN32SiQgVTpEot1KhS6aJM8OdFIxTjWO5fJtzGUxA137CacGPxpbAigVOLpYQiWEesKp4nqdhZSwu+E0Zqd8UScimDqLGD8e9u93sXlzANu2te0zVVamBVKXXQa/+U1Pz7Qtb731FgMGDOCdd95h5cqV9OnTh0cffZS//vWvJ3W+pKQk1q1bx3333cfChQuJiYlh7ty5BAcHc9999xEYGHjCc8TFxfHjjz/y8MMP849//AOHw8GIESP48ssv22XLPvjgA+68806ee+45IiIiuO2225g8eTKXXXZZu/NGRkayfPly7r33Xv71r38RFxfHa6+9xu23335S93qytDbsEAg6Q+hE4A1CJwJv6BU6aTKVyP9cM4+4PszC3lAzNqMJo83KUMlCRZOpRP1vzcQUGKldrW3XoZX2FcePpE/RdnSqwtBMC7tUMwOmmbqlIqgsqxpPbh5Jnkau1DnQu2rRodCfXPqjLS/QqR7i3MXUEE4spaioeCRABw4pED0udCgtWSgVUNDhxh9/nNBkTHEx69jvfz5Rg05vmZ8v6kRST2VlvuCU2LNnD2lpaezevbuloWxrmu28BwwY0G3XrK93sG1bID/9pLn2Nfc7GDBAy0j95je+k5U63dx///288cYb1NXVdWpk8WsyadIkysvL2b17d5eP7W6tZGVldepuKBA0I3Qi8AahE4E3+LROmhrrulzwl79A/ndWfu9nIShAQdXJVESlElWRjU5VUJD5SDUzcJqJiX2sFP1NC7yiYrQ1Ui2BV6aFijIFOUAm6UEzY35vOqUpKqU2tqffQZ/cLYBECbFIKIRSRx+K0eMCwI2Mg0AcGPCgo4Q49jKMUr9EoqUyZjV+RAh2pKZclAeoIRwZBZAw0IAODw705AWnEfrlh/SdfPr6TJ0OnZzo+/mxiDVTZxkVFWVMnEhL/4H587XfDz2kNeo9WwKphmOKk202G++99x7jx4/vkUDK11i8eHFPT0HQCxA6EXiD0InAG3xWJ63WSP3lL/Dll5BRZeKtWjM5+TJKUSnnb/sXUZXZbUwlSvbaGLzDwqAULWD6SDWzrdZESQlsqzXxkWpGDpAZlKIwKstyyn2mjhyBPdV9KSEOFZVYSgmllgiq0OFBRkFuyjjpceGPmwqMqEgEUU8IdYxQdqDgB6ioSChIOAlExoMNIypQSygKOnSAHBVG/LDT22fKF3UiyvzOMpKa8sjN/QfOVi644AImTZrEkCFDKCkpYenSpdTU1PDYY4/19NR8gldeeaWnpyDoBQidCLxB6ETgDT6lk6ZMlFJqo/rzjezbrZC3wkK+wUxjo4lY2cZhfxPZZbEMs3+HPVAljFyyUqdophJuqHQYqT1vAsMiNuK42szAfM21z+GAgAC00r6+ZoZlWdBdNOGU+0xZbUY2OUZjIoMKjMRTRBjVNOKPP41ITQGSthZKjw4PHiQ2cwHxFDLGsxlZ58HlCaQOD364qCcYPzxUEYEfbnaTRn/yUJDR6STUq69Bjj29ZX4+pZMmRDB1lnHw4EEGDTp96VhfZdq0aXz88ce8+eabSJLE+eefz9KlS5k4cWJPT80nmDFjhk92GRf4FkInAm8QOhF4g8/oZP16PBs2sjXVzNo8Ezk7zJyz04JOVZgUaiFASWe0koHOHUC66xsUj4rdIVEck0ZURTZGm7XFVEK9aBK66cMZYzRyvqLZnzc0aOvVk5JAlk1gu7tbGvZWZtno25jDVkYzno1IeJAAA3Z0Tf2iVCTc+COjEEgDOlT0uLATjKoPoF71J0sKI6XRSgl9cBJAEXFEUE0YNfjrVLbqxjFGzaA+OY1BkbaWwPN04TM6aYVYM9WD9MSaKcGZidCKQCAQCASniM2G57Ul7N6pkJWjNdT9pc5EaJGV6zwWQhtKSXHspUE1MEy3lwp9PC5dICv1s0kNLSW5r2Yy0bxm6qGHTt/yiXffhedutXKnsphJrCeVbFTADzcBOAGtBW89wehQkYBKItjEbwiQ3IzoW8EB1UR5XSBhDSVEustYJM0nV0rhTs9izpN2UeMXRWmEibS4Ms6PPIx8/33w29+enhs8jYg1U4Ljcvjw4Z6egqAXMGfOnJ6egqAXIHQi8AahE4E3+IROmtz6snJkFKfCTKeFfg4rVbEmDsemM0zaS6hai8m9hzI1GpcukH/3m89XCXfyRaAZu1OmokzhiloLF/e1ntZ16NHRWsubCCqJwgZNWScJTytbcwkFmTqCcaPDDzcp5KCTQT/6XGKfexC/a2fROGgYH6YtpGDYVAznmtg8ci5lA8aRP/Nehjx/C6Nm9e+xQMondHIMoszvLCPJV7rxCroVVVW96o/lLb5YkyzwPYROBN4gdCLwBl/QiaLA2jwTh0LNXB9mwVGvcGmFhYPBIxmibKfOL4JBukMUyzHY1WBW62fzX91UXC7IdJn4wGDm2gDNdGJYlkUr4QNt/VWHZX50W5lcuNvG3SxmMAfww91kEiHjhxu1yZtPQYeCDEiUEosBB4kUUhXQF8dtcxlz5SDOv95Ewa7hDA80tjTkdblMBDseInGEsWnO3VOaeDL4gk6ORWSmfBhJknC73XRnJWZ5eXm3nUvgG6iqiqIoLY2Cu4OlS5d227kEZy5CJwJvEDoReIMv6CQvD3JyoDHFxN7hZiQ/GT8UzqnbSqSrlBCliqyQ83AHBHM4KI3+gaWkNFpxucDfH5IuMZH0oJlhI2TNVCIzE8+TT5PxvpVnn4X77oN779V+P/ccZLxvxfPk07B+/SnPPSoKBujzSaQQN36UEkcDBpz44yQQF3pcBKCnkTqCqCGCSskIkkRoKAQmaK58sgz9RhoZMgRSU7WfIUO0bS2ZtlMNpE7kXHic/b6gk2MRmSkfJiQkhPLycoqKioiNjcXP79Q/ruDg4G6YmcBXUFWV0tJSFEUhICCg286bnp7ebecSnLkInQi8QehE4A2nrJNmB75TyAA1NGj9Nw0GsBlNRPYfiaFkK9hsJEu7qdDHkxs8hOzQVBId2fSPVfijn4UPg8z0vdjE00+DXm9qyUh5fn8j9dv2UfphBV96/sJ+5WgvqZJNVs7VPUO9tJFgqxXd8OGnFKQEB0NoKGCXqCQKl+pPI3rCqWoyOQeQ0KHgIpDdfucxQreHGp0fIQnhJCae9KW7xvr1sHEjmM1g6qC3ltUKFgtMmACTJrXb7YvPExFM+TCRkZHY7Xaqq6uprq7Gz88PnU53SuVcjY2N+Pv7d+MsBT1Fc0ZKURQMBgNxcXHddu5j+3AJBB0hdCLwBqETgTeckk6OdeDL0YIivR5SUuDivlZGZzdZkHfwBb0Zg0E7pqEBjDYrCSXbUQJshCu7UVSVSEpY3WcO/9VNJSXIyh/9LNhrFa4JsJA0wqwFUqAFRQcPUpNbib1KIc29kXt1z/Cy4S/k6E0ku6zcW/cMaZ6N1PopKEcqiaioOKVgKjERKhLCqamKwe3Rs10aTXRjIYM8+6kjBIBAnCjIFOqT8Y+LIdczmiGNO5Evn3x6LM5tNi2QUhQtYDo2oGoOpBRFG9dBgOmLzxNR5ufD+Pn50a9fPxITEwkNDcXPz++U18Xk5uZ20+wEPY0kSej1eiIiIujXr1+3lvllZ2d327kEZy5CJwJvEDoReMMJddJU+qUoWinevn3ab6XUhmfDRvb9XEv+yxYOrbbidEJgIDidkP21lfyXLezZpeDZsPG4JWRJSVoPTv/DVoZmWtC7ahng2IszMh6PTmaPOpSU0gzCS6wcCTTxWUDnjXeVAYP4hFmobgU/GhmvbuRBxzNMrv+KBx3PMF7dqPV8cit8qs5CGXBqbWvkWCMBl09GDgsmN2Y0QXEh1IX3ZUPwlWzXj2OHfhw/B0zArQ9mZ/JM1qfcghobi2fMOEz6nFNuGuwVRqMWQMny0YDKatX2tQ6kZFkb10Fw6YvPE5GZ8nEkSSIsLIywsLBuOV9AQACJpy2XK+itzJw5s6enIOgFCJ0IvEHoROANx9XJcTNPRgYXpWPa9gJRAUlcH2Zhb6gZm9GE0WZlqGShwqlw8LCM42ozY46T/ZFluCTJyuBa7ZiomFB2nncz4ZU5bPGfgzE7A3elwvXqMnaG30L/y0wEBJqJzbZQOngCMRFGZACbjcNZEHxkP+UYiaUUVLhQ2UhfJZd+HMGPRmTclBJL0JH9HN5qY+DYU8gO2WwM1uewf8w41MJQ1oeaSaCQobaNfGH4I+XlMK3WQnbgOIaH5hB60TSSBps5p5uaBnuNyaQFSs2Bk8UCI0fC9u1tA6mOSgDxzeeJCKbOMp5++mn++c9/9vQ0BD6O0InAG4ROBN4gdCLwhk51YtMyT7t3KuR/buFQqJnGFBMGg1aOl/21lfCDGTgah5IesJeixliG7bZQHD+SPkXb0aEQFdPU+ynfxPnKcXo/2WyMzrZgSNGCr49UM43hJqIjbJSrRvxdKdzgeY5BWJmst/N/tY/zQaYJS/XduCuMDD+sBWOjdy8jzzmOclcoFWhBSjyFSKj0Jxd/GvHHSREJVGCk3BXKL7/AwLGn8AYajegumsA5bKR+oHavhw6ZsNUMJyTMSFoyDAw0Mzrbgjp+AtOvMyLLxp5x5js2oNq6Vdt+gkAKfPN54rNNe/fs2cMTTzzBtm3bKC4uJigoiKFDh/LnP/+ZGTNmtBm7b98+5s2bx6ZNm9Dr9Vx55ZW8/PLLxMTEtIzZv38/b7/9NmvWrCE7O5uQkBDOP/98nnzySUaPHu3VnJxOJ48//jjvvfcelZWVjBgxgmeeeYbLLrvspO+xK03BBAKBQCAQCM42Mt7XSvUUpxYY7R1+NPM04GcLWQe0ZrnKqHTOd2egU5WWYz2SzJ40M9tqTQQEwKOPaqV8ndKUBds20Mx3+SYOHTqaBRsaZ+OG9XcQtGcrO/xG85ThWbJ0JlQVJAkGqVb+R13MhfptVESbuGXLnZg9HzKOzQzmADIeHAQSiAMFHQcYzGbG8aY8l3mvm7j99m54s7rBiKNbON51mksKf/rpaCAFMHo0TJ9++ubYCV39fu6zmanc3Fxqa2uZM2cOCQkJ2O12PvnkE6666ireeOMN7rjjDgDy8/OZOHEi4eHhLFy4kLq6Ol588UUyMzPJyMhA32SS/9Zbb7F06VKuueYa7r77bqqrq3njjTcYN24cq1ev5tJLLz3hnG6++WY+/vhj7r//fgYNGsQ777zDtGnTWLduHePHj/9V34/uYsaMGXz55Zc9PQ2BjyN0IvAGoROBNwidCLyhM50c2/tJRmmTeWpQFPwCZFZIZvxVE33iGulbfPQLenH8SGxGEwY3OBxacHFcJk1CN3w4Y4xGzj82IAmC8nVQX6dg8ORztbyYf/nPJVs2kapYmdW4mCRlMx5dMW5dHNkMZBXTmMoaAnEA4EHCHxf+QDg1rGIaVkx0m9lyUxAiy50EjacjSDmeY9/69bByJVRWgp8f9Ot3dN/27ZrHfEZGp25+vvg88dnMVEcoisKoUaNwOBzs378fgLvvvpt33nmH/fv306/pA/nvf//LZZdd1ibo2rZtG4MHDyYkJKTlfDabjSFDhmAymdi0adNxr52RkcHYsWNZtGgRDz30EAAOh4O0tDRiY2P58ccfu3w/IjMlEAgEAoFA0Dk5OfDss5qZxKhQK8N2W9pknuxOmX/VmMl0mhgeYOX2MAtBAaeQmeqIpkyJq8jGL2PuoF/BT5ornpRAhjSOn3VjGePZQrq6mUS1EBmF7NgLeLhiPne4F3Mx3xFJJQo6qogiggpkPFQSyXdczCL/v/DCZyamTeuWt6xnsdlgyZKO1z/ZbPDUU7B5M5SWQmwsXHwx/OY3WiBVWgp798LQodq+u3umOXBXv5/3Kjc/WZZJSkqiqqqqZdsnn3zC9OnTWwIpgEsvvRSTycSKFStato0aNapNIAVgNBqZMGEC+/btO+G1P/74Y2RZbgnOAAIDA7ntttv46aefyMvLO4U7O33cddddPT0FQS9A6ETgDUInAm8QOhF4Q2c6Obb3U3H8yDb7K/qPpDbeRF+7lUttFlS3VvJXmDAajySjUxWGZlrwP2xlwACt3K1LrF+PZ9GLZLxv5emnobgYFHT44SJBLWSCZz0Pu5/hEs8aEtRC/HDhRoe92skD0stMYCMAdgzkkkIOKeSSgh0DABPYyF90zxDsOA1ueqeD4zn22WxaRqq4GFQVdDot+zR9OqSna4GUosDOndrrDgIpX3ye+GyZXzP19fU0NDRQXV3NF198wddff43ZbAagoKCA0tLSDtc8paens2rVqhOev7i4mOjo6BOO2759OyaTqZ2rXnPzsB07dpB0nH+hpaWllJWVtdmWlZV1wut2N4899thpv6ag9yF0IvAGoROBNwidCLyhM50c2/upT9H2NvsTSrYz1c8fP0cGblXLhuxJ09ZU2YwmhmZaqChTuCLAQlJfM7LcublBC83rjkpt1L/2LtU/W8l12/nF9Tuilb4kcpg+lBJMLRFUosMDgIMA7ARTQCKlbiOjdNvRN7n2FZJAJUaKiMeDhAeIoxQJOFe3m6CwCqDn1gl1K5059v3wA+zapW2LjtbWSGVkQGOjlpkaOlRbQ+XxaMeMHt0uoPLF54nPZ6YefPBBYmJiGDhwIA899BCzZs3itddeA6CoqAiA+Pj4dsfFx8dTUVGB0+ns9NwbN27kp59+agnOjkdRUVGn1wEoLCw87vFLliwhLS2tzU+zveOmTZvYsGEDixYtoqKigjlz5gC0GG3MmzePrKws3n77bVauXElGRgZPP/00drud2bNntxm7YMECMjMz+fDDD/nwww/JzMxkwYIFLWM+++wzZs+ejd1u5+mnnyYjI4OVK1fy9ttvk5WVxbx589qcb86cOVRUVLBo0SI2bNjA6tWrWbx4MQUFBS1/HWgee9ddd1FQUMDixYtZvXr1absnQNxTN9/T5Zdffsbd05n4OfX0PX322Wdn3D2diZ9TT99T8/PkTLqnM/Fz6ul7+uyzzzq8J4tlEbGxFWR/PYuhmRb27HoPjyTzZdF26h1VVOb9yOU7HyLak4nTvZFP/K7ipS//QkkJvPDZg3ykmikp/47YqEL0K/8fH7/xxnHv6d1bbyV/3gMsuX8xt9zyAT9/V4DnyE76FW5mSvn17GAEKrkoQAi1GLATiAM9DgJwYqOBzYzjaeUIW/tMR6KScl0U1ToHu6VwLLrhZNJIjRxOGU5kycNavxr6Th7UKz4nr7X34INgNrNqzRoqysrY/q9/Yd23j/qGBvKBxmHD+L/Vq0FR+PCBB0BR+GHzZiqioymprSU7O5u9e/e2u6cZM2b86vd0oqU/x+Lza6b2799Pfn4+hYWFrFixAr1ez+uvv05cXBwbN25k4sSJWCyWFpE18/jjj/P0009TWVlJREREu/OWlpYyatQo9Ho9O3fubFcCeCypqakMHjy4Xbbr0KFDpKam8sorr3D//fd3enxnmamZM2ee1jVTq1evbvkPm0DQGUInAm8QOhF4g9CJwBuOp5PjufkNzbQg52QT48zj4Kz5HOg/tY0D34ABcHFfK6Oa+yl1YGrQgs2G56E/U/aDlZ9co3hP+R03Fr3AGOUnPMjYiEJFIpIK4ihFjwsJFRVQ0eEkgIOYmM/z7NCN5pPzniLKupnqxiAOBIzgg/C55OhNJLus/L56MYOduwj3txM2ZRxJbz7eow523U6zI99XX7V17IuPb+q2rEBhIURGauOaSwAHDtQWyN1yS4cW6afjeXLGuPk1c84553DOOecAcNNNNzFlyhRmzJjBli1bMBi0etOOsk8Oh+aa0jymNfX19UyfPp3a2lo2bdp0wkCq+TxdvU5rYmNjiY2NPeF1fm1ONE+BAIROBN4hdCLwBqETgTd0qpOOej/Vau58OQ0mdqlmroiyEJsQy1VxGai3jCbPbjzGEtzkdT+lsqxqPLl5JHkauVJyEKjU4kFHAHZSqUTCg57GltI+DQkPEioSEirTWEWdFEFcUC1hSUFY60dgkedyxM+ELMGRQBMWv7ncqSxmQPAuYkNru+dN9BWa3fzS07XyvdaUlmoB01tvafaKERFagNVUbYbRCHPndtpryhefJz5f5ncs1157LT///DNWq7WlxK653K81RUVFREVFERAQ0Ga7y+Xi6quvZteuXXz++eekpaV5dd34+PhOrwOQkJDQ1VvpETIyMnp6CoJegNCJwBuETgTeIHQi8IZOddLUjHbYCJmkB80MnKa58jkcEBAAA6eZSHrQzDljQtFdNAE51khyMgwZorn2tTTo9SKQau7NhKuROHch5zZuJZZS6gjCgJNAGgiiAT/cTcGUigddU4FfIE4CiKKCcWzmD7oPqbv4t8TOGEffhXO56HYTo0dry4JGj4aLbjfRd+FcYmeMQ3fzTWdOVspm0wKp0lJ44QXttyxrNy3L2uu33gK7HaqqtPVSXcAXnyc+n5k6loamBgHV1dUMHjyYmJgYtrZOHzaRkZHBeeed12abx+PhpptuYu3ataxYsYKLLrrI6+ued955rFu3jpqamjYmFFu2bGnZ3xu47bbbenoKgl6A0InAG4ROBN4gdCLwhuPq5Hi9n7qYeToeR46ArRzi0OGPi1hKsRGFhISEgg4VqdV4FQkHAeTRFycGjNjww0UihVQH5BM5Yzy6lPHHn/flD505gRRo95KeDv/7v5pb3969mlvf1KlaD6knntDc/DweSE2FYcO0Y4xGrcwvMlIzn+ioRxW++Tzx2cxUaWlpu22NjY28++67GAwGhg4dCsA111zDV1991caafO3atVitVq677ro2x997771YLBaWLFnC1Vdf3em1y8vL2b9/P3a7vWXbtddei6IovPnmmy3bnE4ny5YtY+zYscd18vMlmhfnCQTHQ+hE4A1CJwJvEDo5C7FpNt+Koi2P2bfv6DKZ1vtbc0KdHNOMtl3mqYmuXPNYDh+GbFdfCkikEX8CsRONDT1O9Lhb1kcBLb/tBPMBf2A9kyggEQV//HBjNDb1oz3RvM+kQAq099li0dY9OZ1aKi4jQ1s7tX69ZonucGg/xcVHj2sdUNXWauew2dp9br74PPHZzNSdd95JTU0NEydOJDExkeLiYj744AP279/PSy+91LLOacGCBfznP/9h8uTJ/OlPf6Kuro5FixYxfPhwbrnllpbzvfrqqyxZsoQLLriAoKAg3n///TbXmzVrFsFN7adfe+01nnzySdatW8ekpoWKY8eO5brrruPRRx+ltLSUgQMHsnz5cnJycli6dOnpeVO6geXLl/f0FAS9AKETgTcInQi8QejkLGP9ejwbNrI11czaPBM5OUfNIFJSNDOI0dntzSBOqJNmu/KOMjwb1+NZ/Q1b027p0jWPJc9uZLE6l9uBSawjlUMYcCLhQUaLypqDKA80mVIYicbGKqbh5wd+bKavrph+/doHemcVQUHah6PTaRHt1q1aXaZeD/X12ofX2Khtv/lmrfwvMhIOHYKff4Y779Q+82XLtKxW0+fmi88Tnw2mzGYzS5cu5fXXX8dmsxEaGsqoUaN4/vnnueqqq1rGJSUlsWHDBh544AEeeeQR9Ho9V155JS+99FKb9VI7duwA4KeffuKnn35qd73Dhw+3BFOd8e677/LYY4/x3nvvUVlZyYgRI/jqq6+YOHFi99z0aWDGjBl8+eWXPT0NgY8jdCLwBqETgTcInZwFtOrLVP35RvbtVshbYeFQtJnGFBPRko1yp5Hsr62YajUziWFsRDd8eEtm5rg6OU6ANiTWxtV7VmLYuQXHJyVkxz9CYcjR8jBlnxVTnYXw6FIGHXPNY1FVOKCaWMU0JrEBCQ8BTY59UksYJeHAHwV/GvEnhHrGsRmAryN+R2IQJAVsI3pAeHe9u70LoxEeeUQLggICICtLK+kzGiE/H375RVsvBRASon2Qe/fCtGmwahVs2gS5ufDSS9r2vXuhpASaPjdffJ74vDX6mUxXrRcFAoFAIBAIThvHywbJTfszM9sGOmusnLPTgk5VCIuUKU9N5/zGDKojkwmvzKGiTEEO0Mwkxvzeuwa6nteWsO/nWg4UhvJ1qJnKGBN+fuB2Q2SZlXt33c6Amu0U6FNYGzCNZeotWDFhwsoNOgsmDjDWtQn7rN/R//2FnV5q+XJ44Y9WbncvZjLrSSULPQ50gA4PKhIu/KknmDJiCaEOPxpxo2ernM4vd7zJVb+xMWrXMnRXTD2+DfuZjtUKixdrTXpBc+zbuVMLjgAkSXPy8/fX0ocmE2RmauM9TU6JqalaOeDYsfDmm6etJLKr3899ds2U4NfBF2tNBb6H0InAG4ROBN4gdNJLWb8ez2tLyHjfygsvwLPP0vJ70SKt95PnhRfxLH+X3TsV8l+2cGi1la01Jj4PNOMXICPbSpm4+QX8s/dx7o53CGisJSpG5utQM9/lm46uZ+I4OjEaOeBMRv55M5SUcsERC45dVnbsAMcuK1Ozl5BYvRc/j4NoRx5h1XlcWW/hYvtXXFlvIa76AOdWb8DtaET/3WqU/Qc7veWkIBtzpcWMYzNRVOAgADd6PEh40KGgoxF/KoiigUBKiEXBHxk38fHw2GMw5vcmdPMf6v2B1InWmHmxBq0drR22VVVz8ysvh/374bPPtGDL08py3maDmhpo1afVF58nPlvmJ/h1mDt3bk9PQdALEDoReIPQicAbhE56ITYbng0btSDpcwuHQrVyPYNBy04dLdcLIEIN5chBJ4ongJl6C+UOM4djTRz2pHPDkRdQFIXAyiIOJ6Wh04eyN03rE3XokJbtSk7WLtmZTpRSG85v1uFXU0+yupVtjOYCLATLIxmhbKfeU4dHBQkIwMFk1qFTwV9SSFGzmKBuADy4VD92N6YxvCGKfp3cdkoKuPT5JDYW4ocLJ4FN5z3q4+cgEANODjGAQv8UUHfQV1fMgBSt7BDo/aYSn3+uZYg6cdRjyxZYswYmdLIGzWrVDCQiIyEx8Whj3qAg7UMvLwdAVVVUVYXqakD7DFvcEmVZSz2GhWlrqyoqwGj0yeeJyEydZXz//fc9PQVBL0DoROANQicCbxA66YUYjWxNNZOVI6M4Fa6XLIwKtRIXB6NCrVwvWVCcCtZDMm/4zeXzqFuIipFBUbi0wsKkuq8YUptBpT4OP73EfjmNQqeRwriR2IxaUOZyaYFZM53ppKAA6gqrCXeW4+eyM9y1lcjGUoY7td+D3XuwEwiADhV/XEz0rGeCex0TPevR4wQkKojkq4bLqNR1Huj06wfR0eCHGwV/iomnmD7k0p+DDCSbVJwEosONQw7l/+JuJS9hHFL/pDNnjdTnn8Pf/64ZQlgsWmDUmm++gQULIDtb6yd1bIaq2c2vtlZz5mt26QOIioL6+ibzDs3MQ6JtENW8HUXR1lT166fZqQ8aBPjm80QEU2cZkZGRPT0FQS9A6ETgDUInAm8QOul9KAqszTPxdaiZqBgZGYVhuy2YrF8xbLcFGYWoGJnP9Ga+zTXhSjaxd7gZyU/GD4Vz6rYS6SolsrGEnOA07AYjDQ0Qlbsdo81KQ4OWxTEYjl6zM53U12vfy1EVolQbEWoFozwZpCpWRnkyMKplRFCNCz2NyATiIIQ6zmEfIdQRiINaQtnEBPo4csjO6Lw8TZa19WCSXk+xXyI/B4zn74ZH+Ub/W54IeJ6N8iQKSUSR9ERGwoSbB9J34VxiZk04Mxrv2mxaRmroUG1t07EB1TffaLWezYvopkxpf89GI4SGwscfH+0b1dy0NzcXT0NDm15drVGP/f96vRZITZ3ast0XnyeizO8sIzExsaenIOgFCJ0IvEHoROANQie9j7w8rUdTY4qJvaFmhu3WDCUSCrcC4JFk9qaZqc0zUbVP+25tM5qI7D8SQ8lWAsrySZazqdDHU6aLZZc8knMatuNpVBiaaSHbNYX4346ldYvOznRSUQE5rr5Ekk9/coiniBDqCcZOBJWEUoMTPQoyKhCEAx3auhsdHhR01BCOBx0WzCRw/IAnJjWcspIk8pyjWKmbixUTW9w2qv2MONQU+jRCgv82Ro4OZ/y9IMeeQY13jUattM9i0V43m0VYLBAbCytWaB+2LMP8+ZoxxLHYbPDUU1ogZbdr55s7VysXPHxYOwd0GFC1bYgMUmysVnvZCl98nojM1FnGN99809NTEPQChE4E3iB0IvAGoZPeR0ODVoZnMGhBUnH8yDb7i+O1cr3mjjJ1dWC0WUko2c5Q905+41yLzl6PobaEdfXpfFQ3nQ/cZgpLZaoPlnL74QX8tua9Nn2YOtNJtZ+RxcxlP4Nx44+MQig1LT8yCm5kKomimsimflBHW+v648ZAg/blXGq1rqkjjEZ0N99EzKwJ9F04l0l3mLjgAkgZbeSCC2DynSaSX5hLonkCYffchBxrbDnOZzhV4wiTSQuAQkKOZqj27YOPPmobSI0e3fHx//63ZiwBmqX5mjUtuxz6EO/vA1CqazRHwFalhr74PBGZqbOMBx98sKenIOgFCJ0IvEHoROANQie/It5Yl5/EF32DQQs6dJU2jH424gq343Ac/S4dV7gdm9FEqdtIeLiR+CNbGFq1BkN9KclVO6mQQghvLGevYmI4GRQRwe6gsXxbnc481wv4Ryqk/vgOHBzXshamM52UlzcZvxFJBUYiqEJCxUADEmrTuhsJCRUjtibnPZkGDPjjQkUhhlKM2DBjISXsbjhedmrSJHTDhzPGaOT8Dt9XH85ErV+vrWPqzDii2RiiM+OIZvbt07JKOh3ExUFhobZdkmD2bM3SfMmSjs9zww2wcCEUFQGgHjiAc6aZsnufJuT/PUkA3uPKK8SwZYv24vHHwWj0yeeJCKbOMm6++WZWNKVYBYLOEDoReIPQicAbhE5+JY7TyDYlBS7ua2V0tgXdRSf44twBSUkw0bOe4M0rMRigwBlJvUNmb+BIhjq2ExyoYCpZTFIDXBkRTHLxFg6UDOVIQCwb9HdxQcM3FOriSaQIqRGektazWZpKrNFJiWso4cperBfezJCmQAo614m+1sZ1qgUZDx4kHATgj+ap7kGmET0edPQlv2l/IMUksE8axhB1D30oRkHHRWwgJ2gEUYO8CIKaAiVZPuo22NF+n8Jm0wIpRdECpmMDquZASlG0cZ01L242oBg6VGueW1JydHFbfDz88AP861+QlqZt6+g8ERF4moIpSVXx37eTyHt+T5Cnpku3JDkatNLAVqV9vvg8EcHUWYavCVDgmwidCLxB6ETgDUInvwJeW5crDGMjus6+OHeCXGVjgm0l5VW7cBRDUeAIvo6fS2Gwidx6E1cXLSbUsYu+/nYG1BdSKPejT8VePtRPZ53fVNL8LmIKa8AF49QfadQHc1vjP8kyXkl9cCxvuf5An7CxmJoyXdC5TiIHGinwT2aqsgodKh78qMNAJZFEUkkADYRThR9u6gmhkER+lCZQqTNi8xi5UN1INOVIwLW6lYSWzQIGdXitXk3r9U7HBlStAylZ1rZ3pIfWBhQbN2ppQX9/bb1UaqpW8ldQAE6nZlv+P//T/jzr1uGxWpEABZoaHqsEeWo6NZ7ojEa/QAKdziYHEg1ffJ6INVNnGTNmzOjpKQh6AUInAm8QOhF4g9BJN9NUurcl2czeAzL2GoWZTgsjgzXr8gv9trRYlx88LLNtYCdfnE+A1Oq3qrbdpzb1dXLKQRRHDaHRI1NiHMqU8AwGeqxkGsaSaUinn76Iav9ogjx15ISfiz0klr3DzVSaxrb0mWqmM52YjDbGB25FjwsjNlz4Uyglslc3nEIpERcByChIqLjRsV03mjJdLNsk7fdmeQJVftH4+6n4x0YQPyyqy+9Fr6F5vZMsHw2ovvqqfSDVUQkgHA3Iqqs1J7/6eq3HU1yctjCutFTb53Rq+5rXRjVjtcIHHyA1dWNuHWQ06+kYKR2fiGitz1R5ueZEgm8+T0Rm6izjyy+/7OkpCHoBQicCbxA6EXiD0Ek3YbNBZibu9Rv5OtTM8ytNUGbmeslCfb1CbPEywuKTmVi8gtrwJIhJ5SPVzMB8E+e3ygB5gxJh5HvjLIIjtAov2RnJFdUW9jq1Mj/ZGElNwAjsdvgofBYuo4EZ+jX41yn8vsHCfsNIzlW3Y/eLw+Dy8INnBE6/vuia+0y5weFo22eqM5306wfDwvPpU12CqkIhiWToxrFevoxJyrekK2DAQTB12HXh6BNj+Ek2Y8WEHRNmLGQ1TiDAsRXPtb87ahpxpnJshmqr5sB43IxUayortaa8zf710dGaGUV2tnYOvV47b0kJzJsHy5Zprn5WKyxejMd6sE0gfixdyU41TpkGebvh6qtb1tb54vNEZKbOMhYsWNDTUxD0AoROBN4gdCLwBqGTU6DJeU1Zu57K//cie/93JSs+VDj4jIXabVbq7BIWzOjtlZxT+B1jf/kn9dUKoVV5ZA+cgj7e2C4D5A15efC9bhLfjnsc66VzSewnk9JP4XLjVlL6KST2k7FeOpfPRzzOl7WTyE8Yy97hZnT+MgF+CiNcW4nxlBLV1GeqMqjvCftMdaaT5t5Psr9MsV8i2wPGsTxoLmsN01keNJe9+vNokIJwSYFIhgC29p1J6CgTY8dC6CgTP/Uzo8bG4h43AZM+58Rudr2Z9es1YwiAkW0dGFteL1mijesImw3+9jeoqdE+oPh46NtXM6AwGCAhQSv3k2UtGrbZ4O23tezX4sWwaxcuV8fZpy5lpJoID5Ng6VK4//6Wbb74PBGZqbOMG264oaenIOgFCJ0IvEHoROANQicnSZPBxI7YKdR+spGc7AAay+w4nZU4dZE8qTxKQmMhn7tmEeM5TJSnBIDCmmC+DLmBGlskU/KXsM84gYaGSV26dLM1ui7SiM1opCRhZEuPKYDCBC3D5CjTqsD8/Nr2mQotzaK/XwE2/3iKPbFsl0YyzHW0z1Rx/VjCrp3Sps/U8XRybO8nGyYiVLBJJj7iQQbayznP/TNBw4aQMmkgDSVHzTgGjDGR1NfMOVlNZhy+aB7RHbQ2oFi8WNvWusHtt99qP5GRxzegCAzU0oEeDwQHw549EBMDQUHaT2Ghtj0wUAu0rFb48MMW974yQ38S2dPutF1dLwWg2B3Ig9qub/PF54kIps4yMjMzGT58eE9PQ+DjCJ0IvEHoROANQicnQSuDiZycNay3p5NSnYFLiSSaQuKUYs5VfsGfRu5XXsCFnkb0lMtx7Occokv3krxxLxXBkZyjbiTYMZzj2oEfQ7M1ekOD1j+qT9H2Nvv7FGnW6G63CX9/zYuguc9UYv1a4hsyyZP6oUfHKt0cvlGnMlgycfNBC+foDnC/ayn2zN8hywtbztmpTpp7P8V9Q98RtzDpiAlj5lG78uHDTQT2e5bgLUsIvXom90wwdmxnbru7ZwKpE9nTn6R9fTuay/uaMkQAjBgBl12mBVGtt82d2/E1jUZ45BGtdG/PHi3oCgqCsjKt3C8rS3ttMMDtt2sW6vn5R63T+/bFlXX41O+lCVtONfHHbPPF54kIpgQCgUAgEAh8CaORralm8j+34HYojHRl8J1/OtMaLAxiL3ocONEThQ0J8MNNDrGs0l3JFerXBCoO6usj2O0YwbZxc5kxomtf1pOSNEvw0i+3MFS/BklVsLtkcqNG0r9iOwa9lmHKdk2hrv9YTLlrGFq+hdDqXPpV7MDj8ZBILgdJ5nwlAwcS30lT2FeTgJk3CZRrMa59BzJmQnr6iSfkVe+nx8BoRMaH7My7q+9TV3A4Tm2/yQQDB2rzCgrS+k0lJGgmEM2vx47VzChq2lud5w2fQUr+j6dwA0epiB3aLpjyRUQwdZbha9G8wDcROhF4g9CJwBuETrqOosDaPBMlgVO4TL+GykqFC53rCVfKiVZKQAUFFQcB6GmknhAqiCK10Qo6lTCqcKjBJ319WYaZte8hZf+LvX7nUqWP5VN/M1mVJgZ6TFztthDhLOUu95/xj44gLGcXW/TjOaAm4XSfyzB24yCA89lOCHXcylI2q2NJlo4gqR48HsgNSyMlNbXlmifUSW/r/dRdfZ+6cr3nntP6MiUlaeV8kZGaAUVkpJaRqqzUrvvcc7BoUcfX27JFK9sLDNReJydr9uiSpGWoYmJg504tK9Xc1HfAAK3Mr6CA4QUHTv4ejsGQu7fdNl98nggDirOMf//73z09BUEvQOhE4A1CJwJvEDrpOnl5oP9xPRPsa/hZl051nUyNM4DD7v7UqKHocRBLOYE4qCUUG0YGcJhBWKnzGNgkTWBf0ChkYySjsy0U7Oqi6cLBgwz++hVi6nPoV7aVzwrTWV9ooqAA1hea+KwgnX5lW4mvOUCK9WuCHDbOrdrAtuqB/JM7OUJf3PhjwM54fiCOYmaxkv5qDkgSR9S+vOO+EVfo0S/zZ5xOmsvuWtuUW63aPm/7Pp0skZFar6jWDB3adg1VR9hssGYN7N6tzTE8XCvhs9u1rNSgQZCTA8XFcOSIlq2SJC0QHDEC7HYi8vae1PqojggcMbTdNl/UiQimzjIWLlx44kGCsx6hE4E3CJ0IvEHopOu4imwk52+krloh6mAGBY2xLb2ePIA/jQDoaURCJYh6JFRiKKOARL4yzGb3xLlExcrsi55AfWAXv6hHRVHtDsHfUYtesTNFWUWyy4rLBckuK1OUVegVO7pGJ3YpGMUjIeHhLv7JpXzL90zGSQBh1CLjxp9GFGQ8SNiI5ntpMoHFOfy8+miQ1yt0ciInwGP3n2rfp67QvN5p3DjNPGLFiqPzsdm01x6Ptv+RRzpfM/X661oJn6LAjh1aKV9ZmWaPXlGh9Zlqpq5OC7jcbhg/Hmpq0Lldp34vTQRgb7fNF3UigqmzDF9sdibwPYROBN4gdCLwBqGTrqOPN7ImwkxFtYxRKWW2tIJkJYvRagZGKtDjwkEgFURRSRQGyYEfbsqJoZ9cwOXyt4SHw5rUuzncf1IbC3JvUBTY6hlJjqcfYWoNY9Ut3CMtZpb/V9wjLWasuoUwtYbDnv5sUdPJJwEkiRjKGMEu0sgkiDp0eJAABR0OAmmUAvhRN4FSKZaPPGb2lx39Qu/zOmm2HW/OLh2L1dqx7fixAdXWrd0fSLW+1qRJsHevdo29e7UAqvXrSZM6v+Y777S48rVQUQGhodoitUOH2h+zaxfExsKXX0JtbfsOz6dARJ+gdtt8UScimDrL8MVmZwLfQ+hE4A1CJwJvEDrpOgkJkKM38aOSzmDPXsKkWi5UNhFHCSHUU0sY5USTRSoh1OJW/agjhFK5D7IMQ9y7GJW5DP2RLAYMoI0FuTfk1Br5tmI0doKolcKIUUs4372Fqx0fcr57CzFqCbVSGC7Vn0p3KN9xGTaikXETSRUJFBLalC0DUPDDQAPBah1hUjUrMHNANeHXauW+T+vk2PVPxwZUx65/ap2hOnhQC1466vtkMmn7uwurFTIytJI+WdZ+63RtX2dkdB4Qdsa+fdpaqsrK9vucTm2N1caNACi6LnSHPgFyZftMoC/qRARTZxmzZ8/u6SkIegFCJwJvEDoReMMZp5PmRrqKtnxk3z7tt6K03X8qFBZq5XQXyhkcIoUoTzkV/rFUEckR+lFONP40MoJMXOjxIFFNOFVSBAdUE9meFGoL67gz689cVfMeche/3+b+YiOyOodtjKZeDcKp6on1FDPMk0mspxinqqdeDWIzF5BPX+qkEH7UTcCNP/40Ek41ATiRUHHjh5MAXOjxo5E0zy76ew63NONtxqd10tX1T828+ircdZfWeHZ7K3t5u117vXSptv/VV099jjabNo+ff9YyRbNna/O227Xfs2dr23/+WRvXHMS11mtiYptTqs0/bjdqfX3L6zbodJCbqzX2crtpiOp7Ug16O6Sqqt0mX9SJcPM7y3jnnXd6egqCXoDQicAbhE4E3nBG6aSpke7WVDNr80zk5BxtDpuSAhf3tTI6u6k57ClYXbuKbEypslAfoVDW0J+vmcmIxu3slNIwOCuJp5BUsvHHhREbGaQTRAMuxQ+Leg2yR+WpiieI1RcQseoVuHmcZh7gJYVOIx+pZmZKFg6RysXqYTzI6KjFj0YCcbBNGkOpGstHmJFUeFx6hiDsBFFHAC5ktOiyniB+5DckkUc8xYR7qvgrT/APA8TGTm25pk/ppKPeT83lehaLVs5msWjZpe3b2wZShYXavrFjj5a+/e//woUXwuDBWkCzYoUWhGRna/2bvvwSrryyS59RO4xGePttLbBpaICJE7UoPzcX0tK0+X3/Paxdq2WnbDa44grt/x9jzX6iYKh5vwRaZkqStH8IwcHIVbZuM6DA6Wy3yad00oTPZqb27NnDddddx4ABAwgKCiI6OpqJEyd2mN7bt28fl19+OSEhIURFRXHjjTdSVlbWbtz//u//ctVVVxEXF4ckSTzxxBNez2f9+vVIktThz+bNm0/lVk8rL730Uk9PQdALEDoReIPQicAbzhidtGqkm/+yhUOrrTidmoO00wnZX1vJf9nCnl0Kng0bTylDpY83ktN3AsHhMg1p6cjGSPaFjKGfnM8kaQNRumrqMaAC1YRTRjQHMFGnBvMsD3O/8hIB7nr8HLVUKSEQFdWl60dFwUHJxBZPOqlko5M0kwuazC50kkoq2WwmnYOYSOYwaZ5dGLAT2JSRAs0sw4NMFRFsZCKFxCPjJkEq4jHlCSLKjpa4+YxOjrc2ymTS+mJt26YFQseufzIaj5YDbtkCF1+sOd55PPDjj1oAVVoKwcHasY2N2v7f/e7UAinQ1jvl5Ghrlv77Xy2gy8uD+HhtrdQHH2jbVRVKSrSs2MMPa/NpVZro6cIlVTga8Hg8YLPhj6fbMlPKOe3d/HxGJ63w2cxUbm4utbW1zJkzh4SEBOx2O5988glXXXUVb7zxBnfccQcA+fn5TJw4kfDwcBYuXEhdXR0vvvgimZmZZGRkoNfrW875l7/8hT59+jBy5Ei++eabk5rXfffdx5gxY9psGzhw4Mnf6Glm6tSpJx4kOOsROhF4g9CJwBvOGJ00NdIt/WQZihKAOdTCFtVMoc7EINXKWCxUOhVyDzpxXH0LY07B6jopCVwXTuKXT11c3LgFKVGhsdzF6JoMglUbetVJGUZqCMIPD+dwgCLiGcEuEilARcKmRpPj6UepZySTFehKpV9wMAyRrUxjFYEeO/64qJdCqJXCkFEIUusJVO1cySoSyecO3iLcU4UTrTeRlpXyADr8cDOarWwhnZ90E5ig20gM5TTGRhA/7GiQ5xM68aY3VEaG1lspN1fLMgUFHV3/BG2zV9u2aVmh3bs1N7ylS7UPNy9P+11Xp2WsCgs7zoadCnv2aIGUokBBAZ4DB1oyRiog2e1Ihw5p66DefFO79rZtXb+Oqmrvw5EjIMvI3ejmV1lkJ/qYbT6hk2Pw2WBq2rRpTJs2rc22e+65h1GjRvHyyy+3BFMLFy6kvr6ebdu20a9fPwDS09O57LLLeOedd1rGARw+fJjk5GTKy8uJiYk5qXlNmDCBa6+99iTvqucpKCjo6SkIegFCJwJvEDoReMOZohNFgYMbCgmusRNmsFOYF0nUQQvFgSOJcmynMFAhLqCShnpt3PnXm7q8VqmZ5qa5fjlLyNSPpkofy/eN00h2rcGPWvQ4iKCKcGqwEUUCBaSSTRD1yCioSNQRgp0g1thGk1JrJDXW++vHyjbulRczhC2EUUMpsVQTQY6USrKaTThVhFHDRaxnNitw4w94yCeRcmIYzD4qiSKGUiQgEAcjpV3si51EljyBAMdWPNf+Djn2aPDgEzppXhvVvAaqdUDVvDaqtFTL7KSlaYEUaKV+JtPRn+ZzNAdO06drlugez9EgLDQU/vQnLZCaMOHUA6nERK3crslNTwXU//5XC5yaflrj8oCutg65thbdH/4Af/sb7s++6FLJmgogSUhut9bcNycHydOV3NbxsRHTLpjyCZ0cg8+W+XWELMskJSVR1WpB2ieffML06dNbAimASy+9FJPJxIoVK9ocn9xhy+yuU1tbi9vt7pZznW4qO3JiEQiOQehE4A1CJwJvOFN0UrDLRvD2jVSqkVrlVkUlkkdhuGMrkkfBU1FJeTlUqpEE/bKx641yW3PwIINXPE1i9T4GlWzk47x0PiiZwr2eV8hmAE4CiaMUAw30oYQIqoigCn/cKEiUEEe1LpJtjCayOofcX7o2l+BgGGTIp49Oc+2rlKLYKqVzUDKxVUqnUoqiVgrDKFXhp1PRy26q/KLZrhuNLHn4mbGUE8NaLqWEPvhLbqqD4vkp+QbU2Fjc4yZg0ue0KYU8ZZ10tQdUZ5hM2nqnjnpDlZZqJXPx8VpANHp0x6YUzQFVaqrmoBcVddRtozmb9ZvfwG23wfXXn9L6ujaoahuTCAnti35Ha5jcyMioSICnvBz+9CeUzL1dupwEeNweLbgMCoJRo5ACA0/lDtqgc9S32+aLzxOfD6bq6+spLy8nOzubV155ha+//ppLLrkE0KLT0tJSRo8e3e649PR0trd2TukmbrnlFsLCwggMDGTy5Mls3bq126/xazJx4sSenoKgFyB0IvAGoROBN5wpOqkPNPJVkJmaeplqKZIEvY1Y2YZer2VyEvQ2qqVIauplvgoyd71R7jHYXX40KhIRSjnXez5gkGrFRQA5JOOHuynjoKJDIYgGJFRUJBT8CMJOlpqq9XNSzRQ6uzaXxEQITginTh+F2z+ITP1oKvWx7Gr6nakfjds/iJqAaCpiTNSGJZAVNwH69efr2JvJCT+Ppcb5lEUM5pegCZT6J7F10O9ImDmWpAfNnDMmVDPpaJWNOSWdnGwPqI549VV4/nnNn751b6jmQCo4WFv/1NCgZZw6c/kzmcDPD77+Gn75RSuDCw09ms364Qet7O9Pf/JuXieioKBL650CaUSildlEfT2yvfo4R7RHBRSPG/r00TJ1Oh2EhnbbminDuHPbbfPF54nPB1MPPvggMTExDBw4kIceeohZs2bx2muvAVDU1FgsPj6+3XHx8fFUVFTg7MAJ5GTQ6/Vcc801/O1vf+Pzzz/nmWeeITMzkwkTJngVtJWWlrJnz542P1lZWd0yt66wePHi035NQe9D6ETgDUInAm84U3Si18Muh4mPZTMx/pVEuwpIrt9NX7uV5PrdRLsKiPGv5GPZTKbTRKsl211GGTCI5/q8wiFPfxTJn0m6jTwlPcZtvMUADqPHhYoONzpUdC2GDy780aESgJPBHGCLR8smddF/AjnWSMDlk5HDgsmNGY2cEMuPfc3sTJrOj33NyAmx5MaMxj9ET6QpBteFF6PGxvJTPzOHx9/Ivsl345o0lb3DzQQlx9I4bgI3T8rhoVtsjPm9Cd09d7fLxpy0Tk6lB9SxHDyoOespitY7qbkBrd2urXtSFO13dLRmMNHcQ+rYgMpm0/Y/+aRmVLFqleZ2V18Pw4ZpY2tr4d57tWBr5sxTt9QPDe3S8NaBlAcJtbGxy0GBBDgDIuD++6F/fy0L53J1m5uf/y8/tdvmi88Tnw+m7r//fr799luWL1/OFVdcgaIouFza4raGhgYAAgIC2h0X2JRmbB5zqlx44YV8/PHH3HrrrVx11VU88sgjbN68GUmSePTRR094/JIlS0hLS2vzM3PmTAA2bdrEhg0bWLRoERUVFcyZMwc42uV53rx5ZGVl8fbbb7Ny5UoyMjJ4+umnsdvtLX77zWMXLFhAZmYmH374IR9++CGZmZksWLCgZcwrr7zC7NmzsdvtPP3002RkZLBy5UrefvttsrKymDdvXpvzzZkzh4qKChYtWsSGDRtYvXo1ixcvpqCggLvuuqvN2LvuuouCggIWL17M6tWrT9s9AeKeuvmemgP9M+mezsTPqafv6ZVXXjnj7ulM/Jx6+p6anye9/Z4aGuxkZWn3ZLN9AYCj4RBudxWNrhJcrhIa3Tbq6jS3sdtvP/l7evTRRWQe2MduKZpqGvF43JzvXoWJA/RjLx4kwI2EhIQCqKioOFFx4YeCC3/VxeXcxRDZyrJlXdPe3o0bcR34giMJYTSEqnzQmI/hXBO1tTMwnGtiae2PKMZI9kbKqGEudPpsskfJRKTrOHBgHkqEkZ9/nsGgK018G/ULaRf4saahgE37dmuf00cftfucXnnllZP7nD7/nG+josgvKmLDd9/hev99/nTFFQDcOXkyWCysXbOGkvJyvgwK4sNvvulce4mJvJ+YSHV9PRVHjlDzj39Qs307q7//Hvz8qP3hBwgJYU9eHjX/8z8s+uwzTXuHDrGiupqa+npe/vlnsNnYPH06OJ1a2Z2i0FhURElsLIcdDjb4+6NkZuJp+o7qqa6Gf//7lJ4RWTv3eJ0Rag52NOVouNxKy/oqb1GBPcMuZMM55/BWbS320FCyXK5uy0ztP1zT7nMqKCj41Z8RmzZt6tI8JVVVu+ueTwtTpkyhqqqKLVu2sG3bNsaMGcO7777LjTfe2Gbc/PnzWbRoEQ6Ho12w1WxA8de//rVL9ugdccMNN/Dpp59it9uRj7PStLS0tJ1de1ZWFjNnzmT37t0MGzbslObhLTNmzPDJ7tEC30LoROANQicCbzhTdLJvH7x0p5Uxu5fhlgMYKGVRLUVSJRuJUGyEq5VkqQPxU5z8nHYLD75hYsiQk7vWitdtWOctAbdCMocYrWQQiAOAQBoIb1ofJeGBlryURA2hlNAHUAnARRmx7A8fR/pXjzNkfBfLDpt6am0baOa7fBOHDh3tqTVggNZTa1RWU0+t4cPBaERRNL+FhgYwGLRlQrKMV051p6yTNWu0bFCzVfmxPaDGjoUpU7w719KlWm8oj0crXUtP11z8GhvB3x/+3//T1ju1eq/YuFE7f2Sklp3auhW++KJliAo0BoVRNvpKonesQV9zTD+mZcvg5ptP+va/eSaDSx8b63WWRCsJlJBQ8aCj0T8Iv8Y6ZLwPqFSg7LF/EPfUPdoGq5XaO+YRsmFVF2ff8bn3XnAraT8ubbP9dDxP9uzZQ1pamtffz0/Zze+pp57i6quvJi0trdMJffLJJzz++OOneikArr32Wu68806sVmtLeV9zuV9rioqKiIqK6jBr1Z0kJSXhcrmor68nLCys03GxsbHExnbBSudX4kz4D5rg10foROANQicCbzhTdBLssHFz8XMEeQ5z2JVEjmKkikgAKjESgY4+8iFS/PIYVlJCsGMRcHLrpmr1RlZgZpZqoVYKJ1Byolcb8QCh1DYFUloeoYEA/FAACbnpK3IDBhoJoI+ulMbAfIKDT2ISkyahGz6cMUYj53cYJJnAdnebIEmWNVO3dnjhVHdKOnn1Va0873e/09zxmtc5NU8qIUFbB7V3r1aSdjysVu0cF16orY2KjobiYu13eflRK3OrVSvxa11m+NlnWklgZKTWgIy2DXD97DXEfP8f/HC32SdB2zK9EwWfHeyPsfytS1klqWkGKhIeJDySjKIPRna1N304HtF5rZa6mEzUuA0E07UMV2foxk9ot80XnyenXOb3xBNPsGvXrk737969myeffPJUL9NCc9ledXU1iYmJxMTEdGgCkZGRwXnnnddt1+2MQ4cOERgYSEhIyK9+re6gOU0uEBwPoROBNwidCLzhTNFJYiKEhIKfy06K+yA61YMiyezwG40iyehUDynug/i57ISGaONPlpQUyJa1prkXqhuJUCsJopZwqgjE0ZRNkKgjmEqiOUwKNYTiwEAcJRhw4PHXU6ePJLRv+MnPpekLe3OQNGSI9rulEKcb+yKdtE46W+fUjKpq2xVFG3fwYMfnaT6XxaIFUYMHwxVXHDWMCAqCyZO17atWgcVCQ76N/3xn5EPFzL6dThp1AdpaqP37YeTIdoYQEjQFwm3xgHYcnLSZRlBVYef31QGtS/0aCET2uFFcji4HQXJNVZvX9v7tG+2eLAM76GPsi8+TX33NVEVFRZvGud5SWlrabltjYyPvvvsuBoOBoUO1D+uaa67hq6++Ii8vr2Xc2rVrsVqtXHfddSc15/Lycvbv34/dbm/ZdmyJHsDOnTv54osvmDJlCjqdzy8/A+CVV17p6SkIegFCJwJvEDoReMOZohM51sjhMWZQPDjVAEYG7OWQMZ2tfaZzyJjOyIC9ONUAUDwcHmtu00Opq/TtC2kBVn7HBxg95QA4MEBzFgEJBRkZDxVEUkQCmxhPAfHYCSZSV01B2DnIoSEETJ18SnM5XZy0TgYNgvnzj5o6vPMONBt8ZWVpr2trtf3z52vjO2L9enjxRfj732H1avj0Uy0oAq28z27Hs3o1jc8vwrN5M3VPvsjwSUZuuw1WPruPdf9n54PFlexaV47n/1Zpx3eFxMSjWa7a2uObadTWtjPTaJx0eZcu17w+SkZFQabBo8cfpUvnkADPoUNt5mmIOpk0aMfo8w612+aLz5OTKvP7/vvvWd8qIv700087dKarqqrCYrEwfPjwLl/jzjvvpKamhokTJ5KYmEhxcTEffPAB+/fv56WXXmrJBC1YsID//Oc/TJ48mT/96U/U1dWxaNEihg8fzi233NLmnO+99x65ubktQdL333/PM888A8CNN95I//79AXjttdd48sknWbduHZOa3GbMZjMGg4ELL7yQ2NhY9u7dy5tvvklQUBDPPfdcl++vp1i6dCl//vOfe3oaAh9H6ETgDUInAm/odTppKqE6dv1PQoCN4d/9jTClgFIplo31E+hbn0Ga1EhfdTs/M5QJ0kaiKSfov39DKR198kGMzcZjumcYxkYa8aeYPvyiG43RU84oMvCjkQAakXETQh2bGUe5XwKNchi497IlbAqxSQY8iQmc09zPqRuzSL8Gp6STqVMhP//oOqcffwS3GzZv1vaXl8Odd2rjWtP8vthsWqCVmQkObW0aO3Zo/aH698fT6Madk49fXWXLmqIgpYbHs3/HYv7EPJ7jIINJqM4npXoLbsmF33Gqto5FBVy2GvRGo5b6e+cdzRmvs6bBe/dq66tafabx+vZ/9D8eCiCjZVUiqMHuCWzpUdWVNVOuwjICFy+Gxx8Ho5HDhyGhSzM5Dh3Up/ri8+Skgql169a1lO5JksSnn37Kp51E4EOHDuUf//hHl69hNptZunQpr7/+OjabjdDQUEaNGsXzzz/PVVdd1TIuKSmJDRs28MADD/DII4+g1+u58soreemll9qtl1q6dCkbNmxocx/r1q0DYPz48S3BVEfMnDmTDz74gJdffpmamhpiYmK4+uqr+etf/8rAgQO7fH89RXp6ek9PQdALEDoReIPQicAbepVOmkwXtqaaWZtnIifnqOlCqqcCc2EOAWoDgUotwVI1smRkFFtRVQhWq1GARtkf/4piivZU0Pckg6kgRwVp6m5kP6hQwtmpjiCXAVQQSRiVGGggiXz8ceOWA9na91pGOrdQ1DCABqIovOxmRl8F5zQbRPh4IAWnqJOO1jnt369Fwno9jB/fdp1T8zFLlmi25EFBUFSkBWCt8FRU4G5wgcuNTtGCrOZAQwJm8jkDyKE/uQzgEEHYCaABSVWpUiIJw0nn1mRHUdCxNy+M82w2yMnRAqm9TQ10LZajZhrNgdTQodq4VkFyZGpMl94yD20b+tYSQRgV+OPq0nkaq6sJbC5RBALyOilPPBmOHGm3yRefJycVTM2fP5977rkHVVWJjY3ln//8J9dcc02bMZIkERQU1GJR3lWuv/56rr/+eq/GDhs2jG+++eaE49YfU1/aGU888UQ7l7/77ruP++67z6vjfZnusooXnNkInQi8QehE4A29Ric2G54NG9m9UyH/cwuHQs00ppgwGLTv5Dt2q/RrHM14z3f4SR7Sddsw+Hk4rBtIiieLoUomFZ5IHIqB941PcHefTsrJvCB+4iC+G3cT/Ta+T2nIUCobBhDc4CRGqcTlCcJFEAXyAPqpOXwbfzOOCVP4yZrMFTUWBvSP4A9DLPhdfjdwd88EUidhoHDSOrHZtIDjwAFtPVN4uJZVysrS+jolJ2vXOnBAG3f33doxzzyjlfYdOADvvw/XXw+vvQZudxtjCL+Gug4zNSpgoIFxbEFBh67JzEFGwY0fDW5/Iry8BRkPhyvDOc9o1DJRFou2ozmg2rpVm3NzIBUbq41rbf6RbfW6aa+KFgA095pyEIAq++FQ/DB0MZhyhMUTetNN2lysVvrUZ3dbnymloqpdMOqLz5OTCqYMBgMGgwGAw4cPExMTQ1DzAj2BT5Odnd3TUxD0AoROBN4gdCLwht6kk62pZko+XobDGcB02cLmWjNVBhODVCujPMsoc+uoIAI9CgaPnTHOH+gj5ZGkHkGSQNFJ7FRHUFwRwHG6pZwQWYbwG6aRcyiHGl0EQwfKfBdzC3WVhUQWrcSjwpHKSMqcyexNnkZQEAy42sSgvuajduU9lY1qtglvLk87luZytQkT2jTuPWmdGI3wzTfwww9alqmmRlvj5HBophM5Odr6pfx8+M1vtHk98wx89x3U1UFurtZYNywMTCY8u3a1CQaOFxjITYVxOjx40AEqbvxwYCCMKq+DCgkY/tHDsHDd0SbAzc1/d++G+HgtcxYffzSQOva9bS5P7MI1QcuKlRLDZsNU0hxbiHTv7tJ5XGmjtc+x6XPtkxKEmt09bn6lV9xM/DHbfPF5csrW6McrjRP4Hs2NggWC4yF0IvAGoROBN/QKnaxfj3v9RjLXJxN8pAKXFEhhYSShuy3k6kcyRv2WWGUbSZ4KPEjIaiMyjbglf6KoAAlktRHVAzWEc759I2X7h2MynfyaqdHZFvYMjaD+sMwKyUxjqAlDrInPY4fjKrJxucFCYlwEVwy04LztbhJHGDu0Kz8ttF571GwT3nq9T/P+5kBKUbRxTf2p4BR08u23WiAFmjV5crLm3T5woJZ1crm0QAq0cXffrZUA1tVp5X2jR0NqqjZXux31mGDqeKjQFEKBDg8NGCimD078iaKcYLx3x1MjWn1mJpPW22r9es2NsLDJqa+kBObM6TBIbQiOwNtmQBJamZ+DoCb7CRV/Ry16nftEh7Y7T1xDLnz1VUtPL31CjNcZshOhW/cN3HRZm22++Dw5ZQs6VVV54403SE9PJzo6GlmW2/34+Z1yzCboJp5++umenoKgFyB0IvAGoROBN/i8TprK+3Z8X8u4n15hYN0O/OsrCWioRHEp/Kb2GwbU7aLR3kgATvqSTwj1eNBRSyiVOiO1hOKW/KlSIxjCXrbJ6VTqTiGgMRrRXTSBYSNkkh40M3CaiYAALfngDjcycJqJfg+ZSb9AJu7aCfQbafxV7Mq9orWVd3OZmiwfDai++Ubb/957RwMpWW5XpnbSOvnoo7avc3K0rsJ//nOHBgb8+KMWSAUGalmeyy7T5mEy4QoK71I2qblMDsCDDn8akfAQQj0qUtf6PqUkH31htWpNguPiQJK0PlmSpL3OyOjQNn1/Xb8uXA0a0FNGFAZchFLDIM8BDK7qLp1DBSRV1coQmz/X4uIuneN4eCZPbbfNF58npxzlzJ8/n5dffpnzzjuPP/zhD0RGRnbHvAS/Ev/85z97egqCXoDQicAbhE4E3uDzOjEatfK+d5cQ7/HHqJYy0A2lUhy1ko1EqYAgTz1RlKPHRR2h6JuMBULVGnQelWC1Fhk3EVIVm5jAKCWDSM9oTrZpL3BSTXNPO51loqZMgTVrNMOEF17QgoD162HUKK057ZQp7bIrJ9RJRgakp9PQoCVCyss1n4np6RMwvP12yzAVUJYvx/7lOkIqK1uCnjb4+UGfPlqpYSsjh+zaOEwdje8ECa1Mrp4ggmgAFJLIp5ZQdLi75IxndBVp/6e1a19JCaSlaZ+x0aitmTIa277XTcRssHh5JQ0DLhIpREFHCPUkevKQ6fp6pJoaaPnmP3Kk9n52E0bbAaBtZsoXnyenHEwtX76ca665hhUrVnTHfAS/MjNmzPDJ7tEC30LoROANQicCb/B1nSgKHNxQSIi9gQMMJlWFRAror+bQqPpTTSTRlBKEnQqisBMEhBJEA6okUSFFEUQdHvyQdBCmVrM+6BquOacbgpxjmuZ2tr/HaG2Y0BxQJSdrX/oHDtQCKEXR1vukpWmBVHq6Vo7X0NBmzdRxdXLPPXi++IoPBz7Gk3m3UVJyNBEyMziRZbQttZKBkIojLYFMa0MJVFU7OC2trZGD1UrwFx906fZVwI6BnYxgKPsIpwYVD+FUUU9Il84VNvOyo2Yaublw+PBRs4lmNz/Q3tuGhqNmGgBGI3XDLoDC7V5fT+sx5UFBRw0hhPnZqXZ3PSxw1bQKwLZvR1HUbjOgKHeGtLNZ98XnySmX+TU0NHDppZd2x1wEpwFfE6DANxE6EXiD0InAG3xdJwW7bPTf8C4JdVYUNxQ2LXkPwEkIdUT8f/bOPD6q+tz/73PObNk3kpCEQCAQdpRFcAHElWoLdY+116q312q1t9Xq1Wo3W61VvGr7q6DWqmitbaz7CoISZA/7DkkgCdnIMtkz+znn98d3ZjLZYCbBEm7P+/XKazJztu8588yZ7zPP83wemoihEzNeEmhBR6eedDqUBLZbL6Ao+iK2Wy+gU0mgVU9kNOUMT3ajRtb/tG9CmrIOaPm/grw8mDOnq2nus8/CJ5/AX/4iwmiSJBrSpqQIx+DTT0X/p9df7zb+fu2kqAjtnXdxVDdz4ZpHmF/6Mg6HKIVyOGDs8bV9Tt77U+BDVcXG+/YJxy5Q0/XAA6QdLozYEVBQmcp+Wkiig2gUhDMRS98qgP3u5+A+cY2cTiGOESo28a1vice0NPH6l1+K9fbuFY2Gi4sZNSN8xzo0YiajYcOFzxqNFW8EIxb7iGk/DlZrMLXT0dgZ0T5ONMadrkm9Xh+K95NBO1OXXHIJW7duPRVjMfgXcOedd57uIRicARh2YhAOhp0YhMNQtxOXCxpccbhckMdhzmIPTSTjxoobKzZcaEioyJhQSaSNBFrYqZ3FEcaiqnCEsezQz8IqubFYZe5qX0Lc8ZLBDSy0FqkvAn2Swmz78rXxhz/Ak0+Kuh5FEX2d2tpEXuLu3cKZ2rABVq8WzWi3bBHbxcV1202/dpKby1F9NIrmIYEWfs0j3Kq+jK7DrerL/JDnI3OAAvVctbXw8sviOh45AkVFyETuAVvwEkMn6Rwn4KYMJDLjaWiGkhJxfYYNE+MLOHvQJUpRWyuWr18vpNzXrYOlS1GaG8M+lgR4/aOUACse3A4VrxJZNE0HSB8m+nNdfrm4tgNw8PU+XpOAjPW9s96G4v1k0M7UsmXL2Lx5M48//jj2ofALicEJ+eUvf3m6h2BwBmDYiUE4GHZiEA5D3U6UtBReNN3NQTWP8RxmJMfIphIvJqJwEkMnIHGc4VSTQQp20migLXo4mqSwQ56FJik0xY+hNW0csRY31TMWkTF/4H2metUi9XSoeqrina75V0kJfPSRGMebb4pI1DnniF5PHR0iUrVtG2ga7NkjHKy6OlH0dffd3dIU+7MTpxMKO2ZRzkhM+Ej0O1RvaDfyax7BhqvPyXhfqMio2aMgNlbseMUK+NGPhJrfRReBbAn71HX/n4KKCR9RuPBiwYvJ73wrYY8LoMKcB+PGiShfY6OIQIWKTQREKTIyxPIZM0TKYnU1bNmC+7PCCI4GTqLoIMav7CfTqcRjVjsi2geAPsqvhDhnjniMi4/YmdRD/kJRYnu3XRqK95OInam4uDji4+ODfxMmTODIkSP88pe/JC0tjZiYmG7L4+PjSUhI+DrGbjAA3n///dM9BIMzAMNODMLBsBODcBjqdqKqsM+TRxFzMOMBdOJpI4kWLHhQ/W1DJSCZFryYUVAZP9pD2xX5SIu+RdsV+UycotCSNIbKjDkkfOfKQfWZ6lMVL3RSfQJVvH8p48bBAw90pfgtXy7qfWw2IfLQ0SEcKZdLRK7MZiFG0YdYWX928sH6FJ51381KvkEFIzHjI4EWLta/JIEWLBGkpklo1MSPh9RUMS6PRzT43bEDJkzAPSpnQJdBoBOFG5cURRtx6KgRORX69q3CKY6KgvPPFxGo+nrxXn/8cZcoRW2tWB4VJSJU6elQV4fcWBvRaKNxoCHjwIKDaOK1VlTJHNkpA+7Y5G7RM8fU2RE5kRqgYgqmHgacKi8Kyr0/6bX+ULyfRFxpdu211yJJp6q0zOBfTW5u7ukegsEZgGEnBuFg2IlBOAx1Ozl2DMb4iplu2sMW77nMYx0SGlbctBNHC4noSGRRDeh4sLLdfC7vJ9+FNy6PxCiodebxVmM+V1gLyBydyOTSgsEr7YWq4gUcqoAQQcCR6kMV71/OwoWij9Pvfiea5a5bJyb5Ho9I+fP5IDFRqOfFx8Po0cKRCQgo+K9Rf3ZSXAwH1TyWcTeKDDdofyeBNhQ0FFTcmDGH6VBJgFrXAJnxIjrV2QkTJogoj9lM1J59UNZPWmUf+/Ig+yfSGhoKzSRhJ408DkQcnYmzHxXXIidHpG5mZAixCRDRPbtdPA808F24UESDli6FLVswHbdHdEwZiKETNxZ8mFGVaPC6gciiU9q0Gd2eV0ePIzWC7YWIRzSxdKD7O1RJgC4pJDcfoaci5lC8n0TsTC1fvvxrGIbBv4qoqKjTPQSDMwDDTgzCwbATg3AY6nZibrPzaPs9jPHtw40ZFzaicKIio6DiwUwqjSj4AAk3VjxR8Uycm8LhRhF0sVphzJV5ZI/IZ3JpAfKF8wYfLSosFD2aFiwQ6V2qKibVIBypflTx/uUUF0NpqYiWbNwook9HjohIVEuLqI1yOoVaxIgRQkThf/8XvvvdbteoPzvx+v0kOynUkUY0DkCk1wFE+Z+HS0rtHhh7DowaJRy+228X41iwgNY3PqZ3zKx/ZDTc2DDhxYuVGDr8DZ0ji0oBKJdeLBym8nKh4nfggIg+7dvX5UDFxIjHSZPEeldeKdIlAarqoLo97OOpKMjoxOBCR6FGyyCehghHDXEt5d1f2L07ou1dWKhkJFlUkUBLMGXOrHtI91QCs7utPxTvJ4OumTI4sygqKjrdQzA4AzDsxCAcDDsxCIehbic58U2k6cdRdC9ZVAYjUu3EoSGTRTWxdKCh4MCGV7KQ7Gtgzhx46CGR5fbQQ3D//XDOd/OQf3TX4J0bu12o3W3eLNTv0tK6Lz+BKt4p5WT7LSmBJ56Ad98VDsl550FDQ1ctj9UqnKvmZlEvtXMn/OY3wsn685/F9n76s5PZs+EiqZDXuJm7tOeQ0NGBVuLREfU+4SIBzjHTYNo0OPdc0bA30GcK8LZG1mfJBMj40FBQ8BBLO8Op9ws8RFYzFedr7krvDKj2HTggomc1NeIxEJkKlXTPy4Mrr0RpjcwGJDRkNHQgmk46VQtRRK7EV+3qHoeSxozpc73+r0XvfNhgPVpSfK9lQ/F+Mug+U6+//voJl0uShM1mY8SIEcyYMQOr1TrYQxoMgu9///unewgGZwCGnRiEg2EnBuFw2u3E35BV7bPxLYyYlszvM+7m+0cfQgZkVOwkc4gJzGEzsf60JzcWijiXeJOLejmD+I6vufdTQO1uyxYRmZo1S+zbbhcRK10XJ9JDFe+UEYiM3XZb36mEATXBt94SE31HHxGipibhULnd4sLX14sUPxAhp3ffhQcfBPq3kykZdh6Tf84MTShH60iUkcNOZjKd7eRSHFEUKNrqFU5UXp5INZzXFUVsaYW0k2wfigRY8KFiArTgOCRUXMRioy3sfVVZ8hgHXap9hYUiEtXQACNHisfYWBGZuvnmrvekuBg+/RRdiqxIT0FHQ0ZGo4VEXJZEOjzxxEcY6bPs7e7cJFbvC/7frb9XP0ThZCTHiPF/zgK1Uz7JhhadQE9JkNN+P+mDQTtTt956a7CGSte7+52hr0uSRHx8PA899BAPPPDAYA9rMEDuvfdeXnvttdM9DIMhjmEnBuFg2IlBOJxWOyksRFu7jm25+XxRmUd5eVcpz+jRcPGIYqbvepUr6jYAMh4s6EACLVzARsx4g5LoNtzkUcxH+jW8HXcXj438GkUfUlJE+tYvfykcKRApfpddJh6PHxevzZ7dSxXvlBCIjJWVCSfp7ru7O1TFxaJWZ8UK4UiBqJuSu0eJdEB3u0UNjCpS37pNrENUCvuzk5GNO8hSt2HCi45ECwlsYQ5vcwMeTIzgGGZcYZ9adNYwESHLy+tWswVga6sLez+BSb9ofuvDjc2fGurFjEoM7d36OZ2Mllr/dQxV7SsrE2IZkiQeQ1X+Ro8W6/trpiSrFcLP8vM7OjqdWHESQ4zFS5s3kUz9eNj7kICk6oNizH77cP3kIdS3n8Hk77elAyqgYULGh0zPayJhxYVEV7NfHWiVEihryeXcHsccit87g07z27VrF9OmTeOiiy7inXfeYffu3ezevZu3336bBQsWcPbZZ7NhwwbeeecdZsyYwUMPPcTzzz9/KsZuMACGmgEaDE0MOzEIB8NODMLhtNmJ3Y62dh37dqtUPVPA0RXFuN1CaM7thiOfFVP1TAHbv+pghLMELxaOkU0zScTRSTROTPhwEI2KjI5EOsep8qVRG5fHzJlf8/i3bBHqGPH+VCddF7VJHo94Hh8vlgf6NoWc9ykhLk44Unv24PvTUra9WczHH8O2N4vx/WmpkDpvauq2ia5paHSXuZZ6PHaTwP7Zz4Lb9msnCQnokpiuaoCG0m2fUgS9oXQQ0uwBQY8e1yqxek/Y+wrsTwJ/RFOjlgw0zP7X9IgiZgn2I2I8oap9kyaJ6FRmpnicNKlL5e/VV+Hpp8X7X1eHLOkRpRWCiKXZ8GLFRU3yJFoyezfJPRE6YEtL6HYtE3cXEnAvQq+P7n/seU0kdEyoSCGjl4BkrRFt+45exxyK3zuDdqaeffZZ0tPTWb16NVdffTVTp05l6tSpXHPNNaxevZrU1FRefvllrrrqKlatWsW5557LsmXLTsXYDQbAokWLTvcQDM4ADDsxCAfDTgzC4bTZSUoK23Lzse+rRXWr3KAXEH+8WPgnx4u5QS9Adas0VHtYZr2XY3IOJYwjjo5gj6AOYmglkaOMwYuJKkawUP6CK5WV1IUfxIickhIhM97aCtHRIgphs4maGbtdyGFHR4vly5d31R6dqka+KSkQE4N2rJL6w3b2/W0Pe3+4lHdu+5i9P1zKvr/tof6wHc0tHLu+nKeToYFI8/PTn51U23LZGTuPTqJxEY0FD2exm5t4k7PYjY4ckRNhv+SGviXnAdO3F4e9n9Dz1AEzXlKwU00GXszUMjyicSVOyuhS8wvURjmdMGWKiPpMmSLe+0AtVXa2iFTV1UF6Oo7hIyM4Gn4XVEJGx4KHIuU8UqXwG/8GcKWP7JYq6Rk/LehGdpc6t/TZS0qspwbXD1xXGZUEqXea5FD83hm0M/X+++/z7W9/u89lkiSxePFi3vV/WGRZ5tprr6W0tHSwhzUYIB999NHpHoLBGYBhJwbhYNiJQTicLjtRVZCf+39MqfiYYdW72LFVJXlVAaYVH5O8qoAdW1WGVe9iTsPHZHiO8f/4MXPYShROFFRaiceESiItuLHyOjdTwWiizCr/1bQE36GSkw9ioIwbJwq8Dh4UYg12O7S1if/dbigvR6urQzt4EFdpJQd94/jk2WKK7ivg0NZ2vF/6G/mGW6zfM5pVUoL66QraWkE/Xo+puZ4xHXu4ovlNxnTsQW62ox+vx+kMiFkPkLFjg//2ZyfNcgpPmR7mKy6kTBmLiyhGUcEFbGAUFd0iGuHQuaekdw8v//nXt/duEnsihACGhOZPUovBQSbH2c50DslTI9pX4pjULjW/0aO7IlNpaaJerrRUpFLu2yeWV1aKerSsLJgzB19sckTHMyGiQj5MtJDIFO9uXK3uiPYB0JE3o5vgirR/D0oPq9BQ8GFCQ+4jMtX9MYAbK+OumdbreEPxe2fQzpSmaRw+fLjf5YcOHULTui6q1WrFZrMN9rAGA+Tee+893UMwOAMw7MQgHAw7MQiH02UndR8VkbvnXSyeTsa3biHPtQtJU5mhbUPSVPJcuxjfugWLt5PF6rsM12pw+8vd24nBSdfEOoUmbLj5h3IT0XEK+0YvwjRh3Nc3+Hfe6Yo2HTokameam8FmQ7fbURuboKxMCCAcK+GFyX9i6/0FbPu0no6PvuRnL+bwxvXvo113A/zoRyc+VmGhiGaFRGhITuaYcxiS04Gi+8ihjBHaMYZrNSRpdjKoQdd1NF/4KXY9UQGntUutrT87KS6GPMcu0qV6vpIvQkNCAhJo9Uc+IpvKdvhsItITcKhCoirOyLQXkIB2YqliBK0koCOhoDKV/YzSIgscuL5c3xWZKivrcqTy82H8eOFIK4pwuLZtE8t/8AMx/mnTiNq3LeyoYMD9lNHxYKFYnkD8yESaYkdFNGYAKcQhBlAS49H9KoEBZDSicQTVA3vS1zsoAVSU93p9KH7vDNqZWrx4McuWLeO5557D5eoqAHS5XPzpT3/ihRde6BaS27RpE2N7XHiDfx13B/oRGBicAMNODMLBsBODcDhddtKRnss2eTYqElE4mct6prMDWYbp7GAu64nCiYZEOTlcL71NBaOpIZPj0giq5BwqpVG0kIQPExeyjsvMa3k1/UHKr7qH7OyvcfA9enrq7e142xx4axvQvV5k1dtt4nyf/igpWj0XaqsZRwl31f+Ki9b8Ckd1M9o77/YfobLbRZPd9vZuKW8eDxypj8ODiTjasOAliypy9COMopxoHMTQiQ/zgE9RBrau7krj6s9OEhtK+L57KXn6Ya73vgF+aXS3P21MjkB8AiC9YpP4JyBAERJV6YyORMtPOIQeLOzkbD7lShpIxefXdsuIsGeTY/z0rsjUzJldjlRenohUPvKISPFTFOFYr1oFU6eKhsNvvokWnxh2jC6QfqchY8FLJjWMG+kmbt70iMYMkNzU3WnU4hLAH4HqqpnS/VLs4aWBirRAM3srEnotG4rfO4N2pv74xz8ya9YsfvzjH5OYmMjo0aMZPXo0iYmJ/OQnP2HGjBn88Y9/BISDFRUVxU9/+tNBD9xgYHz11VenewgGZwCGnRiEg2EnBuFwuuxETUzhfnUJmzgPGY1YOriQQq7W3uZCComlAxmNXUxDQsdskUmUW2gjnmY9CQ2J9dJ81jGPVikRWdI517uOS1yf8k3X2ygnUqIebC+cW28FutciKU31yG3NfaZJpdDK1fyTEdRgws1IKkmgGUXzcFQfDbm5fR8nEAnZvl2IGvgdqq1bob4zBh8KEhomfCioxNOGFTcW3EhoNJMQsehB6Ljbi2uDz/uzk6QksOAmGgcpNDGMRrwo1JOOFwUr4ddpASjTQxyGHiqIqTU7I9iTOG4UTi6mkNEc5TjDqSELkGmzDItoX3JMjBjPvHlC/CPgSAVYuLDLoZIkke73xz/CCy+AqqL20a/pRDiwovnrzUbp5XDOLDJnRFbnpQP2kTO6v1ZZib8irlvNlOx3gk+2/8ByJzb2u3rb7VD83hm0M5WcnMyGDRt4++23ueWWWxg/fjzjx4/nlltu4e2332bjxo0kJ4s8TpvNxksvvcR3vvOdQQ/cYGAkJUXS29vg3xXDTgzCwbATg3A4XXaycycM89TQwDAaEY1FLXgYQSUWhHBCI6kcYxTbmUkCLcREgcOUiCop/EO/kXopjWrLGIqt0+iUYjkWPYE56kYm/eF2MZHti5dfhhtvPHl63Ylob+9VixT4hb8nOmDDQwb1RNGJDQ+aX1ignJEUdszC2bMXbaBGKhAJmTRJiBr4HaqOVZvweYWogmiSK/mrgkSEQUgGKJhwR+TI9CT78Mrg//3ZyYSJEKu3I6Oh+Kf/0bhoI9afOhYZUScoizL5wo9yBSI7NtxY8DCTHVhx45Zs1JBBtSUyQQi52R/JWrBARMz66u01a5ZwqEaOFGqOX30l6r4UBW9uH+ufABMe6khDB3bEX4Rp+jQcSVkRvZ8SoO/orrhndbd320eXqITeWxr/BMTTTtSh3mp+Q/F7Z9B9pkAITVxzzTVcc801p2J3Bl8jWVlZp3sIBmcAhp0YhINhJwbhcLrspGavncXae4ykkgaGEU8LVjyAhBczbiw0MIyRVOLBjCqbaUsYQbqpjeVpD7DJu5D01mIWOQpwOhPwKXHEnJ1Lyp5NyDYb2h//iN0VS+Pi73c1AV7+Mjz6qBjAp5+KCNXs2ZEPvqMj7FW7Cvh1JFR0wIRKDRms5Bu85L6b2PUp3Hijf8XiYiGrvXChmLjn54uIFAiHCkjduZJcNhBDBz4UzKhoyCioCJdOQ8VEfARNafsiu21v8P/+7KR0VTnjEd6g7j9PBZVp7MWKN+JjHncmMbqfZZGej46OFysmfLSQyDDstOrxtBJPoqs+sn01N3c96atvWGGhSMnMzxfvW2iE5oIL8MSOhq8+CXPc4MNKIq3UMYxUvY7hv/g++8sj1zRQ1n0JPBh8HpO/iJYHk0iiexT1RE6vFrK8K5olkXZOTq91h+L3zqAjUwZnFitXrjz5Sgb/9hh2YhAOhp0YhMPpspOYGJENBUKsIIru4ZkonMHXJ3EQc7SFOL2NguQ7qZq8kDlzIG5mHmVps5lhO0B6tpWz2jfCpEm4NDNtTRrao79j9U0v8/DD8Nn1L+N66BH0pmZRdPTznw/MkQLUqNiI1u85aVWRaSSdT7mSg2pel7ZEcTE88QRs3gzvvSciUwExhrQ0IbleVMSY0s8ZQSUKKgoaPkyoQUU2EZWy4iSaniGvyPDe8sPg//3ZSbE3h3rSUJH9PawkLHiIxuF37iLDVV7b77JYLXwnFv9YHETj9V+bDmKIo50MjpPgi0xm3Fpf1f/CQG2bqsJjj4l6qVBWrSLlrcjaDokaJh8Z1JPdcZCjxWrEaY4ATWdd3O35xjeOACdP5wugIerOQiOxEiKKnOvs3fdrKH7vROxMjR49mtzcXLxeb/D5mDFjTviX21+u7gnYv38/119/PWPGjCE6Opphw4Yxf/78PiURDx48yDe+8Q1iY2NJTk7m5ptvpqGhd+Hf7373OxYvXkx6ejqSJPHII49ENCa3282DDz5IZmYmUVFRzJkzh1U9DXqIc999953uIRicARh2YhAOhp0YhMPpspP5V6fwkXI1PhRGUIXir/1pIcFfA6QxgiraieVN+WYyc20knDuJ+amHyHYW4/HARKWYqzKKSJ47idRhGsTG0lCnst83HkeHisepsXjv77j+vRuZ8eEjqPYWVKcLLWc0XHXVgMde3RE3oFqkUJnpFuJYQCHj9GK8XroiUmVlXRsE0v3y8oTjV1YG9fVYVYe/maoQ/ZbR6CCWSkbSQSwKKmbUQf8in2LvUhDsz05cI8bxJ+WnHGEMHQj1PzmYciiI5Fq1jD+v32VKBCcUiKBE4cCCl2E0Ek8bHcRxnOEckcdHMCpwLDpBCUxKinB4jx4VTlVtrZDInz9fPNbWwpGy/rfvAydRfhdZRdOgs8WNk5iI9gHglrtvc7g+CQVv2Ol8OuDC1queSge02Phe6w/F752I0/wuvPBCJElCluVuz081FRUVtLe3c8stt5CZmYnD4eCdd95h8eLFvPjii/zgBz8AoKqqivnz55OQkMDjjz9OR0cH//u//8vevXspKirCYrEE9/mLX/yC4cOHM3369AF5trfeeitvv/0299xzD+PGjWP58uVceeWVrFmzhrlz556yc/86ufXWW3nrrbdO9zAMhjiGnRiEg2EnBuHwtduJ3Q4pKaiqaL3jdEJUFJjNMMl2hCkd+4M6YhWMYrc0g7P0HeRQgYbMJA7ySfR3aPvhArIqt5DhVZnSUUDHuOnEluwkYbyKbE6DiT+m6Tf/j+iKQ1j0UezXxjOBw+jAbHUdsbRhwo1Hk3F3KAymsmPLgXgGUjgR+HVfRuM8tjCKMjKkOiZJ10DBTtGXaJq/d09Skkjvy88Xzz/9FDo7QdeRo6woaEjgj0xJ+FCwk8wwRPqagm9Q9VKAaETspz87GTECfmi9B5dD5kGeIp72bpPugFMTLjmlK4G+69nUq65FiqDhsajj8qCgovrdu3YpgV36WVRIozmfDWHvy+M5yQplZUIuX9dFyHXcOOEAl5fD8ePopsiUFXVkv6OsI+Pjz8pd/I/2GL2K9U5CaV0sZ4c8j6orx0ZXM+eT2UhA2l7DhITPL1YhnL1yPYeelWdD8XsnYmdqeQ+5zp7PTxVXXnklV155ZbfXfvSjHzFz5kyeeeaZoDP1+OOP09nZyfbt2xk5Ulzy2bNnc9lll7F8+fLgegBlZWXk5OTQ2NhIampqROMpKiriH//4B0899RT3338/AN/73veYMmUKDzzwABs3bhzM6f7LGGoGaDA0MezEIBwMOzEIh6/VTgoL0dauY1tuPl9U5lFeLialFguMbyviF65fEEszXkzs5Cy2cw7NpNBACjPZygQOE0snj7h/Bu9fCT+8CbmoiKR4laS6bRCPkKKePRvt7XdRy45hUnVGUo4KOIgikRaicGLzS3T7sOA41kh8QxNKoPbF7/D1S4/lI3a8H5Gj0tek1YKbXCpI1D/CXDsMsqLFuQSkpQsKRNrY0qXi+KWlQiJ9+HBMWdmolcf8iXUiEtSVUieFNUkOh4accxju/78/O0lLg5+ZlnAXT2Dxi2sE6t7MeJH9r4SLNL7/iFFTVScneJd6ISbRqt+lMtNBHE6iAEjWIpNG91TV9b+wpASWLBHOcEaGcKTGjBH9psaMAUB66+2wr4MEJNOM5G84DDL11mxettzDo+0/iWjcTd64bs/jpubgLLBgwdNtPD1tJuAAayhE4UbzJ5WqQBQeZDTaj4XUkfkZit87Z1TNlKIoZGdn09LSEnztnXfe4Vvf+lbQkQK49NJLycvL63XBc3JyBnzst99+G0VRujlnNpuN73//+2zatInKysoB7/tfSWjPLwOD/jDsxCAcDDsxCIevzU7sdrS169i3W6XqmQKOrijG7RbBDrcbSop1fLqCBDRK6exjGk2koOvQRArbpDnsNs1EkUV6V1T1ERGdSevRaygtDT79FPfO/XQ4TbQj6pnGUUwO5cTSiQ1XUD7ci8xG7yyOdQglYwoL4eGHuzfFDaW4WCwPRER+9CNmbous/gXwa+wFJnY6JlRkdFJoIqHFnwI2fbpI6QvUSbndsGePGENdnaiZmjOHhrlXc1wa7o+2CPcpBgep1GPyR6S8mPENchrZtmlf8P/+7CS5tIgH2n9FMs1E04mOjhMbbcTj9KeHRULMvs39LlM7OsPeT5dzIOHDxBHG0kgKzSQwnmIW6IURjSs66gQLx42DRYuEM/zII3DDDd2X33ADzf95X0TXQkT0RMTxBX7AOutlmNXIauB0IEFu7/ZajLsZS4+opegLZu0VURTLdFz+ZUIhUuCSYogb2Tu+OxS/d06JM9XW1sYTTzzBwoULmT59OkX+/gpNTU0888wzlJZG1gU6lM7OThobGzly5AjPPvssn332GZdccgkA1dXV1NfXM2vWrF7bzZ49m507Iy+k64+dO3eSl5dHfHz3/M3Z/uLSXbt2nXD7+vp69u/f3+1vMNdloPRVc2Zg0BPDTgzCwbATg3D42uwkJYVtufnY99WiulVu0AuIP17MsWMQf7yYq6M/pyjuUqqlLI4MvwDLqEziEhWOJs8iLlEhfmQSnrGT2T1sATVj52ONMcOWLfDSS8JR06CtzI5j2XJcX22h021mPeezmdn4kLHhwYwXC26AYBWPGZXdrvEcrE8REZ8HH4S33oIHHujtUBUXi9ffekust2oVvPsuijwwseXQmqlADYoXE6T74z87d4pjlpQIh+qCCyAxERoaIDUVxo6Fu+9mb8ZCtkvn0Eyif6IrYcZLFjXE0oEXMy0k0EzvpqqRIO/dHvy/PztJtx/ArItrLPvPrp04vuBiHJxA57wfokcN73eZHBN+zVCXMyAczhg6sZNCul5HFE68phN5R30cOyP9xCvcc4/oKTV6tHgfQ9m5k87w/cAgGhKdxDKRQ0Q77bQoqWFn+elAK/Hwre7OTaZeiS34mQgoB5pwY0VF6eXw+TBTLY3EiY0onJjxoqJw2HYW2dOSex13KH7vDNqZqqqqYvr06fzqV7+iqqqKPXv20OGX9ExOTubFF1/kT3/604D3f99995GamsrYsWO5//77ufrqq3nuuecAqK0ViiwZGRm9tsvIyKCpqQm32z3gY4dSW1vb73EAampqTrj9smXLmDJlSre/q/zFqevXr2ft2rU89dRTNDU1ccsttwBd3ve9995LaWkpr7zyCu+99x5FRUU8+uijOBwObvD/OhFY9+GHH2bv3r28+eabvPnmm+zdu5eHH344uM7DDz/MDTfcgMPh4NFHH6WoqIj33nuPV155hdLSUu69995u+7vllltoamriqaeeYu3ataxYsYKlS5dSXV3NnXfe2W3dO++8k+rqapYuXcqKFSv+ZecEGOd0is9p3Lhx/+fO6f/i+3S6z+nhhx/+P3dO/xffp9N9ToH7yak+p+997xbUZ59k4tG/k1ixmq2bD5P4+U8xrXiNxM+/y85tKrGtH5Gm15Fc9xnDhneyM89L0/kmymaPRpc30azb2Os+gufWH/BlaQlUVODYuxf7B6v551s7qHh3Ja2HK2jcf5gd9kz+qpWTSTXRtPun0OBDQgXcyLiw4EDlNu1lNvznNDhyhMY9e9A0DeeKFTTdfjurli7llVdeoWLVKvZccQWsXSvmTTU1PPHkk7inT8enhV+PFJicynRv8qsi4wPq5Axe3FOKvaWFndu2UXH77bRfcw3r5s/HU1jIvg0bIDWVPUeOQEoKTz/9NJ9vr6FGa0NHpYVYNL/LYEbM7zQ8VJFBDL3TsCJhb3t18D19+OGH+7S9vxw8gBtLV/NiNJpJopAGFDwRT2R3KEq/tudraYpoX8JZlfGgkE4VM9mCzBE0JLbo1RGOLIzPk67zxqJFoKqs+vJLyocNY8/+/ezdtQv7p5EJognhhyjcOBhOHQs6FnGT9yVcYVYACYfdQ82+97vdI/7+1ctBOxRKfTJOLLjRcPVoLBzoO9WgV2NC9Xc0E0Ixk7ybcVZv6vU+TZw48Wu/761fvz6iaynpuj7Q5tUAfOc73+GLL76gsLCQtLQ00tLSWL16NRdfLKQSH3zwQT7++GP2798/oP0fOnSIqqoqampqeOutt7BYLDz//POkp6ezbt065s+fT0FBQfCmHeBXv/oVjz76KM3NzSQmJnZbFqiZ+vWvfx22ol9ubi7jx4/n008/7fb60aNHyc3N5dlnn+Wee+7pd/v6+vpeCoOlpaVcddVV7Nu3j8mTJ4c1jsGyd+9epk6d+i85lsGZi2EnBuFg2IlBOHxddlLzfhFRN12F7HTQSRRbmMOekFL4WRQxn68w48MnmVky8VWOnXMdUVFCpMJcVswV7QWMG60yObMZua0F7dNP0VraaZMT2WWaRbLaSIpah11J55CWxxRvERMpDjaxVZHxYEVBxYlo1jqWoziIQUpKJGnFP2DvXvjlL8HhEMIBF14I//Vf8Je/wNq1QlAgOlr0p/r+96G4GN+FC1CO9y/h3R+B1DMRDRDyEQeZyMHn1nDjZXYhq71unRiLxSIUB48cgepqOOssUX+jKHzSOIeUP/2akXo58bRiw40XE20kYMOFjIaKjIKPGJwDqp/SgZacqSSXCfnr/uyk+rVVpNy6qFsEMBDpiKGzz0bGJzpm26KbSPzwb30u33v/ciY/fVvY56Mi4cKG6h+PBwsKGk0kodhM5Ln2hrUvHai/85cMf/63/a9UXNxV56YoIk0zLy/4+upXK7io7OWwnUsNcBCNhsJnXE663Eyi1sxUdvZweU68j60/fJVzl90afE1dsQrtm9/EpHlR/dLxbSTQTDLp1DCMpm4qjC0kUs0IUqknmaZgGqkOyJ9/Dpdd1u2Y/4rvnf379zNlypSw5+eDjkx9/vnn/PjHP2bSpEl9qvqNGTNmUPVEEyZM4NJLL+V73/seH3/8MR0dHSxatAhd14mKEiHUvqJPLpcoBA2sM1iioqIGdZy0tDQmT57c7W/s2LGnZGyRsHfv3pOvZPBvj2EnBuFg2IlBOHxddtKRnss2eTYqElE4mct6prMDWYbp7GA2ouRAQ2KHeQ76hRdhtYLLJer4x16ZR/Z9+Uwe60bubIctW+iMz8KhR6F4XUxw7UTXNA5bpnLElMcl3g/IoxT8UuEqMi6i6CQGL2ZsuBhNGTIqcbRhH3++UFvLzRWPNptwnNauhZ/9rMuRstm61gOoqcGVmjUgafRQFAI9mby0ljV1qcG1tUFTU9ekfNw40cA3KQmam0FVmdK4hnY9hjjasOH2O44KjaTgwYINF1G4sA6yz5TlgnOC//dnJ6VxM6iVM9GQcfpra8x4iaXD3z44MjU/V1b/7XpiD2+NYE8EHTk7idSQgY6MgpeRVJDmikyqPGbnuv4X2u19O1IQrH9L1hvDlooPON1RuPAh8w1WMUxpJob2iB2D5PMndXuunDMD3RrlV+XTicKFGyt7mQohcvaBcehIxNGOCR9yj75hhz88jNqjldhQ/N4ZWFJuCE6n84TKeO3t7f0uGwjXXXcdd9xxB8XFxcEUu0C6Xyi1tbUkJydjtVpPyXEzMjKoru4dsg0cOzMz85Qcx8DAwMDAwODkqIkp3K8u4XHuYS7riaWDCylkjHaUbI5hwYMHC5s4j/+Rl/Lm3SnExHRJp2dng6LkwTfuh7Q0NE1Dxkqgi1GU3kmqVk2rN5qFfE4M7m6RHxkNN1YOMpHJ7CfaHyXRkGgnBtN9P+5qtnr22WLQ69eDzwdV/gatJhOce65Yvm4dZGXBunW4HQygGqhn817d7/BZmVPyV9i5AVpbhfx5oG3MlVdCTo6YqEdHC2equZmMVCsmDvgdKQ0NBQ2ZBlLJohoVBQUfOgoMoHFugHoli5O1J1ZV2KtMJ1ZrA3QseAl1FyJWFswZ0++i5I5jkewJHbDiYQS1NOOiExsJuInGEXE9l/WevuXaAaH0OG+esJFQRypAXh7ajf+B+sSHKD0clr4I2LCERhRuGhhGhtXOltxrGXvo2YjGHd9WCYQ0py4sxORsC6nf00nBTiZVRNM9KCEDSTRjxU0UjmDaH4APmXcPjGeUX71fCTdcdhoYdGRq0qRJfPXVV/0uf//995k+ffpgDxPE6RS/grS2tpKVlUVqairbtm3rtV5RURFnB25ep4Czzz6b4uJi2traur2+ZcuW4PIzASMlxyAcDDsxCAfDTgzC4euyk507YZinhgaG0Yj4UdeChxFUYvH3uWkkVfRG8tSwe7fwGyZOFI/Bydkdd6Bpmv+XejdWnJj8/W5i6OR81hITMgkMTN7Fn0YNGUGBacDft0cnQ6/taraqKAHvjeBP7YEoQ+D1/HwRJcrPR7M3RuYghBDq8FnwkIKdcTVfCZGJ2lrIzBRiE48+Cpdf3qXspygiOgW0bT1EIi3+CJyCGwtljAFkKsgJSm8og3CkALTKrh+p+7MTq1UE8HwoxNOO4pdICNTlKETmTFm29h8Birrp2gj2FDi+igkfKTQwjCai6QQkzDgi2lf9xpOIki1YAHfd1duR8tMw+SLaiQs7rVBFQkPB7O+Ttdk8jxinHbWPPfRsqBtAQyJ1enb3F3uIq8n+xs85HOtTgEJ87hz+TnBdxysmjw86L2PVKtgQ0q5rKH7vDNqZuueee/jHP/7Bk08+SWtrKwCaplFaWsrNN9/Mpk2bggVhkVBfX9/rNa/Xy+uvv05UVBSTJomw4rXXXsvHH3/cLZXwiy++oLi4mOuvv35A59TY2MihQ4dwOLo+CNdddx2qqvLnP/85+Jrb7ebVV19lzpw5ZGdn97WrIcff//730z0EgzMAw04MwsGwE4Nw+LrspGavncXae4ykkgaG0eFPtwv0IOogBjcW5lDE97RXqNlr772T4mLRq8ePqDICGQ8gEUMroa1QA06UmBDqWPFwPpsw4/MLkYvpYAxOWp/092/KyxNpfKtXi8iQ1yu8A69XPF+9WiwPSdvyJqRFlLrWc91A6puMTibVKEcPI2QO44Ua3FNPifqsAD0cKqc5wb8fGTc2KsnGhWiw68JGNVl4MQ/SlYKaaV39RPuzk4QEcEoxROPAjDf4uupProo0HbLl8hv7X1bVEdG+Av54QJI+hk4khOO3j+lhj00H3imbcfIVT9CrbPinfyGRtn6XhyKBv8ZLCOgn08TI5t2UV5vR0buNO5CK1xcKOmpza7fX2i+7hg6ig/uQgHjaGU4t8bT3uaeezogETOAQM5pWUV8PmzZ1/QYxFL93Bp3m9x//8R9UVFTwi1/8gp///OcAfOMb30DXdWRZ5vHHHw+q1kXCHXfcQVtbG/PnzycrK4vjx4/zt7/9jUOHDvH0008TGysCww8//DD//Oc/ueiii/jJT35CR0cHTz31FFOnTuW2227rts+//vWvVFRUBJ2kr776isceewyAm2++mVGjRgHw3HPP8Zvf/IY1a9awYMECAObMmcP111/PQw89RH19PWPHjuW1116jvLycl19+eSCX7rTw+OOPn+4hGJwBGHZiEA6GnRiEw9dlJzEx4PV7Ngm0EoUTLaR0PhoHw2igk1jyKMHsLIXQlqz+wn1t7lz0iopukzwTkEhLr4lf98mxhBU3yTQho6EhoyJjwUcn0VTLo0kLHOf554XIA4gUu+xs4dx4POL1558XTk5eHrz8MqkVWwcs6hDYTkMKRsmUznawmUS91MUXd6UdhpKXJ/pQbduGmpPL7nUzydP200oi6dQTSyctJJFIMzF00sgwEtBJJjIHJJRhLV1RjP7spKMDzta3ExdyHBUZB9HE0IEpbDFvge2t5fCDy/pc5muNXF+85/ukIVFNFqu5iBmE16JHonuU7kSoKlRW9kxXBduN16D9/WdhiUfoQDXZxNJOGnU4iMFBNPN9KzD1OCfxEdP7Tac89sEOxl55GaoqsliX/jaZu5jJ+azrti+rP1rccxz9NfaVgbyGdTjOv4yjR8U55+QMze+dATlTc+fOZd68eVxwwQVccMEF/PznP+fmm2/m3XffpaSkBE3TyM3N5ZprrmHMmP5zU09Efn4+L7/8Ms8//zx2u524uDhmzpzJk08+yeLFi4PrZWdns3btWn7605/ys5/9DIvFwje/+U2efvrpXvVSL7/8MmvXrg0+X7NmDWvWrAmeU8CZ6o/XX3+dX/7yl/z1r3+lubmZadOm8fHHHzN//vwBnePpYNGiRUNSo99gaGHYiUE4GHZiEA6DthO7HVJSek0iL1icwn2/uZqpvl2MoMpf1aNTTzJp1COhE42DDmIplcezUP0cipO6KaChqnQePU7P7kIncmRCI1MmfET707l0wIOVRuL5iguxz72P6SD6SK1dC7IMsbFw/vkwYwbs2AEbN4oaqrVrxXp33w2PPIIkm0Dz9jeEfscUGg3AL86gIaPGJ2H2dojI1D//Kf5uvVX0LgpQXBzsXxQbC2tNl9DhsTGVvcjoxNJJG4nE0onkr136hEXczMAjBcOKPgIeBPq3k+GHC8nyHQ4+V5GCUSkVEzKebrU2J0NJSez1WsARaC6Cxb03CYvAe1BPGvUMZxr70JD6SGzrjYaMKyXrhOsExrh+Pezf3/U5mDJFtAsbf3BDtwjPiRwVgDSOY0JD94vqB+y3L6epy+a740OGI0dRvyjkH8cXsHo17NoFk9kfloPR13FCKYk6i2TdTrMnBX+Vz5D83hmQM3Xs2DGefPJJJElCkiQmTJgQdK6uuuoqcnJyBj2wG2+8kRtv7D8UG8rkyZNZuXLlSdcrDHQXPwmPPPJIn5LpNpuNp556iqeeeiqs/QxFhpoBGgxNDDsxCAfDTgzCYVB2UliItnYd23Lz+aIyj/JyEcyxWET611xlAzN8O5DRAIkKRrFbmsFZ+g5yENGmVOrJlqswSTnCgZo+XTgNqgrNzXR6LL2cqf7oSy1NCrZtBdA4wGR+zu+5e1QeHCkSjYADqn0BsQkQDpUsw+bNQmJwyxbhTGVmoh9vQNciqwUSE14pOJZA36lmkonNyQWXX9HPbgezGZYvh29+U9Rp9ZDdrho+ndG8xVhKUVHwYqJOyqRDiqNalxmm13OcDK5kRQQj7I0y/azg//3ZiWn6NFxSNDF6OyoSOkpQGt2EDwVvWA4L/uvhu/Kqbq+pKvzjHyLb8qyKgZ6JwIuZVhIBnU7icGElGtcJ30cdcGJl5rU5/a6jqvDmm+Lv6FFhTpIkHnfsELoUD+TGiUgofTs+XaITgecaUTiR0bDhppoMvJgZx9E+t+3rHCSguiMB5c11bHJMxaGlsFj6iJQe8ucncur6w4eMxdnGpLXLaJ48j6ioBcDQ/N4ZUM3UsWPHOHbsGH/729+48847sVgs/OUvf+F73/seubm5ZGdnc+ONN/Lcc8+xa9cuBtnKyuAU0rMfl4FBXxh2YhAOhp0YhMOA7cRuR1u7jtI1FVQ9U0Dpp8UcPizaIh0+DKb33+Zez5KgdPdeJrOayygmj9Vcxl4mo+DDhoc56kbk0oNiVrptW9CRorkZ65EDAxqeDxMqCh4s/pgYmPFxDlv5KU8zciSiFuraa4VSXsCRUhSYNUs8nn22eD06Wqx32WXw5JO4MgaW1SOFSIUHJsAxtNOYMUU4brouHDdvSNSrj/5FndnjyZNKUCTRRrWNeEy6h+FaNU7dxgEmoUoK2iAF3BOddcH/+7OTtAnJdCgJ3Wp3dCScRPmfhz8GCbB+1f3H9/XrhSPlcMDO6f+FN+wuS90JSLYP5zgWPBQyHwvesJT1rHjIS+u/AfLatfDSS3DokHibTKauP59PvP63ddk9IpO9r0zoWMTYNP/rOh6sJGCPyIFX0Ig9spPPE/Mpa0th/Hg4T+8u8HGy6NOJmObYTKtdJa9+HdnRouZxKH7vDLhmasSIEd2iRx0dHWzcuJENGzawfv16PvnkE/75z38CEB8fT3Pz4LpkG5wali9ffrqHYHAGYNiJQTgYdmIQDie0kx4pfJ5aO5aMFDIzoaY9Bf2j3WTuXk2FeT5jdDjovZyt0hzyKGaYvB2fLhGLlyaS2CxdQLOeBDo0kcIuZpAh1ZOh16ArJkwdrbSV2XHHpmDtsBNrr0DubEeXIp88S4jamE5ikAEVBRtOfzm/m+/yN8rKrgMugx//WDgvGRndewTl5Qkn5uyzIT1drAdCbS8lCWmALTq7aqa6BDWC02qTSUTIJAnmzIHkZFi2rFf/ouEKfJCWz2W1y7HhxqZ2kqw3U08qw2hAkiXs1gwU56GBDdKPkpEe/L8/O2n4fAdJahM6EgqaX4VO8p+j1O2cw8Gb0NXOR1VFpmV9PcycCc6/FfaK4ISDDyXYIymBFsZRzO28gKkPiQ6N3pEMEyoNBWvIvnp2LwlwVYW//11EpEymrt8BAtGpQPuyuYde7KPWqW8CDlzXcx3F/xcp71puorEjj9RU4a+/MGoJ32pajjlE4RIiv6YmNNI8FdTKI9g6Op9v+cU3huL3zqDV/ALExsZy+eWX85vf/IY33niDF198kXPPPRdd13vJiRucPp5++unTPQSDMwDDTgzCwbATg36xi1+RVRV+8YunOXgQysu7FLmw20UK33PLKHqjmCVL4J3/LmTvXcv4/W3FLFoEf7vmbVJ3rkTyeTjHuZbZrjU8qj7M//h+z7W+AsZ49mPBiw+FBKmD0WmdxCUqHE2eRVyigmVUJs3pE+g0J9ARlYp372EaPiui9LNiGj4rom3DXjqONSFLkWnSBaabMjpmfDSRgAcLBCf2Gi45hgkLc7qarfZ0pKC7gl5GhlivpAQKCnD7Ip/WBmqmAhNWrz8Vrt48gtTj+yExUVTwjx0r9OFLS0Xz3nnzeo0tJweazr2SI6YJdEjx6LLCESkXjxxFuxRHmlRPmq8Wu5zW51jCJioq+G9/95PSuBlUkxW8uqJ/lol24lEx9TtB7/f65Y4N/ltZKewy4AjUWbJPuM/+juNDxk6Kv/4IYnEwgeI+13WGKN2F8tkK+Otf6dWktrxc1CE5HKJOqrVVRKNUVTy2torXd9O7DVE4UbGA0z2Xtdh69IE6GTpgsUl4PF1v5aiKwj57XQ1EUEVD5qPofHY78wiIdg/F751Bq/kB7Nu3j/Xr17NhwwY2bNhARUUFVquV6dOnc99993HBBRecisMYnAIWLlx4uodgcAZg2IlBOBh2YtAnPeqcysoWsmSJqHMaPRouHlHMrL2vQn0dxdUxVH1QwHHr5cxsXIfeWMFYtQC7PpsYdTt12jAyOI4JL3PZyHHSUNBwYuU8Nvn75ZioJBtLZirOqfnExubh7MhjdMmryCVeWuQk4tydqJJCtLueWJ+NaFc9Ps2LerwJi6PupKcUIHQSHOh3VM9wNBSicWDCB+g0Kakk6HpYzVbJzxeO1Lx5on5p3jyszyyL6JIHxuXFjIIPkKg25eLVFSwJMdhs/hUWLxZqBUuWwKJF4njjxsHUqd1kt5UWO/9d+xA+7zaqtAy+1OfTLici6xoz2YamwjC1hkQaIhpnL6K7Gtv2dz/R7U14dRMeZEx+dzEaB2nUdRP/CHfyLh3tUhB0OunmCFgsIPl7jEWa7qag0kkUcQhFwP6E4/vrzXW8I4YXHhZ+deilKCuD48eF46T5hQs9IcJ4qbKdZi2Fz/WFOIgiBmdYY+5ypCQcWGkknTEciejcXdgom7QIq4WgQESqr9af9CqIuKlyyHZvRf0nVdF5eGuFqiMMze+dATlTa9euDabzbd68mZaWFtLT0zn//PO5++67Of/885k5cyaWQIdtgyFDdXV40psG/94YdmIQDoadGPQitM7pgwJKY/Ipaa4mOVn88u87UExeZwFJ8Q2kNJWSVnqEUutFjAKS24q4QFvHNmYwg0LaiSEKF3UMI51GTHgZRSWJtCL7lfRkdCoZwQp9IZul27BKeURpUCLlUW6+jfvcq8hwH6FDTgYU7CTT4paQiCONejq1BNIJXzUPxMRQRcKJjVYSkNCpYiQerAynjmg6yPJV0HT/Ywz/27OwYEEvZ6UbeXmiGWtg+YIFqLMvgM/fCWs8wqEEDYUmUnAQRT1pDNNaGK2VInnikHzjhejEhg3CmXrhBeFEBeg5tqYmYo/uwae3YdGT+Ds3Ua6NJp8CtjKLuazDigNrhJGMXqR1Rbb6u580aslMpg4rKm5MfodKJ4ZOAm5kJJP1OtIZ7v8/Kko4UAFHYFJcJZY+29b2TcBRMKOSQAs+zKh+Bb92Yojz950KIAEW3H1K7h9mPHV18NvfwqWXdjWVVlUxPrdbpPlpmlgmSTDXV8i57nW8a8rH6e2SQgln/IHeWE7MaJhJow4XFmIiaDZsxUVebSHS+deybp0YW7we2+v6DAQJ8PhE1KujA1paxOtD8XtnQM7URRddhNls5vrrr+dPf/oT55133oAl0A3+tRi1awbhYNiJQTgYdmLQi5QU6tcfImvjJ6LOSYONHoVN8tXkUczlpgLi5K1kutcgSaD6JGY6v0DCzjzWo+BjLhtpYBiJtGLGg46ECws2vypaAm14MaOhUMoY2olnG7PoyMwj3ir0FaxWOHdyC+O+2o4ExGpN1JFFLG2ATiztuDGRpRVHNBEK1KFoSJSTg4MYnIjoyhouZoRSzUXal2jI+Jy+btflZNctlLjMhAhGBS4UWkgDZIZhJ44OYrR2FElF9nQKBcODfgGOJUuEDHuoM9UDNSGZg+ZppGlb8WDjCj5lGXfzD/K5i6XYcGLFiw854j5PoXhq6gn87N7f/SSqqDDY88uKDx8KIn5kwoQPDcKWjNCBtpAes9nZIqVx/XoYORJGukv727RPQh0FGZDR0FHwIHGMkUzhYLdjBxyY0OeB/bSSgKbBnj1CE2TiRLHMZutK61MUf/RMgiTNzlx9HbKscq2vgOMkEo0jIkcQIAoPbqxUM5oRlEd0/jIQU1PC1Dnw2WfCxNLNF+DGhBXfgB2pAIu87/Bxx7UkJoosVRia3zsDqpmaOnUqqqry97//nSVLlvDUU0/xt7/9jbKyslM9PoNTzJnUE8vg9GHYiUE4GHZi0BN1UxHRm9egejXOcaxlsmsr12n1XKF+zLW+Aia5tnKOYy26qmHyudDRiaaTmWynhUTRYBaVLGqIwuEXdFCJp6uZqoqMjkQn0XQQTwm5jKacuRPtPPSQ8BMeegiuW//fQUU7E5BBNTac6IANJxlU92pQGg5ifxojqMZsArMJ4k0OvqV8hluJ5UvpYipMY/GcNfvkTlQ/KDN717+cZAuseLHgJsrfrNiMiqbLtOXOhN/8RlwYRelyqE7QUqa8PYWfS7/nM66gkyimsYe7WEoexYykgnTq0ZBxENvvPsKhor5LlL6/+8m+1my/cl/g2qt+FToJCS3CqIDExr1xwTQ5RRFtv9LShEKkGhWuSH5fexZ1dF7M+DAznNrgsnB6N/0XLwIiCvPQQ12pfImJIiKl6+IPRASoUU/hHVM+qqQg6yqXsCbi8QYeE2nHRgd2IrfXcY6dRFUWo+tCZ2WCbw+WHo6U+AEiEt1FQQwOctViZLkrFXMofu8MyJnavXs3zc3NfPbZZ1x11VWUlJRw5513MnbsWDIyMrj22mt55pln2Lx5M15vZOFzg6+XpUuXnu4hGJwBGHZiEA6GnRj0pNqWyxZ9Nj4UJHQWsJZZfMg50jZmsZUFrPXLMFvYyjlUMgINmVg6icKJg2gUv7sUUG4zoQUlnFVknETjw0Qc7WRRxXzWU00mlowUcnLEL/o5OeDImRIcV0DVbhj1gM4w6v3xjYFjxku6Vku9MpwUvRFZ17jAtxaz5qEo9mKyE9uDQhwRs2lT2KtKQDQe4mgljg4UfOh+h7NCzuHV7F+iJqaIQpyeDlVJSZ/7LC2F9fV5vM217GEaANPYwx28wNnsxoOZDmJpC7tDV980NnX939/9pD42l0NM6KbcZ8aHFSfmCKIfOuDCyus7p/GTn3Q5K3PnCkX66Ggoa+ztHEbmAOiY8BKFEy82ArHJfuu3/I8+4H/5WfD1r76Ce+8VY2xvF2Mzm8Xb1tHRJUaxx5XHG558fLpI8YxspF0OnQ9oJI1O4iM6Xx1oTxxF3Z8K8NTaiY6GCe7dfar49derqq99BlDQuFEqYLK5S8xjKH7vDFjNLy4uLqjet3r1alpaWigqKuKhhx7CbDbz7LPPcsEFF5CQkDAkvch/V5599tnTPQSDMwDDTgzCwbATg5406inc51vCJs5DQ8GEjwU0crX2NhdS6E/LUtjEeTzPD9nKOdhJQUElnjZi6AD04ITKjIrsn0YH+gw5iPY36YVMakigldulv7B4+JZuYykec0WviaEMTGL/oKSMxa/sMj5M2PVk6tRUNnI+6ComzcP5bGKqtou6BfkDjkxx2WURjQdEChzo/viUlQp5DOv0+eibi9j8iV2oxIU6VAEBij6oqYHbHX/gZzzJbqZRQxYxdDKFfVjwoCNziDziaR/Y+fkxheTn9Xc/OXoUbLgAggmFovbI028/pb4QaYJuhnvLeecdeP558bqiwHXXiUzI4x1xJ+zNdDICCo8qMgk0hR01MwFT2dPttZUr4cUXRWQqJUVEpwIEolS6LuoD/ynnM5zaiOw6VAJeRiaJJrI5GtH5SsDkutW8UzePalcK0dEwylzda53Qx3D2CUJuviU6g7holcXOAtR68cPEUPzeOWXS6IqiMHPmTH784x/z85//nIceeohzzz0Xl8vFhg0bTtVhDAbJokWLTvcQDM4ADDsxCAfDTgx6smEDDPPUUMI4DjARBQ0LHeRQhgUPChoHmEgl2VzEGtpJoJ04vJiQ0fxOktRNC6xrEibRRix1pFFFln9tORihSln5pig2ASguJvuzF/pMrZIZeEQqMPlUUShmHM16EhPUfUiaRqWehQUPMjpjPQfxNLYM8Cig1oSvMBgYlxcFLxaaSeYYI3lBupMcvYya9jh+90IKTz0lmr+qly4UAhT33NPv/tz7SljERyio3M5fyKaCNOox4yWGTnwojKcE9yDT/EbGdqkB9nc/yazfwUiOoaIELSQ0qhKQ9g4HGZ3xHKahQciQezwi2vPPf8LOneDpoacRaVpaqHO3l8kRbTuHrmhkdDS0tcGnn4oaqUCKm9kMcXGijspiEY9xcVBuyYu4gXLoNdTR/V2mzBHtA+D5pJ+z3rSA9HQxng/S7giOZDAtnduIZ0P6tUTFKdTlzcOSIX6YGIrfO4OWRne73WzZsoX169cH1f1aW0V1n9VqZd68ecydO3fQAzU4NXz00UenewgGZwCGnRiEg2EnBj1xVYuieDHt1ekkmpiQKVUn0f66Egs2nExjNzIaJtSgoEDAgepZZ+LCTCex7OEsWkhiJluZzAFsOEmjHrVoPa2/h7bZlxFftIqYxvJTfn4BOelOYrBIPsCJiyhy9VJSpQYapXRipE7WZd7MnNmzB3ycBiWdSDo4OTEhYaGVBOJox04yo9SjbGUmMXo7crOddetSOHwYqqshP3/cCUUbSqVxvMsDPM8dWPASg4M2YjH5BSBSaKKNeCwRKL/1hTq+KxWzv/tJycjLqDw8gkkcwouCEhKpDHVewnWoaskAYP/+rmzK1ashp7yQxZ1PD2ifAQKWrqEwjKYTrtsTW4ikeWencKjKy6GqCmJjCdYNeTzdFOXx+WCarRjVYY1wtKHOjkwadbQRy3DqI9o+UW7HbBbRTIA4J7SQRBLNg/rRIp5WckZLrJLuYsb8FLKzxbKh+L0zoMjUBx98wP/8z/9w3nnnkZCQwEUXXcQvfvELtm7dyrx583jiiSdYv349ra2trF27lt/97nenetwGA+SWW2453UMwOAMw7MQgHAw7MeiJKT2FImYziQMk0kQc7aj4/JLRCnG0k0gT0xB1Fc0kMpoyFFR/CqDUrb5CD/mz4MOLmSyqcRLFNmkO9fJwFHQ8SjTHW6OoXbmHqqfepHblHpzucDXeIkMD2onDF51IgtVFlE0nw9yA1ayDzcrvo37D8nGPk5k58GN0bt0X9roSEIUPBZUonHgwk0UNc1nPWIr5p5RPYm4KM2eKWptVq0QE8YTnqMFf+D6j/REpGY1E2mgiGTM+fJhIoolEOgZ+koC6clXw//7uJ6Mbi0imBRUpKGwg5ODlEzo8Wj9LxiIU+9xu2LsXNm4EZ5X4EcBliQ+uN1BHQEPUdKXRiKdblLVvRC2XiUf5LdBV0ub1ir+yMqFOmZoqnKmAIIWiiMfpMcVcpxZQEzUWtz+yFG5EKLCeGzMbmYudNHwn3KI7XkyUpF1Ae7uIpGka7LbMZh+TIthLbwIiL012iM5O4bzzuqTih+L3zoAiU1dffTUAo0ePJj8/n7lz5zJ37lwmBnQcDYYsQzHX1GDoYdiJQTgYdmLQkytm22lVitBUnRwq0AEZEy0kkEY9OpBDBVVkkc5xzmYXEhoaMh5M2BCqAAEHSkigi9opDYVMatnBdOT4OLJinCS3Oml1JdGipNLutGCzaKS4akS/m86qU35+gbQyCx5itRZUsw2zLNGupJLgbcCh2Zhh2o3XXUxNTR45OQM7jjs9sg2FKIMHHZ042ukkjtEcZRp7iFc7eD9hNbIM48fD9u0iInPBBV0T1J5csv1JRlAdFHvw4eEYo4jCSQWjGEtJUPxhMKlcnpSM4P/93U8+PpDLr/H5hUgEPkzUkEkmNf2KUOj9jK6OdLFch61bRWqaLSuFA3H5jCi3ozavjHhyHLCLwM8AgZo+HROE0cfMTTSjOUITKZjNwmlyOiE+XjhSycmi4XVjoxCgSEoS8ugjXcVc3lxAlE0lM7oVr9OEBe9JHcHAVRGRVpH82kYsW1jMbLYQ/rsqYztejs02Dk0T1/Qbznc4l6LgcU40lsByDQnZXysZun5u6w6mX3YZF1zQ9dpQ/N4ZUGSqoKCA6upqjhw5wmuvvcbtt99uOFJnCC+//PLpHoLBGYBhJwbhYNiJQU/Mw1NIsbRxDtvxoaChUEE8G7mACkahoeBDYQ5bmc4ubLjxYaaR5GAtkhczLsx4sfinwwoNDENFwYeJ8+WtmM6aSMK4NLbHXgiaCoqJMe4D2JxNuFxgczZhDWNSGSCS9WTAh0y1bzgtrig6HRKHfGPZL0/FrUQzW9vM1bVL8dQOUMkPSG85ePKVeoxLQieFJmx4SMLu79Pl4yK+ZNw+0QBYlkWE4+hRqKzsf3+u8y5C9U8RJYQARAqNVJNFBjXBnl+DJcbT1TOov/vJJe6PSKcxeDwN8PgjMB7M/U77lX76X13H37uOHyPS5qKiwJ6Sh8XTFnbPqlACdiGjBx0pBR/mMGxQAmLopIWkYCqfJIlxZWTA7NnC4cvKEiIZOTlinWGSncXOAlISVdIyFWpzzsUW0hA4fHdIp5ixPM4veIUf0EJiWNvqQCdRbPXNIDubYGPuPfq0oIRMT1W/vs5dqAkqfTperqR0rruuu9M/FL93BuRMXX/99WRkZJx8RYMhx+xB5HAb/Ptg2IlBOBh2YtATaXsR+do/kAAvFnZxFqu5gBLyWM1l7OIsv5Okk0wTChrHyWAD82ghCR2JKkZQRi4dxPiV/HRqyWAX01ElMw3mTHYlXEQB+cxo/Jwkmsl2HER3OEloq0RubhSPeAcVNen3HBFRIIu3A5dXYod3CrtdeRx0jcbpVchxHWRc4yainQN3phKdkQlQQGAy331iL9CxN4gULOiqu3E6+9xNcB03XTU4MpCKndkUkYr9lKmXlVTagv/3dz+pJisYkxLiExImVBJpwYQa8Xu8nTmAmKBPnCiEHALX4vOk7wzKZkIjPtG4w75OJlR+xB+w2YSD194uxnXJJZCbKxyoxkbRZPj882HePJhyYQrq+fPIGqlQeV4+dc74kIjYiccHoCIF5V0mc5CHeYxv8iEJtIblKEtAHB1MdO5AkkSvruHDYaale5+pQJTZhyn4f8/9mProS+VDZkPzJN56S6Q9BhiK3zunTM3P4MzAeaK7p4GBH8NODMLBsJMzDH/PI1UVhe0HD4rH4ERloD2RQjCNy6UjLhNJkdltmsk2aQ52fy+iJlLYJs1ht2kmuiKcorroUVRlnENd4kRWywsp4hzqSaeRdKoYSSvxuIiiNnEKZannUGi9nGUjn8SSkcIl0RtJ1hqCkzErTjqJASQ6ifnaJjiiX1UzCTSxh2msZCEqCkm6nYme3Zh9DoZ3HCHz/WUDv6YnChv1QX8NYXWgmWRW1Exj40bxfjsc3RXi+uKZV5JoYFiv2I65R0VN37Gf8NCBV3xd9S/93U++5DLWMh8VEbkUzqI4shzhCFTgb9wMCFGH224TjkqD39n0eiI/j1BCa/1aIujZpAPPcQ8+nxiLrsPkyfDgg70bC4Oom0pNhcYpCyiadRcbG/PoSMxG62H1PVX1Qu2kg1gCH30ZFS9mFlAY7OkWDgoqneYEGhu7xrXA2r1HWiDi3EwSKnKfjlpg1KHjVNBotsOf/yz6bgUYit87g1bzMzizOHLkyOkegsEZgGEnBuFg2MkZRGEh2tp1bMvN54vKPMrLRXTCYhG1GBePKGbWkQLkC+fBggUDPkzWtBT+cdWTZH38PJ7E4cQ7k+isP8KhqFmcpe0kPiEJT9RkdrSkcGTCt8iq3U67ksiksQqFjnzUw59hklQmSwc4rM0i2u3BZpOYFn2EfbYktPgMrvivTKbfACkzHggeV/Qd8mLBiZ2xpFETUVPeSJXbFDSyOM5upvEJ3yKVOn7IMhJpFtESVzvyOTMH3GfKfuXNDNtWNKBtAwQm9Q6iqfcl01IhJuqSBPn5BNXR+mLnseSgat7JjjEY4loqARFp6O9+kksJkzkYTGUUdXgaNlzIfkHwcN8/GTifDRxhHPHxwv7PP18o6h8+DOeohwdsM6EOrA+w4kGje9RCB1qJJ4G2btv6MJFIM0f8n8mMDHjkkS6Hd+5cocK4apWoeQuIUTid0NCQQloazMxtRS+UguPy+CNBFny9nCkdYcM6JnS8NJOAhoKMq880x76cscDzRe63+It5NjU1Iqq2jym9ro2OTj1pJNHAyQht8vsN7WP+cHQ2//gHzJ8vHMuh+L1jOFP/Zlx11VWnewgGZwCGnRiEg2EnQxy7HVJSUOvttH6wjmPrKzjqKKAkKZ+jpjxi3XY6rCn4DhST11lAUnwFuYA8deqAnQBFgXEXZlK/ZQxO1cqIUQol5zxIbNo8nB15jCgvoLkxifgkicuTt9GSnERJmcInvsu5uuVF4k1l7NKm8SQPcLFSiM8Wh02rp7XDxmTnOmKSrCQfaEOuu4O26efDlx8Ejy0BqTQRx2ZsuPsd46lAB2Lp4Mf8iRwqWMyHJGPHRFc+UgfRA+7C1NHQybBTMEYJyKCGqeoO2jIuCyrDxcb2EJ/w20qA+RSS7pfI7s9RGWwKpQRMUEqDz/u7n4yinCTswWiF7o+d6H6lvEj6hvkwcYBJQZGHoqLujsrBmHPwQVjdlvo7ZgNJWFGpIIOpHA6+rgMHmcA/yWcx73EWe4KOlqhtW8Nu02wURThUoe+PoggHeMQIIR5y9Ci4XOK9nD8fzjsPRhxPQH9ZRkJFRaaTGOJp71VDFXBUZFQk//VU0InCRTZ9R0T7O1cd+HvsHZx1lpBwr6+HPb7eSn4mNPI4fFKno+dx2pLHgAa7domoam7u0PzeMdL8/s149NFHT/cQDM4ADDsxCAfDToYwhYVozy2j6I1ilrycwq6CQ4ze/jZxh7cyaksBUetWMrNoGaPW/ZXcbQXEHd5K5sa3qV9/aMCOFAB2O7OOFDBqnBXFqlBAPm/v+RuaBiVSHgXko1gVMicmkhXXzuRxbnJ+cDmjLx2LSYFos5eUFEg4azS7Z9xGZda5NMaNIjrBTLrSSEJ7JY7DlbT94RV8h4r7HMLX7UhBoG7Ky3gOcQuvMZ5DWEJqtGoYzstN10a830AK5ob1p2aMgcdoXxu1tUIkIDZWKMIF0zsLC2HZsq6Gx8BXLKCR5MEP4gTogG/ajODz/u4nFeTgICZ4PgHVNxfWoDMVLgo+EmglJUWcf0tLl6Ny16XF3FN574CjDDrgwcIRxvM4P+NpftZtWS3p1DGcKBx8yNXs5OxuCXV1pJOWJtL52tpEI+HQWiFFEY7T/ffDQw/BAw+Ix/vvF683eJLo9Hd186FgCVHGhN4Rsq66Jh0LXtr8EbNIkID/6vwDx46J1ESAG9tf7FUvJYUcry8nvD/HPN15lJgY8T6VlYnXhuL3jhGZ+jfjhRdeON1DMDgDMOzEIBwMOxmi2O1oa9dxsKidqg8K8GkTmVK/BnSNC9S1WOhgLoU0k8h8CnG7zJzDJlR0YjavQd1UhHLeAIu8U1KQL5zHZMdKXNfcxphjeXTufYHjx0UkYPw38sgemc/kPa8iX/E9qKpiRtnnTLkhiTL9IlL/eZC4yRoLJxWwd2I+aX9pJf34QVTNiscNZmcHtaUdqBXFxDcNrsfRQAmd+Nlwk0VVN+U41d/Utv29VfCTy8Lap6rC+vWi/9O+fTD/4LFTNtYjjGGzZQF5o0RqX8Bhq6yEnDg7rFsnXiwoEF5FXh5JNGH1O6X9RSUGK4suAd/e/xtAXKP+7ieJNGP2p6oFjmnyp/mZIqyZkoDxHGa/fhlms6jxAcBuZ9iXBVSq8SfYujdCEl1CR0ZCQ0ElneN8k894i+vwIWNCw4dCG4mUMZp1zGc6O6kim6ns80vPy5TZJpGZKRryHjnSPRoTiqLQp+R+ezvE+p0hC15kdDT0bpG70MdAvZmKieOkY8bDQdssprt2RRDpk/lk7D1UVgoHMD4e6k1ZBH7PCNdG+jveJ0k393ptKH7vGJGpfzMWLVp0uodgcAZg2IlBOBh2MkRJSeGwJ4eozWugrp7s+u3sViehoqDgYy4byeEo57KJRJo4n01I6PhQ2Mxsqm25Jz/GyZDEL9W6DmvXdrcTPTAr3rAB7ZVXqd5Zz7a7X6XjjfdpqffQ+uU2VrxWj+1H/0lm4d9QWhqQGhqRO1vRNI3kljK8HR5i3PWDH2eE9FUnE9r/SEfGh4nNnMv6zhm9d9AHqgpvvglPPAHLl8PmzbDHd2razehAI6l0OuDcc2HUqC45cKcTEYXMz+/qFFtQAMXFXM5KkmjpNcntS4ltMBxOvzj4/4nuJ5o/pS/0+psiai8rUIECvoPLJRyS2bPFaf9jVQoF1fPYzXQ8IXGGngIOPRHOgkQjyTiJxo2VkVQyjd38gL8Em1DLqGRSQwm5fMK38CKzgLUo/miNikJjXC6KImraekZjwmHYyr92s0WTXz+vL4cm4EyJ2inV35tKJ4uaiBzkNhJIToKRI2HqVEhIgHrb6G776KvOKlwePZpPZ6dwekePFq8Nxe8dw5n6N+Ojjz463UMwOAMw7MQgHAw7GZqo9XbiXnuO1ObDTD6+mvbaDvYzmSPk+js/+RjFMTI4zlnswYQXDYVNnMd93iU06oNL89PWrmNfsZWqZwooW1nMZZd9xPDhog7k6Ipiqp4p4NA+FXX1lxzRRtO6+QBtRxtIbzpIYnslemcnk6tXMqp5N5IuOtCYdSdWzYFZc6H5fES112GLoI/UqSIwMQ3UnUDPWhSNYsbxI5bhiArvOq5dKxTLdu4UNSeNjVDLqWk/IwPnsI2z2dG/ml9eXi+HyttP1dCplpqvbo4J/t/f/aSMXIrJQyMgjS4ISL9HMiYT8DseIDkZrrxSXIf162H1atiZsID2jPHIdKWnicbR/Utx6AgJ+Vqy/JEoIfqQQBsjOYrFX0OnAFF0chcv8Ddu5C5eIJqOoNiDFS+3df4Rq7XPw4RF9Zh5veqiekakeiL7r2gax0mkmWR3dS9FwBMhodLRIerOLrgArplSzAWxu0+Zc1EhjwHg7LO7onFD8XtnyDpT+/fv5/rrr2fMmDFER0czbNgw5s+f3+dFPHjwIN/4xjeIjY0lOTmZm2++mYaG3oohmqaxZMkSRo8ejc1mY9q0afz973/vtV5fLF++HEmS+vw7fvz4oM/3X8Wdd955uodgcAZg2IlBOBh2MjSp23gES2MNqi4zXKvmElYzkmOoKLSQ4HeotGCDURMqB5hICeMY5qlhw4ZBHDwlhW25+XTuOIjqVrlBL0Bb8U2OHYP448XcoBegulVa91Xw4YQHaCxvp8GUQR7FxHbWkeBrYKT3KFl6FaaQPj0yIgJkQiWWNkZQicn/y/rpoL9f3nUkRlDFYt6nj2lILwJRqb17RSSio0P8XU94c5NwMOElnja2b4cdO2D3bjEx7abm18OhuoJPetW9hKbZ9dUvaCDkdOwJ/t/f/SSJJmR02vyKc9DVpDhUirwnoQ5Q6PI9TOeKK+COO8T137gRjh8X1/+T1gtwYgtuo6IgB6Uuuu9HpPiJVM8JHGQ+6ylljH99iMOJy+9cAZjRGE4tl/Alw6nFHNITqhMb70XfjOSP6PaMxoSDdqw6/JX9BHqSOYkimyrcuqXfZsd9EU8H4927RTPo5mLOO1bA+VV/P2Wfy2NSDrm5cOONXYIcQ/F7Z8jWTFVUVNDe3s4tt9xCZmYmDoeDd955h8WLF/Piiy/ygx/8AICqqirmz59PQkICjz/+OB0dHfzv//4ve/fupaioCIvFEtznz3/+c5544gluv/12zjnnHD744ANuuukmJEnixhtvDGtcv/3tbxndw7oTg0m3Q59f/vKXp3sIBmcAhp0YhINhJ0OTprGzedH0CP/jfoQ42hnJMVJpoIlkEmntNjH0YaKDWGR0FDTm6utwVU8FBhadUlUY/vP/JP1YEVHRlTQejucR9SCvffpbJFliu1nlG8rnTHRsw/vnT7FqLpxSNGV6Djk0+ZuddqLp3afIob+w2/Dipfsv7/9KQp0MCYLy10IMQSeJFn7JY9T4FhCQ/e6P8nLRQ6ebIARQT/opGauInFioJBuXS9RJpaT0oeYHwqGaPh22baOBtKCqXXfJbxMmfKfkl3gViar7/l/weX/3kyOM4yCTmMABAldfjKdvNypwzm0kEE8r1hAhBh8y5bO/w/vPiqhUeTmUlgp1vJoaiHYm48UcTL1zYcOGExNdPbVCbU5D9su0uxlJBZVkB+3Bi0wLSQynIWgrZlRSaegV1WxiGE16MukawZ5NodGYcNAnTsKHCUuY6Y+hY7DhpooRTGdHRJ8pExqX1L3JsWIbw2t3Iusq9aYshqmnJgV3a+JC7r7Rzvz5Xfejofi9M2QjU1deeSUrVqzg17/+Nbfffjs/+clPWLNmDWeddRbPPPNMcL3HH3+czs5OvvzyS3784x/z8MMP89Zbb7F7926WL18eXK+6upqnn36au+++mz//+c/cfvvtfPTRR8ybN4//+Z//QQ29i52AK664gv/4j//o9mez2U6+4RDh/fffP91DMDgDMOzEIBwMOzmNnKABb10dvOW6iqe4Hxc2FFTiaWM0ZdhwAQTV0DxYiKOdRJqYxAGKmI0pfeBpfg0vvkNG5WZMeJnkKGKmugmZdm7hVXK1w8xzf85Ex1ZMeInWOjDhI0ZvZzxdEQohga2fcIISmOSfblRkvFhR/aMNOHgxdDA6uVWs01+TZMREvqqq+2sAOzjnlI2xlgzKyMXnA59P1OP0dN4Aoea3cycALqLwYOsRkRKxoO6RuIHjw0Rc6Y7g8/7uJ7mUcAFfYcWNgtrtR4BAWl3omLwoNDIMOyk0kYwXU/B9MaHx5Iy/E/id3emEPXvg2DEhNX6F+hHJNAOilqie1G7phE7/NYGuxrKh8ubZVKKj4MVEMXnE4Ao6YX31egLhpCXQRk7TDvbvh+ZmEZEKjcacEP+9IC0dfGGJuveOsLUTgwkvVcqYsLYP3XZscxGTDryNrKtokkKZbUJE+zgR3/G8ynX1y1DWFQZfG4rfO0M2MtUXiqKQnZ3N1q1bg6+98847fOtb32LkyJHB1y699FLy8vJ46623ghGsDz74AK/Xy1133RVcT5IkfvjDH3LTTTexadMm5s6dG9Y42tvbiY6ORgnLyocWuT1lYQwM+sCwE4NwMOzkNHGSBryuPcX8Xn2COFrZzxTOZSMmfEghiU/CCTBh9ct551BBFVmcqxRxxexZDDQy1TFmGoqUTIregIJKDO3IWGgmnm/xITF0oPhjCtAVzelrMjIUnKWe9NVzqZU4Umjqte5V51Szdi3BWqXQ9+i880SdSW2tXwiiB7GcGqVCCRhJpaiZslyGLENmZoiaX45/xeJiIT6hqqAolJETjHCE1onJIalpg31/LHjZuxeu8j/v734yinKyqPY7LToaEg6i/NV/QlQlFBMqbmy0EU8GVb2EKtKkrqiJuc1OeXlK8L2Zqu8j0CpMAkZQhRsrUbjQkYjC1cN2uyOhoyJTySjWcCk/4v/12werS+pdqPAVmi/D7AabDc4dZ+eCC07wGQz0BSssFGqM+fl4opOw4QzrvekZXY2lk3PYTrOaeJIte9MmJxPfUkFHTBrHRs3nw2ML+WbrqUlTnda5EVnPE+fo7383FL93hrwz1dnZidPppLW1lQ8//JDPPvuM/Px8QESb6uvrmTVrVq/tZs+ezaeffhp8vnPnTmJiYpg4cWKv9QLLw3GmLrroIjo6OrBYLCxcuJCnn36acePGnXS7+vr6XnVcpaWl/az99REVrDg1MOgfw04MwsGwk9OAX+CheEM9VR8UcCQ2n+qYvGCthXqwmPMOv8p0tpNAG00k4yQKMz7M/lmiSIMy4SIGH26iceFDYTbbOGSZiXn4wCNTWkIyJs0ToiimE4ebaCqDtRg9J3IgCvRPV/1TJPRU8vOhUE86CbRiDXE0GkjhJc+teJcLUYnUVCH44HSKeeHhw6JRbEVF38fpGHC7X4JjCIxRQWM8h9kdcxmaP0wSVPODXo4U+fms/1ULPhTM+HpU0AQqlfSgMzHQ900C4tq76nxOdD8JOCQBKXIFDRc2ounsc90RHCOaDuLo6OXwuDP80ZfiYuQXCpjZPo9VLMBigcP6lKAzBWDFh4aPQGPbnu9/qA0Hfhg4ThotJHAOG8NqKByoW/oH1/Gn2W9zVnMh5+5cx+5/5nPOd/O6r2y3i7+CApg2TYTV/KIhuSt2RZT6GmojUbiJwkESkafnpbnL2Wy+EKspmuG1O/lt+fKI99EfSd7qrkZg/v53Q/F7Z8im+QW47777SE1NZezYsdx///1cffXVPPfccwDU1tYCkJHRW/UmIyODpqYm3G53cN309HQkSeq1HkBNTc0JxxEdHc2tt97K0qVLee+993jggQf44osvOP/886ms7LtjdCjLli1jypQp3f4CXZzXr1/P2rVreeqpp2hqauKWW24BuuQf7733XkpLS3nllVd47733KCoq4tFHH8XhcHDDDTd0W/fhhx9m7969vPnmm7z55pvs3buXhx9+OLhOUVERN9xwAw6Hg0cffZSioiLee+89XnnlFUpLS7n33nu77e+WW26hqamJp556irVr17JixQqWLl1KdXV1sAgwsO6dd95JdXU1S5cuZcWKFf+ycwKMczrF5/TDH/7w/9w5/V98n073ORUVFf2fO6ev4326aeFCAH7yk3spLCzlscde4cUX32PTJv85VVb2OqdH77mHvXv38sYbb/LHP77JBx/s5e67H0ZNTOH1P79G2vp38e57iYl73qDyi5+wZk0R1WuWkrv9QVJbd5HLQcy4GMVe4mnDhBcIFRLQ8eCmkkz2EoeGgpUO/sO3nJfuuHrA79O+J/5IHCK9LXRi19OR6ouhGIk6Eaq/siabCkBDDZHvTqaVhpdm4HBAWdkNZGU5OHToUczmImJi3mPfvld4551SXnrpXv/eAnLPtwBNjOb1UzZOHzJFrMfrLcXjeYW6uvdoaSnipZeE7RVccw2oKm/8/e+Qn8/Dy5fTQj1NRKEihfoWyPiCiW0qRCBV0DdazVKg637S1+epgw/xooRM/jWaSaIFLyp9240VH8Opp6/8oSMfvsXhjz5i1X/9Fy12ldmeOxgm2ensvIEs98Fe68sQFJUIpa8IkBCkaCAKJ9B3U+n+ODpiAabWO7nE8j6tVRupWPJrdha8HbzvPbJgAfz2t3ywcCG0t7Pq6acpzc1lz/797N21C3Pl/oiOR4/xm2nr44xOvv1Ry3A2xWey98Ammho6sGmRC2H0R3NUGk9XVUFeXvCe8+Mf//hrv5evXx9Z12xJ1/Uh/WPQoUOHqKqqoqamhrfeeguLxcLzzz9Peno669atY/78+RQUFAS/iAL86le/4tFHH6W5uZnExEQuueQSamtrOXDgQLf1NE1DURR+8pOf8Ic//CGisa1fv5758+fzgx/84KRNxPqLTF111VXs27ePyZMnR3TsgdLU1ERy8tfb1dzgzMewE4NwMOwkDE6SknfxiGJmHSlAvnAeLFhw0m3Ojinhuj9fRnxnLR3E8BlXUsx4djKd6ewkj8Ncwhck0IwJNVjnYsYTFEsIiEq3Ec9aFtBBHBdJa8jQa3FYk2j7bCMjLjp5xkVfPP6fJXz/1fNJpfGk07JAof5QINK0Na9fskNsKxq2gohUReGinVhmsoObfjkOuY+T1DTYvl006D3WR3/e33M/D/B0r/qkSMYYUJurJZOLKKQ2ehzDhwudiQUL4P77/TU5Iali5IlISIpk5xOu5Cx2YsGHhI6O5BdkcPmfi/0rYY6r5/g1oOzJtxn7wLVA//eT/Nwilh+dhw1PUETCTRStxJNGgz+FNTx8wAc3/pPrJh0EVWX3PoXbVuRzUM1DUcDWaecQuSTTGvG1FvVkOm4s+FDYwXTmsTHsa/P9ucWMumQc03b/lQmbl3M8eRLTF6aRdKc/KvPb34pIlNMpmlHddRfcfLOILC5divvVN7C09043DefYKhJNJGHBQ2IEKaY68M/pvyfjDz/j0IfFpK8tIGfvh0x1bxv0jyM6UBU7jpHt3Z3Sf8X3zv79+5kyZUrY8/Ohch/rlwkTJnDppZfyve99j48//piOjg4WLVqEruvBUF8g+hSKyyWKbAPrREVFhbVeJMydO5c5c+awevXqk66blpbG5MmTu/2NHTs24mMOloDXbmBwIgw7MQiHU2InJxBSCF1+SikpAYSDsn49fPyxePR4ui8fNP6UvNI1FVQ9U0Dpp8UcPgxHjog0r5JPRM+lI2sq0NauC6bwnGib4s/LUB0udCCGTi7lc/I4zDnSNvI4zMV8QQwdmFCR0fBgwY2FJpLwouDF7J8EK1jxMI09TDPtJ8bkwSuZacmYSMbkCCcqIe9RhzmZz7gCJ5YTpn8FIhrhST8NHQLnZPJX7AQan8poyP7YlAsLu5hOM8l9OlKAkJJOFXPivnibG/q8fuH++h2IkLmxsY/JNJOMxSKaqg4fDvMm2bvEDRYsEBPzvO4pZW3EdZsQu7Dg7iG20dXtKfxxhdIa16XP3t/9JCWle9NeBR0bTlJoCjqx4R7biwXpi1VoXpHSGH97PvWJeeg6REfDMLkJG+4+xxrOEXTAiocYnMxiU0Rb377vR0Q57CS2lFOXMonhzQfQ6+pFSt8m/76cTqEwo+uwbZv47JWXA9AaOyLiEUOX4Ivk7zkV6XmPyZWYPx++/2QeM5/MJ005+Q8p4WJytvV6bSjOT4Z8zVRPrrvuOu644w6Ki4uDKXqBdL9QamtrSU5OxurvgJaRkcGaNWvQdb1bql9g28zMzAGNJzs7m8OHDw9o29PBa6+9drqHYHAGYNiJQTgM2k4GErUZLH/4A+oHH/Hh+Ad4oWwhx46B1wtmM4waBXfkrGTx4SUo314E99wzuGOlpFC//hBZGz+hwjyfMRps9uVTTB55FHO5qYA4eSuZ3q+oN3+T4b8WNQEn2iZF3sJRPYdzaEBDIZZO0UdKr2Qch4mj3Z+GpePCRjNJfMIVLOZjZJoBGRdR/niVTiY1dKrtWHQHMl4SLI7wFMQC9IhqtJlTmMHOYBShv0lVqNT5qRAz+FcROm4ZHQ0NFQUzHn/fLjcqEjYcwW00DdrauuwsPl44U1FRopdQX3VT/8FrfdaWRYILGy0kUc9wQBx3yhTRWPXcHQUQF/K5SuleJzeaI0xhPwEZfR8mZPCnr4lpt+SPdYY7tkBkNPQaxn3wGvxQ1K73dz85WJNEA+mM4Jg/dVT3J/2dqJ1u38e34qGpzUJLu0LyD/MZmZvH2WfDl1+K3k5XaBuIDhGZCJdASmtoHVKk/XdXT7sfLTqF/VPyySl8FT1pEqPLDkAywnHSNOF9p6eDyT99/9nP4Isv4Pzz8XR6Trj/nvS0qzjaaSMuwlHDlEyRdaUoMOLiPNocdafsM21We9fEDcX5yZCPTPXE6a+YbG1tJSsri9TUVLZt29ZrvaKiIs4+++zg87PPPhuHw8HBg93zYbds2RJcPhCOHj1KamrqgLY9HQRyQw0MToRhJwbhMCg7GUjUZrCUlKB+8BFHDqukv7aE+M0r8XrBahUT3bhNK0l/bQlHDquoH3w06AiVuqmI6M1rUL0a5zjWMtm1lWt9BVyhfsy1vgImubZyjmMtqlcjZvMa1E1FJ91mimcrkzgofmFHw4SPRFqYxi4SaUFBpZoR7GA6Xkx8GnUdiiSRjB0FkPEiodFGHCa8uLAho2HBjRmV6KoS8SaEg90uHCl/ATzFxUwteYfJ7Dtp4X3ohPpMcaT6QkWhkxjUkGayJnSmso/RHKG8XKj5rVsHGzaIx4C6X2ensLu+eINb8NG9UW6k18qNmTbi8fl/N7/jDvjvhcV8s6MAWVfFYPr5XNVYcqknFQnoJBoNCTNeFH/EU8VEJ9ERv3c9J5115i4l5v7uJzWuZNqIB6Tg9gFlwYEcf4J7O+VJ0yFPpPb96EfCqXW7YSEfR7jHLnpKn0sRxnjOrngfgJjWGpSWJuISZawj00UuaHGxeBw9WkQQ3W6RH7p6tTCitWtJaCvrczz90fPaqcjE0xLxNTW9/goUFgazCxxydIR76B8NRZx7CENxfjJknan6+t6KIl6vl9dff52oqCgmTZoEwLXXXsvHH3/cTQTiiy++oLi4mOuvvz742re//W3MZjPLli0LvqbrOi+88AJZWVmcf/75wddra2s5dOgQ3pC7XM96J4BPP/2U7du3841vfGNwJ/sv5KOPPjrdQzA4AzDsxCAcBmUnwajN28Qd3sqYbQU0bChm0yZo2FBM7rYC4g5vJXPj29SvP9Trl/MBMW4cH45/gMZmBUlTeVBawlXRK0lNhauiV/KgtARJU2lsVvho4gMQhlLriai25bJFn40PBQmdBaxlFls5R9rGLLaygLVI6PhQ2Mxsqm25YW1j9jtEDaTiQvQ5DMg/u7BxlNFomChlDJN8e0iJ6sTqr5lSACtuUmjCgwUzHqL19mDdieJoQ41PCu8EU1JEREpRgg7VrMp3ujlKJ+JMdqIgUGsinCjVHysJODxmvGRTyc6dIvKkqiKYoKri+c6dovyls/cP7wCUkYvDr+gXya/8oRPoGFxkU4EFN02k8ODVxZxz1O9Iud3dFNJ6MmdcEyOp9Dfo9dFOnD/FT8GHyd+81zvoSWRmc1d/sf7uJ8OdR8ikmkAKWrj21R8+zCh7dgYn6RYL5OaKyN0KvjXAvfYeU6Tj8za2YO2wM3rd64z2FZMjVSBXlImUvpoa8VhWJsKcLpfwXEaOhNZWcDiw4uv2/kd6fCteLBFuIwGulhYqn3uPPz1i5+UHi4nX7Kfssx1Na/CHmgBDcX4yZJ2pO+64g0suuYTf/OY3/OUvf+Gxxx5j2rRp7Nixg8cee4zYWHGTefjhh4mOjuaiiy7iT3/6E7///e+5/vrrmTp1KrfddltwfyNGjOCee+5h6dKl3HHHHfzlL39h0aJFrFu3jiVLlnTrGfXQQw8xceJEqqu7FEnOP/98brjhBpYsWcKLL77IHXfcwbe//W2ys7ODqlFnAkMx19Rg6GHYiUE4DMZOBhK1GSweD7xQtpCXTHdijlJQdJX8iiV8t/hX5FcsQdFVzFEKL5nu5MWyhV01VAOkUU/hPt8SNnEeGgomfFxIIVdrb3MhhZjwoaGwifO4z7uERj3lpNuY8SKj0kkMbSQgoeP1C597MSOjkUUV4yjmLHaT4S3ncsffgmMSDpWGGS8xOIjGEXS0Ajgm5vU6l37Jy+vmUGVOTetTDmAw9T//CgYy+ZMACx5i6MQScg1Fc9co9jKNpiZRo2SziQwtm008b2oSjXOt/eSCzaeQODoGNSk148WGi8v5nP/iRZS3/fLnx46JAYQSGqEqLuan9Q+S4I9SROMmhk5KGcsBJtFCon/fnkGNTwf2X/1I8Hl/95NqRxI23L2U+QZybFHT5CTaKpx/9WAxW7ZAXBwsWgS3KQNPIetL7S8S2jw2du8Gb1QcqdEOhlXvFu+TyyWag7lc4vm2baKzryQJI4qKgs5OJGVwlTsich3ZuMX11NG/WEPFF6VMLy6ggnGn8LMti94CBQVBGx2K85Mh60zl5+cjyzLPP/88P/zhD3nmmWcYMWIEH3zwAT/96U+D62VnZ7N27Vpyc3P52c9+xpIlS7jyyitZtWpVsF4qwBNPPMHjjz/OypUrufvuuykvL+eNN97gpptuCms8JSUlPP744/z3f/83K1as4Pbbb2fr1q2kp6ef8vP/urj77rtP9xAMzgAMOzEIh8HYyUCiNoOlqAjSDxYyzXyID+NuwuFR8DpVJjd+hdep4vAofBh3E9PMh0jdX0jRIP23DRtgmKeGEsZxgIkoaFjwkEMZFjwoaBxgIiWMY5inhg0bTr6NjEYTQiBiFBVYcaMj0UICOhJW3ORRQjJNKEA2xyiju3Mkhfz1lY7X+rtXIztRSQo6VMeOW/D0US1ypkeh+iJQN2XFFZTO1gAfEnZ/02OLBQ4c8KeulojHgwfF67GxIr2sL+JoH1AEpmcNmgKkYGcWW1E9/oiUzyd+6X/iCfFYWAjLlon//T2njrakhMjoiz5EWVRxmAlIqJj9wvCDqY2RgAkvd83n+rufTGUPVn8N2qmwIy8SJptw/tteKsCxq5i0NLhIKmSCuvcUHKGroW8k473C+0+mX5rC8P+8kuRUGcnjEY6Ew19/53CILs9tflGGceMgK0soZyQkgDo45zZgv5FuowDD2sv4jvsVkhNUcjlFAj4gRvTuu0J0wx9FHYrzkyHrTN14442sWrWK48eP4/V6aWpqYtWqVSxevLjXupMnT2blypV0dnbS3NzMG2+80aeDI8syDz30EOXl5bjdbvbt28d3v/vdXustX74cXdfJCbYGh8cee4ydO3fS0tKCx+OhoqKCZcuWnVGOFMBXX311uodgcAZg2IlBOAzGTgYStRksncfsTO9Yh+ZViWmu4YA2odvyA9oEYppr0H0q0zvW0XlscHVarmo7c/V1KGjI6HTSvZagk2i/wLbGXH0drmp7GNvEoKARTzsWPOhIdBLNJs6jk2h0JH/Kn5jqSkiMpjyicWsxERSh/+EPcOedIv1o+nS0fXuIRqjkBibjofT3i/XpjlJFevzQcwvo2QmVRBkJcBBNM8m4XEKAzeHoenQ4RJAhLk789cXvuWdA5wG90+BkdLKoZsUK8I7IgaQkUWdTViacqPfeg/Z2WLpU/KkqVm9brxqtZJpZyGcMw97rWAMe65EuAa/+7idtxJ9SZzyVOrxXC+ff51aZXlLASHcJIyvWYfbb7qnAF+H6ZTEz+fF37UxzFiFnjxAqJdHR4r2pru4eTQzIMn7/+zBvHowZ49eVHDgibXVg76knOhG3NYHouqN4/Z+BU0Zjo7BRfw3rUJyfDFlnyuDrISkpzFx4g39rDDsxCIfB2MlAojaDJWZkCh/Y8nF4FEZ7D3O5+hnROMScBQeXq58x2nuYTrfCB7Z8YkYOzoEzpadQxGwmcYBEmoij3V9zYkZFIY52EmliEgcoYjam9JTgNtPY3c82raTQiAkfKjJtxPEll1LMBNYzjzbi/BN63T8Z9hJFZPmK0b+9L7wVS0rgo49E6tgjj8Bbb1FtGYfPXz8UruM02Mavp4O+JotCtltoKY7mCNfxFp2dIpUvPr7rz2oVtVKlpWKebLP13pdvkGLLva+9jr3YzvE/viXS/FQVsrNFaKyqCj75BLZsEYVcR4+SSFO3cwxEoJJpiTgV7ITj9HaJ4/d3P5Hpe7I60DF4sATTUy3OFsqy5nHMOo79U/KxMzBl557jCkR9IxljSmcpV30/haKvnGhFW2H6dBg2TGjo+/yumaKgZWTibWyhwRlD+VnfRn34l/Ctb/XZoDgSVAYm8a0CdksmamkZGUfWE3UKP9FmEJFvTROpjQzN+YnhTP2bkZWVdbqHYHAGYNiJQTgMxk4GErUZLDNnQnVMHsd8mcxRN6KgkaQ1Ui8PJ0lrREFjjrqRY75MauPymDlzcMe7Yradc5UiNHRyqAj2I2ohIdifKIcKNHTOVYq4YradK2bbuVEuYARVjKas1zYgdZODPsQEmkkij0OMpJIj5OIL6QNkInIVuL2Z3wxvxXHj4IEHhGdQWwvr1pER08pybsOF0udxA89VwIsJ7wDGN9TQ/aMPjQRZULmUL0hT7MTHQ0xM1198vJBIb20Vf9Om9d7nlywc1Jh6OkJ2UshxHKCt3oW2azeMGCEiVLW1cPQotLQIp6qpCUpKiKf9hGIGPfc/UMqjJgX/7+9+col1XZ+vD9RmjjGaDz8E9UgZcQe3ME3bRUMDNCTlkUz1yXdwEgaqVJlBFTVflRBVuIKWRi9qxTGR2hYdDWYzutOF2t5BR3UL7R3Q+c4KvrjtDY5++ye0vvnxoHu2hdt8uc/t2luZZP+KNG/1Kf0sKyDyYR97DGYLCf2hOD8xnKl/M1auXHm6h2BwBmDYiUE4DMZO+oraaMgnjNoMSB49ZJu6OvimaSXfld6kQR+Gisxey0yOWiaw3Xo+KjIN+jC+K73JlcpK6uoGfHoAmIenkGJp4xy240NBQ6GCUWzkAioY5W/7qnAO20mxtGEenoLVCuPlw2RRHZyiB7apIotAdx8QCn4Z1HIhhVzGSrKpYBylWBBKtCI6JEU8ufG0RZDqVF8PXi+aT8Xp1Em2lzCZPVj9NTUBvD1+NxcTTTXo7J2JBMbtxtzrOito2HAGhScS1ZDUOEloBmia8EPj4iCZ7rY9na2nZIw60EQSx8linzaJZpeNlpRc2LpVfDaamkSUymwWqX/V1dDZSSa1wea8Xydj3V01Sv3dT3aoZ53SY57FdmqWr6Tj/keQq6s5t+R1plhLGPPhH7r1Bxsskdq1DzMOazItaiwmRzuu0ipRw+ZyoZktqG0doKrEdDYQ47TjM1m5cuuvGV2yCuuh3SKKM4ixBmrgBrLtCM8RErRmZNQTRqUj3a8bIDlZhHD9DMX5ieFM/Ztx331hpm8Y/Ftj2IlBL/xOSaCXyMGDcN1196Gq3ZeHSyBqY8JDDhVI6Fjw+CNSXVEbEx7OVYpYPHyLqO8oLAz/IKGF9YDvUAm3Ny8h3uKiU47jI/1bxHsaSXOUc9g3lte4lU45jniLi/9qWoLv0OAKqaXtReRr/0BGw4uFXZzFai6jmDxWcxm7OAsvFmQ08rV/IG0vQj96hEkcxIQXHYl60tjGLDxY/CpxXeLFMpDDEcZSQgLtpHOcZOxBcQCBHvGkLte+KbwVS0pg+XL0hESapBSOtSWitrRyLkXdlO18SDiJ5igju8mHm0LGdiam+gUw+ztChYoxBKJBx70pzHEWcnP7MkZ7hR3quqiZslj8fVhLirlbWsYCCgG4kELi6Rj0uAKTWsU/tW3QUvjQeyVtNR3objesXCmiUtHRYjBut/Dujh7F7E+1DecYgyFR7WqD09/3zihf6SCP0p1k7Nxy9BGkymPo7e3EjBrGgrObmV1/eiW3TXiJiYFqcw4uLJicHWh+GfRjmefSIcchoSOjYdK9xDjsDHNWIes+LJpzwM5QKAPZh/gsCw1P1V9BeCp+IAk6ZS4XvP56sGZqKM5PDGfq34xbb731dA/B4AzAsJOT0IdjUV4unmO3g93e97KQbQe8/3D3cSoIjOOLQpoeW8Z7S4p56CH43e9gyRL4jyu+w1NPQdEbxWjPRebomIenME3Zx7lsQUdHQqeZBBpJoZYMNH8y27ls4RJWk1T0ubgAJ2g0CnQ12u2joaxpwjhaYzIYyTEqk6cxVd6PrupkeCswex2YzBJ70y9mJMeoS56IacLg+kyZxuXitcZixcEhJlLEHCyIxvN2UihiDoeYiBUHmtmCaVwu8V99jE1zIvuVDJtIYhTlLOZ9xlBGPN0bE5kBG25M/o5Hp+JLvTLnovBWHDcObr2VpjaFFR3zqHMnEu+vtQlMyrwo+JBoIJVPWUwNw3tNtk7VL9n/CnqOU0wk1V7KbRIwhb3kaiWc1bYOq7edK9oKyOwopr1daAvExMAYXzEX1hWQILVzkWkduZQwj3Uk0UO6fAAE6nYSaSGdGnQgSztGu0NBbWkXn43GRuHd5eSIRlheL7jdJPWomTrRMU5VZLG/751OYk7REQRWIFM9huJ24EnNQJ40kcvvzCVh1thTepxI6SCOtjZI049jxYNXN6GpoGk6rm370VBQkfyfH43EzkqcmohHDUT5sT8Gvo9T5UZ1IYGISg0bJiJUDM35yeAqHA3OON56663TPQSDMwDDTk5AYSHa2nVsy83ni8o8ystF/yKLBS7UC5nb+B4S8FXK1XwlLwguGz0aLh5RzKwjBcgXzoMFCyLef9j7OIXnuSvtctrfWUdtcTu1HQVstuTTNCyPGbHF3B89i6o3/0qVqZzYzHYmUSXl9wAAjIlJREFUsA556tSwGuwqhav4luc9THgxAZWMoJZM3EThIBoXFsZyBDM+LlC/wv15B9x41QkbjfKHPwhBhAcegIULxboFBUGHKjs2nrTaz9CdLi5z/4NjejbtUhz/5AbSpHqGe+uZV7cOXfcy0neU7Gg7MHARiqws8HRWYkYjj4PE0E42VbzGzTSRiuJ/3YxGakcZXDUL6Vg5ICYR0TjJpIY4Wkigtd+Ja3/Tl4FOdGftX4aqLkVRTr6uetPNPPZCHjPbljJSr8Ac4m4I2WSNWkZQxBwuYTUpfTgJgUn/mUAk1z+bY6SkQKOUw0WtL3HAdBZXuQtYmZhPY3Ie8ceLudpTQJSvnsnabl7SbucI4ygjBzPuU6xgd5wWUpjBdkZ0HELSXGhWE7LVKqS2Az9QyDJoGqYIRUsGitn/4wL0/70zjZ2n7HiBOsJoHLTa0kiMSoBZs1Bam8iq2kr7yXYQAYFPQrjvYyztmDqaSKSRDuKQUdGioohqaiW2sxiTz4mQlJExoaHobsz+vQ/WjTk12+vBCNWpQEjyI4oMJ04Mvj4U5ydnyv3L4BSxaNGi0z0EgzMAw076wW5HW7uO4g31VD1TwJHPijl2TNTiNJfaiVr5Hu2rNtO2ajPRn79Hc6mdujohnlX6aTFVzxRQsqEebW0/0ZUT7D/sfZzi8yx/6XN2HbYyvnYNMZ31LPz/7Z1nmBRV1oDfzpMjwzDkOGQk6CASRRERUAyA4Cqiu2YR1oDx04UV4y4mzGlRUVxXzIKogIgKKKgEZRgyQ5ycQ3ff78ft6twz3RMbuO/z1NNdVbduqtPV99Q599zCpXTMXEHXX5Zi++MFRh94E/PhfUT8uIrMqo5BKVIAFhPoHMGD9UBrDlFCNHZ06BGkcgy947wOMO/4HQYPllG4/OEeWe7xx6ULk/uCsjt2YPj3k5iqSomgnDh7Lm3EAd4zTOc/EdfziyGDM21raWPdi8lWQWzpIQyF9bQOvPsuFlupMwpab7ZThZkL+Yx48pjMuyQ5FkbVIdDt3+th4dABLcilFUex1WHuk0aoVp91jOK119wsoTWwaxcc/bOArmInBp2gGqNHeXoEKRygN1voyC6fBYJPVgSQTxJWG5yjX0WysZAz9D/TMeoY0wxLGZr/GReWL6VT9DEG2H8mlkJGsYou7ORsVjW4tW4dIwBIJI9YWx46YZNv/AsL4cgRGXyitFRaqYxGmuNde6D/nQr8hDusBzqgRERSZknC1rmrNPsDREbWa96Rv3JCZRfd+Ddz2Et7ftFnYKwuh6pqLGW5RNlLMGIH9FRjxIoFzY3XTvNad/XOT3uD/r51gP3QIfk20fHfEo7jE2WZOsX49NPm9QlWnBic0nKSmwvJydhscOCAXBsmMlJGETYkJ3NwSy4tvv8Is2UkvVjKpuqpZJJOOrm0qtpMx+otCKCo0kJWbi6ZJJNOJmNMSzGzg+Q/13Cg5ZV08Kd0JCdzILM8QP5B5tEQuNUj2nQmlxb/SLwowEIJvzCIM1mNDhsDKSWroIBu+nWkiGyKFj+H7bYLMLSsvV7JYwaSSzItyQHAhJ2RfMcXjKM3W4kn3yO6lE6HxyRkJ4775Yws9/jjLoUK4PTToXVreOMNh9uZETt6RxRBOyPFGvJFKpPs75PiqEsxMezQ9aNFfFK9wg1nx3UnFSNmx9taPXYSyUeH4FYWYaLa0zVMp8MuPOc4ybez9bMSaC53wQ5yljCDpbdCaipcdFHNafe/uoLrCh+nWmeh2BBPhd1GWw55lB0J9OQPjF5BKbzreLKhQ1BRDilFWaRW7SfXmEr3kp/5reJ00nU/0y4ml6GWn8kV+aRylELiAehCFtE0bJ+cy9dk0542HHIuMCzsjjlRZWXyN2O3yx+aTkeVY+23piTQ/04mPf0erw/R1UWUIIjetBZ6tpMH7XaqwW1WYv2oq7XnIO04Siqd7XsxGQX6ilLs1RZ0jrmkJkeAmSqHe7ScF9e8aCutNbyjH2C1Yn/qafSTJ0NGRliOT5QydYpx7733smDBguauhiLMaTI5qUlxMbjONxm1uNidp/uK7l+8ha68nEHl31AATGApmxnAOXxNLzYTSTkC6FW9mauqn+cbzmUAm2nJDgbxDRZK0X35X2x/zsTgNSfH9udOYpb/F3N5oU/+webREHjW41siKMeAnQ7sowU55JJEW7IxU0ZftlBlN2PDiOn4IY7+sIvWk2q/Z3s35ZFGmcdA34SNcSxHh91DkRJAccY5xF96qWcmq1fLeVFTp0or1FhHOGlNoXroITlArK6G6GiqC0rYqB9Cgu0Ycfpi9EIw0vYN7e37aCf2Y9OZOKDvyG/2fnxSeQ3tC5JJb1lLXwWSXWClfQwTiCPF4dom21hNC3I8FnrVztl1Bux6MNisPgpVfQklj39xE29VXc0NN8CECQR299u5k56fPs4BUYEOO9tNp5FdHU9ftnkqwsh764675eXkVKSgPfs5O+V3THnVVBBBsvUoJlslp9k3kpfQmT6Ru4kqOYqRAsqJwEw1HdiLmeo6r/kTqC69+Y0+bCfGEdhCABiMcnK/3e4yQwohI/s1Q0iQQP87o2nY6G0CGTChfe5mdAkxsHw5zJwJZ58NP/3UYOXURa6TyOUWnmUIP2HAir6yCnt0HHnlicRYi4ikwpmvGSvVmJzRO5u6rv6ub8jfsvvzQVirYcMGyMgIy3GsUqZOMaZNm9bcVVCcADSJnITL3CANh2vb1t9sHPx4Kbtjp1LdKZ3ISDlQ3vVlJoeyv6BNpZE47ERTwmi+AcCos9FB7CESGVJavo2voAN7OEP3M51FFqP5hihKsaInpzya8sPQtodnFQ4fhtLyaFqiJ4pSj/yDzaMhcK+HiWqsmJChBKRlJZF8BDqHS5qVCiIoIpYnjQ9xXdeMoJa93LxoHZ0dYYjdFSpzgLfhR7JtxDv+TAHfABPeCtVDDyF27MBeUoY1IgYRFUN252H8cKwrkaYy2pqPcGbZKpLJJUqUU6KLo9gQzxNJj7G27HTyq5K5aIOnV2FJCbz2GmzeLBde7dJFumAeOCDHo4mJ8tiQITBsGIg33ySJQuf1rkh2nvOKtHNVdtDXe7lWX0J9W7ydvoBs22+/wcCBARJ26wY9etI282N+EYM4YOxMBIfRoXe+Ra/NEhWq1exEwoqRiTe0I+/ji+m06kmw62lpO0KioYyukaVElRzDmldEGVEYsPEhF/MtYxjAZgbTcIN6gFiKMKN3RMqUva6LipRvAIqKPBML4bAxNC2B/nfasa/ByzJRBXYQhUXokpKw2aDgm81YGryk0Egkj8H8RArHsWGg2h5NVUwSBwrb08261eclix5rWPx+5Hp4ArtDxhrqBZD20qUwvh1xN96CgfAcx6o5U6cYW7ZsqT2R4pSn0eXEXXH591J2L8+kshIiImR03l1fyrlB2363Ne7cIHeSk/m5y1Sy9hqwVdq4XLeUQbGZpKbCoNhMLtctJV8ksMI+lt10woaBOIo4h68ZIVZxJuuxYcCGHjt6bBg4k/WMEKs4h6+Jowg7evbQkbk8Rm6Sr0UpN6kbc3mMPXTEjt4j/2DzaAi862HEit0xQDZgw4jNMdFYYMVIGVEs4kZerLo2qLWZCgth4c6JbKen09e/ppC8ZURSVGaCGTNkkAmQFkttPpTN5gqBnptLVZtOHDpkp6qgDHu1nBuSnWvmi6zu/GFLp4hYIsoLSBY5GLASSRl6UcVxayJbSzqRSzJCSFkEqURNmgQtW8Ls2fCf/8DLL8PcufDvf8PHH8OqVbBuHSxbBq+/LvW7r8wT+Y2+QQUntwM2QxT6GvqhroQ6sGnlcNMTAp5+uoaEubmktjFQaEkhnkKiKvPZTSd0DqtGsOU290CwsbCjZ+A5iZyd+z9iq/OIpgyjEaKthUSXHEVXWIgQEE0ZCeRxGf+jCzu5hUUNLgcWcC45oM2z0ZeVyd+P0Ut9t9mIbmIXPwj8v7OLAPMk64EdnZynaLNi37iR5S/vJWLDaqJoXnlMIJ+WHMeAXT53KyrRoaOl/ZDfAbuhDksfNAZaGIyGnjOlEVV0lMPfyUit4TiOVZYphULR9DgUl4MfL5WKS9xStsdOJTc5neTcTHrplpJXaWPnHgMVl0zlDIerX1WVtPQXFMilUUpL4b335GD3tNPg9tshPr7mot3zSEiQhg6zWY7HvzmQzu7YqVwetxQDNnpvXcqRtAEk79/MgYM2cgsMvMT9nMX33MkTdGYPCRTQn1+xyOUFOUwqeuwkU+Bzbh/tWcB9fFY1linbZJ3d2bYNPqsai5Ei/sH/+c2/tjyCpbBQDpQPH4a0NLjtNlffafVIIJu7eIKuZGHAikDvYUmxoacaE7vozEV8SlV1FL/9NptzznEryM1Vs7AQJk6En3+G8vJkLuMjPmICPZB/kt5/wgIoJopNnM6g/B8hpxDmzYPx46VVRAswcdttsHUrbN+OLbkl234qIfnQMRB2pyLY0ZrFmTmfcExcSB/bRkawCjOV6BBUY6AaC+3Zx+yyf/IxF7I68TK6dpWylZEBf/4plQt/VFXJtU/z8uS4tLBQpj1qTWYF4+jLr5j8tM8dO0ZMtgqfENv1pS5vrVtx2Pk9r5YYHMbDB2kTkU95tQmrDXbRvOGlw4kYStn+yjq6b9worZF2G0JnoNpoQV9WhcFgwFBV6Qh4DYPYyMV8SDv2Aw0rB95uWDrAbrOh91akAGyB57Y1B13IbND8fNpWXMLRp9/zcKFrLtpxAJ1j4VsdApOowlhwhEh9Lf7GYUBjvggyiSoMn34IZ89t4BIaBqVMnWL07du3uaugOAFobDkJpLhkpw4g6s/NZBfZsGHgc8NUBuxNp0+5tAR88YUMvHTsmGvAqvHJJ/DIIzLg2+ef+ypVVVXwwgsyj/375TQakwk6dIBx4+S2dy9Ud0pne+xUem9diq3KxtHPfyarGKqFgaVM5QK+YApLyaYNrTlMBBXOidpWjAgMRFKBcLz51M5VEMEOujOM78mxpbB//yjKy+Gzz+RSLy1ayIB0w2yrGcb37KC7T/7+8tDwzmvCBOnB442nQuM6/uijMlbDp5/K/rnV9hSTWUoeiegcbxt1zjfbYMeAARsWKunCLqwYmcxSNu8fDzgsZpmZ0mI0aRKFA0bRuzccOuS6bzN4k67sCjjg1wExlHEWP2C0WuXk+JIS+P13qUyBPPbHH1Io8vMpNqfQqbAAu13nUKRw1n+Q+IVu/EkspbgvZmvCTgVGIrAyji+4mGWsKF3GkCHvcPnlsGNHYEXKG6tVpq+shJaFO7mbR2ocZLjmizWOu05d8suhhfN7ly61JI6PJ65rS5L26YkssfN362PNPiCtC41RZx1Q8O5n0gKiHRM2RHUVlRiJsFXJqHpoYeQFA9jYCDVx1cdnPztb+qiGAU01PtFc0rT+OK5LYbV9ODN4vdll9ztGcZwWpCEXMzZgw15UQHJzVyxIGrOatk7yRU04jmOVMnWK8e6774alICrCi8aWkwMHPBWXXluWcmi/jUM//UxlJViFgfeYSpYunc93wgcfSCXAsRg8paX+87VapatVr16wfbtLoaqqku5ZX30l84iLk3NeKith0ybIyoL166XHS0wM5Cansy9pAEc++5lKRyC1zQzAjo4pLKULmdgxYnRMALY7nC3MVNKKgw5fdj0VRGDF5PQj78xu0tkOwJcf9OW115I5flwqlwYDJJPLrSzjXL7ESgR67M78/eVBaV/Ky5O56y6pJB4+7MorLQ0uuEDGYoiMBHJzKTQm06uXVGi8iSzPZe3aZHr3hjsu2slkltKN7dgxOweD7u54esfbdCM2UjiOHR2HSSO1p1xYkcxM+Oc/5bymzEyuyO9LdrYrMMUgNnAPj9T656tHzqOyA3adDv2VV4J3IIqEBDh+HFFRQUzpfiqJoMIUS65IoYX1mFvdBXGUePjiA/zMQB5iHou4iUQK0WFnXNUnlH68klWrxjjHmjpd8ErV3r3wNLfUOjHb3dIXLuOlCMfcP4MB/u//akiYnAx3343+4YdpOyCO0z/cTouyXU1TyROE3wxncDqfOCM3yshrVkzVFWhLA2j3vRoTr3E9F/MZEQ5LdEPiV8bs9uCFupEJ9L+T5Iiy2VBoLmkCHUKvZ739DLJp43jx0ry/w07sIpYSj3tlsFaR4OgD73sYLs+MxkYA+bnQlvAcxypl6hQj3CKgKJoAx6T9gJYL90n9DuosJxs2AFDeN4NvH9vAsoMZVFdL5aVLF+hdvoFhw6C8RQatD27gSPsMjiWks+vgAJL3/ozNMWjdxAB2kg5CKk+//ioHdm3aBDd96tAhuPBCWPOhdDF74QWpSFVWQvfu0ipls0GbiFzK05LZu1cqYW3bwtCWO0k2CnK/3uxUpAAG6jZzTKTQi63EUeKITaangkgKiKcFOZg85hnYsaOngHgSycdCJb3YjhEbqeTwz1/+jyKTVOqMRqkIFpTAFbxFMvlYMWDHQCWWgHksi/o/LrgAvv9eXu/O7t3w4ovSZe/LuauxfPkR1393E4cO+c4/6EYmN/I8HzOJNdmj+O83SfyNzURSiR1X2F1/rkIg36gbEPTnN6JT8yAz16VIAdXH89m7JQ/3BXCf5obab6QXVlMEZm9zW7duMGYMZGYibHb0CCxUUGWPIN4mgz+4K4Heda/AjIVqBvAL0ZQhHKqrDcGj73X0G409WHLdLDzuBFKcwkWhikMGJOjdG5KSakn8zDPYV37NVvMZ7CtJJS6EwNLh0NbGJqZwPzZ0GPEcqBu91tsSyHk8A9mEvpEi6fnt7zBRpKDpxycCqNZH0Nu+zdHv4SGTFqp9rNmNNRfpREEHlMt3PGE5jlUBKE4xwnGxM0Ujcsst2CddzNujX6NPHzl/f84c+dm3L7w9+jXsky6GW27xuKxOcnLLLdhHnU3psPNYH3M2p/3jYmyvvcbixfDcc/DbnNcYdO952EeejW3U2dy66mL+suIvHFqdSeLezU5FCmAAm+lGJl0cc2lAKj/79wdfHcuPq6l4+EmqtmbyxRfSItUxNpfsbNi3D0x7Mpmw40naZq0mMVEutXLpn//k2m+mc9q7d2EqOoYNAz9zOjYM6IWNJ5jjtGzIwZF0e9tLB3CEp3UfMFWj4weGUEqUY3aRtOYkk88FfEqrVvLlfny8HLSO51OSyXe4fckZSaVEBczj+3s/5bvvfBUpDasVtqzOJfNvj2H73zIu3vwA3bzmH3Qjk3v5J5NZyr3MJ4lcztrxKpFUOlyPPNEsOu4WFQ0jVsof+KeHIkWrVizt8RDbKj2DZbzELL91DjS00wGishzefdeptAPSbLlpE3Ts6HatnWhbsdN65i9frR0RVNGBvdzAS5iocv4pGrBTfCDfY6wZ6rizsoEXG206BNHR8PXXtSTbsAE+/JDqvBLa719Hj4rNRFF+Sg/6vNlV1V5GjvPCXx+ZqCKLrhgaINR1MOWFG4H+dxpjvSvtp2y2lhJJKZsIFLKyaYmnEL2f/5IT4f41Nok5WUB4jmOVMnWKEY6LnTUrb74JyEnWc+bA5ZfLT+eka8f5E5ING7AvXoz98BHOW3U3I3a/Rnm5tM6Ul8PwXa9x3qq7sR8+gn3xYo8BashysmED9jfeQFdeRlR1ISPsq0njEI9xN1fzGlfzGk9zG4kUEiXK6HVsNfHlhxi8510u+3EOwmbzUFxacIxHmMsSpnEbT/kU565k+SOJXKZWLybvva84/o9F6HZmMrR6NZP3PUlybiadqjOZWb6IERVfcXnOc1QfyWVk1VfMyH+KTsW/MiT3E/7COxykNX/SnaVMpSO76cfvHn9qeqAKI54e+C4EOjLpQQlRGL2G86kcRe/2BLZa5TF3jAhKiKoxj9qmO8SLPIzZ+7AezeUCPuNR7nIqVJoidSEfk8oRzuQnzudL2uCptbqX6nfehdv3rlv/66FIMW0aa6PG+tSrE7v91remQYMeIDpaxiAHuPde+SIgOhosFqqTUh2Kng4DVo+BiLf7jg7XH2AcxcQ5AoYIh1XAhp5CEmuoTe08yd0e7oTuZbsj3D7DxU5w4YVyKlqNdOmCrWMnqKogRhTRgX1UEhE2bQgHhpV96rR41DZvTg/M5vFGH5iF6/0J9L/TguMNXpZ8HsindiuOcS0vhYXCEkdRQKv1qU50gfxfCsdxrHLzO8WYMmUK77//fnNXo3l47DGYO5cjR+DWW+GRz/rSsWI7H81azeVlbzLH9hhLkZFinn0W3o+5mknFb6H/17+gHqE4/bnXlZfD/Ply7lBZGYweLQMhTJgg5/cEirLmHoEtNRUuuUQGUdAWCwXXAqLxhyCpzIYZO0nk8hh3A/Am13I1r/EYd5NELnoElaU2zDaXFaIuclJdbnNGLNP+DJLJ4WlmY6SKSLe3s65Brp0Btp85SjILuJ+dpDOEH5jBf4iiDDsGoniZzxjPLkdQgzGs4EEe4r9M5WlmB6zPIH6mxbGdVP5YyhX5FcRW5dCCPNLIhmoYUrGKVHGEruzgotK36VP5C9GiAKPDgS+RfP7J/RwllfUMph+/E+1YF8m9HUkUMpgfsXi57chzRdzGQr9/kN4KS2UlROE5GUwHdGFPwDy80/sjnyR+s/elm/1PohGMZTkAr/NXLuN9zmMF8Y68YyjjQR4iDc95LzUpUN7EUi5NOPHxcOaZ8NRTTDZn8jLPeaQ7TujRqQRCxidPSpLK/1NPSWFfvhzMZsx2u2PQGvzQQw5ircRT7Bxc6YAIKhnbYy/vb+5W5/n5S7koqDkY4TCI8yYvD378EYYOrWHRXqCgOpoIocNCNWAlWVmmPNjKaZzNuhrlwN16+hmXMIwNjdqH4Xp/mnJ8Eq59UESc37oFqm+4uAY3BV8eP4NrCc9xrFKmTjHePJEtLfWhVSvsR4+y5v6vGW1dyZW8SSe2oUcwqfgtdrOcNhxlNgtpyxFesl3NhYVvocOOfds2ip95kzm/Xs2RI/KleESEDK2dmwtnnAEdO0rXuZgYnKGgy8vhrrtkZLmDB10Bk1rocjlqTfao3pdfysntZrO0UNhsch9klLX+/eX49LffPCOwzZsnX8oPGgSdO7vCfpeWQg9DIp84fOf0CKdCNYaVnMs3TkUKwG638/TiRAZVycVGQ5WT8shEEJ4jTu0BH0uJT3r3P4BEcunH73RkD3Z0XMdLxFHsyMNGWw44rxvDCh5lLp3Yy40s8lCy3OnELpLIR+j0RB3fx1nWbykR0Vh0VXQs30lLcRSjI3qaCR2zyx4mn0SnC51Ga47QglzSyaQag49lSGtnhB83Hu1cAkV+z0VQQXW1dD+02eR9j/RS1kC+rQ6Uh7/03uSRzDg+c9rOIqlkLMtpQzZpHHYqaVq7O7HXEX6gbpQBsSAnu33wAVitDC75gkFs4Bdcc/Nu4cmQ8tVcK9m8WY70Cwvl5DeQn9WueQahDi6k5cB1b7X5KweL453z2eqCuQ5BBMJlYPTbb3KO4oED8vnml7w8zLt3YKIKO3IR5xPVsbGxaMv+oO+pdN89HjYy0NQ01/jEjvwfCgcGsimk+38qyUr0HxuBq8NzHCsUzcbWrVsFILZu3dpkZc6bN6/JygobHn1U2ORQX1hBfMG5YhDrRQkRwu44bnP7/JH+ohq981wJEeJ01gupzgTeEhOFuH/YKlEx8lxRfv54MXy4EDqdEKvJEO9wqQAhurFDfMG54jPOdl7nfv6/TKixjJrOL+Qmj/0XuMajXTYQ1ehEMVGiWgbk9Tg/iQ9E+/ZCvPaaEA895JCT6dOFGDpUfr/pJvl5zTWuvp0+XYhHHxXf3vKBM6+6bMVEinWcKT5kgqhG53HOBuJJZosxLBe/cJrII16UYBK/cJroQmbA/niHKcIGwmqOFGVEiGxaiQoMohyTR95V4MgzwqM/3Oug9Vdd2+e92UCsJsOnzqvJCLqcQHl4b//HAz7tsoEow+SQBc98rSAq/fRBsFsVCJGcLITBIITJJASII71G+bk/l9apDAFC3H67EJmZQsTG+jS4rvfDe98K4sZB64XFUnP/1rT9lwkNKjdNsdlAFIEAIbp3F2L79hqerZmZospgdv6OKjGccO1t7L7MJC2k3/RmujVpHwYS3qaUNY1A45N8jI3aJ1Z0IT17G7MvbuRZ9RsK0D+L026vUU4aklDH50qZakaaQ5lav359k5XV1Bw7JsSVVwoxeLAQ55wjxCefCFFZKYTIyfF4OFlBrGSE3weWpnB4H0sip9aBUxI5opBop5Kyj1RhxaXIZJMs/qSzc78Cg8gn0rlvdUvnL/9skh2DFp3PuWKHIvAbPQQIkUVHD2XJ848Dn3M2EF8gB7zx8UIsXLheDoYDNbZzZyHatnXu12fwrW1lmEQpFr/5lGESW+gu8ogXlQ7FppiIgNXrQqbzPtpAlGOu8SFdXUP9G+OPTRtkedc71IGXvzz8bUVu/eqtYHvnGUhugq1TGQhhNss3CY4K2EBkeL2QOOL4rYRahgAhPvhAiPXrhdDrG20QaAPxatRNQfVv4H4PrS/DYRDlrkxZLEL88UcND9033qhRnk71rS7K1E/0PWWVqUDjk1B/R6HWoQrEI9weFsrUJOr3YvJk3WwgXjrrjRrlpCEJdXyuAlCcYmRnZzd3FRqM7dul+4nRKF3iWraEt96S6wV9842cQB0RAcUtPMMT64HRfOc3Txm9TPgc3xsgxLE71/AqMZQ6XabactRj4nsrcunGbue+CRtxjvkF3umyvcrLpgWtyHXW77+4otks5GaiHCu39+FP9tGSDjW4lmiTob3Pn8NqQHpPpd19O3abLXBjd++WvosOtLC/9SGCamcEOW8sVNOeg0RThNHhrhZFBY9wh9+8buEppwujDjB7ueG532Ft4ndt8xkamlYcDupYqHl4cyVvevSrNhHeXQaE2zn3z1DRARaQ/qrC83f0OLd67JtCjFjmkVtcnHwACN/fakOyu7p9o+bvTbi57FRWysWdA/Luu86vwcwNOxX5jUEhpV/FeY1Uk/CnOcYnWsTSruxo8rL9MZJvm7sKYUtK6W4gPMexYatMbdu2jcmTJ9O5c2eioqJo0aIFI0aM8BvF448//uD8888nJiaGpKQkrrzySo4f943+Yrfbefzxx+nUqRMRERH069ePd93+DGqjoKCA6667jpSUFKKjozn77LPZtGlTvdrZ1OTn53vs9+snFRHv7YorashEV/NfZrFO58ynWKdj1Cj/ZWhptS1QGm1n8GDPc717yxDXNhsB4t/IsVaJnMHh2QRC++O3+wSI9uVJ5vItI3wGpu77gSbyC8CKa5DrrlC5K1ICOEIyk3H9DuawiK30cF7bluMUERnS3BFtPkouMQCcV/lTkFe6rm/cYS1EUOpUpDRySfGbdj7zHCt1SGoLoNAcg8DfGeBzbAUTQsojmPQ/MDSk9te3LwRAie88uae4y2PfGuKUXZ96DR3qo0w1tAxW1TNCdTlRDVORZmTjxhpOLlmCncb/7Z/IRPuZM1oTCeTXnugkxXt80pRUyddAzc4aRjd3FcKWr4+dBjSvnAQibJWpffv2UVxczIwZM3j66ad54IEHALjwwgt5+eWXnekOHjzIiBEjyMrKYsGCBdxxxx18/vnnjBkzhqoqz7fR9913H3PnzmXMmDE8++yztG/fnunTp/Pee+/VWh+73c748eNZsmQJt9xyC48//jjHjh1j1KhR7NxZc5jmcGLEiBGAS4kKFKRuyZIASpWm4fhRqEaNgiqdjmjAig4r8vtXa/wPz7S02ubPJlGl02FHThD9YYP/fCpxlemPfGpbdbJ29NRgpXHjbC+LVzARnDQ0dc1dobKi81CkAFL9TJTtzZ8e1yY4orwFO8hxv86KjviAvVnz9Y2JFinQnSy6+k07gtWYGmnhy4aiH5t9jo3ls5DyCCb9FbzVpMpioD+VfvzmsR9M8IyAbNokzdCNzFjqF4K3Xm0ME44ereHk00+HzUKn4Uoaob1Fb8GxRqpJ+KONT5qD7xnVbGW74/2cVLjocVha7ZpTTgLSyG6HDYrVahWnnXaa6N69u/PYjTfeKCIjI8W+ffucx1auXCkA8dJLLzmPHTx4UJhMJnHzzTc7j9ntdjF8+HDRtm1bYbVaayx76dKlAhD//e9/nceOHTsmEhISxLRp0+rUnuaYMzV79mzRt29ofv/Tpzsu9nfSwciRwmPejHdwg0rwuMzfHBvvdN5pasvH3dfffauvv3WgfBujHO++s/s55l2folquDbV89/1ghaS5fKgD3ZfG9LFvzLqHUu+mksu6bN6V8FfXutarqeTQBqIAQ0jPynDo+4aWzYsuquEP5QRsX3P0Zai/6VN1ztTs2bP9illj90lz9HugOoQyx+5U2mwgttGhRjlpSE7qOVMGg4F27dpRUFDgPPa///2PCRMm0L59e+exc889l/T0dI849B9//DHV1dXcdNNNzmM6nY4bb7yRgwcP8uOPP9ZY9gcffEBqaiqXXHKJ81hKSgpTpkzh448/prIy9BC4zcHChQtDXjJpyRLHF3/zExwWqq/W6JzzZgTSZc3dbc2Iy/JUiWdaLVf3dO5pCDIfKxDnxxYzia9Ca7AfzmZ9rWniEM42h4oAbFCjhSdQO93Lrc8b4nBwfQsWgbRW+rvfAB3JCXO7FOT4cVE8QlpIeQSTfoBjgd7mRCDviTv1mhuyfj288Ub9KhUEt/Jqva4vIr6BatJ8fPxxDSdzcoK02Z+6hCrn4WIhaQ4WLlzYbGVvp2+zle3ODfynuasQtnzHOUDzykkgwl6ZKi0tJScnh127drFw4UK+/PJLzjlHdmh2djbHjh3j9NNP97kuIyODzZs3O/c3b95MdHQ0PXv29Emnna+JzZs3M3DgQPR6zy7LyMigrKyMzMzmH7AEQ1zcxNoT+cHp7udHobLpfJUaCwKL1yDfiHTFC6R04ZbOW5EKJh9LgIH1rwykkOh6+fX/lZeCSpdWh0G8Vv8nuDugUlRbO89jlXPuQl2UoPr0TXOguU9eyZt+z49gNcLxeAvXtm3xM2cqL4hAJ6Gm30U38olq1n7QAbfwtMex7myve4aFhXIRpEZEAMV+5luGguEUUDVySQnb31g4kBpiUJkd9GqkmoQ/EyfWbXxSXwRQQWSzlO3NQDY1dxXClgISgeaTk5oIe2Xq9ttvJyUlha5du3LHHXdw8cUX89xzzwFw+LB8SKWl+b6dTUtLIy8vz2kxOnz4MKmpqei85vpo1x46dKjGehw+fDhgOcFcf+zYMbZt2+axZWVl1XhNY1BcXLc5AE7rFPgoVJrPvL/BvrdC5S+texrwjTJmDTKfQNzC08Q7ouzVBQH8l8uDSptMLvtpG3IZNgx8xCRySK4xnb/zSeRyJYspC5M/g3BgC/0oJRoIXwtbJ3x//0le1pvaCCb9I9xBImXN2g8C+J7hHsfqNWhcu1ZujYgNOEC7euWxj04NU5lw5dNPSTmFF5kNhlADSgygpvCJJzf+AoyB/yBSDYE2aqjGxI9ez6fmYhMD1csJPwhgJWOBwHLSnIS9MjV79mxWrlzJf/7zH8aNG4fNZnMGligvLwfAYvGNwhIREeGRpry8PKh0gajv9c8//zx9+vTx2CZNmgTA999/z5o1a3jiiSfIy8tjxowZgEv7njNnDllZWbz++ussW7aMDRs2MH/+fMrKypgyZYpH2nvvvZctW7awZMkSlixZwpYtW7j33nvd0swApgBlwHxgA7AMeB3IAuY4aqxp/jOAPOAJ1qxZw/Lly1m0aBHZBw/6vHMVgIWDwCJgObAGeAILuT4PB5l2p6PcZVhY7/cBItPdA2zBwjsB8hE1tum5BpjQ+yubPNok+2SG46zsqyRu4FPOoSMH/eYRCBlO2sb3nOkTbEJDUyJllL9EvO/TRN4ixhFmvS4P4kBl1rbh57MpEEApEbzF/xxHbgCyccneekxhPvk/ijxkXRch634DcRSFlEec8633HOTvV/6e5G9gPlDGPeyn2hkovmkIJCPu92kwa+qUtx2Yu24dDB/ufAa5l9VQGIG/MAv5m/e8TxLtGekte65nRC9C9KkOK1xtCvj/VFKiFKlaCPWlweYmjubX3M9yjYkTJzJjxgxuuOEGsrOzWbRoEcuXS9mLobhRytT+9wxUU97M1nsXz4dJPcILGwYK+QcAHTt2pKysjPnz57NhwwaWLVvG66+/TlZWFnPmyLGRNiaeMWMGeXl5PPGE1xg2O5sbbrjBI6277H3//fehVbCR53A1OGPGjBFnnHGGsNvtYuPGjQIQixcv9kl35513CkBUVFQIIYQYP3686Ny5s0+60tJSAYi77767xnKjo6PFNddc43P8888/F4BYvnx5jdcfPXpUbN261WP76KOPQprg1hBAbqD5prVuXhn5TFT1FyCCOgab8JcumHz8bU0VgOIOHg25HO8AG9pnbQEo/ssEZ7kLuaneE1YDXR+scDTXhNSF+F9UtSH6pLHr3lQBKG7k2bAIQLGSoR6HjzsWmq5T3h98IMQbbzR6AIpJfFDn52Wo9zNcNn9yFZDzzjvh2tfUffk600VlkOkrQdzBo6KqCevYnM907wAUubm5fsWsKQJQvM70sAhA8X884LPA+qm8aX1QhV5M4oMa5aQhOakDUABcdtllbNy4kczMTKeLnebu587hw4dJSkpyWpPS0tI4cuQIwstFTbu2devWNZablpYWsJxgrm/ZsiW9e/f22Lp29R/WuTFp1eq1Ol03fbrbjperpB38BogA3yAR/tL6Czah3SX3dLXlE4iGcBEIdp2poyHOH3APwuHdbu924vhuQ+ezzlQZET5v50Oth3aNVuaJQDbt/R6fz7ywn63ib52pUCern0gLfC5yWlMlO+gZIGUQHD4s15mqZc27+tLVjytmKJwMASieeqqGk0uWNIpV8GSikAQI4v9DYuAoqYig059cvPaa//FJY7n5ubOXLlRhavRyauMdrqzX/OeTDa0PiolhW9IoILCcNCcnnDKludMVFhbSpk0bUlJS+NnPEu0bNmygf//+zv3+/ftTVlbGH3/84ZFu/fr1zvM10b9/fzZt2oTdbve5PioqivT09Dq0pul5772MOl33zjuOL34GLwbhG2jCW0kSyLlNRj9BKfwFm/AXlKK2fAIpVE25zlQyvotF14ZWa5vbfqB2Agg/QxczFR7X1mVwo5U5nwfrHJWwqalpnSkDvgsnE2C/OfC3ztTZIUaeDCZ9tGPNMXeao/3e66f4a3/QpKXJdab8RRitA4F+M9d2/rZe+cZRWK/rw4Hbbqvh5Kef+sxxDYVw+B02Nt3ZjtHP/4e/thuxcRZr/aY/FdACgnlT1siLXwvknE4D9VyluwHoy+8+a7fZgBwSA06FOBWIoYjzWm4CAstJcxK2ytSxY77zXKqrq1m8eDGRkZH06iX9kC+99FI+++wzDhw44Ez3zTffkJmZyeTJk53HLrroIkwmE88//7zzmBCCF198kTZt2nDWWWc5jx8+fJg///yT6mrXD+uyyy7j6NGjfPjhh85jOTk5/Pe//2XixIl+51OFI+Xl5fQNMQKo0yrl7y2wYzBz3sjASpI2SNeCRHgHk/AXbMJfUIra8jECRX4Uqnbs86wyNErY7CIvC5s3NQ3o/SmMwbaziMCh5v1hw39dbMACHgSgktAeDg31QA8mH/c0i7nMbxr34/7yPJXe+P0fd/scq+vgtz7cwfyGy+yyy2C+b371ua+l+PZHm32r6NOnHpmGSLgNjGq0SgHMnOn8Wpe6nwq/w2Gs9jlmQ0clFmx+emAKbzdBrcKTQHPPW1LTytF1w/v/9yPGhoU98EHu8di3Acf0bagM3+G6B431DDMC12TLOVO1xShoDsL27lx//fWcc845/OMf/+DVV1/ln//8J/369WPTpk3885//JCYmBpABF6Kiojj77LN59tlneeSRR5g8eTJ9+/ZlptuDvm3btsyePZtFixZx/fXX8+qrrzJx4kTWrl3L448/jsHg+hndc8899OzZk+xs18rll112GWeeeSYzZ85k3rx5PP/884waNQqbzcY//vGPpuuYerJr1y5+/52gFarp092sUt5vgd32V6/2VKjcN3/R9twVhEDp/KWpLZ/a1pkSwB46sZQpAd/y7KCzj7IV7DpTWj38ue9Z8VXihNtnKP3lvc6UdtwOrGFUwDftApjEp34tTx9wGTYM5HY8nawRI2ttrzsNYcmqxMwRUv0qugKcQRTc+zbQOlPXTxMeD7dyU7xHHzcl/gZM4N/Nz9+xmggmvfv6Tt5uoI3xYiFQ/z7wlxzMZtf+p1xa6zUB883MhK/qv36ce56rGedwsXKds/y2jXvugejouuUfqhtmOCkXTz1Vi1UKQAiP35UNQ9iv79bUzOVZj30besqJ5CiplBOJzWsY9jRzG6Ue/p5/AsDU/K5tGrt27fJ7fD1DG7ysakxOWRXAk9zf4GXUhXNwrXlqAw7Thl0dR/MPHvZ4NoUjmntiQ75cdc9ry+l/BQLLSbPSqDO46sG7774rzj33XJGamiqMRqNITEwU5557rvj444990m7dulWcd955IioqSiQkJIgrrrhCHDlyxCedzWYTCxYsEB06dBBms1n07t1bvP322z7pZsyYIQCxZ88ej+N5eXni2muvFcnJySIqKkqMHDlSbNy4sc5tDHWCW0Nw8OBBj/2+ff3PP50+vYZMahEb98nLRSBGjgwc0KIInFugNNpORkbNE739HR8zRoi8nTliJ52EDUQWncRCZok7eURYcU1wLMMobCB20kmcwU9iI/2d560g/q/DGwHL1ra2bYWoPJTjOjBlihCTJ4sKR/vWcaa4mldFpSPP3bQXGxjgPP8wd4siELfc4pnvLbf471v3rRs7RDGIbxglvmGUWMgsUQSiGp2wg6hGTm4ew3KP9OWYnJM7X7dcJza8vUNYrUIc/fRTIbp2dRWwfLnrhoAQO3YIceWVzvM/zv8qYACRIkd7a5pcWo5ZbKWHuJMFogKjT7ocEsXPpsGiSmd0XlNChBjNVx790KmTEG+9JYT1j0whTjtNTqSOjxdHW/YWe6J61GtibxX6gG3YQzu/eVaCOEKKKMPscdwK4n83fiUGDPC8j69F+QbOkPJp9nv8naSbRExMYJlMSBDivPOEOHDBtT7BTqrRi2r0ogR9g050toIQ8fGeFdHpxJY73hAjRgjRsaMQFosQXcgU1hDuhU3Lq317ITIzpSy2alXnyfM2EFZ0DhmNEk9xi3iDK8U2eogqEAeiuokD32aKykohJk8WokULWe9Afe29RUYK8VLETT797t5P/n4Lzb15BwWolX/+U1SDsGIQVRjEYZLCpi3N1X/a92oQN/KsyCdO2EFUYRCFRIvN9BPvME1spp8oJFpUYRB2EPnEiUGsF4dp0eD1qsQgqh3y7l5HERXlV4BDuYd1vd/esuY9PtF4hNsbVKZsII6TKEqIElYQ63UZYjRfiQrH/2FzyK/WF13IFFvoKSpA7KeNWKy7Unz9/A6RaswRf9DVef9sIMrRO/+Xmvs3V4VelBAhrI4xR0P2iRXEIVLEf1/MqVFOGpJQx+dhq0ydCjSHMnX99dc3WVlhQ06O+F/8TPEL/cRCZolu7BBJ5IjDtBRWEFvoId7gSvEL/cSrzBRJ5Ihu7HAqVEdoKaxHc0RlpRDPPCPE2LFCdO4sRLt28nPsWHm8stJR3qpVQtx2mxA//STEzJlyUH/mmVIhEUIqIrfdJsTixULMmiVERoYQAwYI8dFHITXLahVizx4hdvyQI3KvnCX2dx0lfk0cJV6PmyVGtNoh+rfLEZvpKyowiKMkiR/IEAuZJZLIESDEGfwkttJDVGAUB2ktytf85Mz7+uuvl/U780ypzc2bJ0ROjmcFtHasWiUqD+WIQi+FwQbiZ/qLbuwQTzDbY/Boczwgq9GLSr1Z7I3qIeb0Xi5mtv9KVDgUWzng14lqDCI/IlXsu+Q2YTv7bGEzSmWrWm8U80d+JSZNEmLaNCEWLBBizRrZLyIzUyqD8fFCnHaa2HXF/aLaMWBxL7u2B7nNq77+FJp8osU7TBXFmHzO5xEp3mGq2EdbD4WqGp2wLv3AeQ+3b5eflfMf9Rl8Z9JZPMiDIpPOPuc2XPaoGD5ciNathUhMlMpTYqIc+LduLcSIEUIsfT5H2O66W4iICGF3a3sVRlGNQVR7tUtra33+BMUZZ8iK6HROZcr65VfirbeEOP98IdLTpTK1jzSffta+e/e3zZGPGDRIyuKzz7ry97fpPP/UfZVJRCkWUYVeHCBNPMad4mLTp2Ja0nKxNfZM8fbpC8X27VLUv/lG1rtvXyF69ZJiZTAIYTTKT7ciRXy8EKmpsv9vjHrDoz1av1ahE0VEi1IsNUbxbMhBSagDmKD46ishYmKE3WAQVr1BHInuLJ7mxpAU5MZob1Ntgerv/pJoEh+I3bQXFRiditRCZonxfCoWMkvsiJQKVQVGsZv2YjRfiS30rPdv0Ls+mXQUFY5nlLPeBoMU6I4dpfAajU5hrk3ZD/SSINR6uctaoPHJJD5oUFmpBJFLgiiMaCmqImPFvwx3CBBiMdNFaT3a0xB9kUSO+IzzxR7aiTe4Utw2bofIyhLi4jbrRTatRCUGYUUnrOjEYVqIEkdU1Pr2T32ut4L4mtFiH21FMZENKrdFIH6nu5hpWiyKi2uWk4Yk1PG5sVnNYoom58UXX2zuKjQ9ycmcu/gqXpuSyguVM9mJDBZyOUu5hae5l8cAuJo3+Iqx5JFMHslMZymPMpeW828jtWUyBuDWW+H662HDBigogIQEyMjAw32JUaOkH2VyMpSXQ2oqTJoEgwfL8+np8MAD8vzgwRAVBWeeCRddFFKzDAbo2BGIBYzFJLWFtLH9qD7rZu6MSychAba88Qx/vP4ClVhozwFi3dbr2MhgHuFeZvE0RybfxoUjBjvPOeUkPV26Uw0fLuvrjls7zMB35z/M6OV3okOa+39kCNfwJjtJ504WAjCHp5xOLb8wiK5d9ZhEFT+NeIxS01hEFWStGEX60TXkpfYiIhIiqkuIve0WEiZeAEuXyou//x7dsJH85fUxXFoOkZHQrp3sEwC6dYObb5bpH3qIDnGJiKVPIKw2yvQx5MV2ILHsEFHVBYBAoPdwUPJ2L/Ce26e5GpZhpoAWnMVP5JFKBAedfvcC+C9TuZ43uJrX+AcPkcIxIqjCGp1AxDmjQLuHGiY8XE920ZnFXM1mBmDDwFW8SRd2O+sycAD8Ywi89x78+quUSZBy2b8/XH45jBiRjH5JL4iJgYoKdOix6Y0ciuxK6/IsDHbXZHcBVEUlYC4rcLYzFAQO3/HYWOjaFbKyoLAQunXDcMZApiVA+/awbh089FA3/lM1k7t5DAM2j/62o8OOnipMRFLhqofRCGVlkJcH06bB/ffL/LU5q9XVYLdLgejXD93PP4PN5ryHdrc22TBhoQorRkx6QauYciYkbyaz/1TetC+mKLUbQx3rYI8cCUeOwIoVsGMHxMfL37zVChUVUu6iomSzQXZ1XBws3nQ1N/AverGVXFpgxEYsxeSSRASVWDFiR08U5c7+g4Z399PktcHdCDt2hIgIdOXl6Dp04OhNz/PnnTudpxulzEYi1Lq6p9d+szq3TQDrOYO1jGI/HUgkj710ZjWjeJ6bydKlY++czsg2sPs76Mhu9tOBfXQklxYN6solgFJi2U0nOrMbE1ZZX5tNPsdLSyE/X34aDM7fjHsbvb9b0aMPKs5t8NQ0PnF/7tZHpgRQDfwaM5xRxrVU2KO5uOJ/LOc8dup6YAux473rU4aJCKwY6ngH80jmCeZyER/xsv4mHr8xnY4dod2oLuQsSSFJ5FFMLJVYWMdQUjjOMNZhR48Ra71/b3V5BlUCN/ICQ1nLP3iIKA426O/+R4bRP34veTtziRmQHJ7j2EZW7hQ10ByWqQkTJjRZWeFG3s4c0a+fx8s3p5XG+zsOF6k3/5UjLR31wduiE+r5YFi1Soi775bWIjcqK4WYdUWO6G3aIR7mbjGSVR5ttFiEuPuyTJdVzYGHnARZv8pKIX5tc4EoBzGXf/r0JwjxD+4VZSA+MUySfXs0R4jMTA8rW96cecJ2xV+kNeynn1wuXULI9s2bJ8Rf/uLfWuaN27XWG24WFfEtxWeXvCpeHbVY7E08TeRGtBJVBrOoSGwp7Gmt5dtZnU4Ig0HYIyNFaesuPm9oNYtJDgniMC3FAdLEHjqIbFJFKRGiwuE2t4/WHm2/mlfFftqKClOksLVqJcT69X6rbE1u4XA57SzuZ57oxg6na+b9zBM7HRYqa3IL1zVWIbKyhFi5Um5ZWcIltzk5QgwZIk0oer2wmc1i3+TZ4tFHhVjRZ7ao1JudbbLqDMI2bLgQN95Yp7VmbCDEAw9IK+zo0dJC1aqVEI895tlGqzQcdmOH+JU+ogKTqHL0WzkmUUi0yKKT2EVHcYRkUY1OVOIwA/Xu7brvq1YJMW6cEPfcI8Tpp0uTV0yMEBddJMSnn0qXQBBCrxfCYBDW3n1EYWxrsTOmn6g0Rgirziis6MTuFoPE52fOE9+OeFB8PXKe+OuIHeLRR4XHb99qlZbPv/9dFtOtm8PC1kV+9usnxMCBQpxzjhBXXy3EdddJV78xLBeZdBa76SD200ZspYd4h2niF04T+2kjdtNBFBMhKjCJ3039hS0xsUHfwlc4XLtCuYdl/QfU/LtyZ+FCaX13WN7PSMgUFRh8rLnV6EWl47hWjvvWkJaYxt7c+7MKvVjGBLGTzqLK7ZwNxFFaiAeHfiXeNs8UP5IhnmKW6KHfIZKThbj0UiGKi4V4YOoOsZBZ4gcyxKvMFF3IFK8yU5TQMNaGahDHSBSrGCnWGkaK1YZRTiu90OuFuP9+KcQWixRYx2c5JqcbrPtWgVGUECnKMYtSTKK6nvVzt0wFGp90IVMUE+VsT30tRwUYRMnceUJMnCgqYxLEUtN0ERUlxPjoVSGvaeVtWS8iUhS7raEXipX2OBEe45GEBJdDy5oPc8RnLWeKzYaB4h3TleIVw3XiOd0tYreuozhCS1Ggiwt6PbNAdZe/0brdw/uZJ5LIEVfzar1kwl/e3+pHi0d6L3Z6CjTFOFZZphQ18umnn9ae6CQlsWsyv/0mX2rPny+XqmnVKpnRo+Hnn2HZsmTiSuRb5YsvhnPPhaFDkzHU99Wbt0Un1PPB4G4Nc8NshideT+alwcms+uAOtm1PJq5KHj/tNGkMu/76bp6WNbzkJMj6mc3Qc/fnfD57JT9njkH3K0SVS2OB0QgREbA07WHa9R9Fl+vHcMFQhyXJYfXr2BHomAyVw2EtMHWqfGvqTnq6PL50qX9rmTfdujm/Gl54DsPMqzi/YxdK5s7DfKAa8/EK9AlJ6Dp2hDFjYNky+YY2JwedTkdU/iEAHyuVNSaGiKRWWI4eJa8qEp0Aqy4CnbEUXUQU2UMuZFH/N2i1WBpSoqKg5VXXUgqY3puHfuJEadL0JjcXw22zsK9ag7HTSOL0Uyn+LJ24MiiOSiduwlSMdmDPGgxnj4TcXEiWMtqli9x8WL1aCjiA0Yj+pptov3Ahd9jgwNSFlMzOJ+GTxeiEQI8dRo2UPxJCj/rnnEo/dqz8fPxx6NxZmnQuvth5PwwGmDAkl+5ZTxJLCfnEk0ghlVjII5nnuYFWHGMwP5EKVBBJS1MBmIWs265d8t5rcp+bKzs6IUH+sG+/Hfbtk6Y6k0kWOGAAhjffZP+S38n85A/KDqyiR8GPCMykluzi15S2WIoOknfcxjjLUtq1nYrB4JI/gwFGjIA2bWQRZWVSZmNjobhYyrnJJC1Sej3s3Qv9InfyUPlDGLGhw85xWrCO4RyjJW8yg+m8wwjWcpxUrBjYnZxB35ytDWqV0DmC14QSZsBcexIXs2fD+PHOezuyXz5l38UQSyGgp9phfTtCSyKpJIoyR7h+O5qtoQoTBqpDK7cZcVk3dTzNLO5kIWNYwfPcRAd2O5dliKKUh/4dT3nuVWxfuAK6zeSWXunMmCH/ZwC2VKazjZspI4qvGMsuuvEWVzGJd4l0LHlRH4SjxkaqiYkxYYrUs6n6XAYWrELfozv64mI5fjeZ5KfFAmYzReV2dNhIIN9pfarEwn+5jL5spRs7MWLFTvCraPklItb5tabxST7xWChDjw6dI+hSXa0fx2hJfp+pZERDhT6Ow993J7E0l/Uxoygvjfa7nIQ/hNunVh+jI7SFDCwSmuWunEjn9zySiRfyfxNg6IXJfPvzVex4dwWLmUnbskz6VPzM/srudLX+wbdpUxl76BVMttBkRjh+gxVE8Aun0Y3ttKQ4pL7NI4W1DCePZN7kWp7hb0Q7cq4vZcSwO6IXiQV7iSjNBZLDchyrlKlTjBtuuCE8TaRNSFISLFzoeWz8eLjmGumV5+MydqIQQLEwmzX3xOSa3RPdqKucmM1w8fNjGF/lcoWMjZXLAtlsWt+OqblvAyiGTtLT4aab6qaEZmRgyM0lPvsPyD0EsdHyZj/0kFQAhg6V3wHconnqQI6Q7XZ0gLmkBHPpDkS79liEnrI+GURt3YBRl4yuqpJ2U4ax4Gq48UZvmboWLu3rX5EC2abhw9EDHadO5e9d0pl8wD2PdAy7psJSglMmAS69VJb388+yQg7hd7qJfvQmjNwDa9dCz57yTUNuLrz4onSZw3PQ4m+g7zxvMrlCwLkrVBMneii2AJMnwx9vWSkgniO04hgtOI0tzOMB3uRaupEJwGB+wkw1hvEX0XbzZzBhgm//LV0qhdpgkIpUerrcRo+Gb7+FM86AYcPgjTfoZQfRycJOzmZn9GmMPfwmO1NH8XHSTEyFmYyzLKVbJxu9s5ZCrq+cdewoxfP7712KU0KCZ3Xsdjh+HLpmJJG/PIFWHGENo/iaMXRiL0uZyk7S2Usn4J+MYC2ZpGObcQ18uAqxc6fPQMROzeF3/Q0uBXCQNAwI2nMkqGsASqNTiKuhLB/c7u2YG7pw+LtUYiihmFisGMnGxvdcSAL5jGQNNgzEUkwpEVQQgcBIDEWYCb+Qx964u5u9yQynC/NKxnITzzsVKh06lnEJV2ZkEAkMyujLID+/18pK2Ek6/+IO8pDn1zCKrfRjOBtCqhf4vgAxAPEU8Qc9GZ24B4OQ8UW/7nkzg8ckkhhnk28IcnPlWy+rFcxm/qA9g9iMHp0zUuMyLmIGb3M1r/Ew95NIfr1DQh/rc55zSd7a/nd0DkXK7lCnvNdjCpaNnEVRSToZGRnErFpNyy6nU7YzmU4VmWxkBOP4Mqh8dEApkeSRREuOIQAzVqyOofU+OtKN3UHX6z7+7bFvt7ueLQYDjJ43ivVn9uXi1bkkrdyMrQqobIWw5nNGhg6L/kL47/tBl6fJiBUDH3Eht/I8T3IrM3g36DwA1jGCNYxy7q9gPJfwWUh5BK6jge7W7WzQd8GeKH8f4TiOVcrUKcYDDzzQ3FUIS5wDy5MYs1mOJ4OhvnISSll+aUxrXl4e5ORILa9NG5ciBa7PiRM9r+ncWVpDunSB3Y4/RyHQHTyA6eWXib/2WnjtNXj4Yflm9+GHpbXt2mt9y69twUE3ZdJpsXOnLsrk99/D//4nFSt/rFkDzz0Ht9wi9/Py5FtqP3grVh6DGatVXqvVbexY2XdeihTA/tJk3uIqjpLKR0xiI4MZxAZ+QfbPTtJ53vHG/ifOZPrUi7j8nqt8+8+hgLJ2ra81c9kyWLkSOnSQCtfYseiB3mvWUnHJVL49mM6+NRewJXUMFjN0viCddm2n0jtrKfqR/pVVgwHOOktGZ9+xA7p3lwqVht0uj7dsCb17J/PEcjn/4QVuYifpJJHrHDTvJJ0F3E8+z/Mxk7h71GA44xH0l13mobSWGaJ56oz3mL3xcqJsvm/NSw0xZCWeSa+cbzB5qbsP8TAAb3KNx70qJJrVjGY0XxPrpcT8Of4O6ros5qh+eWzTR5NnT6SSCNYwkgMk8ANjGeBYqHkkaxxzbuA4qURTShx5J8wcKyuwgx7M5UmP45pC9Qh3s4pR3MlCrtROBvi9VlXJT00mNLJpByEoU3bAhhGT27yZCsxYqKaQeB5jLhFDdzN03eMYdTba5/5GedJ0EkuzpGnVYpFrSUZGQuvWFB5MdKgsOqowc4g0yonmDNbTlkN8wzmcwzckc6TOSg2AKc+l5Nf0v2PCit5RHysGqjERQQX6OlhAOrCbjb9nwvEN6E8fxODjxYy17WTAjqUMYm3Q+QigGBM76U4Z0XRgH+WYMWOlCjMd2B2STN/NQ7zF1c79igrXPFhwPHu653LmpqUUjbZhLa0k4riV6IIodAfXw6ZNIVm15asyPdWY6cEOEsljMD+EkIOkQwgKY6jk0ZI/ogbRwlKM7VgudEkOy3GsUqZOMT766CNuvvnm5q6GIsw5qeWkWze46ir48EO47z6XAqXx/vvSZ0tDU6QA3n0XhgxxWmyw2+GHH+Daa+UGUqGy2+Vn3xqsUDXRGMpkIEVKQ1OkAP7+94DKlLPs3Fzfc0LIa93dMPwoUiDHb98bRrHF1tc5kPzFawivvbEvNCQzsZjAfVmTNXPMGPnppoDq+/bljORkBtrgwNQxjPOwHqb7tUi5M2yYNFyuXAm//AIpKfL68nJpkWrZUhZbWgrrjKPYYnW10XvQvJN0/skDFBmTpTH0S/lW2BncIDqa/E82cUlaOvmHNxF5TncPa4DdYKDgq19IPHCIiuWdMX76DrpSl8J1Nl/71D+fOM5kI7kkk0wuP3EGiRQ5zyd8/CbcMyZg+2vC3LsbZcPPp2zNEr5nGJl0ZynV7GQCmaQzFRlEZhjfc6RFX5JydpBEHnYvG4fmOhXI8lHTINWqt2C0V9ap/rWhA7bQl8v5wOdeglSodtOZXfiXe28OHPB//BipQddJoFkuBQXEEEcppURzkLYYsPEiN7GLbuzqKus06JvHMWAj8YslcNl4OWqvrJS+h61bQ0YGmzYkk0ABvdnGMVKxUEkbDjKJj6jCQibd+ZazeYS7aEle0HX1Ji+6A+0d3wP97ySQTyTlTkVqP+0xUEVbDqN3BK8JRaEyYmXowaXQ0gaxsXSYOZXxv3Tj92eGk7NxCS35M+i8VjGGN/kbc3mcTfRnBGuxUIURK6VEkEJ+0Hm9wY0e+9XVnsoUmZmwdCl6YSMh2QA3OdZS/ec/5cukqChEYWFQfSGAAuIQGImllETy6cQeDtCNnuwLus4AXzHBY389wxrMMvW7KQNdfCyZA6YyIk3+3sJxfBK2i/YqGocufidVKBSenPRyMnu2tCR5K1Igj2sLWborUiAH8zfe6DJFmEwyvca110oFTa+HCy6omyIVDnz6qXxLDVKpcP+ekyO35GT5FlSncykeOp2nIlUDkZHyZXi+LtmZvTc6nTxvscj0NRKKAur4rlmke/aUn07301ryMhikEWzmTDmPymKR41GLRe7PnCnPR0bKOQ8F+przy9clExHhCEr40kuuE9HR6Ddtou3odHr2hLaj09H/9JPHtfp162g7Op0OM0YR99wC9Js2UR0pnfRs6LiDZ7iDZ5yLR2uK1E7SySOZnaQzPmkjBQ7HPjs6Dt7+TI31rZHcXAaPimRn94ns0nd3uDSeBUjFcSlT2aXvzt6u53JGuyO0NR7GMVvPiQCKiKbaK2t39b5UF+PzFl4ABZZUNne+hAJLqt/zNe0HgwB+o48zKqw/NEVKCzJZE1FR/o9HhDhfqgppiTpEW47SkiIS2MgZ3MpzPM1sZ7qdnceypO1dWKINmEcMltp/XJzchIBDh+S8UeA3BrCPDhQQz1FSiaMYAzZsGFjKVN7kWj5iUkj19MbYIsH5PdD/TgGJFBJHFUay6MrNPM8KLsCGHjs6ygntXpaSREqSzflDNvRMZ9o0mPDkKDK7jA+p/jvoxUrGcj0vcgVLmcRH/Jvb+ZMeZNM6pLzasN/nmDbdldxcaV23uerttMInJsqowdbQovkdIZV1DOc4LdhHB85mFTGUhPy7SMTzxVoyx0PMITBtTEdY32EqsYPSaddOHgvH8YlSpk4xImsdkSgUp4icBLCYANL35pprPBUpjeeegx9/lOc1Hx13rr1Wxip/7rmGq2tzYLfL+Uk5OZ7fNXJyODZ4sDyXkyPP2+2B8/MiI0OOAQwGqXCYTHLKhraZTPK4wSDnOYabXqoFpLjjDrjnHrjrLvl5xx3yuMEg6xwfL79HR/vOw9SOG42ueYwkJ8OqVVLD27TJNwjL4MGweLHsoMWLXUsu4Lg2PZ0jn2xkm7Ev403fUhaRTL4umTF8y2b6OhUpDaMR9lnSOT9xI5vpyzXtvqXDwHq40SYnoxs+nJReLdnaeyrHE9IxGCLR62VZxxPS2dp7Kgn9OsD0Kyhr14tKUyz3Ri6i0uGkmEcCTxnmsk5/rsckf6tj/o4VPd8OuouSaE+FqcIcz6auU/mhw3Q2dZ1KhTneec59rpPda9+b2gaThSQG1RVJSbWncb997tzH40EPagWQyWmsYxjHaMV+OnCcZI7SijNZ75x/qLmgZvcZS9ENczFEO95o9O4tlzLQ66VQ/vADaabj9GI7RSQg0LODdN5nKiXEOuf8AfzA8CBr6Z+k885wfg/0v3Msthv/5k620I85PMVuOtOP36nCQinR5NMi6PJ0QFSEoG1HT4VE+z0nD+wYUv2P0xJwKdBFJGDEyneM4HgI1kWAbIeNTnu5pNO53us53ZndFSlNwUpMlILUr19I5e2kB/vowPcMZRddqcJCrC644BvuhKr4h8LByHSsndMZMsT1/AzH8YlSpk4xNmwI3gdbceqi5ARPi5M3GRm1nz8ZcLcy+bE4veXuOhhihKUuXeRaWCaTa6qGxeLaIiNdg4kBAwJEKgwDAlq3cLXRaJTj1FatoEULqTi1aCH3NSXDo42jRkm3HW9FSuPKK2HbNvnphzZnp/PylFX8HDMKi0UaHdYZRzGGVT4WFaNRWtV22NOZHL8Ky9hR9Z4/+r1xFK+YbmKXQa53ZzRuIDJSWmESE2GXIZ1XjDfxvHk2D57xBbd3/B8/tJjEvywPsJn+vGj5O9+1msqsHis5GJUurVb9+mE8+2wqOveg4NaHOOO+84i5ZSZ6vV6u7WQwEHH9DLo/czNjn51A92duJuL6Gc439ZrilE8iW/QDKCPSQ6FyV9q8lS5v8v249/mja9fa01x/vf/j1/Bq0FYGHfAdZzGL5/idfpQTxS66YMOAARtTWUqaOZdffpH34JI+mfQpXe9p5Rg8WC6optdDixb01W/nEGnYMPALp3OINnzBBTzvmPvXEAggtbMrml+g/53oaHia2UznXVY6Ih7+l6kcoRW76cJ9POaInhdYEdaO2wFrz34YTx/g9/e1U989aAVbADvo7tzvRiZTWYoBGyXEsosgBMCNUqIxGFzKlNHoVcVRo6S7snbQXcG6+WZ5/4JEIKMHFpDIXjqzirNBb2DziDkh1RngAy732F/PEL/lVWAO2Vq8qf3FjBkjY0NphOP4RM2ZOsW41t+EeIXCCyUnimCoj5wYDDLwX1YWHDwoY1doipUQcr6ATifnMc2adQJG18S3jfn5UlE0GuU4Nj9ftrF9ez9tDCHsv79yJ12bzOb9suyqKqmcFpQm4+5PZzB4KrOtuyYzfXr9+tpmk3rg5z8lU1Qky46IuBaTSZ47elS2Ozc3mcxcyMxMprg4maoqWG8ajsEAHxunsj0/ndTiXP5r+gvn995Cz0v6oj8zg6gNG4gaPhxGDYY04KsVsHMn9OmD/orptB3sGGj2TIcNaU6BEsBxUpgf+QhdRBY7bL0YV/0RMZR6KFQuRUpHBRFEOoJzaMdLiWQe84Lqi2DGthERUlko9TIIeLtKuRQ+PTp8o2xWEOUM2qItQH+I1kxlKWsZTmlEMiNGwPBeMoCBXjgUqfPOkwuzWywymkp6OqxahdkoaFOZzadMIIYyp1L2PDd51CuGEp961hSkxn1fB4jDh53nAj1PWrSQi2a7z0N7mtl8hsslr4AEkh1BTFz9JfvKPcJhBRGkpACbN7uifrpRntqRCiKIosIrLwM6p7OsrHsFEeyjI+CpSGlukHZ0/JVXMTnulys/ncPG6srLioGvkW7nQkixTU2Vy5d44P1ccF8eQguO5FZvnZ9PjXUMI5kCqrDQib38z3w5v1yxDtb45uEvX+17G7Kdz22AIuJ80hwmlfeir+OvpQuJc5MZrV7lWIik0qeeYyK+45ypnhGAw3F8oixTpxhz5oT+1kFx6qHkRBEM9ZWT0aPh3null1FUlPwzttnkZ1SUPH7vvXD22Q1U4WbAu402m5zrb7M1bhtHjpRWj/795WA0KUlahTTXSYtF7icny/P9+8v0I0bUr9wDB+CLL2RQR5tN5m21ziE6WlrIWrSQx3NzYf16+aml25I8iqVJN3E8MZ0WLSBHJPN15XB+KOrLoeFT5RzHm26SA0iQ1pQ5c6RZ76abfH3mLr0Uu8XicB1M5I6IRbQWh7AZLOyzdOf/Yp/mCKk+likBlBDLcsZxkLaOUNxygGfDxLl8FVRfBPPziIz0fOuusZKxPnWyY6AcCzYMPnVe6RiIa0Fb1jDKoVzdxBpGccYZ0gX1rInJMlKlu0VKs25kZMhRfJ8+6I069tOBGMpYTwY2DM61hNzZQXdnPD0dvgNvfwNxd6XiWKLLshPoeaIPMFLdRTd20Y0O7CWKMo/+sGOgAotPYBMDNiKqiqTQLV0qgzq40Y/fMWH1k5cZu6PfteMmrPTld5LI9VGkdpJOB/Zic7iuuhQaqaTb3Fagkq6rRjqw16lImc0waVIQc0XB5e5nNiMcZi2tPLsjaIe35c6Onh30YClTnfc2i26Y/3Y1pWndPOqsXadd6/7yIYtuLLVc7bSoGQzQlmwfReqv+v8w3ziPO9p/gM2r+kdowYdcxnGSPRS/KvQktzRj2OV5j8JxfKITIlDIJkVjs23bNvr06cPWrVvp3bt3c1dHoVAomhybDdatk9aM9etdixxrY7yhQ09Mq5Q7zdVGrdx162DLFlluSYksy2aTwduiouSL7aFDG6Yev/0G48ZJ61PLlvgNLiKEXPjYapVWurS0wOmOHYMuCbm8szyZ004LUOjOnQEtdcfve4rCxxYxR/8cP8WPZbR+NRmVa/kseip7TOkMK1vBguNX05qj6JFrGJUQy/em0fwZOZAfbRncUfYPzhA/OUNzv8dk/sH8Gt3dEhPllLfaXCarquRKDL/8Iu9PuVuU+o30ZyC/OQf0eSTwDedyDl+TRAF6h6VkE6dxBr/WWM6TT8ol2Jw4Fvx2sn69tFA5XP9e/LoL2d/tcioIKziPjfif4KXVU4+MLmmzCQxuFiGQg2ObY8ldvWM4vS/xNCrW/UrPnjX30TnnyOXiamIj/RnAb4CrrzYwmLNZRSQVzoV+txtOo3Lx+5y+y38whz/+AEOvrnRlV639vpMu9CALgJGsZjhrPeaTJZHLNl1vWoqjjj7QUUws35jGMbz6axIpwODoi8OkMkC/jVxkwJ2zzpKe07UqU44If9pbmuqXXsWQn+Msr5wI9tGBVI4Q7wggopXXj23kkexcriE2For25PJ7/7/Q6+Byp7ongErHst8Wqp331QYsZxw3RLxFoTGZ0lL5O+7GTjba+xNNmVSkdP9hpX4sLVvCwq7PcdnaWegdqpkNeIur2EcnEsjnAj6jK7udClXO6WNpeeFQ32UvGplQx+fKze8UY+LEiWG5erQivFByogiGhpATbeL30KHSqnFCL5wdgOZqY6ByW7eWQdsaox6ZmVIpMBpdCtKxYxNp2dIlJzqdtDYIgcccEW90OpnPwfJkMjMJrEzV4PK4acRs7l80nu3V3WgRBet1o9hh7kuBQSoS30eN5aaWH7Po2GW0Jps8c2uWi7Ec1HdgmZjKwZh0jkZ14t/5VzPAup4SYjhIB6fLm7/w6CD7tKTE7ykPDh2SVoiEBOnWFR8P+/dDz+INdCzOxi50CPTkk8CDpsd4qfparuY1HmUuSRSgw057sj3WaPPXj+ef73XQXZHKzPRQpJg6lSJLOku/c7mujeUrCkj0USAHsYH2ZAM6MOixRcZgrbCht5Y6LFbactMCqzEKu95ARHUJCDvJZdmU7NgAPWW9Az1PWrasuQ+1OghkX+WRwHweIIki7Bg4h6+xUIkOQVtdNtEdCuD0qS4lZOlS59IJli0biNcXYre78rqbx3gT335PpNDZ72sYxRb6eshDJ3YRpSsHIZWyAuJ5NPFxliVey0V5r3F3wVynQhVNOT0jdnG4TTLjxsGjjwahSHlH+Bs0CIPteUAuslxILN8xkt/pTz9+ZRjfkUgRBmxEUU4ndpFHsrPOHToAu3bR9fBaD0WqmGhm8zQAT3EbsQ7XWAMwgu/oYN9FUcdk9u2T7qqZohv/x8Ncy0vcZXiKFfaxmAzSSj/+4WmUdH6AWHsBlRj5RT+EbF0ndBh4zXAzi003807pRXTnT0p1sSSdPcDnHoXj+ES5+Z1ihJsAKsITJSeKYGhIOakpkMPJQnO10btcs7nx6mE2y/yEcM2hcFekwPOc+3dvtHMGg8y3Lhw/Lgd37kqbpkhpbI3M4MbIxSwzXMbq8xZQndaBL2Kl5aq6Gv6wpXNL9JssM1zGLJ6jlFjW6Xxd3kAqf9HRcn0gjzWCAlBeLl0wO3aU89eOH5cuj2lpYKESgZ4CEpgf9RiftLiW2Fh4k2u5m8fIc0TaM1PzmlotWgR2lQsUcrtvX9ilT3e6gWlzppK8wmADsny9HhIS0N96CzqdVETKIxP5td8MyiMTQacHnY6NGbdQHuGot6gk1S3gXaDnyejRtfej2dFXmvKziNv4juH8ojuDxwz3kU8iAj0RukrMJqSVY+pU2ebhrgW6I8wQqa/0UaSg9n73Jw8GnUBnMFAZlcDi3o/zeeq16HTwZatrebv3Y1RFJSD0BiItgvvvl5bdp58O0r3PO8Jf+/bYqgU2DOSTwD36J7mbx7Fh4BlmM5cnyCMBGwaPOVsa113nqLPe7nTj0xSpN7mWN7mW2TxNMdHO83rsmEwyUmS/fvIlQmwsvGCZzVTTJ3ytH4vZDKefDq+8AjEdkvnqhmV8ZbyAyebPeTRyHgaLgS/ipnIkLp3dxnQuj/iYr4wXsOKmTzD+dabPPQrL8YlQNBtbt24VgNi6dWuTlTl79uwmK0tx4qLkRBEMSk4U3qxdK0T79kLExAiRkiK/x8bOFh06CNGhg9xPSREiMlIIvV5+aum0NO7pYmLk97Vr61af5cuFSE4WIirKtwz3sqKihOiamCM+/1yIpc/niPPPF6JbNyHathWidWv52bd1jjCbhWhpyBHt2sljcXGyjnFxcr9dOyEiIuQ1v/5ae/327BHiuuuEuOoqIa6+WohzzhFi4EAhTjtNiPda3CyOmtLEv3q/KgYMEKJzZyHi44UwGKSaeTWviv2kiWe5WbhUT89Nrxdi0CAhsrJqqMSqVULMmyfEjh3OQ1lZsv9BiG7sEPczT4xkld8yXo24WVS1TBPi1VeFEEIcnHSzyI1ME8+f/qp44AEhlk18VRTEpIn1Z9wsHnhAiOdPf1XkRqaJg5Nu9qhGoOfJjh2yHYHaCEI8y81iP2nial4VIIROJ/uphS5HGAxCXGd8VRzWp4m86Z5lipwcj12rVYiNg28Wx8xp4r7Wr/otK5h+17YfB90sRJrsm8pKKceffio/KyuF7LO0NCFu9qpXKLi1YfcFN4tDujRxU6Sr7knkBFX3V16ReeydcLMoIlLkEOfsT+/25xAriogSi3Q3i7POEqJjRyG6dpVyO2CAEF26yGalpgoxbJgQ337rqm5lpRB3zMwRrVsLER0tRIeYHBEXJ0RsrNxv3Vqer6z0f4+a4n8n1PG5mjPVjDTHnKmsrCy6BhOvVXFKo+REEQxKThTeVFXJJcd++km+Xa+uBr0+C7O5K3a7PG8ySVdAk0mej4qSn2azNHC4pysvl/NHPvmkbtapXbtg/HjpOhcdLctydysUQtaltFS6OX32mXy7/uKL8vuOHbIuZrN0N8vKctVZC9/vnld5ucva9M47MGxYzfWz2eDxx+H772HQIHmsqEiWYTJBj+INHGqTwc8/Q9u28PXXcr6ZwSDrPVAEdu/TLHpau2pcXsBrDlVVFQwZIoPeCYFzXo03Oh0MHAg/PL0B89AMZ5u+engD7+/J4NgxSEmB7kUb2BGXwfHjsh+ndNrAefdleFhFAz1PSkpk1fwt6+eO5nKnRY7UgjkYDNKNcsHFG5j5fEatltg1a2D14xvYqMtgxw55zwOVVRs//wyDbBtqXi5jQy3nQ+D77+HRSzewujSDsjL/Vt9Adf/736UsPvwwfPmPDVTbCdjGQcjw5G0uzGDyZCnre/bI364W2U+vh06d4IorYNo0Twt4VZVcn/zzz10RR81muZzA+PEyGE6g33tT/O+oOVOKGvnuu+/U4EdRK0pOFMGg5EThjdksB0O7dkFxsZwDlJf3HUZjV3Q6uV9aKgfU/fvDr7+60lVUuAZjWrqUFJlfXd38OnaUc8aOHZMKSnGxr9Jmt8soh8OGSUVq6VL48kvYu1eeMxjk5/HjcpCu4S8vk0lGStTWE6sNg0Eqi5mZUnHr3t3zukNxckCfmirTrV4tyzObZX/9YstwKnTuA2e9XkZP1CJHuge28ItXyG1tLpfZLPstz+6rSOn1sr1mMxxqk+EIEu6IuH5fBtHr5Prmu3dDZnwGFrOcwzdkCAwd6qvUBHqefPaZZ78HQhv4x8VJd0u7XbbfapX3JHZ07YoUSDnIzs5g9wqpsNZUVm1s2waDrqolbQOuSzhoEPwZm0F5TmD32UB1P3RIzq1cuhR26DJ8ou5552E2w38WQI8ecnkHLdCNNhezpsA2ZjPceqtUmjZskC6x2sLltf3Ww/F/RylTpxiJicGt3K44tVFyoggGJScKf9x4o1QOVqyAwkIwmxOJjpaD2pISqSiNHQuPPQZz57rSRUXJQbB3ukAL2waDwSDfjGdmut6AV1e7zmtrbHXtCtOnyzf7L78sAwRWVXlanrSw9loADX8KIMhzbdrIaInBIAfvsHKljOqXkiLrVF6O05IzZozMU6+X+VZXu8p1x3s/JkZeE8z8LXdKSmRbo6NlOVo7NWuPXi8VUL1envMOtlGXoCuBnieZmcEpUxoVFVKh0uqhRY3s0SO467UpSG3bSoX60KHgy/bmwIG6X1sXjh6V7a2Lz1mLFjIK54ED8l7Hxsr7ZrX6T2+xyN9IfQLsmM21W2+9Ccf/HaVMnWK0adOmuaugOAFQcqIIBiUnCn+YzbBwoXTj+eIL+OOPNuh0Ulnq1QsuuMDlxuOebu9elwudd7r6oK259c470kpSVeVSCsxm6NxZKlxDh8qAYdu2ueIxmEwuy5M2QK2ulnlER8sQ6Jpbk3ZMp5PWl3btgquf++Bds+RUVMjBqsuSI8N2R0dLa4lmuZNulK726HQua1qLFjKfmJjgrGTuFBTIQXFCghxUFxbK8ux2WV50tKxDcbFMF0hZ04KfBEOg54m2gLcQeLjw1aQwaIpmQoJUCi0WWddg0RSECy6A774L/jpvAlm2GovCQtlevT40BRSkLP/wg5QZTea1wC1aXjqd7MvKSpnuhx/kMm8Q2r2uD+H4v6OUqVOMFStWkNGAJmXFyYmSE0UwKDlRBMLdjeemm1YwaVKGXzee+rj7BIvBIOds1OaKtHevtExVVPifX2WxyAFmSYlMk5Iiv2uWj/btZbp27UJfsyuYt/sxMTKsfWGh3I+KkoN1vd6VxmaTdYyKkvtms7wmWCuZRkKCK//4eLlpLoPaos8gLRmJiaEra/4I9DwZPNhlYQLZ1yDr4k9haN1a1lebM7ZvX90USpBz3zRrqaZg1Ib7nCFNJpqKzEwpOxERrvmAwdKjh7yfWv0rK10Kq/vvwP1lRHMQjv87Spk6xbjdY9U+hcI/Sk4UwaDkRFEbZjM888ztzsF9TelCdfcJhWCUlawsyMnBaUXz50IXHy8HqNXVMh93q1BVlQzyMGaMLKeu9Qz0dr9dOzjzTFmuNljX6qi5Lur1rk0LkBGKlUzDXXHTYlNERLjOCyGPm0x1U9b8Eeh50rOnVNiOH3cprpoC6W4xBHkuMVG2vSHqmJ4uZUGzatWmUGmKCMj+Cta1sKGwWDxdG0MhK0v2tbsl1p/1z11ZrG0NsMYgHP931DpTpxhXX311c1dBcQKg5EQRDEpOFMEQTnJS01pfx49LpaSmhYTBNdgsKnKtJ1VQIN/q5+UFZ72oa92HDZOLFycnyyh9FosrYp1Wb4tFnktKkspdmzZSAQvF7UtT3GJiZL7Z2TKIx/Hj8jM7Wx6PiambsuaPQHLSsaMMQqJZw6qrpdVEs5C4ExsrFYmCAjnXqb51HDJEzqfTXChrm4vkbsnp1Ute35QkJcn26nSB5zr5Q6+XSui4ca41rmpa/w2kkjluXP3qWxfC6XmioSxTpxjvv/9+c1dBcQKg5EQRDEpOFMFwoshJSoorHHsgN6byctcgXgjPt/82m3Qpe/VVOXA/++yGr+OwYVIxeucd6WKozY2xWl1KlU4nFZ6SEvn9m2+ke2OnTnJwP2xY7S6ImuL255+wdats67FjrjlT8fHys0+f0F0aAxFITgwGuPJK6cK2aZN0sfRHZKRUMjVXxPbtZb3r4nYJMp8ff4RWraTlVAtIUpNCpVnMEhPhL39pOFfVYMnIkBEhf/optPaazbKdOTnB19lslulrs/hVVTWsC284Pk/C1jK1ceNGbrnlFnr37k10dDTt27dnypQpZGZm+qR97rnn6NmzJxaLhTZt2vD3v/+d0tJSn3RZWVlcdtllJCYmEhUVxbBhw1i1alVQ9XnzzTfR6XR+tyNHjtS7vU3FxIkTm7sKihMAJSeKYFByogiGE0VOunaVQRu0uSbeg2bNGqUdNxikK1dUlMsFrrxcKh/vvht6AIBgsdmkBSwvT5anRfaz2eTAtaREDnKPHZOfR49KBWzNGnjzTRn6Opi6DRkio+IVF8t2Wyxy4GyxyP3iYnn+zDMbpl01ycmwYVJxi4hwKYzum+bymJAgXfM6dXJZ6MaODd3t0maD996T/WWzQVqaVLQDKdkGg1TmIiKkUn7JJTKqZVOjLU3QsqXLahkI935r21auD6fNx6ttPpR2Xkvvj6oqePppmDgR/vY3mD1bfl54oTxe27phgQjH50nYWqYee+wx1q1bx+TJk+nXrx9HjhzhueeeY+DAgfz000/06dMHgLlz5/L4449z2WWXcdttt7F9+3aeffZZtm3bxooVK5z5HThwgCFDhmAwGLjzzjuJjo7mjTfe4LzzzuObb75hxIgRQdVr3rx5dOrUyeNYQkPMvGwiPv300+auguIEQMmJIhiUnCiC4USRk9rWpNKsUiAHqgkJvgEqtAWA166VAS1qXCi3DqxZIy1f+/ZJV7fqal+lz2p1KVbbt8vFVC0WaU06ckSea9tWziGriR9/dClMdrt0Y9QsU0lJLkXrp59qzysYapKTH3+U/anTSWug+0Dc3cXx8GGpELdvD2ec4YqEGKpV6vvv4auv5GLPQrgi22myoClxFotUoqKipKx061b7orONjfvSBFqwFG90Oqkc2u2yDRdcINuRmSnTR0bKtpaXeyremtKo/R4yM6XbqTdVVVJ5+uorqXjHxbmiAG7aJOdnZWbKaJ6h9lM4Pk/CVpn6+9//zpIlSzC79fLUqVPp27cvjz76KG+//TaHDx/m3//+N1deeSWLFy92pktPT+fWW2/l008/dWqwjz76KAUFBWzdupXu3bsD8Le//Y0ePXowZ84cfvnll6DqNW7cOE4//fQGbGnTcu+997JgwYLmroYizFFyoggGJSeKYDhR5KS2Nam0uVBaIAp/ASq0CHjHj8s8GlKZstlgyRIZut1q9T9nSEM7brPJNhiNUpHSLFo9etSsZNhs0jXwt9/kgLyw0GWVEcIVCv3332W6hnD1CyQnNptUTn//XdbF/Z6AS3nUFMju3WWESO85ccGitV1bUPrYMakEuAdl0Fwq09Lg/PPlHLzUVGnd0eYcNRfuSw58+qlsi7vrqtHoClIRESEti48+Kq91D2CRlORaY0wLaKGtLZab6xnV0ZsXXpCKVGWllDW9mx+c3S4V/BUrZB1vvTW09oXj8yRs3fzOOussD0UKoFu3bvTu3Zs//vgDgB9//BGr1crll1/ukU7bf++995zH1q5dy4ABA5yKFEBUVBQXXnghmzZtYufOnUHXrbi4GFtj2e8bmWnTpjV3FRQnAEpOFMGg5EQRDCeSnGhrUvXvLy0ccXEyqEFcnFSU9Ho5gHSPbOeONsiurpYKVUPiHrrdaHStt+TuruUPm03WvUULl4vg55/XvKDsgQNyDaEjR+TAWQhPl0YtUt7hwzJdQyxOG0hODhyAb7+V5XkvuKy1WQg54C8slKHvNWtVXXBv+7Fjsr+1kPOakiqErMvevfD++/DZZ/D119J9bc2axnPxDBZtyYHPPoOPPpLWsrZtpSxbLHLr3BmuuQY++cSlALoHsNDC7mtrikVHy/2yMnk+Jkam96aqSq4bV1Qk3S11OtmHpaXyU6eTx4uKZLpQ3f3C8XkStpYpfwghOHr0KL179wagsrISgEiv1wBRjhis7tamyspKv6smu6ft1q1brXU4++yzKSkpwWw2M3bsWP71r38Fdd2xY8c47vVkzcrKqvW6hmbLli307du3yctVnFgoOVEEg5ITRTCcSHJS05pUFgt8+GHNUdKEkAPpyEg5d6YhcQ/dbjR6Wsr8BUbQjmkBKkwmGRjh2DGpBNQ036WkRFroSkqkAuVvza2yMs909SWQnJSUwK5dLkXKfa4UuKxF2sLJu3bVrz5am4qLZR9rSpR7P2t9rbk/ZmZKZePAAdixQ0Y7nDq1YQJz1AezWYbqHzNGyvFnn0kZatHCvxXNPYCFTufr6lpVJWVPp5PWOH/LPW3YIN0jY2OlwlRYKJUorQ8jI10vKfbulelDWRYhHJ8nYWuZ8sc777xDdnY2U6dOBXBamdatW+eRbu3atQBkZ2c7j3Xv3p3ff/+dYq8lsL///nuftP6Iiori6quvZtGiRSxbtoy77rqLb775hrPOOosDQbySef755+nTp4/HNmnSJGcd1qxZwxNPPEFeXh4zZswAXJPs5syZQ1ZWFq+//jrLli1jw4YNzJ8/n7KyMqZMmeKR9t5772XLli0sWbKEJUuWsGXLFu69916PNFOmTKGsrIz58+ezYcMGli1bxuuvv05WVhZz5szxSDtjxgzy8vJ44oknWLNmDcuXL2fRokVkZ2dzww03eKS94YYbyM7OZtGiRSxfvly16QRu05NPPnnStelkvE+qTapNJ0KbtOfJidKmO+6YQ+vWWaSkvM7Ikcu4/PINtGo1n9mzyxBiCkLA4cMTEQLy8++lqmoLpaVLKClZQlHRFqqq7iUlBR57rGHb9PjjNzjCgk90DPBvALIRYhFCLEeINcATQB4g2wSynkVFc6iuzqK09HVgGYWFG1iwILDsbdy4hcOHl1BdvQSjcQsFBfI+HTsm0+TkTCEiooyqqvkcO7aBjz5qvPu0aNET5Oe72iTERHQ6sNvnIEQWQsg2wQZgPvn5Zdx6a91/TwsXyjZVVy+jqup1hMgC5jjKnOhQ4mY4+vkJbLY17N+/nLVrF1FYmM2KFTewYgUMHx5ez4gtWzZgNC7DYnmdAQOyuPde3/tUUpJHZOQTxMauoapqOTrdIuz2bAoKbnBYmGRane4Ghg7N5pVXfNv04IMzqK6G7OyJHDkChw/Poawsi+Li1ykuXkZOzgaysuZTXl7GgQNTKCgIrU3PPPNMoz8jNN0gaMQJwh9//CHi4uLEkCFDhNVqdR4fPHiwiImJEa+//rrYs2eP+OKLL0SHDh2EyWQSBoPBme6LL74QgBg3bpzYtGmT2LFjh7jtttuEyWQSgJg/f37IdVq7dq3Q6XTi+uuvrzXt0aNHxdatWz22jz76SABi69atIZddV37//fcmK0tx4qLkRBEMSk4UwXCyyInVKsQ11wiRmChEfLz8TE0VIi1Nfrof/+tfZfqGZPlyIZKThYiKEqJFCyF0Ornp9UIYDO72GbnpdK7Pli2F6NBBiPbthYiOFiIpSYiPPgqurPbt5bXeW/v28nxyskxfXwLJyfLlQsTGutqltdd90+td52Nj61cfre1ms6sPtTLdy/HeYmLkdZ07C3HaaUIsWNDwMlAfrFYh9uwRYvt2+RmobpWVQtx0kxBdugiRkiLvc+fO8jMlRR6/6SaZzh9r18q0MTFS1iwWIYxG2X9Go9yPjpbn27eX6UOhKZ4nW7duDWl8fkK4+R05coTx48cTHx/PBx98gMHNbvq///2PqVOncs011wBgMBj4+9//zpo1a9ixY4cz3bhx43j22We5++67GThwIABdu3bl4Ycf5q677iKmDktjDxs2jMGDB/P111/XmrZly5a0bI6lor149913w848qgg/lJwogkHJiSIYThY5qS1AhebC1LUrTJ/e8C5eWuj2/ful6562xpR7+e6ufu4h3I1GuV9e7prvkpxcc1sjI2UbNTdHdzc/LS8tXUO0NZCcaIEONMci94VxtX33hZK1IAp1RWtTSYlvWTWhucLl5sprtblkHTvWvS4Ngc0m59qtWyfD9mv3s29fOOss33XH3ANYfPGFdMWrrpaunr16ych/NUUrHDRIupSWlcl9IVxz+jRXTO13k5Ym04dCOD5Pwl6ZKiwsZNy4cRQUFLB27Vpat27tcb5NmzZ8//337Ny5kyNHjtCtWzdatWpF69atSU9P90h7yy23MHPmTH7//XfMZjP9+/fntddeA/BJGyzt2rXzUNrCnXCLgKIIT5ScKIJByYkiGE4mOdECVLzzDuze7Yqop9PJwWXnzlLhaohQ4d64h253V6bcgyL4w2SSc6bKy+X3mua7aHTqJBdxLS0NPHfGZJJKWlqaTF9fAsmJVpe8PN8gENqnNlDX6+tfH628/HwZjQ5c4dDdlTZ3dDoZmCMiouHnktUHLQLkkiVyLpnV6uqvX36B776T8jptmq9CdeutUtZDXXD36FFXOUJIOfGO5lddLetQXS3Th6JwhuPzJKyVqYqKCiZOnEhmZiZff/01vXr1Cpi2W7duzkAQ27dv5/Dhw1x99dU+6aKjoxkyZIhz/+uvvyYyMpKhoa7o5mD37t2kNPQs00Zk4sSJYRmjXxFeKDlRBIOSE0UwnExyUlOAir59pbLTEGHCA5XtbhnTgku4KxjuaJEFLRY5mI2Pl8pRSoqM7lbToLhjRxnR8NAhORiOipJBBDSlIj5elmk0woABDWN9CSQnHTvKQfyuXa5ocOBqszZQF0K29cwz61cfre379rki+bmX5w/N+qeFxy8tlcpYbm7d69EQrFkDL78MO3dKBdjbwlZYKOvapg2cfbbv9WZzaMEhtDwrK+V9cZdR9+AdmqWqsrLmQCj+CMfnSdgqUzabjalTp/Ljjz/y8ccfeyhANWG327nrrruIiopyTi4LxA8//MCHH37IjTfeSHx8vPP44cOHKSwspEuXLphMJgCOHz/uozR98cUX/PLLL8yaNSvE1jUf4SaAivBEyYkiGJScKILhZJMTg0FanoYOlW5cmjLVrl3jR29zt4zt2iUH7O5rL+n1crNaXUpPXJwc0JaUyP2xY2UetbVx2jQZme7AAZlnYqJrQKytu9SlC1x+ecO0O5CcaErkxo1SkdSsGlqZWsQ9bdFcbytLqGht//NP2LzZ5a7mL2KidtxikcqU+zFtjabmwn1dMptNtkuzEmnWxfJy6fr37rtSphviPmZmynwjIuQ9KS/3XFzabHa5kJaVBV74NxDh+DwJW2Xq9ttv55NPPmHixInk5eXx9ttve5z/y1/+AsBtt91GRUUF/fv3p7q6miVLlrBhwwb+85//0L59e2f6ffv2MWXKFC688EJatWrFtm3bePHFF+nXr5+PyfCee+7hP//5D3v27KGj4/XGWWedxYABAzj99NOJj49n06ZNvP7667Rr184ZaeREYMqUKbz//vvNXQ1FmKPkRBEMSk4UwXCyyonB0PTzYbwtY7/9JsNwFxXJ83Fx0kWtokK6AxYVyYGsxRLcfBd3Ro6E666TituePS4FTXPd6tSpYV0aa5KTkSPhjjvgySddYdLdLVMWi5xTdvvtDVMfTWl95hm5WLDV6mld0dDpZF9ER7vONfRcsrrivi5ZdHTg8PalpXJR5L17G2aRafeFf2Nj5fy8qiqXQmc2y3rUtvBvIMLxeRK2ytSvv/4KSA3UnxaqKVMDBgzgqaee4p133kGv15ORkcE333zD2V72yri4ONLS0njuuefIy8ujTZs2zJo1i/vuu4/Y2Nha6zN16lQ+//xzvvrqK8rKykhLS+Nvf/sbDz74IKmpqfVvcBPx5ptvNncVFCcASk4UwaDkRBEMSk4aFn+WMU05qqpyWclsttDnu3iX05QujTXJiWadatdOWlHWr3e50CUnw+DBsq4NZV3R2t6mDbzwglQ2iopkn2rz5DQrYESE/KyoaJy5ZHXFfV0yb0UKXMfLyuQC01lZDaNMaQv/apYnbaFnDSFqX/i3JsLxeaIToiYvUEVjsm3bNvr06cPWrVudCxE3NvPnz+eBBx5okrIUJy5KThTBoOREEQxKTk58bLbGd2kMVk5sNmlF2bNH7nfqJC2EjWUFqqqCZcvkQra7dklL1dGj0qKiLXqrBXWIiJDfq6vlorjPP9981qm334abb5b1qUlhycuTdV+0CBx2inpRVSXb/tNPsj+sVv8L/1ZUyGiCn3wSmpLfFM+TUMfnYWuZUjQOY8eObe4qKE4AlJwogkHJiSIYlJyc+DSFS2OwcmIwSAtKQ1hRgsFshqlT4bLLpEK5ahW8+KJUqDQ3tcacS1ZXUlKklay83KXseaMFiIiMlOkbArNZBjjZvVta8+LiXP2i08n9sjJo2bL2QCj+CMfnib72JIqTiezs7OauguIEQMmJIhiUnCiCQcmJIhjCXU40hfKqq2TY8J49XWHntc1kgh495FyzxgiPHwraumSaW523H5r78ZQUmb6huPFGGehEU5zMZjlvy2yW+3FxwQVC8Uc4yomyTJ1i5OfnN3cVFCcASk4UwaDkRBEMSk4UwXCiyElzhscPBfd1yaqr/a8VZrdLV7xhwxrW8ljfhX9rIhzlRClTpxgjmvtVieKEQMmJIhiUnCiCQcmJIhhOJDlpzvD4weK9LllVlSuEPkiXu8hIaZGaPr3h612fhX9rIhzlRLn5nWIsWrSouaugOAFQcqIIBiUnimBQcqIIhhNRTjTXv549GzcIRl3RQrz37y9d/uLiZLjyuDi537+/PN+Y+om28O+ECfKzPooUhKecqGh+zUhzRPNTKBQKhUKhUJwa2GzSHTGcXRLDjVDH58oydYoxceLE5q6C4gRAyYkiGJScKIJByYkiGJScNA6aS+Jdd8GCBa7trrsabl2upiQc5URZppoRZZlSKBQKhUKhUCjCB2WZUtTIjBkzmrsKihMAJSeKYFByoggGJSeKYFByogiGcJQTZZlqRprDMpWXl0dSTUthKxQoOVEEh5ITRTAoOVEEg5ITRTA0hZwoy5SiRl577bXmroLiBEDJiSIYlJwogkHJiSIYlJwogiEc5UQpU6cYGRkZzV0FxQmAkhNFMCg5UQSDkhNFMCg5UQRDOMqJWrS3GamsrAQgKyurycr8888/adGiRZOVpzgxUXKiCAYlJ4pgUHKiCAYlJ4pgaAo50cbl2ji9NpQy1YwcOHAAgEmTJjVvRRQKhUKhUCgUCoWTAwcOMHDgwFrTqQAUzUhBQQFr1qyhXbt2WCyWRi8vKyuLSZMm8dFHH9G1a9dGL09xYqLkRBEMSk4UwaDkRBEMSk4UwdBUclJZWcmBAwcYOXIkCQkJtaZXlqlmJCEhgYsuuqjJy+3atata10pRK0pOFMGg5EQRDEpOFMGg5EQRDE0hJ8FYpDRUAAqFQqFQKBQKhUKhqANKmVIoFAqFQqFQKBSKOqCUKYVCoVAoFAqFQqGoA0qZOoVISUnhwQcfJCUlpbmroghjlJwogkHJiSIYlJwogkHJiSIYwlVOVDQ/hUKhUCgUCoVCoagDyjKlUCgUCoVCoVAoFHVAKVMKhUKhUCgUCoVCUQeUMqVQKBQKhUKhUCgUdUApUwqFQqFQKBQKhUJRB5QypVAoFAqFQqFQKBR1QClTpwCVlZXMnTuX1q1bExkZyeDBg1m5cmVzV0vRgGzcuJFbbrmF3r17Ex0dTfv27ZkyZQqZmZk+af/44w/OP/98YmJiSEpK4sorr+T48eM+6ex2O48//jidOnUiIiKCfv368e677/otP9g8FeHHww8/jE6no0+fPj7nfvjhB4YNG0ZUVBStWrVi1qxZlJSU+KQL5RkTbJ6K5mfTpk1ceOGFJCUlERUVRZ8+fXjmmWc80igZObXZuXMnl19+OW3btiUqKooePXowb948ysrKPNIpOTk1KCkp4cEHH+T8888nKSkJnU7Hm2++6Tdtc45FQskzKITipOfyyy8XRqNR3HHHHeKll14SQ4YMEUajUaxdu7a5q6ZoIC699FLRqlUrceutt4pXXnlFzJ8/X6Smporo6GixZcsWZ7oDBw6IFi1aiC5duoinn35aPPzwwyIxMVGcdtpporKy0iPPu+++WwDib3/7m3j55ZfF+PHjBSDeffddj3Sh5KkILw4cOCCioqJEdHS06N27t8e5zZs3i4iICDFgwADxwgsviPvuu09YLBZx/vnn++QT7DMmlDwVzcuKFSuE2WwWgwcPFv/+97/Fyy+/LObOnSvuvPNOZxolI6c2+/fvFwkJCaJDhw7ikUceES+99JK4+uqrBSAuvPBCZzolJ6cOe/bsEYBo3769GDVqlADEG2+84ZOuucciweYZLEqZOslZv369AMQTTzzhPFZeXi66dOkihgwZ0ow1UzQk69at83lYZGZmCovFIq644grnsRtvvFFERkaKffv2OY+tXLlSAOKll15yHjt48KAwmUzi5ptvdh6z2+1i+PDhom3btsJqtYacpyL8mDp1qhg9erQYOXKkjzI1btw4kZaWJgoLC53HXnnlFQGIFStWOI+F8owJNk9F81JYWChSU1PFxRdfLGw2W8B0SkZObR5++GEBiK1bt3ocv+qqqwQg8vLyhBBKTk4lKioqxOHDh4UQQmzcuDGgMtWcY5FQ8gwWpUyd5Nx5553CYDB4PHCEEGLBggUCEPv372+mmimagoEDB4qBAwc691u2bCkmT57sky49PV2cc845zv1FixYJQGzbts0j3ZIlSwTg8ZYw2DwV4cWaNWuEwWAQv//+u48yVVhYKIxGo4cVQgghKisrRUxMjLj22mudx4J9xoSSp6J5eeGFFwQgtm/fLoQQoqSkxEepUjKimDt3rgDE8ePHfY7r9XpRUlKi5OQUpiZlqjnHIqHkGSxqztRJzubNm0lPTycuLs7jeEZGBgC//vprM9RK0RQIITh69CgtWrQAIDs7m2PHjnH66af7pM3IyGDz5s3O/c2bNxMdHU3Pnj190mnnQ81TET7YbDZuvfVW/vrXv9K3b1+f81u2bMFqtfrcV7PZTP/+/X1kJZhnTCh5KpqXr7/+mri4OLKzs+nevTsxMTHExcVx4403UlFRASgZUcCoUaMAuPbaa/n11185cOAAS5cu5YUXXmDWrFlER0crOVH40NxjkWDzDAWlTJ3kHD58mLS0NJ/j2rFDhw41dZUUTcQ777xDdnY2U6dOBaQsAAHlIS8vj8rKSmfa1NRUdDqdTzpwyU0oeSrChxdffJF9+/Yxf/58v+dru6/uz41gnzGh5KloXnbu3InVauWiiy5i7Nix/O9//+Oaa67hxRdfZObMmYCSEQWcf/75zJ8/n5UrVzJgwADat2/P5Zdfzq233srChQsBJScKX5p7LBJsnqFgDPkKxQlFeXk5FovF53hERITzvOLk488//+Tmm29myJAhzJgxA3Dd69rkwWKxBC03oeSpCA9yc3P5v//7Px544AFSUlL8pqntvro/NxpKVtSzKHwoKSmhrKyMG264wRm975JLLqGqqoqXXnqJefPmKRlRANCxY0dGjBjBpZdeSnJyMp9//jkLFiygVatW3HLLLUpOFD4091ikMcbFSpk6yYmMjPRrGdBcNSIjI5u6SopG5siRI4wfP574+Hg++OADDAYD4LrXwchDsHITSp6K8OD+++8nKSmJW2+9NWCa2u6r+z1tKFlRchI+aPdi2rRpHsenT5/OSy+9xI8//khUVBSgZORU5r333uO6664jMzOTtm3bAlLpttvtzJ07l2nTpqlnicKH5h6LNMa4WLn5neSkpaU5zZ/uaMdat27d1FVSNCKFhYWMGzeOgoICli9f7nF/NRN2IHlISkpyvq1JS0vjyJEjCCF80oFLbkLJU9H87Ny5k5dffplZs2Zx6NAh9u7dy969e6moqKC6upq9e/eSl5dX6331lqtgnjGh5KloXrR7kZqa6nG8ZcuWAOTn5ysZUfD8888zYMAApyKlceGFF1JWVsbmzZuVnCh8aO6xSLB5hoJSpk5y+vfvT2ZmJkVFRR7H169f7zyvODmoqKhg4sSJZGZm8tlnn9GrVy+P823atCElJYWff/7Z59oNGzZ4yEL//v0pKyvjjz/+8EjnLTeh5KlofrKzs7Hb7cyaNYtOnTo5t/Xr15OZmUmnTp2YN28effr0wWg0+tzXqqoqfv31Vx9ZCeYZE0qeiuZl0KBBgJQXd7S5BCkpKUpGFBw9ehSbzeZzvLq6GgCr1arkROFDc49Fgs0zJEKO/6c4ofjpp5981m2oqKgQXbt2FYMHD27GmikaEqvVKi688EJhNBrF559/HjDdDTfcICIjIz1C4n/99dcCEC+88ILz2IEDBwKuw9CmTRuPdRiCzVPR/Bw/flwsW7bMZ+vdu7do3769WLZsmfj999+FEEKcf/75Ii0tTRQVFTmvf/XVVwUgvvzyS+exUJ4xweapaF42bdokADF9+nSP49OmTRNGo1FkZ2cLIZSMnOpMmDBBmM1msWPHDo/jkyZNEnq9XsnJKU5NodGbcywSSp7BopSpU4DJkyc712R46aWXxFlnnSWMRqNYs2ZNc1dN0UDcdtttAhATJ04Ub731ls+msX//fpGcnCy6dOkinnnmGbFgwQKRmJgo+vbtKyoqKjzyvPPOOwUgrrvuOvHKK684Vwh/5513PNKFkqciPPG3aO8vv/wiLBaLGDBggHjhhRfEfffdJyIiIsR5553nc32wz5hQ8lQ0L9dcc40AxJQpU8SiRYvE5MmTBSDuueceZxolI6c22lp1LVu2FPPmzROLFi0S48aNE4D461//6kyn5OTU4tlnnxXz588XN954owDEJZdcIubPny/mz58vCgoKhBDNPxYJNs9gUcrUKUB5ebm44447RKtWrYTFYhFnnHGGWL58eXNXS9GAjBw5UgABN3e2bt0qzjvvPBEVFSUSEhLEFVdcIY4cOeKTp81mEwsWLBAdOnQQZrNZ9O7dW7z99tt+yw82T0V44k+ZEkKItWvXirPOOktERESIlJQUcfPNN3u8CdYI5RkTbJ6K5qWqqko89NBDokOHDsJkMomuXbuKhQsX+qRTMnJqs379ejFu3DjRqlUrYTKZRHp6unj44YdFdXW1RzolJ6cOHTp0CDgW2bNnjzNdc45FQskzGHRCeM3AUigUCoVCoVAoFApFragAFAqFQqFQKBQKhUJRB5QypVAoFAqFQqFQKBR1QClTCoVCoVAoFAqFQlEHlDKlUCgUCoVCoVAoFHVAKVMKhUKhUCgUCoVCUQeUMqVQKBQKhUKhUCgUdUApUwqFQqFQKBQKhUJRB5QypVAoFAqFQqFQKBR1QClTCoVCoVAoFAqFQlEHlDKlUCgUCoVCoVAoFHVAKVMKhUKhOGm4+uqr6dixY3NXw8lDDz2ETqdDp9MRExPT5OX379/fWf6ECROavHyFQqE42TE2dwUUCoVCoagJnU4XVLpVq1Y1ck3qzltvvYXJZGrychcsWEBeXh5z5sxp8rIVCoXiVEApUwqFQqEIa9566y2P/cWLF7Ny5Uqf4z179uSVV17Bbrc3ZfWC4i9/+UuzlHvBBRcAcP/99zdL+QqFQnGyo5QphUKhUIQ13orITz/9xMqVK5tNQVEoFAqFQkPNmVIoFArFSYP3nKm9e/ei0+l48sknWbRoEZ07dyYqKorzzjuPAwcOIIRg/vz5tG3blsjISC666CLy8vJ88v3yyy8ZPnw40dHRxMbGMn78eLZt21avunbs2JEJEyawevVqTj/9dCIjI+nbty+rV68G4MMPP6Rv375EREQwaNAgNm/e7HH9kSNHmDlzJm3btsVisZCWlsZFF13E3r1761UvhUKhUASPskwpFAqF4qTnnXfeoaqqiltvvZW8vDwef/xxpkyZwujRo1m9ejVz584lKyuLZ599ljvuuIPXX3/dee1bb73FjBkzGDt2LI899hhlZWW88MILDBs2jM2bN9cr4EVWVhbTp0/n+uuv5y9/+QtPPvkkEydO5MUXX+Tee+/lpptuAuCRRx5hypQp7NixA71evge99NJL2bZtG7feeisdO3bk2LFjrFy5kv3794dVEA6FQqE4mVHKlEKhUChOerKzs9m5cyfx8fEA2Gw2HnnkEcrLy/n5558xGuXf4fHjx3nnnXd44YUXsFgslJSUMGvWLP7617/y8ssvO/ObMWMG3bt3Z8GCBR7HQ2XHjh388MMPDBkyBIBevXoxduxY/va3v/Hnn3/Svn17ABITE7n++uv57rvvGDVqFAUFBfzwww888cQT3HHHHc787rnnnjrXRaFQKBSho9z8FAqFQnHSM3nyZKciBTB48GBAzsfSFCnteFVVFdnZ2QCsXLmSgoICpk2bRk5OjnMzGAwMHjy43hEEe/Xq5VSk3Os1evRopyLlfnz37t0AREZGYjabWb16Nfn5+fWqg0KhUCjqjrJMKRQKheKkx10xAZyKVbt27fwe1xSUnTt3AlK58UdcXFyz1MtisfDYY49x++23k5qayplnnsmECRO46qqraNWqVb3qpFAoFIrgUcqUQqFQKE56DAZDSMeFEADOMOtvvfWWXyXF3arVlPUCmD17NhMnTuSjjz5ixYoVPPDAAzzyyCN8++23DBgwoF71UigUCkVwKGVKoVAoFIoAdOnSBYCWLVty7rnnNnNtfOnSpQu33347t99+Ozt37qR///7861//4u23327uqikUCsUpgZozpVAoFApFAMaOHUtcXBwLFiygurra5/zx48eboVZQVlZGRUWFx7EuXboQGxtLZWVls9RJoVAoTkWUZUqhUCgUigDExcXxwgsvcOWVVzJw4EAuv/xyUlJS2L9/P59//jlDhw7lueeea/J6ZWZmcs455zBlyhR69eqF0Whk2bJlHD16lMsvv7zJ66NQKBSnKkqZUigUCoWiBqZPn07r1q159NFHeeKJJ6isrKRNmzYMHz6cmTNnNkud2rVrx7Rp0/jmm2946623MBqN9OjRg/fff59LL720WeqkUCgUpyI64T6bVaFQKBQKRYPx0EMP8Y9//IPjx4+j0+lITk5u0vILCgqwWq0MHDiQfv368dlnnzVp+QqFQnGyo+ZMKRQKhULRyKSkpNChQ4cmL3fUqFGkpKRw4MCBJi9boVAoTgWUZUqhUCgUikZi9+7dzoV2jUYjo0aNatLy169fT3FxMSAVutNOO61Jy1coFIqTHaVMKRQKhUKhUCgUCkUdUG5+CoVCoVAoFAqFQlEHlDKlUCgUCoVCoVAoFHVAKVMKhUKhUCgUCoVCUQeUMqVQKBQKhUKhUCgUdUApUwqFQqFQKBQKhUJRB5QypVAoFAqFQqFQKBR1QClTCoVCoVAoFAqFQlEHlDKlUCgUCoVCoVAoFHVAKVMKhUKhUCgUCoVCUQeUMqVQKBQKhUKhUCgUdUApUwqFQqFQKBQKhUJRB/4fLOL5wEM5XTYAAAAASUVORK5CYII=\n", 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" ] @@ -8781,7 +8815,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ diff --git a/doc/tutorials/stdp_windows/stdp_windows.ipynb b/doc/tutorials/stdp_windows/stdp_windows.ipynb index 6bb2f7782..cbf0b0209 100644 --- a/doc/tutorials/stdp_windows/stdp_windows.ipynb +++ b/doc/tutorials/stdp_windows/stdp_windows.ipynb @@ -334,7 +334,7 @@ "-- Detecting CXX compile features - done\n", "\n", "-------------------------------------------------------\n", - "nestml_c74fe99fdb8a4a94b0aaeb52ce20cf1a_module Configuration Summary\n", + "nestml_c343f4cc15ff47b9adbc75b2cdd8dd06_module Configuration Summary\n", "-------------------------------------------------------\n", "\n", "C++ compiler : /usr/bin/c++\n", @@ -346,15 +346,15 @@ "\n", "-------------------------------------------------------\n", "\n", - "You can now build and install 'nestml_c74fe99fdb8a4a94b0aaeb52ce20cf1a_module' using\n", + "You can now build and install 'nestml_c343f4cc15ff47b9adbc75b2cdd8dd06_module' using\n", " make\n", " make install\n", "\n", - "The library file libnestml_c74fe99fdb8a4a94b0aaeb52ce20cf1a_module.so will be installed to\n", - " /tmp/nestml_target_i1uuk7tq\n", + "The library file libnestml_c343f4cc15ff47b9adbc75b2cdd8dd06_module.so will be installed to\n", + " /tmp/nestml_target_4f4go9f_\n", "The module can be loaded into NEST using\n", - " (nestml_c74fe99fdb8a4a94b0aaeb52ce20cf1a_module) Install (in SLI)\n", - " nest.Install(nestml_c74fe99fdb8a4a94b0aaeb52ce20cf1a_module) (in PyNEST)\n", + " (nestml_c343f4cc15ff47b9adbc75b2cdd8dd06_module) Install (in SLI)\n", + " nest.Install(nestml_c343f4cc15ff47b9adbc75b2cdd8dd06_module) (in PyNEST)\n", "\n", "CMake Warning (dev) in CMakeLists.txt:\n", " No cmake_minimum_required command is present. A line of code such as\n", @@ -366,141 +366,149 @@ " information run \"cmake --help-policy CMP0000\".\n", "This warning is for project developers. Use -Wno-dev to suppress it.\n", "\n", - "-- Configuring done (0.5s)\n", + "-- Configuring done (0.2s)\n", "-- Generating done (0.0s)\n", - "-- Build files have been written to: /home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target\n", - "[ 25%] Building CXX object CMakeFiles/nestml_c74fe99fdb8a4a94b0aaeb52ce20cf1a_module_module.dir/nestml_c74fe99fdb8a4a94b0aaeb52ce20cf1a_module.o\n", - "[ 50%] Building CXX object CMakeFiles/nestml_c74fe99fdb8a4a94b0aaeb52ce20cf1a_module_module.dir/iaf_psc_delta_neuron_nestml.o\n", - "[ 75%] Building CXX object CMakeFiles/nestml_c74fe99fdb8a4a94b0aaeb52ce20cf1a_module_module.dir/iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml.o\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml.cpp: In member function ‘void iaf_psc_delta_neuron_nestml::init_state_internal_()’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml.cpp:173:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + "-- Build files have been written to: /home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target\n", + "[ 25%] Building CXX object CMakeFiles/nestml_c343f4cc15ff47b9adbc75b2cdd8dd06_module_module.dir/nestml_c343f4cc15ff47b9adbc75b2cdd8dd06_module.o\n", + "[ 50%] Building CXX object CMakeFiles/nestml_c343f4cc15ff47b9adbc75b2cdd8dd06_module_module.dir/iaf_psc_delta_neuron_nestml.o\n", + "[ 75%] Building CXX object CMakeFiles/nestml_c343f4cc15ff47b9adbc75b2cdd8dd06_module_module.dir/iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml.o\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml.cpp: In member function ‘void iaf_psc_delta_neuron_nestml::init_state_internal_()’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml.cpp:173:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", " 173 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml.cpp: In member function ‘virtual void iaf_psc_delta_neuron_nestml::update(const nest::Time&, long int, long int)’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml.cpp:266:24: warning: comparison of integer expressions of different signedness: ‘long int’ and ‘const size_t’ {aka ‘const long unsigned int’} [-Wsign-compare]\n", - " 266 | for (long i = 0; i < NUM_SPIKE_RECEPTORS; ++i)\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml.cpp: In member function ‘virtual void iaf_psc_delta_neuron_nestml::update(const nest::Time&, long int, long int)’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml.cpp:262:24: warning: comparison of integer expressions of different signedness: ‘long int’ and ‘const size_t’ {aka ‘const long unsigned int’} [-Wsign-compare]\n", + " 262 | for (long i = 0; i < NUM_SPIKE_RECEPTORS; ++i)\n", " | ~~^~~~~~~~~~~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml.cpp:261:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 261 | auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml.cpp:257:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 257 | auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml.cpp: In member function ‘void iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml::init_state_internal_()’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml.cpp:183:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml.cpp: In member function ‘void iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml::init_state_internal_()’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml.cpp:183:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", " 183 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml.cpp: In member function ‘virtual void iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml::update(const nest::Time&, long int, long int)’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml.cpp:287:24: warning: comparison of integer expressions of different signedness: ‘long int’ and ‘const size_t’ {aka ‘const long unsigned int’} [-Wsign-compare]\n", - " 287 | for (long i = 0; i < NUM_SPIKE_RECEPTORS; ++i)\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml.cpp: In member function ‘virtual void iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml::update(const nest::Time&, long int, long int)’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml.cpp:283:24: warning: comparison of integer expressions of different signedness: ‘long int’ and ‘const size_t’ {aka ‘const long unsigned int’} [-Wsign-compare]\n", + " 283 | for (long i = 0; i < NUM_SPIKE_RECEPTORS; ++i)\n", " | ~~^~~~~~~~~~~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml.cpp:282:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 282 | auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml.cpp:278:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 278 | auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", " | ^~~~~\n", - "In file included from /home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/nestml_c74fe99fdb8a4a94b0aaeb52ce20cf1a_module.cpp:36:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", + "In file included from /home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/nestml_c343f4cc15ff47b9adbc75b2cdd8dd06_module.cpp:36:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_model.h:164:25: required from ‘nest::GenericConnectorModel::GenericConnectorModel(std::string) [with ConnectionT = nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:62:5: required from ‘void nest::ModelManager::register_connection_model(const std::string&) [with ConnectionT = nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/nest_impl.h:37:70: required from ‘void nest::register_connection_model(const std::string&) [with ConnectorModelT = stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:568:91: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:683:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:557:91: required from here\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:683:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", " 683 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::recompute_internal_variables() [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:695:3: required from ‘nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierPtrRport]’\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::recompute_internal_variables() [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:696:3: required from ‘nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierPtrRport]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_model.h:164:25: required from ‘nest::GenericConnectorModel::GenericConnectorModel(std::string) [with ConnectionT = nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:62:5: required from ‘void nest::ModelManager::register_connection_model(const std::string&) [with ConnectionT = nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/nest_impl.h:37:70: required from ‘void nest::register_connection_model(const std::string&) [with ConnectorModelT = stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:568:91: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:671:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:557:91: required from here\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:671:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", " 671 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierIndex]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierIndex]’:\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_model.h:164:25: required from ‘nest::GenericConnectorModel::GenericConnectorModel(std::string) [with ConnectionT = nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:103:34: required from ‘void nest::ModelManager::register_specific_connection_model_(const std::string&) [with CompleteConnecionT = nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:67:80: required from ‘void nest::ModelManager::register_connection_model(const std::string&) [with ConnectionT = nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/nest_impl.h:37:70: required from ‘void nest::register_connection_model(const std::string&) [with ConnectorModelT = stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:568:91: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:683:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:557:91: required from here\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:683:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", " 683 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::recompute_internal_variables() [with targetidentifierT = nest::TargetIdentifierIndex]’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:695:3: required from ‘nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierIndex]’\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::recompute_internal_variables() [with targetidentifierT = nest::TargetIdentifierIndex]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:696:3: required from ‘nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierIndex]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_model.h:164:25: required from ‘nest::GenericConnectorModel::GenericConnectorModel(std::string) [with ConnectionT = nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:103:34: required from ‘void nest::ModelManager::register_specific_connection_model_(const std::string&) [with CompleteConnecionT = nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:67:80: required from ‘void nest::ModelManager::register_connection_model(const std::string&) [with ConnectionT = nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/nest_impl.h:37:70: required from ‘void nest::register_connection_model(const std::string&) [with ConnectorModelT = stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:568:91: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:671:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:557:91: required from here\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:671:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", " 671 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘bool nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport; size_t = long unsigned int]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘bool nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport; size_t = long unsigned int]’:\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:391:22: required from ‘void nest::Connector::send_to_all(size_t, const std::vector&, nest::Event&) [with ConnectionT = nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:383:3: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:484:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 484 | auto get_t = [_tr_t](){ return _tr_t; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:473:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 473 | auto get_t = [_tr_t](){ return _tr_t; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:509:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 509 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:498:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 498 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:545:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 545 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:534:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 534 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:417:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 417 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:406:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 406 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:419:10: warning: variable ‘get_thread’ set but not used [-Wunused-but-set-variable]\n", - " 419 | auto get_thread = [tid]()\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:408:10: warning: variable ‘get_thread’ set but not used [-Wunused-but-set-variable]\n", + " 408 | auto get_thread = [tid]()\n", " | ^~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘bool nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex; size_t = long unsigned int]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘bool nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex; size_t = long unsigned int]’:\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:391:22: required from ‘void nest::Connector::send_to_all(size_t, const std::vector&, nest::Event&) [with ConnectionT = nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:383:3: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:484:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 484 | auto get_t = [_tr_t](){ return _tr_t; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:473:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 473 | auto get_t = [_tr_t](){ return _tr_t; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:509:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 509 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:498:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 498 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:545:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 545 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:534:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 534 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:417:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 417 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:406:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 406 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:419:10: warning: variable ‘get_thread’ set but not used [-Wunused-but-set-variable]\n", - " 419 | auto get_thread = [tid]()\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:408:10: warning: variable ‘get_thread’ set but not used [-Wunused-but-set-variable]\n", + " 408 | auto get_thread = [tid]()\n", " | ^~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::update_internal_state_(double, double, const nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:479:9: required from ‘bool nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport; size_t = long unsigned int]’\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::update_internal_state_(double, double, const nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:468:9: required from ‘bool nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:391:22: required from ‘void nest::Connector::send_to_all(size_t, const std::vector&, nest::Event&) [with ConnectionT = nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:383:3: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:745:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 745 | const double __resolution = timestep; // do not remove, this is necessary for the resolution() function\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:743:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 743 | const double __resolution = timestep; // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:746:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 746 | auto get_t = [t_start](){ return t_start; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:744:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 744 | auto get_t = [t_start](){ return t_start; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::update_internal_state_(double, double, const nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex]’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:479:9: required from ‘bool nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex; size_t = long unsigned int]’\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::update_internal_state_(double, double, const nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:468:9: required from ‘bool nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:391:22: required from ‘void nest::Connector::send_to_all(size_t, const std::vector&, nest::Event&) [with ConnectionT = nest::stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:383:3: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:745:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 745 | const double __resolution = timestep; // do not remove, this is necessary for the resolution() function\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:743:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 743 | const double __resolution = timestep; // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:746:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 746 | auto get_t = [t_start](){ return t_start; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", - " | ^~~~~\n", - "[100%] Linking CXX shared module nestml_c74fe99fdb8a4a94b0aaeb52ce20cf1a_module.so\n", - "[100%] Built target nestml_c74fe99fdb8a4a94b0aaeb52ce20cf1a_module_module\n", - "[100%] Built target nestml_c74fe99fdb8a4a94b0aaeb52ce20cf1a_module_module\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:744:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 744 | auto get_t = [t_start](){ return t_start; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + " | ^~~~~\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[100%] Linking CXX shared module nestml_c343f4cc15ff47b9adbc75b2cdd8dd06_module.so\n", + "[100%] Built target nestml_c343f4cc15ff47b9adbc75b2cdd8dd06_module_module\n", + "[100%] Built target nestml_c343f4cc15ff47b9adbc75b2cdd8dd06_module_module\n", "Install the project...\n", "-- Install configuration: \"\"\n", - "-- Installing: /tmp/nestml_target_i1uuk7tq/nestml_c74fe99fdb8a4a94b0aaeb52ce20cf1a_module.so\n" + "-- Installing: /tmp/nestml_target_4f4go9f_/nestml_c343f4cc15ff47b9adbc75b2cdd8dd06_module.so\n" ] } ], "source": [ - "module_name, neuron_model_name, synapse_model_name = NESTCodeGeneratorUtils.generate_code_for(\n", - " \"../../../models/neurons/iaf_psc_delta_neuron.nestml\",\n", - " nestml_stdp_model,\n", - " post_ports=[\"post_spikes\"])" + "module_name, neuron_model_name, synapse_model_name = \\\n", + " NESTCodeGeneratorUtils.generate_code_for(\"../../../models/neurons/iaf_psc_delta_neuron.nestml\",\n", + " nestml_stdp_model,\n", + " post_ports=[\"post_spikes\"],\n", + " codegen_opts={\"delay_variable\": {\"stdp_synapse\": \"d\"},\n", + " \"weight_variable\": {\"stdp_synapse\": \"w\"}})" ] }, { @@ -660,1206 +668,1218 @@ "output_type": "stream", "text": [ "\n", - "Apr 19 11:51:50 Install [Info]: \n", - " loaded module nestml_c74fe99fdb8a4a94b0aaeb52ce20cf1a_module\n", + "Apr 30 14:54:02 Install [Info]: \n", + " loaded module nestml_c343f4cc15ff47b9adbc75b2cdd8dd06_module\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:50 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", - "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:51 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:52 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:02 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n" ] @@ -1904,1203 +1924,1215 @@ "output_type": "stream", "text": [ "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:53 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:54 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:55 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:56 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:56 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:56 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:56 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:56 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:56 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:56 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:56 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:56 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:56 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:56 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:51:56 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", + "Apr 30 14:54:03 iaf_psc_delta_neuron_nestml__with_stdp_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n" ] @@ -3234,7 +3266,20 @@ "\n", "[17,stdp_windowed_synapse_nestml, WARNING, [10:8;10:28]]: Variable 'd' has the same name as a physical unit!\n", "[25,stdp_windowed_synapse_nestml, WARNING, [10:8;10:28]]: Variable 'd' has the same name as a physical unit!\n", - "[35,stdp_windowed_synapse_nestml, WARNING, [10:8;10:28]]: Variable 'd' has the same name as a physical unit!\n", + "[35,stdp_windowed_synapse_nestml, WARNING, [10:8;10:28]]: Variable 'd' has the same name as a physical unit!\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:Not preserving expression for variable \"V_m\" as it is solved by propagator solver\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "[64,stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml, WARNING, [10:8;10:28]]: Variable 'd' has the same name as a physical unit!\n" ] }, @@ -3242,7 +3287,6 @@ "name": "stderr", "output_type": "stream", "text": [ - "WARNING:Not preserving expression for variable \"V_m\" as it is solved by propagator solver\n", "WARNING:Not preserving expression for variable \"V_m\" as it is solved by propagator solver\n", "WARNING:Not preserving expression for variable \"post_nn_trace__for_stdp_windowed_synapse_nestml\" as it is solved by propagator solver\n", "WARNING:Not preserving expression for variable \"pre_nn_trace\" as it is solved by propagator solver\n" @@ -3268,7 +3312,7 @@ "-- Detecting CXX compile features - done\n", "\n", "-------------------------------------------------------\n", - "nestml_81cef8d40f4e47aea7c9c5093486008d_module Configuration Summary\n", + "nestml_ca37c3b6c2f443979bd170336b21e392_module Configuration Summary\n", "-------------------------------------------------------\n", "\n", "C++ compiler : /usr/bin/c++\n", @@ -3280,15 +3324,15 @@ "\n", "-------------------------------------------------------\n", "\n", - "You can now build and install 'nestml_81cef8d40f4e47aea7c9c5093486008d_module' using\n", + "You can now build and install 'nestml_ca37c3b6c2f443979bd170336b21e392_module' using\n", " make\n", " make install\n", "\n", - "The library file libnestml_81cef8d40f4e47aea7c9c5093486008d_module.so will be installed to\n", - " /tmp/nestml_target_kubgfbw2\n", + "The library file libnestml_ca37c3b6c2f443979bd170336b21e392_module.so will be installed to\n", + " /tmp/nestml_target_c658rzes\n", "The module can be loaded into NEST using\n", - " (nestml_81cef8d40f4e47aea7c9c5093486008d_module) Install (in SLI)\n", - " nest.Install(nestml_81cef8d40f4e47aea7c9c5093486008d_module) (in PyNEST)\n", + " (nestml_ca37c3b6c2f443979bd170336b21e392_module) Install (in SLI)\n", + " nest.Install(nestml_ca37c3b6c2f443979bd170336b21e392_module) (in PyNEST)\n", "\n", "CMake Warning (dev) in CMakeLists.txt:\n", " No cmake_minimum_required command is present. A line of code such as\n", @@ -3300,141 +3344,155 @@ " information run \"cmake --help-policy CMP0000\".\n", "This warning is for project developers. Use -Wno-dev to suppress it.\n", "\n", - "-- Configuring done (0.5s)\n", + "-- Configuring done (0.1s)\n", "-- Generating done (0.0s)\n", - "-- Build files have been written to: /home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target\n", - "[ 25%] Building CXX object CMakeFiles/nestml_81cef8d40f4e47aea7c9c5093486008d_module_module.dir/nestml_81cef8d40f4e47aea7c9c5093486008d_module.o\n", - "[ 50%] Building CXX object CMakeFiles/nestml_81cef8d40f4e47aea7c9c5093486008d_module_module.dir/iaf_psc_delta_neuron_nestml.o\n", - "[ 75%] Building CXX object CMakeFiles/nestml_81cef8d40f4e47aea7c9c5093486008d_module_module.dir/iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml.o\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml.cpp: In member function ‘void iaf_psc_delta_neuron_nestml::init_state_internal_()’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml.cpp:173:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + "-- Build files have been written to: /home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target\n", + "[ 25%] Building CXX object CMakeFiles/nestml_ca37c3b6c2f443979bd170336b21e392_module_module.dir/nestml_ca37c3b6c2f443979bd170336b21e392_module.o\n", + "[ 50%] Building CXX object CMakeFiles/nestml_ca37c3b6c2f443979bd170336b21e392_module_module.dir/iaf_psc_delta_neuron_nestml.o\n", + "[ 75%] Building CXX object CMakeFiles/nestml_ca37c3b6c2f443979bd170336b21e392_module_module.dir/iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml.o\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml.cpp: In member function ‘void iaf_psc_delta_neuron_nestml::init_state_internal_()’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml.cpp:173:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", " 173 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml.cpp: In member function ‘virtual void iaf_psc_delta_neuron_nestml::update(const nest::Time&, long int, long int)’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml.cpp:266:24: warning: comparison of integer expressions of different signedness: ‘long int’ and ‘const size_t’ {aka ‘const long unsigned int’} [-Wsign-compare]\n", - " 266 | for (long i = 0; i < NUM_SPIKE_RECEPTORS; ++i)\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml.cpp: In member function ‘virtual void iaf_psc_delta_neuron_nestml::update(const nest::Time&, long int, long int)’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml.cpp:262:24: warning: comparison of integer expressions of different signedness: ‘long int’ and ‘const size_t’ {aka ‘const long unsigned int’} [-Wsign-compare]\n", + " 262 | for (long i = 0; i < NUM_SPIKE_RECEPTORS; ++i)\n", " | ~~^~~~~~~~~~~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml.cpp:261:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 261 | auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml.cpp:257:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 257 | auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml.cpp: In member function ‘void iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml::init_state_internal_()’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml.cpp:188:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml.cpp: In member function ‘void iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml::init_state_internal_()’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml.cpp:188:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", " 188 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml.cpp: In member function ‘virtual void iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml::update(const nest::Time&, long int, long int)’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml.cpp:297:24: warning: comparison of integer expressions of different signedness: ‘long int’ and ‘const size_t’ {aka ‘const long unsigned int’} [-Wsign-compare]\n", - " 297 | for (long i = 0; i < NUM_SPIKE_RECEPTORS; ++i)\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml.cpp: In member function ‘virtual void iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml::update(const nest::Time&, long int, long int)’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml.cpp:293:24: warning: comparison of integer expressions of different signedness: ‘long int’ and ‘const size_t’ {aka ‘const long unsigned int’} [-Wsign-compare]\n", + " 293 | for (long i = 0; i < NUM_SPIKE_RECEPTORS; ++i)\n", " | ~~^~~~~~~~~~~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml.cpp:292:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 292 | auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml.cpp:288:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 288 | auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", " | ^~~~~\n", - "In file included from /home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/nestml_81cef8d40f4e47aea7c9c5093486008d_module.cpp:36:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", + "In file included from /home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/nestml_ca37c3b6c2f443979bd170336b21e392_module.cpp:36:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_model.h:164:25: required from ‘nest::GenericConnectorModel::GenericConnectorModel(std::string) [with ConnectionT = nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:62:5: required from ‘void nest::ModelManager::register_connection_model(const std::string&) [with ConnectionT = nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/nest_impl.h:37:70: required from ‘void nest::register_connection_model(const std::string&) [with ConnectorModelT = stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:611:100: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:739:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 739 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", - " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml::recompute_internal_variables() [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:753:3: required from ‘nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierPtrRport]’\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:598:100: required from here\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:737:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 737 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " | ^~~~~~~~~~~~\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml::recompute_internal_variables() [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:752:3: required from ‘nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierPtrRport]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_model.h:164:25: required from ‘nest::GenericConnectorModel::GenericConnectorModel(std::string) [with ConnectionT = nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:62:5: required from ‘void nest::ModelManager::register_connection_model(const std::string&) [with ConnectionT = nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/nest_impl.h:37:70: required from ‘void nest::register_connection_model(const std::string&) [with ConnectorModelT = stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:611:100: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:726:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 726 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:598:100: required from here\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:724:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 724 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierIndex]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierIndex]’:\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_model.h:164:25: required from ‘nest::GenericConnectorModel::GenericConnectorModel(std::string) [with ConnectionT = nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:103:34: required from ‘void nest::ModelManager::register_specific_connection_model_(const std::string&) [with CompleteConnecionT = nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:67:80: required from ‘void nest::ModelManager::register_connection_model(const std::string&) [with ConnectionT = nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/nest_impl.h:37:70: required from ‘void nest::register_connection_model(const std::string&) [with ConnectorModelT = stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:611:100: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:739:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 739 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:598:100: required from here\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:737:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 737 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml::recompute_internal_variables() [with targetidentifierT = nest::TargetIdentifierIndex]’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:753:3: required from ‘nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierIndex]’\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml::recompute_internal_variables() [with targetidentifierT = nest::TargetIdentifierIndex]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:752:3: required from ‘nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierIndex]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_model.h:164:25: required from ‘nest::GenericConnectorModel::GenericConnectorModel(std::string) [with ConnectionT = nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:103:34: required from ‘void nest::ModelManager::register_specific_connection_model_(const std::string&) [with CompleteConnecionT = nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:67:80: required from ‘void nest::ModelManager::register_connection_model(const std::string&) [with ConnectionT = nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/nest_impl.h:37:70: required from ‘void nest::register_connection_model(const std::string&) [with ConnectorModelT = stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:611:100: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:726:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 726 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:598:100: required from here\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:724:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 724 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘bool nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport; size_t = long unsigned int]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘bool nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport; size_t = long unsigned int]’:\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:391:22: required from ‘void nest::Connector::send_to_all(size_t, const std::vector&, nest::Event&) [with ConnectionT = nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:383:3: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:517:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 517 | auto get_t = [_tr_t](){ return _tr_t; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:504:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 504 | auto get_t = [_tr_t](){ return _tr_t; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:545:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 545 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:532:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 532 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:585:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 585 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:572:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 572 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:450:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 450 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:437:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 437 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:452:10: warning: variable ‘get_thread’ set but not used [-Wunused-but-set-variable]\n", - " 452 | auto get_thread = [tid]()\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:439:10: warning: variable ‘get_thread’ set but not used [-Wunused-but-set-variable]\n", + " 439 | auto get_thread = [tid]()\n", " | ^~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘bool nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex; size_t = long unsigned int]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘bool nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex; size_t = long unsigned int]’:\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:391:22: required from ‘void nest::Connector::send_to_all(size_t, const std::vector&, nest::Event&) [with ConnectionT = nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:383:3: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:517:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 517 | auto get_t = [_tr_t](){ return _tr_t; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:504:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 504 | auto get_t = [_tr_t](){ return _tr_t; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:545:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 545 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:532:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 532 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:585:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 585 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:572:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 572 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:450:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 450 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:437:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 437 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:452:10: warning: variable ‘get_thread’ set but not used [-Wunused-but-set-variable]\n", - " 452 | auto get_thread = [tid]()\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:439:10: warning: variable ‘get_thread’ set but not used [-Wunused-but-set-variable]\n", + " 439 | auto get_thread = [tid]()\n", " | ^~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml::update_internal_state_(double, double, const nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:512:9: required from ‘bool nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport; size_t = long unsigned int]’\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml::update_internal_state_(double, double, const nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:499:9: required from ‘bool nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:391:22: required from ‘void nest::Connector::send_to_all(size_t, const std::vector&, nest::Event&) [with ConnectionT = nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:383:3: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:807:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 807 | const double __resolution = timestep; // do not remove, this is necessary for the resolution() function\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:803:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 803 | const double __resolution = timestep; // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:808:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 808 | auto get_t = [t_start](){ return t_start; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:804:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 804 | auto get_t = [t_start](){ return t_start; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml::update_internal_state_(double, double, const nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex]’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:512:9: required from ‘bool nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex; size_t = long unsigned int]’\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml::update_internal_state_(double, double, const nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:499:9: required from ‘bool nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:391:22: required from ‘void nest::Connector::send_to_all(size_t, const std::vector&, nest::Event&) [with ConnectionT = nest::stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:383:3: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:807:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 807 | const double __resolution = timestep; // do not remove, this is necessary for the resolution() function\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:803:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 803 | const double __resolution = timestep; // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:808:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 808 | auto get_t = [t_start](){ return t_start; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", - " | ^~~~~\n", - "[100%] Linking CXX shared module nestml_81cef8d40f4e47aea7c9c5093486008d_module.so\n", - "[100%] Built target nestml_81cef8d40f4e47aea7c9c5093486008d_module_module\n", - "[100%] Built target nestml_81cef8d40f4e47aea7c9c5093486008d_module_module\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_windowed_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:804:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 804 | auto get_t = [t_start](){ return t_start; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + " | ^~~~~\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[100%] Linking CXX shared module nestml_ca37c3b6c2f443979bd170336b21e392_module.so\n", + "[100%] Built target nestml_ca37c3b6c2f443979bd170336b21e392_module_module\n", + "[100%] Built target nestml_ca37c3b6c2f443979bd170336b21e392_module_module\n", "Install the project...\n", "-- Install configuration: \"\"\n", - "-- Installing: /tmp/nestml_target_kubgfbw2/nestml_81cef8d40f4e47aea7c9c5093486008d_module.so\n" + "-- Installing: /tmp/nestml_target_c658rzes/nestml_ca37c3b6c2f443979bd170336b21e392_module.so\n" ] } ], "source": [ - "module_name, neuron_model_name, synapse_model_name = NESTCodeGeneratorUtils.generate_code_for(\n", - " \"../../../models/neurons/iaf_psc_delta_neuron.nestml\",\n", - " nestml_windowed_stdp_model,\n", - " post_ports=[\"post_spikes\"])" + "module_name, neuron_model_name, synapse_model_name = \\\n", + " NESTCodeGeneratorUtils.generate_code_for(\"../../../models/neurons/iaf_psc_delta_neuron.nestml\",\n", + " nestml_windowed_stdp_model,\n", + " post_ports=[\"post_spikes\"],\n", + " codegen_opts={\"delay_variable\": {\"stdp_windowed_synapse\": \"d\"},\n", + " \"weight_variable\": {\"stdp_windowed_synapse\": \"w\"}})" ] }, { @@ -3447,1203 +3505,1227 @@ "output_type": "stream", "text": [ "\n", - "Apr 19 11:52:39 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:39 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:39 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:39 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:39 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:39 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:39 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:39 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:39 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:39 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:39 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:39 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:39 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:39 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:39 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:39 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:39 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:39 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:39 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:39 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:39 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:39 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:39 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:39 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:39 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:39 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:39 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:39 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:39 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:39 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:39 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:39 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:39 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:39 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:39 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:39 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:39 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:39 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", + " model have been reset!\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", - "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:40 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:13 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:41 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml [Warning]: \n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 11:52:42 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", + "Apr 30 14:54:14 iaf_psc_delta_neuron_nestml__with_stdp_windowed_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n" ] @@ -4657,2340 +4739,1423 @@ }, "metadata": {}, "output_type": "display_data" - }, + } + ], + "source": [ + "dt_vec, dw_vec, delay = stdp_window(module_name, neuron_model_name, synapse_model_name)\n", + "plot_stdp_window(dt_vec, dw_vec, delay)" + ] + }, + { + "attachments": { + "image.png": { + "image/png": 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" + } + }, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Symmetric inhibitory STDP\n", + "--------------------\n", + "\n", + "\n", + "
\n", + "\n", + "
\n", + "\n", + "The symmetric STDP window in the figure can be observed experimentally and was used to achieve a self-organised balance between excitation and inhibition in recurrent networks [4]_." + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "nestml_stdp_vogels_model = \"\"\"\n", + "model stdp_vogels_synapse:\n", + "\n", + " state:\n", + " w real = 1.\n", + "\n", + " parameters:\n", + " d ms = 1 ms @nest::delay # !!! cannot have a variable called \"delay\"\n", + " lambda real = .01\n", + " offset real = 1.\n", + " tau_tr_pre ms = 20 ms\n", + " tau_tr_post ms = 20 ms\n", + " alpha real = 1\n", + " mu_plus real = 1\n", + " mu_minus real = 1\n", + " Wmax real = 100.\n", + " Wmin real = 0.\n", + "\n", + " equations:\n", + " kernel pre_trace_kernel = exp(-t / tau_tr_pre)\n", + " inline pre_trace real = convolve(pre_trace_kernel, pre_spikes)\n", + "\n", + " # all-to-all trace of postsynaptic neuron\n", + " kernel post_trace_kernel = exp(-t / tau_tr_post)\n", + " inline post_trace real = convolve(post_trace_kernel, post_spikes)\n", + "\n", + " input:\n", + " pre_spikes <- spike\n", + " post_spikes <- spike\n", + "\n", + " output:\n", + " spike\n", + "\n", + " onReceive(post_spikes, priority=2):\n", + " w += lambda * (pre_trace + post_trace)\n", + "\n", + " onReceive(pre_spikes, priority=1):\n", + " w += lambda * (pre_trace + post_trace - offset)\n", + "\n", + " # deliver spike to postsynaptic partner\n", + " emit_spike(w, d)\n", + " \n", + " update:\n", + " integrate_odes()\n", + "\"\"\"" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Save to a temporary file and make the model available to instantiate in NEST:" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - " model have been reset!\n", "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", + " -- N E S T --\n", + " Copyright (C) 2004 The NEST Initiative\n", "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", + " Version: 3.6.0-post0.dev0\n", + " Built: Mar 26 2024 08:52:51\n", "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", + " This program is provided AS IS and comes with\n", + " NO WARRANTY. See the file LICENSE for details.\n", "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", + " Problems or suggestions?\n", + " Visit https://www.nest-simulator.org\n", "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", + " Type 'nest.help()' to find out more about NEST.\n", "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", + "[17,stdp_vogels_synapse_nestml, WARNING, [8:8;8:28]]: Variable 'd' has the same name as a physical unit!\n", + "[23,stdp_vogels_synapse_nestml, WARNING, [8:8;8:28]]: Variable 'd' has the same name as a physical unit!\n", + "[31,stdp_vogels_synapse_nestml, WARNING, [8:8;8:28]]: Variable 'd' has the same name as a physical unit!\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:Not preserving expression for variable \"V_m\" as it is solved by propagator solver\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[52,stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml, WARNING, [8:8;8:28]]: Variable 'd' has the same name as a physical unit!\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:Not preserving expression for variable \"V_m\" as it is solved by propagator solver\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[66,stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml, WARNING, [8:8;8:28]]: Variable 'd' has the same name as a physical unit!\n", + "[71,stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml, WARNING, [8:8;8:28]]: Variable 'd' has the same name as a physical unit!\n", + "CMake Warning (dev) at CMakeLists.txt:95 (project):\n", + " cmake_minimum_required() should be called prior to this top-level project()\n", + " call. Please see the cmake-commands(7) manual for usage documentation of\n", + " both commands.\n", + "This warning is for project developers. Use -Wno-dev to suppress it.\n", "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", + "-- The CXX compiler identification is GNU 12.3.0\n", + "-- Detecting CXX compiler ABI info\n", + "-- Detecting CXX compiler ABI info - done\n", + "-- Check for working CXX compiler: /usr/bin/c++ - skipped\n", + "-- Detecting CXX compile features\n", + "-- Detecting CXX compile features - done\n", "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", + "-------------------------------------------------------\n", + "nestml_2eb2d0739d344962b295d706d7d2c7f2_module Configuration Summary\n", + "-------------------------------------------------------\n", "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:07 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n" - ] - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "dt_vec, dw_vec, delay = stdp_window(module_name, neuron_model_name, synapse_model_name)\n", - "plot_stdp_window(dt_vec, dw_vec, delay)" - ] - }, - { - "attachments": { - "image.png": { - "image/png": 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" - } - }, - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Symmetric inhibitory STDP\n", - "--------------------\n", - "\n", - "\n", - "
\n", - "\n", - "
\n", - "\n", - "The symmetric STDP window in the figure can be observed experimentally and was used to achieve a self-organised balance between excitation and inhibition in recurrent networks [4]_." - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [], - "source": [ - "nestml_stdp_vogels_model = \"\"\"\n", - "model stdp_vogels_synapse:\n", - "\n", - " state:\n", - " w real = 1.\n", - "\n", - " parameters:\n", - " d ms = 1 ms @nest::delay # !!! cannot have a variable called \"delay\"\n", - " lambda real = .01\n", - " offset real = 1.\n", - " tau_tr_pre ms = 20 ms\n", - " tau_tr_post ms = 20 ms\n", - " alpha real = 1\n", - " mu_plus real = 1\n", - " mu_minus real = 1\n", - " Wmax real = 100.\n", - " Wmin real = 0.\n", - "\n", - " equations:\n", - " kernel pre_trace_kernel = exp(-t / tau_tr_pre)\n", - " inline pre_trace real = convolve(pre_trace_kernel, pre_spikes)\n", - "\n", - " # all-to-all trace of postsynaptic neuron\n", - " kernel post_trace_kernel = exp(-t / tau_tr_post)\n", - " inline post_trace real = convolve(post_trace_kernel, post_spikes)\n", - "\n", - " input:\n", - " pre_spikes <- spike\n", - " post_spikes <- spike\n", - "\n", - " output:\n", - " spike\n", - "\n", - " onReceive(post_spikes, priority=2):\n", - " w += lambda * (pre_trace + post_trace)\n", - "\n", - " onReceive(pre_spikes, priority=1):\n", - " w += lambda * (pre_trace + post_trace - offset)\n", - "\n", - " # deliver spike to postsynaptic partner\n", - " emit_spike(w, d)\n", - " \n", - " update:\n", - " integrate_odes()\n", - "\"\"\"" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Save to a temporary file and make the model available to instantiate in NEST:" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - " -- N E S T --\n", - " Copyright (C) 2004 The NEST Initiative\n", - "\n", - " Version: 3.6.0-post0.dev0\n", - " Built: Mar 26 2024 08:52:51\n", - "\n", - " This program is provided AS IS and comes with\n", - " NO WARRANTY. See the file LICENSE for details.\n", - "\n", - " Problems or suggestions?\n", - " Visit https://www.nest-simulator.org\n", - "\n", - " Type 'nest.help()' to find out more about NEST.\n", - "\n", - "[17,stdp_vogels_synapse_nestml, WARNING, [8:8;8:28]]: Variable 'd' has the same name as a physical unit!\n", - "[23,stdp_vogels_synapse_nestml, WARNING, [8:8;8:28]]: Variable 'd' has the same name as a physical unit!\n", - "[31,stdp_vogels_synapse_nestml, WARNING, [8:8;8:28]]: Variable 'd' has the same name as a physical unit!\n", - "[52,stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml, WARNING, [8:8;8:28]]: Variable 'd' has the same name as a physical unit!\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "WARNING:Not preserving expression for variable \"V_m\" as it is solved by propagator solver\n", - "WARNING:Not preserving expression for variable \"V_m\" as it is solved by propagator solver\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[66,stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml, WARNING, [8:8;8:28]]: Variable 'd' has the same name as a physical unit!\n", - "[71,stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml, WARNING, [8:8;8:28]]: Variable 'd' has the same name as a physical unit!\n", - "CMake Warning (dev) at CMakeLists.txt:95 (project):\n", - " cmake_minimum_required() should be called prior to this top-level project()\n", - " call. Please see the cmake-commands(7) manual for usage documentation of\n", - " both commands.\n", - "This warning is for project developers. Use -Wno-dev to suppress it.\n", - "\n", - "-- The CXX compiler identification is GNU 12.3.0\n", - "-- Detecting CXX compiler ABI info\n", - "-- Detecting CXX compiler ABI info - done\n", - "-- Check for working CXX compiler: /usr/bin/c++ - skipped\n", - "-- Detecting CXX compile features\n", - "-- Detecting CXX compile features - done\n", - "\n", - "-------------------------------------------------------\n", - "nestml_8e9daa037f484288a6e9ba0cf082d818_module Configuration Summary\n", - "-------------------------------------------------------\n", - "\n", - "C++ compiler : /usr/bin/c++\n", - "Build static libs : OFF\n", - "C++ compiler flags : \n", - "NEST compiler flags : -std=c++17 -Wall -fopenmp -O2 -fdiagnostics-color=auto\n", - "NEST include dirs : -I/home/charl/julich/nest-simulator-install/include/nest -I/usr/include -I/usr/include -I/usr/include\n", - "NEST libraries flags : -L/home/charl/julich/nest-simulator-install/lib/nest -lnest -lsli /usr/lib/x86_64-linux-gnu/libltdl.so /usr/lib/x86_64-linux-gnu/libgsl.so /usr/lib/x86_64-linux-gnu/libgslcblas.so /usr/lib/gcc/x86_64-linux-gnu/12/libgomp.so /usr/lib/x86_64-linux-gnu/libpthread.a\n", - "\n", - "-------------------------------------------------------\n", - "\n", - "You can now build and install 'nestml_8e9daa037f484288a6e9ba0cf082d818_module' using\n", - " make\n", - " make install\n", - "\n", - "The library file libnestml_8e9daa037f484288a6e9ba0cf082d818_module.so will be installed to\n", - " /tmp/nestml_target_creme1gl\n", - "The module can be loaded into NEST using\n", - " (nestml_8e9daa037f484288a6e9ba0cf082d818_module) Install (in SLI)\n", - " nest.Install(nestml_8e9daa037f484288a6e9ba0cf082d818_module) (in PyNEST)\n", - "\n", - "CMake Warning (dev) in CMakeLists.txt:\n", - " No cmake_minimum_required command is present. A line of code such as\n", - "\n", - " cmake_minimum_required(VERSION 3.26)\n", - "\n", - " should be added at the top of the file. The version specified may be lower\n", - " if you wish to support older CMake versions for this project. For more\n", - " information run \"cmake --help-policy CMP0000\".\n", - "This warning is for project developers. Use -Wno-dev to suppress it.\n", - "\n", - "-- Configuring done (0.5s)\n", - "-- Generating done (0.0s)\n", - "-- Build files have been written to: /home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target\n", - "[ 25%] Building CXX object CMakeFiles/nestml_8e9daa037f484288a6e9ba0cf082d818_module_module.dir/nestml_8e9daa037f484288a6e9ba0cf082d818_module.o\n", - "[ 50%] Building CXX object CMakeFiles/nestml_8e9daa037f484288a6e9ba0cf082d818_module_module.dir/iaf_psc_delta_neuron_nestml.o\n", - "[ 75%] Building CXX object CMakeFiles/nestml_8e9daa037f484288a6e9ba0cf082d818_module_module.dir/iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml.o\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml.cpp: In member function ‘void iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml::init_state_internal_()’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml.cpp:183:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 183 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", - " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml.cpp: In member function ‘virtual void iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml::update(const nest::Time&, long int, long int)’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml.cpp:287:24: warning: comparison of integer expressions of different signedness: ‘long int’ and ‘const size_t’ {aka ‘const long unsigned int’} [-Wsign-compare]\n", - " 287 | for (long i = 0; i < NUM_SPIKE_RECEPTORS; ++i)\n", - " | ~~^~~~~~~~~~~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml.cpp:282:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 282 | auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", - " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml.cpp: In member function ‘void iaf_psc_delta_neuron_nestml::init_state_internal_()’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml.cpp:173:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 173 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", - " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml.cpp: In member function ‘virtual void iaf_psc_delta_neuron_nestml::update(const nest::Time&, long int, long int)’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml.cpp:266:24: warning: comparison of integer expressions of different signedness: ‘long int’ and ‘const size_t’ {aka ‘const long unsigned int’} [-Wsign-compare]\n", - " 266 | for (long i = 0; i < NUM_SPIKE_RECEPTORS; ++i)\n", - " | ~~^~~~~~~~~~~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml.cpp:261:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 261 | auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", - " | ^~~~~\n", - "In file included from /home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/nestml_8e9daa037f484288a6e9ba0cf082d818_module.cpp:36:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", - "/home/charl/julich/nest-simulator-install/include/nest/connector_model.h:164:25: required from ‘nest::GenericConnectorModel::GenericConnectorModel(std::string) [with ConnectionT = nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", - "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:62:5: required from ‘void nest::ModelManager::register_connection_model(const std::string&) [with ConnectionT = nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", - "/home/charl/julich/nest-simulator-install/include/nest/nest_impl.h:37:70: required from ‘void nest::register_connection_model(const std::string&) [with ConnectorModelT = stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:576:98: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:695:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 695 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", - " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml::recompute_internal_variables() [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:708:3: required from ‘nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierPtrRport]’\n", - "/home/charl/julich/nest-simulator-install/include/nest/connector_model.h:164:25: required from ‘nest::GenericConnectorModel::GenericConnectorModel(std::string) [with ConnectionT = nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", - "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:62:5: required from ‘void nest::ModelManager::register_connection_model(const std::string&) [with ConnectionT = nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", - "/home/charl/julich/nest-simulator-install/include/nest/nest_impl.h:37:70: required from ‘void nest::register_connection_model(const std::string&) [with ConnectorModelT = stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:576:98: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:683:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 683 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", - " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierIndex]’:\n", - "/home/charl/julich/nest-simulator-install/include/nest/connector_model.h:164:25: required from ‘nest::GenericConnectorModel::GenericConnectorModel(std::string) [with ConnectionT = nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", - "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:103:34: required from ‘void nest::ModelManager::register_specific_connection_model_(const std::string&) [with CompleteConnecionT = nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", - "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:67:80: required from ‘void nest::ModelManager::register_connection_model(const std::string&) [with ConnectionT = nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", - "/home/charl/julich/nest-simulator-install/include/nest/nest_impl.h:37:70: required from ‘void nest::register_connection_model(const std::string&) [with ConnectorModelT = stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:576:98: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:695:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 695 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", - " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml::recompute_internal_variables() [with targetidentifierT = nest::TargetIdentifierIndex]’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:708:3: required from ‘nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierIndex]’\n", - "/home/charl/julich/nest-simulator-install/include/nest/connector_model.h:164:25: required from ‘nest::GenericConnectorModel::GenericConnectorModel(std::string) [with ConnectionT = nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", - "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:103:34: required from ‘void nest::ModelManager::register_specific_connection_model_(const std::string&) [with CompleteConnecionT = nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", - "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:67:80: required from ‘void nest::ModelManager::register_connection_model(const std::string&) [with ConnectionT = nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", - "/home/charl/julich/nest-simulator-install/include/nest/nest_impl.h:37:70: required from ‘void nest::register_connection_model(const std::string&) [with ConnectorModelT = stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:576:98: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:683:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 683 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", - " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘bool nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport; size_t = long unsigned int]’:\n", - "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:391:22: required from ‘void nest::Connector::send_to_all(size_t, const std::vector&, nest::Event&) [with ConnectionT = nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml; size_t = long unsigned int]’\n", - "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:383:3: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:495:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 495 | auto get_t = [_tr_t](){ return _tr_t; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", - " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:519:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 519 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", - " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:554:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 554 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", - " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:428:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 428 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", - " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:430:10: warning: variable ‘get_thread’ set but not used [-Wunused-but-set-variable]\n", - " 430 | auto get_thread = [tid]()\n", - " | ^~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘bool nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex; size_t = long unsigned int]’:\n", - "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:391:22: required from ‘void nest::Connector::send_to_all(size_t, const std::vector&, nest::Event&) [with ConnectionT = nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml; size_t = long unsigned int]’\n", - "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:383:3: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:495:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 495 | auto get_t = [_tr_t](){ return _tr_t; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", - " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:519:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 519 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", - " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:554:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 554 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", - " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:428:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 428 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", - " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:430:10: warning: variable ‘get_thread’ set but not used [-Wunused-but-set-variable]\n", - " 430 | auto get_thread = [tid]()\n", - " | ^~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml::update_internal_state_(double, double, const nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:490:9: required from ‘bool nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport; size_t = long unsigned int]’\n", - "/home/charl/julich/nest-simulator-i" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[100%] Linking CXX shared module nestml_913e0b5b31a0403a9a7bfc51a747debd_module.so\n", - "[100%] Built target nestml_913e0b5b31a0403a9a7bfc51a747debd_module_module\n", - "[100%] Built target nestml_913e0b5b31a0403a9a7bfc51a747debd_module_module\n", - "Install the project...\n", - "-- Install configuration: \"\"\n", - "-- Installing: /home/charl/julich/nest-simulator-install/lib/nest/nestml_913e0b5b31a0403a9a7bfc51a747debd_module.so\n" - ] - } - ], - "source": [ - "module_name, neuron_model_name, synapse_model_name = NESTCodeGeneratorUtils.generate_code_for(\n", - " \"../../../models/neurons/iaf_psc_delta_neuron.nestml\",\n", - " nestml_stdp_vogels_model,\n", - " post_ports=[\"post_spikes\"])" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", + "C++ compiler : /usr/bin/c++\n", + "Build static libs : OFF\n", + "C++ compiler flags : \n", + "NEST compiler flags : -std=c++17 -Wall -fopenmp -O2 -fdiagnostics-color=auto\n", + "NEST include dirs : -I/home/charl/julich/nest-simulator-install/include/nest -I/usr/include -I/usr/include -I/usr/include\n", + "NEST libraries flags : -L/home/charl/julich/nest-simulator-install/lib/nest -lnest -lsli /usr/lib/x86_64-linux-gnu/libltdl.so /usr/lib/x86_64-linux-gnu/libgsl.so /usr/lib/x86_64-linux-gnu/libgslcblas.so /usr/lib/gcc/x86_64-linux-gnu/12/libgomp.so /usr/lib/x86_64-linux-gnu/libpthread.a\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", + "-------------------------------------------------------\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", + "You can now build and install 'nestml_2eb2d0739d344962b295d706d7d2c7f2_module' using\n", + " make\n", + " make install\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", + "The library file libnestml_2eb2d0739d344962b295d706d7d2c7f2_module.so will be installed to\n", + " /tmp/nestml_target_mwbt6667\n", + "The module can be loaded into NEST using\n", + " (nestml_2eb2d0739d344962b295d706d7d2c7f2_module) Install (in SLI)\n", + " nest.Install(nestml_2eb2d0739d344962b295d706d7d2c7f2_module) (in PyNEST)\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", + "CMake Warning (dev) in CMakeLists.txt:\n", + " No cmake_minimum_required command is present. A line of code such as\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", + " cmake_minimum_required(VERSION 3.26)\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", + " should be added at the top of the file. The version specified may be lower\n", + " if you wish to support older CMake versions for this project. For more\n", + " information run \"cmake --help-policy CMP0000\".\n", + "This warning is for project developers. Use -Wno-dev to suppress it.\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", + "-- Configuring done (0.1s)\n", + "-- Generating done (0.0s)\n", + "-- Build files have been written to: /home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target\n", + "[ 25%] Building CXX object CMakeFiles/nestml_2eb2d0739d344962b295d706d7d2c7f2_module_module.dir/nestml_2eb2d0739d344962b295d706d7d2c7f2_module.o\n", + "[ 50%] Building CXX object CMakeFiles/nestml_2eb2d0739d344962b295d706d7d2c7f2_module_module.dir/iaf_psc_delta_neuron_nestml.o\n", + "[ 75%] Building CXX object CMakeFiles/nestml_2eb2d0739d344962b295d706d7d2c7f2_module_module.dir/iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml.o\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml.cpp: In member function ‘void iaf_psc_delta_neuron_nestml::init_state_internal_()’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml.cpp:173:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 173 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " | ^~~~~~~~~~~~\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml.cpp: In member function ‘virtual void iaf_psc_delta_neuron_nestml::update(const nest::Time&, long int, long int)’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml.cpp:262:24: warning: comparison of integer expressions of different signedness: ‘long int’ and ‘const size_t’ {aka ‘const long unsigned int’} [-Wsign-compare]\n", + " 262 | for (long i = 0; i < NUM_SPIKE_RECEPTORS; ++i)\n", + " | ~~^~~~~~~~~~~~~~~~~~~~~\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml.cpp:257:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 257 | auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", + " | ^~~~~\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml.cpp: In member function ‘void iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml::init_state_internal_()’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml.cpp:183:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 183 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " | ^~~~~~~~~~~~\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml.cpp: In member function ‘virtual void iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml::update(const nest::Time&, long int, long int)’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml.cpp:283:24: warning: comparison of integer expressions of different signedness: ‘long int’ and ‘const size_t’ {aka ‘const long unsigned int’} [-Wsign-compare]\n", + " 283 | for (long i = 0; i < NUM_SPIKE_RECEPTORS; ++i)\n", + " | ~~^~~~~~~~~~~~~~~~~~~~~\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml.cpp:278:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 278 | auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", + " | ^~~~~\n", + "In file included from /home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/nestml_2eb2d0739d344962b295d706d7d2c7f2_module.cpp:36:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", + "/home/charl/julich/nest-simulator-install/include/nest/connector_model.h:164:25: required from ‘nest::GenericConnectorModel::GenericConnectorModel(std::string) [with ConnectionT = nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", + "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:62:5: required from ‘void nest::ModelManager::register_connection_model(const std::string&) [with ConnectionT = nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", + "/home/charl/julich/nest-simulator-install/include/nest/nest_impl.h:37:70: required from ‘void nest::register_connection_model(const std::string&) [with ConnectorModelT = stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:564:98: required from here\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:694:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 694 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " | ^~~~~~~~~~~~\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml::recompute_internal_variables() [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:708:3: required from ‘nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierPtrRport]’\n", + "/home/charl/julich/nest-simulator-install/include/nest/connector_model.h:164:25: required from ‘nest::GenericConnectorModel::GenericConnectorModel(std::string) [with ConnectionT = nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", + "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:62:5: required from ‘void nest::ModelManager::register_connection_model(const std::string&) [with ConnectionT = nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", + "/home/charl/julich/nest-simulator-install/include/nest/nest_impl.h:37:70: required from ‘void nest::register_connection_model(const std::string&) [with ConnectorModelT = stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:564:98: required from here\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:682:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 682 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " | ^~~~~~~~~~~~\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierIndex]’:\n", + "/home/charl/julich/nest-simulator-install/include/nest/connector_model.h:164:25: required from ‘nest::GenericConnectorModel::GenericConnectorModel(std::string) [with ConnectionT = nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", + "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:103:34: required from ‘void nest::ModelManager::register_specific_connection_model_(const std::string&) [with CompleteConnecionT = nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", + "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:67:80: required from ‘void nest::ModelManager::register_connection_model(const std::string&) [with ConnectionT = nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", + "/home/charl/julich/nest-simulator-install/include/nest/nest_impl.h:37:70: required from ‘void nest::register_connection_model(const std::string&) [with ConnectorModelT = stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:564:98: required from here\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:694:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 694 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " | ^~~~~~~~~~~~\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml::recompute_internal_variables() [with targetidentifierT = nest::TargetIdentifierIndex]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:708:3: required from ‘nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierIndex]’\n", + "/home/charl/julich/nest-simulator-install/include/nest/connector_model.h:164:25: required from ‘nest::GenericConnectorModel::GenericConnectorModel(std::string) [with ConnectionT = nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", + "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:103:34: required from ‘void nest::ModelManager::register_specific_connection_model_(const std::string&) [with CompleteConnecionT = nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", + "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:67:80: required from ‘void nest::ModelManager::register_connection_model(const std::string&) [with ConnectionT = nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", + "/home/charl/julich/nest-simulator-install/include/nest/nest_impl.h:37:70: required from ‘void nest::register_connection_model(const std::string&) [with ConnectorModelT = stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:564:98: required from here\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:682:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 682 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " | ^~~~~~~~~~~~\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘bool nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport; size_t = long unsigned int]’:\n", + "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:391:22: required from ‘void nest::Connector::send_to_all(size_t, const std::vector&, nest::Event&) [with ConnectionT = nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml; size_t = long unsigned int]’\n", + "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:383:3: required from here\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:483:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 483 | auto get_t = [_tr_t](){ return _tr_t; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + " | ^~~~~\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:507:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 507 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + " | ^~~~~\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:542:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 542 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + " | ^~~~~\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:416:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 416 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " | ^~~~~~~~~~~~\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:418:10: warning: variable ‘get_thread’ set but not used [-Wunused-but-set-variable]\n", + " 418 | auto get_thread = [tid]()\n", + " | ^~~~~~~~~~\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘bool nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex; size_t = long unsigned int]’:\n", + "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:391:22: required from ‘void nest::Connector::send_to_all(size_t, const std::vector&, nest::Event&) [with ConnectionT = nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml; size_t = long unsigned int]’\n", + "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:383:3: required from here\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:483:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 483 | auto get_t = [_tr_t](){ return _tr_t; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + " | ^~~~~\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:507:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 507 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + " | ^~~~~\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:542:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 542 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + " | ^~~~~\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:416:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 416 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " | ^~~~~~~~~~~~\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:418:10: warning: variable ‘get_thread’ set but not used [-Wunused-but-set-variable]\n", + " 418 | auto get_thread = [tid]()\n", + " | ^~~~~~~~~~\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml::update_internal_state_(double, double, const nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:478:9: required from ‘bool nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport; size_t = long unsigned int]’\n", + "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:391:22: required from ‘void nest::Connector::send_to_all(size_t, const std::vector&, nest::Event&) [with ConnectionT = nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml; size_t = long unsigned int]’\n", + "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:383:3: required from here\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:756:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 756 | const double __resolution = timestep; // do not remove, this is necessary for the resolution() function\n", + " | ^~~~~~~~~~~~\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:757:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 757 | auto get_t = [t_start](){ return t_start; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + " | ^~~~~\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml::update_internal_state_(double, double, const nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:478:9: required from ‘bool nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex; size_t = long unsigned int]’\n", + "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:391:22: required from ‘void nest::Connector::send_to_all(size_t, const std::vector&, nest::Event&) [with ConnectionT = nest::stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml; size_t = long unsigned int]’\n", + "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:383:3: required from here\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:756:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 756 | const double __resolution = timestep; // do not remove, this is necessary for the resolution() function\n", + " | ^~~~~~~~~~~~\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/stdp_windows/target/stdp_vogels_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:757:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 757 | auto get_t = [t_start](){ return t_start; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + " | ^~~~~\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[100%] Linking CXX shared module nestml_2eb2d0739d344962b295d706d7d2c7f2_module.so\n", + "[100%] Built target nestml_2eb2d0739d344962b295d706d7d2c7f2_module_module\n", + "[100%] Built target nestml_2eb2d0739d344962b295d706d7d2c7f2_module_module\n", + "Install the project...\n", + "-- Install configuration: \"\"\n", + "-- Installing: /tmp/nestml_target_mwbt6667/nestml_2eb2d0739d344962b295d706d7d2c7f2_module.so\n" + ] + } + ], + "source": [ + "module_name, neuron_model_name, synapse_model_name = \\\n", + " NESTCodeGeneratorUtils.generate_code_for(\"../../../models/neurons/iaf_psc_delta_neuron.nestml\",\n", + " nestml_stdp_vogels_model,\n", + " post_ports=[\"post_spikes\"],\n", + " codegen_opts={\"delay_variable\": {\"stdp_vogels_synapse\": \"d\"},\n", + " \"weight_variable\": {\"stdp_vogels_synapse\": \"w\"}})" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", + " model have been reset!\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:35 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", + " model have been reset!\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:23 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n" ] @@ -7000,250 +6165,154 @@ "output_type": "stream", "text": [ "\n", - "Oct 19 05:07:24 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:24 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:24 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:24 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:24 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:24 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:24 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:24 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:24 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:24 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:24 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:24 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:24 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:24 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:24 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:24 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:24 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:24 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:24 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:24 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:24 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:24 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:24 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:24 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Oct 19 05:07:24 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta484e294c98d344e8b3ee6c4b42d9261c_neuron_nestml__with_stdp484e294c98d344e8b3ee6c4b42d9261c_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta79a98d48ee834ca4914e80a2fa3e1cfb_neuron_nestml__with_stdp_windowed79a98d48ee834ca4914e80a2fa3e1cfb_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Oct 19 05:07:24 iaf_psc_delta913e0b5b31a0403a9a7bfc51a747debd_neuron_nestml__with_stdp_vogels913e0b5b31a0403a9a7bfc51a747debd_synapse_nestml [Warning]: \n", + "Apr 30 14:58:36 iaf_psc_delta_neuron_nestml__with_stdp_vogels_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n" ] }, { "data": { - "image/png": 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\n", + "image/png": 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\n", "text/plain": [ "
" ] @@ -7255,7 +6324,7 @@ "source": [ "dt_vec, dw_vec, delay = stdp_window(module_name, neuron_model_name,\n", " synapse_model_name,\n", - " synapse_parameters={\"offset\": .6})\n", + " synapse_parameters={\"offset\": .1})\n", "plot_stdp_window(dt_vec, dw_vec, delay)" ] }, diff --git a/doc/tutorials/triplet_stdp_synapse/triplet_stdp_synapse.ipynb b/doc/tutorials/triplet_stdp_synapse/triplet_stdp_synapse.ipynb index 792e15cdb..6168bb9b2 100644 --- a/doc/tutorials/triplet_stdp_synapse/triplet_stdp_synapse.ipynb +++ b/doc/tutorials/triplet_stdp_synapse/triplet_stdp_synapse.ipynb @@ -22,14 +22,6 @@ "id": "orange-zambia", "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/charl/.local/lib/python3.11/site-packages/matplotlib/projections/__init__.py:63: UserWarning: Unable to import Axes3D. This may be due to multiple versions of Matplotlib being installed (e.g. as a system package and as a pip package). As a result, the 3D projection is not available.\n", - " warnings.warn(\"Unable to import Axes3D. This may be due to multiple versions of \"\n" - ] - }, { "name": "stdout", "output_type": "stream", @@ -50,6 +42,14 @@ " Type 'nest.help()' to find out more about NEST.\n", "\n" ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/charl/.local/lib/python3.11/site-packages/matplotlib/projections/__init__.py:63: UserWarning: Unable to import Axes3D. This may be due to multiple versions of Matplotlib being installed (e.g. as a system package and as a pip package). As a result, the 3D projection is not available.\n", + " warnings.warn(\"Unable to import Axes3D. This may be due to multiple versions of \"\n" + ] } ], "source": [ @@ -190,7 +190,7 @@ " tr_o2 real = 0.\n", "\n", " parameters:\n", - " d ms = 1 ms @nest::delay\n", + " d ms = 1 ms\n", "\n", " tau_plus ms = 16.8 ms # time constant for tr_r1\n", " tau_x ms = 101 ms # time constant for tr_r2\n", @@ -254,12 +254,11 @@ "name": "stdout", "output_type": "stream", "text": [ - "Automatic pdb calling has been turned ON\n", "[1,GLOBAL, INFO]: List of files that will be processed:\n", - "[2,GLOBAL, INFO]: /home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/iaf_psc_delta_neuron.nestml\n", - "[3,GLOBAL, INFO]: /home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/stdp_triplet_synapse.nestml\n", - "[4,GLOBAL, INFO]: Target platform code will be generated in directory: '/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target'\n", - "[5,GLOBAL, INFO]: Target platform code will be installed in directory: '/tmp/nestml_target_yocmq5xi'\n", + "[2,GLOBAL, INFO]: /home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/iaf_psc_delta_neuron.nestml\n", + "[3,GLOBAL, INFO]: /home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/stdp_triplet_synapse.nestml\n", + "[4,GLOBAL, INFO]: Creating target directory: '/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target'\n", + "[5,GLOBAL, INFO]: Target platform code will be installed in directory: '/tmp/nestml_target_zo8wlcs5'\n", "\n", " -- N E S T --\n", " Copyright (C) 2004 The NEST Initiative\n", @@ -276,17 +275,17 @@ " Type 'nest.help()' to find out more about NEST.\n", "\n", "[6,GLOBAL, INFO]: The NEST Simulator version was automatically detected as: master\n", - "[7,GLOBAL, INFO]: Given template root path is not an absolute path. Creating the absolute path with default templates directory '/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/pynestml/codegeneration/resources_nest/point_neuron'\n", - "[8,GLOBAL, INFO]: Given template root path is not an absolute path. Creating the absolute path with default templates directory '/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/pynestml/codegeneration/resources_nest/point_neuron'\n", - "[9,GLOBAL, INFO]: Given template root path is not an absolute path. Creating the absolute path with default templates directory '/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/pynestml/codegeneration/resources_nest/point_neuron'\n", + "[7,GLOBAL, INFO]: Given template root path is not an absolute path. Creating the absolute path with default templates directory '/home/charl/julich/nestml-fork-nest-delay/nestml/pynestml/codegeneration/resources_nest/point_neuron'\n", + "[8,GLOBAL, INFO]: Given template root path is not an absolute path. Creating the absolute path with default templates directory '/home/charl/julich/nestml-fork-nest-delay/nestml/pynestml/codegeneration/resources_nest/point_neuron'\n", + "[9,GLOBAL, INFO]: Given template root path is not an absolute path. Creating the absolute path with default templates directory '/home/charl/julich/nestml-fork-nest-delay/nestml/pynestml/codegeneration/resources_nest/point_neuron'\n", "[10,GLOBAL, INFO]: The NEST Simulator installation path was automatically detected as: /home/charl/julich/nest-simulator-install\n", - "[11,GLOBAL, INFO]: Start processing '/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/iaf_psc_delta_neuron.nestml'!\n", + "[11,GLOBAL, INFO]: Start processing '/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/iaf_psc_delta_neuron.nestml'!\n", "[12,iaf_psc_delta_neuron_nestml, DEBUG, [43:0;94:0]]: Start building symbol table!\n", "[13,iaf_psc_delta_neuron_nestml, INFO, [51:79;51:79]]: Implicit magnitude conversion from pA to pA buffer with factor 1.0 \n", "[14,iaf_psc_delta_neuron_nestml, INFO, [51:15;51:74]]: Implicit magnitude conversion from mV / ms to pA / pF with factor 1.0 \n", - "[15,GLOBAL, INFO]: Start processing '/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/stdp_triplet_synapse.nestml'!\n", + "[15,GLOBAL, INFO]: Start processing '/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/stdp_triplet_synapse.nestml'!\n", "[16,stdp_triplet_synapse_nestml, DEBUG, [2:0;63:0]]: Start building symbol table!\n", - "[17,stdp_triplet_synapse_nestml, WARNING, [13:8;13:28]]: Variable 'd' has the same name as a physical unit!\n", + "[17,stdp_triplet_synapse_nestml, WARNING, [13:8;13:17]]: Variable 'd' has the same name as a physical unit!\n", "[18,stdp_triplet_synapse_nestml, INFO, [43:17;43:17]]: Implicit casting from (compatible) type 'integer' to 'real'.\n", "[19,stdp_triplet_synapse_nestml, INFO, [44:17;44:17]]: Implicit casting from (compatible) type 'integer' to 'real'.\n", "[20,stdp_triplet_synapse_nestml, WARNING, [47:16;47:16]]: Implicit casting from (compatible) type 'nS' to 'real'.\n", @@ -295,7 +294,7 @@ "[23,stdp_triplet_synapse_nestml, WARNING, [56:16;56:16]]: Implicit casting from (compatible) type 'nS' to 'real'.\n", "[24,iaf_psc_delta_neuron_nestml, DEBUG, [43:0;94:0]]: Start building symbol table!\n", "[25,stdp_triplet_synapse_nestml, DEBUG, [2:0;63:0]]: Start building symbol table!\n", - "[26,stdp_triplet_synapse_nestml, WARNING, [13:8;13:28]]: Variable 'd' has the same name as a physical unit!\n", + "[26,stdp_triplet_synapse_nestml, WARNING, [13:8;13:17]]: Variable 'd' has the same name as a physical unit!\n", "[27,stdp_triplet_synapse_nestml, INFO, [43:17;43:17]]: Implicit casting from (compatible) type 'integer' to 'real'.\n", "[28,stdp_triplet_synapse_nestml, INFO, [44:17;44:17]]: Implicit casting from (compatible) type 'integer' to 'real'.\n", "[29,stdp_triplet_synapse_nestml, INFO, [52:17;52:17]]: Implicit casting from (compatible) type 'integer' to 'real'.\n", @@ -304,7 +303,7 @@ "[32,iaf_psc_delta_neuron_nestml, INFO, [51:79;51:79]]: Implicit magnitude conversion from pA to pA buffer with factor 1.0 \n", "[33,iaf_psc_delta_neuron_nestml, INFO, [51:15;51:74]]: Implicit magnitude conversion from mV / ms to pA / pF with factor 1.0 \n", "[34,stdp_triplet_synapse_nestml, DEBUG, [2:0;63:0]]: Start building symbol table!\n", - "[35,stdp_triplet_synapse_nestml, WARNING, [13:8;13:28]]: Variable 'd' has the same name as a physical unit!\n", + "[35,stdp_triplet_synapse_nestml, WARNING, [13:8;13:17]]: Variable 'd' has the same name as a physical unit!\n", "[36,stdp_triplet_synapse_nestml, INFO, [43:17;43:17]]: Implicit casting from (compatible) type 'integer' to 'real'.\n", "[37,stdp_triplet_synapse_nestml, INFO, [44:17;44:17]]: Implicit casting from (compatible) type 'integer' to 'real'.\n", "[38,stdp_triplet_synapse_nestml, WARNING, [47:16;47:16]]: Implicit casting from (compatible) type 'nS' to 'real'.\n", @@ -312,7 +311,7 @@ "[40,stdp_triplet_synapse_nestml, INFO, [53:17;53:17]]: Implicit casting from (compatible) type 'integer' to 'real'.\n", "[41,stdp_triplet_synapse_nestml, WARNING, [56:16;56:16]]: Implicit casting from (compatible) type 'nS' to 'real'.\n", "[42,GLOBAL, INFO]: State variables that will be moved from synapse to neuron: ['tr_o1', 'tr_o2']\n", - "[43,GLOBAL, INFO]: Parameters that will be copied from synapse to neuron: ['tau_y', 'tau_minus']\n", + "[43,GLOBAL, INFO]: Parameters that will be copied from synapse to neuron: ['tau_minus', 'tau_y']\n", "[44,GLOBAL, INFO]: Moving state var defining equation(s) tr_o1\n", "[45,GLOBAL, INFO]: Moving state var defining equation(s) tr_o2\n", "[46,GLOBAL, INFO]: Moving state variables for equation(s) tr_o1\n", @@ -324,8 +323,8 @@ "[51,GLOBAL, INFO]: \tMoving statement tr_o2 += 1\n", "[52,GLOBAL, INFO]: In synapse: replacing ``continuous`` type input ports that are connected to postsynaptic neuron with suffixed external variable references\n", "[53,GLOBAL, INFO]: Copying parameters from synapse to neuron...\n", - "[54,GLOBAL, INFO]: Copying definition of tau_y from synapse to neuron\n", - "[55,GLOBAL, INFO]: Copying definition of tau_minus from synapse to neuron\n", + "[54,GLOBAL, INFO]: Copying definition of tau_minus from synapse to neuron\n", + "[55,GLOBAL, INFO]: Copying definition of tau_y from synapse to neuron\n", "[56,GLOBAL, INFO]: Adding suffix to variables in spike updates\n", "[57,GLOBAL, INFO]: In synapse: replacing variables with suffixed external variable references\n", "[58,GLOBAL, INFO]: \t• Replacing variable tr_o1\n", @@ -334,9 +333,7 @@ "[61,GLOBAL, INFO]: ASTSimpleExpression replacement made (var = tr_o2__for_stdp_triplet_synapse_nestml) in expression: A3_plus * tr_o2\n", "[62,iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml, DEBUG, [43:0;94:0]]: Start building symbol table!\n", "[63,stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml, DEBUG, [2:0;63:0]]: Start building symbol table!\n", - "[64,stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml, WARNING, [13:8;13:28]]: Variable 'd' has the same name as a physical unit!\n", - "[65,stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml, INFO, [52:17;52:17]]: Implicit casting from (compatible) type 'integer' to 'real'.\n", - "[66,stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml, INFO, [53:17;53:17]]: Implicit casting from (compatible) type 'integer' to 'real'.\n" + "[64,stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml, WARNING, [13:8;13:17]]: Variable 'd' has the same name as a physical unit!\n" ] }, { @@ -379,7 +376,7 @@ "DEBUG:Created Shape with symbol V_m, derivative_factors = [-1/tau_m], inhom_term = E_L/tau_m + I_e/C_m, nonlin_term = I_stim/C_m\n", "INFO:\tReturning shape: Shape \"V_m\" of order 1\n", "INFO:Shape V_m: reconstituting expression E_L/tau_m - V_m/tau_m + I_e/C_m + I_stim/C_m\n", - "INFO:All known variables: [V_m], all parameters used in ODEs: {I_stim, C_m, tau_m, I_e, E_L}\n", + "INFO:All known variables: [V_m], all parameters used in ODEs: {E_L, I_e, I_stim, C_m, tau_m}\n", "INFO:No numerical value specified for parameter \"I_stim\"\n", "INFO:\n", "Processing differential-equation form shape V_m with defining expression = \"(-(V_m - E_L)) / tau_m + 0 * (1.0 / 1.0) + (I_e + I_stim) / C_m\"\n", @@ -394,18 +391,35 @@ "DEBUG:\tlinear factors: Matrix([[-1/tau_m]])\n", "DEBUG:\tinhomogeneous term: E_L/tau_m + I_e/C_m + I_stim/C_m\n", "DEBUG:\tnonlinear term: 0.0\n", - "DEBUG:Initializing system of shapes with x = Matrix([[V_m]]), A = Matrix([[-1/tau_m]]), b = Matrix([[E_L/tau_m + I_e/C_m + I_stim/C_m]]), c = Matrix([[0.0]])\n", + "DEBUG:Initializing system of shapes with x = Matrix([[V_m]]), A = Matrix([[-1/tau_m]]), b = Matrix([[E_L/tau_m + I_e/C_m + I_stim/C_m]]), c = Matrix([[0]])\n", "INFO:Finding analytically solvable equations...\n", "INFO:Saving dependency graph plot to /tmp/ode_dependency_graph.dot\n", "DEBUG:os.makedirs('/tmp')\n", "DEBUG:write lines to '/tmp/ode_dependency_graph.dot'\n", - "DEBUG:run [PosixPath('dot'), '-Kdot', '-Tpdf', '-O', 'ode_dependency_graph.dot']\n" + "DEBUG:run [PosixPath('dot'), '-Kdot', '-Tpdf', '-O', 'ode_dependency_graph.dot']\n", + "INFO:Shape V_m: reconstituting expression E_L/tau_m - V_m/tau_m + I_e/C_m + I_stim/C_m\n", + "DEBUG:Splitting expression E_L/tau_m - V_m/tau_m + I_e/C_m + I_stim/C_m (symbols [V_m])\n", + "DEBUG:\tlinear factors: Matrix([[-1/tau_m]])\n", + "DEBUG:\tinhomogeneous term: E_L/tau_m + I_e/C_m + I_stim/C_m\n", + "DEBUG:\tnonlinear term: 0.0\n", + "INFO:Saving dependency graph plot to /tmp/ode_dependency_graph_analytically_solvable_before_propagated.dot\n", + "DEBUG:os.makedirs('/tmp')\n", + "DEBUG:write lines to '/tmp/ode_dependency_graph_analytically_solvable_before_propagated.dot'\n", + "DEBUG:run [PosixPath('dot'), '-Kdot', '-Tpdf', '-O', 'ode_dependency_graph_analytically_solvable_before_propagated.dot']\n", + "INFO:Saving dependency graph plot to /tmp/ode_dependency_graph_analytically_solvable.dot\n", + "DEBUG:os.makedirs('/tmp')\n", + "DEBUG:write lines to '/tmp/ode_dependency_graph_analytically_solvable.dot'\n", + "DEBUG:run [PosixPath('dot'), '-Kdot', '-Tpdf', '-O', 'ode_dependency_graph_analytically_solvable.dot']\n", + "INFO:Generating propagators for the following symbols: V_m\n", + "DEBUG:Initializing system of shapes with x = Matrix([[V_m]]), A = Matrix([[-1/tau_m]]), b = Matrix([[E_L/tau_m + I_e/C_m + I_stim/C_m]]), c = Matrix([[0]])\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ + "[65,stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml, INFO, [52:17;52:17]]: Implicit casting from (compatible) type 'integer' to 'real'.\n", + "[66,stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml, INFO, [53:17;53:17]]: Implicit casting from (compatible) type 'integer' to 'real'.\n", "[67,GLOBAL, INFO]: Successfully constructed neuron-synapse pair iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml, stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml\n", "[68,GLOBAL, INFO]: Analysing/transforming model 'iaf_psc_delta_neuron_nestml'\n", "[69,iaf_psc_delta_neuron_nestml, INFO, [43:0;94:0]]: Starts processing of the model 'iaf_psc_delta_neuron_nestml'\n" @@ -415,21 +429,6 @@ "name": "stderr", "output_type": "stream", "text": [ - "INFO:Shape V_m: reconstituting expression E_L/tau_m - V_m/tau_m + I_e/C_m + I_stim/C_m\n", - "DEBUG:Splitting expression E_L/tau_m - V_m/tau_m + I_e/C_m + I_stim/C_m (symbols [V_m])\n", - "DEBUG:\tlinear factors: Matrix([[-1/tau_m]])\n", - "DEBUG:\tinhomogeneous term: E_L/tau_m + I_e/C_m + I_stim/C_m\n", - "DEBUG:\tnonlinear term: 0.0\n", - "INFO:Saving dependency graph plot to /tmp/ode_dependency_graph_analytically_solvable_before_propagated.dot\n", - "DEBUG:os.makedirs('/tmp')\n", - "DEBUG:write lines to '/tmp/ode_dependency_graph_analytically_solvable_before_propagated.dot'\n", - "DEBUG:run [PosixPath('dot'), '-Kdot', '-Tpdf', '-O', 'ode_dependency_graph_analytically_solvable_before_propagated.dot']\n", - "INFO:Saving dependency graph plot to /tmp/ode_dependency_graph_analytically_solvable.dot\n", - "DEBUG:os.makedirs('/tmp')\n", - "DEBUG:write lines to '/tmp/ode_dependency_graph_analytically_solvable.dot'\n", - "DEBUG:run [PosixPath('dot'), '-Kdot', '-Tpdf', '-O', 'ode_dependency_graph_analytically_solvable.dot']\n", - "INFO:Generating propagators for the following symbols: V_m\n", - "DEBUG:Initializing system of shapes with x = Matrix([[V_m]]), A = Matrix([[-1/tau_m]]), b = Matrix([[E_L/tau_m + I_e/C_m + I_stim/C_m]]), c = Matrix([[0]])\n", "DEBUG:System of equations:\n", "DEBUG:x = Matrix([[V_m]])\n", "DEBUG:A = Matrix([[-1/tau_m]])\n", @@ -460,20 +459,7 @@ " \"V_m\": \"-E_L*__P__V_m__V_m + E_L + V_m*__P__V_m__V_m - I_e*__P__V_m__V_m*tau_m/C_m + I_e*tau_m/C_m - I_stim*__P__V_m__V_m*tau_m/C_m + I_stim*tau_m/C_m\"\n", " }\n", " }\n", - "]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[70,iaf_psc_delta_neuron_nestml, DEBUG, [43:0;94:0]]: Start building symbol table!\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ + "]\n", "INFO:Analysing input:\n", "INFO:{\n", " \"dynamics\": [\n", @@ -542,7 +528,7 @@ "DEBUG:Created Shape with symbol tr_o2__for_stdp_triplet_synapse_nestml, derivative_factors = [-1/tau_y__for_stdp_triplet_synapse_nestml], inhom_term = 0.0, nonlin_term = 0.0\n", "INFO:\tReturning shape: Shape \"tr_o2__for_stdp_triplet_synapse_nestml\" of order 1\n", "INFO:Shape tr_o2__for_stdp_triplet_synapse_nestml: reconstituting expression -tr_o2__for_stdp_triplet_synapse_nestml/tau_y__for_stdp_triplet_synapse_nestml\n", - "INFO:All known variables: [V_m, tr_o1__for_stdp_triplet_synapse_nestml, tr_o2__for_stdp_triplet_synapse_nestml], all parameters used in ODEs: {tau_y__for_stdp_triplet_synapse_nestml, I_stim, tau_m, E_L, C_m, tau_minus__for_stdp_triplet_synapse_nestml, I_e}\n", + "INFO:All known variables: [V_m, tr_o1__for_stdp_triplet_synapse_nestml, tr_o2__for_stdp_triplet_synapse_nestml], all parameters used in ODEs: {E_L, I_e, I_stim, tau_minus__for_stdp_triplet_synapse_nestml, tau_y__for_stdp_triplet_synapse_nestml, C_m, tau_m}\n", "INFO:No numerical value specified for parameter \"I_stim\"\n", "INFO:\n", "Processing differential-equation form shape V_m with defining expression = \"(-(V_m - E_L)) / tau_m + 0 * (1.0 / 1.0) + (I_e + I_stim) / C_m\"\n", @@ -572,23 +558,15 @@ "DEBUG:Splitting expression E_L/tau_m - V_m/tau_m + I_e/C_m + I_stim/C_m (symbols Matrix([[V_m], [tr_o1__for_stdp_triplet_synapse_nestml], [tr_o2__for_stdp_triplet_synapse_nestml]]))\n", "DEBUG:\tlinear factors: Matrix([[-1/tau_m], [0], [0]])\n", "DEBUG:\tinhomogeneous term: E_L/tau_m + I_e/C_m + I_stim/C_m\n", - "DEBUG:\tnonlinear term: 0.0\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[71,GLOBAL, INFO]: Analysing/transforming model 'iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml'\n", - "[72,iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml, INFO, [43:0;94:0]]: Starts processing of the model 'iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml'\n" + "DEBUG:\tnonlinear term: 0.0\n", + "INFO:Shape tr_o1__for_stdp_triplet_synapse_nestml: reconstituting expression -tr_o1__for_stdp_triplet_synapse_nestml/tau_minus__for_stdp_triplet_synapse_nestml\n", + "DEBUG:Splitting expression -tr_o1__for_stdp_triplet_synapse_nestml/tau_minus__for_stdp_triplet_synapse_nestml (symbols Matrix([[V_m], [tr_o1__for_stdp_triplet_synapse_nestml], [tr_o2__for_stdp_triplet_synapse_nestml]]))\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "INFO:Shape tr_o1__for_stdp_triplet_synapse_nestml: reconstituting expression -tr_o1__for_stdp_triplet_synapse_nestml/tau_minus__for_stdp_triplet_synapse_nestml\n", - "DEBUG:Splitting expression -tr_o1__for_stdp_triplet_synapse_nestml/tau_minus__for_stdp_triplet_synapse_nestml (symbols Matrix([[V_m], [tr_o1__for_stdp_triplet_synapse_nestml], [tr_o2__for_stdp_triplet_synapse_nestml]]))\n", "DEBUG:\tlinear factors: Matrix([[0], [-1/tau_minus__for_stdp_triplet_synapse_nestml], [0]])\n", "DEBUG:\tinhomogeneous term: 0.0\n", "DEBUG:\tnonlinear term: 0.0\n", @@ -597,7 +575,7 @@ "DEBUG:\tlinear factors: Matrix([[0], [0], [-1/tau_y__for_stdp_triplet_synapse_nestml]])\n", "DEBUG:\tinhomogeneous term: 0.0\n", "DEBUG:\tnonlinear term: 0.0\n", - "DEBUG:Initializing system of shapes with x = Matrix([[V_m], [tr_o1__for_stdp_triplet_synapse_nestml], [tr_o2__for_stdp_triplet_synapse_nestml]]), A = Matrix([[-1/tau_m, 0, 0], [0, -1/tau_minus__for_stdp_triplet_synapse_nestml, 0], [0, 0, -1/tau_y__for_stdp_triplet_synapse_nestml]]), b = Matrix([[E_L/tau_m + I_e/C_m + I_stim/C_m], [0.0], [0.0]]), c = Matrix([[0.0], [0.0], [0.0]])\n", + "DEBUG:Initializing system of shapes with x = Matrix([[V_m], [tr_o1__for_stdp_triplet_synapse_nestml], [tr_o2__for_stdp_triplet_synapse_nestml]]), A = Matrix([[-1/tau_m, 0, 0], [0, -1/tau_minus__for_stdp_triplet_synapse_nestml, 0], [0, 0, -1/tau_y__for_stdp_triplet_synapse_nestml]]), b = Matrix([[E_L/tau_m + I_e/C_m + I_stim/C_m], [0], [0]]), c = Matrix([[0], [0], [0]])\n", "INFO:Finding analytically solvable equations...\n", "INFO:Saving dependency graph plot to /tmp/ode_dependency_graph.dot\n", "DEBUG:os.makedirs('/tmp')\n", @@ -621,20 +599,35 @@ "INFO:Saving dependency graph plot to /tmp/ode_dependency_graph_analytically_solvable_before_propagated.dot\n", "DEBUG:os.makedirs('/tmp')\n", "DEBUG:write lines to '/tmp/ode_dependency_graph_analytically_solvable_before_propagated.dot'\n", - "DEBUG:run [PosixPath('dot'), '-Kdot', '-Tpdf', '-O', 'ode_dependency_graph_analytically_solvable_before_propagated.dot']\n", + "DEBUG:run [PosixPath('dot'), '-Kdot', '-Tpdf', '-O', 'ode_dependency_graph_analytically_solvable_before_propagated.dot']\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[70,iaf_psc_delta_neuron_nestml, DEBUG, [43:0;94:0]]: Start building symbol table!\n", + "[71,GLOBAL, INFO]: Analysing/transforming model 'iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml'\n", + "[72,iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml, INFO, [43:0;94:0]]: Starts processing of the model 'iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml'\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ "INFO:Saving dependency graph plot to /tmp/ode_dependency_graph_analytically_solvable.dot\n", "DEBUG:os.makedirs('/tmp')\n", "DEBUG:write lines to '/tmp/ode_dependency_graph_analytically_solvable.dot'\n", "DEBUG:run [PosixPath('dot'), '-Kdot', '-Tpdf', '-O', 'ode_dependency_graph_analytically_solvable.dot']\n", "INFO:Generating propagators for the following symbols: V_m, tr_o1__for_stdp_triplet_synapse_nestml, tr_o2__for_stdp_triplet_synapse_nestml\n", - "DEBUG:Initializing system of shapes with x = Matrix([[V_m], [tr_o1__for_stdp_triplet_synapse_nestml], [tr_o2__for_stdp_triplet_synapse_nestml]]), A = Matrix([[-1/tau_m, 0, 0], [0, -1/tau_minus__for_stdp_triplet_synapse_nestml, 0], [0, 0, -1/tau_y__for_stdp_triplet_synapse_nestml]]), b = Matrix([[E_L/tau_m + I_e/C_m + I_stim/C_m], [0.0], [0.0]]), c = Matrix([[0], [0], [0]])\n", + "DEBUG:Initializing system of shapes with x = Matrix([[V_m], [tr_o1__for_stdp_triplet_synapse_nestml], [tr_o2__for_stdp_triplet_synapse_nestml]]), A = Matrix([[-1/tau_m, 0, 0], [0, -1/tau_minus__for_stdp_triplet_synapse_nestml, 0], [0, 0, -1/tau_y__for_stdp_triplet_synapse_nestml]]), b = Matrix([[E_L/tau_m + I_e/C_m + I_stim/C_m], [0], [0]]), c = Matrix([[0], [0], [0]])\n", "DEBUG:System of equations:\n", "DEBUG:x = Matrix([[V_m], [tr_o1__for_stdp_triplet_synapse_nestml], [tr_o2__for_stdp_triplet_synapse_nestml]])\n", "DEBUG:A = Matrix([\n", "[-1/tau_m, 0, 0],\n", "[ 0, -1/tau_minus__for_stdp_triplet_synapse_nestml, 0],\n", "[ 0, 0, -1/tau_y__for_stdp_triplet_synapse_nestml]])\n", - "DEBUG:b = Matrix([[E_L/tau_m + I_e/C_m + I_stim/C_m], [0.0], [0.0]])\n", + "DEBUG:b = Matrix([[E_L/tau_m + I_e/C_m + I_stim/C_m], [0], [0]])\n", "DEBUG:c = Matrix([[0], [0], [0]])\n", "INFO:update_expr[V_m] = -E_L*__P__V_m__V_m + E_L + V_m*__P__V_m__V_m - I_e*__P__V_m__V_m*tau_m/C_m + I_e*tau_m/C_m - I_stim*__P__V_m__V_m*tau_m/C_m + I_stim*tau_m/C_m\n", "INFO:update_expr[tr_o1__for_stdp_triplet_synapse_nestml] = __P__tr_o1__for_stdp_triplet_synapse_nestml__tr_o1__for_stdp_triplet_synapse_nestml*tr_o1__for_stdp_triplet_synapse_nestml\n", @@ -675,20 +668,7 @@ " \"tr_o2__for_stdp_triplet_synapse_nestml\": \"__P__tr_o2__for_stdp_triplet_synapse_nestml__tr_o2__for_stdp_triplet_synapse_nestml*tr_o2__for_stdp_triplet_synapse_nestml\"\n", " }\n", " }\n", - "]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[73,iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml, DEBUG, [43:0;94:0]]: Start building symbol table!\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ + "]\n", "INFO:Analysing input:\n", "INFO:{\n", " \"dynamics\": [\n", @@ -742,7 +722,7 @@ "DEBUG:Created Shape with symbol tr_r2, derivative_factors = [-1/tau_x], inhom_term = 0.0, nonlin_term = 0.0\n", "INFO:\tReturning shape: Shape \"tr_r2\" of order 1\n", "INFO:Shape tr_r2: reconstituting expression -tr_r2/tau_x\n", - "INFO:All known variables: [tr_r1, tr_r2], all parameters used in ODEs: {tau_x, tau_plus}\n", + "INFO:All known variables: [tr_r1, tr_r2], all parameters used in ODEs: {tau_plus, tau_x}\n", "INFO:\n", "Processing differential-equation form shape tr_r1 with defining expression = \"(-tr_r1) / tau_plus\"\n", "DEBUG:Splitting expression -tr_r1/tau_plus (symbols [tr_r1, tr_r2, tr_r1])\n", @@ -769,18 +749,39 @@ "DEBUG:\tlinear factors: Matrix([[0], [-1/tau_x]])\n", "DEBUG:\tinhomogeneous term: 0.0\n", "DEBUG:\tnonlinear term: 0.0\n", - "DEBUG:Initializing system of shapes with x = Matrix([[tr_r1], [tr_r2]]), A = Matrix([[-1/tau_plus, 0], [0, -1/tau_x]]), b = Matrix([[0.0], [0.0]]), c = Matrix([[0.0], [0.0]])\n", + "DEBUG:Initializing system of shapes with x = Matrix([[tr_r1], [tr_r2]]), A = Matrix([[-1/tau_plus, 0], [0, -1/tau_x]]), b = Matrix([[0], [0]]), c = Matrix([[0], [0]])\n", "INFO:Finding analytically solvable equations...\n", "INFO:Saving dependency graph plot to /tmp/ode_dependency_graph.dot\n", "DEBUG:os.makedirs('/tmp')\n", "DEBUG:write lines to '/tmp/ode_dependency_graph.dot'\n", - "DEBUG:run [PosixPath('dot'), '-Kdot', '-Tpdf', '-O', 'ode_dependency_graph.dot']\n" + "DEBUG:run [PosixPath('dot'), '-Kdot', '-Tpdf', '-O', 'ode_dependency_graph.dot']\n", + "INFO:Shape tr_r1: reconstituting expression -tr_r1/tau_plus\n", + "DEBUG:Splitting expression -tr_r1/tau_plus (symbols [tr_r1, tr_r2])\n", + "DEBUG:\tlinear factors: Matrix([[-1/tau_plus], [0]])\n", + "DEBUG:\tinhomogeneous term: 0.0\n", + "DEBUG:\tnonlinear term: 0.0\n", + "INFO:Shape tr_r2: reconstituting expression -tr_r2/tau_x\n", + "DEBUG:Splitting expression -tr_r2/tau_x (symbols [tr_r1, tr_r2])\n", + "DEBUG:\tlinear factors: Matrix([[0], [-1/tau_x]])\n", + "DEBUG:\tinhomogeneous term: 0.0\n", + "DEBUG:\tnonlinear term: 0.0\n", + "INFO:Saving dependency graph plot to /tmp/ode_dependency_graph_analytically_solvable_before_propagated.dot\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "DEBUG:os.makedirs('/tmp')\n", + "DEBUG:write lines to '/tmp/ode_dependency_graph_analytically_solvable_before_propagated.dot'\n", + "DEBUG:run [PosixPath('dot'), '-Kdot', '-Tpdf', '-O', 'ode_dependency_graph_analytically_solvable_before_propagated.dot']\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ + "[73,iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml, DEBUG, [43:0;94:0]]: Start building symbol table!\n", "[74,GLOBAL, INFO]: Analysing/transforming synapse stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.\n", "[75,stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml, INFO, [2:0;63:0]]: Starts processing of the model 'stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml'\n" ] @@ -789,32 +790,18 @@ "name": "stderr", "output_type": "stream", "text": [ - "INFO:Shape tr_r1: reconstituting expression -tr_r1/tau_plus\n", - "DEBUG:Splitting expression -tr_r1/tau_plus (symbols [tr_r1, tr_r2])\n", - "DEBUG:\tlinear factors: Matrix([[-1/tau_plus], [0]])\n", - "DEBUG:\tinhomogeneous term: 0.0\n", - "DEBUG:\tnonlinear term: 0.0\n", - "INFO:Shape tr_r2: reconstituting expression -tr_r2/tau_x\n", - "DEBUG:Splitting expression -tr_r2/tau_x (symbols [tr_r1, tr_r2])\n", - "DEBUG:\tlinear factors: Matrix([[0], [-1/tau_x]])\n", - "DEBUG:\tinhomogeneous term: 0.0\n", - "DEBUG:\tnonlinear term: 0.0\n", - "INFO:Saving dependency graph plot to /tmp/ode_dependency_graph_analytically_solvable_before_propagated.dot\n", - "DEBUG:os.makedirs('/tmp')\n", - "DEBUG:write lines to '/tmp/ode_dependency_graph_analytically_solvable_before_propagated.dot'\n", - "DEBUG:run [PosixPath('dot'), '-Kdot', '-Tpdf', '-O', 'ode_dependency_graph_analytically_solvable_before_propagated.dot']\n", "INFO:Saving dependency graph plot to /tmp/ode_dependency_graph_analytically_solvable.dot\n", "DEBUG:os.makedirs('/tmp')\n", "DEBUG:write lines to '/tmp/ode_dependency_graph_analytically_solvable.dot'\n", "DEBUG:run [PosixPath('dot'), '-Kdot', '-Tpdf', '-O', 'ode_dependency_graph_analytically_solvable.dot']\n", "INFO:Generating propagators for the following symbols: tr_r1, tr_r2\n", - "DEBUG:Initializing system of shapes with x = Matrix([[tr_r1], [tr_r2]]), A = Matrix([[-1/tau_plus, 0], [0, -1/tau_x]]), b = Matrix([[0.0], [0.0]]), c = Matrix([[0], [0]])\n", + "DEBUG:Initializing system of shapes with x = Matrix([[tr_r1], [tr_r2]]), A = Matrix([[-1/tau_plus, 0], [0, -1/tau_x]]), b = Matrix([[0], [0]]), c = Matrix([[0], [0]])\n", "DEBUG:System of equations:\n", "DEBUG:x = Matrix([[tr_r1], [tr_r2]])\n", "DEBUG:A = Matrix([\n", "[-1/tau_plus, 0],\n", "[ 0, -1/tau_x]])\n", - "DEBUG:b = Matrix([[0.0], [0.0]])\n", + "DEBUG:b = Matrix([[0], [0]])\n", "DEBUG:c = Matrix([[0], [0]])\n", "INFO:update_expr[tr_r1] = __P__tr_r1__tr_r1*tr_r1\n", "INFO:update_expr[tr_r2] = __P__tr_r2__tr_r2*tr_r2\n", @@ -853,25 +840,25 @@ "output_type": "stream", "text": [ "[76,stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml, DEBUG, [2:0;63:0]]: Start building symbol table!\n", - "[77,stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml, WARNING, [13:8;13:28]]: Variable 'd' has the same name as a physical unit!\n", + "[77,stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml, WARNING, [13:8;13:17]]: Variable 'd' has the same name as a physical unit!\n", "[78,stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml, INFO, [52:17;52:17]]: Implicit casting from (compatible) type 'integer' to 'real'.\n", "[79,stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml, INFO, [53:17;53:17]]: Implicit casting from (compatible) type 'integer' to 'real'.\n", "[80,stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml, DEBUG, [2:0;63:0]]: Start building symbol table!\n", - "[81,stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml, WARNING, [13:8;13:28]]: Variable 'd' has the same name as a physical unit!\n", + "[81,stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml, WARNING, [13:8;13:17]]: Variable 'd' has the same name as a physical unit!\n", "[82,stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml, INFO, [52:17;52:17]]: Implicit casting from (compatible) type 'integer' to 'real'.\n", "[83,stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml, INFO, [53:17;53:17]]: Implicit casting from (compatible) type 'integer' to 'real'.\n", - "[84,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml.cpp\n", - "[85,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml.h\n", - "[86,iaf_psc_delta_neuron_nestml, INFO, [43:0;94:0]]: Successfully generated code for the model: 'iaf_psc_delta_neuron_nestml' in: '/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target' !\n", - "[87,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml.cpp\n", - "[88,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml.h\n", - "[89,iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml, INFO, [43:0;94:0]]: Successfully generated code for the model: 'iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml' in: '/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target' !\n", - "[90,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h\n", - "[91,stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml, INFO, [2:0;63:0]]: Successfully generated code for the model: 'stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml' in: '/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target' !\n", - "[92,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/nestml_3c70a8ed53be4c46854ae5b0aa248ab9_module.cpp\n", - "[93,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/nestml_3c70a8ed53be4c46854ae5b0aa248ab9_module.h\n", - "[94,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/CMakeLists.txt\n", - "[95,GLOBAL, INFO]: Successfully generated NEST module code in '/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target' !\n", + "[84,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml.cpp\n", + "[85,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml.h\n", + "[86,iaf_psc_delta_neuron_nestml, INFO, [43:0;94:0]]: Successfully generated code for the model: 'iaf_psc_delta_neuron_nestml' in: '/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target' !\n", + "[87,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml.cpp\n", + "[88,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml.h\n", + "[89,iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml, INFO, [43:0;94:0]]: Successfully generated code for the model: 'iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml' in: '/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target' !\n", + "[90,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h\n", + "[91,stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml, INFO, [2:0;63:0]]: Successfully generated code for the model: 'stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml' in: '/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target' !\n", + "[92,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/nestml_82fabdb7b0ca411190789324e0b5cb66_module.cpp\n", + "[93,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/nestml_82fabdb7b0ca411190789324e0b5cb66_module.h\n", + "[94,GLOBAL, INFO]: Rendering template /home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/CMakeLists.txt\n", + "[95,GLOBAL, INFO]: Successfully generated NEST module code in '/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target' !\n", "CMake Warning (dev) at CMakeLists.txt:95 (project):\n", " cmake_minimum_required() should be called prior to this top-level project()\n", " call. Please see the cmake-commands(7) manual for usage documentation of\n", @@ -886,7 +873,7 @@ "-- Detecting CXX compile features - done\n", "\n", "-------------------------------------------------------\n", - "nestml_3c70a8ed53be4c46854ae5b0aa248ab9_module Configuration Summary\n", + "nestml_82fabdb7b0ca411190789324e0b5cb66_module Configuration Summary\n", "-------------------------------------------------------\n", "\n", "C++ compiler : /usr/bin/c++\n", @@ -898,15 +885,15 @@ "\n", "-------------------------------------------------------\n", "\n", - "You can now build and install 'nestml_3c70a8ed53be4c46854ae5b0aa248ab9_module' using\n", + "You can now build and install 'nestml_82fabdb7b0ca411190789324e0b5cb66_module' using\n", " make\n", " make install\n", "\n", - "The library file libnestml_3c70a8ed53be4c46854ae5b0aa248ab9_module.so will be installed to\n", - " /tmp/nestml_target_yocmq5xi\n", + "The library file libnestml_82fabdb7b0ca411190789324e0b5cb66_module.so will be installed to\n", + " /tmp/nestml_target_zo8wlcs5\n", "The module can be loaded into NEST using\n", - " (nestml_3c70a8ed53be4c46854ae5b0aa248ab9_module) Install (in SLI)\n", - " nest.Install(nestml_3c70a8ed53be4c46854ae5b0aa248ab9_module) (in PyNEST)\n", + " (nestml_82fabdb7b0ca411190789324e0b5cb66_module) Install (in SLI)\n", + " nest.Install(nestml_82fabdb7b0ca411190789324e0b5cb66_module) (in PyNEST)\n", "\n", "CMake Warning (dev) in CMakeLists.txt:\n", " No cmake_minimum_required command is present. A line of code such as\n", @@ -918,194 +905,132 @@ " information run \"cmake --help-policy CMP0000\".\n", "This warning is for project developers. Use -Wno-dev to suppress it.\n", "\n", - "-- Configuring done (0.5s)\n", + "-- Configuring done (0.1s)\n", "-- Generating done (0.0s)\n", - "-- Build files have been written to: /home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target\n", - "[ 25%] Building CXX object CMakeFiles/nestml_3c70a8ed53be4c46854ae5b0aa248ab9_module_module.dir/nestml_3c70a8ed53be4c46854ae5b0aa248ab9_module.o\n", - "[ 50%] Building CXX object CMakeFiles/nestml_3c70a8ed53be4c46854ae5b0aa248ab9_module_module.dir/iaf_psc_delta_neuron_nestml.o\n", - "[ 75%] Building CXX object CMakeFiles/nestml_3c70a8ed53be4c46854ae5b0aa248ab9_module_module.dir/iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml.o\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml.cpp: In member function ‘void iaf_psc_delta_neuron_nestml::init_state_internal_()’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml.cpp:173:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 173 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + "-- Build files have been written to: /home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target\n", + "[ 25%] Building CXX object CMakeFiles/nestml_82fabdb7b0ca411190789324e0b5cb66_module_module.dir/nestml_82fabdb7b0ca411190789324e0b5cb66_module.o\n", + "[ 50%] Building CXX object CMakeFiles/nestml_82fabdb7b0ca411190789324e0b5cb66_module_module.dir/iaf_psc_delta_neuron_nestml.o\n", + "[ 75%] Building CXX object CMakeFiles/nestml_82fabdb7b0ca411190789324e0b5cb66_module_module.dir/iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml.o\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml.cpp: In member function ‘void iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml::init_state_internal_()’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml.cpp:188:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 188 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml.cpp: In member function ‘virtual void iaf_psc_delta_neuron_nestml::update(const nest::Time&, long int, long int)’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml.cpp:266:24: warning: comparison of integer expressions of different signedness: ‘long int’ and ‘const size_t’ {aka ‘const long unsigned int’} [-Wsign-compare]\n", - " 266 | for (long i = 0; i < NUM_SPIKE_RECEPTORS; ++i)\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml.cpp: In member function ‘virtual void iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml::update(const nest::Time&, long int, long int)’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml.cpp:293:24: warning: comparison of integer expressions of different signedness: ‘long int’ and ‘const size_t’ {aka ‘const long unsigned int’} [-Wsign-compare]\n", + " 293 | for (long i = 0; i < NUM_SPIKE_RECEPTORS; ++i)\n", " | ~~^~~~~~~~~~~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml.cpp:261:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 261 | auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml.cpp:288:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 288 | auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml.cpp: In member function ‘void iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml::init_state_internal_()’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml.cpp:188:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 188 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml.cpp: In member function ‘void iaf_psc_delta_neuron_nestml::init_state_internal_()’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml.cpp:173:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 173 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml.cpp: In member function ‘virtual void iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml::update(const nest::Time&, long int, long int)’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml.cpp:297:24: warning: comparison of integer expressions of different signedness: ‘long int’ and ‘const size_t’ {aka ‘const long unsigned int’} [-Wsign-compare]\n", - " 297 | for (long i = 0; i < NUM_SPIKE_RECEPTORS; ++i)\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml.cpp: In member function ‘virtual void iaf_psc_delta_neuron_nestml::update(const nest::Time&, long int, long int)’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml.cpp:262:24: warning: comparison of integer expressions of different signedness: ‘long int’ and ‘const size_t’ {aka ‘const long unsigned int’} [-Wsign-compare]\n", + " 262 | for (long i = 0; i < NUM_SPIKE_RECEPTORS; ++i)\n", " | ~~^~~~~~~~~~~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml.cpp:292:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 292 | auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", - " | ^~~~~\n", - "In file included from /home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/nestml_3c70a8ed53be4c46854ae5b0aa248ab9_module.cpp:36:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml.cpp:257:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 257 | auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", + " | ^~~~~\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "In file included from /home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/nestml_82fabdb7b0ca411190789324e0b5cb66_module.cpp:36:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_model.h:164:25: required from ‘nest::GenericConnectorModel::GenericConnectorModel(std::string) [with ConnectionT = nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:62:5: required from ‘void nest::ModelManager::register_connection_model(const std::string&) [with ConnectionT = nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/nest_impl.h:37:70: required from ‘void nest::register_connection_model(const std::string&) [with ConnectorModelT = stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:603:99: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:731:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 731 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:590:99: required from here\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:729:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 729 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml::recompute_internal_variables() [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:745:3: required from ‘nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierPtrRport]’\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml::recompute_internal_variables() [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:744:3: required from ‘nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierPtrRport]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_model.h:164:25: required from ‘nest::GenericConnectorModel::GenericConnectorModel(std::string) [with ConnectionT = nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:62:5: required from ‘void nest::ModelManager::register_connection_model(const std::string&) [with ConnectionT = nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/nest_impl.h:37:70: required from ‘void nest::register_connection_model(const std::string&) [with ConnectorModelT = stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:603:99: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:718:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 718 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:590:99: required from here\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:716:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 716 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierIndex]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierIndex]’:\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_model.h:164:25: required from ‘nest::GenericConnectorModel::GenericConnectorModel(std::string) [with ConnectionT = nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:103:34: required from ‘void nest::ModelManager::register_specific_connection_model_(const std::string&) [with CompleteConnecionT = nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:67:80: required from ‘void nest::ModelManager::register_connection_model(const std::string&) [with ConnectionT = nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/nest_impl.h:37:70: required from ‘void nest::register_connection_model(const std::string&) [with ConnectorModelT = stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:603:99: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:731:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 731 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:590:99: required from here\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:729:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 729 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml::recompute_internal_variables() [with targetidentifierT = nest::TargetIdentifierIndex]’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:745:3: required from ‘nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierIndex]’\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml::recompute_internal_variables() [with targetidentifierT = nest::TargetIdentifierIndex]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:744:3: required from ‘nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierIndex]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_model.h:164:25: required from ‘nest::GenericConnectorModel::GenericConnectorModel(std::string) [with ConnectionT = nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:103:34: required from ‘void nest::ModelManager::register_specific_connection_model_(const std::string&) [with CompleteConnecionT = nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:67:80: required from ‘void nest::ModelManager::register_connection_model(const std::string&) [with ConnectionT = nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/nest_impl.h:37:70: required from ‘void nest::register_connection_model(const std::string&) [with ConnectorModelT = stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:603:99: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:718:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 718 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:590:99: required from here\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:716:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 716 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘bool nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport; size_t = long unsigned int]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘bool nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport; size_t = long unsigned int]’:\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:391:22: required from ‘void nest::Connector::send_to_all(size_t, const std::vector&, nest::Event&) [with ConnectionT = nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:383:3: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:518:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 518 | auto get_t = [_tr_t](){ return _tr_t; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:505:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 505 | auto get_t = [_tr_t](){ return _tr_t; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:543:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 543 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:530:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 530 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:580:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 580 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:567:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 567 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:451:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 451 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:438:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 438 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:453:10: warning: variable ‘get_thread’ set but not used [-Wunused-but-set-variable]\n", - " 453 | auto get_thread = [tid]()\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:440:10: warning: variable ‘get_thread’ set but not used [-Wunused-but-set-variable]\n", + " 440 | auto get_thread = [tid]()\n", " | ^~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘bool nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex; size_t = long unsigned int]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘bool nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex; size_t = long unsigned int]’:\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:391:22: required from ‘void nest::Connector::send_to_all(size_t, const std::vector&, nest::Event&) [with ConnectionT = nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:383:3: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:518:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 518 | auto get_t = [_tr_t](){ return _tr_t; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:505:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 505 | auto get_t = [_tr_t](){ return _tr_t; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:543:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 543 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:530:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 530 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:580:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 580 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:567:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 567 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:451:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 451 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:438:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 438 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:453:10: warning: variable ‘get_thread’ set but not used [-Wunused-but-set-variable]\n", - " 453 | auto get_thread = [tid]()\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:440:10: warning: variable ‘get_thread’ set but not used [-Wunused-but-set-variable]\n", + " 440 | auto get_thread = [tid]()\n", " | ^~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml::update_internal_state_(double, double, const nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:513:9: required from ‘bool nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport; size_t = long unsigned int]’\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml::update_internal_state_(double, double, const nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:500:9: required from ‘bool nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:391:22: required from ‘void nest::Connector::send_to_all(size_t, const std::vector&, nest::Event&) [with ConnectionT = nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:383:3: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:799:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 799 | const double __resolution = timestep; // do not remove, this is necessary for the resolution() function\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:795:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 795 | const double __resolution = timestep; // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:800:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 800 | auto get_t = [t_start](){ return t_start; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:796:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 796 | auto get_t = [t_start](){ return t_start; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml::update_internal_state_(double, double, const nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex]’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:513:9: required from ‘bool nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex; size_t = long unsigned int]’\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml::update_internal_state_(double, double, const nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:500:9: required from ‘bool nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:391:22: required from ‘void nest::Connector::send_to_all(size_t, const std::vector&, nest::Event&) [with ConnectionT = nest::stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:383:3: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:799:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 799 | const double __resolution = timestep; // do not remove, this is necessary for the resolution() function\n", - " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:800:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 800 | auto get_t = [t_start](){ return t_start; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", - " | ^~~~~\n", - "[100%] Linking CXX shared module nestml_3c70a8ed53be4c46854ae5b0aa248ab9_module.so\n", - "[100%] Built target nestml_3c70a8ed53be4c46854ae5b0aa248ab9_module_module\n", - "[100%] Built target nestml_3c70a8ed53be4c46854ae5b0aa248ab9_module_module\n", - "Install the project...\n", - "-- Install configuration: \"\"\n", - "-- Installing: /tmp/nestml_target_yocmq5xi/nestml_3c70a8ed53be4c46854ae5b0aa248ab9_module.so\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_tripletb1d27d2bd4604585bbb6bb0e9e18dc93_synapse_nestml__with_iaf_psc_deltab1d27d2bd4604585bbb6bb0e9e18dc93_neuron_nestml.h: In instantiation of ‘void nest::stdp_tripletb1d27d2bd4604585bbb6bb0e9e18dc93_synapse_nestml__with_iaf_psc_deltab1d27d2bd4604585bbb6bb0e9e18dc93_neuron_nestml::send(nest::Event&, size_t, const nest::stdp_tripletb1d27d2bd4604585bbb6bb0e9e18dc93_synapse_nestml__with_iaf_psc_deltab1d27d2bd4604585bbb6bb0e9e18dc93_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport; size_t = long unsigned int]’:\n", - "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:381:22: required from ‘void nest::Connector::send_to_all(size_t, const std::vector&, nest::Event&) [with ConnectionT = nest::stdp_tripletb1d27d2bd4604585bbb6bb0e9e18dc93_synapse_nestml__with_iaf_psc_deltab1d27d2bd4604585bbb6bb0e9e18dc93_neuron_nestml; size_t = long unsigned int]’\n", - "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:373:3: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_tripletb1d27d2bd4604585bbb6bb0e9e18dc93_synapse_nestml__with_iaf_psc_deltab1d27d2bd4604585bbb6bb0e9e18dc93_neuron_nestml.h:517:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 517 | auto get_t = [_tr_t](){ return _tr_t; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", - " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_tripletb1d27d2bd4604585bbb6bb0e9e18dc93_synapse_nestml__with_iaf_psc_deltab1d27d2bd4604585bbb6bb0e9e18dc93_neuron_nestml.h:542:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 542 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", - " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_tripletb1d27d2bd4604585bbb6bb0e9e18dc93_synapse_nestml__with_iaf_psc_deltab1d27d2bd4604585bbb6bb0e9e18dc93_neuron_nestml.h:579:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 579 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", - " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_tripletb1d27d2bd4604585bbb6bb0e9e18dc93_synapse_nestml__with_iaf_psc_deltab1d27d2bd4604585bbb6bb0e9e18dc93_neuron_nestml.h:450:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 450 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:795:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 795 | const double __resolution = timestep; // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_tripletb1d27d2bd4604585bbb6bb0e9e18dc93_synapse_nestml__with_iaf_psc_deltab1d27d2bd4604585bbb6bb0e9e18dc93_neuron_nestml.h:452:10: warning: variable ‘get_thread’ set but not used [-Wunused-but-set-variable]\n", - " 452 | auto get_thread = [tid]()\n", - " | ^~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_tripletb1d27d2bd4604585bbb6bb0e9e18dc93_synapse_nestml__with_iaf_psc_deltab1d27d2bd4604585bbb6bb0e9e18dc93_neuron_nestml.h: In instantiation of ‘void nest::stdp_tripletb1d27d2bd4604585bbb6bb0e9e18dc93_synapse_nestml__with_iaf_psc_deltab1d27d2bd4604585bbb6bb0e9e18dc93_neuron_nestml::send(nest::Event&, size_t, const nest::stdp_tripletb1d27d2bd4604585bbb6bb0e9e18dc93_synapse_nestml__with_iaf_psc_deltab1d27d2bd4604585bbb6bb0e9e18dc93_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex; size_t = long unsigned int]’:\n", - "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:381:22: required from ‘void nest::Connector::send_to_all(size_t, const std::vector&, nest::Event&) [with ConnectionT = nest::stdp_tripletb1d27d2bd4604585bbb6bb0e9e18dc93_synapse_nestml__with_iaf_psc_deltab1d27d2bd4604585bbb6bb0e9e18dc93_neuron_nestml; size_t = long unsigned int]’\n", - "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:373:3: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_tripletb1d27d2bd4604585bbb6bb0e9e18dc93_synapse_nestml__with_iaf_psc_deltab1d27d2bd4604585bbb6bb0e9e18dc93_neuron_nestml.h:517:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 517 | auto get_t = [_tr_t](){ return _tr_t; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", - " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_tripletb1d27d2bd4604585bbb6bb0e9e18dc93_synapse_nestml__with_iaf_psc_deltab1d27d2bd4604585bbb6bb0e9e18dc93_neuron_nestml.h:542:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 542 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", - " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_tripletb1d27d2bd4604585bbb6bb0e9e18dc93_synapse_nestml__with_iaf_psc_deltab1d27d2bd4604585bbb6bb0e9e18dc93_neuron_nestml.h:579:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 579 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", - " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_tripletb1d27d2bd4604585bbb6bb0e9e18dc93_synapse_nestml__with_iaf_psc_deltab1d27d2bd4604585bbb6bb0e9e18dc93_neuron_nestml.h:450:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 450 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", - " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_tripletb1d27d2bd4604585bbb6bb0e9e18dc93_synapse_nestml__with_iaf_psc_deltab1d27d2bd4604585bbb6bb0e9e18dc93_neuron_nestml.h:452:10: warning: variable ‘get_thread’ set but not used [-Wunused-but-set-variable]\n", - " 452 | auto get_thread = [tid]()\n", - " | ^~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_tripletb1d27d2bd4604585bbb6bb0e9e18dc93_synapse_nestml__with_iaf_psc_deltab1d27d2bd4604585bbb6bb0e9e18dc93_neuron_nestml.h: In instantiation of ‘void nest::stdp_tripletb1d27d2bd4604585bbb6bb0e9e18dc93_synapse_nestml__with_iaf_psc_deltab1d27d2bd4604585bbb6bb0e9e18dc93_neuron_nestml::update_internal_state_(double, double, const nest::stdp_tripletb1d27d2bd4604585bbb6bb0e9e18dc93_synapse_nestml__with_iaf_psc_deltab1d27d2bd4604585bbb6bb0e9e18dc93_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_tripletb1d27d2bd4604585bbb6bb0e9e18dc93_synapse_nestml__with_iaf_psc_deltab1d27d2bd4604585bbb6bb0e9e18dc93_neuron_nestml.h:512:9: required from ‘void nest::stdp_tripletb1d27d2bd4604585bbb6bb0e9e18dc93_synapse_nestml__with_iaf_psc_deltab1d27d2bd4604585bbb6bb0e9e18dc93_neuron_nestml::send(nest::Event&, size_t, const nest::stdp_tripletb1d27d2bd4604585bbb6bb0e9e18dc93_synapse_nestml__with_iaf_psc_deltab1d27d2bd4604585bbb6bb0e9e18dc93_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport; size_t = long unsigned int]’\n", - "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:381:22: required from ‘void nest::Connector::send_to_all(size_t, const std::vector&, nest::Event&) [with ConnectionT = nest::stdp_tripletb1d27d2bd4604585bbb6bb0e9e18dc93_synapse_nestml__with_iaf_psc_deltab1d27d2bd4604585bbb6bb0e9e18dc93_neuron_nestml; size_t = long unsigned int]’\n", - "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:373:3: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_tripletb1d27d2bd4604585bbb6bb0e9e18dc93_synapse_nestml__with_iaf_psc_deltab1d27d2bd4604585bbb6bb0e9e18dc93_neuron_nestml.h:792:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 792 | const double __resolution = timestep; // do not remove, this is necessary for the resolution() function\n", - " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_tripletb1d27d2bd4604585bbb6bb0e9e18dc93_synapse_nestml__with_iaf_psc_deltab1d27d2bd4604585bbb6bb0e9e18dc93_neuron_nestml.h:793:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 793 | auto get_t = [t_start](){ return t_start; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", - " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_tripletb1d27d2bd4604585bbb6bb0e9e18dc93_synapse_nestml__with_iaf_psc_deltab1d27d2bd4604585bbb6bb0e9e18dc93_neuron_nestml.h: In instantiation of ‘void nest::stdp_tripletb1d27d2bd4604585bbb6bb0e9e18dc93_synapse_nestml__with_iaf_psc_deltab1d27d2bd4604585bbb6bb0e9e18dc93_neuron_nestml::update_internal_state_(double, double, const nest::stdp_tripletb1d27d2bd4604585bbb6bb0e9e18dc93_synapse_nestml__with_iaf_psc_deltab1d27d2bd4604585bbb6bb0e9e18dc93_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex]’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_tripletb1d27d2bd4604585bbb6bb0e9e18dc93_synapse_nestml__with_iaf_psc_deltab1d27d2bd4604585bbb6bb0e9e18dc93_neuron_nestml.h:512:9: required from ‘void nest::stdp_tripletb1d27d2bd4604585bbb6bb0e9e18dc93_synapse_nestml__with_iaf_psc_deltab1d27d2bd4604585bbb6bb0e9e18dc93_neuron_nestml::send(nest::Event&, size_t, const nest::stdp_tripletb1d27d2bd4604585bbb6bb0e9e18dc93_synapse_nestml__with_iaf_psc_deltab1d27d2bd4604585bbb6bb0e9e18dc93_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex; size_t = long unsigned int]’\n", - "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:381:22: required from ‘void nest::Connector::send_to_all(size_t, const std::vector&, nest::Event&) [with ConnectionT = nest::stdp_tripletb1d27d2bd4604585bbb6bb0e9e18dc93_synapse_nestml__with_iaf_psc_deltab1d27d2bd4604585bbb6bb0e9e18dc93_neuron_nestml; size_t = long unsigned int]’\n", - "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:373:3: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_tripletb1d27d2bd4604585bbb6bb0e9e18dc93_synapse_nestml__with_iaf_psc_deltab1d27d2bd4604585bbb6bb0e9e18dc93_neuron_nestml.h:792:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 792 | const double __resolution = timestep; // do not remove, this is necessary for the resolution() function\n", - " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_tripletb1d27d2bd4604585bbb6bb0e9e18dc93_synapse_nestml__with_iaf_psc_deltab1d27d2bd4604585bbb6bb0e9e18dc93_neuron_nestml.h:793:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 793 | auto get_t = [t_start](){ return t_start; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:796:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 796 | auto get_t = [t_start](){ return t_start; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", " | ^~~~~\n" ] }, @@ -1113,25 +1038,24 @@ "name": "stdout", "output_type": "stream", "text": [ - "[100%] Linking CXX shared module nestml_b1d27d2bd4604585bbb6bb0e9e18dc93_module.so\n", - "[100%] Built target nestml_b1d27d2bd4604585bbb6bb0e9e18dc93_module_module\n", - "[100%] Built target nestml_b1d27d2bd4604585bbb6bb0e9e18dc93_module_module\n", + "[100%] Linking CXX shared module nestml_82fabdb7b0ca411190789324e0b5cb66_module.so\n", + "[100%] Built target nestml_82fabdb7b0ca411190789324e0b5cb66_module_module\n", + "[100%] Built target nestml_82fabdb7b0ca411190789324e0b5cb66_module_module\n", "Install the project...\n", "-- Install configuration: \"\"\n", - "-- Installing: /home/charl/julich/nest-simulator-install/lib/nest/nestml_b1d27d2bd4604585bbb6bb0e9e18dc93_module.so\n", - "\n", - "Oct 19 05:01:52 Install [Info]: \n", - " loaded module nestml_b1d27d2bd4604585bbb6bb0e9e18dc93_module\n" + "-- Installing: /tmp/nestml_target_zo8wlcs5/nestml_82fabdb7b0ca411190789324e0b5cb66_module.so\n" ] } ], "source": [ - "%pdb \n", "# Generate code for All-to-All spike interaction\n", - "module_name, neuron_model_name, synapse_model_name = NESTCodeGeneratorUtils.generate_code_for(\"../../../models/neurons/iaf_psc_delta_neuron.nestml\",\n", - " nestml_triplet_stdp_model,\n", - " post_ports=[\"post_spikes\"],\n", - " logging_level=\"DEBUG\")" + "module_name, neuron_model_name, synapse_model_name = \\\n", + " NESTCodeGeneratorUtils.generate_code_for(\"../../../models/neurons/iaf_psc_delta_neuron.nestml\",\n", + " nestml_triplet_stdp_model,\n", + " post_ports=[\"post_spikes\"],\n", + " logging_level=\"DEBUG\",\n", + " codegen_opts={\"delay_variable\": {\"stdp_triplet_synapse\": \"d\"},\n", + " \"weight_variable\": {\"stdp_triplet_synapse\": \"w\"}})" ] }, { @@ -1170,7 +1094,7 @@ " tr_o2 real = 0.\n", "\n", " parameters:\n", - " d ms = 1 ms @nest::delay\n", + " d ms = 1 ms\n", "\n", " tau_plus ms = 16.8 ms # time constant for tr_r1\n", " tau_x ms = 101 ms # time constant for tr_r2\n", @@ -1251,21 +1175,33 @@ "\n", " Type 'nest.help()' to find out more about NEST.\n", "\n", - "[17,stdp_triplet_nn_synapse_nestml, WARNING, [13:8;13:28]]: Variable 'd' has the same name as a physical unit!\n", + "[17,stdp_triplet_nn_synapse_nestml, WARNING, [13:8;13:17]]: Variable 'd' has the same name as a physical unit!\n", "[20,stdp_triplet_nn_synapse_nestml, WARNING, [48:16;48:16]]: Implicit casting from (compatible) type 'nS' to 'real'.\n", "[23,stdp_triplet_nn_synapse_nestml, WARNING, [58:16;58:16]]: Implicit casting from (compatible) type 'nS' to 'real'.\n", - "[26,stdp_triplet_nn_synapse_nestml, WARNING, [13:8;13:28]]: Variable 'd' has the same name as a physical unit!\n", - "[35,stdp_triplet_nn_synapse_nestml, WARNING, [13:8;13:28]]: Variable 'd' has the same name as a physical unit!\n", + "[26,stdp_triplet_nn_synapse_nestml, WARNING, [13:8;13:17]]: Variable 'd' has the same name as a physical unit!\n", + "[35,stdp_triplet_nn_synapse_nestml, WARNING, [13:8;13:17]]: Variable 'd' has the same name as a physical unit!\n", "[38,stdp_triplet_nn_synapse_nestml, WARNING, [48:16;48:16]]: Implicit casting from (compatible) type 'nS' to 'real'.\n", - "[41,stdp_triplet_nn_synapse_nestml, WARNING, [58:16;58:16]]: Implicit casting from (compatible) type 'nS' to 'real'.\n", - "[64,stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml, WARNING, [13:8;13:28]]: Variable 'd' has the same name as a physical unit!\n" + "[41,stdp_triplet_nn_synapse_nestml, WARNING, [58:16;58:16]]: Implicit casting from (compatible) type 'nS' to 'real'.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:Not preserving expression for variable \"V_m\" as it is solved by propagator solver\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[64,stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml, WARNING, [13:8;13:17]]: Variable 'd' has the same name as a physical unit!\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "WARNING:Not preserving expression for variable \"V_m\" as it is solved by propagator solver\n", "WARNING:Not preserving expression for variable \"V_m\" as it is solved by propagator solver\n", "WARNING:Not preserving expression for variable \"tr_o1__for_stdp_triplet_nn_synapse_nestml\" as it is solved by propagator solver\n", "WARNING:Not preserving expression for variable \"tr_o2__for_stdp_triplet_nn_synapse_nestml\" as it is solved by propagator solver\n", @@ -1277,8 +1213,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "[77,stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml, WARNING, [13:8;13:28]]: Variable 'd' has the same name as a physical unit!\n", - "[81,stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml, WARNING, [13:8;13:28]]: Variable 'd' has the same name as a physical unit!\n", + "[77,stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml, WARNING, [13:8;13:17]]: Variable 'd' has the same name as a physical unit!\n", + "[81,stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml, WARNING, [13:8;13:17]]: Variable 'd' has the same name as a physical unit!\n", "CMake Warning (dev) at CMakeLists.txt:95 (project):\n", " cmake_minimum_required() should be called prior to this top-level project()\n", " call. Please see the cmake-commands(7) manual for usage documentation of\n", @@ -1293,7 +1229,7 @@ "-- Detecting CXX compile features - done\n", "\n", "-------------------------------------------------------\n", - "nestml_4940100b28f446be95429cd7b36f439e_module Configuration Summary\n", + "nestml_d21f76a04f014810b633adbbfabc1701_module Configuration Summary\n", "-------------------------------------------------------\n", "\n", "C++ compiler : /usr/bin/c++\n", @@ -1305,15 +1241,15 @@ "\n", "-------------------------------------------------------\n", "\n", - "You can now build and install 'nestml_4940100b28f446be95429cd7b36f439e_module' using\n", + "You can now build and install 'nestml_d21f76a04f014810b633adbbfabc1701_module' using\n", " make\n", " make install\n", "\n", - "The library file libnestml_4940100b28f446be95429cd7b36f439e_module.so will be installed to\n", - " /tmp/nestml_target_tz6lmulj\n", + "The library file libnestml_d21f76a04f014810b633adbbfabc1701_module.so will be installed to\n", + " /tmp/nestml_target_4f42fhl3\n", "The module can be loaded into NEST using\n", - " (nestml_4940100b28f446be95429cd7b36f439e_module) Install (in SLI)\n", - " nest.Install(nestml_4940100b28f446be95429cd7b36f439e_module) (in PyNEST)\n", + " (nestml_d21f76a04f014810b633adbbfabc1701_module) Install (in SLI)\n", + " nest.Install(nestml_d21f76a04f014810b633adbbfabc1701_module) (in PyNEST)\n", "\n", "CMake Warning (dev) in CMakeLists.txt:\n", " No cmake_minimum_required command is present. A line of code such as\n", @@ -1325,133 +1261,139 @@ " information run \"cmake --help-policy CMP0000\".\n", "This warning is for project developers. Use -Wno-dev to suppress it.\n", "\n", - "-- Configuring done (0.5s)\n", + "-- Configuring done (0.1s)\n", "-- Generating done (0.0s)\n", - "-- Build files have been written to: /home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target\n", - "[ 25%] Building CXX object CMakeFiles/nestml_4940100b28f446be95429cd7b36f439e_module_module.dir/nestml_4940100b28f446be95429cd7b36f439e_module.o\n", - "[ 50%] Building CXX object CMakeFiles/nestml_4940100b28f446be95429cd7b36f439e_module_module.dir/iaf_psc_delta_neuron_nestml.o\n", - "[ 75%] Building CXX object CMakeFiles/nestml_4940100b28f446be95429cd7b36f439e_module_module.dir/iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml.o\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml.cpp: In member function ‘void iaf_psc_delta_neuron_nestml::init_state_internal_()’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml.cpp:173:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + "-- Build files have been written to: /home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target\n", + "[ 25%] Building CXX object CMakeFiles/nestml_d21f76a04f014810b633adbbfabc1701_module_module.dir/nestml_d21f76a04f014810b633adbbfabc1701_module.o\n", + "[ 50%] Building CXX object CMakeFiles/nestml_d21f76a04f014810b633adbbfabc1701_module_module.dir/iaf_psc_delta_neuron_nestml.o\n", + "[ 75%] Building CXX object CMakeFiles/nestml_d21f76a04f014810b633adbbfabc1701_module_module.dir/iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml.o\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml.cpp: In member function ‘void iaf_psc_delta_neuron_nestml::init_state_internal_()’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml.cpp:173:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", " 173 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml.cpp: In member function ‘virtual void iaf_psc_delta_neuron_nestml::update(const nest::Time&, long int, long int)’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml.cpp:266:24: warning: comparison of integer expressions of different signedness: ‘long int’ and ‘const size_t’ {aka ‘const long unsigned int’} [-Wsign-compare]\n", - " 266 | for (long i = 0; i < NUM_SPIKE_RECEPTORS; ++i)\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml.cpp: In member function ‘virtual void iaf_psc_delta_neuron_nestml::update(const nest::Time&, long int, long int)’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml.cpp:262:24: warning: comparison of integer expressions of different signedness: ‘long int’ and ‘const size_t’ {aka ‘const long unsigned int’} [-Wsign-compare]\n", + " 262 | for (long i = 0; i < NUM_SPIKE_RECEPTORS; ++i)\n", " | ~~^~~~~~~~~~~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml.cpp:261:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 261 | auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml.cpp:257:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 257 | auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml.cpp: In member function ‘void iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml::init_state_internal_()’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml.cpp:188:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml.cpp: In member function ‘void iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml::init_state_internal_()’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml.cpp:188:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", " 188 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml.cpp: In member function ‘virtual void iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml::update(const nest::Time&, long int, long int)’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml.cpp:297:24: warning: comparison of integer expressions of different signedness: ‘long int’ and ‘const size_t’ {aka ‘const long unsigned int’} [-Wsign-compare]\n", - " 297 | for (long i = 0; i < NUM_SPIKE_RECEPTORS; ++i)\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml.cpp: In member function ‘virtual void iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml::update(const nest::Time&, long int, long int)’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml.cpp:293:24: warning: comparison of integer expressions of different signedness: ‘long int’ and ‘const size_t’ {aka ‘const long unsigned int’} [-Wsign-compare]\n", + " 293 | for (long i = 0; i < NUM_SPIKE_RECEPTORS; ++i)\n", " | ~~^~~~~~~~~~~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml.cpp:292:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 292 | auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml.cpp:288:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 288 | auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", " | ^~~~~\n", - "In file included from /home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/nestml_4940100b28f446be95429cd7b36f439e_module.cpp:36:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", + "In file included from /home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/nestml_d21f76a04f014810b633adbbfabc1701_module.cpp:36:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_model.h:164:25: required from ‘nest::GenericConnectorModel::GenericConnectorModel(std::string) [with ConnectionT = nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:62:5: required from ‘void nest::ModelManager::register_connection_model(const std::string&) [with ConnectionT = nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/nest_impl.h:37:70: required from ‘void nest::register_connection_model(const std::string&) [with ConnectorModelT = stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:603:102: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:731:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 731 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:590:102: required from here\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:729:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 729 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml::recompute_internal_variables() [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:745:3: required from ‘nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierPtrRport]’\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml::recompute_internal_variables() [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:744:3: required from ‘nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierPtrRport]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_model.h:164:25: required from ‘nest::GenericConnectorModel::GenericConnectorModel(std::string) [with ConnectionT = nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:62:5: required from ‘void nest::ModelManager::register_connection_model(const std::string&) [with ConnectionT = nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/nest_impl.h:37:70: required from ‘void nest::register_connection_model(const std::string&) [with ConnectorModelT = stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:603:102: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:718:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 718 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:590:102: required from here\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:716:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 716 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierIndex]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierIndex]’:\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_model.h:164:25: required from ‘nest::GenericConnectorModel::GenericConnectorModel(std::string) [with ConnectionT = nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:103:34: required from ‘void nest::ModelManager::register_specific_connection_model_(const std::string&) [with CompleteConnecionT = nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:67:80: required from ‘void nest::ModelManager::register_connection_model(const std::string&) [with ConnectionT = nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/nest_impl.h:37:70: required from ‘void nest::register_connection_model(const std::string&) [with ConnectorModelT = stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:603:102: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:731:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 731 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:590:102: required from here\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:729:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 729 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml::recompute_internal_variables() [with targetidentifierT = nest::TargetIdentifierIndex]’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:745:3: required from ‘nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierIndex]’\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml::recompute_internal_variables() [with targetidentifierT = nest::TargetIdentifierIndex]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:744:3: required from ‘nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml() [with targetidentifierT = nest::TargetIdentifierIndex]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_model.h:164:25: required from ‘nest::GenericConnectorModel::GenericConnectorModel(std::string) [with ConnectionT = nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:103:34: required from ‘void nest::ModelManager::register_specific_connection_model_(const std::string&) [with CompleteConnecionT = nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/model_manager_impl.h:67:80: required from ‘void nest::ModelManager::register_connection_model(const std::string&) [with ConnectionT = nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", "/home/charl/julich/nest-simulator-install/include/nest/nest_impl.h:37:70: required from ‘void nest::register_connection_model(const std::string&) [with ConnectorModelT = stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml; std::string = std::__cxx11::basic_string]’\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:603:102: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:718:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 718 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:590:102: required from here\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:716:16: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 716 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘bool nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport; size_t = long unsigned int]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘bool nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport; size_t = long unsigned int]’:\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:391:22: required from ‘void nest::Connector::send_to_all(size_t, const std::vector&, nest::Event&) [with ConnectionT = nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:383:3: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:518:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 518 | auto get_t = [_tr_t](){ return _tr_t; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:505:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 505 | auto get_t = [_tr_t](){ return _tr_t; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:543:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 543 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:530:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 530 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:580:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 580 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:567:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 567 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:451:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 451 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:438:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 438 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:453:10: warning: variable ‘get_thread’ set but not used [-Wunused-but-set-variable]\n", - " 453 | auto get_thread = [tid]()\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:440:10: warning: variable ‘get_thread’ set but not used [-Wunused-but-set-variable]\n", + " 440 | auto get_thread = [tid]()\n", " | ^~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘bool nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex; size_t = long unsigned int]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘bool nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex; size_t = long unsigned int]’:\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:391:22: required from ‘void nest::Connector::send_to_all(size_t, const std::vector&, nest::Event&) [with ConnectionT = nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:383:3: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:518:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 518 | auto get_t = [_tr_t](){ return _tr_t; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:505:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 505 | auto get_t = [_tr_t](){ return _tr_t; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:543:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 543 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:530:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 530 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:580:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 580 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:567:14: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 567 | auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:451:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 451 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:438:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 438 | const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:453:10: warning: variable ‘get_thread’ set but not used [-Wunused-but-set-variable]\n", - " 453 | auto get_thread = [tid]()\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:440:10: warning: variable ‘get_thread’ set but not used [-Wunused-but-set-variable]\n", + " 440 | auto get_thread = [tid]()\n", " | ^~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml::update_internal_state_(double, double, const nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:513:9: required from ‘bool nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport; size_t = long unsigned int]’\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml::update_internal_state_(double, double, const nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:500:9: required from ‘bool nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierPtrRport; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:391:22: required from ‘void nest::Connector::send_to_all(size_t, const std::vector&, nest::Event&) [with ConnectionT = nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:383:3: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:799:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 799 | const double __resolution = timestep; // do not remove, this is necessary for the resolution() function\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:795:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 795 | const double __resolution = timestep; // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:800:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 800 | auto get_t = [t_start](){ return t_start; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", - " | ^~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml::update_internal_state_(double, double, const nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex]’:\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:513:9: required from ‘bool nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex; size_t = long unsigned int]’\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:796:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 796 | auto get_t = [t_start](){ return t_start; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + " | ^~~~~\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h: In instantiation of ‘void nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml::update_internal_state_(double, double, const nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex]’:\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:500:9: required from ‘bool nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml::send(nest::Event&, size_t, const nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestmlCommonSynapseProperties&) [with targetidentifierT = nest::TargetIdentifierIndex; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:391:22: required from ‘void nest::Connector::send_to_all(size_t, const std::vector&, nest::Event&) [with ConnectionT = nest::stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml; size_t = long unsigned int]’\n", "/home/charl/julich/nest-simulator-install/include/nest/connector_base.h:383:3: required from here\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:799:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", - " 799 | const double __resolution = timestep; // do not remove, this is necessary for the resolution() function\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:795:18: warning: unused variable ‘__resolution’ [-Wunused-variable]\n", + " 795 | const double __resolution = timestep; // do not remove, this is necessary for the resolution() function\n", " | ^~~~~~~~~~~~\n", - "/home/charl/julich/nestml-fork-integrate_specific_odes/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:800:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", - " 800 | auto get_t = [t_start](){ return t_start; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + "/home/charl/julich/nestml-fork-nest-delay/nestml/doc/tutorials/triplet_stdp_synapse/target/stdp_triplet_nn_synapse_nestml__with_iaf_psc_delta_neuron_nestml.h:796:10: warning: variable ‘get_t’ set but not used [-Wunused-but-set-variable]\n", + " 796 | auto get_t = [t_start](){ return t_start; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", " | ^~~~~\n", - "[100%] Linking CXX shared module nestml_4940100b28f446be95429cd7b36f439e_module.so\n", - "[100%] Built target nestml_4940100b28f446be95429cd7b36f439e_module_module\n", - "[100%] Built target nestml_4940100b28f446be95429cd7b36f439e_module_module\n", + "[100%] Linking CXX shared module nestml_d21f76a04f014810b633adbbfabc1701_module.so\n", + "[100%] Built target nestml_d21f76a04f014810b633adbbfabc1701_module_module\n", + "[100%] Built target nestml_d21f76a04f014810b633adbbfabc1701_module_module\n", "Install the project...\n", "-- Install configuration: \"\"\n", - "-- Installing: /tmp/nestml_target_tz6lmulj/nestml_4940100b28f446be95429cd7b36f439e_module.so\n" + "-- Installing: /tmp/nestml_target_4f42fhl3/nestml_d21f76a04f014810b633adbbfabc1701_module.so\n" ] } ], @@ -1460,7 +1402,9 @@ "module_name_nn, neuron_model_name_nn, synapse_model_name_nn = \\\n", " NESTCodeGeneratorUtils.generate_code_for(\"../../../models/neurons/iaf_psc_delta_neuron.nestml\",\n", " nestml_triplet_stdp_nn_model,\n", - " post_ports=[\"post_spikes\"])" + " post_ports=[\"post_spikes\"],\n", + " codegen_opts={\"delay_variable\": {\"stdp_triplet_nn_synapse\": \"d\"},\n", + " \"weight_variable\": {\"stdp_triplet_nn_synapse\": \"w\"}})" ] }, { @@ -1674,437 +1618,443 @@ "name": "stdout", "output_type": "stream", "text": [ - "\n", - "Apr 19 12:03:37 Install [Info]: \n", - " loaded module nestml_3c70a8ed53be4c46854ae5b0aa248ab9_module\n", "Initial weight: 1.0, Updated weight: 1.000062712440608\n", "\n", - "Apr 19 12:03:37 correlation_detector [Info]: \n", + "Apr 30 14:28:10 Install [Info]: \n", + " loaded module nestml_82fabdb7b0ca411190789324e0b5cb66_module\n", + "\n", + "Apr 30 14:28:10 correlation_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:37 correlomatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlomatrix_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:37 correlospinmatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlospinmatrix_detector [Info]: \n", " Default for delta_tau changed from 0.1 to 1 ms\n", "\n", - "Apr 19 12:03:37 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:37 iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml [Warning]: \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:37 SimulationManager::set_status [Info]: \n", + "Apr 30 14:28:10 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 1 ms.\n", "\n", - "Apr 19 12:03:37 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:28:10 NodeManager::prepare_nodes [Info]: \n", " Preparing 6 nodes for simulation.\n", "\n", - "Apr 19 12:03:37 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:28:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 6\n", " Simulation time (ms): 59034\n", - " Number of OpenMP thInitial weight: 1.0, Updated weight: 1.045481723674705\n", - "reads: 1\n", + " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 12:03:37 SimulationManager::run [Info]: \n", + "Apr 30 14:28:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 12:03:37 Install [Info]: \n", - " loaded module nestml_3c70a8ed53be4c46854ae5b0aa248ab9_module\n", + "Apr 30 14:28:10 Install [Info]: \n", + " loaded module nestml_82fabdb7b0ca411190789324e0b5cb66_module\n", "\n", - "Apr 19 12:03:37 correlation_detector [Info]: \n", + "Apr 30 14:28:10 correlation_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:37 correlomatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlomatrix_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:37 correlospinmatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlospinmatrix_detector [Info]: \n", " Default for delta_tau changed from 0.1 to 1 ms\n", "\n", - "Apr 19 12:03:37 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:37 iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml [Warning]: \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:37 SimulationManager::set_status [Info]: \n", + "Apr 30 14:28:10 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 1 ms.\n", "\n", - "Apr 19 12:03:37 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:28:10 NodeManager::prepare_nodes [Info]: \n", " Preparing 6 nodes for simulation.\n", "\n", - "Apr 19 12:03:37 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:28:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 6\n", " Simulation time (ms): 11834\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 12:03:37 SimulationManager::run [Info]: \n", + "Apr 30 14:28:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", + "Initial weight: 1.0, Updated weight: 1.045481723674705\n", + "Initial weight: 1.0, Updated weight: 1.1180707933363045\n", "\n", - "Apr 19 12:03:37 Install [Info]: \n", - " loaded module nestml_3c70a8ed53be4c46854ae5b0aa248ab9_module\n", + "Apr 30 14:28:10 Install [Info]: \n", + " loaded module nestml_82fabdb7b0ca411190789324e0b5cb66_module\n", + "Initial weight: 1.0, Updated weight: 1.205329009261286\n", + "Initial weight: 1.0, Updated weight: 1.4186655196495506\n", + "Initial weight: 1.0, Updated weight: 1.5813821544865971\n", "\n", - "Apr 19 12:03:37 correlation_detector [Info]: \n", + "Apr 30 14:28:10 correlation_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:37 correlomatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlomatrix_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:37 correlospinmatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlospinmatrix_detector [Info]: \n", " Default for delta_tau changed from 0.1 to 1 ms\n", "\n", - "Apr 19 12:03:37 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:37 iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. InternaInitial weight: 1.0, Updated weight: 1.1180707933363045\n", - "l state and parameters of the \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml [Warning]: \n", + " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:37 SimulationManager::set_status [Info]: \n", + "Apr 30 14:28:10 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 1 ms.\n", "\n", - "Apr 19 12:03:37 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:28:10 NodeManager::prepare_nodes [Info]: \n", " Preparing 6 nodes for simulation.\n", "\n", - "Apr 19 12:03:37 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:28:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 6\n", " Simulation time (ms): 5934\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 12:03:37 SimulationManager::run [Info]: \n", + "Apr 30 14:28:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 12:03:37 Install [Info]: \n", - " loaded module nestml_3c70a8ed53be4c46854ae5b0aa248ab9_module\n", + "Apr 30 14:28:10 Install [Info]: \n", + " loaded module nestml_82fabdb7b0ca411190789324e0b5cb66_module\n", "\n", - "Apr 19 12:03:37 correlation_detector [Info]: \n", + "Apr 30 14:28:10 correlation_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:37 correlomatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlomatrix_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:37 correlospinmatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlospinmatrix_detector [Info]: \n", " Default for delta_tau changed from 0.1 to 1 ms\n", "\n", - "Apr 19 12:03:37 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:37 iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml [Warning]: \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:37 SimulationManager::set_status [Info]: \n", + "Apr 30 14:28:10 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 1 ms.\n", - "Initial weight: 1.0, Updated weight: 1.205329009261286\n", "\n", - "Apr 19 12:03:37 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:28:10 NodeManager::prepare_nodes [Info]: \n", " Preparing 6 nodes for simulation.\n", "\n", - "Apr 19 12:03:37 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:28:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 6\n", " Simulation time (ms): 2984\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 12:03:37 SimulationManager::run [Info]: \n", + "Apr 30 14:28:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 12:03:37 Install [Info]: \n", - " loaded module nestml_3c70a8ed53be4c46854ae5b0aa248ab9_module\n", + "Apr 30 14:28:10 Install [Info]: \n", + " loaded module nestml_82fabdb7b0ca411190789324e0b5cb66_module\n", "\n", - "Apr 19 12:03:37 correlation_detector [Info]: \n", + "Apr 30 14:28:10 correlation_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:37 correlomatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlomatrix_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:37 correlospinmatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlospinmatrix_detector [Info]: \n", " Default for delta_tau changed from 0.1 to 1 ms\n", "\n", - "Apr 19 12:03:37 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:37 iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml [Warning]: \n", - " SimulatInitial weight: 1.0, Updated weight: 1.4186655196495506\n", - "ion resolution has changed. Internal state and parameters of the \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml [Warning]: \n", + " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:37 SimulationManager::set_status [Info]: \n", + "Apr 30 14:28:10 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 1 ms.\n", "\n", - "Apr 19 12:03:37 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:28:10 NodeManager::prepare_nodes [Info]: \n", " Preparing 6 nodes for simulation.\n", "\n", - "Apr 19 12:03:37 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:28:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 6\n", " Simulation time (ms): 1509\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 12:03:37 SimulationManager::run [Info]: \n", + "Apr 30 14:28:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 12:03:37 Install [Info]: \n", - " loaded module nestml_3c70a8ed53be4c46854ae5b0aa248ab9_module\n", + "Apr 30 14:28:10 Install [Info]: \n", + " loaded module nestml_82fabdb7b0ca411190789324e0b5cb66_module\n", "\n", - "Apr 19 12:03:37 correlation_detector [Info]: \n", + "Apr 30 14:28:10 correlation_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:37 correlomatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlomatrix_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:37 correlospinmatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlospinmatrix_detector [Info]: \n", " Default for delta_tau changed from 0.1 to 1 ms\n", "\n", - "Apr 19 12:03:37 iaf_psc_delta_neuron_nestml [Warning]: \n", - " SimInitial weight: 1.0, Updated weight: 1.5813821544865971\n", - "ulation resolution has changed. Internal state and parameters of the \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml [Warning]: \n", + " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:37 iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml [Warning]: \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:37 SimulationManager::set_status [Info]: \n", + "Apr 30 14:28:10 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 1 ms.\n", "\n", - "Apr 19 12:03:37 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:28:10 NodeManager::prepare_nodes [Info]: \n", " Preparing 6 nodes for simulation.\n", "\n", - "Apr 19 12:03:37 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:28:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 6\n", " Simulation time (ms): 1214\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 12:03:37 SimulationManager::run [Info]: \n", + "Apr 30 14:28:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 12:03:37 Install [Info]: \n", - " loaded module nestml_3c70a8ed53be4c46854ae5b0aa248ab9_module\n", + "Apr 30 14:28:10 Install [Info]: \n", + " loaded module nestml_82fabdb7b0ca411190789324e0b5cb66_module\n", "\n", - "Apr 19 12:03:37 correlation_detector [Info]: \n", + "Apr 30 14:28:10 correlation_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:37 correlomatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlomatrix_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:37 correlospinmatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlospinmatrix_detector [Info]: \n", " Default for delta_tau changed from 0.1 to 1 ms\n", "\n", - "Apr 19 12:03:37 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:37 iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml [Warning]: \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:37 SimulationManager::set_status [Info]: \n", + "Apr 30 14:28:10 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 1 ms.\n", "\n", - "Apr 19 12:03:37 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:28:10 NodeManager::prepare_nodes [Info]: \n", " Preparing 6 nodes for simulation.\n", "\n", - "Apr 19 12:03:37 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:28:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 6\n", " Simulation time (ms): 59024\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 12:03:37 SimulationManager::run [Info]: \n", + "Apr 30 14:28:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "Initial weight: 1.0, Updated weight: 0.6678711978627694\n", + "Initial weight: 1.0, Updated weight: 0.6678711978627694\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Initial weight: 1.0, Updated weight: 0.6653426131462727\n", + "Initial weight: 1.0, Updated weight: 0.6450780469148971\n", + "Initial weight: 1.0, Updated weight: 0.6180411107607721\n", + "Initial weight: 1.0, Updated weight: 1.068737821702289\n", + "Initial weight: 1.0, Updated weight: 1.5937453662768748\n", "\n", - "Apr 19 12:03:37 Install [Info]: \n", - " loaded module nestml_3c70a8ed53be4c46854ae5b0aa248ab9_module\n", + "Apr 30 14:28:10 Install [Info]: \n", + " loaded module nestml_82fabdb7b0ca411190789324e0b5cb66_module\n", "\n", - "Apr 19 12:03:37 correlation_detector [Info]: \n", + "Apr 30 14:28:10 correlation_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:37 correlomatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlomatrix_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:37 correlospinmatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlospinmatrix_detector [Info]: \n", " Default for delta_tau changed from 0.1 to 1 ms\n", "\n", - "Apr 19 12:03:37 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:37 iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml [Warning]: \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:37 SimulationManager::set_status [Info]: \n", + "Apr 30 14:28:10 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 1 ms.\n", "\n", - "Apr 19 12:03:37 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:28:10 NodeManager::prepare_nodes [Info]: \n", " Preparing 6 nodes for simulation.\n", "\n", - "Apr 19 12:03:37 SimulationManager::start_updaInitial weight: 1.0, Updated weight: 0.6653426131462727\n", - "ting_ [Info]: \n", + "Apr 30 14:28:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 6\n", " Simulation time (ms): 11824\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 12:03:37 SimulationManager::run [Info]: \n", + "Apr 30 14:28:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 12:03:37 Install [Info]: \n", - " loaded module nestml_3c70a8ed53be4c46854ae5b0aa248ab9_module\n", + "Apr 30 14:28:10 Install [Info]: \n", + " loaded module nestml_82fabdb7b0ca411190789324e0b5cb66_module\n", "\n", - "Apr 19 12:03:37 correlation_detector [Info]: \n", + "Apr 30 14:28:10 correlation_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:37 correlomatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlomatrix_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:37 correlospinmatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlospinmatrix_detector [Info]: \n", " Default for delta_tau changed from 0.1 to 1 ms\n", "\n", - "Apr 19 12:03:37 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:37 iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml [Warning]: \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:37 SimulationManager::set_status [Info]: \n", + "Apr 30 14:28:10 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 1 ms.\n", - "Initial weight: 1.0, Updated weight: 0.6450780469148971\n", "\n", - "Apr 19 12:03:37 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:28:10 NodeManager::prepare_nodes [Info]: \n", " Preparing 6 nodes for simulation.\n", "\n", - "Apr 19 12:03:37 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:28:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 6\n", " Simulation time (ms): 5924\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 12:03:37 SimulationManager::run [Info]: \n", + "Apr 30 14:28:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 12:03:37 Install [Info]: \n", - " loaded module nestml_3c70a8ed53be4c46854ae5b0aa248ab9_module\n", + "Apr 30 14:28:10 Install [Info]: \n", + " loaded module nestml_82fabdb7b0ca411190789324e0b5cb66_module\n", "\n", - "Apr 19 12:03:37 correlation_detector [Info]: \n", + "Apr 30 14:28:10 correlation_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:37 correlomatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlomatrix_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:37 correlospinmatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlospinmatrix_detector [Info]: \n", " Default for delta_tau changed from 0.1 to 1 ms\n", "\n", - "Apr 19 12:03:37 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:37 iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml [Warning]: \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:37 SimulationManager::set_status [Info]: \n", + "Apr 30 14:28:10 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 1 ms.\n", - "Initial weight: 1.0, Updated weight: 0.6180411107607721\n", "\n", - "Apr 19 12:03:37 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:28:10 NodeManager::prepare_nodes [Info]: \n", " Preparing 6 nodes for simulation.\n", "\n", - "Apr 19 12:03:37 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:28:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 6\n", " Simulation time (ms): 2974\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 12:03:37 SimulationManager::run [Info]: \n", + "Apr 30 14:28:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 12:03:38 Install [Info]: \n", - " loaded module nestml_3c70a8ed53be4c46854ae5b0aa248ab9_module\n", + "Apr 30 14:28:10 Install [Info]: \n", + " loaded module nestml_82fabdb7b0ca411190789324e0b5cb66_module\n", "\n", - "Apr 19 12:03:38 correlation_detector [Info]: \n", + "Apr 30 14:28:10 correlation_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:38 correlomatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlomatrix_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:38 correlospinmatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlospinmatrix_detector [Info]: \n", " Default for delta_tau changed from 0.1 to 1 ms\n", "\n", - "Apr 19 12:03:38 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:38 iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml [Warning]: \n", - " SimulatInitial weight: 1.0, Updated weight: 1.068737821702289\n", - "ion resolution has changed. Internal state and parameters of the \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml [Warning]: \n", + " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:38 SimulationManager::set_status [Info]: \n", + "Apr 30 14:28:10 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 1 ms.\n", "\n", - "Apr 19 12:03:38 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:28:10 NodeManager::prepare_nodes [Info]: \n", " Preparing 6 nodes for simulation.\n", "\n", - "Apr 19 12:03:38 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:28:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 6\n", " Simulation time (ms): 1499\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 12:03:38 SimulationManager::run [Info]: \n", + "Apr 30 14:28:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 12:03:38 Install [Info]: \n", - " loaded module nestml_3c70a8ed53be4c46854ae5b0aa248ab9_module\n", + "Apr 30 14:28:10 Install [Info]: \n", + " loaded module nestml_82fabdb7b0ca411190789324e0b5cb66_module\n", "\n", - "Apr 19 12:03:38 correlation_detector [Info]: \n", + "Apr 30 14:28:10 correlation_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:38 correlomatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlomatrix_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:38 correlospinmatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlospinmatrix_detector [Info]: \n", " Default for delta_tau changed from 0.1 to 1 ms\n", "\n", - "Apr 19 12:03:38 iaf_psc_delta_neuron_nestml [Warning]: \n", - " SimInitial weight: 1.0, Updated weight: 1.5937453662768748\n", - "ulation resolution has changed. Internal state and parameters of the \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml [Warning]: \n", + " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:38 iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml [Warning]: \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:38 SimulationManager::set_status [Info]: \n", + "Apr 30 14:28:10 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 1 ms.\n", "\n", - "Apr 19 12:03:38 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:28:10 NodeManager::prepare_nodes [Info]: \n", " Preparing 6 nodes for simulation.\n", "\n", - "Apr 19 12:03:38 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:28:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 6\n", " Simulation time (ms): 1204\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 12:03:38 SimulationManager::run [Info]: \n", + "Apr 30 14:28:10 SimulationManager::run [Info]: \n", " Simulation finished.\n" ] } @@ -2157,436 +2107,436 @@ "output_type": "stream", "text": [ "\n", - "Apr 19 12:03:38 Install [Info]: \n", - " loaded module nestml_4940100b28f446be95429cd7b36f439e_module\n", - "Initial weight: 1.0, Updated weight: 1.0000000027196625\n", - "Initial weight: 1.0, Updated weight: 1.0086627050654013\n", + "Apr 30 14:28:10 Install [Info]: \n", + " loaded module nestml_d21f76a04f014810b633adbbfabc1701_module\n", "\n", - "Apr 19 12:03:38 correlation_detector [Info]: \n", + "Apr 30 14:28:10 correlation_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:38 correlomatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlomatrix_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:38 correlospinmatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlospinmatrix_detector [Info]: \n", " Default for delta_tau changed from 0.1 to 1 ms\n", "\n", - "Apr 19 12:03:38 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:38 iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml [Warning]: \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:38 SimulationManager::set_status [Info]: \n", + "Apr 30 14:28:10 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 1 ms.\n", "\n", - "Apr 19 12:03:38 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:28:10 NodeManager::prepare_nodes [Info]: \n", " Preparing 6 nodes for simulation.\n", "\n", - "Apr 19 12:03:38 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:28:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 6\n", " Simulation time (ms): 59034\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 12:03:38 SimulationManager::run [Info]: \n", + "Apr 30 14:28:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", + "Initial weight: 1.0, Updated weight: 1.0000000027196625\n", "\n", - "Apr 19 12:03:38 Install [Info]: \n", - " loaded module nestml_4940100b28f446be95429cd7b36f439e_module\n", + "Apr 30 14:28:10 Install [Info]: \n", + "Initial weight: 1.0, Updated weight: 1.0086627050654013\n", + "Initial weight: 1.0, Updated weight: 1.0903003652138468\n", + " loaded module nestml_d21f76a04f014810b633adbbfabc1701_module\n", "\n", - "Apr 19 12:03:38 correlation_detector [Info]: \n", + "Apr 30 14:28:10 correlation_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:38 correlomatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlomatrix_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:38 correlospinmatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlospinmatrix_detector [Info]: \n", " Default for delta_tau changed from 0.1 to 1 ms\n", "\n", - "Apr 19 12:03:38 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:38 iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml [Warning]: \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:38 SimulationManager::set_status [Info]: \n", + "Apr 30 14:28:10 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 1 ms.\n", "\n", - "Apr 19 12:03:38 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:28:10 NodeManager::prepare_nodes [Info]: \n", " Preparing 6 nodes for simulation.\n", "\n", - "Apr 19 12:03:38 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 6\n", + "Apr 30 14:28:10 SimulationManager::start_updating_ [Info]: \n", + " Number of loInitial weight: 1.0, Updated weight: 1.2776911537160713\n", + "Initial weight: 1.0, Updated weight: 1.4771400111243256\n", + "Initial weight: 1.0, Updated weight: 1.530550096954562\n", + "cal nodes: 6\n", " Simulation time (ms): 11834\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 12:03:38 SimulationManager::run [Info]: \n", + "Apr 30 14:28:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 12:03:38 Install [Info]: \n", - " loaded module nestml_4940100b28f446be95429cd7b36f439e_module\n", + "Apr 30 14:28:10 Install [Info]: \n", + " loaded module nestml_d21f76a04f014810b633adbbfabc1701_module\n", "\n", - "Apr 19 12:03:38 correlation_detector [Info]: \n", + "Apr 30 14:28:10 correlation_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:38 correlomatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlomatrix_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:38 correlospinmatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlospinmatrix_detector [Info]: \n", " Default for delta_tau changed from 0.1 to 1 ms\n", "\n", - "Apr 19 12:03:38 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:38 iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml [Warning]: \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:38 SimulationManager::set_status [Info]: \n", + "Apr 30 14:28:10 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 1 ms.\n", "\n", - "Apr 19 12:03:38 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:28:10 NodeManager::prepare_nodes [Info]: \n", " Preparing 6 nodes for simulation.\n", "\n", - "Apr 19 12:03:38 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:28:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 6\n", " Simulation time (ms): 5934\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 12:03:38 SimulationManager::run [Info]: \n", + "Apr 30 14:28:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "Initial weight: 1.0, Updated weight: 1.0903003652138468\n", "\n", - "Apr 19 12:03:38 Install [Info]: \n", - " loaded module nestml_4940100b28f446be95429cd7b36f439e_module\n", + "Apr 30 14:28:10 Install [Info]: \n", + " loaded module nestml_d21f76a04f014810b633adbbfabc1701_module\n", "\n", - "Apr 19 12:03:38 correlation_detector [Info]: \n", + "Apr 30 14:28:10 correlation_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:38 correlomatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlomatrix_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:38 correlospinmatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlospinmatrix_detector [Info]: \n", " Default for delta_tau changed from 0.1 to 1 ms\n", "\n", - "Apr 19 12:03:38 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:38 iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml [Warning]: \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:38 SimulationManager::set_status [Info]: \n", + "Apr 30 14:28:10 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 1 ms.\n", - "Initial weight: 1.0, Updated weight: 1.2776911537160713\n", "\n", - "Apr 19 12:03:38 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:28:10 NodeManager::prepare_nodes [Info]: \n", " Preparing 6 nodes for simulation.\n", "\n", - "Apr 19 12:03:38 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:28:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 6\n", " Simulation time (ms): 2984\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 12:03:38 SimulationManager::run [Info]: \n", + "Apr 30 14:28:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 12:03:38 Install [Info]: \n", - " loaded module nestml_4940100b28f446be95429cd7b36f439e_module\n", + "Apr 30 14:28:10 Install [Info]: \n", + " loaded module nestml_d21f76a04f014810b633adbbfabc1701_module\n", "\n", - "Apr 19 12:03:38 correlation_detector [Info]: \n", + "Apr 30 14:28:10 correlation_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:38 correlomatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlomatrix_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:38 correlospinmatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlospinmatrix_detector [Info]: \n", " Default for delta_tau changed from 0.1 to 1 ms\n", "\n", - "Apr 19 12:03:38 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:38 iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml [Warning]: \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:38 SimulationManager::set_status [Info]: \n", + "Apr 30 14:28:10 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 1 ms.\n", - "Initial weight: 1.0, Updated weight: 1.4771400111243256\n", "\n", - "Apr 19 12:03:38 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:28:10 NodeManager::prepare_nodes [Info]: \n", " Preparing 6 nodes for simulation.\n", "\n", - "Apr 19 12:03:38 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:28:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 6\n", " Simulation time (ms): 1509\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 12:03:38 SimulationManager::run [Info]: \n", + "Apr 30 14:28:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 12:03:38 Install [Info]: \n", - " loaded module nestml_4940100b28f446be95429cd7b36f439e_module\n", + "Apr 30 14:28:10 Install [Info]: \n", + " loaded module nestml_d21f76a04f014810b633adbbfabc1701_module\n", "\n", - "Apr 19 12:03:38 correlation_detector [Info]: \n", + "Apr 30 14:28:10 correlation_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:38 correlomatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlomatrInitial weight: 1.0, Updated weight: 0.554406040254968\n", + "ix_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:38 correlospinmatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlospinmatrix_detector [Info]: \n", " Default for delta_tau changed from 0.1 to 1 ms\n", "\n", - "Apr 19 12:03:38 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:38 iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml [Warning]: \n", - " SimuInitial weight: 1.0, Updated weight: 1.530550096954562\n", - "lation resolution has changed. Internal state and parameters of the \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml [Warning]: \n", + " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:38 SimulationManager::set_status [Info]: \n", + "Apr 30 14:28:10 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 1 ms.\n", "\n", - "Apr 19 12:03:38 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:28:10 NodeManager::prepare_nodes [Info]: \n", " Preparing 6 nodes for simulation.\n", "\n", - "Apr 19 12:03:38 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:28:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 6\n", " Simulation time (ms): 1214\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 12:03:38 SimulationManager::run [Info]: \n", + "Apr 30 14:28:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 12:03:38 Install [Info]: \n", - " loaded module nestml_4940100b28f446be95429cd7b36f439e_module\n", + "Apr 30 14:28:10 InstalInitial weight: 1.0, Updated weight: 0.5544062835543123\n", + "Initial weight: 1.0, Updated weight: 0.5555461935366892\n", + "Initial weight: 1.0, Updated weight: 0.632456315445355\n", + "Initial weight: 1.0, Updated weight: 1.2001792723059206\n", + "Initial weight: 1.0, Updated weight: 1.5398255566140917\n", + "l [Info]: \n", + " loaded module nestml_d21f76a04f014810b633adbbfabc1701_module\n", "\n", - "Apr 19 12:03:38 correlation_detector [Info]: \n", + "Apr 30 14:28:10 correlation_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:38 correlomatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlomatrix_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:38 correlospinmatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlospinmatrix_detector [Info]: \n", " Default for delta_tau changed from 0.1 to 1 ms\n", "\n", - "Apr 19 12:03:38 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:38 iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml [Warning]: \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:38 SimulationManager::set_status [Info]: \n", + "Apr 30 14:28:10 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 1 ms.\n", - "Initial weight: 1.0, Updated weight: 0.554406040254968\n", "\n", - "Apr 19 12:03:38 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:28:10 NodeManager::prepare_nodes [Info]: \n", " Preparing 6 nodes for simulation.\n", "\n", - "Apr 19 12:03:38 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:28:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 6\n", " Simulation time (ms): 59024\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 12:03:38 SimulationManager::run [Info]: \n", + "Apr 30 14:28:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 12:03:38 Install [Info]: \n", - " loaded module nestml_4940100b28f446be95429cd7b36f439e_module\n", + "Apr 30 14:28:10 Install [Info]: \n", + " loaded module nestml_d21f76a04f014810b633adbbfabc1701_module\n", "\n", - "Apr 19 12:03:38 correlation_detector [Info]: \n", + "Apr 30 14:28:10 correlation_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:38 correlomatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlomatrix_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:38 correlospinmatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlospinmatrix_detector [Info]: \n", " Default for delta_tau changed from 0.1 to 1 ms\n", "\n", - "Apr 19 12:03:38 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:38 iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml [Warning]: \n", - " SimInitial weight: 1.0, Updated weight: 0.5544062835543123\n", - "ulation resolution has changed. Internal state and parameters of the \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml [Warning]: \n", + " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:38 SimulationManager::set_status [Info]: \n", + "Apr 30 14:28:10 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 1 ms.\n", "\n", - "Apr 19 12:03:38 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:28:10 NodeManager::prepare_nodes [Info]: \n", " Preparing 6 nodes for simulation.\n", "\n", - "Apr 19 12:03:38 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:28:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 6\n", " Simulation time (ms): 11824\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 12:03:38 SimulationManager::run [Info]: \n", + "Apr 30 14:28:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 12:03:38 Install [Info]: \n", - " loaded module nestml_4940100b28f446be95429cd7b36f439e_module\n", + "Apr 30 14:28:10 Install [Info]: \n", + " loaded module nestml_d21f76a04f014810b633adbbfabc1701_module\n", "\n", - "Apr 19 12:03:38 correlation_detector [Info]: \n", + "Apr 30 14:28:10 correlation_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:38 correlomatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlomatrix_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:38 correlospinmatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlospinmatrix_detector [Info]: \n", " Default for delta_tau changed from 0.1 to 1 ms\n", "\n", - "Apr 19 12:03:38 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:38 iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml [Warning]: \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:38 SimulationManager::set_status [Info]: \n", + "Apr 30 14:28:10 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 1 ms.\n", - "Initial weight: 1.0, Updated weight: 0.5555461935366892\n", "\n", - "Apr 19 12:03:38 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:28:10 NodeManager::prepare_nodes [Info]: \n", " Preparing 6 nodes for simulation.\n", "\n", - "Apr 19 12:03:38 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:28:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 6\n", " Simulation time (ms): 5924\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 12:03:38 SimulationManager::run [Info]: \n", + "Apr 30 14:28:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 12:03:38 Install [Info]: \n", - " loaded module nestml_4940100b28f446be95429cd7b36f439e_module\n", + "Apr 30 14:28:10 Install [Info]: \n", + " loaded module nestml_d21f76a04f014810b633adbbfabc1701_module\n", "\n", - "Apr 19 12:03:38 correlation_detector [Info]: \n", + "Apr 30 14:28:10 correlation_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:38 correlomatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlomatrix_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:38 correlospinmatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlospinmatrix_detector [Info]: \n", " Default for delta_tau changed from 0.1 to 1 ms\n", "\n", - "Apr 19 12:03:38 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:38 iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml [Warning]: \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:38 SimulationManager::set_status [Info]: \n", + "Apr 30 14:28:10 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 1 ms.\n", - "Initial weight: 1.0, Updated weight: 0.632456315445355\n", "\n", - "Apr 19 12:03:38 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:28:10 NodeManager::prepare_nodes [Info]: \n", " Preparing 6 nodes for simulation.\n", "\n", - "Apr 19 12:03:38 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:28:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 6\n", " Simulation time (ms): 2974\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 12:03:38 SimulationManager::run [Info]: \n", + "Apr 30 14:28:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 12:03:38 Install [Info]: \n", - " loaded module nestml_4940100b28f446be95429cd7b36f439e_module\n", + "Apr 30 14:28:10 Install [Info]: \n", + " loaded module nestml_d21f76a04f014810b633adbbfabc1701_module\n", "\n", - "Apr 19 12:03:38 correlation_detector [Info]: \n", + "Apr 30 14:28:10 correlation_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:38 correlomatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlomatrix_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:38 correlospinmatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlospinmatrix_detector [Info]: \n", " Default for delta_tau changed from 0.1 to 1 ms\n", "\n", - "Apr 19 12:03:38 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:38 iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml [Warning]: \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:38 SimulationManager::set_status [Info]: \n", + "Apr 30 14:28:10 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 1 ms.\n", - "Initial weight: 1.0, Updated weight: 1.2001792723059206\n", "\n", - "Apr 19 12:03:38 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:28:10 NodeManager::prepare_nodes [Info]: \n", " Preparing 6 nodes for simulation.\n", "\n", - "Apr 19 12:03:38 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:28:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 6\n", " Simulation time (ms): 1499\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 12:03:38 SimulationManager::run [Info]: \n", + "Apr 30 14:28:10 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 12:03:38 Install [Info]: \n", - " loaded module nestml_4940100b28f446be95429cd7b36f439e_module\n", + "Apr 30 14:28:10 Install [Info]: \n", + " loaded module nestml_d21f76a04f014810b633adbbfabc1701_module\n", "\n", - "Apr 19 12:03:38 correlation_detector [Info]: \n", + "Apr 30 14:28:10 correlation_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:38 correlomatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlomatrix_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:38 correlospinmatrix_detector [Info]: \n", + "Apr 30 14:28:10 correlospinmatrix_detector [Info]: \n", " Default for delta_tau changed from 0.1 to 1 ms\n", "\n", - "Apr 19 12:03:38 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:38 iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml [Warning]: \n", + "Apr 30 14:28:10 iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:38 SimulationManager::set_status [Info]: \n", + "Apr 30 14:28:10 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 1 ms.\n", - "Initial weight: 1.0, Updated weight: 1.5398255566140917\n", "\n", - "Apr 19 12:03:38 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:28:10 NodeManager::prepare_nodes [Info]: \n", " Preparing 6 nodes for simulation.\n", "\n", - "Apr 19 12:03:38 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:28:10 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 6\n", " Simulation time (ms): 1204\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 12:03:38 SimulationManager::run [Info]: \n", + "Apr 30 14:28:10 SimulationManager::run [Info]: \n", " Simulation finished.\n" ] } @@ -2637,7 +2587,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 12, @@ -2918,300 +2868,300 @@ "output_type": "stream", "text": [ "Simulating for (delta_t1, delta_t2) = (5, -5)\n", - "\n", - "Apr 19 12:03:40 Install [Info]: \n", - " loaded module nestml_3c70a8ed53be4c46854ae5b0aa248ab9_module\n", "Initial weight: 1.0, Updated weight: 1.0003735276417982\n", "Simulating for (delta_t1, delta_t2) = (10, -10)\n", + "Initial weight: 1.0, Updated weight: 0.9998230228609227\n", + "Simulating for (delta_t1, delta_t2) = (15, -5)\n", + "Initial weight: 1.0, Updated weight: 0.9984719712644969\n", + "Simulating for (delta_t1, delta_t2) = (5, -15)\n", + "Initial weight: 1.0, Updated weight: 1.001383086591746\n", + "Simulating for (delta_t1, delta_t2) = (5, -5)\n", + "Initial weight: 1.0, Updated weight: 1.0005542494412774\n", + "Simulating for (delta_t1, delta_t2) = (10, -10)\n", + "Initial weight: 1.0, Updated weight: 1.0000931206450185\n", + "Simulating for (delta_t1, delta_t2) = (15, -5)\n", + "Initial weight: 1.0, Updated weight: 0.9991105337807658\n", + "Simulating for (delta_t1, delta_t2) = (5, -15)\n", + "Initial weight: 1.0, Updated weight: 1.0012383200640604\n", "\n", - "Apr 19 12:03:40 correlation_detector [Info]: \n", + "Apr 30 14:28:11 Install [Info]: \n", + " loaded module nestml_82fabdb7b0ca411190789324e0b5cb66_module\n", + "\n", + "Apr 30 14:28:11 correlation_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:40 correlomatrix_detector [Info]: \n", + "Apr 30 14:28:11 correlomatrix_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:40 correlospinmatrix_detector [Info]: \n", + "Apr 30 14:28:11 correlospinmatrix_detector [Info]: \n", " Default for delta_tau changed from 0.1 to 1 ms\n", "\n", - "Apr 19 12:03:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:28:11 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:40 iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml [Warning]: \n", + "Apr 30 14:28:11 iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:40 SimulationManager::set_status [Info]: \n", + "Apr 30 14:28:11 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 1 ms.\n", "\n", - "Apr 19 12:03:40 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:28:11 NodeManager::prepare_nodes [Info]: \n", " Preparing 6 nodes for simulation.\n", "\n", - "Apr 19 12:03:40 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:28:11 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 6\n", " Simulation time (ms): 24\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 12:03:40 SimulationManager::run [Info]: \n", + "Apr 30 14:28:11 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 12:03:40 Install [Info]: \n", - " loaded module nestml_3c70a8ed53be4c46854ae5b0aa248ab9_module\n", + "Apr 30 14:28:11 Install [Info]: \n", + " loaded module nestml_82fabdb7b0ca411190789324e0b5cb66_module\n", "\n", - "Apr 19 12:03:40 correlation_detector [Info]: \n", + "Apr 30 14:28:11 correlation_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:40 correlomatrix_detector [Info]: \n", + "Apr 30 14:28:11 correlomatrix_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:40 correlospinmatrix_detector [Info]: \n", + "Apr 30 14:28:11 correlospinmatrix_detector [Info]: \n", " Default for delta_tau changed from 0.1 to 1 ms\n", "\n", - "Apr 19 12:03:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:28:11 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:40 iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml [Warning]: \n", + "Apr 30 14:28:11 iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:40 SimulationManager::set_status [Info]: \n", + "Apr 30 14:28:11 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 1 ms.\n", - "Initial weight: 1.0, Updated weight: 0.9998230228609227\n", - "Simulating for (delta_t1, delta_t2) = (15, -5)\n", "\n", - "Apr 19 12:03:40 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:28:11 NodeManager::prepare_nodes [Info]: \n", " Preparing 6 nodes for simulation.\n", "\n", - "Apr 19 12:03:40 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:28:11 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 6\n", " Simulation time (ms): 34\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 12:03:40 SimulationManager::run [Info]: \n", + "Apr 30 14:28:11 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 12:03:40 Install [Info]: \n", - " loaded module nestml_3c70a8ed53be4c46854ae5b0aa248ab9_module\n", + "Apr 30 14:28:11 Install [Info]: \n", + " loaded module nestml_82fabdb7b0ca411190789324e0b5cb66_module\n", "\n", - "Apr 19 12:03:40 correlation_detector [Info]: \n", + "Apr 30 14:28:11 correlation_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:40 correlomatrix_detector [Info]: \n", + "Apr 30 14:28:11 correlomatrix_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:40 correlospinmatrix_detector [Info]: \n", + "Apr 30 14:28:11 correlospinmatrix_detector [Info]: \n", " Default for delta_tau changed from 0.1 to 1 ms\n", "\n", - "Apr 19 12:03:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:28:11 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:40 iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml [Warning]: \n", + "Apr 30 14:28:11 iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", - "Initial weight: 1.0, Updated weight: 0.9984719712644969\n", - "Simulating for (delta_t1, delta_t2) = (5, -15)\n", "\n", - "Apr 19 12:03:40 SimulationManager::set_status [Info]: \n", + "Apr 30 14:28:11 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 1 ms.\n", "\n", - "Apr 19 12:03:40 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:28:11 NodeManager::prepare_nodes [Info]: \n", " Preparing 6 nodes for simulation.\n", "\n", - "Apr 19 12:03:40 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:28:11 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 6\n", " Simulation time (ms): 34\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 12:03:40 SimulationManager::run [Info]: \n", + "Apr 30 14:28:11 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 12:03:40 Install [Info]: \n", - " loaded module nestml_3c70a8ed53be4c46854ae5b0aa248ab9_module\n", + "Apr 30 14:28:11 Install [Info]: \n", + " loaded module nestml_82fabdb7b0ca411190789324e0b5cb66_module\n", "\n", - "Apr 19 12:03:40 correlation_detector [Info]: \n", + "Apr 30 14:28:11 correlation_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:40 correlomatrix_detector [Info]: \n", + "Apr 30 14:28:11 correlomatrix_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:40 correlospinmatrix_detector [Info]: \n", + "Apr 30 14:28:11 correlospinmatrix_detector [Info]: \n", " Default for delta_tau changed from 0.1 to 1 ms\n", "\n", - "Apr 19 12:03:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:28:11 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been resetInitial weight: 1.0, Updated weight: 1.001383086591746\n", - "Simulating for (delta_t1, delta_t2) = (5, -5)\n", - "!\n", + " model have been reset!\n", "\n", - "Apr 19 12:03:40 iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml [Warning]: \n", + "Apr 30 14:28:11 iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:40 SimulationManager::set_status [Info]: \n", + "Apr 30 14:28:11 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 1 ms.\n", "\n", - "Apr 19 12:03:40 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:28:11 NodeManager::prepare_nodes [Info]: \n", " Preparing 6 nodes for simulation.\n", "\n", - "Apr 19 12:03:40 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:28:11 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 6\n", " Simulation time (ms): 34\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 12:03:40 SimulationManager::run [Info]: \n", + "Apr 30 14:28:11 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 12:03:40 Install [Info]: \n", - " loaded module nestml_4940100b28f446be95429cd7b36f439e_module\n", + "Apr 30 14:28:11 Install [Info]: \n", + " loaded module nestml_d21f76a04f014810b633adbbfabc1701_module\n", "\n", - "Apr 19 12:03:40 correlation_detector [Info]: \n", + "Apr 30 14:28:11 correlation_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:40 correlomatrix_detector [Info]: \n", + "Apr 30 14:28:11 correlomatrix_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:40 correlospinmatrix_detector [Info]: \n", - " Default fInitial weight: 1.0, Updated weight: 1.0005542494412774\n", - "or delta_tau changed from 0.1 to 1 ms\n", + "Apr 30 14:28:11 correlospinmatrix_detector [Info]: \n", + " Default for delta_tau changed from 0.1 to 1 ms\n", "\n", - "Apr 19 12:03:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:28:11 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:40 iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml [Warning]: \n", + "Apr 30 14:28:11 iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:40 SimulationManager::set_status [Info]: \n", + "Apr 30 14:28:11 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 1 ms.\n", "\n", - "Apr 19 12:03:40 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:28:11 NodeManager::prepare_nodes [Info]: \n", " Preparing 6 nodes for simulation.\n", "\n", - "Apr 19 12:03:40 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:28:11 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 6\n", " Simulation time (ms): 24\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 12:03:40 SimulationManager::run [Info]: \n", + "Apr 30 14:28:11 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "Simulating for (delta_t1, delta_t2) = (10, -10)\n", "\n", - "Apr 19 12:03:40 Install [Info]: \n", - " loaded module nestml_4940100b28f446be95429cd7b36f439e_module\n", + "Apr 30 14:28:11 Install [Info]: \n", + " loaded module nestml_d21f76a04f014810b633adbbfabc1701_module\n", "\n", - "Apr 19 12:03:40 correlation_detector [Info]: \n", + "Apr 30 14:28:11 correlation_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:40 correlomatrix_detector [Info]: \n", + "Apr 30 14:28:11 correlomatrix_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:40 correlospinmatrix_detector [Info]: \n", + "Apr 30 14:28:11 correlospinmatrix_detector [Info]: \n", " Default for delta_tau changed from 0.1 to 1 ms\n", "\n", - "Apr 19 12:03:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:28:11 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:40 iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml [Warning]: \n", + "Apr 30 14:28:11 iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:40 SimulationManager::set_status [Info]: \n", + "Apr 30 14:28:11 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 1 ms.\n", - "Initial weight: 1.0, Updated weight: 1.0000931206450185\n", - "Simulating for (delta_t1, delta_t2) = (15, -5)\n", "\n", - "Apr 19 12:03:40 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:28:11 NodeManager::prepare_nodes [Info]: \n", " Preparing 6 nodes for simulation.\n", "\n", - "Apr 19 12:03:40 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:28:11 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 6\n", " Simulation time (ms): 34\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", - "Initial weight: 1.0, Updated weight: 0.9991105337807658\n", - "Simulating for (delta_t1, delta_t2) = (5, -15)\n", "\n", - "Apr 19 12:03:40 SimulationManager::run [Info]: \n", + "Apr 30 14:28:11 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 12:03:40 Install [Info]: \n", - " loaded module nestml_4940100b28f446be95429cd7b36f439e_module\n", + "Apr 30 14:28:11 Install [Info]: \n", + " loaded module nestml_d21f76a04f014810b633adbbfabc1701_module\n", "\n", - "Apr 19 12:03:40 correlation_detector [Info]: \n", + "Apr 30 14:28:11 correlation_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:40 correlomatrix_detector [Info]: \n", + "Apr 30 14:28:11 correlomatrix_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:40 correlospinmatrix_detector [Info]: \n", + "Apr 30 14:28:11 correlospinmatrix_detector [Info]: \n", " Default for delta_tau changed from 0.1 to 1 ms\n", "\n", - "Apr 19 12:03:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:28:11 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:40 iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml [Warning]: \n", + "Apr 30 14:28:11 iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:40 SimulationManager::set_status [Info]: \n", + "Apr 30 14:28:11 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 1 ms.\n", "\n", - "Apr 19 12:03:40 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:28:11 NodeManager::prepare_nodes [Info]: \n", " Preparing 6 nodes for simulation.\n", "\n", - "Apr 19 12:03:40 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:28:11 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 6\n", " Simulation time (ms): 34\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 12:03:40 SimulationManager::run [Info]: \n", + "Apr 30 14:28:11 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 12:03:40 Install [Info]: \n", - " loaded module nestml_4940100b28f446be95429cd7b36f439e_module\n", + "Apr 30 14:28:11 Install [Info]: \n", + " loaded module nestml_d21f76a04f014810b633adbbfabc1701_module\n", "\n", - "Apr 19 12:03:40 correlation_detector [Info]: \n", + "Apr 30 14:28:11 correlation_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:40 correlomatrix_detector [Info]: \n", + "Apr 30 14:28:11 correlomatrix_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:40 correlospinmatrix_detector [Info]: \n", + "Apr 30 14:28:11 correlospinmatrix_detector [Info]: \n", " Default for delta_tau changed from 0.1 to 1 ms\n", "\n", - "Apr 19 12:03:40 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:28:11 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:40 iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml [Warning]: \n", + "Apr 30 14:28:11 iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:40 SimulationManager::set_status [Info]: \n", + "Apr 30 14:28:11 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 1 ms.\n", - "Initial weight: 1.0, Updated weight: 1.0012383200640604\n", "\n", - "Apr 19 12:03:40 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:28:11 NodeManager::prepare_nodes [Info]: \n", " Preparing 6 nodes for simulation.\n", "\n", - "Apr 19 12:03:40 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:28:11 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 6\n", " Simulation time (ms): 34\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 12:03:40 SimulationManager::run [Info]: \n", + "Apr 30 14:28:11 SimulationManager::run [Info]: \n", " Simulation finished.\n" ] } @@ -3286,299 +3236,299 @@ "text": [ "Simulating for (delta_t1, delta_t2) = (-5, 5)\n", "\n", - "Apr 19 12:03:41 Install [Info]: \n", - " loaded module nestml_3c70a8ed53be4c46854ae5b0aa248ab9_module\n", + "Apr 30 14:28:11 Install [Info]: \n", + " loaded module nestml_82fabdb7b0ca411190789324e0b5cb66_module\n", + "Initial weight: 1.0, Updated weight: 1.0452168105331474\n", + "Simulating for (delta_t1, delta_t2) = (-10, 10)\n", "\n", - "Apr 19 12:03:41 correlation_detector [Info]: \n", + "Apr 30 14:28:11 correlation_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:41 correlomatrix_detector [Info]: \n", + "Apr 30 14:28:11 correlomatrix_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:41 correlospinmatrix_detector [Info]: \n", + "Apr 30 14:28:11 correlospinmatrix_detector [Info]: \n", " Default for delta_tau changed from 0.1 to 1 ms\n", "\n", - "Apr 19 12:03:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:28:11 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:41 iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml [Warning]: \n", + "Apr 30 14:28:11 iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:41 SimulationManager::set_status [Info]: \n", + "Apr 30 14:28:11 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 1 ms.\n", - "Initial weight: 1.0, Updated weight: 1.0452168105331474\n", - "Simulating for (delta_t1, delta_t2) = (-10, 10)\n", "\n", - "Apr 19 12:03:41 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:28:11 NodeManager::prepare_nodes [Info]: \n", " Preparing 6 nodes for simulation.\n", "\n", - "Apr 19 12:03:41 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:28:11 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 6\n", " Simulation time (ms): 9114\n", - " Number of OpenMP threads: 1\n", + " Number of OpenMP thrInitial weight: 1.0, Updated weight: 1.0275785817728278\n", + "Simulating for (delta_t1, delta_t2) = (-5, 15)\n", + "Initial weight: 1.0, Updated weight: 1.008936270857372\n", + "eads: 1\n", " Not using MPI\n", "\n", - "Apr 19 12:03:41 SimulationManager::run [Info]: \n", + "Apr 30 14:28:11 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 12:03:41 Install [Info]: \n", - " loaded module nestml_3c70a8ed53be4c46854ae5b0aa248ab9_module\n", + "Apr 30 14:28:11 Install [Info]: \n", + " loaded module nestml_82fabdb7b0ca411190789324e0b5cb66_module\n", "\n", - "Apr 19 12:03:41 correlation_detector [Info]: \n", + "Apr 30 14:28:11 correlation_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:41 correlomatrix_detector [Info]: \n", + "Apr 30 14:28:11 correlomatrix_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:41 correlospinmatrix_detector [Info]: \n", + "Apr 30 14:28:11 correlospinmatrix_detector [Info]: \n", " Default for delta_tau changed from 0.1 to 1 ms\n", "\n", - "Apr 19 12:03:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:28:11 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:41 iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml [Warning]: \n", + "Apr 30 14:28:11 iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:41 SimulationManager::set_status [Info]: \n", + "Apr 30 14:28:11 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 1 ms.\n", "\n", - "Apr 19 12:03:41 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:28:11 NodeManager::prepareSimulating for (delta_t1, delta_t2) = (-15, 5)\n", + "Initial weight: 1.0, Updated weight: 1.050539844879153\n", + "Simulating for (delta_t1, delta_t2) = (-5, 5)\n", + "_nodes [Info]: \n", " Preparing 6 nodes for simulation.\n", "\n", - "Apr 19 12:03:41 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:28:11 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 6\n", " Simulation time (ms): 9214\n", - " Number of OpenMP thrInitial weight: 1.0, Updated weight: 1.0275785817728278\n", - "Simulating for (delta_t1, delta_t2) = (-5, 15)\n", - "eads: 1\n", + " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 12:03:41 SimulationManager::run [Info]: \n", + "Apr 30 14:28:11 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 12:03:41 Install [Info]: \n", - " loaded module nestml_3c70a8ed53be4c46854ae5b0aa248ab9_module\n", + "Apr 30 14:28:11 Install [Info]: \n", + " loaded module nestml_82fabdb7b0ca411190789324e0b5cb66_module\n", "\n", - "Apr 19 12:03:41 correlation_detector [Info]: \n", + "Apr 30 14:28:11 correlation_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:41 correlomatrix_detector [Info]: \n", + "Apr 30 14:28:11 correlomatrix_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:41 correlospinmatrix_detector [Info]: \n", + "Apr 30 14:28:11 correlospinmatrix_detector [Info]: \n", " Default for delta_tau changed from 0.1 to 1 ms\n", "\n", - "Apr 19 12:03:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:28:11 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:41 iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", + "Apr 30 14:28:11 iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml [Warning]: \n", + " Simulation resolution has changed. Internal Initial weight: 1.0, Updated weight: 1.048644757755009\n", + "Simulating for (delta_t1, delta_t2) = (-10, 10)\n", + "state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:41 SimulationManager::set_status [Info]: \n", + "Apr 30 14:28:11 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 1 ms.\n", "\n", - "Apr 19 12:03:41 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:28:11 NodeManager::prepare_nodes [Info]: \n", " Preparing 6 nodes for simulation.\n", "\n", - "Apr 19 12:03:41 SimulationManager::start_updaInitial weight: 1.0, Updated weight: 1.008936270857372\n", - "ting_ [Info]: \n", + "Apr 30 14:28:11 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 6\n", " Simulation time (ms): 9214\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 12:03:41 SimulationManager::run [Info]: \n", + "Apr 30 14:28:11 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "Simulating for (delta_t1, delta_t2) = (-15, 5)\n", "\n", - "Apr 19 12:03:41 Install [Info]: \n", - " loaded module nestml_3c70a8ed53be4c46854ae5b0aa248ab9_module\n", + "Apr 30 14:28:11 Install [Info]: \n", + " loaded module nestml_82fabdb7b0ca411190789324e0b5cb66_module\n", "\n", - "Apr 19 12:03:41 correlation_detector [Info]: \n", + "Apr 30 14:28:11 correlation_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:41 correlomatrix_detector [Info]: \n", + "Apr 30 14:28:11 correlomatrix_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:41 correlospinmatrix_detector [Info]: \n", + "Apr 30 14:28:11 correlospinmatrix_detector [Info]: \n", " Default for delta_tau changed from 0.1 to 1 ms\n", "\n", - "Apr 19 12:03:41 iaf_psc_delta_neuron_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", + "Apr 30 14:28:11 iaf_psc_delta_neuron_nestml [Warning]: \n", + " Simulation resolution has changed. InterInitial weight: 1.0, Updated weight: 1.026345906763637\n", + "Simulating for (delta_t1, delta_t2) = (-5, 15)\n", + "nal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:41 iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml [Warning]: \n", + "Apr 30 14:28:11 iaf_psc_delta_neuron_nestml__with_stdp_triplet_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:41 SimulationManager::set_status [Info]: \n", + "Apr 30 14:28:11 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 1 ms.\n", "\n", - "Apr 19 12:03:41 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:28:11 NodeManager::prepare_nodes [Info]: \n", " Preparing 6 nodes for simulation.\n", "\n", - "Apr 19 12:03:41 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:28:11 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 6\n", " Simulation time (ms): 9214\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 12:03:41 SimulationManager::run [Info]: \n", + "Apr 30 14:28:11 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "Initial weight: 1.0, Updated weight: 1.050539844879153\n", - "Simulating for (delta_t1, delta_t2) = (-5, 5)\n", "\n", - "Apr 19 12:03:41 Install [Info]: \n", - " loaded module nestml_4940100b28f446be95429cd7b36f439e_module\n", + "Apr 30 14:28:11 Install [Info]: \n", + " loaded module nestml_d21f76a04f014810b633adbbfabc1701_module\n", "\n", - "Apr 19 12:03:41 correlation_detector [Info]: \n", + "Apr 30 14:28:11 correlation_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:41 correlomatrix_detector [Info]: \n", + "Apr 30 14:28:11 correlomatrix_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:41 correlospinmatrix_detector [Info]: \n", + "Apr 3Initial weight: 1.0, Updated weight: 1.0099778920748412\n", + "0 14:28:11 correlospinmatrix_detector [Info]: \n", " Default for delta_tau changed from 0.1 to 1 ms\n", "\n", - "Apr 19 12:03:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:28:11 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:41 iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml [Warning]: \n", + "Apr 30 14:28:11 iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:41 SimulationManager::set_status [Info]: \n", + "Apr 30 14:28:11 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 1 ms.\n", "\n", - "Apr 19 12:03:41 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:28:11 NodeManager::prepare_nodes [Info]: \n", " Preparing 6 nodes for simulation.\n", "\n", - "Apr 19 12:03:41 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:28:11 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 6\n", " Simulation time (ms): 9114\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 12:03:41 SimulationManager::run [Info]: \n", + "Apr 30 14:28:11 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "Initial weight: 1.0, Updated weight: 1.048644757755009\n", - "Simulating for (delta_t1, delta_t2) = (-10, 10)\n", "\n", - "Apr 19 12:03:41 Install [Info]: \n", - " loaded module nestml_4940100b28f446be95429cd7b36f439e_module\n", + "Apr 30 14:28:11 Install [Info]: \n", + " loaded module nestml_d21f76a04f014810b633adbbfabc1701_module\n", "\n", - "Apr 19 12:03:41 correlation_detector [Info]: \n", + "Apr 30 14:28:11 correlation_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:41 correlomatrix_detector [Info]: \n", + "Apr 30 14:28:11 correlomatrix_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:41 correlospinmatrix_detector [Info]: \n", + "Apr 30 14:28:11 correlospinmatrix_detector [Info]: \n", " Default for delta_tau changed from 0.1 to 1 ms\n", "\n", - "Apr 19 12:03:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:28:11 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:41 iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml [Warning]: \n", + "Apr 30 14:28:11 iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:41 SimulationManager::set_status [Info]: \n", + "Apr 30 14:28:11 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 1 ms.\n", "\n", - "Apr 19 12:03:41 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:28:11 NodeManager::prepare_nodes [Info]: \n", " Preparing 6 nodes for simulation.\n", - "Initial weight: 1.0, Updated weight: 1.026345906763637\n", "\n", - "Apr 19 12:03:41 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:28:11 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 6\n", " Simulation time (ms): 9214\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 12:03:41 SimulationManager::run [Info]: \n", + "Apr 30 14:28:11 SimulationManager::run [Info]: \n", " Simulation finished.\n", - "Simulating for (delta_t1, delta_t2) = (-5, 15)\n", "\n", - "Apr 19 12:03:41 Install [Info]: \n", - " loaded module nestml_4940100b28f446be95429cd7b36f439e_module\n", + "Apr 30 14:28:11 Install [Info]: \n", + " loaded module nestml_d21f76a04f014810b633adbbfabc1701_module\n", "\n", - "Apr 19 12:03:41 correlation_detector [Info]: \n", + "Apr 30 14:28:11 correlation_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:41 correlomatrix_detector [Info]: \n", + "Apr 30 14:28:11 correlomatrix_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:41 correlospinmatrix_detector [Info]: \n", + "Apr 30 14:28:11 correlospinmatrix_detector [Info]: \n", " Default for delta_tau changed from 0.1 to 1 ms\n", "\n", - "Apr 19 12:03:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:28:11 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:41 iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml [Warning]: \n", + "Apr 30 14:28:11 iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:41 SimulationManager::set_status [Info]: \n", + "Apr 30 14:28:11 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 1 ms.\n", "\n", - "Apr 19 12:03:41 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:28:11 NodeManager::preSimulating for (delta_t1, delta_t2) = (-15, 5)\n", + "Initial weight: 1.0, Updated weight: 1.0466078732990223\n", + "pare_nodes [Info]: \n", " Preparing 6 nodes for simulation.\n", "\n", - "Apr 19 12:03:41 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:28:11 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 6\n", " Simulation time (ms): 9214\n", - " Number of OpenMP Initial weight: 1.0, Updated weight: 1.0099778920748412\n", - "Simulating for (delta_t1, delta_t2) = (-15, 5)\n", - "threads: 1\n", + " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 12:03:41 SimulationManager::run [Info]: \n", + "Apr 30 14:28:11 SimulationManager::run [Info]: \n", " Simulation finished.\n", "\n", - "Apr 19 12:03:41 Install [Info]: \n", - " loaded module nestml_4940100b28f446be95429cd7b36f439e_module\n", + "Apr 30 14:28:11 Install [Info]: \n", + " loaded module nestml_d21f76a04f014810b633adbbfabc1701_module\n", "\n", - "Apr 19 12:03:41 correlation_detector [Info]: \n", + "Apr 30 14:28:11 correlation_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:41 correlomatrix_detector [Info]: \n", + "Apr 30 14:28:11 correlomatrix_detector [Info]: \n", " Default for delta_tau changed from 0.5 to 5 ms\n", "\n", - "Apr 19 12:03:41 correlospinmatrix_detector [Info]: \n", + "Apr 30 14:28:11 correlospinmatrix_detector [Info]: \n", " Default for delta_tau changed from 0.1 to 1 ms\n", "\n", - "Apr 19 12:03:41 iaf_psc_delta_neuron_nestml [Warning]: \n", + "Apr 30 14:28:11 iaf_psc_delta_neuron_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:41 iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml [Warning]: \n", + "Apr 30 14:28:11 iaf_psc_delta_neuron_nestml__with_stdp_triplet_nn_synapse_nestml [Warning]: \n", " Simulation resolution has changed. Internal state and parameters of the \n", " model have been reset!\n", "\n", - "Apr 19 12:03:41 SimulationManager::set_status [Info]: \n", + "Apr 30 14:28:11 SimulationManager::set_status [Info]: \n", " Temporal resolution changed from 0.1 to 1 ms.\n", - "Initial weight: 1.0, Updated weight: 1.0466078732990223\n", "\n", - "Apr 19 12:03:41 NodeManager::prepare_nodes [Info]: \n", + "Apr 30 14:28:11 NodeManager::prepare_nodes [Info]: \n", " Preparing 6 nodes for simulation.\n", "\n", - "Apr 19 12:03:41 SimulationManager::start_updating_ [Info]: \n", + "Apr 30 14:28:11 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 6\n", " Simulation time (ms): 9214\n", " Number of OpenMP threads: 1\n", " Not using MPI\n", "\n", - "Apr 19 12:03:41 SimulationManager::run [Info]: \n", + "Apr 30 14:28:11 SimulationManager::run [Info]: \n", " Simulation finished.\n" ] } diff --git a/models/synapses/neuromodulated_stdp_synapse.nestml b/models/synapses/neuromodulated_stdp_synapse.nestml index 5747dd108..917678610 100644 --- a/models/synapses/neuromodulated_stdp_synapse.nestml +++ b/models/synapses/neuromodulated_stdp_synapse.nestml @@ -32,8 +32,8 @@ model neuromodulated_stdp_synapse: post_tr real = 0. parameters: - d ms = 1 ms @nest::delay # Synaptic transmission delay - tau_tr_pre ms = 20 ms # STDP time constant for weight changes caused by pre-before-post spike pairings. + d ms = 1 ms # Synaptic transmission delay + tau_tr_pre ms = 20 ms # STDP time constant for weight changes caused by pre-before-post spike pairings. tau_tr_post ms = 20 ms # STDP time constant for weight changes caused by post-before-pre spike pairings. tau_c ms = 1000 ms # Time constant of eligibility trace tau_n ms = 200 ms # Time constant of dopaminergic trace diff --git a/models/synapses/noisy_synapse.nestml b/models/synapses/noisy_synapse.nestml index b546d4a8c..8a1d0bbfa 100644 --- a/models/synapses/noisy_synapse.nestml +++ b/models/synapses/noisy_synapse.nestml @@ -9,8 +9,8 @@ Each presynaptic spike is passed to the postsynaptic partner with a weight sampl """ model noisy_synapse: parameters: - w real = 1 # Synaptic weight - d ms = 1 ms @nest::delay # Synaptic transmission delay + w real = 1 # Synaptic weight + d ms = 1 ms # Synaptic transmission delay A_noise real = .4 input: diff --git a/models/synapses/static_synapse.nestml b/models/synapses/static_synapse.nestml index 99e2bc499..097dcae6b 100644 --- a/models/synapses/static_synapse.nestml +++ b/models/synapses/static_synapse.nestml @@ -8,8 +8,8 @@ A synapse where the synaptic strength (weight) does not evolve with simulated ti """ model static_synapse: parameters: - w real = 1 @nest::weight # Synaptic weight - d ms = 1 ms @nest::delay # Synaptic transmission delay + w real = 1 # Synaptic weight + d ms = 1 ms # Synaptic transmission delay input: pre_spikes <- spike diff --git a/models/synapses/stdp_nn_pre_centered_synapse.nestml b/models/synapses/stdp_nn_pre_centered_synapse.nestml index 18dbb119e..2787d26ed 100644 --- a/models/synapses/stdp_nn_pre_centered_synapse.nestml +++ b/models/synapses/stdp_nn_pre_centered_synapse.nestml @@ -57,7 +57,7 @@ model stdp_nn_pre_centered_synapse: post_trace real = 0. parameters: - d ms = 1 ms @nest::delay # Synaptic transmission delay + d ms = 1 ms # Synaptic transmission delay lambda real = .01 tau_tr_pre ms = 20 ms tau_tr_post ms = 20 ms diff --git a/models/synapses/stdp_nn_restr_symm_synapse.nestml b/models/synapses/stdp_nn_restr_symm_synapse.nestml index 29fc38e12..86efefbff 100644 --- a/models/synapses/stdp_nn_restr_symm_synapse.nestml +++ b/models/synapses/stdp_nn_restr_symm_synapse.nestml @@ -50,7 +50,7 @@ model stdp_nn_restr_symm_synapse: pre_handled boolean = True parameters: - d ms = 1 ms @nest::delay # Synaptic transmission delay + d ms = 1 ms # Synaptic transmission delay lambda real = .01 tau_tr_pre ms = 20 ms tau_tr_post ms = 20 ms diff --git a/models/synapses/stdp_nn_symm_synapse.nestml b/models/synapses/stdp_nn_symm_synapse.nestml index aefcacbc8..22cb9d565 100644 --- a/models/synapses/stdp_nn_symm_synapse.nestml +++ b/models/synapses/stdp_nn_symm_synapse.nestml @@ -49,12 +49,12 @@ References """ model stdp_nn_symm_synapse: state: - w real = 1. # Synaptic weight + w real = 1 # Synaptic weight pre_trace real = 0. post_trace real = 0. parameters: - d ms = 1 ms @nest::delay # Synaptic transmission delay + d ms = 1 ms # Synaptic transmission delay lambda real = .01 tau_tr_pre ms = 20 ms tau_tr_post ms = 20 ms diff --git a/models/synapses/stdp_synapse.nestml b/models/synapses/stdp_synapse.nestml index ed637e27f..f04b4b971 100644 --- a/models/synapses/stdp_synapse.nestml +++ b/models/synapses/stdp_synapse.nestml @@ -35,12 +35,12 @@ References """ model stdp_synapse: state: - w real = 1. @nest::weight # Synaptic weight + w real = 1 # Synaptic weight pre_trace real = 0. post_trace real = 0. parameters: - d ms = 1 ms @nest::delay # Synaptic transmission delay + d ms = 1 ms # Synaptic transmission delay lambda real = .01 tau_tr_pre ms = 20 ms tau_tr_post ms = 20 ms diff --git a/models/synapses/stdp_triplet_synapse.nestml b/models/synapses/stdp_triplet_synapse.nestml index a0bf57a4c..063360db8 100644 --- a/models/synapses/stdp_triplet_synapse.nestml +++ b/models/synapses/stdp_triplet_synapse.nestml @@ -26,7 +26,7 @@ model stdp_triplet_synapse: tr_o2 real = 0. parameters: - d ms = 1 ms @nest::delay # Synaptic transmission delay + d ms = 1 ms # Synaptic transmission delay tau_plus ms = 16.8 ms # time constant for tr_r1 tau_x ms = 101 ms # time constant for tr_r2 diff --git a/models/synapses/third_factor_stdp_synapse.nestml b/models/synapses/third_factor_stdp_synapse.nestml index 6bff294e3..b049838ef 100644 --- a/models/synapses/third_factor_stdp_synapse.nestml +++ b/models/synapses/third_factor_stdp_synapse.nestml @@ -41,7 +41,7 @@ model third_factor_stdp_synapse: w real = 1. # Synaptic weight parameters: - d ms = 1 ms @nest::delay # Synaptic transmission delay + d ms = 1 ms # Synaptic transmission delay lambda real = .01 tau_tr_pre ms = 20 ms tau_tr_post ms = 20 ms diff --git a/pynestml/cocos/co_co_all_variables_defined.py b/pynestml/cocos/co_co_all_variables_defined.py index a02adace2..e41b0727e 100644 --- a/pynestml/cocos/co_co_all_variables_defined.py +++ b/pynestml/cocos/co_co_all_variables_defined.py @@ -96,7 +96,7 @@ def check_co_co(cls, node: ASTModel, after_ast_rewrite: bool = False): code, message = Messages.get_variable_not_defined(var.get_complete_name()) Logger.log_message(code=code, message=message, error_position=node.get_source_position(), log_level=LoggingLevel.ERROR, node=node) - return + continue # check if it is part of an invariant # if it is the case, there is no "recursive" declaration diff --git a/pynestml/cocos/co_co_nest_delay_decorator_specified.py b/pynestml/cocos/co_co_nest_delay_decorator_specified.py deleted file mode 100644 index 487532fb0..000000000 --- a/pynestml/cocos/co_co_nest_delay_decorator_specified.py +++ /dev/null @@ -1,49 +0,0 @@ -# -*- coding: utf-8 -*- -# -# co_co_nest_delay_decorator_specified.py -# -# This file is part of NEST. -# -# Copyright (C) 2004 The NEST Initiative -# -# NEST is free software: you can redistribute it and/or modify -# it under the terms of the GNU General Public License as published by -# the Free Software Foundation, either version 2 of the License, or -# (at your option) any later version. -# -# NEST is distributed in the hope that it will be useful, -# but WITHOUT ANY WARRANTY; without even the implied warranty of -# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the -# GNU General Public License for more details. -# -# You should have received a copy of the GNU General Public License -# along with NEST. If not, see . - -from pynestml.cocos.co_co import CoCo -from pynestml.meta_model.ast_model import ASTModel -from pynestml.utils.logger import Logger, LoggingLevel -from pynestml.utils.messages import Messages - - -class CoCoNESTDelayDecoratorSpecified(CoCo): - """ - This CoCo ensures that there is precisely one parameter decorated as "@nest::delay". - """ - - @classmethod - def check_co_co(cls, node: ASTModel): - """ - Checks if the coco applies for the node. - :param node: - """ - decorator_found = False - for variable in node.get_parameter_symbols() + node.get_internal_symbols(): - if variable.get_namespace_decorator("nest") == "delay": - decorator_found = True - break - - if not decorator_found: - code, message = Messages.get_nest_delay_decorator_not_found() - Logger.log_message(node=node, error_position=None, - code=code, message=message, - log_level=LoggingLevel.ERROR) diff --git a/pynestml/cocos/co_co_nest_synapse_delay_not_assigned_to.py b/pynestml/cocos/co_co_nest_synapse_delay_not_assigned_to.py new file mode 100644 index 000000000..50c86cc72 --- /dev/null +++ b/pynestml/cocos/co_co_nest_synapse_delay_not_assigned_to.py @@ -0,0 +1,60 @@ +# -*- coding: utf-8 -*- +# +# co_co_nest_synapse_delay_not_assigned_to.py +# +# This file is part of NEST. +# +# Copyright (C) 2004 The NEST Initiative +# +# NEST is free software: you can redistribute it and/or modify +# it under the terms of the GNU General Public License as published by +# the Free Software Foundation, either version 2 of the License, or +# (at your option) any later version. +# +# NEST is distributed in the hope that it will be useful, +# but WITHOUT ANY WARRANTY; without even the implied warranty of +# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +# GNU General Public License for more details. +# +# You should have received a copy of the GNU General Public License +# along with NEST. If not, see . + +from pynestml.meta_model.ast_assignment import ASTAssignment +from pynestml.meta_model.ast_model import ASTModel +from pynestml.cocos.co_co import CoCo +from pynestml.symbol_table.scope import ScopeType +from pynestml.symbols.symbol import SymbolKind +from pynestml.symbols.variable_symbol import BlockType +from pynestml.utils.ast_utils import ASTUtils +from pynestml.utils.logger import LoggingLevel, Logger +from pynestml.utils.messages import Messages +from pynestml.visitors.ast_visitor import ASTVisitor + + +class CoCoNESTSynapseDelayNotAssignedTo(CoCo): + r""" + This coco checks that the delay variable or parameter is not assigned to inside of a NESTML model. (This could be possible in general, but is not supported for now.) + """ + + @classmethod + def check_co_co(cls, delay_variable: str, node: ASTModel): + """ + Ensures the coco for the handed over neuron. + :param node: a single neuron instance. + """ + visitor = CoCoNESTSynapseDelayNotAssignedToVisitor() + visitor.delay_variable_ = delay_variable + node.accept(visitor) + + +class CoCoNESTSynapseDelayNotAssignedToVisitor(ASTVisitor): + def visit_assignment(self, node: ASTAssignment) -> None: + """ + Checks the coco on the current node. + :param node: a single node. + """ + variable = node.get_variable() + if variable.get_name() == self.delay_variable_: + Logger.log_message(error_position=node.get_source_position(), + code=None, message="Delay variable '" + str(variable.get_name()) + "' may not be assigned to in NEST synapse models", + log_level=LoggingLevel.ERROR) diff --git a/pynestml/cocos/co_co_no_kernels_except_in_convolve.py b/pynestml/cocos/co_co_no_kernels_except_in_convolve.py index c991ca351..4da392223 100644 --- a/pynestml/cocos/co_co_no_kernels_except_in_convolve.py +++ b/pynestml/cocos/co_co_no_kernels_except_in_convolve.py @@ -22,11 +22,11 @@ from typing import List from pynestml.cocos.co_co import CoCo -from pynestml.meta_model.ast_external_variable import ASTExternalVariable from pynestml.meta_model.ast_function_call import ASTFunctionCall from pynestml.meta_model.ast_kernel import ASTKernel from pynestml.meta_model.ast_model import ASTModel from pynestml.meta_model.ast_node import ASTNode +from pynestml.meta_model.ast_variable import ASTVariable from pynestml.symbols.symbol import SymbolKind from pynestml.utils.logger import Logger, LoggingLevel from pynestml.utils.messages import Messages @@ -86,7 +86,7 @@ def visit_variable(self, node: ASTNode): symbol = node.get_scope().resolve_to_symbol(kernelName, SymbolKind.VARIABLE) # if it is not a kernel just continue if symbol is None: - if not isinstance(node, ASTExternalVariable): + if not (isinstance(node, ASTVariable) and node.get_alternate_name()): code, message = Messages.get_no_variable_found(kernelName) Logger.log_message(node=self.__neuron_node, code=code, message=message, log_level=LoggingLevel.ERROR) continue diff --git a/pynestml/cocos/co_cos_manager.py b/pynestml/cocos/co_cos_manager.py index e3b439a7a..83900539b 100644 --- a/pynestml/cocos/co_cos_manager.py +++ b/pynestml/cocos/co_cos_manager.py @@ -74,7 +74,6 @@ class CoCosManager: """ This class provides a set of context conditions which have to hold for each model instance. """ - @classmethod def check_function_defined(cls, model: ASTModel): """ diff --git a/pynestml/codegeneration/nest_code_generator.py b/pynestml/codegeneration/nest_code_generator.py index 8fdb04566..ee707c029 100644 --- a/pynestml/codegeneration/nest_code_generator.py +++ b/pynestml/codegeneration/nest_code_generator.py @@ -27,7 +27,7 @@ import odetoolbox import pynestml -from pynestml.cocos.co_co_nest_delay_decorator_specified import CoCoNESTDelayDecoratorSpecified +from pynestml.cocos.co_co_nest_synapse_delay_not_assigned_to import CoCoNESTSynapseDelayNotAssignedTo from pynestml.codegeneration.code_generator import CodeGenerator from pynestml.codegeneration.code_generator_utils import CodeGeneratorUtils from pynestml.codegeneration.nest_assignments_helper import NestAssignmentsHelper @@ -67,6 +67,7 @@ from pynestml.utils.messages import Messages from pynestml.utils.model_parser import ModelParser from pynestml.utils.ode_toolbox_utils import ODEToolboxUtils +from pynestml.utils.string_utils import removesuffix from pynestml.visitors.ast_equations_with_delay_vars_visitor import ASTEquationsWithDelayVarsVisitor from pynestml.visitors.ast_equations_with_vector_variables import ASTEquationsWithVectorVariablesVisitor from pynestml.visitors.ast_mark_delay_vars_visitor import ASTMarkDelayVarsVisitor @@ -109,6 +110,8 @@ class NESTCodeGenerator(CodeGenerator): - **nest_version**: A string identifying the version of NEST Simulator to generate code for. The string corresponds to the NEST Simulator git repository tag or git branch name, for instance, ``"v2.20.2"`` or ``"master"``. The default is the empty string, which causes the NEST version to be automatically identified from the ``nest`` Python module. - **solver**: A string identifying the preferred ODE solver. ``"analytic"`` for propagator solver preferred; fallback to numeric solver in case ODEs are not analytically solvable. Use ``"numeric"`` to disable analytic solver. - **numeric_solver**: A string identifying the preferred numeric ODE solver. Supported are ``"rk45"`` and ``"forward-Euler"``. + - **delay_variable**: A mapping identifying, for each synapse (the name of which is given as a key), the variable or parameter in the model that corresponds with the NEST ``Connection`` class delay property. + - **weight_variable**: Like ``delay_variable``, but for synaptic weight. - **redirect_build_output**: An optional boolean key for redirecting the build output. Setting the key to ``True``, two files will be created for redirecting the ``stdout`` and the ``stderr`. The ``target_path`` will be used as the default location for creating the two files. - **build_output_dir**: An optional string key representing the new path where the files corresponding to the output of the build phase will be created. This key requires that the ``redirect_build_output`` is set to ``True``. @@ -137,7 +140,9 @@ class NESTCodeGenerator(CodeGenerator): }, "nest_version": "", "solver": "analytic", - "numeric_solver": "rk45" + "numeric_solver": "rk45", + "delay_variable": {}, + "weight_variable": {} } def __init__(self, options: Optional[Mapping[str, Any]] = None): @@ -161,6 +166,14 @@ def __init__(self, options: Optional[Mapping[str, Any]] = None): self.setup_template_env() self.setup_printers() + def run_nest_target_specific_cocos(self, neurons: Sequence[ASTModel], synapses: Sequence[ASTModel]): + for synapse in synapses: + synapse_name_stripped = removesuffix(removesuffix(synapse.name.split("_with_")[0], "_"), FrontendConfiguration.suffix) + delay_variable = self.get_option("delay_variable")[synapse_name_stripped] + CoCoNESTSynapseDelayNotAssignedTo.check_co_co(delay_variable, synapse) + if Logger.has_errors(synapse): + raise Exception("Error(s) occurred during code generation") + def setup_printers(self): self._constant_printer = ConstantPrinter() @@ -221,11 +234,14 @@ def set_options(self, options: Mapping[str, Any]) -> Mapping[str, Any]: return ret - def run_nest_target_specific_cocos(self, neurons: Sequence[ASTModel], synapses: Sequence[ASTModel]): - for synapse in synapses: - CoCoNESTDelayDecoratorSpecified.check_co_co(synapse) - if Logger.has_errors(synapse): - raise Exception("Error(s) occurred during code generation") + def generate_synapse_code(self, synapse: ASTModel) -> None: + # special case for delay variable + synapse_name_stripped = removesuffix(removesuffix(synapse.name.split("_with_")[0], "_"), FrontendConfiguration.suffix) + variables_special_cases = {self.get_option("delay_variable")[synapse_name_stripped]: "get_delay()"} + self._nest_variable_printer.variables_special_cases = variables_special_cases + self._nest_variable_printer_no_origin.variables_special_cases = variables_special_cases + + super().generate_synapse_code(synapse) def generate_code(self, models: Sequence[ASTModel]) -> None: neurons, synapses = CodeGeneratorUtils.get_model_types_from_names(models, neuron_models=self.get_option("neuron_models"), synapse_models=self.get_option("synapse_models")) @@ -414,7 +430,12 @@ def analyse_synapse(self, synapse: ASTModel) -> Dict[str, ASTAssignment]: ASTUtils.add_timestep_symbol(synapse) self.update_symbol_table(synapse) + synapse_name_stripped = removesuffix(removesuffix(synapse.name.split("_with_")[0], "_"), FrontendConfiguration.suffix) + # special case for NEST delay variable (state or parameter) + ASTUtils.update_blocktype_for_common_parameters(synapse) + assert synapse_name_stripped in self.get_option("delay_variable").keys(), "Please specify a delay variable for synapse '" + synapse_name_stripped + "' in the code generator options" + assert ASTUtils.get_variable_by_name(synapse, self.get_option("delay_variable")[synapse_name_stripped]), "Delay variable '" + self.get_option("delay_variable")[synapse_name_stripped] + "' not found in synapse '" + synapse_name_stripped + "'" return spike_updates @@ -569,6 +590,18 @@ def _get_synapse_model_namespace(self, synapse: ASTModel) -> Dict: namespace["spike_updates"] = synapse.spike_updates + synapse_name_stripped = removesuffix(removesuffix(synapse.name.split("_with_")[0], "_"), FrontendConfiguration.suffix) + + # special case for NEST delay variable (state or parameter) + assert synapse_name_stripped in self.get_option("delay_variable").keys() and ASTUtils.get_variable_by_name(synapse, self.get_option("delay_variable")[synapse_name_stripped]), "For synapse '" + synapse_name_stripped + "', a delay variable or parameter has to be specified for the NEST target; see https://nestml.readthedocs.io/en/latest/running/running_nest.html#dendritic-delay" + namespace["nest_codegen_opt_delay_variable"] = self.get_option("delay_variable")[synapse_name_stripped] + + # special case for NEST weight variable (state or parameter) + if synapse_name_stripped in self.get_option("weight_variable").keys() and ASTUtils.get_variable_by_name(synapse, self.get_option("weight_variable")[synapse_name_stripped]): + namespace["synapse_weight_variable"] = self.get_option("weight_variable")[synapse_name_stripped] + else: + namespace["synapse_weight_variable"] = "" + return namespace def _get_neuron_model_namespace(self, neuron: ASTModel) -> Dict: diff --git a/pynestml/codegeneration/nest_code_generator_utils.py b/pynestml/codegeneration/nest_code_generator_utils.py index c749bb81c..68448e40f 100644 --- a/pynestml/codegeneration/nest_code_generator_utils.py +++ b/pynestml/codegeneration/nest_code_generator_utils.py @@ -23,10 +23,13 @@ import re import tempfile import uuid +from pynestml.meta_model.ast_node import ASTNode from pynestml.meta_model.ast_variable import ASTVariable +from pynestml.symbols.symbol import SymbolKind from pynestml.symbols.variable_symbol import BlockType from pynestml.symbols.variable_symbol import VariableSymbol +from pynestml.visitors.ast_visitor import ASTVisitor class NESTCodeGeneratorUtils: diff --git a/pynestml/codegeneration/printers/nest_variable_printer.py b/pynestml/codegeneration/printers/nest_variable_printer.py index 2578cf2aa..3f6fc61dd 100644 --- a/pynestml/codegeneration/printers/nest_variable_printer.py +++ b/pynestml/codegeneration/printers/nest_variable_printer.py @@ -43,11 +43,12 @@ class NESTVariablePrinter(CppVariablePrinter): Variable printer for C++ syntax and the NEST API. """ - def __init__(self, expression_printer: ExpressionPrinter, with_origin: bool = True, with_vector_parameter: bool = True, enforce_getter: bool = True) -> None: + def __init__(self, expression_printer: ExpressionPrinter, with_origin: bool = True, with_vector_parameter: bool = True, enforce_getter: bool = True, variables_special_cases: Optional[Dict[str, str]] = None) -> None: super().__init__(expression_printer) self.with_origin = with_origin self.with_vector_parameter = with_vector_parameter self.enforce_getter = enforce_getter + self.variables_special_cases = variables_special_cases def print_variable(self, variable: ASTVariable) -> str: """ @@ -57,6 +58,11 @@ def print_variable(self, variable: ASTVariable) -> str: """ assert isinstance(variable, ASTVariable) + # print special cases such as synaptic delay variable + if self.variables_special_cases and variable.get_name() in self.variables_special_cases.keys(): + return self.variables_special_cases[variable.get_name()] + + # print external variables (such as a variable in the synapse that needs to call the getter method on the postsynaptic partner) if isinstance(variable, ASTExternalVariable): _name = str(variable) if variable.get_alternate_name(): @@ -68,11 +74,11 @@ def print_variable(self, variable: ASTVariable) -> str: if variable.get_name() == PredefinedVariables.E_CONSTANT: return "numerics::e" - symbol = variable.get_scope().resolve_to_symbol(variable.get_complete_name(), SymbolKind.VARIABLE) - if variable.get_name() == PredefinedVariables.TIME_CONSTANT: return "get_t()" + symbol = variable.get_scope().resolve_to_symbol(variable.get_complete_name(), SymbolKind.VARIABLE) + if symbol is None: # test if variable name can be resolved to a type if PredefinedUnits.is_unit(variable.get_complete_name()): diff --git a/pynestml/codegeneration/resources_nest/point_neuron/common/NeuronClass.jinja2 b/pynestml/codegeneration/resources_nest/point_neuron/common/NeuronClass.jinja2 index 2cbaf8c71..7f20b6b66 100644 --- a/pynestml/codegeneration/resources_nest/point_neuron/common/NeuronClass.jinja2 +++ b/pynestml/codegeneration/resources_nest/point_neuron/common/NeuronClass.jinja2 @@ -1079,6 +1079,9 @@ void while ( history_.size() > 1 ) { const double next_t_sp = history_[ 1 ].t_; + // Note that ``access_counter`` now has an extra multiplicative factor equal (``n_incoming_``) to the number of trace values that exist, so that spikes are removed from the history only after they have been read out for the sake of computing each trace. + // see https://www.frontiersin.org/files/Articles/1382/fncom-04-00141-r1/image_m/fncom-04-00141-g003.jpg (Potjans et al. 2010) + if ( history_.front().access_counter_ >= n_incoming_ * num_transferred_variables and t_sp_ms - next_t_sp > max_delay_ + nest::Time::delay_steps_to_ms(nest::kernel().connection_manager.get_min_delay()) + nest::kernel().connection_manager.get_stdp_eps() ) { @@ -1123,7 +1126,7 @@ void { recompute_internal_variables(true); -{%- filter indent(10, True) -%} +{%- filter indent(6, True) -%} {# emulate a call to ``integrate_odes(purely_numeric_state_variables_moved + analytic_state_variables_moved)`` #} {%- set args = utils.resolve_variables_to_expressions(astnode, purely_numeric_state_variables_moved + analytic_state_variables_moved) %} {%- set ast = ASTNodeFactory.create_ast_function_call("integrate_odes", args) %} @@ -1138,9 +1141,11 @@ void * print extra on-emit statements transferred from synapse **/ +{%- filter indent(4, True) %} {%- for stmt in extra_on_emit_spike_stmts_from_synapse %} {%- include "directives_cpp/Statement.jinja2" %} {%- endfor %} +{%- endfilter %} /** * print updates due to convolutions diff --git a/pynestml/codegeneration/resources_nest/point_neuron/common/SynapseHeader.h.jinja2 b/pynestml/codegeneration/resources_nest/point_neuron/common/SynapseHeader.h.jinja2 index 3d727ea23..e50c37573 100644 --- a/pynestml/codegeneration/resources_nest/point_neuron/common/SynapseHeader.h.jinja2 +++ b/pynestml/codegeneration/resources_nest/point_neuron/common/SynapseHeader.h.jinja2 @@ -132,10 +132,6 @@ public: {%- for parameter in synapse.get_parameter_symbols() %} {%- set isHomogeneous = PyNestMLLexer["DECORATOR_HOMOGENEOUS"] in parameter.get_decorators() %} {%- if isHomogeneous %} -{%- set namespaceName = parameter.get_namespace_decorator("nest") %} -{%- if namespaceName == '' %} -{{ raise('nest::names decorator is required for parameter "%s" when used in a common properties class' % printer.print(utils.get_parameter_variable_by_name(astnode, parameter.get_symbol_name()))) }} -{%- endif %} {%- set variable_symbol = parameter %} {%- set variable = utils.get_variable_by_name(astnode, variable_symbol.get_symbol_name()) %} {%- include "directives_cpp/CommonPropertiesDictionaryWriter.jinja2" %} @@ -156,10 +152,6 @@ public: {%- for parameter in synapse.get_parameter_symbols() %} {%- set isHomogeneous = PyNestMLLexer["DECORATOR_HOMOGENEOUS"] in parameter.get_decorators() %} {%- if isHomogeneous %} -{%- set namespaceName = parameter.get_namespace_decorator("nest") %} -{%- if (namespaceName == '') %} - {{ raise('nest::names decorator is required for parameter "%s" when used in a common properties class' % printer.print(utils.get_parameter_variable_by_name(astnode, parameter.get_symbol_name()))) }} -{%- endif %} {%- set variable_symbol = parameter %} {%- set variable = utils.get_variable_by_name(astnode, variable_symbol.get_symbol_name()) %} {%- include "directives_cpp/CommonPropertiesDictionaryReader.jinja2" %} @@ -337,9 +329,9 @@ private: {%- for variable_symbol in synapse.get_parameter_symbols() %} {%- set isHomogeneous = PyNestMLLexer["DECORATOR_HOMOGENEOUS"] in variable_symbol.get_decorators() %} {%- set variable = utils.get_parameter_variable_by_name(astnode, variable_symbol.get_symbol_name()) %} -{%- if not isHomogeneous %} +{%- if not isHomogeneous and not (variable_symbol.get_symbol_name() == nest_codegen_opt_delay_variable) %} {%- include 'directives_cpp/MemberDeclaration.jinja2' %} -{%- else %} +{%- elif isHomogeneous %} // N.B. the parameter `{{ printer.print(variable) }}` is defined in the common properties class {%- endif %} {%- endfor %} @@ -376,31 +368,30 @@ private: Parameters_ P_; //!< Free parameters. State_ S_; //!< Dynamic state. Variables_ V_; //!< Internal Variables -{%- if synapse.get_state_symbols()|length > 0 %} +{%- if synapse.get_state_symbols()|length > 0 or synapse.get_parameter_symbols()|length > 0 %} // ------------------------------------------------------------------------- - // Getters/setters for state block + // Getters/setters for parameters and state variables // ------------------------------------------------------------------------- -{% filter indent(2, True) -%} -{%- for variable_symbol in synapse.get_state_symbols() %} -{%- set variable = utils.get_state_variable_by_name(astnode, variable_symbol.get_symbol_name()) %} -{%- include "directives_cpp/MemberVariableGetterSetter.jinja2" %} - -{% endfor %} -{%- endfilter %} -{%- endif %} - -{%- if synapse.get_parameter_symbols()|length > 0 %} - // ------------------------------------------------------------------------- - // Getters/setters for parameters - // ------------------------------------------------------------------------- - -{% filter indent(2, True) -%} -{%- for variable_symbol in synapse.get_parameter_symbols() %} +{% filter indent(2, True) -%} +{%- for variable_symbol in synapse.get_state_symbols() + synapse.get_parameter_symbols() %} +{%- set variable = utils.get_variable_by_name(astnode, variable_symbol.get_symbol_name()) %} {%- set isHomogeneous = PyNestMLLexer["DECORATOR_HOMOGENEOUS"] in variable_symbol.get_decorators() %} {%- if not isHomogeneous %} -{%- set variable = utils.get_parameter_variable_by_name(astnode, variable_symbol.get_symbol_name()) %} -{%- include "directives_cpp/MemberVariableGetterSetter.jinja2" %} +{%- if variable.get_name() != nest_codegen_opt_delay_variable and variable.get_name() != synapse_weight_variable %} +{%- include "directives_cpp/MemberVariableGetterSetter.jinja2" %} +{%- elif variable.get_name() == synapse_weight_variable and variable.get_name() != "weight" %} +{# weight is its own special case in NEST #} +inline {{ declarations.print_variable_type(variable_symbol) }} get_{{ variable.get_name() }}() const +{ + return {{ printer.print(variable) }}; +} + +inline void set_{{ variable.get_name() }}(const {{ declarations.print_variable_type(variable_symbol) }} __v) +{ + set_weight(__v); +} +{%- endif %} {%- endif %} {%- endfor %} {%- endfilter %} @@ -600,26 +591,36 @@ public: return invalid_port; {%- endif %} } }; +{%- if synapse_weight_variable | length > 0 and synapse_weight_variable != "weight" %} +{%- set variable = utils.get_variable_by_name(astnode, synapse_weight_variable) %} +{%- set variable_symbol = variable.get_scope().resolve_to_symbol(variable.get_complete_name(), SymbolKind.VARIABLE) %} +{%- set isHomogeneous = PyNestMLLexer["DECORATOR_HOMOGENEOUS"] in variable_symbol.get_decorators() %} /** - * special case for weights in NEST: only in case a NESTML state variable was decorated by @nest::weight + * special case for weights in NEST: only in case a NESTML state variable was specified in code generation options as ``weight_variable`` **/ inline void set_weight(double w) { -{%- for variable_symbol in synapse.get_state_symbols() %} -{%- if variable_symbol.get_namespace_decorator("nest")|length > 0 %} - // special case for variable marked with @nest::weight decorator -{%- set nest_namespace_name = variable_symbol.get_namespace_decorator("nest") %} -{%- if nest_namespace_name == "weight" %} - set_{{ printer_no_origin.print(utils.get_state_variable_by_name(astnode, variable_symbol.get_symbol_name()))}}(w); - return; -{%- endif %} +{%- if isHomogeneous %} + throw BadProperty( + "Setting of individual weights is not possible! The common weights can " + "be changed via " + "CopyModel()." ); +{%- else %} + {{ printer.print(variable) }} = w; {%- endif %} -{%- endfor %} + } - // no variable was decorated by @nest::weight, so no "weight" defined from the NEST perspective - assert(0); +{%- if not isHomogeneous %} + /** + * special case for weights in NEST: only in case a NESTML state variable was specified in code generation options as ``weight_variable`` + **/ + inline double get_weight() const + { + return {{ printer.print(variable) }}; } +{%- endif %} +{%- endif %} {%- if not (nest_version.startswith("v2") or nest_version.startswith("v3.0") or nest_version.startswith("v3.1") or nest_version.startswith("v3.2") or nest_version.startswith("v3.3") or nest_version.startswith("v3.4")) %} void @@ -969,34 +970,22 @@ void ConnectionBase::get_status( __d ); def< long >( __d, names::size_of, sizeof( *this ) ); - // parameters -{%- for variable_symbol in synapse.get_parameter_symbols() %} -{%- set variable = utils.get_parameter_variable_by_name(astnode, variable_symbol.get_symbol_name()) %} + // parameters and state variables +{%- filter indent(2,True) %} +{%- for variable_symbol in synapse.get_parameter_symbols() + synapse.get_state_symbols() %} +{%- set variable = utils.get_variable_by_name(astnode, variable_symbol.get_symbol_name()) %} {%- set isHomogeneous = PyNestMLLexer["DECORATOR_HOMOGENEOUS"] in variable_symbol.get_decorators() %} {%- if not isHomogeneous %} -{%- set namespaceName = variable_symbol.get_namespace_decorator('nest') %} -{%- if namespaceName == '' %} -{%- filter indent(2,True) %} -{%- include "directives_cpp/WriteInDictionary.jinja2" %} -{%- endfilter %} +{%- if variable.get_name() == nest_codegen_opt_delay_variable %} +{#- special case for NEST special variable delay #} +def< {{ declarations.print_variable_type(variable_symbol) }} >( __d, names::delay, {{ printer.print(variable) }} ); // NEST special case for delay variable +def(__d, nest::{{ synapseName }}_names::_{{ nest_codegen_opt_delay_variable }}, {{ printer.print(variable) }}); +{#- special case for NEST special variable weight #} +{%- elif variable.get_name() == synapse_weight_variable %} +def< {{ declarations.print_variable_type(variable_symbol) }} >( __d, names::weight, {{ printer.print(variable) }} ); // NEST special case for weight variable +def< {{ declarations.print_variable_type(variable_symbol) }} >( __d, nest::{{ synapseName }}_names::_{{ synapse_weight_variable }}, {{ printer.print(variable) }} ); // NEST special case for weight variable {%- else %} - def< {{ declarations.print_variable_type(variable_symbol) }} >( __d, names::{{ namespaceName }}, {{ printer.print(variable) }} ); -{%- endif %} -{%- endif %} -{%- endfor %} - - // initial values for state variables in ODE or kernel -{%- filter indent(2,True) %} -{%- for variable_symbol in synapse.get_state_symbols() %} -{%- set variable = utils.get_state_variable_by_name(astnode, variable_symbol.get_symbol_name()) %} -{%- if not is_delta_kernel(synapse.get_kernel_by_name(variable_symbol.get_symbol_name())) %} -{%- include "directives_cpp/WriteInDictionary.jinja2" %} -{%- if variable_symbol.get_namespace_decorator("nest")|length > 0 %} -// special treatment for variable marked with @nest::name decorator -{%- set nest_namespace_name = variable_symbol.get_namespace_decorator("nest") %} -{%- if not variable_symbol.is_internals() %} -def<{{declarations.print_variable_type(variable_symbol)}}>(__d, names::{{nest_namespace_name}}, get_{{printer_no_origin.print(variable)}}()); -{%- endif %} +{%- include "directives_cpp/WriteInDictionary.jinja2" %} {%- endif %} {%- endif %} {%- endfor %} @@ -1008,44 +997,51 @@ void {{synapseName}}< targetidentifierT >::set_status( const DictionaryDatum& __d, ConnectorModel& cm ) { - // parameters -{%- for variable_symbol in synapse.get_parameter_symbols() %} -{%- set variable = utils.get_parameter_variable_by_name(astnode, variable_symbol.get_symbol_name()) %} -{%- set namespaceName = variable_symbol.get_namespace_decorator('nest') %} -{%- set isHomogeneous = PyNestMLLexer["DECORATOR_HOMOGENEOUS"] in variable_symbol.get_decorators() %} -{%- if not isHomogeneous %} -{%- filter indent(2,True) %} -{%- include "directives_cpp/ReadFromDictionaryToTmp.jinja2" %} -{%- endfilter %} -{%- endif %} -{%- endfor %} +{%- if synapse_weight_variable|length > 0 and synapse_weight_variable != "weight" %} + if (__d->known(nest::{{ synapseName }}_names::_{{ synapse_weight_variable }}) and __d->known(nest::names::weight)) + { + throw BadProperty( "To prevent inconsistencies, please set either 'weight' or '{{ synapse_weight_variable }}' variable; not both at the same time." ); + } +{%- endif %} + +{%- if nest_codegen_opt_delay_variable != "delay" %} + if (__d->known(nest::{{ synapseName }}_names::_{{ nest_codegen_opt_delay_variable }}) and __d->known(nest::names::delay)) + { + throw BadProperty( "To prevent inconsistencies, please set either 'delay' or '{{ nest_codegen_opt_delay_variable }}' variable; not both at the same time." ); + } +{%- endif %} - // initial values for state variables in ODE or kernel + // call parent class method + ConnectionBase::set_status( __d, cm ); + + // state variables and parameters {%- filter indent(2,True) %} -{%- for variable_symbol in synapse.get_state_symbols() %} -{%- set variable = utils.get_state_variable_by_name(astnode, variable_symbol.get_symbol_name()) %} -{%- if not is_delta_kernel(synapse.get_kernel_by_name(variable_symbol.name)) %} -{%- include "directives_cpp/ReadFromDictionaryToTmp.jinja2" %} -{%- if variable_symbol.get_namespace_decorator("nest")|length > 0 %} -// special treatment for variables marked with @nest::name decorator -{%- set nest_namespace_name = variable_symbol.get_namespace_decorator("nest") %} -{#- -------- XXX: TODO: this is almost the content of directives_cpp/ReadFromDictionaryToTmp.jinja2 verbatim, refactor this ---------- #} -{%- if not variable_symbol.is_inline_expression and not variable_symbol.is_state() %} -tmp_{{ printer_no_origin.print(variable) }} = get_{{ printer_no_origin.print(variable) }}(); -updateValue<{{ declarations.print_variable_type(variable_symbol) }}>(__d, "{{ nest_namespace_name }}", tmp_{{ printer_no_origin.print(variable) }}); -{%- elif not variable_symbol.is_inline_expression and variable_symbol.is_state() %} -tmp_{{ printer_no_origin.print(variable) }} = get_{{ printer_no_origin.print(variable) }}(); -updateValue<{{ declarations.print_variable_type(variable_symbol) }}>(__d, "{{ nest_namespace_name }}", tmp_{{ printer_no_origin.print(variable) }}); -{%- else %} - // ignores '{{ printer_no_origin.print(variable) }}' {{ declarations.print_variable_type(variable_symbol) }}' since it is an function and setter isn't defined -{%- endif %} -{#- -------------------------------------------------------------------------------------------------------------------------------- #} +{%- for variable_symbol in synapse.get_state_symbols() + synapse.get_parameter_symbols() %} +{%- set isHomogeneous = PyNestMLLexer["DECORATOR_HOMOGENEOUS"] in variable_symbol.get_decorators() %} +{%- set variable = utils.get_variable_by_name(astnode, variable_symbol.get_symbol_name()) %} +{%- if not isHomogeneous and not is_delta_kernel(synapse.get_kernel_by_name(variable_symbol.name)) and not variable_symbol.is_inline_expression %} +{%- if variable.get_name() == nest_codegen_opt_delay_variable %} +// special treatment of NEST delay +double tmp_{{ nest_codegen_opt_delay_variable }} = get_delay(); +updateValue(__d, nest::{{ synapseName }}_names::_{{ nest_codegen_opt_delay_variable }}, tmp_{{nest_codegen_opt_delay_variable}}); +{%- elif variable.get_name() == synapse_weight_variable %} +// special treatment of NEST weight +double tmp_{{ synapse_weight_variable }} = get_weight(); +if (__d->known(nest::{{ synapseName }}_names::_{{ synapse_weight_variable }})) +{ + updateValue(__d, nest::{{ synapseName }}_names::_{{ synapse_weight_variable }}, tmp_{{synapse_weight_variable}}); +} +if (__d->known(nest::names::weight)) +{ + updateValue(__d, nest::names::weight, tmp_{{synapse_weight_variable}}); +} +{%- else %} +{%- include "directives_cpp/ReadFromDictionaryToTmp.jinja2" %} {%- endif %} -{%- endif %} +{%- endif %} {%- endfor %} {%- endfilter %} - // We now know that (ptmp, stmp) are consistent. We do not // write them back to (P_, S_) before we are also sure that // the properties to be set in the parent class are internally @@ -1054,52 +1050,42 @@ updateValue<{{ declarations.print_variable_type(variable_symbol) }}>(__d, "{{ ne // if we get here, temporaries contain consistent set of properties - // set parameters -{%- for variable_symbol in synapse.get_parameter_symbols() %} -{%- set variable = utils.get_parameter_variable_by_name(astnode, variable_symbol.get_symbol_name()) %} -{%- set namespaceName = variable_symbol.get_namespace_decorator('nest') %} -{%- set isHomogeneous = PyNestMLLexer["DECORATOR_HOMOGENEOUS"] in variable_symbol.get_decorators() %} -{%- if not isHomogeneous %} -{%- filter indent(2,True) %} -{%- include "directives_cpp/AssignTmpDictionaryValue.jinja2" %} -{%- endfilter %} -{%- endif %} -{%- endfor %} - - // set state -{%- for variable_symbol in synapse.get_state_symbols() %} -{%- set variable = utils.get_state_variable_by_name(astnode, variable_symbol.get_symbol_name()) %} -{%- if not is_delta_kernel(synapse.get_kernel_by_name(variable_symbol.name)) %} -{%- filter indent(2,True) %} + // set state and parameters +{%- filter indent(2,True) %} +{%- for variable_symbol in synapse.get_state_symbols() + synapse.get_parameter_symbols() %} +{%- set variable = utils.get_variable_by_name(astnode, variable_symbol.get_symbol_name()) %} +{%- set isHomogeneous = PyNestMLLexer["DECORATOR_HOMOGENEOUS"] in variable_symbol.get_decorators() %} +{%- if not isHomogeneous and not is_delta_kernel(synapse.get_kernel_by_name(variable_symbol.name)) %} +{%- if variable.get_name() == nest_codegen_opt_delay_variable %} +// special treatment of NEST delay +set_delay(tmp_{{ nest_codegen_opt_delay_variable }}); +{%- else %} {%- include "directives_cpp/AssignTmpDictionaryValue.jinja2" %} -{%- endfilter %} +{%- endif %} {%- endif %} {%- endfor %} +{%- endfilter %} +{%- if synapse.get_parameter_invariants() | length > 0 %} // check invariants {% for invariant in synapse.get_parameter_invariants() %} - if ( !({{printer.print(invariant)}}) ) { + if ( !({{printer.print(invariant)}}) ) + { throw nest::BadProperty("The constraint '{{nestml_printer.print(invariant)}}' is violated!"); } {%- endfor %} -{% if uses_numeric_solver %} +{%- endif %} + +{% if uses_numeric_solver %} {%- if numeric_solver == "rk45" %} updateValue< double >(__d, nest::names::gsl_error_tol, P_.__gsl_error_tol); - if ( P_.__gsl_error_tol <= 0. ){ + if ( P_.__gsl_error_tol <= 0. ) + { throw nest::BadProperty( "The gsl_error_tol must be strictly positive." ); } -{% endif %} -{% endif %} - - // special treatment of NEST delay - set_delay({%- for variable_symbol in synapse.get_parameter_symbols() %} -{%- set namespaceName = variable_symbol.get_namespace_decorator("nest") %} -{%- set variable = utils.get_parameter_variable_by_name(astnode, variable_symbol.get_symbol_name()) %} -{%- if namespaceName == "delay" %} -get_{{ printer_no_origin.print(variable) }}() -{%- endif %} -{%- endfor %}); +{%- endif %} +{% endif %} // recompute internal variables in case they are dependent on parameters or state that might have been updated in this call to set_status() V_.__h = nest::Time::get_resolution().get_ms(); @@ -1132,22 +1118,31 @@ template < typename targetidentifierT > { const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function + // initial values for parameters +{%- filter indent(2, True) %} {%- for variable_symbol in synapse.get_parameter_symbols() %} {%- set variable = utils.get_parameter_variable_by_name(astnode, variable_symbol.get_symbol_name()) %} {%- set isHomogeneous = PyNestMLLexer["DECORATOR_HOMOGENEOUS"] in variable_symbol.get_decorators() %} {%- if not isHomogeneous %} -{%- include "directives_cpp/MemberInitialization.jinja2" %} +{%- if variable.get_name() != nest_codegen_opt_delay_variable %} +{%- include "directives_cpp/MemberInitialization.jinja2" %} +{%- endif %} {%- endif %} {%- endfor %} +{%- endfilter %} V_.__h = nest::Time::get_resolution().get_ms(); recompute_internal_variables(); - // initial values for state variables in ODE or kernel + // initial values for state variables +{%- filter indent(2, True) %} {%- for variable_symbol in synapse.get_state_symbols() %} {%- set variable = utils.get_state_variable_by_name(astnode, variable_symbol.get_symbol_name()) %} -{%- include "directives_cpp/MemberInitialization.jinja2" %} +{%- if variable.get_name() != synapse_weight_variable and variable.get_name() != nest_codegen_opt_delay_variable %} +{%- include "directives_cpp/MemberInitialization.jinja2" %} +{%- endif %} {%- endfor %} +{%- endfilter %} t_lastspike_ = 0.; {%- if vt_ports is defined and vt_ports|length > 0 %} @@ -1162,29 +1157,38 @@ template < typename targetidentifierT > {{synapseName}}< targetidentifierT >::{{synapseName}}( const {{synapseName}}< targetidentifierT >& rhs ) : ConnectionBase( rhs ) { + // parameters {%- for variable_symbol in synapse.get_parameter_symbols() %} {%- set isHomogeneous = PyNestMLLexer["DECORATOR_HOMOGENEOUS"] in variable_symbol.get_decorators() %} {%- set variable = utils.get_parameter_variable_by_name(astnode, variable_symbol.get_symbol_name()) %} -{%- if not isHomogeneous %} - {{ printer.print(variable) }} = rhs.{{ printer.print(variable) }}; +{%- if not isHomogeneous and variable.get_name() != synapse_weight_variable and variable.get_name() != nest_codegen_opt_delay_variable %} + {{ printer.print(variable) }} = rhs.{{ printer.print(variable) }}; {%- endif %} {%- endfor %} - // state variables in ODE or kernel + // state variables {%- for variable_symbol in synapse.get_state_symbols() %} {%- set variable = utils.get_state_variable_by_name(astnode, variable_symbol.get_symbol_name()) %} - {{ printer.print(variable) }} = rhs.{{ printer.print(variable) }}; +{%- if variable.get_name() != synapse_weight_variable and variable.get_name() != nest_codegen_opt_delay_variable %} + {{ printer.print(variable) }} = rhs.{{ printer.print(variable) }}; +{%- endif %} {%- endfor %} - //weight_ = get_named_parameter(names::weight); - //set_weight( *rhs.weight_ ); {%- if vt_ports is defined and vt_ports|length > 0 %} - t_last_update_ = rhs.t_last_update_; + t_last_update_ = rhs.t_last_update_; {%- endif %} - t_lastspike_ = rhs.t_lastspike_; + t_lastspike_ = rhs.t_lastspike_; - // special treatment of NEST delay - set_delay(rhs.get_delay()); + // special treatment of NEST delay + set_delay(rhs.get_delay()); +{%- if synapse_weight_variable | length > 0 %} +{%- set variable_symbol = synapse.get_scope().resolve_to_symbol(variable.get_complete_name(), SymbolKind.VARIABLE) %} +{%- set isHomogeneous = PyNestMLLexer["DECORATOR_HOMOGENEOUS"] in variable_symbol.get_decorators() %} +{%- if not isHomogeneous %} + // special treatment of NEST weight + set_weight(rhs.get_weight()); +{%- endif %} +{%- endif %} } template < typename targetidentifierT > diff --git a/pynestml/codegeneration/resources_nest/point_neuron/directives_cpp/CommonPropertiesDictionaryReader.jinja2 b/pynestml/codegeneration/resources_nest/point_neuron/directives_cpp/CommonPropertiesDictionaryReader.jinja2 index 0ff40dd1f..2dbb9af03 100644 --- a/pynestml/codegeneration/resources_nest/point_neuron/directives_cpp/CommonPropertiesDictionaryReader.jinja2 +++ b/pynestml/codegeneration/resources_nest/point_neuron/directives_cpp/CommonPropertiesDictionaryReader.jinja2 @@ -6,5 +6,5 @@ {%- if variable_symbol.has_vector_parameter() %} {{ raise('Vector parameters not supported in common properties dictionary.') }} {%- endif %} -updateValue< {{ declarations.print_variable_type(variable_symbol) }} >(d, names::{{namespaceName}}, this->{{ printer_no_origin.print(variable) }} ); +updateValue< {{ declarations.print_variable_type(variable_symbol) }} >(d, nest::{{ synapseName }}_names::_{{ printer_no_origin.print(variable) }}, this->{{ printer_no_origin.print(variable) }} ); diff --git a/pynestml/codegeneration/resources_nest/point_neuron/directives_cpp/CommonPropertiesDictionaryWriter.jinja2 b/pynestml/codegeneration/resources_nest/point_neuron/directives_cpp/CommonPropertiesDictionaryWriter.jinja2 index b40b1a719..9791b58d7 100644 --- a/pynestml/codegeneration/resources_nest/point_neuron/directives_cpp/CommonPropertiesDictionaryWriter.jinja2 +++ b/pynestml/codegeneration/resources_nest/point_neuron/directives_cpp/CommonPropertiesDictionaryWriter.jinja2 @@ -6,4 +6,4 @@ {%- if variable_symbol.has_vector_parameter() %} {{ raise('Vector parameters not supported in common properties dictionary.') }} {%- endif %} -def< {{ declarations.print_variable_type(variable_symbol) }} >(d, names::{{ namespaceName }}, this->{{ printer_no_origin.print(variable) }} ); +def< {{ declarations.print_variable_type(variable_symbol) }} >(d, nest::{{ synapseName }}_names::_{{ printer_no_origin.print(variable) }}, this->{{ printer_no_origin.print(variable) }} ); diff --git a/pynestml/codegeneration/resources_nest/point_neuron/directives_cpp/WriteInDictionary.jinja2 b/pynestml/codegeneration/resources_nest/point_neuron/directives_cpp/WriteInDictionary.jinja2 index 5782c14d9..2d8d62d40 100644 --- a/pynestml/codegeneration/resources_nest/point_neuron/directives_cpp/WriteInDictionary.jinja2 +++ b/pynestml/codegeneration/resources_nest/point_neuron/directives_cpp/WriteInDictionary.jinja2 @@ -4,5 +4,5 @@ #} {%- if tracing %}/* generated by {{self._TemplateReference__context.name}} */ {% endif %} {%- if not variable_symbol.is_internals() %} -def<{{declarations.print_variable_type(variable_symbol)}}>(__d, nest::{{names_namespace}}::_{{variable_symbol.get_symbol_name()}}, get_{{printer_no_origin.print(variable)}}()); +def< {{declarations.print_variable_type(variable_symbol)}} >(__d, nest::{{names_namespace}}::_{{variable_symbol.get_symbol_name()}}, get_{{printer_no_origin.print(variable)}}()); {%- endif %} diff --git a/pynestml/codegeneration/resources_spinnaker/@SYNAPSE_NAME@_impl.c.jinja2 b/pynestml/codegeneration/resources_spinnaker/@SYNAPSE_NAME@_impl.c.jinja2 index cae90bd07..e7fe320a3 100644 --- a/pynestml/codegeneration/resources_spinnaker/@SYNAPSE_NAME@_impl.c.jinja2 +++ b/pynestml/codegeneration/resources_spinnaker/@SYNAPSE_NAME@_impl.c.jinja2 @@ -2,14 +2,14 @@ #include -// Only adds prototypes for weight depression and potentiation -> maybe remove +// Only adds prototypes for weight depression and potentiation -> maybe remove // TODO: Ensure this includes and implements the correct interface #include // Should be good at the moment -// defines plastic_synapse_t -> plastic part of synapse +// defines plastic_synapse_t -> plastic part of synapse // similar to state for nestml, but that also contains pre and posttrace -// TODO: Choose the required synapse structure +// TODO: Choose the required synapse structure #include #include @@ -27,7 +27,7 @@ struct synapse_row_plastic_data_t { // Possibly irrelevant -//static stdp_params params; +//static stdp_params params; extern uint32_t skipped_synapses; @@ -173,10 +173,10 @@ static inline update_state_t timing_apply_post_spike( pre_trace_t last_pre_trace, uint32_t last_post_time, post_trace_t last_post_trace, update_state_t previous_state) { - // update_state_t == weight_state_t + // update_state_t == weight_state_t update_state_t *state = &previous_state; const plasticity_weight_region_data_t* parameter = state->parameter; - + uint32_t time_since_last_pre = time - last_pre_time; if (time_since_last_pre > 0) { @@ -210,7 +210,7 @@ static inline update_state_t timing_apply_pre_spike( uint32_t time, pre_trace_t trace, uint32_t last_pre_time, pre_trace_t last_pre_trace, uint32_t last_post_time, post_trace_t last_post_trace, update_state_t previous_state) { - + update_state_t *state = &previous_state; const plasticity_weight_region_data_t* parameter = state->parameter; // Get time of event relative to last post-synaptic event @@ -313,12 +313,12 @@ static inline final_state_t plasticity_update_synapse( -// TAG: POST +// TAG: POST // Exponential decay of post spike -// TAG: GENERATE -// Add +// TAG: GENERATE +// Add static inline post_trace_t timing_decay_post( uint32_t time, uint32_t last_time, post_trace_t last_trace) { extern int16_lut *tau_minus_lookup; @@ -339,7 +339,7 @@ static inline post_trace_t timing_decay_post( //! \return the updated post trace static inline post_trace_t timing_add_post_spike( uint32_t time, uint32_t last_time, post_trace_t last_trace) { - plasticity_weight_region_data_t* parameter = &plasticity_weight_region_data[0]; + plasticity_weight_region_data_t* parameter = &plasticity_weight_region_data[0]; struct tmp_struct { post_trace_t post_trace; @@ -436,7 +436,7 @@ static inline pre_trace_t timing_add_pre_spike( } tmp = {.pre_trace = last_trace}; struct tmp_struct *state = &tmp; - plasticity_weight_region_data_t* parameter = &plasticity_weight_region_data[0]; + plasticity_weight_region_data_t* parameter = &plasticity_weight_region_data[0]; // update propagator based on deltatime int32_t temp__h = parameter->__h; parameter->__h = time - last_time; @@ -480,11 +480,11 @@ bool synapse_dynamics_process_plastic_synapses( // Array of weights plastic_synapse_t *plastic_words = plastic_region_address->synapses; - // control_t = uint16_t + // control_t = uint16_t const control_t *control_words = synapse_row_plastic_controls(fixed_region); size_t n_plastic_synapses = synapse_row_num_plastic_controls(fixed_region); - // This method is called on presynaptic event + // This method is called on presynaptic event num_plastic_pre_synaptic_events += n_plastic_synapses; // Backup last presynaptic spike @@ -498,7 +498,7 @@ bool synapse_dynamics_process_plastic_synapses( // Loop through plastic synapses for (; n_plastic_synapses > 0; n_plastic_synapses--) { - // Get control word, increment after + // Get control word, increment after uint32_t control_word = *control_words++; plastic_words[0] = process_plastic_synapse( @@ -530,12 +530,10 @@ static inline weight_state_t weight_get_initial( s1615 s1615_weight = kbits(weight << weight_shift[synapse_type]); return (weight_state_t) { {%- for variable_symbol in synapse.get_state_symbols() %} -{%- if variable_symbol.get_namespace_decorator("nest")|length > 0 %} - // special case for variable marked with @nest::weight decorator -{%- set nest_namespace_name = variable_symbol.get_namespace_decorator("nest") %} -{%- if nest_namespace_name == "weight" %} - .{{ printer_no_origin.print(utils.get_state_variable_by_name(astnode, variable_symbol.get_symbol_name()))}} = s1615_weight, -{%- endif %} +{%- if variable_symbol.variable_symbol.get_symbol_name() == synapse_weight_variable %} +{%- set variable = utils.get_state_variable_by_name(astnode, variable_symbol.get_symbol_name()) %} + // special case for weight variable + .{{ printer_no_origin.print(variable) }} = s1615_weight, {%- endif %} {%- endfor %} .weight_shift = weight_shift[synapse_type], @@ -562,13 +560,11 @@ static inline weight_t weight_get_final(weight_state_t state) { // state, taking into account all potentiation and depression // Note: it is recommended to do a single complex operation here rather // than one for each potentiation or depression if possible - {%- for variable_symbol in synapse.get_state_symbols() %} -{%- if variable_symbol.get_namespace_decorator("nest")|length > 0 %} - // special case for variable marked with @nest::weight decorator -{%- set nest_namespace_name = variable_symbol.get_namespace_decorator("nest") %} -{%- if nest_namespace_name == "weight" %} +{%- for variable_symbol in synapse.get_state_symbols() %} +{%- if variable_symbol.variable_symbol.get_symbol_name() == synapse_weight_variable %} +{%- set variable = utils.get_state_variable_by_name(astnode, variable_symbol.get_symbol_name()) %} + // special case for weight variable return (weight_t)(bitsk(state.{{ printer_no_origin.print(utils.get_state_variable_by_name(astnode, variable_symbol.get_symbol_name()))}}) >> state.weight_shift); -{%- endif %} {%- endif %} {%- endfor %} } @@ -585,12 +581,10 @@ static void weight_decay(weight_state_t *state, int32_t decay) { __attribute__((unused)) // Marked unused as only used sometimes static accum weight_get_update(weight_state_t state) { {%- for variable_symbol in synapse.get_state_symbols() %} -{%- if variable_symbol.get_namespace_decorator("nest")|length > 0 %} - // special case for variable marked with @nest::weight decorator -{%- set nest_namespace_name = variable_symbol.get_namespace_decorator("nest") %} -{%- if nest_namespace_name == "weight" %} +{%- if variable_symbol.variable_symbol.get_symbol_name() == synapse_weight_variable %} +{%- set variable = utils.get_state_variable_by_name(astnode, variable_symbol.get_symbol_name()) %} + // special case for weight variable return state.{{ printer_no_origin.print(utils.get_state_variable_by_name(astnode, variable_symbol.get_symbol_name()))}}; -{%- endif %} {%- endif %} {%- endfor %} } diff --git a/pynestml/meta_model/ast_external_variable.py b/pynestml/meta_model/ast_external_variable.py index c1c59b0b1..5418ffc85 100644 --- a/pynestml/meta_model/ast_external_variable.py +++ b/pynestml/meta_model/ast_external_variable.py @@ -69,5 +69,6 @@ def get_alternate_name(self): def get_scope(self): if self._altscope: - return self._altscope.get_scope() + return self._altscope + return self.scope diff --git a/pynestml/meta_model/ast_variable.py b/pynestml/meta_model/ast_variable.py index ecb200d46..c0645be25 100644 --- a/pynestml/meta_model/ast_variable.py +++ b/pynestml/meta_model/ast_variable.py @@ -24,6 +24,7 @@ from copy import copy from pynestml.meta_model.ast_node import ASTNode +from pynestml.symbol_table.scope import Scope from pynestml.symbols.type_symbol import TypeSymbol @@ -43,7 +44,7 @@ class ASTVariable(ASTNode): def __init__(self, name, differential_order=0, type_symbol: Optional[str] = None, vector_parameter: Optional[str] = None, is_homogeneous: bool = False, delay_parameter: Optional[str] = None, *args, **kwargs): - """ + r""" Standard constructor. :param name: the name of the variable :type name: str diff --git a/pynestml/transformers/synapse_post_neuron_transformer.py b/pynestml/transformers/synapse_post_neuron_transformer.py index 5dd4aa3e0..a74c4b159 100644 --- a/pynestml/transformers/synapse_post_neuron_transformer.py +++ b/pynestml/transformers/synapse_post_neuron_transformer.py @@ -53,6 +53,22 @@ class SynapsePostNeuronTransformer(Transformer): def __init__(self, options: Optional[Mapping[str, Any]] = None): super(Transformer, self).__init__(options) + self._copy_custom_options(options) + + def _copy_custom_options(self, options): + if options: + if "delay_variable" in options: + self._options["delay_variable"] = options["delay_variable"].copy() + + if "weight_variable" in options: + self._options["weight_variable"] = options["weight_variable"].copy() + + def set_options(self, options: Mapping[str, Any]) -> Mapping[str, Any]: + r"""Set options. "Eats off" any options that it knows how to set, and returns the rest as "unhandled" options.""" + unused_options = super().set_options(options) + self._copy_custom_options(options) + + return unused_options def is_special_port(self, special_type: str, port_name: str, neuron_name: str, synapse_name: str) -> bool: """ @@ -207,7 +223,6 @@ def visit_assignment(self, node): symbol = node.get_scope().resolve_to_symbol(node.get_variable().get_complete_name(), SymbolKind.VARIABLE) assert symbol is not None # should have been checked in a CoCo before self._variable_names.append(node.get_variable().get_name()) - # print("-------> adding " + node.get_variable().get_name()) if node is None: return [] @@ -267,6 +282,12 @@ def transform_neuron_synapse_pair_(self, neuron, synapse): # exclude certain variables from being moved: # exclude any variable assigned to in any block that is not connected to a postsynaptic port strictly_synaptic_vars = ["t"] # "seed" this with the predefined variable t + if self.option_exists("delay_variable") and removesuffix(synapse.get_name(), FrontendConfiguration.suffix) in self.get_option("delay_variable").keys() and self.get_option("delay_variable")[removesuffix(synapse.get_name(), FrontendConfiguration.suffix)]: + strictly_synaptic_vars.append(self.get_option("delay_variable")[removesuffix(synapse.get_name(), FrontendConfiguration.suffix)]) + + if self.option_exists("weight_variable") and removesuffix(synapse.get_name(), FrontendConfiguration.suffix) in self.get_option("weight_variable").keys() and self.get_option("weight_variable")[removesuffix(synapse.get_name(), FrontendConfiguration.suffix)]: + strictly_synaptic_vars.append(self.get_option("weight_variable")[removesuffix(synapse.get_name(), FrontendConfiguration.suffix)]) + for input_block in new_synapse.get_input_blocks(): for port in input_block.get_input_ports(): if not self.is_post_port(port.name, neuron.name, synapse.name): @@ -307,7 +328,11 @@ def transform_neuron_synapse_pair_(self, neuron, synapse): # collect all the parameters # - all_declared_params = [s.get_variables() for s in new_synapse.get_parameters_blocks()[0].get_declarations()] + if new_synapse.get_parameters_blocks(): + all_declared_params = [s.get_variables() for s in new_synapse.get_parameters_blocks()[0].get_declarations()] + else: + all_declared_params = [] + all_declared_params = sum(all_declared_params, []) all_declared_params = [var.name for var in all_declared_params] @@ -371,6 +396,7 @@ def transform_neuron_synapse_pair_(self, neuron, synapse): for state_var in syn_to_neuron_state_vars: Logger.log_message(None, -1, "Moving state var defining equation(s) " + str(state_var), None, LoggingLevel.INFO) + # move the ODE so a solver will be generated for it by ODE-toolbox decls = ASTUtils.equations_from_block_to_block(state_var, new_synapse.get_equations_blocks()[0], new_neuron.get_equations_blocks()[0], @@ -378,6 +404,8 @@ def transform_neuron_synapse_pair_(self, neuron, synapse): mode="move") ASTUtils.add_suffix_to_variable_names2(post_port_names + syn_to_neuron_state_vars + syn_to_neuron_params, decls, var_name_suffix) ASTUtils.remove_state_var_from_integrate_odes_calls(new_synapse, state_var) + # ASTUtils.add_integrate_odes_call_to_update_block(new_neuron, state_var) # the moved state variables are never needed inside the neuron, their values are only read out from the side of the synapse. Therefore they do not have to be added to integrate_odes() calls; we just have to make sure the value has been updated before the end of the timestep + # for now, moved variables are integrated separately in time in set_spiketime() # # move initial values for equations @@ -465,7 +493,7 @@ def mark_post_port(_expr=None): # Logger.log_message( - None, -1, "In synapse: replacing ``continuous`` type input ports that are connected to postsynaptic neuron with suffixed external variable references", None, LoggingLevel.INFO) + None, -1, "In synapse: replacing ``continuous`` type input ports that are connected to postsynaptic neuron with external variable references", None, LoggingLevel.INFO) post_connected_continuous_input_ports = [] post_variable_names = [] for input_block in synapse.get_input_blocks(): @@ -477,8 +505,7 @@ def mark_post_port(_expr=None): for state_var, alternate_name in zip(post_connected_continuous_input_ports, post_variable_names): Logger.log_message(None, -1, "\t• Replacing variable " + str(state_var), None, LoggingLevel.INFO) - ASTUtils.replace_with_external_variable(state_var, new_synapse, "", - new_synapse.get_equations_blocks()[0], alternate_name) + ASTUtils.replace_with_external_variable(state_var, new_synapse, "", new_synapse.get_equations_blocks()[0].get_scope(), alternate_name) # # copy parameters @@ -509,12 +536,16 @@ def mark_post_port(_expr=None): # replace occurrences of the variables in expressions in the original synapse with calls to the corresponding neuron getters # + # make sure the moved symbols can be resolved in the scope of the neuron (that's where ``ASTExternalVariable._altscope`` will be pointing to) + ast_symbol_table_visitor = ASTSymbolTableVisitor() + ast_symbol_table_visitor.after_ast_rewrite_ = True + new_neuron.accept(ast_symbol_table_visitor) + Logger.log_message( None, -1, "In synapse: replacing variables with suffixed external variable references", None, LoggingLevel.INFO) for state_var in syn_to_neuron_state_vars: Logger.log_message(None, -1, "\t• Replacing variable " + str(state_var), None, LoggingLevel.INFO) - ASTUtils.replace_with_external_variable( - state_var, new_synapse, var_name_suffix, new_neuron.get_equations_blocks()[0]) + ASTUtils.replace_with_external_variable(state_var, new_synapse, var_name_suffix, new_neuron.get_equations_blocks()[0].get_scope()) # # rename neuron diff --git a/pynestml/utils/ast_mechanism_information_collector.py b/pynestml/utils/ast_mechanism_information_collector.py index 1b994a42f..eed37601d 100644 --- a/pynestml/utils/ast_mechanism_information_collector.py +++ b/pynestml/utils/ast_mechanism_information_collector.py @@ -19,8 +19,9 @@ # You should have received a copy of the GNU General Public License # along with NEST. If not, see . -from pynestml.frontend.frontend_configuration import FrontendConfiguration from collections import defaultdict + +from pynestml.frontend.frontend_configuration import FrontendConfiguration from pynestml.visitors.ast_visitor import ASTVisitor diff --git a/pynestml/utils/ast_utils.py b/pynestml/utils/ast_utils.py index 680d9635a..e9ae0daa0 100644 --- a/pynestml/utils/ast_utils.py +++ b/pynestml/utils/ast_utils.py @@ -551,7 +551,7 @@ def replace_var(_expr=None): @classmethod def remove_state_var_from_integrate_odes_calls(cls, model: ASTModel, state_var_name: str): - r"""Remove a state variable from the arguments to integrate_odes() calls in the model.""" + r"""Remove a state variable from the arguments (where it exists) of each integrate_odes() call in the model.""" class RemoveStateVarFromIntegrateODEsCallsVisitor(ASTVisitor): def visit_function_call(self, node: ASTFunctionCall): @@ -641,7 +641,7 @@ def get_kernel_by_name(cls, node, name: str) -> Optional[ASTKernel]: @classmethod def replace_with_external_variable(cls, var_name, node: ASTNode, suffix, new_scope, alternate_name=None): - """ + r""" Replace all occurrences of variables (``ASTVariable``s) (e.g. ``post_trace'``) in the node with ``ASTExternalVariable``s, indicating that they are moved to the postsynaptic neuron. """ @@ -659,11 +659,11 @@ def replace_var(_expr=None): ast_ext_var = ASTExternalVariable(var.get_name() + suffix, differential_order=var.get_differential_order(), source_position=var.get_source_position()) + if alternate_name: ast_ext_var.set_alternate_name(alternate_name) ast_ext_var.parent_ = _expr - ast_ext_var.update_alt_scope(new_scope) from pynestml.visitors.ast_symbol_table_visitor import ASTSymbolTableVisitor ast_ext_var.accept(ASTSymbolTableVisitor()) diff --git a/pynestml/utils/messages.py b/pynestml/utils/messages.py index 9df4742b1..f39d9ecdb 100644 --- a/pynestml/utils/messages.py +++ b/pynestml/utils/messages.py @@ -113,7 +113,6 @@ class MessageCode(Enum): PRIORITY_DEFINED_FOR_ONLY_ONE_EVENT_HANDLER = 82 REPEATED_PRIORITY_VALUE = 83 DELAY_VARIABLE = 84 - NEST_DELAY_DECORATOR_NOT_FOUND = 85 INPUT_PORT_SIZE_NOT_INTEGER = 86 INPUT_PORT_SIZE_NOT_GREATER_THAN_ZERO = 87 INSTALL_PATH_INFO = 88 @@ -1269,11 +1268,6 @@ def get_syns_bad_buffer_count(cls, buffers: set, synapse_name: str): message += " However exaxtly one spike input buffer per synapse is allowed." return MessageCode.SYNS_BAD_BUFFER_COUNT, message - @classmethod - def get_nest_delay_decorator_not_found(cls): - message = "To generate code for NEST Simulator, at least one parameter in the model should be decorated with the ``@nest::delay`` keyword." - return MessageCode.NEST_DELAY_DECORATOR_NOT_FOUND, message - @classmethod def get_input_port_size_not_integer(cls, port_name: str): message = "The size of the input port " + port_name + " is not of integer type." diff --git a/pynestml/utils/with_options.py b/pynestml/utils/with_options.py index 3d951a817..13bed92d2 100644 --- a/pynestml/utils/with_options.py +++ b/pynestml/utils/with_options.py @@ -53,6 +53,9 @@ def add_options(self, options: Mapping[str, Any]) -> None: def set_options(self, options: Mapping[str, Any]) -> Mapping[str, Any]: r"""Set options. "Eats off" any options that it knows how to set, and returns the rest as "unhandled" options.""" + if not options: + return {} + unhandled_options = {} for k in options.keys(): if k in self.__class__._default_options: diff --git a/tests/cocos_test.py b/tests/cocos_test.py index 8c46f3ea3..f557faaf0 100644 --- a/tests/cocos_test.py +++ b/tests/cocos_test.py @@ -103,7 +103,7 @@ def test_invalid_element_not_defined_in_scope(self): os.path.join(os.path.realpath(os.path.join(os.path.dirname(__file__), 'invalid')), 'CoCoVariableNotDefined.nestml')) self.assertEqual(len(Logger.get_all_messages_of_level_and_or_node(model.get_model_list()[0], - LoggingLevel.ERROR)), 4) + LoggingLevel.ERROR)), 5) def test_valid_element_not_defined_in_scope(self): Logger.set_logging_level(LoggingLevel.INFO) diff --git a/tests/invalid/CoCoResolutionLegallyUsed.nestml b/tests/invalid/CoCoResolutionLegallyUsed.nestml index 926e236c7..c7090282a 100644 --- a/tests/invalid/CoCoResolutionLegallyUsed.nestml +++ b/tests/invalid/CoCoResolutionLegallyUsed.nestml @@ -37,11 +37,13 @@ model resolution_legally_used_synapse: x' = -x / tau + (resolution() / ms**2) function test(tau ms) real: - w ms = resolution() - return w + z ms = resolution() + return z parameters: tau ms = 10 ms + w real = 1 # dummy weight variable + d ms = 1 ms # dummy delay variable update: integrate_odes() diff --git a/tests/invalid/stdp_synapse_missing_delay_decorator.nestml b/tests/invalid/stdp_synapse_missing_delay_decorator.nestml index d6c9903fe..8c6c03589 100644 --- a/tests/invalid/stdp_synapse_missing_delay_decorator.nestml +++ b/tests/invalid/stdp_synapse_missing_delay_decorator.nestml @@ -35,7 +35,7 @@ References """ model stdp_synapse: state: - w real = 1. @nest::weight # Synaptic weight + w real = 1 # Synaptic weight pre_trace real = 0. post_trace real = 0. diff --git a/tests/nest_compartmental_tests/cocos_test.py b/tests/nest_compartmental_tests/cocos_test.py index 4cbe63bd1..b3355d8e3 100644 --- a/tests/nest_compartmental_tests/cocos_test.py +++ b/tests/nest_compartmental_tests/cocos_test.py @@ -60,7 +60,7 @@ def test_invalid_cm_variables_declared(self): 'invalid')), 'CoCoCmVariablesDeclared.nestml')) self.assertEqual(len(Logger.get_all_messages_of_level_and_or_node( - model.get_model_list()[0], LoggingLevel.ERROR)), 4) + model.get_model_list()[0], LoggingLevel.ERROR)), 5) def test_valid_cm_variables_declared(self): Logger.set_logging_level(LoggingLevel.INFO) diff --git a/tests/nest_tests/delay_decorator_specified.py b/tests/nest_tests/delay_decorator_specified.py deleted file mode 100644 index 61d933cec..000000000 --- a/tests/nest_tests/delay_decorator_specified.py +++ /dev/null @@ -1,59 +0,0 @@ -# -*- coding: utf-8 -*- -# -# delay_decorator_specified.py -# -# This file is part of NEST. -# -# Copyright (C) 2004 The NEST Initiative -# -# NEST is free software: you can redistribute it and/or modify -# it under the terms of the GNU General Public License as published by -# the Free Software Foundation, either version 2 of the License, or -# (at your option) any later version. -# -# NEST is distributed in the hope that it will be useful, -# but WITHOUT ANY WARRANTY; without even the implied warranty of -# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the -# GNU General Public License for more details. -# -# You should have received a copy of the GNU General Public License -# along with NEST. If not, see . - -import os -import pytest - -from pynestml.frontend.pynestml_frontend import generate_nest_target - - -class TestDelayDecoratorSpecified: - - neuron_model_name = "iaf_psc_exp_neuron_nestml__with_stdp_nestml" - ref_neuron_model_name = "iaf_psc_exp_neuron_nestml_non_jit" - - synapse_model_name = "stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml" - ref_synapse_model_name = "stdp_synapse" - - @pytest.mark.xfail(strict=True) - def test_delay_decorator_not_specified_results_in_failure(self): - r"""Generate the model code""" - - jit_codegen_opts = {"neuron_synapse_pairs": [{"neuron": "iaf_psc_exp_neuron", - "synapse": "stdp_synapse", - "post_ports": ["post_spikes"]}]} - - files = [os.path.join("models", "neurons", "iaf_psc_exp_neuron.nestml"), - os.path.join("tests", "invalid", "stdp_synapse_missing_delay_decorator.nestml")] - # remove ``@nest::delay`` decorator from the file - with open(os.path.join("models", "synapses", "stdp_synapse.nestml"), "r") as syn_file: - lines = syn_file.read() - lines = lines.replace("@nest::delay", "") - with open(os.path.join("tests", "invalid", "stdp_synapse_missing_delay_decorator.nestml"), "w") as invalid_syn_file: - invalid_syn_file.writelines(lines) - input_path = [os.path.realpath(os.path.join(os.path.dirname(__file__), os.path.join( - os.pardir, os.pardir, s))) for s in files] - generate_nest_target(input_path=input_path, - target_path="/tmp/nestml-jit", - logging_level="INFO", - module_name="nestml_jit_module", - suffix="_nestml", - codegen_opts=jit_codegen_opts) diff --git a/tests/nest_tests/nest_custom_templates_test.py b/tests/nest_tests/nest_custom_templates_test.py index 471d9ebc4..c1a130dfc 100644 --- a/tests/nest_tests/nest_custom_templates_test.py +++ b/tests/nest_tests/nest_custom_templates_test.py @@ -107,6 +107,8 @@ def test_custom_templates_with_synapse(self): "neuron_synapse_pairs": [{"neuron": "iaf_psc_delta_neuron", "synapse": "stdp_triplet_synapse", "post_ports": ["post_spikes"]}], + "delay_variable": {"stdp_triplet_synapse": "d"}, + "weight_variable": {"stdp_triplet_synapse": "w"}, "templates": { "path": "resources_nest/point_neuron", "model_templates": { diff --git a/tests/nest_tests/nest_multithreading_test.py b/tests/nest_tests/nest_multithreading_test.py index b4ca5429a..c26231541 100644 --- a/tests/nest_tests/nest_multithreading_test.py +++ b/tests/nest_tests/nest_multithreading_test.py @@ -59,7 +59,9 @@ def nestml_generate_target(self) -> None: "neuron_parent_class_include": "structural_plasticity_node.h", "neuron_synapse_pairs": [{"neuron": "iaf_psc_exp_neuron", "synapse": "stdp_synapse", - "post_ports": ["post_spikes"]}]}) + "post_ports": ["post_spikes"]}], + "delay_variable": {"stdp_synapse": "d"}, + "weight_variable": {"stdp_synapse": "w"}}) # Neuron model generate_nest_target(input_path=neuron_path, diff --git a/tests/nest_tests/nest_resolution_builtin_test.py b/tests/nest_tests/nest_resolution_builtin_test.py index 27a3f39b9..d22e2ccb2 100644 --- a/tests/nest_tests/nest_resolution_builtin_test.py +++ b/tests/nest_tests/nest_resolution_builtin_test.py @@ -46,7 +46,9 @@ def setUp(self): codegen_opts={"neuron_parent_class": "StructuralPlasticityNode", "neuron_parent_class_include": "structural_plasticity_node.h", "neuron_synapse_pairs": [{"neuron": "iaf_psc_exp_resolution_test_neuron", - "synapse": "resolution_legally_used_synapse"}]}) + "synapse": "resolution_legally_used_synapse"}], + "delay_variable": {"resolution_legally_used_synapse": "d"}, + "weight_variable": {"resolution_legally_used_synapse": "w"}}) @pytest.mark.skipif(NESTTools.detect_nest_version().startswith("v2"), reason="This test does not support NEST 2") diff --git a/tests/nest_tests/nest_set_with_distribution_test.py b/tests/nest_tests/nest_set_with_distribution_test.py index dedba1c00..1e85ff2d1 100644 --- a/tests/nest_tests/nest_set_with_distribution_test.py +++ b/tests/nest_tests/nest_set_with_distribution_test.py @@ -40,7 +40,9 @@ def setUp(self): codegen_opts = {"neuron_synapse_pairs": [{"neuron": "iaf_psc_exp_neuron", "synapse": "stdp_synapse", - "post_ports": ["post_spikes"]}]} + "post_ports": ["post_spikes"]}], + "delay_variable": {"stdp_synapse": "d"}, + "weight_variable": {"stdp_synapse": "w"}} # generate the "jit" model (co-generated neuron and synapse), that does not rely on ArchivingNode files = [os.path.join("models", "neurons", "iaf_psc_exp_neuron.nestml"), diff --git a/tests/nest_tests/noisy_synapse_test.py b/tests/nest_tests/noisy_synapse_test.py index f157b5553..acf65c92a 100644 --- a/tests/nest_tests/noisy_synapse_test.py +++ b/tests/nest_tests/noisy_synapse_test.py @@ -52,7 +52,9 @@ def setUp(self): target_path="/tmp/nestml-noisy-synapse", logging_level="INFO", module_name="nestml_noisy_synapse_module", - suffix="_nestml") + suffix="_nestml", + codegen_opts={"delay_variable": {"noisy_synapse": "d"}, + "weight_variable": {"noisy_synapse": "w"}}) @pytest.mark.skipif(NESTTools.detect_nest_version().startswith("v2"), reason="This test does not support NEST 2") diff --git a/tests/nest_tests/resources/TimeVariablePrePostSynapse.nestml b/tests/nest_tests/resources/TimeVariablePrePostSynapse.nestml index 262d78dc5..d5cbd40b1 100644 --- a/tests/nest_tests/resources/TimeVariablePrePostSynapse.nestml +++ b/tests/nest_tests/resources/TimeVariablePrePostSynapse.nestml @@ -36,7 +36,8 @@ model time_variable_pre_post_synapse: z = t parameters: - d ms = 1 ms @nest::delay + w real = 1 + d ms = 1 ms input: pre_spikes <- spike diff --git a/tests/nest_tests/resources/TimeVariableSynapse.nestml b/tests/nest_tests/resources/TimeVariableSynapse.nestml index 41545a08b..da8bc81e8 100644 --- a/tests/nest_tests/resources/TimeVariableSynapse.nestml +++ b/tests/nest_tests/resources/TimeVariableSynapse.nestml @@ -32,7 +32,8 @@ model time_variable_synapse: y = t parameters: - d ms = 1 ms @nest::delay + w real = 1 + d ms = 1 ms input: pre_spikes <- spike diff --git a/tests/nest_tests/resources/delay_test_assigned_delay2_synapse.nestml b/tests/nest_tests/resources/delay_test_assigned_delay2_synapse.nestml new file mode 100644 index 000000000..bb382c0dc --- /dev/null +++ b/tests/nest_tests/resources/delay_test_assigned_delay2_synapse.nestml @@ -0,0 +1,17 @@ +""" +delay_test_assigned_delay2_synapse +################################## +""" +model delay_test_assigned_delay2_synapse: + state: + w real = 1 # Synaptic weight + delay ms = 1 ms # Synaptic transmission delay + + input: + pre_spikes <- spike + + output: + spike + + onReceive(pre_spikes): + emit_spike(w, d) diff --git a/tests/nest_tests/resources/delay_test_assigned_delay_synapse.nestml b/tests/nest_tests/resources/delay_test_assigned_delay_synapse.nestml new file mode 100644 index 000000000..23d1d4929 --- /dev/null +++ b/tests/nest_tests/resources/delay_test_assigned_delay_synapse.nestml @@ -0,0 +1,18 @@ +""" +delay_test_assigned_delay_synapse +################################# +""" +model delay_test_assigned_delay_synapse: + state: + w real = 1 # Synaptic weight + d ms = 1 ms # Synaptic transmission delay + + input: + pre_spikes <- spike + + output: + spike + + onReceive(pre_spikes): + d = 2 ms # not allowed! + emit_spike(w, d) diff --git a/tests/nest_tests/resources/delay_test_assigned_synapse.nestml b/tests/nest_tests/resources/delay_test_assigned_synapse.nestml new file mode 100644 index 000000000..3774d79e9 --- /dev/null +++ b/tests/nest_tests/resources/delay_test_assigned_synapse.nestml @@ -0,0 +1,18 @@ +""" +delay_test_assigned_synapse +########################### +""" +model delay_test_assigned_synapse: + state: + w real = 1 # Synaptic weight + d ms = 1 ms # Synaptic transmission delay + + input: + pre_spikes <- spike + + output: + spike + + onReceive(pre_spikes): + w = 2 + emit_spike(w, d) diff --git a/tests/nest_tests/resources/delay_test_plastic_synapse.nestml b/tests/nest_tests/resources/delay_test_plastic_synapse.nestml new file mode 100644 index 000000000..b639827cc --- /dev/null +++ b/tests/nest_tests/resources/delay_test_plastic_synapse.nestml @@ -0,0 +1,21 @@ +""" +delay_test_synapse_plastic +########################## +""" +model delay_test_plastic_synapse: + state: + x ms = 0 ms + w real = 1 # Synaptic weight + d ms = 1 ms # Synaptic transmission delay + + input: + pre_spikes <- spike + + output: + spike + + onReceive(pre_spikes): + emit_spike(w, d) + + update: + x = d diff --git a/tests/nest_tests/resources/delay_test_synapse.nestml b/tests/nest_tests/resources/delay_test_synapse.nestml new file mode 100644 index 000000000..3663d76ab --- /dev/null +++ b/tests/nest_tests/resources/delay_test_synapse.nestml @@ -0,0 +1,23 @@ +""" +delay_test_synapse +################## +""" +model delay_test_synapse: + state: + x ms = 0 ms + + parameters: + w real = 1 # Synaptic weight + d ms = 1 ms # Synaptic transmission delay + + input: + pre_spikes <- spike + + output: + spike + + onReceive(pre_spikes): + emit_spike(w, d) + + update: + x = d diff --git a/tests/nest_tests/resources/dopa_second_order_synapse.nestml b/tests/nest_tests/resources/dopa_second_order_synapse.nestml index 91531163a..662465217 100644 --- a/tests/nest_tests/resources/dopa_second_order_synapse.nestml +++ b/tests/nest_tests/resources/dopa_second_order_synapse.nestml @@ -37,7 +37,8 @@ model dopa_second_order_synapse: parameters: tau_dopa ms = 100 ms - d ms = 1 ms @nest::delay + w real = 1 + d ms = 1 ms equations: dopa_rate' = dopa_rate_d / ms diff --git a/tests/nest_tests/resources/homogeneous_parameters_synapse.nestml b/tests/nest_tests/resources/homogeneous_parameters_synapse.nestml index 7c48af662..4b6ead791 100644 --- a/tests/nest_tests/resources/homogeneous_parameters_synapse.nestml +++ b/tests/nest_tests/resources/homogeneous_parameters_synapse.nestml @@ -9,10 +9,10 @@ A synapse where the synaptic strength (weight) does not evolve with simulated ti model static_synapse: parameters: - w real = 900 @nest::weight @homogeneous - d ms = .9 ms @nest::delay @heterogeneous - a real = 3.141592653589793 @nest::a @homogeneous - b real = 100. @nest::b @heterogeneous + w real = 900 @homogeneous + d ms = .9 ms @heterogeneous + a real = 3.141592653589793 @homogeneous + b real = 100. @heterogeneous input: pre_spikes <- spike diff --git a/tests/nest_tests/resources/weight_test_assigned_synapse.nestml b/tests/nest_tests/resources/weight_test_assigned_synapse.nestml new file mode 100644 index 000000000..1737c4c57 --- /dev/null +++ b/tests/nest_tests/resources/weight_test_assigned_synapse.nestml @@ -0,0 +1,18 @@ +""" +weight_test_assigned_synapse +########################### +""" +model weight_test_assigned_synapse: + state: + w real = 1 # Synaptic weight + d ms = 1 ms # Synaptic transmission delay + + input: + pre_spikes <- spike + + output: + spike + + onReceive(pre_spikes): + w = 2 + emit_spike(w, d) diff --git a/tests/nest_tests/resources/weight_test_plastic_synapse.nestml b/tests/nest_tests/resources/weight_test_plastic_synapse.nestml new file mode 100644 index 000000000..8860a472c --- /dev/null +++ b/tests/nest_tests/resources/weight_test_plastic_synapse.nestml @@ -0,0 +1,21 @@ +""" +weight_test_plastic_synapse +########################### +""" +model weight_test_plastic_synapse: + state: + x real = 0 + w real = 1 # Synaptic weight + d ms = 1 ms # Synaptic transmission delay + + input: + pre_spikes <- spike + + output: + spike + + onReceive(pre_spikes): + emit_spike(w, d) + + update: + x = w diff --git a/tests/nest_tests/stdp_neuromod_test.py b/tests/nest_tests/stdp_neuromod_test.py index d5b3d1ae8..bf3cf33f2 100644 --- a/tests/nest_tests/stdp_neuromod_test.py +++ b/tests/nest_tests/stdp_neuromod_test.py @@ -69,7 +69,9 @@ def setUp(self): "neuron_synapse_pairs": [{"neuron": "iaf_psc_exp_neuron", "synapse": "neuromodulated_stdp_synapse", "post_ports": ["post_spikes"], - "vt_ports": ["mod_spikes"]}]}) + "vt_ports": ["mod_spikes"]}], + "delay_variable": {"neuromodulated_stdp_synapse": "d"}, + "weight_variable": {"neuromodulated_stdp_synapse": "w"}}) generate_nest_target(input_path=os.path.realpath(os.path.join(os.path.dirname(__file__), os.path.join(os.pardir, os.pardir, "models", "neurons", "iaf_psc_exp_neuron.nestml"))), diff --git a/tests/nest_tests/stdp_nn_pre_centered_test.py b/tests/nest_tests/stdp_nn_pre_centered_test.py index 1cd44217a..a7474a4f3 100644 --- a/tests/nest_tests/stdp_nn_pre_centered_test.py +++ b/tests/nest_tests/stdp_nn_pre_centered_test.py @@ -67,7 +67,9 @@ def setUp(self): "neuron_parent_class_include": "structural_plasticity_node.h", "neuron_synapse_pairs": [{"neuron": "iaf_psc_exp_neuron", "synapse": "stdp_nn_pre_centered_synapse", - "post_ports": ["post_spikes"]}]}) + "post_ports": ["post_spikes"]}], + "delay_variable": {"stdp_nn_pre_centered_synapse": "d"}, + "weight_variable": {"stdp_nn_pre_centered_synapse": "w"}}) # generate the "non-jit" model, that relies on ArchivingNode generate_nest_target(input_path=os.path.realpath(os.path.join(os.path.dirname(__file__), diff --git a/tests/nest_tests/stdp_nn_restr_symm_test.py b/tests/nest_tests/stdp_nn_restr_symm_test.py index a89ad4c3e..dc5b72f49 100644 --- a/tests/nest_tests/stdp_nn_restr_symm_test.py +++ b/tests/nest_tests/stdp_nn_restr_symm_test.py @@ -67,7 +67,9 @@ def setUp(self): "neuron_parent_class_include": "structural_plasticity_node.h", "neuron_synapse_pairs": [{"neuron": "iaf_psc_exp_neuron", "synapse": "stdp_nn_restr_symm_synapse", - "post_ports": ["post_spikes"]}]}) + "post_ports": ["post_spikes"]}], + "delay_variable": {"stdp_nn_restr_symm_synapse": "d"}, + "weight_variable": {"stdp_nn_restr_symm_synapse": "w"}}) # generate the "non-jit" model, that relies on ArchivingNode generate_nest_target(input_path=os.path.realpath(os.path.join(os.path.dirname(__file__), diff --git a/tests/nest_tests/stdp_nn_synapse_test.py b/tests/nest_tests/stdp_nn_synapse_test.py index 2bd709266..594fcf156 100644 --- a/tests/nest_tests/stdp_nn_synapse_test.py +++ b/tests/nest_tests/stdp_nn_synapse_test.py @@ -67,7 +67,9 @@ def setUp(self): "neuron_parent_class_include": "structural_plasticity_node.h", "neuron_synapse_pairs": [{"neuron": "iaf_psc_exp_neuron", "synapse": "stdp_nn_symm_synapse", - "post_ports": ["post_spikes"]}]}) + "post_ports": ["post_spikes"]}], + "delay_variable": {"stdp_nn_symm_synapse": "d"}, + "weight_variable": {"stdp_nn_symm_synapse": "w"}}) # generate the "non-jit" model, that relies on ArchivingNode generate_nest_target(input_path=os.path.realpath(os.path.join(os.path.dirname(__file__), diff --git a/tests/nest_tests/stdp_synapse_test.py b/tests/nest_tests/stdp_synapse_test.py index 29a3fb8cd..e6ec31cb9 100644 --- a/tests/nest_tests/stdp_synapse_test.py +++ b/tests/nest_tests/stdp_synapse_test.py @@ -58,7 +58,9 @@ def generate_model_code(self): jit_codegen_opts = {"neuron_synapse_pairs": [{"neuron": "iaf_psc_exp_neuron", "synapse": "stdp_synapse", - "post_ports": ["post_spikes"]}]} + "post_ports": ["post_spikes"]}], + "delay_variable": {"stdp_synapse": "d"}, + "weight_variable": {"stdp_synapse": "w"}} if not NESTTools.detect_nest_version().startswith("v2"): jit_codegen_opts["neuron_parent_class"] = "StructuralPlasticityNode" jit_codegen_opts["neuron_parent_class_include"] = "structural_plasticity_node.h" diff --git a/tests/nest_tests/stdp_triplet_synapse_test.py b/tests/nest_tests/stdp_triplet_synapse_test.py index b21949d15..28a9402e9 100644 --- a/tests/nest_tests/stdp_triplet_synapse_test.py +++ b/tests/nest_tests/stdp_triplet_synapse_test.py @@ -55,7 +55,9 @@ def nestml_generate_target(): "neuron_parent_class_include": "structural_plasticity_node.h", "neuron_synapse_pairs": [{"neuron": "iaf_psc_delta_neuron", "synapse": "stdp_triplet_synapse", - "post_ports": ["post_spikes"]}]}) + "post_ports": ["post_spikes"]}], + "delay_variable": {"stdp_triplet_synapse": "d"}, + "weight_variable": {"stdp_triplet_synapse": "w"}}) def get_trace_at(t, t_spikes, tau, initial=0., increment=1., before_increment=False, extra_debug=False): diff --git a/tests/nest_tests/stdp_window_test.py b/tests/nest_tests/stdp_window_test.py index 9723c3108..7b3922928 100644 --- a/tests/nest_tests/stdp_window_test.py +++ b/tests/nest_tests/stdp_window_test.py @@ -57,7 +57,9 @@ def nestml_generate_target(): "post_ports": ["post_spikes"]}, {"neuron": "izhikevich_neuron", "synapse": "stdp_synapse", - "post_ports": ["post_spikes"]}]}) + "post_ports": ["post_spikes"]}], + "delay_variable": {"stdp_synapse": "d"}, + "weight_variable": {"stdp_synapse": "w"}}) def run_stdp_network(pre_spike_time, post_spike_time, @@ -85,12 +87,11 @@ def run_stdp_network(pre_spike_time, post_spike_time, wr = nest.Create("weight_recorder") if "__with" in synapse_model_name: weight_variable_name = "w" - nest.CopyModel(synapse_model_name, "stdp_nestml_rec", - {"weight_recorder": wr[0], weight_variable_name: 1., "delay": delay, "d": delay, "receptor_type": 0, "mu_minus": 0., "mu_plus": 0.}) else: weight_variable_name = "weight" - nest.CopyModel(synapse_model_name, "stdp_nestml_rec", - {"weight_recorder": wr[0], weight_variable_name: 1., "delay": delay, "receptor_type": 0, "mu_minus": 0., "mu_plus": 0.}) + + nest.CopyModel(synapse_model_name, "stdp_nestml_rec", + {"weight_recorder": wr[0], weight_variable_name: 1., "delay": delay, "receptor_type": 0, "mu_minus": 0., "mu_plus": 0.}) # create spike_generators with these times pre_sg = nest.Create("spike_generator", diff --git a/tests/nest_tests/test_delay_variable_specified.py b/tests/nest_tests/test_delay_variable_specified.py new file mode 100644 index 000000000..8d029add9 --- /dev/null +++ b/tests/nest_tests/test_delay_variable_specified.py @@ -0,0 +1,182 @@ +# -*- coding: utf-8 -*- +# +# test_delay_variable_specified.py +# +# This file is part of NEST. +# +# Copyright (C) 2004 The NEST Initiative +# +# NEST is free software: you can redistribute it and/or modify +# it under the terms of the GNU General Public License as published by +# the Free Software Foundation, either version 2 of the License, or +# (at your option) any later version. +# +# NEST is distributed in the hope that it will be useful, +# but WITHOUT ANY WARRANTY; without even the implied warranty of +# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +# GNU General Public License for more details. +# +# You should have received a copy of the GNU General Public License +# along with NEST. If not, see . + +import numpy as np +import os +import pytest + +import nest +from nest.lib.hl_api_exceptions import NESTErrors + +from pynestml.frontend.pynestml_frontend import generate_nest_target +from pynestml.codegeneration.nest_tools import NESTTools + + +class TestDelayVariableSpecified: + r"""Test that forgetting to specify the ``delay_variable`` when using a synapse results in failure to generate code.""" + + @pytest.mark.xfail(strict=True) + def test_delay_variable_not_specified_results_in_failure(self): + r"""Generate the model code""" + + files = [os.path.join("models", "neurons", "iaf_psc_exp_neuron.nestml"), + os.path.join("models", "synapses", "stdp_synapse.nestml")] + input_path = [os.path.realpath(os.path.join(os.path.dirname(__file__), os.path.join(os.pardir, os.pardir, s))) for s in files] + generate_nest_target(input_path=input_path, + logging_level="DEBUG", + suffix="_nestml", + codegen_opts={"neuron_synapse_pairs": [{"neuron": "iaf_psc_exp_neuron", + "synapse": "stdp_synapse", + "post_ports": ["post_spikes"]}], + "weight_variable": {"stdp_synapse": "w"}}) + + +@pytest.mark.skipif(NESTTools.detect_nest_version().startswith("v2"), + reason="This test does not support NEST 2") +class TestSynapseDelayGetSet: + """Check that we can get and set the delay parameter of a synapse""" + + @pytest.fixture(scope="module", autouse=True) + def setUp(self): + input_path = [os.path.realpath(os.path.join(os.path.dirname(__file__), os.path.join(os.pardir, os.pardir, "models", "neurons", "iaf_psc_exp_neuron.nestml"))), + os.path.realpath(os.path.join(os.path.dirname(__file__), os.path.join(os.pardir, os.pardir, "models", "synapses", "stdp_synapse.nestml"))), + os.path.join(os.path.realpath(os.path.join(os.path.dirname(__file__), "resources", "delay_test_synapse.nestml"))), + os.path.join(os.path.realpath(os.path.join(os.path.dirname(__file__), "resources", "delay_test_assigned_synapse.nestml"))), + os.path.join(os.path.realpath(os.path.join(os.path.dirname(__file__), "resources", "delay_test_assigned_delay2_synapse.nestml"))), + os.path.join(os.path.realpath(os.path.join(os.path.dirname(__file__), "resources", "delay_test_plastic_synapse.nestml")))] + logging_level = "DEBUG" + suffix = "_nestml" + + nest.set_verbosity("M_ALL") + + generate_nest_target(input_path, + logging_level=logging_level, + suffix=suffix, + codegen_opts={"neuron_parent_class": "StructuralPlasticityNode", + "neuron_parent_class_include": "structural_plasticity_node.h", + "neuron_synapse_pairs": [{"neuron": "iaf_psc_exp_neuron", + "synapse": "stdp_synapse", + "post_ports": ["post_spikes"]}, + {"neuron": "iaf_psc_exp_neuron", + "synapse": "delay_test_assigned_delay2_synapse"}], + "delay_variable": {"delay_test_synapse": "d", + "delay_test_plastic_synapse": "d", + "delay_test_assigned_delay2_synapse": "delay", + "delay_test_assigned_synapse": "d", + "stdp_synapse": "d"}, + "weight_variable": {"delay_test_synapse": "w", + "delay_test_plastic_synapse": "w", + "delay_test_assigned_delay2_synapse": "w", + "delay_test_assigned_synapse": "w", + "stdp_synapse": "w"}}) + + @pytest.mark.xfail(strict=True, raises=NESTErrors.BadProperty) + def test_synapse_delay_set_status1(self): + nest.ResetKernel() + nest.Install("nestmlmodule") + + nrn = nest.Create("iaf_psc_exp_neuron_nestml__with_stdp_synapse_nestml") + nest.Connect(nrn, nrn, syn_spec={"synapse_model": "stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml"}) + syn = nest.GetConnections(nrn, nrn) + assert len(syn) == 1 + nest.SetStatus(syn, {"d": 42., "delay": 123.}) + + def test_synapse_delay_set_status(self): + nest.ResetKernel() + nest.Install("nestmlmodule") + + nrn = nest.Create("iaf_psc_exp_neuron_nestml__with_stdp_synapse_nestml") + nest.Connect(nrn, nrn, syn_spec={"synapse_model": "stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml", "delay": 42.}) + syn = nest.GetConnections(nrn, nrn) + assert len(syn) == 1 + np.testing.assert_allclose(syn[0].get("delay"), 42.) + syn.delay = 123. + np.testing.assert_allclose(syn[0].get("delay"), 123.) + + def test_synapse_delay_creation_alt1(self): + nest.ResetKernel() + nest.Install("nestmlmodule") + + nrn = nest.Create("iaf_psc_exp_neuron_nestml__with_stdp_synapse_nestml") + nest.Connect(nrn, nrn, syn_spec={"synapse_model": "stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml", "d": 42.}) + syn = nest.GetConnections(nrn, nrn) + np.testing.assert_allclose(syn[0].get("delay"), 42.) + np.testing.assert_allclose(syn[0].get("d"), 42.) + + def test_synapse_delay_creation_alt2(self): + nest.ResetKernel() + nest.Install("nestmlmodule") + + nrn = nest.Create("iaf_psc_exp_neuron_nestml__with_stdp_synapse_nestml") + nest.Connect(nrn, nrn, syn_spec={"synapse_model": "stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml", "delay": 42.}) + syn = nest.GetConnections(nrn, nrn) + np.testing.assert_allclose(syn[0].get("delay"), 42.) + np.testing.assert_allclose(syn[0].get("d"), 42.) + + def test_synapse_delay_creation_alt2(self): + nest.ResetKernel() + nest.Install("nestmlmodule") + + nrn = nest.Create("iaf_psc_exp_neuron_nestml__with_delay_test_assigned_delay2_synapse_nestml") + nest.Connect(nrn, nrn, syn_spec={"synapse_model": "delay_test_assigned_delay2_synapse_nestml__with_iaf_psc_exp_neuron_nestml", "delay": 42.}) + syn = nest.GetConnections(nrn, nrn) + np.testing.assert_allclose(syn[0].get("delay"), 42.) + syn.delay = 123. + np.testing.assert_allclose(syn[0].get("delay"), 123.) + + @pytest.mark.parametrize("synapse_model_name", ["delay_test_synapse_nestml", "delay_test_plastic_synapse_nestml"]) + def test_synapse_delay(self, synapse_model_name: str): + """Check that the synapse can itself access the set delay value properly""" + nest.ResetKernel() + nest.Install("nestmlmodule") + + nrn = nest.Create("iaf_psc_exp") + nrn.I_e = 1000. # [pA] -- assure there are pre spikes to trigger synapse update + nest.Connect(nrn, nrn, syn_spec={"synapse_model": synapse_model_name}) + syn = nest.GetConnections(nrn, nrn) + syn[0].delay = 42. + syn = nest.GetConnections(nrn, nrn) + assert len(syn) == 1 + nest.Simulate(100.) + np.testing.assert_allclose(syn[0].get("delay"), 42.) + np.testing.assert_allclose(syn[0].get("x"), 42.) + syn.delay = 21. + nest.Simulate(100.) + np.testing.assert_allclose(syn[0].get("delay"), 21.) + np.testing.assert_allclose(syn[0].get("x"), 21.) + + @pytest.mark.xfail(strict=True, raises=Exception) + def test_cannot_assign_to_delay_parameter(self): + r"""Test that delay parameter cannot be assigned to from inside the NESTML model""" + input_path = [os.path.realpath(os.path.join(os.path.dirname(__file__), os.path.join(os.pardir, os.pardir, "models", "neurons", "iaf_psc_exp_neuron.nestml"))), + os.path.join(os.path.realpath(os.path.join(os.path.dirname(__file__), "resources", "delay_test_assigned_delay_synapse.nestml")))] + logging_level = "DEBUG" + suffix = "_nestml" + + generate_nest_target(input_path, + logging_level=logging_level, + suffix=suffix, + codegen_opts={"neuron_parent_class": "StructuralPlasticityNode", + "neuron_parent_class_include": "structural_plasticity_node.h", + "neuron_synapse_pairs": [{"neuron": "iaf_psc_exp_neuron", + "synapse": "delay_test_assigned_delay_synapse"}], + "delay_variable": {"delay_test_assigned_delay_synapse": "d"}, + "weight_variable": {"delay_test_assigned_delay_synapse": "w"}}) diff --git a/tests/nest_tests/test_dopa_second_order_synapse.py b/tests/nest_tests/test_dopa_second_order_synapse.py index aef6a36e2..4758f414e 100644 --- a/tests/nest_tests/test_dopa_second_order_synapse.py +++ b/tests/nest_tests/test_dopa_second_order_synapse.py @@ -61,11 +61,13 @@ def setUp(self): "neuron_parent_class_include": "structural_plasticity_node.h", "neuron_synapse_pairs": [{"neuron": "iaf_psc_exp_neuron", "synapse": "dopa_second_order_synapse", - "vt_ports": ["dopa_spikes"]}]}) + "vt_ports": ["dopa_spikes"]}], + "delay_variable": {"dopa_second_order_synapse": "d"}, + "weight_variable": {"dopa_second_order_synapse": "w"}}) @pytest.mark.skipif(NESTTools.detect_nest_version().startswith("v2"), reason="This test does not support NEST 2") - def test_nest_stdp_synapse(self): + def test_synapse(self): resolution = .25 # [ms] delay = 1. # [ms] diff --git a/tests/nest_tests/test_homogeneous_parameters_synapse.py b/tests/nest_tests/test_homogeneous_parameters_synapse.py index 179fb5db7..d41960b25 100644 --- a/tests/nest_tests/test_homogeneous_parameters_synapse.py +++ b/tests/nest_tests/test_homogeneous_parameters_synapse.py @@ -54,7 +54,9 @@ def setUp(self): generate_nest_target(input_path=input_path, logging_level="INFO", module_name="nestmlmodule", - suffix="_nestml") + suffix="_nestml", + codegen_opts={"delay_variable": {"static_synapse": "d"}, + "weight_variable": {"static_synapse": "w"}}) def test_homogeneous_parameters_synapse(self): @@ -67,6 +69,8 @@ def test_homogeneous_parameters_synapse(self): nest.SetKernelStatus({"resolution": .1}) nest.Install("nestmlmodule") + nest.CopyModel(synapse_model_name, "my_synapse_model", {"w": 1., "a": 42.}) + # create spike_generators with these times pre_sg = nest.Create("spike_generator", params={"spike_times": 10. * (1 + np.arange(sim_time))}) @@ -75,7 +79,7 @@ def test_homogeneous_parameters_synapse(self): post_neuron = nest.Create(neuron_model_name) nest.Connect(pre_sg, pre_neuron, "one_to_one") - nest.Connect(pre_neuron, post_neuron, "all_to_all", syn_spec={"synapse_model": synapse_model_name}) + nest.Connect(pre_neuron, post_neuron, "all_to_all", syn_spec={"synapse_model": "my_synapse_model"}) V_m_before_sim = post_neuron.V_m diff --git a/tests/nest_tests/test_ignore_and_fire.py b/tests/nest_tests/test_ignore_and_fire.py index bda6abbee..e5737c246 100644 --- a/tests/nest_tests/test_ignore_and_fire.py +++ b/tests/nest_tests/test_ignore_and_fire.py @@ -49,7 +49,9 @@ def setUp(self): codegen_opts = {"neuron_synapse_pairs": [{"neuron": "ignore_and_fire_neuron", "synapse": "stdp_synapse", - "post_ports": ["post_spikes"]}]} + "post_ports": ["post_spikes"]}], + "delay_variable": {"stdp_synapse": "d"}, + "weight_variable": {"stdp_synapse": "w"}} files = [os.path.join("models", "neurons", "ignore_and_fire_neuron.nestml"), os.path.join("models", "synapses", "stdp_synapse.nestml")] diff --git a/tests/nest_tests/test_priority_synapse.py b/tests/nest_tests/test_priority_synapse.py index 3555554c1..a6d9743b8 100644 --- a/tests/nest_tests/test_priority_synapse.py +++ b/tests/nest_tests/test_priority_synapse.py @@ -59,7 +59,11 @@ def setUp(self): "post_ports": ["post_spikes"]}, {"neuron": "iaf_psc_delta_neuron", "synapse": "event_inv_priority_test_synapse", - "post_ports": ["post_spikes"]}]}) + "post_ports": ["post_spikes"]}], + "delay_variable": {"event_priority_test_synapse": "d", + "event_inv_priority_test_synapse": "d"}, + "weight_variable": {"event_priority_test_synapse": "w", + "event_inv_priority_test_synapse": "w"}}) @pytest.mark.skipif(NESTTools.detect_nest_version().startswith("v2"), reason="This test does not support NEST 2") diff --git a/tests/nest_tests/test_static_synapse.py b/tests/nest_tests/test_static_synapse.py index 1357a3352..9763b5985 100644 --- a/tests/nest_tests/test_static_synapse.py +++ b/tests/nest_tests/test_static_synapse.py @@ -47,7 +47,11 @@ def setUp(self): generate_nest_target(input_path=input_path, logging_level="DEBUG", module_name="nestmlmodule", - suffix="_nestml") + suffix="_nestml", + codegen_opts={"delay_variable": {"static_synapse": "d", + "noisy_synapse": "d"}, + "weight_variable": {"static_synapse": "w", + "noisy_synapse": "w"}}) @pytest.mark.parametrize("synapse_model_name", ["static_synapse_nestml", "noisy_synapse_nestml"]) def test_static_synapse(self, synapse_model_name: str): @@ -81,6 +85,7 @@ def test_static_synapse(self, synapse_model_name: str): V_m_before_sim = post_neuron.V_m syn = nest.GetConnections(source=pre_neuron, synapse_model="syn_nestml_rec") + assert syn.weight == 1. nest.Simulate(sim_time) diff --git a/tests/nest_tests/test_time_variable.py b/tests/nest_tests/test_time_variable.py index 4e3752898..5c6861400 100644 --- a/tests/nest_tests/test_time_variable.py +++ b/tests/nest_tests/test_time_variable.py @@ -53,7 +53,11 @@ def setUp(self): suffix=suffix, codegen_opts={"neuron_synapse_pairs": [{"neuron": "iaf_psc_delta_neuron", "synapse": "time_variable_pre_post_synapse", - "post_ports": ["post_spikes"]}]}) + "post_ports": ["post_spikes"]}], + "delay_variable": {"time_variable_synapse": "d", + "time_variable_pre_post_synapse": "d"}, + "weight_variable": {"time_variable_synapse": "w", + "time_variable_pre_post_synapse": "w"}}) def test_time_variable_neuron(self): nest.ResetKernel() diff --git a/tests/nest_tests/test_weight_variable_specified.py b/tests/nest_tests/test_weight_variable_specified.py new file mode 100644 index 000000000..15f990fd7 --- /dev/null +++ b/tests/nest_tests/test_weight_variable_specified.py @@ -0,0 +1,154 @@ +# -*- coding: utf-8 -*- +# +# test_weight_variable_specified.py +# +# This file is part of NEST. +# +# Copyright (C) 2004 The NEST Initiative +# +# NEST is free software: you can redistribute it and/or modify +# it under the terms of the GNU General Public License as published by +# the Free Software Foundation, either version 2 of the License, or +# (at your option) any later version. +# +# NEST is distributed in the hope that it will be useful, +# but WITHOUT ANY WARRANTY; without even the implied warranty of +# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +# GNU General Public License for more details. +# +# You should have received a copy of the GNU General Public License +# along with NEST. If not, see . + +import numpy as np +import os +import pytest + +import nest +from nest.lib.hl_api_exceptions import NESTErrors + +from pynestml.frontend.pynestml_frontend import generate_nest_target +from pynestml.codegeneration.nest_tools import NESTTools + + +class TestWeightVariableSpecified: + r"""Test that forgetting to specify the ``weight_variable`` when using a synapse results in failure to generate code.""" + + @pytest.mark.xfail(strict=True) + def test_weight_variable_not_specified_results_in_failure(self): + r"""Generate the model code""" + + files = [os.path.join("models", "neurons", "iaf_psc_exp_neuron.nestml"), + os.path.join("models", "synapses", "stdp_synapse.nestml")] + input_path = [os.path.realpath(os.path.join(os.path.dirname(__file__), os.path.join(os.pardir, os.pardir, s))) for s in files] + generate_nest_target(input_path=input_path, + logging_level="DEBUG", + suffix="_nestml", + codegen_opts={"neuron_synapse_pairs": [{"neuron": "iaf_psc_exp_neuron", + "synapse": "stdp_synapse", + "post_ports": ["post_spikes"]}], + "delay_variable": {"stdp_synapse": "d"}}) + + +@pytest.mark.skipif(NESTTools.detect_nest_version().startswith("v2"), + reason="This test does not support NEST 2") +class TestSynapseWeightGetSet: + """Check that we can get and set the weight parameter of a synapse""" + + @pytest.fixture(scope="module", autouse=True) + def setUp(self): + input_path = [os.path.realpath(os.path.join(os.path.dirname(__file__), os.path.join(os.pardir, os.pardir, "models", "neurons", "iaf_psc_exp_neuron.nestml"))), + os.path.realpath(os.path.join(os.path.dirname(__file__), os.path.join(os.pardir, os.pardir, "models", "synapses", "stdp_synapse.nestml"))), + os.path.join(os.path.realpath(os.path.join(os.path.dirname(__file__), "resources", "weight_test_assigned_synapse.nestml"))), + os.path.join(os.path.realpath(os.path.join(os.path.dirname(__file__), "resources", "weight_test_plastic_synapse.nestml")))] + logging_level = "DEBUG" + suffix = "_nestml" + + nest.set_verbosity("M_ALL") + + generate_nest_target(input_path, + logging_level=logging_level, + suffix=suffix, + codegen_opts={"neuron_parent_class": "StructuralPlasticityNode", + "neuron_parent_class_include": "structural_plasticity_node.h", + "neuron_synapse_pairs": [{"neuron": "iaf_psc_exp_neuron", + "synapse": "stdp_synapse", + "post_ports": ["post_spikes"]}], + "delay_variable": {"weight_test_plastic_synapse": "d", + "weight_test_assigned_synapse": "d", + "stdp_synapse": "d"}, + "weight_variable": {"weight_test_plastic_synapse": "w", + "weight_test_assigned_synapse": "w", + "stdp_synapse": "w"}}) + + @pytest.mark.xfail(strict=True, raises=NESTErrors.BadProperty) + def test_synapse_weight_set_status1(self): + nest.ResetKernel() + nest.Install("nestmlmodule") + + nrn = nest.Create("iaf_psc_exp_neuron_nestml__with_stdp_synapse_nestml") + nest.Connect(nrn, nrn, syn_spec={"synapse_model": "stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml", "weight": 42., "w": 123.}) + + @pytest.mark.xfail(strict=True) + def test_synapse_weight_set_status1(self): + nest.ResetKernel() + nest.Install("nestmlmodule") + + nrn = nest.Create("iaf_psc_exp_neuron_nestml__with_stdp_synapse_nestml") + nest.Connect(nrn, nrn, syn_spec={"synapse_model": "stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml"}) + syn = nest.GetConnections(nrn, nrn) + assert len(syn) == 1 + nest.SetStatus(syn, {"w": 42., "weight": 123.}) + + def test_synapse_weight_set_status(self): + nest.ResetKernel() + nest.Install("nestmlmodule") + + nrn = nest.Create("iaf_psc_exp_neuron_nestml__with_stdp_synapse_nestml") + nest.Connect(nrn, nrn, syn_spec={"synapse_model": "stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml", "weight": 42.}) + syn = nest.GetConnections(nrn, nrn) + assert len(syn) == 1 + np.testing.assert_allclose(syn[0].get("w"), 42.) + np.testing.assert_allclose(syn[0].get("weight"), 42.) + syn.w = 123. + np.testing.assert_allclose(syn[0].get("w"), 123.) + np.testing.assert_allclose(syn[0].get("weight"), 123.) + syn.weight = 3.14159 + np.testing.assert_allclose(syn[0].get("w"), 3.14159) + np.testing.assert_allclose(syn[0].get("weight"), 3.14159) + + def test_synapse_weight_set_status_alt(self): + nest.ResetKernel() + nest.Install("nestmlmodule") + + nrn = nest.Create("iaf_psc_exp_neuron_nestml__with_stdp_synapse_nestml") + nest.Connect(nrn, nrn, syn_spec={"synapse_model": "stdp_synapse_nestml__with_iaf_psc_exp_neuron_nestml", "w": 42.}) + syn = nest.GetConnections(nrn, nrn) + assert len(syn) == 1 + np.testing.assert_allclose(syn[0].get("w"), 42.) + np.testing.assert_allclose(syn[0].get("weight"), 42.) + syn.w = 123. + np.testing.assert_allclose(syn[0].get("w"), 123.) + np.testing.assert_allclose(syn[0].get("weight"), 123.) + syn.weight = 3.14159 + np.testing.assert_allclose(syn[0].get("w"), 3.14159) + np.testing.assert_allclose(syn[0].get("weight"), 3.14159) + + @pytest.mark.parametrize("synapse_model_name", ["weight_test_plastic_synapse_nestml"]) + def test_synapse_weight(self, synapse_model_name: str): + """Check that the synapse can itself access the set weight value properly""" + nest.ResetKernel() + nest.Install("nestmlmodule") + + nrn = nest.Create("iaf_psc_exp") + nrn.I_e = 1000. # [pA] -- assure there are pre spikes to trigger synapse update + nest.Connect(nrn, nrn, syn_spec={"synapse_model": synapse_model_name}) + syn = nest.GetConnections(nrn, nrn) + assert len(syn) == 1 + syn[0].weight = 42. + nest.Simulate(100.) + np.testing.assert_allclose(syn[0].get("weight"), 42.) + np.testing.assert_allclose(syn[0].get("x"), 42.) + syn.weight = 21. + nest.Simulate(100.) + np.testing.assert_allclose(syn[0].get("weight"), 21.) + np.testing.assert_allclose(syn[0].get("x"), 21.) diff --git a/tests/nest_tests/third_factor_stdp_synapse_test.py b/tests/nest_tests/third_factor_stdp_synapse_test.py index d2980ebe6..228cb7d75 100644 --- a/tests/nest_tests/third_factor_stdp_synapse_test.py +++ b/tests/nest_tests/third_factor_stdp_synapse_test.py @@ -50,7 +50,9 @@ def setUp(self): codegen_opts = {"neuron_synapse_pairs": [{"neuron": "iaf_psc_exp_dend_neuron", "synapse": "third_factor_stdp_synapse", "post_ports": ["post_spikes", - ["I_post_dend", "I_dend"]]}]} + ["I_post_dend", "I_dend"]]}], + "delay_variable": {"third_factor_stdp_synapse": "d"}, + "weight_variable": {"third_factor_stdp_synapse": "w"}} if not NESTTools.detect_nest_version().startswith("v2"): codegen_opts["neuron_parent_class"] = "StructuralPlasticityNode" diff --git a/tests/resources/SynapseEventSequenceTest.nestml b/tests/resources/SynapseEventSequenceTest.nestml index 02f8a38ee..1e5826b3d 100644 --- a/tests/resources/SynapseEventSequenceTest.nestml +++ b/tests/resources/SynapseEventSequenceTest.nestml @@ -30,6 +30,10 @@ You should have received a copy of the GNU General Public License along with NEST. If not, see . """ model event_sequence_test_synapse: + parameters: + w real = 1 + d ms = 1 ms + state: tr real = 1. diff --git a/tests/resources/neuron_event_inv_priority_test.nestml b/tests/resources/neuron_event_inv_priority_test.nestml index c6a7145fe..5a58abab7 100644 --- a/tests/resources/neuron_event_inv_priority_test.nestml +++ b/tests/resources/neuron_event_inv_priority_test.nestml @@ -34,7 +34,8 @@ model event_inv_priority_test_neuron: tr real = 1. parameters: - d ms = 1. ms @nest::delay + w real = 1 + d ms = 1 ms input: in_port1 <- spike diff --git a/tests/resources/neuron_event_priority_test.nestml b/tests/resources/neuron_event_priority_test.nestml index 5ea640ab1..20fb6f018 100644 --- a/tests/resources/neuron_event_priority_test.nestml +++ b/tests/resources/neuron_event_priority_test.nestml @@ -34,7 +34,8 @@ model event_priority_test_neuron: tr real = 1. parameters: - d ms = 1. ms @nest::delay + w real = 1 + d ms = 1 ms input: in_port1 <- spike diff --git a/tests/resources/synapse_event_inv_priority_test.nestml b/tests/resources/synapse_event_inv_priority_test.nestml index ad6977b86..e8ae16242 100644 --- a/tests/resources/synapse_event_inv_priority_test.nestml +++ b/tests/resources/synapse_event_inv_priority_test.nestml @@ -34,8 +34,8 @@ model event_inv_priority_test_synapse: tr real = 1. parameters: - w real = 1. @nest::weight - d ms = 1. ms @nest::delay + w real = 1 + d ms = 1 ms input: pre_spikes <- spike diff --git a/tests/resources/synapse_event_priority_test.nestml b/tests/resources/synapse_event_priority_test.nestml index ab7e2882a..e8aae17b2 100644 --- a/tests/resources/synapse_event_priority_test.nestml +++ b/tests/resources/synapse_event_priority_test.nestml @@ -34,8 +34,8 @@ model event_priority_test_synapse: tr real = 1. parameters: - w real = 1. @nest::weight - d ms = 1. ms @nest::delay + w real = 1 + d ms = 1 ms input: pre_spikes <- spike diff --git a/tests/valid/CoCoResolutionLegallyUsed.nestml b/tests/valid/CoCoResolutionLegallyUsed.nestml index ff08834d5..9be89fe2d 100644 --- a/tests/valid/CoCoResolutionLegallyUsed.nestml +++ b/tests/valid/CoCoResolutionLegallyUsed.nestml @@ -31,7 +31,8 @@ along with NEST. If not, see . """ model resolution_legally_used_synapse: parameters: - d ms = 1 ms @nest::delay + d ms = 1 ms + w real = 1 a ms = resolution() internals: