Networkunit 0.2.2

Patch release updating the package dependencies, the example notebooks, and fixing a few minor bugs in the model classes.

NetworkUnit 0.2.1

Patch release to update the package dependencies. Also, this release adopts the pyproject.toml convention for the package description.

NetworkUnit 0.2.0

• parameter handling
  • generate_prediction() and other custom class function no longer take optional extra parameter as arguments, but only use self.params
  • no class function should accept arguments that override class parameters
  • default_params test class attribute are inherited by using default_params = {**parent.default_params, 'new_param':0}
• caching
  • improved caching of intermediate test- and simulation results, e.g. for the correlation matrix
  • improving backend definitions
• parallelization
  • automatic parallelization for loops over spiketrains or lists of spiketrains. To use set params['parallel executor'] to ProcessPoolExecutor(), MPIPoolExecutor(), or MPICommExecutor() (see documentation in Elephant package)
• various bug fixes
• new features
  • adding the joint_test class that enables the combination of multiple neuron-wise tests for multidimensional testing with the Wasserstein score
• new test classes
  • joint_test
  • power_spectrum_test
    • freqband_power_test
  • timescale_test
  • avg_std_correlation_test
• new score classes
  • wasserstein_distance
  • eigenangle (see publication Gutzen et al. 2022

NetworkUnit 0.1.2

This patch contains:

• a fix for an issue where the setup script was failing to properly install the backend directory (see issue #20)

NetworkUnit 0.1.1

This patch contains:

• a new backend class, which handles the storage of generated predictions in memory or on disk. To make use of it just set backend='storage' in the model instantiation. By default predictions are stored in memory. To change that set model.get_backend().use_disk_cache = True and model.get_backend().use_memory_cache = False .

• various bug fixes

• updated requirements.txt and environment.yaml