Move modules in probnum.core to top level

benchmarks/random_variables.py

@@ -4,7 +4,7 @@
 
 import numpy as np
 
-from probnum.core import random_variable as rvs
+from probnum import random_variables as rvs
 import probnum.linalg.linops as linops
 
 # Module level variables

src/probnum/__init__.py

@@ -28,10 +28,10 @@
 from . import filtsmooth
 from . import linalg
 from . import quad
+from . import random_variables
 from . import utils
 
-from .core import *
-
+from .random_variables import asrandvar, RandomVariable
 
 # -*- coding: utf-8 -*-
 from pkg_resources import get_distribution, DistributionNotFound

src/probnum/diffeq/odefiltsmooth/ivp2filter.py

@@ -7,7 +7,7 @@
 
 from probnum.filtsmooth import ExtendedKalman, UnscentedKalman
 from probnum.filtsmooth.statespace.discrete import DiscreteGaussianModel
-from probnum.core import random_variables as rvs
+from probnum import random_variables as rvs
 
 
 def ivp2ekf0(ivp, prior, evlvar):

src/probnum/diffeq/odefiltsmooth/ivpfiltsmooth.py

@@ -1,7 +1,7 @@
 import warnings
 import numpy as np
 
-from probnum.core.random_variables import Normal
+from probnum.random_variables import Normal
 from probnum.diffeq import odesolver
 from probnum.diffeq.odefiltsmooth.prior import ODEPrior
 from probnum.diffeq.odesolution import ODESolution

src/probnum/diffeq/odefiltsmooth/prior.py

@@ -14,7 +14,7 @@
 from scipy.special import factorial  # vectorised factorial for IBM-Q(h)
 
 from probnum.filtsmooth.statespace.continuous import LTISDEModel
-from probnum.core.random_variables import Normal
+from probnum.random_variables import Normal
 
 
 class ODEPrior(LTISDEModel):

src/probnum/diffeq/odesolution.py

@@ -5,8 +5,8 @@
 Provides dense output by being callable.
 Can function values can also be accessed by indexing.
 """
-from probnum.core.random_variables import Normal
-from probnum.core._randomvariablelist import _RandomVariableList
+from probnum.random_variables import Normal
+from probnum._randomvariablelist import _RandomVariableList
 from probnum.filtsmooth.filtsmoothposterior import FiltSmoothPosterior
 from probnum.filtsmooth import KalmanPosterior
 

src/probnum/filtsmooth/gaussfiltsmooth/extendedkalman.py

@@ -8,7 +8,7 @@
     GaussFiltSmooth,
     linear_discrete_update,
 )
-from probnum.core.random_variables import Normal
+from probnum.random_variables import Normal
 from probnum.filtsmooth.statespace import (
     LinearSDEModel,
     DiscreteGaussianModel,

src/probnum/filtsmooth/gaussfiltsmooth/gaussfiltsmooth.py

@@ -5,7 +5,7 @@
 
 import numpy as np
 
-from probnum.core.random_variables import Normal
+from probnum.random_variables import Normal
 from probnum.filtsmooth.bayesfiltsmooth import BayesFiltSmooth
 from probnum.filtsmooth.gaussfiltsmooth.kalmanposterior import KalmanPosterior
 

src/probnum/filtsmooth/gaussfiltsmooth/kalman.py

@@ -8,7 +8,7 @@
     GaussFiltSmooth,
     linear_discrete_update,
 )
-from probnum.core.random_variables import Normal
+from probnum.random_variables import Normal
 from probnum.filtsmooth.statespace import (
     LinearSDEModel,
     DiscreteGaussianLinearModel,

src/probnum/filtsmooth/gaussfiltsmooth/kalmanposterior.py

@@ -9,7 +9,7 @@
 
 import numpy as np
 
-from probnum.core._randomvariablelist import _RandomVariableList
+from probnum._randomvariablelist import _RandomVariableList
 from probnum.filtsmooth.filtsmoothposterior import FiltSmoothPosterior
 
 

src/probnum/filtsmooth/gaussfiltsmooth/unscentedkalman.py

@@ -11,7 +11,7 @@
     GaussFiltSmooth,
     linear_discrete_update,
 )
-from probnum.core.random_variables import Normal
+from probnum.random_variables import Normal
 from probnum.filtsmooth.gaussfiltsmooth.unscentedtransform import UnscentedTransform
 from probnum.filtsmooth.statespace import (
     ContinuousModel,

src/probnum/filtsmooth/statespace/continuous/linearsdemodel.py

@@ -10,7 +10,7 @@
 import numpy as np
 import scipy.linalg
 from probnum.filtsmooth.statespace.continuous import continuousmodel
-from probnum.core.random_variables import Normal
+from probnum.random_variables import Normal
 
 __all__ = ["LinearSDEModel", "LTISDEModel"]
 

src/probnum/filtsmooth/statespace/discrete/discretegaussianmodel.py

@@ -3,7 +3,7 @@
 x_{i+1} = N(g(i, x_i), S(i))
 """
 
-from probnum.core.random_variables import Normal
+from probnum.random_variables import Normal
 from probnum.filtsmooth.statespace.discrete import discretemodel
 
 

src/probnum/linalg/linearsolvers/matrixbased.py

@@ -11,7 +11,7 @@
 import GPy
 
 import probnum
-from probnum.core import random_variables as rvs
+from probnum import random_variables as rvs
 from probnum.linalg import linops
 
 

src/probnum/random_variables/__init__.py

@@ -0,0 +1,21 @@
+"""
+This package implements random variables. Random variables are the primary in- and
+outputs of probabilistic numerical methods. A generic signature of such methods looks
+like this:
+
+.. highlight:: python
+.. code-block:: python
+
+    randvar_out, info = probnum_method(problem, randvar_in, **kwargs)
+
+"""
+
+from ._random_variable import (
+    asrandvar,
+    RandomVariable,
+    DiscreteRandomVariable,
+    ContinuousRandomVariable,
+)
+
+from ._dirac import Dirac
+from ._normal import Normal

src/probnum/core/random_variables/_arithmetic.py → src/probnum/random_variables/_arithmetic.py

@@ -2,7 +2,7 @@
 from typing import Any, Callable, Dict, Tuple, Union
 
 from ._random_variable import RandomVariable as _RandomVariable
-from probnum.core.random_variables import Dirac as _Dirac, Normal as _Normal
+from probnum.random_variables import Dirac as _Dirac, Normal as _Normal
 
 
 def add(rv1: _RandomVariable, rv2: _RandomVariable) -> _RandomVariable:

src/probnum/core/random_variables/_dirac.py → src/probnum/random_variables/_dirac.py

@@ -148,7 +148,7 @@ def _binary_operator_factory(
     ) -> Callable[["Dirac", "Dirac"], "Dirac"]:
         def _dirac_binary_operator(dirac_rv1: Dirac, dirac_rv2: Dirac) -> Dirac:
             return Dirac(
-                support=operator(dirac_rv1, dirac_rv2),
+                support=operator(dirac_rv1.support, dirac_rv2.support),
                 random_state=_utils.derive_random_seed(
                     dirac_rv1.random_state, dirac_rv2.random_state,
                 ),

src/probnum/core/random_variables/_normal.py → src/probnum/random_variables/_normal.py

@@ -477,7 +477,7 @@ def _scale(self, scalar, other_random_state=None):
             )
 
         if scalar == 0:
-            from probnum.core import random_variables as rvs
+            from probnum import random_variables as rvs
 
             return rvs.Dirac(
                 support=np.zeros_like(self._mean), random_state=derived_random_seed,

src/probnum/core/random_variables/_random_variable.py → src/probnum/random_variables/_random_variable.py

@@ -818,7 +818,7 @@ def asrandvar(obj) -> RandomVariable:
     """
 
     # pylint: disable=import-outside-toplevel
-    from probnum.core import random_variables as rvs
+    from probnum import random_variables as rvs
 
     # RandomVariable
     if isinstance(obj, RandomVariable):
@@ -868,7 +868,7 @@ def _scipystats_to_rv(
     """
 
     # pylint: disable=import-outside-toplevel
-    from probnum.core import random_variables as rvs
+    from probnum import random_variables as rvs
 
     # Univariate distributions (implemented in this package)
     if isinstance(scipyrv, scipy.stats._distn_infrastructure.rv_frozen):

tests/test_diffeq/test_ode/test_ivp.py

@@ -1,7 +1,7 @@
 import unittest
 import numpy as np
 from probnum.diffeq.ode import ivp
-from probnum.core.random_variables import Dirac
+from probnum.random_variables import Dirac
 from tests.testing import NumpyAssertions
 
 TEST_NDIM = 3

tests/test_diffeq/test_odefiltsmooth/test_ivp2filter.py

@@ -12,7 +12,7 @@
 
 from probnum.diffeq import IBM, ivp2filter, lotkavolterra
 from probnum.filtsmooth import ExtendedKalman, UnscentedKalman
-from probnum.core.random_variables import Dirac
+from probnum.random_variables import Dirac
 from tests.testing import NumpyAssertions
 
 

tests/test_diffeq/test_odefiltsmooth/test_odefiltsmooth.py

@@ -16,7 +16,7 @@
 
 from probnum.diffeq.odefiltsmooth import probsolve_ivp
 from probnum.diffeq import ode
-from probnum.core.random_variables import Dirac
+from probnum.random_variables import Dirac
 
 from tests.testing import NumpyAssertions
 

tests/test_diffeq/test_odefiltsmooth/test_prior.py

@@ -10,7 +10,7 @@
 
 import numpy as np
 
-from probnum.core.random_variables import Normal
+from probnum.random_variables import Normal
 from probnum.diffeq.odefiltsmooth import prior
 from tests.testing import NumpyAssertions
 

tests/test_diffeq/test_odesolution.py

@@ -1,8 +1,8 @@
 import unittest
 import numpy as np
 
-from probnum.core.random_variables import Dirac
-from probnum.core._randomvariablelist import _RandomVariableList
+from probnum.random_variables import Dirac
+from probnum._randomvariablelist import _RandomVariableList
 from probnum.diffeq import probsolve_ivp
 from probnum.diffeq.ode import lotkavolterra, logistic
 

tests/test_filtsmooth/test_gaussfiltsmooth/filtsmooth_testcases.py

@@ -12,7 +12,7 @@
     generate_cd,
     DiscreteGaussianModel,
 )
-from probnum.core.random_variables import Normal
+from probnum.random_variables import Normal
 from tests.testing import NumpyAssertions
 
 __all__ = [

tests/test_filtsmooth/test_gaussfiltsmooth/test_kalmanposterior.py

@@ -1,7 +1,7 @@
 import numpy as np
 
 from probnum.filtsmooth.gaussfiltsmooth import Kalman
-from probnum.core._randomvariablelist import _RandomVariableList
+from probnum._randomvariablelist import _RandomVariableList
 from tests.testing import NumpyAssertions
 
 from .filtsmooth_testcases import CarTrackingDDTestCase

tests/test_filtsmooth/test_statespace/test_continuous/test_continuousmodel.py

@@ -2,7 +2,7 @@
 
 import numpy as np
 
-from probnum.core.random_variables import Normal, Dirac
+from probnum.random_variables import Normal, Dirac
 from probnum.filtsmooth.statespace.continuous import continuousmodel
 
 VISUALISE = False

tests/test_filtsmooth/test_statespace/test_continuous/test_linearsdemodel.py

@@ -2,7 +2,7 @@
 
 import numpy as np
 
-from probnum.core.random_variables import Normal
+from probnum.random_variables import Normal
 from probnum.filtsmooth.statespace.continuous import linearsdemodel
 
 TEST_NDIM = 2