Remove scipy.stats compatibility

Author: marvinpfoertner

src/probnum/randvars/__init__.py

@@ -15,11 +15,6 @@
     RandomVariable,
 )
 from ._randomvariablelist import _RandomVariableList
-from ._scipy_stats import (
-    WrappedSciPyContinuousRandomVariable,
-    WrappedSciPyDiscreteRandomVariable,
-    WrappedSciPyRandomVariable,
-)
 from ._sym_mat_normal import SymmetricMatrixNormal
 from ._utils import asrandvar
 
@@ -33,9 +28,6 @@
     "Normal",
     "SymmetricMatrixNormal",
     "Categorical",
-    "WrappedSciPyRandomVariable",
-    "WrappedSciPyDiscreteRandomVariable",
-    "WrappedSciPyContinuousRandomVariable",
     "_RandomVariableList",
 ]
 
@@ -44,10 +36,6 @@
 DiscreteRandomVariable.__module__ = "probnum.randvars"
 ContinuousRandomVariable.__module__ = "probnum.randvars"
 
-WrappedSciPyRandomVariable.__module__ = "probnum.randvars"
-WrappedSciPyDiscreteRandomVariable.__module__ = "probnum.randvars"
-WrappedSciPyContinuousRandomVariable.__module__ = "probnum.randvars"
-
 Constant.__module__ = "probnum.randvars"
 Normal.__module__ = "probnum.randvars"
 SymmetricMatrixNormal.__module__ = "probnum.randvars"

src/probnum/randvars/_scipy_stats.py

@@ -1,12 +1,11 @@
 """Utility functions for random variables."""
 from typing import Any
 
-import numpy as np
 import scipy.sparse
 
-import probnum.linops
+from probnum import backend, linops
 
-from . import _constant, _random_variable, _scipy_stats
+from . import _constant, _random_variable
 
 
 def asrandvar(obj: Any) -> _random_variable.RandomVariable:
@@ -17,51 +16,40 @@ def asrandvar(obj: Any) -> _random_variable.RandomVariable:
 
     Parameters
     ----------
-    obj :
+    obj
         Object to be represented as a :class:`RandomVariable`.
 
+    Returns
+    -------
+    randvar
+        Object as a :class:`RandomVariable`.
+
+    Raises
+    ------
+    ValueError
+        If the object cannot be represented as a :class:`RandomVariable`.
+
     See Also
     --------
     RandomVariable : Class representing random variables.
-
-    Examples
-    --------
-    >>> from scipy.stats import bernoulli
-    >>> import probnum as pn
-    >>> import numpy as np
-    >>> bern = bernoulli(p=0.5)
-    >>> bern_pn = pn.asrandvar(bern)
-    >>> rng = np.random.default_rng(42)
-    >>> bern_pn.sample(rng=rng, size=5)
-    array([1, 0, 1, 1, 0])
     """
 
-    # pylint: disable=protected-access
-
     # RandomVariable
     if isinstance(obj, _random_variable.RandomVariable):
         return obj
+
     # Scalar
-    elif np.isscalar(obj):
+    if backend.ndim(obj) == 0:
         return _constant.Constant(support=obj)
-    # Numpy array or sparse matrix
-    elif isinstance(obj, (np.ndarray, scipy.sparse.spmatrix)):
+
+    # NumPy array or sparse matrix
+    if isinstance(obj, (backend.ndarray, scipy.sparse.spmatrix)):
         return _constant.Constant(support=obj)
+
     # Linear Operators
-    elif isinstance(
-        obj, (probnum.linops.LinearOperator, scipy.sparse.linalg.LinearOperator)
-    ):
-        return _constant.Constant(support=probnum.linops.aslinop(obj))
-    # Scipy random variable
-    elif isinstance(
-        obj,
-        (
-            scipy.stats._distn_infrastructure.rv_frozen,
-            scipy.stats._multivariate.multi_rv_frozen,
-        ),
-    ):
-        return _scipy_stats.wrap_scipy_rv(obj)
-    else:
-        raise ValueError(
-            f"Argument of type {type(obj)} cannot be converted to a random variable."
-        )
+    if isinstance(obj, (linops.LinearOperator, scipy.sparse.linalg.LinearOperator)):
+        return _constant.Constant(support=linops.aslinop(obj))
+
+    raise ValueError(
+        f"Argument of type {type(obj)} cannot be converted to a random variable."
+    )