A few Pylint fixes

Author: marvinpfoertner

src/probnum/randvars/_constant.py

@@ -4,8 +4,14 @@
 
 import numpy as np
 
-from probnum import config, linops, utils as _utils
-from probnum.typing import ArrayLikeGetitemArgType, ArrayType, ShapeArgType, ShapeType
+from probnum import backend, config, linops, utils as _utils
+from probnum.typing import (
+    ArrayLikeGetitemArgType,
+    ArrayType,
+    SeedType,
+    ShapeArgType,
+    ShapeType,
+)
 
 from . import _random_variable
 
@@ -60,10 +66,7 @@ def __init__(
         self,
         support: ArrayType,
     ):
-        if np.isscalar(support):
-            support = _utils.as_numpy_scalar(support)
-
-        self._support = support
+        self._support = backend.asarray(support)
 
         support_floating = self._support.astype(
             np.promote_types(self._support.dtype, np.float_)
@@ -142,13 +145,13 @@ def transpose(self, *axes: int) -> "Constant":
             support=self._support.transpose(*axes),
         )
 
-    def _sample(self, rng: np.random.Generator, size: ShapeArgType = ()) -> ArrayType:
-        size = _utils.as_shape(size)
+    def _sample(self, seed: SeedType, sample_shape: ShapeArgType = ()) -> ArrayType:
+        # pylint: disable=unused-argument
 
-        if size == ():
+        if sample_shape == ():
             return self._support.copy()
-        else:
-            return np.tile(self._support, reps=size + (1,) * self.ndim)
+
+        return np.tile(self._support, reps=sample_shape + (1,) * self.ndim)
 
     # Unary arithmetic operations
 

src/probnum/randvars/_normal.py

@@ -460,10 +460,11 @@ def _sample(self, seed: SeedLike, sample_shape: ShapeType = ()) -> ArrayType:
     def _arg_todense(x: Union[ArrayType, linops.LinearOperator]) -> ArrayType:
         if isinstance(x, linops.LinearOperator):
             return x.todense()
-        elif isinstance(x, backend.ndarray):
+
+        if isinstance(x, backend.ndarray):
             return x
-        else:
-            raise ValueError(f"Unsupported argument type {type(x)}")
+
+        raise ValueError(f"Unsupported argument type {type(x)}")
 
     @backend.jit_method
     def _in_support(self, x: ArrayType) -> ArrayType:
@@ -504,7 +505,7 @@ def _cdf(self, x: ArrayType) -> ArrayType:
         if backend.BACKEND is not backend.Backend.NUMPY:
             raise NotImplementedError()
 
-        import scipy.stats
+        import scipy.stats  # pylint: disable=import-outside-toplevel
 
         return scipy.stats.multivariate_normal.cdf(
             Normal._arg_todense(x).reshape(x.shape[: -self.ndim] + (-1,)),
@@ -516,7 +517,7 @@ def _logcdf(self, x: ArrayType) -> ArrayType:
         if backend.BACKEND is not backend.Backend.NUMPY:
             raise NotImplementedError()
 
-        import scipy.stats
+        import scipy.stats  # pylint: disable=import-outside-toplevel
 
         return scipy.stats.multivariate_normal.logcdf(
             Normal._arg_todense(x).reshape(x.shape[: -self.ndim] + (-1,)),

src/probnum/randvars/_random_variable.py

@@ -11,7 +11,6 @@
     ArrayLikeGetitemArgType,
     ArrayType,
     DTypeArgType,
-    FloatArgType,
     ScalarType,
     SeedType,
     ShapeArgType,
@@ -337,7 +336,8 @@ def var(self) -> ArrayType:
     def std(self) -> ArrayType:
         """Standard deviation of the random variable.
 
-        To learn about the dtype of the standard deviation, see :attr:`expectation_dtype`.
+        To learn about the dtype of the standard deviation, see
+        :attr:`expectation_dtype`.
         """
         if self.__std is None:
             std = backend.sqrt(self.var)
@@ -578,7 +578,9 @@ def __neg__(self) -> "RandomVariable":
         return RandomVariable(
             shape=self.shape,
             dtype=self.dtype,
-            sample=lambda rng, size: -self.sample(rng=rng, size=size),
+            sample=lambda seed, sample_shape: -self.sample(
+                seed=seed, sample_shape=sample_shape
+            ),
             in_support=lambda x: self.in_support(-x),
             mode=lambda: -self.mode,
             median=lambda: -self.median,
@@ -592,7 +594,9 @@ def __pos__(self) -> "RandomVariable":
         return RandomVariable(
             shape=self.shape,
             dtype=self.dtype,
-            sample=lambda rng, size: +self.sample(rng=rng, size=size),
+            sample=lambda seed, sample_shape: +self.sample(
+                seed=seed, sample_shape=sample_shape
+            ),
             in_support=lambda x: self.in_support(+x),
             mode=lambda: +self.mode,
             median=lambda: +self.median,
@@ -606,7 +610,9 @@ def __abs__(self) -> "RandomVariable":
         return RandomVariable(
             shape=self.shape,
             dtype=self.dtype,
-            sample=lambda rng, size: abs(self.sample(rng=rng, size=size)),
+            sample=lambda seed, sample_shape: abs(
+                self.sample(seed=seed, sample_shape=sample_shape)
+            ),
         )
 
     # Binary arithmetic operations
@@ -891,6 +897,8 @@ def __init__(
         std: Optional[Callable[[], ArrayType]] = None,
         entropy: Optional[Callable[[], ScalarType]] = None,
     ):
+        # pylint: disable=too-many-arguments,too-many-locals
+
         # Probability mass function
         self.__pmf = pmf
         self.__logpmf = logpmf
@@ -1098,6 +1106,8 @@ def __init__(
         std: Optional[Callable[[], ArrayType]] = None,
         entropy: Optional[Callable[[], ArrayType]] = None,
     ):
+        # pylint: disable=too-many-arguments,too-many-locals
+
         # Probability density function
         self.__pdf = pdf
         self.__logpdf = logpdf

src/probnum/randvars/_randomvariablelist.py

@@ -4,7 +4,7 @@
 
 import numpy as np
 
-from probnum import randvars
+from probnum.randvars import _random_variable
 
 try:
     # functools.cached_property is only available in Python >=3.8
@@ -30,14 +30,16 @@ def __init__(self, rv_list: list):
         if len(rv_list) > 0:
 
             # First element as a proxy for checking all elements
-            if not isinstance(rv_list[0], randvars.RandomVariable):
+            if not isinstance(rv_list[0], _random_variable.RandomVariable):
                 raise TypeError(
                     "RandomVariableList expects RandomVariable elements, but "
                     + f"first element has type {type(rv_list[0])}."
                 )
         super().__init__(rv_list)
 
-    def __getitem__(self, idx) -> Union[randvars.RandomVariable, "_RandomVariableList"]:
+    def __getitem__(
+        self, idx
+    ) -> Union[_random_variable.RandomVariable, "_RandomVariableList"]:
 
         result = super().__getitem__(idx)
         # Make sure to wrap the result into a _RandomVariableList if necessary

tox.ini

@@ -79,7 +79,7 @@ commands =
     pylint src/probnum/quad --disable="function-redefined,too-many-arguments,else-if-used,line-too-long,missing-module-docstring,missing-function-docstring,missing-raises-doc,missing-return-doc" --jobs=0
     pylint src/probnum/randprocs --disable="arguments-differ,arguments-renamed,too-many-instance-attributes,too-many-arguments,too-many-locals,protected-access,unused-argument,no-else-return,duplicate-code,line-too-long,missing-module-docstring,missing-function-docstring,missing-type-doc,missing-raises-doc,useless-param-doc,useless-type-doc,missing-return-doc,missing-return-type-doc" --jobs=0
     pylint src/probnum/randprocs/kernels --jobs=0
-    pylint src/probnum/randvars --disable="too-many-arguments,too-many-locals,too-many-branches,too-few-public-methods,protected-access,unused-argument,no-else-return,duplicate-code,line-too-long,missing-function-docstring,missing-raises-doc,missing-return-doc" --jobs=0
+    pylint src/probnum/randvars --disable="missing-function-docstring,missing-raises-doc,missing-return-doc" --jobs=0
     pylint src/probnum/utils --disable="no-else-return,else-if-used,line-too-long,missing-raises-doc,missing-return-doc,missing-return-type-doc" --jobs=0
     # Benchmark and Test Code Linting Pass
     # pylint benchmarks --disable="unused-argument,attribute-defined-outside-init,missing-function-docstring" --jobs=0 # not a work in progress, but final