[MegaLinter] Apply linters automatic fixes

src/pyrecest/_backend/pytorch/random.py

@@ -267,9 +267,7 @@ def _validate_randint_array_dtype_bounds(low, high, dtype):
     # representable by the output dtype, as in randint(255, 256, dtype=uint8).
     # For int64, input tensors cannot represent max + 1, so every accepted high
     # value is already within the valid endpoint range.
-    if dtype != _torch.int64 and bool(
-        _torch.any(high_int64 > dtype_info.max + 1)
-    ):
+    if dtype != _torch.int64 and bool(_torch.any(high_int64 > dtype_info.max + 1)):
         raise ValueError(f"high is out of bounds for {dtype_name}")
 
 

src/pyrecest/models/linear_gaussian.py

@@ -2,8 +2,8 @@
 
 from numbers import Complex, Integral, Real
 
+from pyrecest.backend import all as backend_all
 from pyrecest.backend import (
-    all as backend_all,
     asarray,
 )
 from pyrecest.backend import copy as backend_copy

tests/backend/test_pytorch_randint_dtype_bounds.py

@@ -1,7 +1,6 @@
 import numpy as np
 import pytest
 
-
 torch = pytest.importorskip("torch")
 
 from pyrecest._backend.pytorch import random  # noqa: E402
@@ -16,9 +15,7 @@
         ([0], [129], np.int8, "high is out of bounds for int8"),
     ],
 )
-def test_array_randint_rejects_bounds_outside_output_dtype(
-    low, high, dtype, message
-):
+def test_array_randint_rejects_bounds_outside_output_dtype(low, high, dtype, message):
     with pytest.raises(ValueError, match=message):
         random.randint(low, high, dtype=dtype)
 

tests/distributions/test_ellipsoidal_ball_temporal_sample_count.py

@@ -1,6 +1,5 @@
 import numpy as np
 import pytest
-
 from pyrecest.backend import array, diag
 from pyrecest.distributions import EllipsoidalBallUniformDistribution
 

tests/filters/test_relaxed_s3f_process_noise_validation.py

@@ -28,7 +28,9 @@ def test_rejects_nonsymmetric_process_noise_without_mutating_state(self):
 
         self.assertTrue(
             bool(
-                (filter_.filter_state.linear_distributions[0].C == covariance_before).all()
+                (
+                    filter_.filter_state.linear_distributions[0].C == covariance_before
+                ).all()
             )
         )
 
@@ -45,7 +47,9 @@ def test_rejects_indefinite_process_noise_without_mutating_state(self):
 
         self.assertTrue(
             bool(
-                (filter_.filter_state.linear_distributions[0].C == covariance_before).all()
+                (
+                    filter_.filter_state.linear_distributions[0].C == covariance_before
+                ).all()
             )
         )
 

tests/models/test_linear_gaussian_finite_inputs.py

@@ -15,27 +15,19 @@ def test_models_reject_nonfinite_system_and_measurement_matrices(self):
         for value in (np.nan, np.inf, -np.inf):
             with self.subTest(model="transition", value=value):
                 with self.assertRaisesRegex(ValueError, "matrix.*finite"):
-                    LinearGaussianTransitionModel(
-                        array([[value]]), array([[1.0]])
-                    )
+                    LinearGaussianTransitionModel(array([[value]]), array([[1.0]]))
             with self.subTest(model="measurement", value=value):
                 with self.assertRaisesRegex(ValueError, "matrix.*finite"):
-                    LinearGaussianMeasurementModel(
-                        array([[value]]), array([[1.0]])
-                    )
+                    LinearGaussianMeasurementModel(array([[value]]), array([[1.0]]))
 
     def test_models_reject_nonfinite_noise_covariances(self):
         for value in (np.nan, np.inf, -np.inf):
             with self.subTest(model="transition", value=value):
                 with self.assertRaisesRegex(ValueError, "noise_cov.*finite"):
-                    LinearGaussianTransitionModel(
-                        array([[1.0]]), array([[value]])
-                    )
+                    LinearGaussianTransitionModel(array([[1.0]]), array([[value]]))
             with self.subTest(model="measurement", value=value):
                 with self.assertRaisesRegex(ValueError, "noise_cov.*finite"):
-                    LinearGaussianMeasurementModel(
-                        array([[1.0]]), array([[value]])
-                    )
+                    LinearGaussianMeasurementModel(array([[1.0]]), array([[value]]))
 
     def test_transition_model_rejects_nonfinite_offset(self):
         for value in (np.nan, np.inf, -np.inf):
@@ -55,12 +47,8 @@ def test_identity_models_reject_nonfinite_scalar_noise(self):
                     IdentityGaussianMeasurementModel(1, value)
 
     def test_prediction_rejects_nonfinite_state_inputs(self):
-        transition = LinearGaussianTransitionModel(
-            array([[1.0]]), array([[1.0]])
-        )
-        measurement = LinearGaussianMeasurementModel(
-            array([[1.0]]), array([[1.0]])
-        )
+        transition = LinearGaussianTransitionModel(array([[1.0]]), array([[1.0]]))
+        measurement = LinearGaussianMeasurementModel(array([[1.0]]), array([[1.0]]))
 
         for value in (np.nan, np.inf, -np.inf):
             with self.subTest(method="transition mean", value=value):

tests/test_deprecation_helper.py

@@ -25,9 +25,9 @@ def test_deprecated_decorator_supports_partial_callables():
     def add(left, right):
         return left + right
 
-    legacy_add_one = deprecated(
-        since="2.3.0", remove_in="3.0.0", replacement="add"
-    )(functools.partial(add, 1))
+    legacy_add_one = deprecated(since="2.3.0", remove_in="3.0.0", replacement="add")(
+        functools.partial(add, 1)
+    )
 
     with warnings.catch_warnings(record=True) as caught:
         warnings.simplefilter("always")

tests/test_evidence_terminal_posterior_validation.py

@@ -1,5 +1,4 @@
 import pytest
-
 from pyrecest.evidence import EvidenceComputationMode
 
 

tests/test_gaussian_sampler_zero_samples.py

@@ -1,5 +1,4 @@
 import numpy as np
-
 from pyrecest.sampling.euclidean_sampler import GaussianSampler