diff --git a/src/pyrecest/_backend/numpy/linalg.py b/src/pyrecest/_backend/numpy/linalg.py
index fe9b33ad29..cd1312f9e7 100644
--- a/src/pyrecest/_backend/numpy/linalg.py
+++ b/src/pyrecest/_backend/numpy/linalg.py
@@ -22,16 +22,20 @@
 
 from .._shared_numpy.linalg import (
     _normalize_fractional_matrix_power_exponent,
-    fractional_matrix_power as _fractional_matrix_power,
+)
+from .._shared_numpy.linalg import fractional_matrix_power as _fractional_matrix_power
+from .._shared_numpy.linalg import (
     is_single_matrix_pd,
-    logm as _logm,
+)
+from .._shared_numpy.linalg import logm as _logm
+from .._shared_numpy.linalg import (
     polar,
     qr,
     quadratic_assignment,
     solve,
     solve_sylvester,
-    sqrtm as _sqrtm,
 )
+from .._shared_numpy.linalg import sqrtm as _sqrtm
 
 
 def _empty_zero_by_zero_matrix_result(value):
diff --git a/src/pyrecest/_backend/pytorch/random.py b/src/pyrecest/_backend/pytorch/random.py
index 54340db9d7..eaf5728a57 100644
--- a/src/pyrecest/_backend/pytorch/random.py
+++ b/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}")
 
 
diff --git a/src/pyrecest/backend_support/_pytorch_one_hot_scalar_contract.py b/src/pyrecest/backend_support/_pytorch_one_hot_scalar_contract.py
index 4e5b06bd89..94cea6bc0c 100644
--- a/src/pyrecest/backend_support/_pytorch_one_hot_scalar_contract.py
+++ b/src/pyrecest/backend_support/_pytorch_one_hot_scalar_contract.py
@@ -277,9 +277,7 @@ def array_equal(a, b, equal_nan=False):
 
         comparison = torch_module.eq(a, b)
         if dtype.is_floating_point or dtype.is_complex:
-            comparison = comparison | (
-                torch_module.isnan(a) & torch_module.isnan(b)
-            )
+            comparison = comparison | (torch_module.isnan(a) & torch_module.isnan(b))
         return bool(torch_module.all(comparison))
 
     array_equal.__name__ = getattr(original_array_equal, "__name__", "array_equal")
diff --git a/src/pyrecest/distributions/abstract_custom_distribution.py b/src/pyrecest/distributions/abstract_custom_distribution.py
index 7fa21201e4..d3a596f8bd 100644
--- a/src/pyrecest/distributions/abstract_custom_distribution.py
+++ b/src/pyrecest/distributions/abstract_custom_distribution.py
@@ -10,7 +10,6 @@
 
 from .abstract_distribution_type import AbstractDistributionType
 
-
 _INVALID_INTEGRAL_TYPES = (
     bool,
     np.bool_,
diff --git a/src/pyrecest/distributions/cart_prod/gauss_von_mises_distribution.py b/src/pyrecest/distributions/cart_prod/gauss_von_mises_distribution.py
index 3f2359e890..0f1962eca3 100644
--- a/src/pyrecest/distributions/cart_prod/gauss_von_mises_distribution.py
+++ b/src/pyrecest/distributions/cart_prod/gauss_von_mises_distribution.py
@@ -37,7 +37,6 @@
 from ..nonperiodic.gaussian_distribution import GaussianDistribution
 from .abstract_hypercylindrical_distribution import AbstractHypercylindricalDistribution
 
-
 _INVALID_SCALAR_TYPES = (
     str,
     bytes,
diff --git a/src/pyrecest/distributions/cart_prod/hypercylindrical_state_space_subdivision_distribution.py b/src/pyrecest/distributions/cart_prod/hypercylindrical_state_space_subdivision_distribution.py
index 82cd2a09e2..3c63bbe58c 100644
--- a/src/pyrecest/distributions/cart_prod/hypercylindrical_state_space_subdivision_distribution.py
+++ b/src/pyrecest/distributions/cart_prod/hypercylindrical_state_space_subdivision_distribution.py
@@ -38,7 +38,9 @@
 from pyrecest.distributions.nonperiodic.custom_linear_distribution import (
     CustomLinearDistribution,
 )
-from pyrecest.distributions.nonperiodic.gaussian_distribution import GaussianDistribution
+from pyrecest.distributions.nonperiodic.gaussian_distribution import (
+    GaussianDistribution,
+)
 from pyrecest.distributions.nonperiodic.linear_mixture import LinearMixture
 
 
diff --git a/src/pyrecest/distributions/hypersphere_subset/von_mises_fisher_distribution.py b/src/pyrecest/distributions/hypersphere_subset/von_mises_fisher_distribution.py
index e5b96943be..fabc78a7bc 100644
--- a/src/pyrecest/distributions/hypersphere_subset/von_mises_fisher_distribution.py
+++ b/src/pyrecest/distributions/hypersphere_subset/von_mises_fisher_distribution.py
@@ -33,7 +33,6 @@
 
 from .abstract_hyperspherical_distribution import AbstractHypersphericalDistribution
 
-
 _INVALID_REAL_SCALAR_TYPES = (
     bool,
     np.bool_,
diff --git a/src/pyrecest/distributions/hypersphere_subset/watson_distribution.py b/src/pyrecest/distributions/hypersphere_subset/watson_distribution.py
index f4dcebb91c..36e2886120 100644
--- a/src/pyrecest/distributions/hypersphere_subset/watson_distribution.py
+++ b/src/pyrecest/distributions/hypersphere_subset/watson_distribution.py
@@ -29,7 +29,6 @@
 from .abstract_hyperspherical_distribution import AbstractHypersphericalDistribution
 from .bingham_distribution import BinghamDistribution
 
-
 _INVALID_REAL_SCALAR_TYPES = (
     bool,
     np.bool_,
diff --git a/src/pyrecest/evaluation/check_and_fix_config.py b/src/pyrecest/evaluation/check_and_fix_config.py
index d90cb058a1..b4429a4c0f 100644
--- a/src/pyrecest/evaluation/check_and_fix_config.py
+++ b/src/pyrecest/evaluation/check_and_fix_config.py
@@ -1,7 +1,6 @@
 from numbers import Integral, Real
 
 import numpy as np
-
 from pyrecest.distributions import AbstractManifoldSpecificDistribution
 
 
@@ -12,9 +11,9 @@ def _is_integer_count(value):
 
 
 def _validate_probability(value, name):
-    if isinstance(value, (bool, np.bool_, np.datetime64, np.timedelta64)) or not isinstance(
-        value, Real
-    ):
+    if isinstance(
+        value, (bool, np.bool_, np.datetime64, np.timedelta64)
+    ) or not isinstance(value, Real):
         raise TypeError(f"{name} must be a real scalar")
     value = float(value)
     if not np.isfinite(value) or not 0.0 <= value <= 1.0:
diff --git a/src/pyrecest/evaluation/get_distance_function.py b/src/pyrecest/evaluation/get_distance_function.py
index 44a2cb3407..1e0b325153 100644
--- a/src/pyrecest/evaluation/get_distance_function.py
+++ b/src/pyrecest/evaluation/get_distance_function.py
@@ -164,9 +164,7 @@ def distance_function(xest, xtrue):
     return distance_function
 
 
-def _target_matrix_candidates(
-    value, name: str
-) -> list[tuple[numpy.ndarray, int]]:
+def _target_matrix_candidates(value, name: str) -> list[tuple[numpy.ndarray, int]]:
     value = _as_real_numeric_array(value, name)
     if value.ndim not in (1, 2):
         raise ValueError(f"{name} must be a one- or two-dimensional target set")
diff --git a/src/pyrecest/experimental/dvs/vectorized_flow.py b/src/pyrecest/experimental/dvs/vectorized_flow.py
index 6e1eea314a..2d80d4ca9a 100644
--- a/src/pyrecest/experimental/dvs/vectorized_flow.py
+++ b/src/pyrecest/experimental/dvs/vectorized_flow.py
@@ -48,9 +48,7 @@ def tracker_signed_normal_flows_vectorized(
     except Exception:  # pragma: no cover - backend-specific safety fallback
         return np.asarray(
             [
-                tracker.signed_normal_flow_for_measurement(
-                    measurement, unit_velocity
-                )
+                tracker.signed_normal_flow_for_measurement(measurement, unit_velocity)
                 for measurement in measurements
             ],
             dtype=float,
diff --git a/src/pyrecest/filters/daum_huang_particle_filter.py b/src/pyrecest/filters/daum_huang_particle_filter.py
index 794d846a9b..3bbee63112 100644
--- a/src/pyrecest/filters/daum_huang_particle_filter.py
+++ b/src/pyrecest/filters/daum_huang_particle_filter.py
@@ -261,9 +261,7 @@ def __init__(
             self.flow_type if flow_type is None else flow_type
         )
         self.n_steps = _validate_positive_int(n_steps, "n_steps")
-        self.step_schedule = (
-            None if step_schedule is None else tuple(step_schedule)
-        )
+        self.step_schedule = None if step_schedule is None else tuple(step_schedule)
         self.jitter = _validate_nonnegative_float(jitter, "jitter")
 
     def update_identity(self, meas_noise, measurement, **kwargs):
@@ -736,10 +734,7 @@ def _regularize_cov_np(covariance, jitter):
     eigenvalues = np.linalg.eigvalsh(covariance)
     spectral_scale = max(float(np.max(np.abs(eigenvalues))), 1.0)
     tolerance = (
-        10.0
-        * np.finfo(float).eps
-        * max(covariance.shape[0], 1)
-        * spectral_scale
+        10.0 * np.finfo(float).eps * max(covariance.shape[0], 1) * spectral_scale
     )
     min_eigenvalue = float(eigenvalues[0])
     if min_eigenvalue < -tolerance:
diff --git a/src/pyrecest/filters/global_nearest_neighbor.py b/src/pyrecest/filters/global_nearest_neighbor.py
index 82f7b0f9e1..7fd108c49f 100644
--- a/src/pyrecest/filters/global_nearest_neighbor.py
+++ b/src/pyrecest/filters/global_nearest_neighbor.py
@@ -22,7 +22,6 @@
 
 from .abstract_nearest_neighbor_tracker import AbstractNearestNeighborTracker
 
-
 _INVALID_PAIRWISE_COST_SCALAR_TYPES = (
     type(None),
     bool,
diff --git a/src/pyrecest/filters/mode_rbpf_manifold_ukf_tracker.py b/src/pyrecest/filters/mode_rbpf_manifold_ukf_tracker.py
index 18d94faa0e..dc61fa6139 100644
--- a/src/pyrecest/filters/mode_rbpf_manifold_ukf_tracker.py
+++ b/src/pyrecest/filters/mode_rbpf_manifold_ukf_tracker.py
@@ -876,9 +876,7 @@ def _normalize_probs(probs):
             )
         total = float(np.sum(probs))
         if total <= 0.0:
-            raise ValueError(
-                "initial_mode_probs must have positive total probability"
-            )
+            raise ValueError("initial_mode_probs must have positive total probability")
         return probs / total
 
     @staticmethod
diff --git a/src/pyrecest/filters/multisensor_hdp_association.py b/src/pyrecest/filters/multisensor_hdp_association.py
index 6c03018ada..1722a0912b 100644
--- a/src/pyrecest/filters/multisensor_hdp_association.py
+++ b/src/pyrecest/filters/multisensor_hdp_association.py
@@ -337,19 +337,14 @@ def multisensor_hdp_association(
         )
 
         log_concentration = np.log(concentration)
-        target_log_priors = (
-            np.logaddexp(
-                _safe_log(counts),
-                log_concentration + _safe_log(base_target_weights),
-            )
-            + _safe_log(detection)
-        )
+        target_log_priors = np.logaddexp(
+            _safe_log(counts),
+            log_concentration + _safe_log(base_target_weights),
+        ) + _safe_log(detection)
         existing_log_weights = log_likelihoods + target_log_priors[None, :]
 
         birth_log_weights = (
-            birth_log_likelihood
-            + log_concentration
-            + _safe_log(base_birth_weight)
+            birth_log_likelihood + log_concentration + _safe_log(base_birth_weight)
         )
         clutter_log_weights = clutter_log_likelihood + _safe_log(clutter_weight)
         log_weights = np.concatenate(
diff --git a/src/pyrecest/filters/sequence_association.py b/src/pyrecest/filters/sequence_association.py
index 6f62962c7a..dc55ec4676 100644
--- a/src/pyrecest/filters/sequence_association.py
+++ b/src/pyrecest/filters/sequence_association.py
@@ -360,9 +360,8 @@ def _validate_integer(value: object, name: str) -> int:
         raise ValueError(message) from exc
     if value_array.ndim != 0 or value_array.dtype == np.bool_:
         raise ValueError(message)
-    if (
-        value_array.dtype.kind in {"S", "U", "c"}
-        or _is_temporal_scalar_array(value_array)
+    if value_array.dtype.kind in {"S", "U", "c"} or _is_temporal_scalar_array(
+        value_array
     ):
         raise ValueError(message)
 
diff --git a/src/pyrecest/models/linear_gaussian.py b/src/pyrecest/models/linear_gaussian.py
index 7ed22d4ae5..c784cc2bc6 100644
--- a/src/pyrecest/models/linear_gaussian.py
+++ b/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
diff --git a/src/pyrecest/smoothers/abstract_smoother.py b/src/pyrecest/smoothers/abstract_smoother.py
index 867352fa36..64978d4d46 100644
--- a/src/pyrecest/smoothers/abstract_smoother.py
+++ b/src/pyrecest/smoothers/abstract_smoother.py
@@ -161,9 +161,7 @@ def _normalize_vector_sequence(  # pylint: disable=too-many-return-statements
         expected_shape = (vector_dim,)
         shape_error = f"{name} must contain vectors with shape {expected_shape}."
 
-        if isinstance(values, (list, tuple)) and any(
-            value is None for value in values
-        ):
+        if isinstance(values, (list, tuple)) and any(value is None for value in values):
             values_arr = None
         else:
             try:
diff --git a/src/pyrecest/utils/_point_set_registration_common.py b/src/pyrecest/utils/_point_set_registration_common.py
index 46fdafacb5..84405b9a2f 100644
--- a/src/pyrecest/utils/_point_set_registration_common.py
+++ b/src/pyrecest/utils/_point_set_registration_common.py
@@ -25,7 +25,6 @@
 from scipy.optimize import linear_sum_assignment
 from scipy.spatial.distance import cdist
 
-
 _INVALID_REAL_SCALAR_TYPES = (
     type(None),
     bool,
diff --git a/src/pyrecest/utils/_roi_assignment_extreme_range.py b/src/pyrecest/utils/_roi_assignment_extreme_range.py
index abed064058..de721ce304 100644
--- a/src/pyrecest/utils/_roi_assignment_extreme_range.py
+++ b/src/pyrecest/utils/_roi_assignment_extreme_range.py
@@ -15,8 +15,7 @@ def _cost_conversion_is_finite(
     threshold_cost = max_similarity - min_similarity
     dummy_penalty = max(
         1e-12,
-        sys.float_info.epsilon
-        * max(1.0, abs(max_similarity), abs(min_similarity)),
+        sys.float_info.epsilon * max(1.0, abs(max_similarity), abs(min_similarity)),
     )
     return math.isfinite(threshold_cost) and math.isfinite(
         threshold_cost + dummy_penalty
diff --git a/src/pyrecest/utils/metrics.py b/src/pyrecest/utils/metrics.py
index 0153d8e2aa..9b869436a4 100644
--- a/src/pyrecest/utils/metrics.py
+++ b/src/pyrecest/utils/metrics.py
@@ -579,11 +579,7 @@ def _as_covariance_stack(
 
 def _as_positive_int(value: Any, name: str) -> int:
     array = np.asarray(value)
-    if (
-        array.ndim != 0
-        or array.dtype == np.bool_
-        or array.dtype.kind in {"M", "m"}
-    ):
+    if array.ndim != 0 or array.dtype == np.bool_ or array.dtype.kind in {"M", "m"}:
         raise ValueError(f"{name} must be a positive integer")
     scalar = array.item()
     if isinstance(scalar, (int, np.integer)) and not isinstance(scalar, bool):
diff --git a/src/pyrecest/utils/point_set_registration.py b/src/pyrecest/utils/point_set_registration.py
index 1a7d60b724..f291b54715 100644
--- a/src/pyrecest/utils/point_set_registration.py
+++ b/src/pyrecest/utils/point_set_registration.py
@@ -214,8 +214,10 @@ def _validate_positive_integer(value, name: str, *, minimum: int = 1) -> int:
         except TypeError:
             pass
 
-    if isinstance(value, np.ndarray) and value.shape == () and isinstance(
-        value.item(), temporal_types
+    if (
+        isinstance(value, np.ndarray)
+        and value.shape == ()
+        and isinstance(value.item(), temporal_types)
     ):
         raise ValueError(error_message)
 
diff --git a/tests/backend/test_numpy_fractional_matrix_power_exponent_validation.py b/tests/backend/test_numpy_fractional_matrix_power_exponent_validation.py
index e554d48271..ee5b57c7e4 100644
--- a/tests/backend/test_numpy_fractional_matrix_power_exponent_validation.py
+++ b/tests/backend/test_numpy_fractional_matrix_power_exponent_validation.py
@@ -2,7 +2,6 @@
 import pytest
 from pyrecest._backend.numpy import linalg
 
-
 _MATRIX = np.diag([4.0, 9.0])
 
 
@@ -16,9 +15,7 @@
         np.timedelta64(2, "ns"),
         np.datetime64("1970-01-01T00:00:00.000000002"),
         np.array(np.timedelta64(2, "ns"), dtype=object),
-        np.array(
-            np.datetime64("1970-01-01T00:00:00.000000002"), dtype=object
-        ),
+        np.array(np.datetime64("1970-01-01T00:00:00.000000002"), dtype=object),
         "0.5",
         0.5 + 0.0j,
     ],
diff --git a/tests/backend/test_numpy_linalg_zero_by_zero_matrix_functions.py b/tests/backend/test_numpy_linalg_zero_by_zero_matrix_functions.py
index 92668c9444..c96767d251 100644
--- a/tests/backend/test_numpy_linalg_zero_by_zero_matrix_functions.py
+++ b/tests/backend/test_numpy_linalg_zero_by_zero_matrix_functions.py
@@ -1,6 +1,5 @@
 import numpy as np
 import pytest
-
 from pyrecest._backend.numpy import linalg
 
 
diff --git a/tests/backend/test_numpy_random_masked_parameters.py b/tests/backend/test_numpy_random_masked_parameters.py
index b950f833b1..354b4d9255 100644
--- a/tests/backend/test_numpy_random_masked_parameters.py
+++ b/tests/backend/test_numpy_random_masked_parameters.py
@@ -1,6 +1,5 @@
 import numpy as np
 import pytest
-
 from pyrecest._backend.numpy import random
 
 
diff --git a/tests/backend/test_numpy_random_masked_size.py b/tests/backend/test_numpy_random_masked_size.py
index a1a9a3a8bc..f283db127e 100644
--- a/tests/backend/test_numpy_random_masked_size.py
+++ b/tests/backend/test_numpy_random_masked_size.py
@@ -2,7 +2,6 @@
 import pytest
 from pyrecest._backend.numpy import random
 
-
 _MASKED_SIZE_ARGUMENTS = (
     np.ma.masked,
     np.ma.array(3, mask=True),
diff --git a/tests/backend/test_pytorch_randint_dtype_bounds.py b/tests/backend/test_pytorch_randint_dtype_bounds.py
index d633ecfa4b..3de40b1f37 100644
--- a/tests/backend/test_pytorch_randint_dtype_bounds.py
+++ b/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)
 
diff --git a/tests/backend/test_pytorch_random_multivariate_normal_keywords.py b/tests/backend/test_pytorch_random_multivariate_normal_keywords.py
index f4d1982ee3..4f4fd0e773 100644
--- a/tests/backend/test_pytorch_random_multivariate_normal_keywords.py
+++ b/tests/backend/test_pytorch_random_multivariate_normal_keywords.py
@@ -1,7 +1,6 @@
 import numpy as np
 import pytest
 
-
 torch = pytest.importorskip("torch")
 from pyrecest._backend.pytorch import random  # noqa: E402
 
diff --git a/tests/distributions/test_abstract_mixture_temporal_weights.py b/tests/distributions/test_abstract_mixture_temporal_weights.py
index e18ba4cb95..a6a3ccaf71 100644
--- a/tests/distributions/test_abstract_mixture_temporal_weights.py
+++ b/tests/distributions/test_abstract_mixture_temporal_weights.py
@@ -1,7 +1,6 @@
 import unittest
 
 import numpy as np
-
 from pyrecest.distributions.abstract_mixture import _validate_mixture_weight_values
 
 
diff --git a/tests/distributions/test_complex_acg_sample_count_precision.py b/tests/distributions/test_complex_acg_sample_count_precision.py
index be98466cb2..53b99159ab 100644
--- a/tests/distributions/test_complex_acg_sample_count_precision.py
+++ b/tests/distributions/test_complex_acg_sample_count_precision.py
@@ -2,7 +2,6 @@
 from fractions import Fraction
 
 import numpy as np
-
 from pyrecest.distributions.hypersphere_subset.complex_angular_central_gaussian_distribution import (
     _validate_positive_sample_count,
 )
diff --git a/tests/distributions/test_complex_watson_temporal_sample_count.py b/tests/distributions/test_complex_watson_temporal_sample_count.py
index 12dd3e549b..ef8688604a 100644
--- a/tests/distributions/test_complex_watson_temporal_sample_count.py
+++ b/tests/distributions/test_complex_watson_temporal_sample_count.py
@@ -1,11 +1,9 @@
 import numpy as np
-import pytest
-
 import pyrecest.backend
+import pytest
 from pyrecest.backend import array, complex128
 from pyrecest.distributions import ComplexWatsonDistribution
 
-
 pytestmark = pytest.mark.skipif(
     pyrecest.backend.__backend_name__ == "jax",
     reason="Complex Watson sampling is not supported on the JAX backend",
diff --git a/tests/distributions/test_ellipsoidal_ball_temporal_sample_count.py b/tests/distributions/test_ellipsoidal_ball_temporal_sample_count.py
index 0e5cd24c2e..8a4eda0594 100644
--- a/tests/distributions/test_ellipsoidal_ball_temporal_sample_count.py
+++ b/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
 
diff --git a/tests/distributions/test_gauss_von_mises_scalar_validation.py b/tests/distributions/test_gauss_von_mises_scalar_validation.py
index 4f7a6c0b2e..db93e5af25 100644
--- a/tests/distributions/test_gauss_von_mises_scalar_validation.py
+++ b/tests/distributions/test_gauss_von_mises_scalar_validation.py
@@ -49,9 +49,7 @@ def test_rejects_nonreal_or_masked_sample_counts(invalid_count):
         0.5 + 0.0j,
     ],
 )
-def test_constructor_rejects_nonreal_or_masked_scalars(
-    parameter_name, invalid_value
-):
+def test_constructor_rejects_nonreal_or_masked_scalars(parameter_name, invalid_value):
     with pytest.raises(ValueError, match=parameter_name):
         _make_distribution(**{parameter_name: invalid_value})
 
diff --git a/tests/distributions/test_gaussian_marginalize_out_validation.py b/tests/distributions/test_gaussian_marginalize_out_validation.py
index 9da6cbc212..510256396e 100644
--- a/tests/distributions/test_gaussian_marginalize_out_validation.py
+++ b/tests/distributions/test_gaussian_marginalize_out_validation.py
@@ -1,7 +1,6 @@
 import unittest
 
 import numpy as np
-
 from pyrecest.backend import array
 from pyrecest.distributions import GaussianDistribution
 
diff --git a/tests/distributions/test_gaussian_mixture_complex_mean.py b/tests/distributions/test_gaussian_mixture_complex_mean.py
index 4604d27a14..48c3ba18df 100644
--- a/tests/distributions/test_gaussian_mixture_complex_mean.py
+++ b/tests/distributions/test_gaussian_mixture_complex_mean.py
@@ -11,12 +11,8 @@
 
 class GaussianMixtureComplexMeanTest(unittest.TestCase):
     def test_set_mean_rejects_complex_target_without_mutating_components(self):
-        component_1 = GaussianDistribution(
-            array([0.0, 1.0]), diag(array([1.0, 2.0]))
-        )
-        component_2 = GaussianDistribution(
-            array([2.0, 3.0]), diag(array([3.0, 4.0]))
-        )
+        component_1 = GaussianDistribution(array([0.0, 1.0]), diag(array([1.0, 2.0])))
+        component_2 = GaussianDistribution(array([2.0, 3.0]), diag(array([3.0, 4.0])))
         mixture = GaussianMixture([component_1, component_2], array([0.25, 0.75]))
         original_means = [to_numpy(dist.mu).copy() for dist in mixture.dists]
 
diff --git a/tests/distributions/test_hypercylindrical_zero_marginals.py b/tests/distributions/test_hypercylindrical_zero_marginals.py
index d782d86cc5..673982ab36 100644
--- a/tests/distributions/test_hypercylindrical_zero_marginals.py
+++ b/tests/distributions/test_hypercylindrical_zero_marginals.py
@@ -2,7 +2,6 @@
 from math import pi
 
 import numpy as np
-
 from pyrecest.backend import __backend_name__ as backend_name
 from pyrecest.backend import array
 from pyrecest.distributions.cart_prod.hypercylindrical_state_space_subdivision_distribution import (
diff --git a/tests/distributions/test_hypertoroidal_mixed_boolean_input_validation.py b/tests/distributions/test_hypertoroidal_mixed_boolean_input_validation.py
index decf71c831..2061319113 100644
--- a/tests/distributions/test_hypertoroidal_mixed_boolean_input_validation.py
+++ b/tests/distributions/test_hypertoroidal_mixed_boolean_input_validation.py
@@ -23,9 +23,7 @@ def test_rejects_mixed_boolean_evaluation_points(self):
 
     def test_numeric_python_sequences_remain_valid(self):
         npt.assert_allclose(as_shift_vector([0.0, 1.0], 2), [0.0, 1.0])
-        npt.assert_allclose(
-            as_hypertoroidal_points([[0.0, 1.0]], 2), [[0.0, 1.0]]
-        )
+        npt.assert_allclose(as_hypertoroidal_points([[0.0, 1.0]], 2), [[0.0, 1.0]])
 
 
 if __name__ == "__main__":
diff --git a/tests/distributions/test_hypertoroidal_python_scalar_integrand.py b/tests/distributions/test_hypertoroidal_python_scalar_integrand.py
index a94be22f9e..1c2077135b 100644
--- a/tests/distributions/test_hypertoroidal_python_scalar_integrand.py
+++ b/tests/distributions/test_hypertoroidal_python_scalar_integrand.py
@@ -1,7 +1,6 @@
 import numpy as np
 import numpy.testing as npt
 import pytest
-
 from pyrecest import backend
 from pyrecest.distributions import AbstractHypertoroidalDistribution
 
diff --git a/tests/distributions/test_linear_box_particle_temporal_count.py b/tests/distributions/test_linear_box_particle_temporal_count.py
index e75c61e84a..31e9ef6859 100644
--- a/tests/distributions/test_linear_box_particle_temporal_count.py
+++ b/tests/distributions/test_linear_box_particle_temporal_count.py
@@ -1,6 +1,5 @@
 import numpy as np
 import pytest
-
 from pyrecest.backend import array
 from pyrecest.distributions.nonperiodic.linear_box_particle_distribution import (
     LinearBoxParticleDistribution,
diff --git a/tests/distributions/test_partially_wrapped_normal_hybrid_moment_order.py b/tests/distributions/test_partially_wrapped_normal_hybrid_moment_order.py
index d1d045a31a..15c01efee8 100644
--- a/tests/distributions/test_partially_wrapped_normal_hybrid_moment_order.py
+++ b/tests/distributions/test_partially_wrapped_normal_hybrid_moment_order.py
@@ -2,7 +2,6 @@
 
 import numpy as np
 import numpy.testing as npt
-
 from pyrecest.backend import array
 from pyrecest.distributions.cart_prod.partially_wrapped_normal_distribution import (
     PartiallyWrappedNormalDistribution,
diff --git a/tests/distributions/test_piecewise_constant_interval_index_validation.py b/tests/distributions/test_piecewise_constant_interval_index_validation.py
index 521852682a..675aa59025 100644
--- a/tests/distributions/test_piecewise_constant_interval_index_validation.py
+++ b/tests/distributions/test_piecewise_constant_interval_index_validation.py
@@ -1,6 +1,5 @@
 import numpy as np
 import pytest
-
 from pyrecest.distributions.circle.piecewise_constant_distribution import (
     PiecewiseConstantDistribution,
 )
diff --git a/tests/distributions/test_se2_dirac_temporal_particle_count.py b/tests/distributions/test_se2_dirac_temporal_particle_count.py
index 20704ce014..8be4cda233 100644
--- a/tests/distributions/test_se2_dirac_temporal_particle_count.py
+++ b/tests/distributions/test_se2_dirac_temporal_particle_count.py
@@ -1,6 +1,5 @@
 import numpy as np
 import pytest
-
 from pyrecest.distributions import SE2DiracDistribution
 from pyrecest.distributions.cart_prod.abstract_hypercylindrical_distribution import (
     AbstractHypercylindricalDistribution,
@@ -18,10 +17,14 @@ def sample(self, n):
         raise AssertionError("invalid temporal counts must not reach sampling")
 
     def marginalize_linear(self):
-        raise AssertionError("marginalization must not be evaluated for count validation")
+        raise AssertionError(
+            "marginalization must not be evaluated for count validation"
+        )
 
     def marginalize_periodic(self):
-        raise AssertionError("marginalization must not be evaluated for count validation")
+        raise AssertionError(
+            "marginalization must not be evaluated for count validation"
+        )
 
 
 @pytest.mark.parametrize(
diff --git a/tests/distributions/test_so3_conversion_validation.py b/tests/distributions/test_so3_conversion_validation.py
index 09ebb67f14..d3b6f9e697 100644
--- a/tests/distributions/test_so3_conversion_validation.py
+++ b/tests/distributions/test_so3_conversion_validation.py
@@ -16,7 +16,6 @@
     SO3TangentGaussianDistribution,
 )
 
-
 _TEMPORAL_VALUES = (
     np.timedelta64(3, "ns"),
     np.timedelta64(3, "us"),
diff --git a/tests/distributions/test_von_mises_temporal_sample_count.py b/tests/distributions/test_von_mises_temporal_sample_count.py
index 467b42c503..66d58a2ad4 100644
--- a/tests/distributions/test_von_mises_temporal_sample_count.py
+++ b/tests/distributions/test_von_mises_temporal_sample_count.py
@@ -1,6 +1,5 @@
 import numpy as np
 import pytest
-
 from pyrecest.distributions import VonMisesDistribution
 
 
diff --git a/tests/distributions/test_wrapped_exponential_extreme_rate.py b/tests/distributions/test_wrapped_exponential_extreme_rate.py
index 0f24e350e6..98ec27b1e4 100644
--- a/tests/distributions/test_wrapped_exponential_extreme_rate.py
+++ b/tests/distributions/test_wrapped_exponential_extreme_rate.py
@@ -2,7 +2,6 @@
 
 import numpy as np
 import numpy.testing as npt
-
 import pyrecest.backend
 from pyrecest.backend import array
 from pyrecest.distributions.circle.wrapped_exponential_distribution import (
diff --git a/tests/distributions/test_wrapped_normal_temporal_sample_counts.py b/tests/distributions/test_wrapped_normal_temporal_sample_counts.py
index 1a697b5480..fc39951a19 100644
--- a/tests/distributions/test_wrapped_normal_temporal_sample_counts.py
+++ b/tests/distributions/test_wrapped_normal_temporal_sample_counts.py
@@ -1,6 +1,5 @@
 import numpy as np
 import pytest
-
 from pyrecest.distributions import WrappedNormalDistribution
 
 
diff --git a/tests/evaluation/test_integer_estimate_history.py b/tests/evaluation/test_integer_estimate_history.py
index 82f48dde1a..385f8379e0 100644
--- a/tests/evaluation/test_integer_estimate_history.py
+++ b/tests/evaluation/test_integer_estimate_history.py
@@ -1,7 +1,6 @@
 import numpy as np
 import numpy.testing as npt
 import pytest
-
 from pyrecest.backend import array, get_backend_name
 from pyrecest.evaluation import perform_predict_update_cycles
 from pyrecest.evaluation.configure_for_filter import register_filter_factory
diff --git a/tests/filters/test_daum_huang_particle_flow_validation.py b/tests/filters/test_daum_huang_particle_flow_validation.py
index 228fbd8c1f..8e4659c4ac 100644
--- a/tests/filters/test_daum_huang_particle_flow_validation.py
+++ b/tests/filters/test_daum_huang_particle_flow_validation.py
@@ -1,6 +1,5 @@
 import numpy as np
 import pytest
-
 from pyrecest.backend import array, to_numpy
 from pyrecest.filters.daum_huang_particle_filter import (
     gaussian_bridge_moments,
diff --git a/tests/filters/test_euclidean_boxed_particle_filter_zero_support_likelihood.py b/tests/filters/test_euclidean_boxed_particle_filter_zero_support_likelihood.py
index f1de6cd213..b4144dcfe4 100644
--- a/tests/filters/test_euclidean_boxed_particle_filter_zero_support_likelihood.py
+++ b/tests/filters/test_euclidean_boxed_particle_filter_zero_support_likelihood.py
@@ -2,7 +2,6 @@
 
 import numpy as np
 import numpy.testing as npt
-
 from pyrecest.backend import array, to_numpy
 from pyrecest.distributions.nonperiodic.linear_dirac_distribution import (
     LinearDiracDistribution,
diff --git a/tests/filters/test_gnn_pairwise_cost_weight_validation.py b/tests/filters/test_gnn_pairwise_cost_weight_validation.py
index a3be13f890..d2f3f2e6fe 100644
--- a/tests/filters/test_gnn_pairwise_cost_weight_validation.py
+++ b/tests/filters/test_gnn_pairwise_cost_weight_validation.py
@@ -36,15 +36,13 @@ def test_rejects_invalid_pairwise_cost_weights(self):
     def test_accepts_finite_nonnegative_scalar_weights(self):
         for valid_weight in (0, 0.5, np.float64(2.0)):
             with self.subTest(pairwise_cost_weight=valid_weight):
-                validated_weight = (
-                    GlobalNearestNeighbor._validate_pairwise_cost_weight(valid_weight)
+                validated_weight = GlobalNearestNeighbor._validate_pairwise_cost_weight(
+                    valid_weight
                 )
                 self.assertEqual(validated_weight, float(valid_weight))
 
     def test_zero_weight_ignores_positive_infinite_pairwise_gate(self):
-        tracker = GlobalNearestNeighbor(
-            association_param={"pairwise_cost_weight": 0.0}
-        )
+        tracker = GlobalNearestNeighbor(association_param={"pairwise_cost_weight": 0.0})
         geometric_costs = np.array([[1.25]])
 
         combined_costs = tracker._apply_pairwise_cost_matrix(
@@ -54,9 +52,7 @@ def test_zero_weight_ignores_positive_infinite_pairwise_gate(self):
         npt.assert_array_equal(combined_costs, geometric_costs)
 
     def test_positive_weight_scales_pairwise_costs(self):
-        tracker = GlobalNearestNeighbor(
-            association_param={"pairwise_cost_weight": 2.0}
-        )
+        tracker = GlobalNearestNeighbor(association_param={"pairwise_cost_weight": 2.0})
 
         combined_costs = tracker._apply_pairwise_cost_matrix(
             np.array([[1.0, 2.0]]), np.array([[3.0, 4.0]])
diff --git a/tests/filters/test_gnn_pairwise_object_cost_validation.py b/tests/filters/test_gnn_pairwise_object_cost_validation.py
index 1956a965ac..53222d0fb1 100644
--- a/tests/filters/test_gnn_pairwise_object_cost_validation.py
+++ b/tests/filters/test_gnn_pairwise_object_cost_validation.py
@@ -78,12 +78,10 @@ def test_rejects_native_temporal_dtypes(self):
                     )
 
     def test_accepts_real_numeric_values(self):
-        pairwise_cost_matrix = (
-            GlobalNearestNeighbor._validate_pairwise_cost_matrix(
-                [[1, 2.5]],
-                1,
-                2,
-            )
+        pairwise_cost_matrix = GlobalNearestNeighbor._validate_pairwise_cost_matrix(
+            [[1, 2.5]],
+            1,
+            2,
         )
 
         np.testing.assert_allclose(pairwise_cost_matrix, [[1.0, 2.5]])
diff --git a/tests/filters/test_measurement_reliability_temporal_counts.py b/tests/filters/test_measurement_reliability_temporal_counts.py
index 2abed5d82b..4ff98c2a3b 100644
--- a/tests/filters/test_measurement_reliability_temporal_counts.py
+++ b/tests/filters/test_measurement_reliability_temporal_counts.py
@@ -1,7 +1,6 @@
 import unittest
 
 import numpy as np
-
 from pyrecest.filters import (
     normalize_active_measurement_mask,
     normalize_measurement_noise_covariances,
diff --git a/tests/filters/test_mode_rbpf_manifold_ukf_tracker.py b/tests/filters/test_mode_rbpf_manifold_ukf_tracker.py
index bd6e3c87ae..ca3e7521eb 100644
--- a/tests/filters/test_mode_rbpf_manifold_ukf_tracker.py
+++ b/tests/filters/test_mode_rbpf_manifold_ukf_tracker.py
@@ -161,7 +161,6 @@ def test_update_without_measurements_is_noop(self):
 
         npt.assert_allclose(posterior, prior)
 
-
     def test_preserves_impossible_mode_probabilities(self):
         transition_matrix = np.eye(3)
         tracker = self.make_tracker(
diff --git a/tests/filters/test_nonadditive_arraylike_samples.py b/tests/filters/test_nonadditive_arraylike_samples.py
index ae6d5c316c..67907c49e3 100644
--- a/tests/filters/test_nonadditive_arraylike_samples.py
+++ b/tests/filters/test_nonadditive_arraylike_samples.py
@@ -1,5 +1,4 @@
 import numpy.testing as npt
-
 from pyrecest.backend import array
 from pyrecest.distributions import LinearDiracDistribution
 from pyrecest.filters.euclidean_particle_filter import EuclideanParticleFilter
@@ -7,9 +6,7 @@
 
 def test_predict_nonlinear_nonadditive_accepts_array_like_samples_and_weights():
     particle_filter = EuclideanParticleFilter(n_particles=3, dim=1)
-    particle_filter.filter_state = LinearDiracDistribution(
-        array([[0.0], [1.0], [2.0]])
-    )
+    particle_filter.filter_state = LinearDiracDistribution(array([[0.0], [1.0], [2.0]]))
 
     particle_filter.predict_nonlinear_nonadditive(
         lambda particle, noise: particle + noise,
diff --git a/tests/filters/test_particle_filter_count_precision.py b/tests/filters/test_particle_filter_count_precision.py
index def36a006b..9dee320f71 100644
--- a/tests/filters/test_particle_filter_count_precision.py
+++ b/tests/filters/test_particle_filter_count_precision.py
@@ -35,9 +35,7 @@ def test_particle_filter_count_validation_is_exact(validator):
         np.timedelta64(3, "ns"),
         np.datetime64("1970-01-01T00:00:00.000000003"),
         np.array(np.timedelta64(3, "ns"), dtype=object),
-        np.array(
-            np.datetime64("1970-01-01T00:00:00.000000003"), dtype=object
-        ),
+        np.array(np.datetime64("1970-01-01T00:00:00.000000003"), dtype=object),
     ],
     ids=["timedelta", "datetime", "object-timedelta", "object-datetime"],
 )
diff --git a/tests/filters/test_relaxed_s3f_process_noise_validation.py b/tests/filters/test_relaxed_s3f_process_noise_validation.py
index b8d1cdca07..a02a22037c 100644
--- a/tests/filters/test_relaxed_s3f_process_noise_validation.py
+++ b/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()
             )
         )
 
diff --git a/tests/filters/test_sequence_association_temporal_validation.py b/tests/filters/test_sequence_association_temporal_validation.py
index 895b4fc60d..a3fb56a458 100644
--- a/tests/filters/test_sequence_association_temporal_validation.py
+++ b/tests/filters/test_sequence_association_temporal_validation.py
@@ -6,7 +6,6 @@
     solve_viterbi_sequence_association,
 )
 
-
 _TEMPORAL_VALUES = (
     pytest.param(np.timedelta64(1, "ns"), id="timedelta-ns"),
     pytest.param(np.timedelta64(1, "us"), id="timedelta-us"),
diff --git a/tests/models/test_linear_gaussian_finite_inputs.py b/tests/models/test_linear_gaussian_finite_inputs.py
index 07c87cc393..0227adce6d 100644
--- a/tests/models/test_linear_gaussian_finite_inputs.py
+++ b/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):
diff --git a/tests/smoothers/test_mem_rbpf_ffbsi_option_validation.py b/tests/smoothers/test_mem_rbpf_ffbsi_option_validation.py
index 0e6ba4fcfe..33fcc8e481 100644
--- a/tests/smoothers/test_mem_rbpf_ffbsi_option_validation.py
+++ b/tests/smoothers/test_mem_rbpf_ffbsi_option_validation.py
@@ -6,7 +6,6 @@
 from pyrecest import backend
 from pyrecest.smoothers import MEMRBPFFFBSiSmoother, MEMRBPFForwardRecord
 
-
 pytestmark = pytest.mark.skipif(
     backend.__backend_name__ != "numpy",
     reason="MEM-RBPF FFBSi tests use NumPy sampling paths",
diff --git a/tests/test_deprecation_helper.py b/tests/test_deprecation_helper.py
index ef851b7ed4..7251d5a62f 100644
--- a/tests/test_deprecation_helper.py
+++ b/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")
diff --git a/tests/test_evidence_support_masked_flags.py b/tests/test_evidence_support_masked_flags.py
index 8db18cec28..0e5da4518a 100644
--- a/tests/test_evidence_support_masked_flags.py
+++ b/tests/test_evidence_support_masked_flags.py
@@ -1,6 +1,5 @@
 import numpy as np
 import pytest
-
 from pyrecest.diagnostics import EvidenceSupport
 
 
diff --git a/tests/test_evidence_terminal_posterior_validation.py b/tests/test_evidence_terminal_posterior_validation.py
index 0f0cf09aa5..33f52d94b3 100644
--- a/tests/test_evidence_terminal_posterior_validation.py
+++ b/tests/test_evidence_terminal_posterior_validation.py
@@ -1,5 +1,4 @@
 import pytest
-
 from pyrecest.evidence import EvidenceComputationMode
 
 
diff --git a/tests/test_gaussian_sampler_zero_samples.py b/tests/test_gaussian_sampler_zero_samples.py
index 22397d2cab..bd4d6b1083 100644
--- a/tests/test_gaussian_sampler_zero_samples.py
+++ b/tests/test_gaussian_sampler_zero_samples.py
@@ -1,5 +1,4 @@
 import numpy as np
-
 from pyrecest.sampling.euclidean_sampler import GaussianSampler
 
 
diff --git a/tests/test_group_results_by_filter.py b/tests/test_group_results_by_filter.py
index 7eb8b683f3..8ae2c73b79 100644
--- a/tests/test_group_results_by_filter.py
+++ b/tests/test_group_results_by_filter.py
@@ -28,9 +28,7 @@ def test_nan_parameter_does_not_disrupt_numeric_order(self):
 
         grouped = group_results_by_filter(rows)["pf"]
 
-        self.assertEqual(
-            grouped["score"], ["none", "zero", "one", "nan", "category"]
-        )
+        self.assertEqual(grouped["score"], ["none", "zero", "one", "nan", "category"])
         self.assertTrue(math.isnan(grouped["parameter"][3]))
 
 
diff --git a/tests/test_history_recorder_masked_flags.py b/tests/test_history_recorder_masked_flags.py
index ac228ccab6..f265d1fe3f 100644
--- a/tests/test_history_recorder_masked_flags.py
+++ b/tests/test_history_recorder_masked_flags.py
@@ -1,6 +1,5 @@
 import numpy as np
 import pytest
-
 from pyrecest.utils import HistoryRecorder
 
 
diff --git a/tests/test_history_recorder_masked_values.py b/tests/test_history_recorder_masked_values.py
index ddf4e75bab..1761c85390 100644
--- a/tests/test_history_recorder_masked_values.py
+++ b/tests/test_history_recorder_masked_values.py
@@ -1,8 +1,7 @@
 import numpy as np
 import numpy.testing as npt
-import pytest
-
 import pyrecest.backend as backend
+import pytest
 from pyrecest.utils import HistoryRecorder
 
 
diff --git a/tests/test_hypertoroidal_sampler_masked_controls.py b/tests/test_hypertoroidal_sampler_masked_controls.py
index 690c0c0f82..95f4c43cf6 100644
--- a/tests/test_hypertoroidal_sampler_masked_controls.py
+++ b/tests/test_hypertoroidal_sampler_masked_controls.py
@@ -1,7 +1,6 @@
 import unittest
 
 import numpy as np
-
 from pyrecest.sampling.hypertoroidal_sampler import (
     CircularUniformSampler,
     _validate_integral_scalar,
diff --git a/tests/test_leopardi_small_symmetric_partitions.py b/tests/test_leopardi_small_symmetric_partitions.py
index 90aa4b35cf..5a2a8376d9 100644
--- a/tests/test_leopardi_small_symmetric_partitions.py
+++ b/tests/test_leopardi_small_symmetric_partitions.py
@@ -3,7 +3,6 @@
 import pytest
 from pyrecest.sampling.leopardi_sampler import get_partition_points_cartesian
 
-
 pytestmark = pytest.mark.skipif(
     pyrecest.backend.__backend_name__ == "jax",
     reason="Leopardi sampling uses SciPy root finding.",
diff --git a/tests/test_metrics_temporal_counts.py b/tests/test_metrics_temporal_counts.py
index 84650c8ae4..99e0842753 100644
--- a/tests/test_metrics_temporal_counts.py
+++ b/tests/test_metrics_temporal_counts.py
@@ -1,9 +1,7 @@
 import numpy as np
 import pytest
-
 from pyrecest.utils.metrics import chi_square_confidence_bounds
 
-
 _TEMPORAL_COUNTS = (
     np.timedelta64(2, "ns"),
     np.timedelta64(2, "us"),
diff --git a/tests/test_model_comparison_comparable_flags.py b/tests/test_model_comparison_comparable_flags.py
index bef9fa05e9..8edaa14e9d 100644
--- a/tests/test_model_comparison_comparable_flags.py
+++ b/tests/test_model_comparison_comparable_flags.py
@@ -1,5 +1,4 @@
 import pandas as pd
-
 from pyrecest.evaluation.model_comparison import (
     evidence_margin_table,
     paired_model_margin_decisions,
diff --git a/tests/test_pytorch_array_equal_mixed_dtypes.py b/tests/test_pytorch_array_equal_mixed_dtypes.py
index 8e318e0e8b..e9f8cdc19c 100644
--- a/tests/test_pytorch_array_equal_mixed_dtypes.py
+++ b/tests/test_pytorch_array_equal_mixed_dtypes.py
@@ -35,9 +35,7 @@ def test_mixed_int64_float32_comparison_matches_numpy(self):
             pytorch_backend.array_equal(integer_tensor, float_tensor), expected
         )
         self.assertEqual(
-            pytorch_backend.array_equal(
-                integer_tensor, float_tensor, equal_nan=True
-            ),
+            pytorch_backend.array_equal(integer_tensor, float_tensor, equal_nan=True),
             expected,
         )
 
diff --git a/tests/test_pytorch_split_index_contract.py b/tests/test_pytorch_split_index_contract.py
index e4b94f39cb..f066514b0f 100644
--- a/tests/test_pytorch_split_index_contract.py
+++ b/tests/test_pytorch_split_index_contract.py
@@ -2,7 +2,6 @@
 from fractions import Fraction
 
 import numpy as np
-
 from pyrecest.backend_support._pytorch_split_index_contract import (
     _normalize_split_section_count,
 )
diff --git a/tests/test_sigma_points_masked_parameters.py b/tests/test_sigma_points_masked_parameters.py
index 2c68cc30cf..1fbb9eede6 100644
--- a/tests/test_sigma_points_masked_parameters.py
+++ b/tests/test_sigma_points_masked_parameters.py
@@ -1,6 +1,5 @@
 import numpy as np
 import pytest
-
 from pyrecest.sampling import JulierSigmaPoints, MerweScaledSigmaPoints
 
 
diff --git a/tests/test_sigma_points_temporal_parameters.py b/tests/test_sigma_points_temporal_parameters.py
index bcfaacd403..b7185b3815 100644
--- a/tests/test_sigma_points_temporal_parameters.py
+++ b/tests/test_sigma_points_temporal_parameters.py
@@ -1,9 +1,7 @@
 import numpy as np
 import pytest
-
 from pyrecest.sampling import JulierSigmaPoints, MerweScaledSigmaPoints
 
-
 _TEMPORAL_VALUES = (
     np.timedelta64(2, "ns"),
     np.timedelta64(2, "us"),
diff --git a/tests/tracking/test_hypothesis_replay_temporal_validation.py b/tests/tracking/test_hypothesis_replay_temporal_validation.py
index 5a581260e2..4dfa2c21cb 100644
--- a/tests/tracking/test_hypothesis_replay_temporal_validation.py
+++ b/tests/tracking/test_hypothesis_replay_temporal_validation.py
@@ -8,7 +8,6 @@
     rank_hypothesis_replays,
 )
 
-
 _TEMPORAL_VALUES = (
     np.timedelta64(2, "ns"),
     np.datetime64("1970-01-01T00:00:00.000000002"),
@@ -45,9 +44,7 @@ def test_temporal_record_statistics_are_ignored() -> None:
         records=[
             {
                 "nis": np.timedelta64(4, "ns"),
-                "residual_norm_m": np.datetime64(
-                    "1970-01-01T00:00:00.000000005"
-                ),
+                "residual_norm_m": np.datetime64("1970-01-01T00:00:00.000000005"),
             },
             {
                 "nis": np.asarray(np.timedelta64(6, "ns"), dtype=object),
diff --git a/tests/utils/test_association_model_failed_refit.py b/tests/utils/test_association_model_failed_refit.py
index ee8abe1ed6..24e6e53be0 100644
--- a/tests/utils/test_association_model_failed_refit.py
+++ b/tests/utils/test_association_model_failed_refit.py
@@ -1,6 +1,5 @@
 import numpy.testing as npt
 import pytest
-
 from pyrecest.backend import array, zeros
 from pyrecest.utils import LogisticPairwiseAssociationModel
 
@@ -17,9 +16,7 @@ def test_failed_refit_preserves_previous_fitted_state():
     converged_before = model.converged_
     class_weights_before = model.class_weights_
 
-    replacement_features = array(
-        [[-2.0, 0.0], [-1.0, 0.0], [1.0, 0.0], [2.0, 0.0]]
-    )
+    replacement_features = array([[-2.0, 0.0], [-1.0, 0.0], [1.0, 0.0], [2.0, 0.0]])
     with pytest.raises(
         ValueError, match="At least one example must receive positive weight"
     ):
diff --git a/tests/utils/test_history_recorder_empty_steps.py b/tests/utils/test_history_recorder_empty_steps.py
index 75dd94f1e8..d8073885d6 100644
--- a/tests/utils/test_history_recorder_empty_steps.py
+++ b/tests/utils/test_history_recorder_empty_steps.py
@@ -14,9 +14,7 @@ def test_empty_padded_record_preserves_time_axis():
 
     recorder.record("estimate", backend.array([1.0, 2.0]), pad_with_nan=True)
     recorder.record("estimate", backend.array([]), pad_with_nan=True)
-    history = recorder.record(
-        "estimate", backend.array([3.0]), pad_with_nan=True
-    )
+    history = recorder.record("estimate", backend.array([3.0]), pad_with_nan=True)
 
     npt.assert_allclose(
         _to_numpy(history),