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[MegaLinter] Apply linters automatic fixes #2050

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Merged
FlorianPfaff merged 1 commit into from
May 15, 2026
Merged

[MegaLinter] Apply linters automatic fixes #2050

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23 changes: 16 additions & 7 deletions src/pyrecest/filters/iterated_batch_mem_qkf_tracker.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,7 +4,6 @@

# pylint: disable=no-name-in-module,no-member,too-many-arguments,too-many-locals,protected-access
import numpy as np

from pyrecest.backend import array, diag, linalg, mean, zeros

from .mem_qkf_tracker import MEMQKFTracker
Expand Down Expand Up @@ -151,9 +150,13 @@ def update(
shape_measurement_covariance=shape_measurement_covariance,
)
)
posterior_orientation = prior_orientation + self.damping * self._axial_delta(
prior_orientation,
full_orientation,
posterior_orientation = (
prior_orientation
+ self.damping
* self._axial_delta(
prior_orientation,
full_orientation,
)
)

full_axes, posterior_axis_covariance = self._batch_axis_posterior(
Expand Down Expand Up @@ -208,7 +211,9 @@ def _batch_extent_center_and_additive_covariance(
return mean(measurements, axis=1), zeros((2, 2))

center_estimate = measurement_matrix @ self.kinematic_state
additive_shape_covariance = measurement_matrix @ self.covariance @ measurement_matrix.T
additive_shape_covariance = (
measurement_matrix @ self.covariance @ measurement_matrix.T
)
return center_estimate, additive_shape_covariance

# pylint: disable=too-many-arguments,too-many-positional-arguments
Expand Down Expand Up @@ -247,7 +252,9 @@ def _batch_orientation_posterior(
]
)

extent_covariance = extent_transform @ multiplicative_noise_cov @ extent_transform.T
extent_covariance = (
extent_transform @ multiplicative_noise_cov @ extent_transform.T
)
orientation_covariance = orientation_variance * array(
[
[
Expand Down Expand Up @@ -428,7 +435,9 @@ def _batch_axis_posterior(
- axis_sensitivity @ (prior_axes - semi_axes)
)
posterior_axes = prior_axes + axis_gain @ innovation
posterior_axis_covariance = axis_covariance - axis_gain @ axis_cross_covariance.T
posterior_axis_covariance = (
axis_covariance - axis_gain @ axis_cross_covariance.T
)
return posterior_axes, self._symmetrize(posterior_axis_covariance)

@staticmethod
Expand Down