11from __future__ import annotations
22
3- import warnings
43from abc import abstractmethod
54from collections .abc import Callable , Mapping
65from dataclasses import dataclass
@@ -668,18 +667,15 @@ def _(
668667
669668 # materialize the points in the intrinsic coordinate system once
670669 points_pd = points .compute ()
671-
670+
672671 # checking the type of the transformation
673672 # in the case of an identity or scaling transform, we can skip the whole
674673 # projection into intrinsic space and reprojection into the global coordinate system
675674 is_identity_transform = input_axes_without_c == output_axes_without_c and np .allclose (
676675 m_without_c , np .eye (m_without_c .shape [0 ])
677676 )
678- is_scaling_transform = (
679- input_axes_without_c == output_axes_without_c
680- and _is_scaling_transform (m_without_c_linear )
681- )
682-
677+ is_scaling_transform = input_axes_without_c == output_axes_without_c and _is_scaling_transform (m_without_c_linear )
678+
683679 # if the transform is identity, we can save extra for the affine transformation
684680 if is_identity_transform :
685681 bounding_box_masks = _bounding_box_mask_points (
@@ -691,8 +687,8 @@ def _(
691687 )
692688 elif is_scaling_transform :
693689 # Pull scale factors from the diagonal and the translation from the last column
694- scales = np .diagonal (m_without_c_linear ) # shape: (n_axes,)
695- translation = m_without_c [:- 1 , - 1 ] # shape: (n_axes,)
690+ scales = np .diagonal (m_without_c_linear ) # shape: (n_axes,)
691+ translation = m_without_c [:- 1 , - 1 ] # shape: (n_axes,)
696692
697693 # Invert the affine: x_intrinsic = (x_output - translation) / scale
698694 min_intrinsic = (min_coordinate_adjusted - translation ) / scales
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