torchio.transforms.preprocessing.spatial.transpose.Transpose.apply_transform() - Code Metrics - Inspection of "Add Transpose transform (#1350)" - TorchIO-project/torchio - Measure and Improve Code Quality continuously with Scrutinizer

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by Fernando

created 2025-07-19 09:27 UTC

Transpose.apply_transform() A

↳ Parent: torchio.transforms.preprocessing.spatial.transpose

Complexity

Conditions

Size

Total Lines	9
Code Lines	9

Duplication

Lines	0
Ratio	0 %

Importance

Changes

Metric	Value
cc	2
eloc	9
nop	2
dl	0
loc	9
rs	9.95
c	0
b	0
f	0

from ....data.subject import Subject
from ...spatial_transform import SpatialTransform
from .to_orientation import ToOrientation


class Transpose(SpatialTransform):
    """Swap the first and last spatial dimensions of the image.

    The spatial metadata is updated accordingly, so the world coordinates of
    all voxels in the input and output spaces match.

    Example:

    >>> import torchio as tio
    >>> image = tio.datasets.FPG().t1
    >>> image
    ScalarImage(shape: (1, 256, 256, 176); spacing: (1.00, 1.00, 1.00); orientation: PIR+; path: "/home/fernando/.cache/torchio/fpg/t1.nii.gz")
    >>> transpose = tio.Transpose()
    >>> transposed = transpose(image)
    >>> transposed
    ScalarImage(shape: (1, 176, 256, 256); spacing: (1.00, 1.00, 1.00); orientation: RIP+; dtype: torch.IntTensor; memory: 44.0 MiB)
    """

    def apply_transform(self, subject: Subject) -> Subject:
        for image in self.get_images(subject):
            old_orientation = image.orientation_str
            new_orientation = old_orientation[::-1]
            transform = ToOrientation(new_orientation)
            transposed = transform(image)
            image.set_data(transposed.data)
            image.affine = transposed.affine
        return subject

    def is_invertible(self):
        return True

    def inverse(self):
        return self


1			from ....data.subject import Subject
2			from ...spatial_transform import SpatialTransform
3			from .to_orientation import ToOrientation
4
5
6			class Transpose(SpatialTransform):
7			"""Swap the first and last spatial dimensions of the image.
8
9			The spatial metadata is updated accordingly, so the world coordinates of
10			all voxels in the input and output spaces match.
11
12			Example:
13
14			>>> import torchio as tio
15			>>> image = tio.datasets.FPG().t1
16			>>> image
17			ScalarImage(shape: (1, 256, 256, 176); spacing: (1.00, 1.00, 1.00); orientation: PIR+; path: "/home/fernando/.cache/torchio/fpg/t1.nii.gz")
18			>>> transpose = tio.Transpose()
19			>>> transposed = transpose(image)
20			>>> transposed
21			ScalarImage(shape: (1, 176, 256, 256); spacing: (1.00, 1.00, 1.00); orientation: RIP+; dtype: torch.IntTensor; memory: 44.0 MiB)
22			"""
23
24			def apply_transform(self, subject: Subject) -> Subject:
25			for image in self.get_images(subject):
26			old_orientation = image.orientation_str
27			new_orientation = old_orientation[::-1]
28			transform = ToOrientation(new_orientation)
29			transposed = transform(image)
30			image.set_data(transposed.data)
31			image.affine = transposed.affine
32			return subject
33
34			def is_invertible(self):
35			return True
36
37			def inverse(self):
38			return self
39

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Transpose.apply_transform() A

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