torchio.transforms.preprocessing.spatial.transpose

Complexity

Total Complexity

4

Size/Duplication

Total Lines	34
Duplicated Lines	0 %

Importance

Changes

0

3 Methods

Rating	Name	Duplication	Size	Complexity
A	Transpose.inverse()	0	2	1
A	Transpose.is_invertible()	0	2	1
A	Transpose.apply_transform()	0	7	2

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, respecting metadata.

    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):
            transform = ToOrientation(image.orientation_str[::-1])
            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