Sep 19, 2023 · Sep 20, 2023 · Sep 20, 2023 · Sep 20, 2023 · Sep 20, 2023 · Sep 22, 2023
diff --git a/nibabel/coordimage.py b/nibabel/coordimage.py
 import numpy as np

 import nibabel as nib
 import nibabel.pointset as ps
 from nibabel.fileslice import fill_slicer


        self.coordaxis = coordaxis
        self.header = header

    @classmethod
    def from_image(klass, img):
        coordaxis = CoordinateAxis.from_header(img.header)
        if isinstance(img, nib.Cifti2Image):
            if img.ndim != 2:
                raise ValueError('Can only interpret 2D images')
            for i in img.header.mapped_indices:
                if isinstance(img.header.get_axis(i), nib.cifti2.BrainModelAxis):
                    break
            # Reinterpret data ordering based on location of coordinate axis
            data = img.dataobj.copy()
            data.order = ['F', 'C'][i]
            if i == 1:
                data._shape = data._shape[::-1]
        return klass(data, coordaxis, img.header)


 class CoordinateAxis:
    """
    def __len__(self):
        return sum(len(parcel) for parcel in self.parcels)

    # Hacky factory method for now
    @classmethod
    def from_header(klass, hdr):
        parcels = []
        if isinstance(hdr, nib.Cifti2Header):
            axes = [hdr.get_axis(i) for i in hdr.mapped_indices]
            for ax in axes:
                if isinstance(ax, nib.cifti2.BrainModelAxis):
                    break
            else:
                raise ValueError('No BrainModelAxis, cannot create CoordinateAxis')
            for name, slicer, struct in ax.iter_structures():
                if struct.volume_shape:
                    substruct = ps.NdGrid(struct.volume_shape, struct.affine)
                    indices = struct.voxel
                else:
                    substruct = None
                    indices = struct.vertex
                parcels.append(Parcel(name, substruct, indices))

        return klass(parcels)


 class Parcel:
    """
diff --git a/nibabel/tests/test_coordimage.py b/nibabel/tests/test_coordimage.py

 def test_Cifti2Image_as_CoordImage():
    ones = nb.load(CIFTI2_DATA / 'ones.dscalar.nii')
    axes = [ones.header.get_axis(i) for i in range(ones.ndim)]

    parcels = []
    for name, slicer, bma in axes[1].iter_structures():
        if bma.volume_shape:
            substruct = ps.NdGrid(bma.volume_shape, bma.affine)
            indices = bma.voxel
        else:
            substruct = None
            indices = bma.vertex
        parcels.append(ci.Parcel(name, None, indices))
    caxis = ci.CoordinateAxis(parcels)
    dobj = ones.dataobj.copy()
    dobj.order = 'C'  # Hack for image with BMA as the last axis
    cimg = ci.CoordinateImage(dobj, caxis, ones.header)
    assert ones.shape == (1, 91282)
    cimg = ci.CoordinateImage.from_image(ones)
    assert cimg.shape == (91282, 1)

    caxis = cimg.coordaxis
    assert len(caxis) == 91282
    assert caxis[...] is caxis
    assert caxis[:] is caxis
Original file line number	Diff line number	Diff line change
		@@ -1,5 +1,7 @@
		import numpy as np

		import nibabel as nib
		import nibabel.pointset as ps
		from nibabel.fileslice import fill_slicer


Expand All		@@ -17,6 +19,22 @@ def __init__(self, data, coordaxis, header=None):
		self.coordaxis = coordaxis
		self.header = header

		@classmethod
		def from_image(klass, img):
		coordaxis = CoordinateAxis.from_header(img.header)
		if isinstance(img, nib.Cifti2Image):
		if img.ndim != 2:
		raise ValueError('Can only interpret 2D images')
		for i in img.header.mapped_indices:
		if isinstance(img.header.get_axis(i), nib.cifti2.BrainModelAxis):
		break
		# Reinterpret data ordering based on location of coordinate axis
		data = img.dataobj.copy()
		data.order = ['F', 'C'][i]
		if i == 1:
		data._shape = data._shape[::-1]
		return klass(data, coordaxis, img.header)


		class CoordinateAxis:
		"""
Expand DownExpand Up		@@ -85,6 +103,28 @@ def get_indices(self, parcel, indices=None):
		def __len__(self):
		return sum(len(parcel) for parcel in self.parcels)

		# Hacky factory method for now
		@classmethod
		def from_header(klass, hdr):
		parcels = []
		if isinstance(hdr, nib.Cifti2Header):
		axes = [hdr.get_axis(i) for i in hdr.mapped_indices]
		for ax in axes:
		if isinstance(ax, nib.cifti2.BrainModelAxis):
		break
		else:
		raise ValueError('No BrainModelAxis, cannot create CoordinateAxis')
		for name, slicer, struct in ax.iter_structures():
		if struct.volume_shape:
		substruct = ps.NdGrid(struct.volume_shape, struct.affine)
		indices = struct.voxel
		else:
		substruct = None
		indices = struct.vertex
		parcels.append(Parcel(name, substruct, indices))

		return klass(parcels)


		class Parcel:
		"""
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -51,22 +51,12 @@ def from_spec(klass, pathlike):

		def test_Cifti2Image_as_CoordImage():
		ones = nb.load(CIFTI2_DATA / 'ones.dscalar.nii')
		axes = [ones.header.get_axis(i) for i in range(ones.ndim)]

		parcels = []
		for name, slicer, bma in axes[1].iter_structures():
		if bma.volume_shape:
		substruct = ps.NdGrid(bma.volume_shape, bma.affine)
		indices = bma.voxel
		else:
		substruct = None
		indices = bma.vertex
		parcels.append(ci.Parcel(name, None, indices))
		caxis = ci.CoordinateAxis(parcels)
		dobj = ones.dataobj.copy()
		dobj.order = 'C' # Hack for image with BMA as the last axis
		cimg = ci.CoordinateImage(dobj, caxis, ones.header)
		assert ones.shape == (1, 91282)
		cimg = ci.CoordinateImage.from_image(ones)
		assert cimg.shape == (91282, 1)

		caxis = cimg.coordaxis
		assert len(caxis) == 91282
		assert caxis[...] is caxis
		assert caxis[:] is caxis

Expand Down