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RF: adjusted some type desciptions
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nibabel/cifti2/cifti2_axes.py

Lines changed: 8 additions & 8 deletions
Original file line numberDiff line numberDiff line change
@@ -31,7 +31,7 @@ def to_header(axes):
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Parameters
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----------
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axes : iterable[Axis]
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axes : iterable of :py:class:`Axis` objects
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one or more axes describing each dimension in turn
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Returns
@@ -140,10 +140,10 @@ def __init__(self, name, voxel=None, vertex=None, affine=None,
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affine : np.ndarray
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(4, 4) array mapping voxel indices to mm space (not needed for CIFTI files only
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covering the surface)
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volume_shape : Tuple[int, int, int]
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volume_shape : tuple of three integers
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shape of the volume in which the voxels were defined (not needed for CIFTI files only
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covering the surface)
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nvertices : dict[String -> int]
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nvertices : dict from string to integer
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maps names of surface elements to integers (not needed for volumetric CIFTI files)
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"""
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if voxel is None:
@@ -361,7 +361,7 @@ def to_cifti_brain_structure_name(name):
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Parameters
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----------
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name: (str, tuple)
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name: iterable of 2-element tuples of integer and string
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input name of an anatomical region
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Returns
@@ -598,7 +598,7 @@ def __init__(self, name, voxels, vertices, affine=None, volume_shape=None, nvert
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affine : np.ndarray
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(4, 4) array mapping voxel indices to mm space (not needed for CIFTI files only
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covering the surface)
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volume_shape : Tuple[int, int, int]
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volume_shape : tuple of three integers
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shape of the volume in which the voxels were defined (not needed for CIFTI files only
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covering the surface)
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nvertices : dict[String -> int]
@@ -634,7 +634,7 @@ def from_brain_models(cls, named_brain_models):
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Parameters
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----------
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named_brain_models : List[Tuple[String, BrainModel]]
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named_brain_models : iterable of 2-element tuples of string and BrainModel
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list of (parcel name, brain model representation) pairs defining each parcel
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Returns
@@ -889,9 +889,9 @@ def __init__(self, name, meta=None):
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"""
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Parameters
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----------
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name : np.ndarray
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name : np.ndarray of string
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(N, ) string array with the parcel names
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meta : np.ndarray
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meta : np.ndarray of dict
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(N, ) object array with a dictionary of metadata for each row/column.
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Defaults to empty dictionary
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"""

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