algorithms.statistics.utils
Module: algorithms.statistics.utils
Functions
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nipy.algorithms.statistics.utils.combinations(iterable, r)
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nipy.algorithms.statistics.utils.complex(maximal=[, (0, 3, 2, 7), (0, 6, 2, 7), (0, 7, 5, 4), (0, 7, 5, 1), (0, 7, 4, 6), (0, 3, 1, 7)], vertices=None)
Take a list of maximal simplices (by
default a triangulation of a cube into 6 tetrahedra) and
computes all faces, edges, vertices.
If vertices is not None, then the
vertices in ‘maximal’ are replaced with
these vertices, by index.
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nipy.algorithms.statistics.utils.cube_with_strides_center(center=[, 0, 0, 0], strides=(4, 2, 1))
Cube in an array of voxels with a given center and strides.
This triangulates a cube with vertices [center[i] + 1].
The dimension of the cube is determined by len(center)
which should agree with len(center).
The allowable dimensions are [1,2,3].
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nipy.algorithms.statistics.utils.decompose2d(shape, dim=3)
- Return all (dim-1)-dimensional simplices in a triangulation
of a square of a given shape. The vertices in the triangulation
are indices in a ‘flattened’ array of the specified shape.
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nipy.algorithms.statistics.utils.decompose3d(shape, dim=4)
- Return all (dim-1)-dimensional simplices in a triangulation
of a cube of a given shape. The vertices in the triangulation
are indices in a ‘flattened’ array of the specified shape.
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nipy.algorithms.statistics.utils.join_complexes(*complexes)
- Join a sequence of simplicial complexes.
Returns the union of all the particular faces.
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nipy.algorithms.statistics.utils.test_EC2(shape)
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nipy.algorithms.statistics.utils.test_EC3(shape)