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algorithms.statistics.utils

Module: algorithms.statistics.utils

Functions

nipy.algorithms.statistics.utils.combinations(iterable, r)
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.

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].

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.
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.
nipy.algorithms.statistics.utils.join_complexes(*complexes)
Join a sequence of simplicial complexes. Returns the union of all the particular faces.
nipy.algorithms.statistics.utils.test_EC2(shape)
nipy.algorithms.statistics.utils.test_EC3(shape)