Return binary array arr as uint8 type, or raise if not binary.
Parameters: | arr : array-like |
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Returns: | bin8_arr : uint8 array
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Raises: | ValueError :
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Faces from simplices
Take a list of maximal simplices (by default a triangulation of a cube into 6 tetrahedra) and computes all faces
Parameters: | maximal : sequence of sequences, optional
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Returns: | faces : dict |
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].
Parameters: | center : (d,) sequence of int, optional
strides : (d,) sequence of int, optional
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Returns: | complex : dict
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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.
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.
Join a sequence of simplicial complexes.
Returns the union of all the particular faces.
Compute the inverse of a set of arrays in-place
Parameters: | a: array_like of shape (n_samples, M, M) :
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Returns: | a: ndarray shape (n_samples, M, M) :
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Raises: | LinAlgError : :
ValueError : :
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Notes
This function is copied from scipy.linalg.inv, but with some customizations for speed-up from operating on multiple arrays. It also has some conditionals to work with different scipy versions.
Returns the squared Mahalanobis distance for a given set of samples
Parameters: | effect: array of shape (n_features, n_samples), :
covariance: array of shape (n_features, n_features, n_samples), :
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Returns: | sqd: array of shape (n_samples,) :
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Return the z-score corresponding to a given p-value.