brainspace.null_models.moran.moran_randomization¶
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brainspace.null_models.moran.
moran_randomization
(x, mem, n_rep=100, procedure='singleton', joint=False, random_state=None)[source]¶ Generate random samples from x based on Moran spectral randomization.
Parameters: - x (1D or 2D ndarray, shape = (n_vertices,) or (n_vertices, n_feat)) – Array of variables arranged in columns, where n_feat is the number of variables.
- mem (2D ndarray, shape = (n_vertices, nv)) – Moran eigenvectors map, where nv is the number of eigenvectors arranged in columns.
- n_rep (int, optional) – Number of random samples. Default is 100.
- procedure ({'singleton, 'pair'}, optional) – Procedure to generate the random samples. Default is ‘singleton’.
- joint (boolean, optional) – If True variables are randomized jointly. Otherwise, each variable is randomized separately. Default is False.
- random_state (int or None, optional) – Random state. Default is None.
Returns: output (ndarray, shape = (n_rep, n_vertices, n_feat)) – Random samples. If
n_feat == 1
, shape = (n_rep, n_vertices).See also
References
- Wagner H.H. and Dray S. (2015). Generating spatially constrained null models for irregularly spaced data using Moran spectral randomization methods. Methods in Ecology and Evolution, 6(10):1169-78.