pyriemann.datasets.make_gaussian_blobs

pyriemann.datasets.make_gaussian_blobs(n_matrices=100, n_dim=2, class_sep=1.0, class_disp=1.0, return_centers=False, center_dataset=False, random_state=None, centers=None, *, n_jobs=1, sampling_method='auto')

Generate SPD dataset with two classes sampled from Riemannian Gaussian.

Generate a dataset with SPD matrices drawn from two Riemannian Gaussian distributions. The distributions have the same class dispersions and the distance between their centers of mass is an input parameter. Useful for testing classification or clustering methods.

Parameters:

n_matricesint, default=100

How many matrices to generate for each class.

n_dimint, default=2

Dimensionality of the SPD matrices generated by the distributions.

class_sepfloat, default=1.0

Parameter controlling the separability of the classes.

class_dispfloat, default=1.0

Intra dispersion of the points sampled from each class.

centersndarray, shape (2, n_dim, n_dim), default=None

List with the centers of mass for each class. If None, the centers are sampled randomly based on class_sep.

return_centersbool, default=False

If True, then return the centers of each cluster

center_datasetbool, default=False

If True, re-center the simulated dataset to the Identity. If False, the dataset is centered around a random SPD matrix.

random_stateint, RandomState instance or None, default=None

Pass an int for reproducible output across multiple function calls.

n_jobsint, default=1

The number of jobs to use for the computation. This works by computing each of the class centroid in parallel. If -1 all CPUs are used.

sampling_methodstr, default=’auto’

Name of the sampling method used to sample samples_r. It can be ‘auto’, ‘slice’ or ‘rejection’. If it is ‘auto’, the sampling_method will be equal to ‘slice’ for n_dim != 2 and equal to ‘rejection’ for n_dim = 2.

New in version 0.4.

Returns:

Xndarray, shape (2*n_matrices, n_dim, n_dim)

Set of SPD matrices.

yndarray, shape (2*n_matrices,)

Labels corresponding to each matrix.

centersndarray, shape (2, n_dim, n_dim)

The centers of each class. Only returned if return_centers=True.

Notes

New in version 0.3.