mvpa2.datasets.sources.skl_data.skl_moons(n_samples=100, shuffle=True, noise=None, random_state=None)

Make two interleaving half circles

A simple toy dataset to visualize clustering and classification algorithms.


n_samples : int, optional (default=100)

The total number of points generated.

shuffle : bool, optional (default=True)

Whether to shuffle the samples.

noise : double or None (default=None)

Standard deviation of Gaussian noise added to the data.


X : array of shape [n_samples, 2]

The generated samples.

y : array of shape [n_samples]

The integer labels (0 or 1) for class membership of each sample.


This function has been auto-generated by wrapping make_moons() from the sklearn package. The documentation of this function has been kept verbatim. Consequently, the actual return value is not as described in the documentation, but the data is returned as a PyMVPA dataset.