mvpa2.datasets.sources.skl_data.skl_checkerboard

mvpa2.datasets.sources.skl_data.skl_checkerboard(shape, n_clusters, noise=0.0, minval=10, maxval=100, shuffle=True, random_state=None)

Generate an array with block checkerboard structure for biclustering.

Parameters:

shape : iterable (n_rows, n_cols)

The shape of the result.

n_clusters : integer or iterable (n_row_clusters, n_column_clusters)

The number of row and column clusters.

noise : float, optional (default=0.0)

The standard deviation of the gaussian noise.

minval : int, optional (default=10)

Minimum value of a bicluster.

maxval : int, optional (default=100)

Maximum value of a bicluster.

shuffle : boolean, optional (default=True)

Shuffle the samples.

random_state : int, RandomState instance or None, optional (default=None)

If int, random_state is the seed used by the random number generator; If RandomState instance, random_state is the random number generator; If None, the random number generator is the RandomState instance used by np.random.

Returns:

X : array of shape shape

The generated array.

rows : array of shape (n_clusters, X.shape[0],)

The indicators for cluster membership of each row.

cols : array of shape (n_clusters, X.shape[1],)

The indicators for cluster membership of each column.

See also

make_biclusters

Notes

This function has been auto-generated by wrapping make_checkerboard() 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.

References

[R23]

Kluger, Y., Basri, R., Chang, J. T., & Gerstein, M. (2003). Spectral biclustering of microarray data: coclustering genes and conditions. Genome research, 13(4), 703-716.