PCA_Distance¶

class turbustat.statistics.PCA_Distance(cube1, cube2, n_eigs=50, fiducial_model=None, normalize=True)[source] [edit on github]¶

Bases: object

Compare two data cubes based on the eigenvalues of the PCA decomposition. The distance is the Euclidean distance between the eigenvalues.

Parameters:	cube1 : numpy.ndarray Data cube. cube2 : numpy.ndarray Data cube. n_eigs : int Number of eigenvalues to compute. fiducial_model : PCA Computed PCA object. Use to avoid recomputing. normalize : bool, optional Sets whether to normalize the eigenvalues by the 0th eigenvalue.

Methods Summary

Methods Documentation

distance_metric(verbose=False)[source] [edit on github]¶

Computes the distance between the cubes.

Parameters:	verbose : bool, optional Enables plotting.