BiSpectrum_Distance¶

class turbustat.statistics.BiSpectrum_Distance(data1, data2, nsamples=100, fiducial_model=None)[source] [edit on github]¶

Bases: object

Calculate the distance between two images based on their bicoherence. The distance is the L2 norm between the bicoherence surfaces.

Parameters:

data1 : numpy.ndarray or astropy.io.fits.PrimaryHDU or spectral_cube.LowerDimensionalObject Contains the data and header of the image. data2 : numpy.ndarray or astropy.io.fits.PrimaryHDU or spectral_cube.LowerDimensionalObject Contains the data and header of the image. nsamples : int, optional Sets the number of samples to take at each vector magnitude. fiducial_model : Bispectrum Computed Bispectrum object. use to avoid recomputing.

Methods Summary

distance_metric([metric, verbose, label1, ...])

verbose : bool, optional

Methods Documentation

distance_metric(metric='average', verbose=False, label1=None, label2=None, save_name=None)[source] [edit on github]¶

verbose : bool, optional

Enable plotting.

label1 : str, optional

Object or region name for data1

label2 : str, optional

Object or region name for data2

save_name : str,optional

Save the figure when a file name is given.