Bispectrum_Distance

class turbustat.statistics.Bispectrum_Distance(data1, data2, stat_kwargs={})

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 astropy.io.fits.ImageHDU or spectral_cube.Projection or spectral_cube.Slice or Bispectrum

Contains the data and header of the image. Or a Bispectrum class may be given which can be pre-computed.

data2 : numpy.ndarray or astropy.io.fits.PrimaryHDU or astropy.io.fits.ImageHDU or spectral_cube.Projection or spectral_cube.Slice or Bispectrum

Contains the data and header of the second image. Or a Bispectrum class may be given which can be pre-computed.

stat_kwargs : dict, optional

Passed to run.

Attributes Summary

mean_distance	Absolute difference between the mean bicoherence.
surface_distance	L2 distance between the bicoherence surfaces.

Methods Summary

distance_metric(self[, verbose, label1, …])

verbose : bool, optional

Attributes Documentation

mean_distance

Absolute difference between the mean bicoherence.

surface_distance

L2 distance between the bicoherence surfaces.

Methods Documentation

distance_metric(self, verbose=False, label1=None, label2=None, save_name=None, cmap='viridis')

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.

cmap : str, optional

Colormap to show the bicoherence surfaces.