Tsallis¶

class turbustat.statistics.Tsallis(img, lags=None, num_bins=500, periodic=False)[source] [edit on github]¶

Bases: turbustat.statistics.base_statistic.BaseStatisticMixIn

The Tsallis Distribution (see Tofflemire et al., 2011)

Parameters:	img : numpy.ndarray or astropy.io.fits.PrimaryHDU or spectral_cube.LowerDimensionalObject 2D image. lags : numpy.ndarray or list Lags to calculate at. num_bins : int, optional Number of bins to use in the histograms. periodic : bool, optional Sets whether the boundaries are periodic.
Parameters:	periodic : bool, optional Use for simulations with periodic boundaries.

Methods Summary

fit_tsallis([sigma_clip])	Fit the Tsallis distributions.
make_tsallis()	Calculate the Tsallis distribution at each lag.
run([verbose, sigma_clip, save_name])	Run all steps.

Methods Documentation

fit_tsallis(sigma_clip=2)[source] [edit on github]¶

Fit the Tsallis distributions.

Parameters:	sigma_clip : float Sets the sigma value to clip data at.

make_tsallis()[source] [edit on github]¶

Calculate the Tsallis distribution at each lag. We standardize each distribution such that it has a mean of zero and variance of one.

run(verbose=False, sigma_clip=2, save_name=None)[source] [edit on github]¶

Run all steps.

Parameters:	verbose : bool, optional Enables plotting. sigma_clip : float Sets the sigma value to clip data at. Passed to fit_tsallis(). save_name : str,optional Save the figure when a file name is given.