DeltaVariance_Distance¶

class turbustat.statistics.DeltaVariance_Distance(dataset1, dataset2, weights1=None, weights2=None, diam_ratio=1.5, lags=None, fiducial_model=None)[source] [edit on github]¶

Bases: object

Compares 2 datasets using delta-variance. The distance between them is given by the Euclidean distance between the curves weighted by the bootstrapped errors.

Parameters:

dataset1 : FITS hdu Contains the data and header for one dataset. dataset2 : FITS hdu See above. weights1 : numpy.ndarray Weights for dataset1. weights2 : numpy.ndarray See above. diam_ratio : float, optional The ratio between the kernel sizes. lags : numpy.ndarray or list, optional The pixel scales to compute the delta-variance at. fiducial_model : DeltaVariance A computed DeltaVariance model. Used to avoid recomputing.

Methods Summary

Methods Documentation

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

Applies the Euclidean distance to the delta-variance curves.

Parameters:	verbose : bool, optional Enables plotting.