DeltaVariance_Distance¶

class turbustat.statistics.DeltaVariance_Distance(dataset1, dataset2, weights1=None, weights2=None, diam_ratio=1.5, lags=None, fiducial_model=None, xlow=None, xhigh=None, boundary='wrap')[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 : numpy.ndarray or astropy.io.fits.PrimaryHDU or spectral_cube.LowerDimensionalObject Contains the data and header for one dataset. dataset2 : numpy.ndarray or astropy.io.fits.PrimaryHDU or spectral_cube.LowerDimensionalObject See above. weights1 : numpy.ndarray or astropy.io.fits.PrimaryHDU or spectral_cube.LowerDimensionalObject Weights for dataset1. weights2 : numpy.ndarray or astropy.io.fits.PrimaryHDU or spectral_cube.LowerDimensionalObject 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. ang_units : bool, optional Convert frequencies to angular units using the given header. xlow : float or np.ndarray, optional The lower lag fitting limit. An array with 2 elements can be passed to give separate lower limits for the datasets. xhigh : float or np.ndarray, optional The upper lag fitting limit. See xlow above. boundary : str, np.ndarray or list, optional Set how boundaries should be handled. If a string is not passed, a two element list/array with separate boundary conditions is expected.

Methods Summary

distance_metric([verbose, label1, label2, ...])

Applies the Euclidean distance to the delta-variance curves.

Methods Documentation

distance_metric(verbose=False, label1=None, label2=None, ang_units=False, unit=Unit("deg"), save_name=None)[source] [edit on github]¶

Applies the Euclidean distance to the delta-variance curves.

Parameters:

verbose : bool, optional Enables plotting. label1 : str, optional Object or region name for dataset1 label2 : str, optional Object or region name for dataset2 ang_units : bool, optional Convert frequencies to angular units using the given header. unit : u.Unit, optional Choose the angular unit to convert to when ang_units is enabled. save_name : str,optional Save the figure when a file name is given.