SCF_Distance¶

class turbustat.statistics.SCF_Distance(cube1, cube2, size=21, boundary='continuous', fiducial_model=None, weighted=True)[source] [edit on github]¶

Bases: object

Calculates the distance between two data cubes based on their SCF surfaces. The distance is the L2 norm between the surfaces. We weight the surface by 1/r^2 where r is the distance from the centre.

Parameters:

cube1 : numpy.ndarray or astropy.io.fits.PrimaryHDU or SpectralCube Data cube. cube2 : numpy.ndarray or astropy.io.fits.PrimaryHDU or SpectralCube Data cube. size : int, optional Maximum size roll over which SCF will be calculated. boundary : {“continuous”, “cut”} Treat the boundary as continuous (wrap-around) or cut values beyond the edge (i.e., for most observational data). A two element list can also be passed for treating the boundaries differently between the given cubes. fiducial_model : SCF Computed SCF object. Use to avoid recomputing. weighted : bool, optional Sets whether to apply the 1/r^2 weighting to the distance.

Methods Summary

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

Compute the distance between the surfaces.

Methods Documentation

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

Compute the distance between the surfaces.

Parameters:	verbose : bool, optional Enables plotting. label1 : str, optional Object or region name for cube1 label2 : str, optional Object or region name for cube2 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.