PSpec_Distance¶
-
class
turbustat.statistics.
PSpec_Distance
(data1, data2, weights1=None, weights2=None, breaks=None, low_cut=None, high_cut=<Quantity 0.5 1 / pix>, pspec_kwargs={}, pspec2_kwargs=None)[source] [edit on github]¶ Bases:
object
Distance metric for the spatial power spectrum. A linear model with an interaction term is fit to the powerlaws. The distance is the t-statistic of the interaction term.
Parameters: - data1 : numpy.ndarray or astropy.io.fits.PrimaryHDU or astropy.io.fits.ImageHDU or spectral_cube.Projection or spectral_cube.Slice or
PowerSpectrum
Data with an associated header. Or a
PowerSpectrum
class which may 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
PowerSpectrum
See
data1
.- weights1 : numpy.ndarray or astropy.io.fits.PrimaryHDU or astropy.io.fits.ImageHDU or spectral_cube.Projection or spectral_cube.Slice, optional
Weights to apply to data1
- weights2 : numpy.ndarray or astropy.io.fits.PrimaryHDU or astropy.io.fits.ImageHDU or spectral_cube.Projection or spectral_cube.Slice, optional
Weights to apply to data2
- breaks :
Quantity
, list or array, optional Specify where the break point is with appropriate units. If none is given, no break point will be used in the fit.
- low_cut :
Quantity
or np.ndarray, optional The lower frequency fitting limit. An array with 2 elements can be passed to give separate lower limits for the datasets.
- high_cut :
Quantity
or np.ndarray, optional The upper frequency fitting limit. See
low_cut
above. Defaults to 0.5.- pspec_kwargs : dict, optional
Passed to
radial_pspec_kwargs
inrun
.- pspec2_kwargs : dict or None, optional
Passed to
radial_pspec_kwargs
inrun
fordata2
. WhenNone
is given, setting frompspec_kwargs
are used fordata2
.
Methods Summary
distance_metric
([verbose, xunit, save_name, …])Implements the distance metric for 2 Power Spectrum transforms. Methods Documentation
-
distance_metric
(verbose=False, xunit=Unit("1 / pix"), save_name=None, plot_kwargs1={}, plot_kwargs2={}, use_wavenumber=False)[source] [edit on github]¶ Implements the distance metric for 2 Power Spectrum transforms. We fit the linear portion of the transform to represent the powerlaw A linear model with an interaction term is fit to the two powerlaws. The distance is the t-statistic of the interaction.
Parameters: - verbose : bool, optional
Enables plotting.
- xunit :
Unit
, optional Unit of the x-axis in the plot in pixel, angular, or physical units.
- save_name : str, optional
Name of the save file. Enables saving the figure.
- plot_kwargs1 : dict, optional
Pass kwargs to
plot_fit
fordata1
.- plot_kwargs2 : dict, optional
Pass kwargs to
plot_fit
fordata2
.- use_wavenumber : bool, optional
Plot the x-axis as the wavenumber rather than spatial frequency.
- data1 : numpy.ndarray or astropy.io.fits.PrimaryHDU or astropy.io.fits.ImageHDU or spectral_cube.Projection or spectral_cube.Slice or