Wavelet¶

class turbustat.statistics.Wavelet(data, header=None, scales=None, num=50, scale_normalization=True)[source] [edit on github]¶

Bases: turbustat.statistics.base_statistic.BaseStatisticMixIn

Compute the wavelet transform of a 2D array.

Parameters:

array : numpy.ndarray or astropy.io.fits.PrimaryHDU or spectral_cube.LowerDimensionalObject 2D data. header : FITS header, optional Header for the array. scales : numpy.ndarray or list The scales where the transform is calculated. num : int, optional Number of scales to compute the transform at. scale_normalization: bool, optional Compute the transform with the correct scale-invariant normalization.

Attributes Summary

slope
slope_err

Methods Summary

compute_transform()	Compute the wavelet transform at each scale.
fit_transform([xlow, xhigh])	Perform a fit to the transform in log-log space.
make_1D_transform()	Create the 1D transform.
plot_transform([ang_units, unit, show, ...])	Plot the transform and the fit.
run([verbose, ang_units, unit, xlow, xhigh])	Compute the Wavelet transform.

Attributes Documentation

slope¶

slope_err¶

Methods Documentation

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

Compute the wavelet transform at each scale.

fit_transform(xlow=None, xhigh=None)[source] [edit on github]¶

Perform a fit to the transform in log-log space.

make_1D_transform()[source] [edit on github]¶

Create the 1D transform.

plot_transform(ang_units=False, unit=Unit("deg"), show=True, color='b', symbol='D', label=None)[source] [edit on github]¶

Plot the transform and the fit.

run(verbose=False, ang_units=False, unit=Unit("deg"), xlow=None, xhigh=None)[source] [edit on github]¶

Compute the Wavelet transform.

Parameters:	verbose : bool, optional Plot wavelet transform. 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.