wt2D¶

class turbustat.statistics.wt2D(array, header, scales=None, dx=0.25, dy=0.25, wavelet=<turbustat.statistics.wavelets.wavelet_transform.Mexican_hat instance>, num=50, ang_units=True)[source] [edit on github]¶

Bases: object

Compute the wavelet transform of a 2D array.

Parameters:	array : numpy.ndarray 2D array. header : FITS header Header for the array. scales : numpy.ndarray or list The scales where the transform is calculated. dx : float, optional Spacing in the x-direction. dy : float, optional Spacing in the y-direction. wavelet : wavelet class The wavelet class to use.

Methods Summary

Methods Documentation

astropy_cwt2d(dx=None, dy=None)[source] [edit on github]¶

Same as cwt2D except it uses astropy.convolve_fft’s ability to interpolate over NaNs.

Parameters:	dx : float, optional Spacing in the x-direction. dy : float, optional Spacing in the y-direction.

cwt2d(dx=None, dy=None)[source] [edit on github]¶

Bi-dimensional continuous wavelet transform of the signal at specified scale a.

Parameters:	dx : float, optional Spacing in the x-direction. dy : float, optional Spacing in the y-direction.

icwt2d(da=0.25)[source] [edit on github]¶

Inverse bi-dimensional continuous wavelet transform as in Wang and Lu (2010), equation [5].

Parameters:	da : float, optional Spacing in the frequency axis.

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

run()[source] [edit on github]¶

Compute the Wavelet transform.