pygwb.postprocessing.calc_Y_sigma_from_Yf_sigmaf

pygwb.postprocessing.calc_Y_sigma_from_Yf_sigmaf(Y_f, sigma_f, frequency_mask=True, alpha=None, fref=None)[source]

Calculate the omega point estimate and sigma from their respective spectra, or spectrograms, taking into account the desired spectral weighting. To apply weighting, the frequency array associated to the spectra must be supplied.

If applied to a 1D array, you get single numbers out. If applied to a 2D array, it combines over the second dimension. That is, if dimension is Ntimes x Nfrequencies, then the resulting spectra are Ntimes long.

Parameters:

  • Y_f (pygwb.omega_spectrogram.OmegaSpectrogram) – Point estimate spectrum.

  • sigma_f (pygwb.omega_spectrogram.OmegaSpectrogram) – Sigma spectrum.

  • frequency_mask (array-like, optional) – Boolean mask to apply to frequencies for the calculation. Default set to True including all frequencies.

  • alpha (float, optional) – Spectral index to use in case re-weighting is requested. Default set to None.

  • fref (float, optional) – Reference frequency to use in case re-weighting is requested. Default set to None.

Returns:
Y: array-like or float

Point estimate or Point estimate spectrum.

sigma: array-like or float

Point estimate standard deviation (theoretical) or spectrum of point estimate standard deviations.

Notes

If passing in spectrograms, the point estimate and sigma will be calculated per spectrum, without any time-averaging applied. Y_f and sigma_f can also be gwpy.spectrogram.Spectrogram objects, or numpy arrays. In these cases however the reweight functionality is not supported.