obspy.signal.tf_misfit.fpg

fpg(st1, st2, dt=0.01, fmin=1.0, fmax=10.0, nf=100, w0=6, norm='global', st2_isref=True, a=10.0, k=1.0)[source]

Frequency-dependent Phase Goodness-of-Fit

See also

[Kristekova2009], Eq.(16)

Parameters:

  • st1 – signal 1 of two signals to compare, type numpy.ndarray with shape (number of components, number of time samples) or (number of timesamples, ) for single component data

  • st2 – signal 2 of two signals to compare, type and shape as st1

  • dt – time step between two samples in st1 and st2

  • fmin – minimal frequency to be analyzed

  • fmax – maximal frequency to be analyzed

  • nf – number of frequencies (will be chosen with logarithmic spacing)

  • w0 – parameter for the wavelet, tradeoff between time and frequency resolution

  • norm – ‘global’ or ‘local’ normalization of the misfit

  • st2_isref (bool) – True if st2 is a reference signal, False if none is a reference

  • a – Maximum value of Goodness-of-Fit for perfect agreement

  • k – sensitivity of Goodness-of-Fit to the misfit

Returns:

frequency dependent Phase Goodness-of-Fit, type numpy.ndarray with shape (nf,) for single component data and (number of components, nf) for multicomponent data