dug_seis.event_processing.picking.picker_virginie module#
- dug_seis.event_processing.picking.picker_virginie.KurtoF(data, window_sample, n_bands)#
- dug_seis.event_processing.picking.picker_virginie.KurtoFreq(tr, freqmin, t_long, cnr, perc_taper)#
Calculate statistics for each band.
- dug_seis.event_processing.picking.picker_virginie.N_bands(tr, freqmin)#
Determine number of band n_bands in term of sampling rate. :param freqmin: The center frequency of first octave filtering band.
- dug_seis.event_processing.picking.picker_virginie.filter(tr, freqmin, cnr, perc_taper)#
Filter data for each band.
- dug_seis.event_processing.picking.picker_virginie.inc_zeros(small_v, n, i)#
- dug_seis.event_processing.picking.picker_virginie.rolling_window(a, window)#
Efficient rolling statistics with NumPy: This is applied to Picker._statistics() to calculate statistics and Summary.threshold() to calcuate threshold to trigger event Reference from: http://www.rigtorp.se/2011/01/01/rolling-statistics-numpy.html
- dug_seis.event_processing.picking.picker_virginie.threshold(tr, HOS, t_ma, nsigma)#
Control the threshold level with nsigma.
- dug_seis.event_processing.picking.picker_virginie.virginie_picker(st: Stream, number_of_parallel_jobs: int, t_win: float, freqmin: float, cnr: float, perc_taper: float, nsigma: float, t_ma: float, t_Tr: float, ncum0: float, ncum1: float)#
Main entry point for the picker. Should likely be renamed. Will run in parallel using joblib. :param st: The waveforms to pick on. :param number_of_parallel_jobs: Parallelize the picker. :param t_win: … :param freqmin: … :param cnr: … :param perc_taper: … :param nsigma: … :param t_ma: … :param t_Tr: … :param ncum0: … :param ncum1: …