array_processing(stream, win_len, win_frac, sll_x, slm_x, sll_y, slm_y, sl_s, semb_thres, vel_thres, frqlow, frqhigh, stime, etime, prewhiten, verbose=False, coordsys='lonlat', timestamp='mlabday', method=0, store=None)[source]

Method for Seismic-Array-Beamforming/FK-Analysis/Capon

  • stream Stream object, the trace.stats dict like class must contain an AttribDict with ‘latitude’, ‘longitude’ (in degrees) and ‘elevation’ (in km), or ‘x’, ‘y’, ‘elevation’ (in km) items/attributes. See param coordsys.
  • win_len (float) Sliding window length in seconds
  • win_frac (float) Fraction of sliding window to use for step
  • sll_x (float) slowness x min (lower)
  • slm_x (float) slowness x max
  • sll_y (float) slowness y min (lower)
  • slm_y (float) slowness y max
  • sl_s (float) slowness step
  • semb_thres (float) Threshold for semblance
  • vel_thres (float) Threshold for velocity
  • frqlow (float) lower frequency for fk/capon
  • frqhigh (float) higher frequency for fk/capon
  • stime (UTCDateTime) Start time of interest
  • etime (UTCDateTime) End time of interest
  • prewhiten (int) Do prewhitening, values: 1 or 0
  • coordsys valid values: ‘lonlat’ and ‘xy’, choose which stream attributes to use for coordinates
  • timestamp (str) valid values: ‘julsec’ and ‘mlabday’; ‘julsec’ returns the timestamp in seconds since 1970-01-01T00:00:00, ‘mlabday’ returns the timestamp in days (decimals represent hours, minutes and seconds) since ‘0001-01-01T00:00:00’ as needed for matplotlib date plotting (see e.g. matplotlib’s num2date)
  • method (int) the method to use 0 == bf, 1 == capon
  • store (function) A custom function which gets called on each iteration. It is called with the relative power map and the time offset as first and second arguments and the iteration number as third argument. Useful for storing or plotting the map for each iteration. For this purpose the dump function of this module can be used.

numpy.ndarray of timestamp, relative relpow, absolute relpow, backazimuth, slowness