obspy.signal.array_analysis.array_processing¶

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

Parameters:

Parameters:	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.
Returns:	`numpy.ndarray` of timestamp, relative relpow, absolute relpow, backazimuth, slowness

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.

Returns:

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