AutoQuakePycker package¶

Submodules¶

AutoQuakePycker.nlloc_wrapping module¶

Various wrapping functions for integrating AutoQuakePycker with NonLinLoc

AutoQuakePycker.nlloc_wrapping.get_theoretical_tt(event)¶

Find theoretical arrival times from NLLoc Time2EQ (containing 1 event).

Parameters:	event (ObsPy event object) –
Returns:	e
Return type:	ObsPy event object containing theoretical arrival times

AutoQuakePycker.nlloc_wrapping.relocate(evt_refined)¶

Carry out relocation using newly picked events in NonLinLoc

Parameters:	evt_refined (ObsPy event object) – tr (ObsPy trace object) –
Returns:	ev_new
Return type:	ObsPy event object containing relocated event

AutoQuakePycker.pickerfuncs module¶

Various functions for the Kurtosis picker of AutoQuakePycker

AutoQuakePycker.pickerfuncs.CF_kurtosis(kurt_win_size, tr)¶

This is the Kurtosis function of Baillard et al. (2014, SRL) (Eq. 10). Sets values outside of window to NaN.

Parameters:	kurt_win_size (kurtosis window length in seconds) – tr (ObsPy trace object) –
Returns:	cf
Return type:	kurtosis characteristic function time series

AutoQuakePycker.pickerfuncs.get_best_picks(sta, max_wind, orig_time, comps, sptype, cfg)¶

Define best Picks Choose whether to use fixed min S-P time or variable S-P time depending on P-arrival time and Vp/Vs ratio (Wadati method) This is quite messy. Could benefit from some improvements.

Parameters:	sta (Station dictionary containing picking results) – max_wind (Window length around theoretical arrival time to select pick in) – orig_time (UTCDateTime) –
Returns:	f4
Return type:	f4 kurtosis transform time series

AutoQuakePycker.pickerfuncs.kurt_transform_f2(f1, kurt_win_size, tr)¶

Apply transformations as per Baillard (BSSA). Remove neg slope of the CF from the sliding kurtosis fonction.

Parameters:	f1 (f1 transform time series) – kurt_win_size (kurtosis window length in seconds) – tr (ObsPy trace object) –
Returns:	f2
Return type:	f2 kurtosis transform time series

AutoQuakePycker.pickerfuncs.kurt_transform_f3(f2, kurt_win_size, tr)¶

Remove the linear trend of F2. Eq. 12

Parameters:	f2 (f2 transform time series) – kurt_win_size (kurtosis window length in seconds) – tr (ObsPy trace object) –
Returns:	f3
Return type:	f3 kurtosis transform time series

AutoQuakePycker.pickerfuncs.kurt_transform_f4(f3, kurt_win_size, tr)¶

Find greatest minima correspond to the greatest onset strengths.

Parameters:	f3 (f3 transform time series) – kurt_win_size (kurtosis window length in seconds) – tr (ObsPy trace object) –
Returns:	f4
Return type:	f4 kurtosis transform time series

AutoQuakePycker.plotting module¶

Routines for plotting the results of AutoQuakePycker

AutoQuakePycker.plotting.plot_record_section(st_sta)¶: TODO

AutoQuakePycker.plotting.plot_sta_results(sta, st_sta, runtype, orig_time, pdf, fig, cmps, cfg)¶

Plot picking results for each station

Parameters:	sta (Dictionary of station pick results) – st_sta (ObsPy stream containing waveform data for station) – runtype – tr (ObsPy trace object) –
Returns:	ev_new
Return type:	ObsPy event object containing relocated event

AutoQuakePycker.running_funcs module¶

Main functions for processing events on different processors

AutoQuakePycker.running_funcs.AutoQuakePycker_run()¶: Starts up AutoQuakePycker and sets-up processes

AutoQuakePycker.running_funcs.process_events(cat_data, n_run, cfg, sta_locs)¶: This is the main function that runs a given set of events and does the multi-stage refinement.

AutoQuakePycker.running_funcs.process_station(sta, st_sta, dist, ev_dict, evt, orig_time, phase, cmps, cfg)¶: Get ready to process data. Sets up emtpy arrays. Checks noise level of data.

AutoQuakePycker.running_funcs.process_trace(n_tr, tr, sta, orig_time, cmps, cfg)¶: Process picking on each trace parsed by process_station.

AutoQuakePycker.running_funcs.refine_events(st, stations_dist, cmps, max_pick_diff, evt, do_plot, n_refine, fig, sptype, path_to_figs, ev_dict, ev_id, cfg, rot=False)¶: This is one of the main functions of this code. It processes a refinement attempt for each event.

AutoQuakePycker.utils module¶

Routines for plotting the results of AutoQuakePycker

AutoQuakePycker.utils.add_picks(sta, e, orig_time, st, cfg)¶

Add picks made to ObsPy event structure.

Parameters:	sta (variable station & picking data (dict)) – e (event (ObsPy event object)) – orig_time (event origin time (ObsPy UTCDateTime object)) – st (stream of ObsPy traces containing data (Obspy stream object)) –
Returns:	e
Return type:	event containg added picks (ObsPy event object)

AutoQuakePycker.utils.compute_magnitude(evt, st, cfg)¶

Compute local magnitude for event. Uses the same approach as Bie et al. (2019, SRL), although we don’t bother with checking signal-to-noise ratio this time.

Parameters:	evt (ObsPy event object) – st (Obspy event stream containing waveform data) – cfg (Attribute-style dictionary containing picker configuration) –
Returns:	evt
Return type:	ObsPy event object containing computed magnitude

AutoQuakePycker.utils.compute_noise_levels(tr, cfg)¶: Get simple estimate of trace noise level using STA/LTA function - similar to thhat described by Baillard et al. (2014, BSSA).

AutoQuakePycker.utils.copytree(src, dst, symlinks=False, ignore=None)¶

Make NLLOC run directory for each process

Parameters:	src (Copy source location (str)) – dst (Copy desination location (dst)) –

AutoQuakePycker.utils.do_smooth(d, WT, sample_rate)¶

Simple windowing smoothing function. (takes data to right of smoothing point).

Parameters:	d (Time series to smooth (NumPy array)) – WT (Smoothing window length in seconds (float)) – sample_rate (sampling rate of time series (float)) –
Returns:	d_smooth
Return type:	smoothed time series (NumPy array)

AutoQuakePycker.utils.rotate(st, evt)¶

Rotate raw 3-component data to ZRT coordinate system. Throws up flag if rotation cannot be done (e.g. due to not all components spanning the same time)

Parameters:

st (ObsPy stream containing waveform data) –
evt (ObsPy event object containing epicentre information for rotation) –

Returns:

st_sta_rot (ObsPy event object containing rotated traces)
done (Boolean flag stating whether rotation was succesful or not)

AutoQuakePycker.utils.write_evt(evt, ev_id)¶

Write refined event with new picks to stationxml file

Parameters:	evt (Obspy event object) – ev_id (Event ID (str)) –