4.6.2.1.1. eqcorrscan.core.lag_calc.lag_calc

eqcorrscan.core.lag_calc.lag_calc(detections, detect_data, template_names, templates, shift_len=0.2, min_cc=0.4, horizontal_chans=['E', 'N', '1', '2'], vertical_chans=['Z'], cores=1, interpolate=False, plot=False, parallel=True, debug=0)[source]

Main lag-calculation function for detections of specific events.

Overseer function to take a list of detection objects, cut the data for them to lengths of the same length of the template + shift_len on either side. This will output a obspy.core.event.Catalog of picked events. Pick times are based on the lag-times found at the maximum correlation, providing that correlation is above the min_cc.

Parameters:
  • detections (list) List of eqcorrscan.core.match_filter.Detection objects.
  • detect_data (obspy.core.stream.Stream) All the data needed to cut from - can be a gappy Stream.
  • template_names (list) List of the template names, used to help identify families of events. Must be in the same order as templates.
  • templates (list)
    List of the templates, templates must be a list of
    obspy.core.stream.Stream objects.
  • shift_len (float) Shift length allowed for the pick in seconds, will be plus/minus this amount - default=0.2
  • min_cc (float) Minimum cross-correlation value to be considered a pick, default=0.4.
  • horizontal_chans (list) List of channel endings for horizontal-channels, on which S-picks will be made.
  • vertical_chans (list) List of channel endings for vertical-channels, on which P-picks will be made.
  • cores (int) Number of cores to use in parallel processing, defaults to one.
  • interpolate (bool) Interpolate the correlation function to achieve sub-sample precision.
  • plot (bool) To generate a plot for every detection or not, defaults to False
  • parallel (bool) Turn parallel processing on or off.
  • debug (int) Debug output level, 0-5 with 5 being the most output.
Returns:

Catalog of events with picks. No origin information is included. These events can then be written out via obspy.core.event.Catalog.write(), or to Nordic Sfiles using eqcorrscan.utils.sfile_util.eventtosfile() and located externally.

Return type:

obspy.core.event.Catalog

Note

Picks output in catalog are generated relative to the template start-time. For example, if you generated your template with a pre_pick time of 0.2 seconds, you should expect picks generated by lag_calc to occur 0.2 seconds before the true phase-pick. This is because we do not currently store template meta-data alongside the templates.

Warning

Because of the above note, origin times will be consistently shifted by the static pre_pick applied to the templates.

Warning

This routine requires only one template per channel (e.g. you should not use templates with a P and S template on a single channel). If this does occur an error will be raised.

Note

S-picks will be made on horizontal channels, and P picks made on vertical channels - the default is that horizontal channels end in one of: ‘E’, ‘N’, ‘1’ or ‘2’, and that vertical channels end in ‘Z’. The options vertical_chans and horizontal_chans can be changed to suit your dataset.

Note

Individual channel cross-correlations are stored as a obspy.core.event.Comment for each pick, and the summed cross-correlation value resulting from these is stored as a obspy.core.event.Comment in the main obspy.core.event.Event object.

Note

The order of events is preserved (e.g. detections[n] == output[n]), providing picks have been made for that event. If no picks have been made for an event, it will not be included in the output. However, as each detection has an ID associated with it, these can be mapped to the output resource_id for each Event in the output Catalog. e.g.

detections[n].id == output[m].resource_id

if the output[m] is for the same event as detections[n].