5.2.10.3. eqcorrscan.utils.plotting.detection_multiplot¶
- eqcorrscan.utils.plotting.detection_multiplot(stream, template, times, streamcolour='k', templatecolour='r', **kwargs)[source]¶
Plot a stream of data with a template on top of it at detection times.
- Parameters:
stream (obspy.core.stream.Stream) – Stream of data to be plotted as the background.
template (obspy.core.stream.Stream) – Template to be plotted on top of the base stream.
times (list) – list of detection times, one for each event
streamcolour (str) – String of matplotlib colour types for the stream
templatecolour (str) – Colour to plot the template in.
title (str) – Title of figure
show (bool) – Whether to show the figure or not (defaults to True)
save (bool) – Whether to save the figure or not (defaults to False)
savefile (str) – Filename to save figure to, if save==True (defaults to “EQcorrscan_figure.png”)
return_figure (bool) – Whether to return the figure or not (defaults to True), if False then the figure will be cleared and closed.
size (tuple of float) – Figure size as (width, height) in inches. Defaults to (10.5, 7.5)
- Returns:
Example
>>> from obspy import read, read_events >>> import os >>> from eqcorrscan.core import template_gen >>> from eqcorrscan.utils.plotting import detection_multiplot >>> # Get the path to the test data >>> import eqcorrscan >>> import os >>> TEST_PATH = os.path.dirname(eqcorrscan.__file__) + '/tests/test_data' >>> >>> test_file = os.path.join(TEST_PATH, 'REA', ... 'TEST_', '01-0411-15L.S201309') >>> test_wavefile = os.path.join( ... TEST_PATH, 'WAV', 'TEST_', '2013-09-01-0410-35.DFDPC_024_00') >>> event = read_events(test_file)[0] >>> st = read(test_wavefile) >>> st = st.filter('bandpass', freqmin=2.0, freqmax=15.0) >>> for tr in st: ... tr = tr.trim(tr.stats.starttime + 30, tr.stats.endtime - 30) ... # Hack around seisan 2-letter channel naming ... tr.stats.channel = tr.stats.channel[0] + tr.stats.channel[-1] >>> template = template_gen._template_gen(event.picks, st, 2) >>> times = [min([pk.time -0.05 for pk in event.picks])] >>> detection_multiplot(stream=st, template=template, ... times=times)