# stream.detrend('demean')
# stream.resample(samp_rate)
# stream.write('scripts/brightness_test_daylong.ms',format='MSEED')
stream=obsread('scripts/brightness_test_daylong.ms')
stream.trim(starttime=UTCDateTime('2011-09-04 17:05:00'),\
endtime=UTCDateTime('2011-09-04 17:15:00'))#, pad=True,\
# fill_value=0)
# for tr in stream:
# if tr.stats.station=='WVZ':
# stream.remove(tr)
stream.filter('bandpass',freqmin=4.0, freqmax=8.0)
# stream.trim(stream[0].stats.starttime+90, stream[0].stats.endtime)
stream.trim(stream[0].stats.starttime, stream[0].stats.endtime, pad=True, fill_value=0)
stream.plot(size=(800,600),equal_scale=False)
instance=0
# Cut the nodes...
cutnodes=[nodes[0]]+[nodes[116]]
cutlags=np.array([lags[:,0]]+[lags[:,116]]).T
detect_templates, detect_nodes=bright_lights.brightness(stations, \
nodes, lags, stream,
brightdef.threshold, brightdef.thresh_type,\
brightdef.coherance, instance, matchdef, templatedef,\
brightdef)
plotting.threeD_gridplot(detect_nodes)
# detect_templates, detect_nodes=bright_lights.brightness(stations, \
# cutnodes, cutlags, stream,
# brightdef.threshold, brightdef.thresh_type,\
# brightdef.coherance, instance, matchdef, templatedef)
stream=Stream(stream)
print stream
if not Prep:
#stream_copy=stream.copy() # Keep the stream safe
print "Running the detection routine"
# Check that the data are okay
detect_templates, detect_nodes=bright_lights.brightness(stations, \
nodes, lags, stream,
brightdef.threshold, brightdef.thresh_type,\
brightdef.coherance, instance, matchdef, templatedef,\
brightdef)
del detect_templates#, stream # Delete templates from memory to conserve RAM!
#stream=stream_copy
nodesout+=detect_nodes
if Split:
plotting.threeD_gridplot(nodesout, save=brightdef.plotsave,\
savefile='Detected_nodes_'+str(instance)+'.png')
else:
plotting.threeD_gridplot(nodesout, save=brightdef.plotsave,\
savefile='Detected_nodes.png')
else:
for tr in stream:
print "Writing data as: test_data/"+tr.stats.station+'-'+tr.stats.channel+\
'-'+str(tr.stats.starttime.year)+\
'-'+str(tr.stats.starttime.month).zfill(2)+\
'-'+str(tr.stats.starttime.day).zfill(2)+\
'-processed.ms'
tr.write('test_data/'+tr.stats.station+'-'+tr.stats.channel+\
'-'+str(tr.stats.starttime.year)+\
'-'+str(tr.stats.starttime.month).zfill(2)+\
'-'+str(tr.stats.starttime.day).zfill(2)+\
stream = obsread('scripts/brightness_test_daylong.ms')
stream.trim(starttime=UTCDateTime('2011-09-04 17:05:00'),\
endtime=UTCDateTime('2011-09-04 17:15:00'))#, pad=True,\
# fill_value=0)
# for tr in stream:
# if tr.stats.station=='WVZ':
# stream.remove(tr)
stream.filter('bandpass', freqmin=4.0, freqmax=8.0)
# stream.trim(stream[0].stats.starttime+90, stream[0].stats.endtime)
stream.trim(stream[0].stats.starttime,
stream[0].stats.endtime,
pad=True,
fill_value=0)
stream.plot(size=(800, 600), equal_scale=False)
instance = 0
# Cut the nodes...
cutnodes = [nodes[0]] + [nodes[116]]
cutlags = np.array([lags[:, 0]] + [lags[:, 116]]).T
detect_templates, detect_nodes=bright_lights.brightness(stations, \
nodes, lags, stream,
brightdef.threshold, brightdef.thresh_type,\
brightdef.coherance, instance, matchdef, templatedef,\
brightdef)
plotting.threeD_gridplot(detect_nodes)
# detect_templates, detect_nodes=bright_lights.brightness(stations, \
# cutnodes, cutlags, stream,
# brightdef.threshold, brightdef.thresh_type,\
# brightdef.coherance, instance, matchdef, templatedef)
