#!/usr/bin/env python
# encoding: utf-8
from glob import glob
from plot_dsp import read_dsp, plot_all_map
print "Plotting coverage using all dsp files for all events"
periods = [20, 50, 100, 150]
# get all the filenames
dsp_files = glob('*/*.dsp')
# create a list for all the files
dsp_list = []
# loop over the files
for fname in dsp_files:
# read the dispersion
dsp, dsp_dict = read_dsp(fname)
# add the information to the list
dsp_list.append((dsp, dsp_dict))
# plot the coverage map
plot_all_map(dsp_list, coverage=True)
for per in periods:
print "Treating period %.1f" % per
plot_all_map(dsp_list, coverage=True, period=per)
for sta in stations:
events = event_array[station_array == sta, :]
dsp_shortlist = dsp_array[station_array == sta]
print sta, events.shape, dsp_shortlist.shape
# cluster on events so as to compare dispersion curves for nearby
# events
brc = Birch(branching_factor=50, n_clusters=None, threshold=dist, compute_labels=True)
brc.fit(events)
labels = brc.predict(events)
print np.max(labels)
for lab in np.unique(labels):
dsp_this_label_list = dsp_shortlist[labels == lab]
cluster_name = os.path.join(dirname, "cluster_%s_%03d" % (sta, lab))
plot_all_dsp(dsp_this_label_list, legend=False, fname="%s_gvel.png" % cluster_name)
plot_all_map(dsp_this_label_list, fname="%s_map.png" % cluster_name, legend=False)
f = open("%s_info.txt" % cluster_name, "w")
for (dsp, dsp_dict) in dsp_this_label_list:
f.write(
"%s %s %d %03d %02d %02d %.3f %.3f\n"
% (
dsp_dict["STA"],
dsp_dict["COMP"],
dsp_dict["YEAR"],
dsp_dict["JDAY"],
dsp_dict["HOUR"],
dsp_dict["MIN"],
dsp_dict["EVLA"],
dsp_dict["EVLO"],
)
)
for sta in stations:
events = event_array[station_array == sta, :]
dsp_shortlist = dsp_array[station_array == sta]
print sta, events.shape, dsp_shortlist.shape
# cluster on events so as to compare dispersion curves for nearby
# events
brc = Birch(branching_factor=50,
n_clusters=None,
threshold=dist,
compute_labels=True)
brc.fit(events)
labels = brc.predict(events)
print np.max(labels)
for lab in np.unique(labels):
dsp_this_label_list = dsp_shortlist[labels == lab]
cluster_name = os.path.join(dirname, 'cluster_%s_%03d' % (sta, lab))
plot_all_dsp(dsp_this_label_list,
legend=False,
fname='%s_gvel.png' % cluster_name)
plot_all_map(dsp_this_label_list,
fname='%s_map.png' % cluster_name,
legend=False)
f = open('%s_info.txt' % cluster_name, 'w')
for (dsp, dsp_dict) in dsp_this_label_list:
f.write('%s %s %d %03d %02d %02d %.3f %.3f\n' %
(dsp_dict["STA"], dsp_dict["COMP"], dsp_dict["YEAR"],
dsp_dict["JDAY"], dsp_dict["HOUR"], dsp_dict["MIN"],
dsp_dict["EVLA"], dsp_dict["EVLO"]))
f.close()
#!/usr/bin/env python
# encoding: utf-8
from glob import glob
from plot_dsp import read_dsp, plot_all_map
print "Plotting coverage using all dsp files for all events"
periods = [20, 50, 100, 150]
# get all the filenames
dsp_files = glob('*/*.dsp')
# create a list for all the files
dsp_list = []
# loop over the files
for fname in dsp_files:
# read the dispersion
dsp, dsp_dict = read_dsp(fname)
# add the information to the list
dsp_list.append((dsp, dsp_dict))
# plot the coverage map
plot_all_map(dsp_list, coverage=True)
for per in periods:
print "Treating period %.1f"%per
plot_all_map(dsp_list, coverage=True, period=per)