tmin = str_to_time('2013-01-01 00:00:00')
tmax = str_to_time('2014-01-01 00:00:00')
print 'download event data....'
all_events = map(lambda x: x.get_events((tmin, tmax)), catalogs)
print 'done'
# unravel lists and filter lists with more than two entries:
# TODO: die Fehlerbalken muessen unterschieden werden, um keine Wertigkeit in
# Abhaengigkeit von der Anzahl der Verfuegbaren Kataloge zu haben.
all_events = [item for sublist in all_events for item in sublist]
all_events_shallow = filter(lambda x: x.depth<33000, all_events)
magmin = 0
magmax = 6.
grouped_events = Event.grouped(all_events)
grouped_events = filter(lambda x: len(x)>=2, grouped_events)
grouped_events = filter_by_attribute(grouped_events, attr='magnitude',
maxlim=magmax, minlim=magmin)
remove_duplicates(grouped_events)
grouped_events_shallow = Event.grouped(all_events_shallow)
grouped_events_shallow = filter(lambda x: len(x)>=2, grouped_events_shallow)
grouped_events_shallow = filter_by_attribute(grouped_events_shallow,
attr='magnitude', maxlim=8., minlim=0.)
remove_duplicates(grouped_events_shallow)
grp_mean = group_mean(grouped_events_shallow)
fig = plt.figure(figsize=(4,3), dpi=160)
