def coincidences_stations(station_numbers,
group_name='Specific stations',
date=None):
if date is None:
date = datetime.date(2016, 2, 1)
stations_with_data = []
cluster_groups = []
for station_id in station_numbers:
try:
info = Station(station_id)
except:
continue
if info.has_data(year=date.year, month=date.month, day=date.day):
cluster_groups.append(info.cluster().lower())
stations_with_data.append(station_id)
if len(stations_with_data) <= 1:
return
filepath = os.path.join(ESD_PATH, date.strftime('%Y/%-m/%Y_%-m_%-d.h5'))
with tables.open_file(filepath, 'r') as data:
coinc, event_tables = get_event_tables(data, cluster_groups,
stations_with_data)
windows, counts, n_events = find_n_coincidences(coinc, event_tables)
n_stations = len(stations_with_data)
plot_coinc_window(windows, counts, group_name, n_events, n_stations,
date)
return windows, counts
def main(station_number=501, date=datetime.date(2016, 2, 1)):
filepath = os.path.join(ESD_PATH, date.strftime('%Y/%-m/%Y_%-m_%-d.h5'))
with tables.open_file(filepath, 'r') as data:
station = Station(station_number)
events = data.get_node(
'/hisparc/cluster_%s/station_%d' %
(station.cluster().lower(), station_number), 'events')
ext_timestamps = events.col('ext_timestamp')
ext_timestamps.sort()
difs = ext_timestamps[1:] - ext_timestamps[:-1]
print('Minimum: %d. Maximum: %d. n(diff < 100 us): %d' %
(min(difs), max(difs), len(numpy.where(difs < 1e5)[0])))
bins = numpy.logspace(2, 11)
plot = Plot('semilogx')
plot.histogram(*numpy.histogram(difs, bins=bins))
plot.set_xlabel(r'Time between subsequent triggers [\si{\ns}]')
plot.set_ylabel('Occurance')
plot.set_ylimits(min=0)
plot.set_xlimits(min(bins), max(bins))
plot.save_as_pdf('time_between_triggers_%d' % station_number)