def test_station_arrival_time(self, mock_detector_ids,
mock_detector_arrival_times):
mock_detector_ids.return_value = range(4)
mock_detector_arrival_times.return_value = [7.5, 5., 2.5, 5.]
event_dict = {'t_trigger': 10, 'ext_timestamp': 1000}
event = MagicMock()
event.__getitem__.side_effect = lambda name: event_dict[name]
ref_ets = 500
rel_arrival_time = event_dict['ext_timestamp'] - ref_ets - event_dict[
't_trigger']
self.assertEqual(
event_utils.station_arrival_time(event, ref_ets, range(4),
sentinel.offsets,
sentinel.station),
rel_arrival_time + 2.5)
self.assertEqual(mock_detector_ids.call_count, 0)
self.assertEqual(
event_utils.station_arrival_time(event, ref_ets, None,
sentinel.offsets),
rel_arrival_time + 2.5)
mock_detector_ids.assert_called_once_with(None, event)
self.assertEqual(
event_utils.station_arrival_time(event, ref_ets, None,
sentinel.offsets,
sentinel.station),
rel_arrival_time + 2.5)
mock_detector_ids.assert_called_with(sentinel.station, event)
def determine_time_differences(coin_events, ref_station, station, ref_d_off,
d_off):
"""Determine the arrival time differences between two stations.
:param coin_events: coincidence events.
:param ref_station,station: station numbers.
:param ref_d_off,d_off: `detector_timing_offset` methods of Station objects
for the two stations, to retrieve applicable offsets.
:return: extended timestamp of the first event and time difference,
t - t_ref. Not corrected for altitude differences.
"""
dt = []
ets = []
for events in coin_events:
ref_ets = events[0][1]['ext_timestamp']
ref_ts = ref_ets / int(1e9)
# Filter for possibility of same station twice in coincidence
if len(events) is not 2:
continue
if events[0][0] == ref_station:
ref_id = 0
id = 1
else:
ref_id = 1
id = 0
ref_t = station_arrival_time(events[ref_id][1], ref_ets, [0, 1, 2, 3],
ref_d_off(ref_ts))
t = station_arrival_time(events[id][1], ref_ets, [0, 1, 2, 3],
d_off(ref_ts))
if isnan(t) or isnan(ref_t):
continue
dt.append(t - ref_t)
ets.append(ref_ets)
return ets, dt
def test_station_arrival_time(self, mock_detector_ids, mock_detector_arrival_times):
mock_detector_ids.return_value = range(4)
mock_detector_arrival_times.return_value = [7.5, 5., 2.5, 5.]
event_dict = {'t_trigger': 10, 'ext_timestamp': 1000}
event = MagicMock()
event.__getitem__.side_effect = lambda name: event_dict[name]
ref_ets = 500
rel_arrival_time = event_dict['ext_timestamp'] - ref_ets - event_dict['t_trigger']
self.assertEqual(event_utils.station_arrival_time(event, ref_ets, range(4), sentinel.offsets, sentinel.station),
rel_arrival_time + 2.5)
self.assertEqual(mock_detector_ids.call_count, 0)
self.assertEqual(event_utils.station_arrival_time(event, ref_ets, None, sentinel.offsets),
rel_arrival_time + 2.5)
mock_detector_ids.assert_called_once_with(None, event)
self.assertEqual(event_utils.station_arrival_time(event, ref_ets, None, sentinel.offsets, sentinel.station),
rel_arrival_time + 2.5)
mock_detector_ids.assert_called_with(sentinel.station, event)
def test_nan_station_arrival_time(self, mock_detector_ids, mock_detector_arrival_times):
mock_detector_ids.return_value = range(4)
mock_detector_arrival_times.return_value = [7.5, 5., nan, 5.]
event_dict = {'t_trigger': 10, 'ext_timestamp': 1000}
event = MagicMock()
event.__getitem__.side_effect = lambda name: event_dict[name]
ref_ets = 500
rel_arrival_time = event_dict['ext_timestamp'] - ref_ets - event_dict['t_trigger']
self.assertEqual(event_utils.station_arrival_time(event, ref_ets, None, sentinel.offsets, sentinel.station),
rel_arrival_time + 5)
event_dict['t_trigger'] = -999
self.assertTrue(isnan(event_utils.station_arrival_time(event, ref_ets, None, sentinel.offsets, sentinel.station)))
event_dict['t_trigger'] = nan
self.assertTrue(isnan(event_utils.station_arrival_time(event, ref_ets, None, sentinel.offsets, sentinel.station)))
event_dict['t_trigger'] = 10
mock_detector_arrival_times.return_value = [nan, nan, nan, nan]
with warnings.catch_warnings(record=True) as warned:
self.assertTrue(isnan(event_utils.station_arrival_time(event, ref_ets, None, sentinel.offsets, sentinel.station)))
self.assertEqual(len(warned), 1)
def test_nan_station_arrival_time(self, mock_detector_ids,
mock_detector_arrival_times):
mock_detector_ids.return_value = range(4)
mock_detector_arrival_times.return_value = [7.5, 5., nan, 5.]
event_dict = {'t_trigger': 10, 'ext_timestamp': 1000}
event = MagicMock()
event.__getitem__.side_effect = lambda name: event_dict[name]
ref_ets = 500
rel_arrival_time = event_dict['ext_timestamp'] - ref_ets - event_dict[
't_trigger']
self.assertEqual(
event_utils.station_arrival_time(event, ref_ets, None,
sentinel.offsets,
sentinel.station),
rel_arrival_time + 5)
event_dict['t_trigger'] = -999
self.assertTrue(
isnan(
event_utils.station_arrival_time(event, ref_ets, None,
sentinel.offsets,
sentinel.station)))
event_dict['t_trigger'] = nan
self.assertTrue(
isnan(
event_utils.station_arrival_time(event, ref_ets, None,
sentinel.offsets,
sentinel.station)))
event_dict['t_trigger'] = 10
mock_detector_arrival_times.return_value = [nan, nan, nan, nan]
with warnings.catch_warnings(record=True) as warned:
self.assertTrue(
isnan(
event_utils.station_arrival_time(event, ref_ets, None,
sentinel.offsets,
sentinel.station)))
self.assertEqual(len(warned), 1)
def plot_arrival_time_distribution_v_distance(data, seeds):
results = []
cor_t = None
for group in data.walk_groups('/'):
if (seeds not in group._v_pathname or group._v_name != 'coincidences'):
continue
coincidences = group.coincidences
events = data.get_node(group.s_index[0]).events
r = next(
int(y[1:]) for y in group._v_pathname.split('/')
if y.startswith('r'))
seeds = next(y[1:] for y in group._v_pathname.split('/')
if y.startswith('s'))
if cor_t is None:
with tables.open_file(CORSIKA_DATA % seeds) as data:
gp = data.root.groundparticles
query = '(x < 10) & (x > -10) & (r < 10)'
cor_t = gp.read_where(query, field='t').min()
# i = get_info(seeds)['first_interaction_altitude']
# cor_t = i / 0.299792458
# Round ts to seconds because it is the ts for first event, not the shower
t = [
station_arrival_time(
event,
int(cets['ext_timestamp'] / int(1e9)) * int(1e9),
detector_ids=[0, 1, 2, 3]) - cor_t for event, cets in zip(
events[:], coincidences.read_where('N == 1'))
]
if not len(t) or len(t) < 10:
continue
quantiles = [25, 50, 75]
qt = percentile(t, q=quantiles)
results.append([r] + list(qt) +
[100 * events.nrows / float(coincidences.nrows)])
if not len(results):
return
results = sorted(results)
(core_distances, arrival_times_low, arrival_times, arrival_times_high,
efficiency) = zip(*results)
causal = causal_front(i, core_distances)
plot = MultiPlot(2, 1)
splot = plot.get_subplot_at(0, 0)
plot_shower_profile(seeds, splot, core_distances, cor_t)
splot.plot(core_distances, causal, mark=None, linestyle='purple, dashed')
splot.plot(core_distances, arrival_times, mark='*')
splot.shade_region(core_distances,
arrival_times_low,
arrival_times_high,
color='blue, semitransparent')
splot.set_ylabel(r'Arrival time [\si{\ns}]')
splot = plot.get_subplot_at(1, 0)
splot.plot(core_distances, efficiency)
splot.set_ylabel(r'Detection efficiency [\si{\percent}]')
splot.set_axis_options(r'height=0.25\textwidth')
plot.set_ylimits(0, 0, min=-10, max=210)
plot.set_ylimits(1, 0, min=-5, max=105)
plot.set_xlimits_for_all(None, 0, 550)
plot.set_xlabel(r'Core distance [\si{\meter}]')
plot.show_xticklabels(1, 0)
plot.show_yticklabels_for_all()
plot.save_as_document(
'/data/hisparc/adelaat/corsika_accuracy/plots/%s.tex' %
get_info_string(seeds))