def download_coincidences_pair(pair):
path = DATAPATH % tuple(pair)
tmp_path = path + '_tmp'
if os.path.exists(path):
print 'Skipping', pair
return
print 'Starting', pair, datetime.datetime.now()
distance = distance_between_stations(*pair)
timestamp_ranges = get_timestamp_ranges(pair)
total_exposure = get_total_exposure(timestamp_ranges)
with tables.open_file(tmp_path, 'w') as data:
data.set_node_attr('/', 'total_exposure', total_exposure)
data.set_node_attr('/', 'distance', distance)
for ts_start, ts_end in timestamp_ranges:
download_coincidences(data, stations=list(pair),
start=gps_to_datetime(ts_start),
end=gps_to_datetime(ts_end),
progress=False)
try:
coin = data.get_node('/coincidences')
except tables.NoSuchNodeError:
print 'No coincidences for', pair
os.rename(tmp_path, path)
return
rate = coin.coincidences.nrows / total_exposure
data.set_node_attr('/', 'n_rate', rate)
data.set_node_attr('/', 'n_coincidences', coin.coincidences.nrows)
os.rename(tmp_path, path)
determine_rate(path)
print 'Finished', pair, datetime.datetime.now()
def download_dataset():
delta_data = genfromtxt('time_delta_fixed.tsv',
delimiter='\t',
dtype=None,
names=['ext_timestamp', 'time_delta'])
start = gps_to_datetime(delta_data['ext_timestamp'][0] / int(1e9))
end = gps_to_datetime(delta_data['ext_timestamp'][-1] / int(1e9))
with tables.open_file('data.h5', 'w') as data:
download_data(data, '/s501', 501, start, end)
download_data(data, '/s501_original', 501, start, end)
with tables.open_file('data.h5', 'a') as data:
events = data.root.s501.events
idx = delta_data['ext_timestamp'].tolist().index(
events[-1]['ext_timestamp']) + 1
time_delta = delta_data['time_delta'][:idx]
t3 = data.root.s501.events.col('t3')[1:]
t4 = data.root.s501.events.col('t4')[1:]
events.modify_column(start=1,
colname='t3',
column=where(t3 >= 0, t3 + time_delta, t3))
events.modify_column(start=1,
colname='t4',
column=where(t4 >= 0, t4 + time_delta, t4))
events.flush()
def download_dataset():
print 'Downloading data . . .'
with tables.open_file(DATA, 'w'):
# Clear previous data
pass
for station in STATIONS:
delta_data = genfromtxt('data/time_delta_%d.tsv' % station,
delimiter='\t',
dtype=None,
names=['ext_timestamp', 'time_delta'])
start = gps_to_datetime(delta_data['ext_timestamp'][0] / int(1e9))
end = gps_to_datetime(delta_data['ext_timestamp'][-1] / int(1e9))
with tables.open_file(DATA, 'a') as data:
download_data(data, '/s%d' % station, station, start, end)
download_data(data, '/s%d_original' % station, station, start, end)
with tables.open_file(DATA, 'a') as data:
events = data.get_node('/s%d' % station, 'events')
# Data ends before delta list because I got delta data from today
delta_ets_list = delta_data['ext_timestamp'].tolist()
stop_idx = delta_ets_list.index(events[-1]['ext_timestamp']) + 1
time_delta = delta_data['time_delta'][:stop_idx]
event_ets_list = events.col('ext_timestamp').tolist()
idx = event_ets_list.index(delta_ets_list[0])
events.remove_rows(0, idx)
try:
last_idx = event_ets_list[idx::].index(
delta_ets_list[-1]) - idx
except ValueError:
pass
else:
events.remove_rows(last_idx)
events.flush()
assert all(
events.col('ext_timestamp') == delta_data['ext_timestamp'])
t3 = events.col('t3')
t4 = events.col('t4')
events.modify_column(colname='t3',
column=where(t3 >= 0, t3 + time_delta, t3))
events.modify_column(colname='t4',
column=where(t4 >= 0, t4 + time_delta, t4))
events.flush()
def plot_histogram(data, timestamps, station_numbers):
"""Make a 2D histogram plot of the number of events over time per station
:param data: list of lists, with the number of events.
:param station_numbers: list of station numbers in the data list.
"""
plot = Plot(width=r'\linewidth', height=r'1.3\linewidth')
plot.histogram2d(data.T[::7][1:],
timestamps[::7] / 1e9,
np.arange(len(station_numbers) + 1),
type='reverse_bw',
bitmap=True)
plot.set_label(
gps_to_datetime(timestamps[-1]).date().isoformat(), 'upper left')
plot.set_xlimits(min=YEARS_TICKS[0] / 1e9, max=timestamps[-1] / 1e9)
plot.set_xticks(YEARS_TICKS / 1e9)
plot.set_xtick_labels(YEARS_LABELS)
plot.set_yticks(np.arange(0.5, len(station_numbers) + 0.5))
plot.set_ytick_labels(['%d' % s for s in sorted(station_numbers)],
style=r'font=\sffamily\tiny')
plot.set_axis_options('ytick pos=right')
plot.save_as_pdf('eventtime_histogram_network_hour')
def test_gps_to_datetime(self):
for date, timestamp, _ in self.combinations:
dt = datetime.datetime.strptime(date, '%B %d, %Y')
self.assertEqual(clock.gps_to_datetime(timestamp), dt)
def test_gps_to_datetime(self):
for date, timestamp, _ in self.combinations:
dt = datetime.datetime.strptime(date, '%B %d, %Y')
self.assertEqual(clock.gps_to_datetime(timestamp), dt)
STATION = 501
# Select the timestamp with the correct GPS location,
# relative to the existing station layout.
GOOD_GPS = 1412347557
OTHER_GPS = 1414406502
if __name__ == "__main__":
cluster = HiSPARCStations([STATION])
station = cluster.get_station(STATION)
# Move detectors of the 'bad' location to the correct and get the new
# relative coordinates.
cluster.set_timestamp(GOOD_GPS)
x0, y0 = station.get_xy_coordinates()
cluster.set_timestamp(OTHER_GPS)
x1, y1 = station.get_xy_coordinates()
print 'Station layout was good on', gps_to_datetime(GOOD_GPS)
print 'Station layout to be calculated for', gps_to_datetime(OTHER_GPS)
dx = x1 - x0
dy = y1 - y0
print 'GPS position moved by: %.3f m, %.3f m.' % (dx, dy)
print 'New relative detector coordinates'
cluster.set_timestamp(OTHER_GPS)
for d in station.detectors:
d.x[d.index] -= dx
d.y[d.index] -= dy
print cartesian_to_compass(d.x[d.index], d.y[d.index], d.z[d.index])