def search_coincidences(self):
if '/c_index' not in self.data and '/timestamps' not in self.data:
c_index, timestamps = \
coincidences.search_coincidences(self.data,
self.station_groups)
timestamps = np.array(timestamps, dtype=np.uint64)
self.data.createArray('/', 'timestamps', timestamps)
self.data.createVLArray('/', 'c_index', tables.UInt32Atom())
for coincidence in c_index:
self.data.root.c_index.append(coincidence)
def determine_station_offsets(self, overwrite=False):
offsets_group = '/station_offsets'
if offsets_group in self.data and not overwrite:
self.station_offsets = self.data.root.station_offsets.read()
else:
ref_group = '/s501'
station_groups = list(self.station_groups)
station_groups.remove(ref_group)
gauss = lambda x, N, mu, sigma: N * norm.pdf(x, mu, sigma)
bins = linspace(-1e3, 1e3, 101)
for station_id, station_group in enumerate(station_groups):
c_index, timestamps = coincidences.search_coincidences(
self.data, [ref_group, station_group])
dt = []
c_index = [c for c in c_index if len(c) == 2]
for i, j in c_index:
stations = [timestamps[u][1] for u in [i, j]]
t0, t1 = [int(timestamps[u][0]) for u in [i, j]]
if stations[0] > stations[1]:
t0, t1 = t1, t0
dt.append(t1 - t0)
print ref_group, station_group, len(dt),
y, bins = np.histogram(dt, bins=bins)
x = (bins[:-1] + bins[1:]) / 2
popt, pcov = curve_fit(gauss, x, y, p0=(len(dt), 0, 100.))
print popt
self.station_offsets.append(popt[1])
ref_idx = self.station_groups.index(ref_group)
self.station_offsets.insert(ref_idx, 0.)
if offsets_group in self.data:
self.data.removeNode(offsets_group)
group, node = os.path.split(offsets_group)
self.data.createArray(group, node, self.station_offsets)
import tables
import datetime
from hisparc.publicdb import download_data
from hisparc.analysis import coincidences
import time
if __name__ == '__main__':
data = tables.openFile('test.h5', 'w')
t0 = time.time()
for station in range(501, 506):
download_data(
data, '/hisparc/station' + str(station), station_id=station,
start=datetime.datetime(2009, 2, 24, 12),
end=datetime.datetime(2009, 2, 24, 13))
t1 = time.time()
coincidences, timestamps = coincidences.search_coincidences(
data,
['/hisparc/station501',
'/hisparc/station502',
'/hisparc/station503',
'/hisparc/station504',
'/hisparc/station505'],
shifts=[None, None, -15, None, None])
t2 = time.time()
print 'Download: %f (%.1f%%)' % (t1 - t0, 100 * (t1 - t0) / (t2 - t0))
print 'Processing: %f (%.1f%%)' % (t2 - t1,
100 * (t2 - t1) / (t2 - t0))
print 'Total:', t2 - t0
