def read_and_store_data(self):
"""Read and store KASCADE data matching HiSPARC data
This function looks at the HiSPARC event data in the specified datafile
and then processes and adds KASCADE data surrounding those events, for
later coincidence processing.
"""
# Determine start and end timestamps from HiSPARC data
try:
timestamps = self.hisparc.col('timestamp')
start = gpstime.gps_to_utc(min(timestamps))
stop = gpstime.gps_to_utc(max(timestamps))
except IndexError:
raise RuntimeError("HiSPARC event table is empty")
print "Processing data from %s to %s" % (time.ctime(start),
time.ctime(stop))
self._process_events_in_range(start, stop)
def helper(hisparc, kascade, kascadefile):
"""Helper for quickly processing KASCADE data
This function looks at the HiSPARC event data in the specified datafile
and then processes and adds KASCADE data surrounding those events, for
later coincidence processing. Also, existing KASCADE data rows are
inspected to determine the time window.
:param hisparc: HiSPARC event table
:param kascade: KASCADE event table
:param kascadefile: KASCADE data file
Example::
>>> import tables
>>> import hisparc
>>> data = tables.openFile('kascade.h5', 'a')
>>> data.createGroup('/', 'kascade', "KASCADE data")
/kascade (Group) 'KASCADE data'
children := []
>>> data.createTable('/kascade', 'events', hisparc.containers.KascadeEvent, "KASCADE events")
/kascade/events (Table(0,)) 'KASCADE events'
description := {
"run_id": Int32Col(shape=(), dflt=0, pos=0),
"event_id": Int64Col(shape=(), dflt=0, pos=1),
"timestamp": Time32Col(shape=(), dflt=0, pos=2),
"nanoseconds": UInt32Col(shape=(), dflt=0, pos=3),
"ext_timestamp": UInt64Col(shape=(), dflt=0, pos=4),
"energy": Float64Col(shape=(), dflt=0.0, pos=5),
"core_pos": Float64Col(shape=(2,), dflt=0.0, pos=6),
"zenith": Float64Col(shape=(), dflt=0.0, pos=7),
"azimuth": Float64Col(shape=(), dflt=0.0, pos=8),
"Num_e": Float64Col(shape=(), dflt=0.0, pos=9),
"Num_mu": Float64Col(shape=(), dflt=0.0, pos=10),
"dens_e": Float64Col(shape=(4,), dflt=0.0, pos=11),
"dens_mu": Float64Col(shape=(4,), dflt=0.0, pos=12),
"P200": Float64Col(shape=(), dflt=0.0, pos=13),
"T200": Float64Col(shape=(), dflt=0.0, pos=14)}
byteorder := 'little'
chunkshape := (399,)
>>> hisparc.kascade.helper(data.root.hisparc.cluster_kascade.station_601.events, data.root.kascade.events, 'HiSparc.dat.gz')
Processing data from Tue Jul 1 16:29:31 2008 to Tue Jul 1 17:15:06 2008
"""
# Determine start and end timestamps from HiSPARC data
try:
ts = hisparc[:]['timestamp']
hstart = gpstime.gps_to_utc(min(ts))
hstop = gpstime.gps_to_utc(max(ts))
except IndexError:
print "There is no HiSPARC data yet."
return
# Determine start and stop timestamps from KASCADE data
try:
ts = kascade[:]['timestamp']
kstart = min(ts)
kstop = max(ts)
except ValueError:
kstart = None
kstop = None
if hstart < kstart and kstart is not None:
# This should never happen
print "WARNING: HiSPARC data found which is earlier than KASCADE"
print "data. Please check your timestamps:"
print "First HiSPARC data:", hstart
print "First KASCADE data:", kstart
print "The timestamps should not differ by much."
if kstart is None:
# There is no KASCADE data yet
start, stop = hstart, hstop
else:
# To avoid duplicates in the case of an aborted previous run,
# remove rows which share the latest timestamp, because we want to
# reprocess that timestamp
l = kascade.getWhereList('timestamp==%d' % kstop)
kascade.removeRows(start=l[0], stop=l[-1] + 1)
start, stop = kstop, hstop
print "Processing data from %s to %s" % (time.ctime(start),
time.ctime(stop))
process_events(kascadefile, kascade, start, stop)
