def download_data(self):
start, end = self.datetimerange
for station, group_path in zip(self.stations, self.station_groups):
if not group_path in self.data:
print "Downloading data for station", station
download_data(self.data, group_path, station,
start, end, get_blobs=True)
def download_data(self):
start, end = self.datetimerange
for station, group_path in zip(self.stations, self.station_groups):
if not group_path in self.data:
print "Downloading data for station", station
download_data(self.data,
group_path,
station,
start,
end,
get_blobs=True)
def first_download(station): # Not used in the current script; could be integrated later on
""" Downloads data from HDF5
Including data for referencedate (if necessary)
"""
group = '/s%s' % station
with openFile(filepath, 'a') as datafile:
if group not in datafile:
download_data(datafile, group, station, START, STOP)
nextday = REFDATE + timedelta(days=1)
if REFDATE < START or nextday > STOP:
download_data(datafile, '/s%s' % station, station, REFDATE, nextday)
def download_part(station_id, start, stop):
""" Download HiSPARC data from start till stop
"""
hisp_station = int(station_id)
tree = '/s' + station_id
path = 'data.root.s' + station_id
filename = 'data_s%d_%s_%s.h5' % (hisp_station,
start.strftime('%Y%m%d'),
stop.strftime('%Y%m%d'))
with tables.openFile(filename, 'w') as data:
download_data(data, tree, hisp_station, start, stop)
remove_duplicate_events(data, eval(path))
weather_data_in_file = check_if_weather(data, filename)
if weather_data_in_file:
remove_duplicate_events(data, eval(path), kind='weather')
print ''
print "'" + filename + "' has downloaded."
print 'You can find it at the location: ' + os.getcwd()
print ''
return filename
This script is a small demonstration which shows how to download some
data from one particular detector, in this case 4001 at KVI, and make
a simple pulse height histogram.
"""
import tables
import datetime
from hisparc.publicdb import download_data
import pylab
if __name__ == '__main__':
# Open data file and download data
data = tables.openFile('kvi.h5', 'w')
download_data(data, '/hisparc/kvi', station_id=4001,
start=datetime.datetime(2009, 11, 23),
end=datetime.datetime(2009, 11, 24))
# Fetch pulseheights...
ph = [x['pulseheights'] for x in data.root.hisparc.kvi.events]
# ...and rearrange
ph = zip(*ph)
# ...and drop detectors 3 and 4 (slave not attached)
ph = ph[:2]
# Convert to mV
ph = [[x * .57 for x in det] for det in ph]
# Bin pulseheights of detector 1 and 2
pylab.hist(ph[0], bins=100, range=[0, 2000], histtype='step')
pylab.hist(ph[1], bins=100, range=[0, 2000], histtype='step')
pylab.figure()
for x in data:
pylab.hist(x, bins=bins, log=True, histtype='step')
pylab.title(title)
pylab.xlabel('pulse height (raw ADC values)')
pylab.ylabel('count')
if xlim:
pylab.xlim(xlim)
if __name__ == '__main__':
if os.path.exists('jos.h5'):
data = tables.openFile('jos.h5', 'r')
else:
data = tables.openFile('jos.h5', 'w')
download_data(data, '/hisparc/s501', station_id=501,
start=datetime.datetime(2009, 1, 3),
end=datetime.datetime(2009, 1, 11))
download_data(data, '/hisparc/s505', station_id=505,
start=datetime.datetime(2009, 1, 3),
end=datetime.datetime(2009, 1, 11))
ph = [x['pulseheights'] for x in data.root.hisparc.s501.events]
twohigh = zip(*[x for x in ph if (x >= 123).tolist().count(True) >= 2])
#threelow = zip(*[x for x in ph if (x >= 53).tolist().count(True) >= 3])
#twoscint = zip(*[x[:2] for x in ph if (x[:2] >= 123).tolist().count(True) >= 2])
make_hist(twohigh, bins=range(0, 2000, 20),
title="Trigger: at least two high (20 ADC values per bin)")
make_hist(twohigh, bins=range(0, 2000, 1),
title="Trigger: at least two high (1 ADC values per bin)")
make_hist(twohigh, bins=range(0, 2000, 1),
and you're set.
"""
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))
