def dump_data(self, hdf5_folder, filename, timezone, subjects={}):
mprintln('Dumping the data from: ' + filename)
out_h5ls = check_output([hdf5_folder + 'h5ls', filename + '/subjects'])
# cache_filenmae = 'obj.save'
# if os.path.isfile(cache_filenmae):
# f = file(cache_filenmae, 'rb')
# loaded_data = cPickle.load(f)
# f.close()
# return loaded_data
for n in subjects:
print n + " - " + str(len(subjects[n]))
for n in out_h5ls.split('\n'):
subject = n.split(' ')[0]
if subject:
out_h5dump = check_output([hdf5_folder + 'h5dump', '--group=subjects/' + subject, filename])
if subject not in subjects:
subjects[subject] = []
subjects[subject] += self.extract_data(out_h5dump, filename)
# f = file(cache_filenmae, 'wb')
# cPickle.dump(subjects, f, protocol=cPickle.HIGHEST_PROTOCOL)
# f.close()
for n in subjects:
print n + " - " + str(len(subjects[n]))
return subjects
def save_to_csv(self, fname, subjects):
mprintln('Saving the data to: ' + fname)
with open(fname, 'wb') as csvfile:
writer = csv.writer(csvfile, delimiter=',', quotechar='|', quoting=csv.QUOTE_MINIMAL)
for subject in subjects:
for record in subject:
writer.writerow(record)
def process_all(self, hdf5_folder, columns, antennas, timezone, input_files, bin_time):
mprintln('Processing the data...')
mprint(str(len(input_files)) + ' file(s) found')
result = {}
subjects_data = {}
for n in range(len(input_files)):
subjects_data = self.dump_data(hdf5_folder, input_files[n], subjects_data)
for subject in subjects_data:
while True:
binned_data = self.get_binned_record(subjects_data[subject], bin_time)
if binned_data:
# remove the records from the list
subjects_data[subject] = subjects_data[subject][len(binned_data):]
# add binned data to the result list
result = self.add_record_to_dictionary(result, timezone, subject, binned_data, columns, antennas)
else:
break
return result
