def spike_detection_job(DatFileNames, ProbeFileName, output_dir, output_name):
"""
Top level function that starts a data processing job.
"""
for DatFileName in DatFileNames:
if not os.path.exists(DatFileName):
raise Exception("Dat file %s does not exist" % DatFileName)
DatFileNames = [os.path.abspath(DatFileName)
for DatFileName in DatFileNames]
probe = probes.Probe(ProbeFileName)
n_ch_dat = Parameters['NCHANNELS']
sample_rate = Parameters['SAMPLERATE']
high_frequency_factor = Parameters['F_HIGH_FACTOR']
set_globals_samples(sample_rate, high_frequency_factor)
Parameters['CHUNK_OVERLAP'] = int(
sample_rate * Parameters['CHUNK_OVERLAP_SECONDS'])
Parameters['N_CH'] = probe.num_channels
max_spikes = Parameters['MAX_SPIKES']
basename = basenamefolder = output_name
# OutDir = join(output_dir, basenamefolder)
OutDir = output_dir
with indir(OutDir):
# Create a log file
GlobalVariables['log_fd'] = open(basename + '.log', 'w')
if Parameters['DEBUG']:
GlobalVariables['debug_fd'] = open(basename + '.debug', 'w')
Channels_dat = np.arange(probe.num_channels)
# Print Parameters dictionary to .log file
log_message("\n".join(["{0:s} = {1:s}".format(key, str(value))
for key, value in sorted(Parameters.iteritems()) if not key.startswith('_')]))
spike_detection_from_raw_data(basename, DatFileNames, n_ch_dat,
Channels_dat, probe.channel_graph,
probe, max_spikes)
numwarn = GlobalVariables['warnings']
if numwarn:
log_message(
'WARNINGS ENCOUNTERED: ' + str(numwarn) + ', check log file.')
# Close the log file at the end.
if 'log_fd' in GlobalVariables:
GlobalVariables['log_fd'].close()
def openmc(self, state):
"""Runs OpenMC for a given state."""
# make inpurs
pwd = self.pwd(state)
if not os.path.isdir(pwd):
os.makedirs(pwd)
self._make_omc_input(state)
# run openmc
statepoint = _find_statepoint(pwd)
if statepoint is None:
with indir(pwd):
subprocess.check_call(['openmc'])
statepoint = _find_statepoint(pwd)
# parse & prepare results
k, phi_g = self._parse_statepoint(statepoint)
xstab = self._generate_xs(phi_g)
return k, phi_g, xstab
