def main():
# Argument parser for config file name
parser = argparse.ArgumentParser(description='PETALO Output Comparator.')
parser.add_argument("-f",
"--json_file",
action="store_true",
help="Control File (json)")
parser.add_argument('arg1', metavar='N', nargs='?', help='')
parser.add_argument("-d",
"--directory",
action="store_true",
help="Work directory")
parser.add_argument('arg2', metavar='N', nargs='?', help='')
args = parser.parse_args()
if args.json_file:
file_name = ''.join(args.arg1)
else:
file_name = "sim_config"
if args.directory:
path = ''.join(args.arg2)
else:
path = "./"
config_file = file_name + ".json"
CG = CFG.SIM_DATA(filename=path + config_file, read=True)
CG = CG.data
DAQ_outfile = HF.DAQ_IO(
path=CG['ENVIRONMENT']['path_to_files'],
daq_filename=CG['ENVIRONMENT']['file_name'],
ref_filename=CG['ENVIRONMENT']['file_name'] + "0.h5",
daq_outfile=CG['ENVIRONMENT']['out_file_name'] + "_" + file_name +
".h5")
FASTDAQ_outfile = HF.DAQ_IO(
path=CG['ENVIRONMENT']['path_to_files'],
daq_filename=CG['ENVIRONMENT']['file_name'],
ref_filename=CG['ENVIRONMENT']['file_name'] + "0.h5",
daq_outfile=CG['ENVIRONMENT']['MC_out_file_name'] + "_" + file_name +
".h5")
data_DAQ, sensors = DAQ_outfile.read()
data_FASTDAQ, sensors = FASTDAQ_outfile.read()
i = 0
for event_F in data_FASTDAQ:
if (np.any(np.abs(event_F - data_DAQ[i]) != 0)):
print("Event %d is different in FASTDAQ and DAQ simulation" % i)
i += 1
def __init__(self,path,jsonfilename,file_number,encoder_data):
self.SIM_CONT = CFG.SIM_DATA(filename=path+jsonfilename+".json",read=True)
self.path = self.SIM_CONT.data['ENVIRONMENT']['path_to_files']
self.in_file = self.SIM_CONT.data['ENVIRONMENT']['MC_file_name']+"."+\
str(file_number).zfill(3)+".pet.h5"
self.out_file = self.SIM_CONT.data['ENVIRONMENT']['MC_out_file_name']+"."+\
str(file_number).zfill(3)+\
".h5"
self.TE1 = self.SIM_CONT.data['TOFPET']['TE']
self.TE2 = self.SIM_CONT.data['L1']['TE']
self.time_bin = self.SIM_CONT.data['ENVIRONMENT']['time_bin']
self.n_rows = self.SIM_CONT.data['TOPOLOGY']['n_rows']
self.n_L1 = len(self.SIM_CONT.data['L1']['L1_mapping_I'])+\
len(self.SIM_CONT.data['L1']['L1_mapping_O'])
# TOPOLOGY
self.L1, SiPM_I, SiPM_O, topology = DAQ.SiPM_Mapping(self.SIM_CONT.data,
self.SIM_CONT.data['L1']['map_style'])
self.sipmtoL1 = np.zeros(topology['n_sipms'],dtype='int32')
# Vector with SiPM assignment into L1
# Number of SiPMs per L1
L1_count = 0
for i in self.L1:
for j in i:
for l in j:
self.sipmtoL1[l] = L1_count
L1_count += 1
self.COMP = encoder_data
self.waves = np.array([])
self.tof = np.array([])
self.extents = np.array([])
self.sensors = np.array([])
self.n_events = 0
self.out_table = np.array([])
self.out_table_tof = np.array([])
self.data_enc = np.array([])
self.data_recons = np.array([])
self.sensors_t = np.array([])
self.gamma1_i1 = np.array([])
self.gamma2_i1 = np.array([])
self.table = None
self.h5file = None
if args.file_n:
file_n = int(''.join(args.arg3))
else:
file_n = 0
if args.show_photons:
g_opt['photons_id'] = True
else:
g_opt['photons_id'] = False
if args.show_sipmID:
g_opt['sipm_id'] = True
else:
g_opt['sipm_id'] = False
config_file = file_name + ".json"
SIM_CONT=conf.SIM_DATA(filename=path + config_file ,read=True)
path = SIM_CONT.data['ENVIRONMENT']['path_to_files']
filename = SIM_CONT.data['ENVIRONMENT']['MC_out_file_name']+'.'+str(file_n).zfill(3)
#filename = "./VER5/DAQ_OF5mm_test_REAL"
positions = np.array(pd.read_hdf(path+filename+".h5",key='sensors'))
data_TE = np.array(pd.read_hdf(path+filename+".h5",key='MC_TE'), dtype = 'int32')
data_recons = np.array(pd.read_hdf(path+filename+".h5",key='MC_recons'), dtype = 'int32')
#data_TE = np.array(pd.read_hdf(path+filename+".h5",key='MC'), dtype = 'int32')
#data_recons = np.array(pd.read_hdf(path+filename+".h5",key='MC'), dtype = 'int32')
Qtapp = pg.QtGui.QApplication([])
window = QtGui.QWidget()
args = parser.parse_args()
if args.json_file:
json_file = ''.join(args.arg1)
else:
json_file = "test"
if args.directory:
path = ''.join(args.arg2)
else:
path="/home/viherbos/DAQ_DATA/NEUTRINOS/PETit-ring/5mm_pitch/"
#json_file = "./VER2/test"
#path = "/home/viherbos/DAQ_DATA/NEUTRINOS/PETit-ring/5mm_pitch/"
SIM_JSON = CFG.SIM_DATA(filename = path + json_file +".json",read=True)
encoder_file = SIM_JSON.data['ENVIRONMENT']['AUTOENCODER_file_name']
Tenc = SIM_JSON.data['L1']['Tenc']
# MATLAB AUTOENCODER DATA READING (Trick to read easily and keep names)
# COMP={}
# with pd.HDFStore(path + encoder_file) as store:
# keys = store.keys()
# COMP = {i[1:]:np.array(pd.read_hdf(path + encoder_file,key=i[1:])) for i in keys}
# Keras Model read hack:
try:
with tb.open_file(path + encoder_file[2:] + ".h5") as h5file:
B=[]
event_info = np.hstack([true_data, event_info])
print("Event %d is Valid" % event)
else:
event_info = np.zeros(9 + self.n_sipms * 2) - 1
return event_info
if __name__ == '__main__':
# CONFIGURATION READING
path = "/volumedisk0/home/viherbos/DAQ_data/"
jsonfilename = "CUBE"
SIM_CONT = conf.SIM_DATA(filename=path + jsonfilename + ".json", read=True)
data = SIM_CONT.data
L1_Slice, Matrix_I, Matrix_O, topo = DAQ.SiPM_Mapping(
data, data['L1']['map_style'])
SIPM = {'n_sipms': 3500, 'first_sipm': 1000, 'tau_sipm': [100, 15000]}
# Add SiPM info in .json file
# GENERAL PARAMETERS
n_files = 50
time_bin = 5
cores = 20
name = "petit_ring_tof_all_tables"
path = "/volumedisk0/home/paolafer/vicente/"
help="Work directory")
parser.add_argument('arg2', metavar='N', nargs='?', help='')
args = parser.parse_args()
if args.json_file:
file_name = ''.join(args.arg1)
else:
file_name = "sim_config"
if args.directory:
path = ''.join(args.arg2)
else:
path = "./"
config_file = file_name + ".json"
CG = CFG.SIM_DATA(filename=path + config_file, read=True)
CG = CG.data
# Read data from json file
n_sipms_int = CG['TOPOLOGY']['sipm_int_row'] * CG['TOPOLOGY']['n_rows']
n_sipms_ext = CG['TOPOLOGY']['sipm_ext_row'] * CG['TOPOLOGY']['n_rows']
n_sipms = n_sipms_int + n_sipms_ext
first_sipm = CG['TOPOLOGY']['first_sipm']
n_files = CG['ENVIRONMENT']['n_files']
# Number of files to group for data input
A = HF.hdf_compose(CG['ENVIRONMENT']['path_to_files'],
CG['ENVIRONMENT']['file_name'], n_files, n_sipms)
DATA, TDC, sensors, n_events = A.compose()
# Number of events for simulation