parser.add_argument('--f_start', default=200e6, type=float)
parser.add_argument('--f_stop', default=300e6, type=float)
parser.add_argument('--array_geometry_file', default=None)
args = parser.parse_args()
directory = args.d
correlator = FakeCorrelator()
correlator.add_cable_length_calibrations('/home/jgowans/workspace/directionFinder_backend/config/cable_length_calibration_actual_array.json')
correlator.add_time_domain_calibration('/home/jgowans/workspace/directionFinder_backend/config/time_domain_calibration_through_rf_chain.json')
fs = correlator.fs
array = AntennaArray.mk_from_config(args.array_geometry_file)
df = DirectionFinder(correlator, array, args.f_start, logger.getChild('df'))
df.set_time()
contents = os.listdir(directory)
contents.sort()
for timestamp_str in contents:
try:
timestamp = float(timestamp_str)
except ValueError:
continue
#fig = plt.figure()
correlator.time_domain_signals = None
num_channels = 4
for channel in range(num_channels):
filename = "{c}.npy".format(c = channel)
with open("{d}/{t}/{f}".format(d = directory, t = timestamp, f = filename)) as f:
signal = np.load(f)
directory = args.d
correlator = FakeCorrelator()
correlator.add_cable_length_calibrations(
'/home/jgowans/workspace/directionFinder_backend/config/cable_length_calibration_actual_array.json'
)
correlator.add_time_domain_calibration(
'/home/jgowans/workspace/directionFinder_backend/config/time_domain_calibration_through_rf_chain.json'
)
fs = correlator.fs
array = AntennaArray.mk_from_config(args.array_geometry_file)
df = DirectionFinder(correlator, array, args.f_start,
logger.getChild('df'))
df.set_time()
contents = os.listdir(directory)
contents.sort()
for timestamp_str in contents:
try:
timestamp = float(timestamp_str)
except ValueError:
continue
#fig = plt.figure()
correlator.time_domain_signals = None
num_channels = 4
for channel in range(num_channels):
filename = "{c}.npy".format(c=channel)
with open("{d}/{t}/{f}".format(d=directory,
t=timestamp,
os.mkdir(df_raw_dir)
array = AntennaArray.mk_from_config(args.array_geometry_file)
correlator = Correlator(logger=logger.getChild('correlator'))
correlator.set_accumulation_len(args.acc_len)
correlator.add_cable_length_calibrations(
'/home/jgowans/workspace/directionFinder_backend/config/cable_length_calibration_actual_array.json'
)
correlator.add_frequency_bin_calibrations(
'/home/jgowans/workspace/directionFinder_backend/config/frequency_domain_calibration_through_chain.json'
)
df = DirectionFinder(correlator, array, args.f_start,
logger.getChild('df'))
if args.impulse == True:
df.set_time() # go into time mode
# 100 impulse filter len = 0.5 us
correlator.set_impulse_filter_len(100)
correlator.set_impulse_setpoint(args.impulse_setpoint)
correlator.re_sync()
time.sleep(0.1)
correlator.impulse_arm()
while True:
if args.impulse == True:
if df.fetch_impulse() == True:
correlator.save_time_domain_snapshots(df_raw_dir)
# not necessary to apply cal as it's done in the correlation routine
df.df_impulse(df_raw_dir)
else:
df.fetch_frequency_crosses()
parser.add_argument('--comment', type=str)
args = parser.parse_args()
df_raw_dir = '/home/jgowans/Documents/df_raw/{c}/'.format(c = args.comment)
if not os.path.exists(df_raw_dir):
os.mkdir(df_raw_dir)
array = AntennaArray.mk_from_config(args.array_geometry_file)
correlator = Correlator(logger = logger.getChild('correlator'))
correlator.set_accumulation_len(args.acc_len)
correlator.add_cable_length_calibrations('/home/jgowans/workspace/directionFinder_backend/config/cable_length_calibration_actual_array.json')
correlator.add_frequency_bin_calibrations('/home/jgowans/workspace/directionFinder_backend/config/frequency_domain_calibration_through_chain.json')
df = DirectionFinder(correlator, array, args.f_start, logger.getChild('df'))
if args.impulse == True:
df.set_time() # go into time mode
# 100 impulse filter len = 0.5 us
correlator.set_impulse_filter_len(100)
correlator.set_impulse_setpoint(args.impulse_setpoint)
correlator.re_sync()
time.sleep(0.1)
correlator.impulse_arm()
while True:
if args.impulse == True:
if df.fetch_impulse() == True:
correlator.save_time_domain_snapshots(df_raw_dir)
# not necessary to apply cal as it's done in the correlation routine
df.df_impulse(df_raw_dir)
else:
df.fetch_frequency_crosses()
