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()