parser.add_argument('--d', type=str)
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:
continue
correlations = {}
num_channels = 4
cross_combinations = list(
itertools.combinations(range(num_channels), 2))
for comb in cross_combinations:
filename = "{a}x{b}.npy".format(a=comb[0], b=comb[1])
with open("{d}/{t}/{f}".format(d=directory,
t=timestamp,
f=filename)) as f:
signal = np.load(f)
correlations[comb] = signal
correlator = FakeCorrelator(signals=correlations)
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'
)
correlator.apply_frequency_domain_calibrations()
array = AntennaArray.mk_from_config(args.array_geometry_file)
df = DirectionFinder(correlator, array, args.f_start,
logger.getChild('df'))
df.df_strongest_signal(args.f_start,
args.f_stop,
directory,
t=timestamp)
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
for elements in [3, 4]:
array = AntennaArray.mk_circular(args.radius * (elements / 4.0),
elements)
named_antenna_arrays.append(NamedArray(str(elements), array))
if args.array_geometry_file:
array = AntennaArray.mk_from_config(args.array_geometry_file)
named_antenna_arrays.append(NamedArray("4'", array))
for elements in [5, 6, 7]:
array = AntennaArray.mk_circular(args.radius * (elements / 4.0),
elements)
named_antenna_arrays.append(NamedArray(str(elements), array))
for named_arr in named_antenna_arrays:
name = named_arr.name
arr = named_arr.array
df = DirectionFinder(None, arr, args.freq, logger.getChild('df'))
logging.info("Doing array: {arr}".format(arr=name))
y = []
for visibility_rms_err in visibility_rms_errs:
logging.info("Doing rms visibility error: {er}".format(
er=visibility_rms_err))
df_errors = []
for phi in phi_domain:
array_response = arr.each_pair_phase_difference_at_angle(
phi, args.freq)
visibility_errors = np.random.normal(0, visibility_rms_err,
array_response.shape)
array_response += visibility_errors
angle_out = df.find_closest_point(array_response)
angular_error = np.arctan2(np.sin(phi - angle_out),
np.cos(phi - angle_out))
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,
parser.add_argument('--impulse', type=bool, default=False)
parser.add_argument('--impulse_setpoint', type=int)
parser.add_argument('--acc_len', type=int, default=40000)
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
parser.add_argument('--array_geometry_file', default=None)
args = parser.parse_args()
directory = args.d
contents = os.listdir(directory)
contents.sort()
for timestamp_str in contents:
try:
timestamp = float(timestamp_str)
except ValueError:
continue
correlations = {}
num_channels = 4
cross_combinations = list(itertools.combinations(range(num_channels), 2))
for comb in cross_combinations:
filename = "{a}x{b}.npy".format(a = comb[0], b = comb[1])
with open("{d}/{t}/{f}".format(d = directory, t = timestamp, f = filename)) as f:
signal = np.load(f)
correlations[comb] = signal
correlator = FakeCorrelator(signals = correlations)
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')
correlator.apply_frequency_domain_calibrations()
array = AntennaArray.mk_from_config(args.array_geometry_file)
df = DirectionFinder(correlator, array, args.f_start, logger.getChild('df'))
df.df_strongest_signal(args.f_start, args.f_stop, directory, t = timestamp)
