def __init__(self, file_root, time=0, freq=0, level="approx"):
# Get model
fname = file_root + ".uvh5"
print("Get true model from", fname)
uvdata = UVData()
uvdata.read_uvh5(fname)
assert uvdata.Nants_data == uvdata.Nants_telescope, \
"Not all antennas have data"
nant = uvdata.Nants_data
# Map antenna numbers to the vis index
ants_to_baseline = []
for i in range(nant):
for j in range(i + 1, nant):
ants_to_baseline.append((i, j))
assert uvdata.Nbls-nant == len(ants_to_baseline), \
"Data does not contain expected number of baselines"
nvis = len(ants_to_baseline)
# Load model
V_model = np.zeros(nvis, dtype=np.complex64)
for i, bl in enumerate(ants_to_baseline):
V_model[i] = uvdata.get_data(bl[0], bl[1], "XX")[time][freq]
# Get true gains
fname = file_root + ".calfits"
print("Get true gains from", fname)
uvc = UVCal()
uvc.read_calfits(fname)
g_bar = np.zeros(nant, dtype=np.complex64)
for i in range(nant):
g_bar[i] = uvc.get_gains(i)[0, 0]
# Get V_obs
fname = file_root + "_g.uvh5"
print("Get V_obs from", fname)
uvdata = UVData()
uvdata.read_uvh5(fname)
assert uvdata.Nants_data == uvdata.Nants_telescope, \
"Not all antennas have data"
assert uvdata.Nbls-nant == nvis, \
"Data does not contain expected number of baselines"
# Load V_obs
V = np.zeros(nvis, dtype=np.complex64)
for i, bl in enumerate(ants_to_baseline):
V[i] = uvdata.get_data(bl[0], bl[1], "XX")[time][freq]
self.level = level
self.nant = nant
self.nvis = nvis
self.g_bar = g_bar
self.V_model = V_model
self.x = np.zeros(g_bar.size, dtype=np.complex64)
self.V_obs = V
self.obs_variance = np.full(V.size, 1)
self.redundant_groups, _, _ = uvdata.get_redundancies()
def __init__(self, file_root, time=0, freq=0, level="approx"):
"""
file_root: str
The file path referring to a non-redundant-pipeline simulation "case".
Use that path to select files from the simulation based on their extension.
"""
# Get V_obs from last file generated by analyse_sims.py
fname = file_root + "_g.uvh5"
print("Get V_obs from", fname)
uvdata = UVData()
uvdata.read_uvh5(fname)
assert uvdata.Nants_data == uvdata.Nants_telescope, \
"Not all antennas have data"
nant = uvdata.Nants_data
# Map antenna numbers to the vis index
ants_to_baseline = []
for i in range(nant):
for j in range(i + 1, nant):
ants_to_baseline.append((i, j))
assert uvdata.Nbls-nant == len(ants_to_baseline), \
"Data does not contain expected number of baselines"
nvis = len(ants_to_baseline)
# Load V_obs
V = np.zeros(nvis, dtype=np.complex64)
for i, bl in enumerate(ants_to_baseline):
V[i] = uvdata.get_data(bl[0], bl[1], "XX")[time][freq]
# Get things out of calibration: model, redundant groups, weights
fname = file_root + "_g_cal_dict.npz"
print("Get model from", fname)
cal = hkl.load(fname)
baseline_groups = cal["all_reds"]
redundant_groups = [[] for bg in baseline_groups]
assert len(cal["v_omnical"].keys()) == len(baseline_groups), \
"Number of baseline groups: "+str(len(baseline_groups))+ \
" Number of model groups: "+str(len(cal["v_omnical"].keys()))
V_model = np.zeros(nvis, dtype=np.complex64)
for key in cal["v_omnical"].keys():
baseline = (key[0], key[1])
# Find the baselines in this group. First item will be "ants"
group_index = -1
for i in range(len(baseline_groups)):
if (baseline_groups[i][0][0],
baseline_groups[i][0][1]) == baseline:
group_index = i
break
if group_index == -1:
raise RuntimeError("Couldn't find redundant group for model " +
str(key))
for bl in baseline_groups[group_index]:
try:
i = ants_to_baseline.index((bl[0], bl[1]))
V_model[i] = cal["v_omnical"][key][time][freq]
except:
i = ants_to_baseline.index((bl[1], bl[0]))
V_model[i] = np.conj(cal["v_omnical"][key][time][freq])
redundant_groups[group_index].append(i)
assert np.min(np.abs(V_model)) > 0, "Model has missing values"
# Get the weights used by calibration
num_weights = len(list(cal["omni_meta"]["data_wgts"]))
assert num_weights == V.size, "Not enough weights for baselines " + str(
num_weights) + " " + str(V.size)
weights = np.zeros(V.size)
for key in cal["omni_meta"]["data_wgts"].keys():
try:
i = ants_to_baseline.index((key[0], key[1]))
except:
i = ants_to_baseline.index((key[1], key[0]))
weights[i] = cal["omni_meta"]["data_wgts"][key][time][freq]
# Get the gains generated from calibration
fname = file_root + "_g_new.calfits"
print("Get gains from", fname)
uvc = UVCal()
uvc.read_calfits(fname)
g_bar = np.zeros(nant, dtype=np.complex64)
for i in range(nant):
g_bar[i] = uvc.get_gains(i)[0, 0]
self.level = level
self.nant = nant
self.nvis = nvis
self.V_obs = V
self.V_model = V_model
self.g_bar = g_bar
self.x = np.zeros(g_bar.size, dtype=np.complex64)
self.obs_variance = weights
self.redundant_groups = redundant_groups
