def apply_cal_factor_to_prof(dir,
psr_file,
cal_factor,
rfi_mitigation=False,
threshold=3,
setdata=True):
file = dir + psr_file
ar = Archive(file, verbose=False)
if rfi_mitigation:
rfi_mit = RFIMitigator(ar)
rfi_mit.zap_minmax(threshold=threshold)
nchan = ar.getNchan()
nsub = ar.getNsubint()
data = ar.getData()
converted_data_aa, converted_data_bb = IQUV_to_AABB(data,
basis="cartesian")
new_converted_aa, new_converted_bb, new_converted, new_data = np.empty(
nsub, dtype=object), np.empty(nsub, dtype=object), np.empty(
nsub, dtype=object), np.empty(nsub, dtype=object)
for i, sub in enumerate(np.arange(nsub)):
new_converted_aa[i] = row_multiply(converted_data_aa[i], cal_factor[0])
new_converted_bb[i] = row_multiply(converted_data_bb[i], cal_factor[1])
new_converted[i] = np.array((new_converted_aa[i], new_converted_bb[i]))
new_data[i] = AABB_to_IQUV(new_converted[i], basis="cartesian")
if setdata:
ar.setData(new_data)
return new_data, ar
def apply_cal_factor_to_prof(dir,
psr_file,
cal_factor,
rfi_mitigation=False,
threshold=3,
setdata=True):
cal_fa = vector_to_diagonal(cal_factor[0])
cal_fb = vector_to_diagonal(cal_factor[1])
file = dir + psr_file
ar = Archive(file, verbose=False)
if rfi_mitigation:
rfi_mit = RFIMitigator(ar)
rfi_mit.zap_minmax(threshold=threshold)
nchan = ar.getNchan()
nsub = ar.getNsubint()
data = ar.getData(squeeze=False)
print(data.shape)
print(cal_fa.shape)
converted_data = IQUV_to_AABB(data, basis="cartesian")
print(converted_data.shape)
exit()
new_converted = []
new_data = []
s = np.array(s)
aa = np.dot(converted_data, cal_fa)
bb = np.dot(s, cal_fb)
new_converted.append((aa, bb))
new_data.append(AABB_to_IQUV(new_converted[i], basis="cartesian"))
print("Almost done")
a = np.array(new_converted)
new_data = np.array(new_data)
print(new_data.shape)
if setdata:
ra = ar.setData(new_data)
return new_data, ra