Tibeuleu/FOC_Reduction
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change name convention and cleanup

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Tibeuleu
2023-02-09 15:28:21 +01:00
parent fc80bafc66
commit ce670f4a19
8 changed files with 31 additions and 21 deletions
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5
src/comparison_Kishimoto.py
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@@ -15,12 +15,13 @@ root_dir = path_join('/home/t.barnouin/Documents/Thesis/HST')
root_dir_K = path_join(root_dir,'Kishimoto','output')
root_dir_S = path_join(root_dir,'FOC_Reduction','output')
root_dir_data_S = path_join(root_dir,'FOC_Reduction','data','NGC1068_x274020')
filename_S = "NGC1068_FOC_bg_b_10px.fits"
data_K = {}
data_S = {}
for d,i in zip(['I','Q','U','P','PA','sI','sQ','sU','sP','sPA'],[0,1,2,5,8,(3,0,0),(3,1,1),(3,2,2),6,9]):
data_K[d] = np.loadtxt(path_join(root_dir_K,d+'.txt'))
with fits.open(path_join(root_dir_data_S,'NGC1068_FOC_bin10px.fits')) as f:
with fits.open(path_join(root_dir_data_S,filename_S)) as f:
if not type(i) is int:
data_S[d] = np.sqrt(f[i[0]].data[i[1],i[2]])
else:
@@ -110,7 +111,7 @@ print("This pipeline : average sI/I={0:.2f} ; sQ/Q={1:.2f} ; sU/U={2:.2f} ; sP/P
print("Kishimoto's pipeline : average sI/I={0:.2f} ; sQ/Q={1:.2f} ; sU/U={2:.2f} ; sP/P={3:.2f}".format(np.mean(data_K['sI'][data_S['mask']]/data_K['I'][data_S['mask']]),np.mean(data_K['sQ'][data_S['mask']]/data_K['Q'][data_S['mask']]),np.mean(data_K['sU'][data_S['mask']]/data_K['U'][data_S['mask']]),np.mean(data_K['sP'][data_S['mask']]/data_K['P'][data_S['mask']])))
for d,i in zip(['I','Q','U','P','PA','sI','sQ','sU','sP','sPA'],[0,1,2,5,8,(3,0,0),(3,1,1),(3,2,2),6,9]):
data_K[d] = np.loadtxt(path_join(root_dir_K,d+'.txt'))
with fits.open(path_join(root_dir_data_S,'NGC1068_FOC_bin10px.fits')) as f:
with fits.open(path_join(root_dir_data_S,filename_S)) as f:
if not type(i) is int:
data_S[d] = np.sqrt(f[i[0]].data[i[1],i[2]])
else: