Tibeuleu/FOC_Reduction
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allow to play with background estimation

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Tibeuleu
2023-02-10 17:01:25 +01:00
parent 22758be11a
commit 001759556d
6 changed files with 57 additions and 35 deletions
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7
src/comparison_Kishimoto.py
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@@ -15,7 +15,7 @@ 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"
filename_S = "NGC1068_FOC_b_10px.fits"
data_K = {}
data_S = {}
@@ -31,13 +31,16 @@ for d,i in zip(['I','Q','U','P','PA','sI','sQ','sU','sP','sPA'],[0,1,2,5,8,(3,0,
wcs = WCS(header)
convert_flux = header['photflam']
bkg_S = np.median(data_S['I'])/3
bkg_K = np.median(data_K['I'])/3
#zeropad data to get same size of array
shape = data_S['I'].shape
for d in data_K:
data_K[d] = zeropad(data_K[d],shape)
#shift array to get same information in same pixel
data_arr, error_ar, heads, data_msk, shifts, shifts_err = align_data(np.array([data_S['I'],data_K['I']]), [header, header], upsample_factor=10., return_shifts=True)
data_arr, error_ar, heads, data_msk, shifts, shifts_err = align_data(np.array([data_S['I'],data_K['I']]), [header, header], error_array=np.array([data_S['sI'],data_K['sI']]), background=np.array([bkg_S,bkg_K]), upsample_factor=10., return_shifts=True)
for d in data_K:
data_K[d] = shift(data_K[d],shifts[1],order=1,cval=0.)