Tibeuleu/FOC_Reduction
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Test reduction and error from ELR propositions

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This commit is contained in:
Thibault Barnouin
2021-06-03 16:19:55 +02:00
parent c1b0fead8a
commit 26fc1eb668
46 changed files with 1965 additions and 20 deletions
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28
src/FOC_reduction.py
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@@ -73,28 +73,28 @@ def main():
iterations = 10
# Error estimation
error_sub_shape = (75,75)
display_error = True
display_error = False
# Data binning
rebin = True
if rebin:
pxsize = 8
px_scale = 'px' #pixel or arcsec
pxsize = 0.1
px_scale = 'arcsec' #pixel or arcsec
rebin_operation = 'sum' #sum or average
# Alignement
align_center = 'image' #If None will align image to image center
display_data = True
display_data = False
# Smoothing
smoothing_function = 'gaussian' #gaussian or combine
smoothing_FWHM = 1 #If None, no smoothing is done
smoothing_scale = 'pixel' #pixel or arcsec
smoothing_function = 'combine' #gaussian or combine
smoothing_FWHM = 0.1 #If None, no smoothing is done
smoothing_scale = 'arcsec' #pixel or arcsec
# Rotation
rotate = False #rotation to North convention can give erroneous results
rotate_library = 'scipy' #scipy or pillow
# Polarization map output
figname = 'NGC1068_FOC' #target/intrument name
figtype = '_ELR_same_params' #additionnal informations
figtype = '_combine_FWHM010' #additionnal informations
SNRp_cut = 3 #P measurments with SNR>3
SNRi_cut = 4 #I measurments with SNR>30, which implies an uncertainty in P of 4.7%.
SNRi_cut = 30 #I measurments with SNR>30, which implies an uncertainty in P of 4.7%.
step_vec = 1 #plot all vectors in the array. if step_vec = 2, then every other vector will be plotted
##### Pipeline start
@@ -112,7 +112,7 @@ def main():
if rebin:
data_array, error_array, headers, Dxy = proj_red.rebin_array(data_array, error_array, headers, pxsize=pxsize, scale=px_scale, operation=rebin_operation)
#Align and rescale images with oversampling.
data_array, error_array = proj_red.align_data(data_array, error_array, upsample_factor=np.min(Dxy).astype(int), ref_center=align_center, return_shifts=False)
data_array, error_array = proj_red.align_data(data_array, error_array, upsample_factor=int(Dxy.min()), ref_center=align_center, return_shifts=False)
#Plot array for checking output
if display_data:
@@ -139,13 +139,15 @@ def main():
## Step 4:
# Save image to FITS.
Stokes_test = proj_fits.save_Stokes(I_stokes, Q_stokes, U_stokes, Stokes_cov, P, debiased_P, s_P, s_P_P, PA, s_PA, s_PA_P, headers[0], figname+figtype, data_folder=data_folder, return_hdul=True)
Stokes_test = proj_fits.save_Stokes(I_stokes, Q_stokes, U_stokes, Stokes_cov, P, debiased_P, s_P, s_P_P, PA, s_PA, s_PA_P, headers, figname+figtype, data_folder=data_folder, return_hdul=True)
## Step 5:
# Plot polarization map (Background is either total Flux, Polarization degree or Polarization degree error).
proj_plots.polarization_map(copy.deepcopy(Stokes_test), SNRp_cut=SNRp_cut, SNRi_cut=SNRi_cut, step_vec=step_vec, savename=figname+figtype, plots_folder=plots_folder, display=None)
proj_plots.polarization_map(copy.deepcopy(Stokes_test), SNRp_cut=SNRp_cut, SNRi_cut=SNRi_cut, step_vec=step_vec, savename=figname+figtype+"_P", plots_folder=plots_folder, display='Pol_deg')
proj_plots.polarization_map(copy.deepcopy(Stokes_test), SNRp_cut=SNRp_cut, SNRi_cut=SNRi_cut, step_vec=step_vec, savename=figname+figtype+"_P_err", plots_folder=plots_folder, display='Pol_deg_err')
#proj_plots.polarization_map(copy.deepcopy(Stokes_test), SNRp_cut=SNRp_cut, SNRi_cut=SNRi_cut, step_vec=step_vec, savename=figname+figtype+"_P", plots_folder=plots_folder, display='Pol_deg')
#proj_plots.polarization_map(copy.deepcopy(Stokes_test), SNRp_cut=SNRp_cut, SNRi_cut=SNRi_cut, step_vec=step_vec, savename=figname+figtype+"_P_err", plots_folder=plots_folder, display='Pol_deg_err')
proj_plots.polarization_map(copy.deepcopy(Stokes_test), SNRp_cut=SNRp_cut, SNRi_cut=SNRi_cut, step_vec=step_vec, savename=figname+figtype+"_SNRi", plots_folder=plots_folder, display='SNRi')
proj_plots.polarization_map(copy.deepcopy(Stokes_test), SNRp_cut=SNRp_cut, SNRi_cut=SNRi_cut, step_vec=step_vec, savename=figname+figtype+"_SNRp", plots_folder=plots_folder, display='SNRp')
return 0