Tibeuleu/FOC_Reduction
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Add Stokes_cov_stat to fits and compute again P_debiased in plots

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Thibault Barnouin
2025-08-08 11:45:11 +02:00
parent e639695618
commit f4effac343
4 changed files with 223 additions and 142 deletions
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26
package/FOC_reduction.py
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@@ -41,7 +41,7 @@ def main(target=None, proposal_id=None, infiles=None, output_dir="./data", crop=
# Background estimation
error_sub_type = "scott" # sqrt, sturges, rice, scott, freedman-diaconis (default) or shape (example (51, 51))
subtract_error = 0.50
subtract_error = 0.80
display_bkg = False
# Data binning
@@ -203,24 +203,38 @@ def main(target=None, proposal_id=None, infiles=None, output_dir="./data", crop=
# FWHM of FOC have been estimated at about 0.03" across 1500-5000 Angstrom band, which is about 2 detector pixels wide
# see Jedrzejewski, R.; Nota, A.; Hack, W. J., A Comparison Between FOC and WFPC2
# Bibcode : 1995chst.conf...10J
Stokes, Stokes_cov, header_stokes, s_IQU_stat = proj_red.compute_Stokes(
Stokes, Stokes_cov, header_stokes, Stokes_cov_stat = proj_red.compute_Stokes(
data_array, error_array, data_mask, headers, FWHM=smoothing_FWHM, scale=smoothing_scale, smoothing=smoothing_function, transmitcorr=transmitcorr
)
# Step 3:
# Rotate images to have North up
if rotate_North:
Stokes, Stokes_cov, data_mask, header_stokes, s_IQU_stat = proj_red.rotate_Stokes(
Stokes, Stokes_cov, data_mask, header_stokes, s_IQU_stat=s_IQU_stat, SNRi_cut=None
Stokes, Stokes_cov, data_mask, header_stokes, Stokes_cov_stat = proj_red.rotate_Stokes(
Stokes, Stokes_cov, data_mask, header_stokes, Stokes_cov_stat=Stokes_cov_stat, SNRi_cut=None
)
# Compute polarimetric parameters (polarization degree and angle).
P, debiased_P, s_P, s_P_P, PA, s_PA, s_PA_P = proj_red.compute_pol(Stokes, Stokes_cov, header_stokes, s_IQU_stat=s_IQU_stat)
P, debiased_P, s_P, s_P_P, PA, s_PA, s_PA_P = proj_red.compute_pol(Stokes, Stokes_cov, header_stokes, Stokes_cov_stat=Stokes_cov_stat)
# Step 4:
# Save image to FITS.
figname = "_".join([figname, figtype]) if figtype != "" else figname
Stokes_hdul = proj_fits.save_Stokes(
Stokes, Stokes_cov, P, debiased_P, s_P, s_P_P, PA, s_PA, s_PA_P, header_stokes, data_mask, figname, data_folder=data_folder, return_hdul=True
Stokes,
Stokes_cov,
Stokes_cov_stat,
P,
debiased_P,
s_P,
s_P_P,
PA,
s_PA,
s_PA_P,
header_stokes,
data_mask,
figname,
data_folder=data_folder,
return_hdul=True,
)
outfiles.append("/".join([data_folder, Stokes_hdul[0].header["FILENAME"] + ".fits"]))