Tibeuleu/FOC_Reduction
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small fixes and improvments

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This commit is contained in:
Thibault Barnouin
2024-10-17 17:05:35 +02:00
parent bd7cad46a1
commit f6d62bff73
8 changed files with 119 additions and 174 deletions
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134
package/FOC_reduction.py
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@@ -41,8 +41,8 @@ def main(target=None, proposal_id=None, infiles=None, output_dir="./data", crop=
# Background estimation
error_sub_type = "freedman-diaconis" # sqrt, sturges, rice, scott, freedman-diaconis (default) or shape (example (51, 51))
subtract_error = 0.5
display_bkg = False
subtract_error = 1.0
display_bkg = True
# Data binning
pxsize = 0.05
@@ -51,7 +51,7 @@ def main(target=None, proposal_id=None, infiles=None, output_dir="./data", crop=
# Alignement
align_center = "center" # If None will not align the images
display_align = False
display_align = True
display_data = False
# Transmittance correction
@@ -176,6 +176,7 @@ def main(target=None, proposal_id=None, infiles=None, output_dir="./data", crop=
proj_plots.plot_obs(
data_array,
headers,
shifts=shifts,
savename="_".join([figname, str(align_center)]),
plots_folder=plots_folder,
norm=LogNorm(vmin=data_array[data_array > 0.0].min() * headers[0]["photflam"], vmax=data_array[data_array > 0.0].max() * headers[0]["photflam"]),
@@ -305,114 +306,25 @@ def main(target=None, proposal_id=None, infiles=None, output_dir="./data", crop=
savename="_".join([figname]),
plots_folder=plots_folder,
)
proj_plots.polarization_map(
deepcopy(Stokes_hdul),
data_mask,
P_cut=P_cut,
SNRi_cut=SNRi_cut,
flux_lim=flux_lim,
step_vec=step_vec,
scale_vec=scale_vec,
savename="_".join([figname, "I"]),
plots_folder=plots_folder,
display="Intensity",
)
proj_plots.polarization_map(
deepcopy(Stokes_hdul),
data_mask,
P_cut=P_cut,
SNRi_cut=SNRi_cut,
flux_lim=flux_lim,
step_vec=step_vec,
scale_vec=scale_vec,
savename="_".join([figname, "P_flux"]),
plots_folder=plots_folder,
display="Pol_Flux",
)
proj_plots.polarization_map(
deepcopy(Stokes_hdul),
data_mask,
P_cut=P_cut,
SNRi_cut=SNRi_cut,
flux_lim=flux_lim,
step_vec=step_vec,
scale_vec=scale_vec,
savename="_".join([figname, "P"]),
plots_folder=plots_folder,
display="Pol_deg",
)
proj_plots.polarization_map(
deepcopy(Stokes_hdul),
data_mask,
P_cut=P_cut,
SNRi_cut=SNRi_cut,
flux_lim=flux_lim,
step_vec=step_vec,
scale_vec=scale_vec,
savename="_".join([figname, "PA"]),
plots_folder=plots_folder,
display="Pol_ang",
)
proj_plots.polarization_map(
deepcopy(Stokes_hdul),
data_mask,
P_cut=P_cut,
SNRi_cut=SNRi_cut,
flux_lim=flux_lim,
step_vec=step_vec,
scale_vec=scale_vec,
savename="_".join([figname, "I_err"]),
plots_folder=plots_folder,
display="I_err",
)
proj_plots.polarization_map(
deepcopy(Stokes_hdul),
data_mask,
P_cut=P_cut,
SNRi_cut=SNRi_cut,
flux_lim=flux_lim,
step_vec=step_vec,
scale_vec=scale_vec,
savename="_".join([figname, "P_err"]),
plots_folder=plots_folder,
display="Pol_deg_err",
)
proj_plots.polarization_map(
deepcopy(Stokes_hdul),
data_mask,
P_cut=P_cut,
SNRi_cut=SNRi_cut,
flux_lim=flux_lim,
step_vec=step_vec,
scale_vec=scale_vec,
savename="_".join([figname, "SNRi"]),
plots_folder=plots_folder,
display="SNRi",
)
proj_plots.polarization_map(
deepcopy(Stokes_hdul),
data_mask,
P_cut=P_cut if P_cut >= 1.0 else 3.0,
SNRi_cut=SNRi_cut,
flux_lim=flux_lim,
step_vec=step_vec,
scale_vec=scale_vec,
savename="_".join([figname, "SNRp"]),
plots_folder=plots_folder,
display="SNRp",
)
proj_plots.polarization_map(
deepcopy(Stokes_hdul),
data_mask,
P_cut=P_cut if P_cut < 1.0 else 0.99,
SNRi_cut=SNRi_cut,
flux_lim=flux_lim,
step_vec=step_vec,
scale_vec=scale_vec,
savename="_".join([figname, "confP"]),
plots_folder=plots_folder,
display="confp",
)
for figtype, figsuffix in zip(
["Intensity", "Pol_flux", "Pol_deg", "Pol_ang", "I_err", "P_err", "SNRi", "SNRp", "confp"],
["I", "P_flux", "P", "PA", "I_err", "P_err", "SNRi", "SNRp", "confP"],
):
try:
proj_plots.polarization_map(
deepcopy(Stokes_hdul),
data_mask,
P_cut=P_cut,
SNRi_cut=SNRi_cut,
flux_lim=flux_lim,
step_vec=step_vec,
scale_vec=scale_vec,
savename="_".join([figname, figsuffix]),
plots_folder=plots_folder,
display=figtype,
)
except ValueError:
pass
elif not interactive:
proj_plots.polarization_map(
deepcopy(Stokes_hdul), data_mask, P_cut=P_cut, SNRi_cut=SNRi_cut, savename=figname, plots_folder=plots_folder, display="integrate"