Tibeuleu/FOC_Reduction
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change background estimation to gaussian mean+factor*sigma

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Thibault Barnouin
2024-03-11 17:25:32 +01:00
parent 38604aa82d
commit 0d8e3a8c47
3 changed files with 14 additions and 19 deletions
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15
src/FOC_reduction.py
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@@ -33,13 +33,12 @@ 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 = 1.20
subtract_error = 1.00
display_bkg = False
display_error = False
# Data binning
rebin = True
pxsize = 0.10
pxsize = 0.05
px_scale = 'arcsec' # pixel, arcsec or full
rebin_operation = 'sum' # sum or average
@@ -50,7 +49,7 @@ def main(target=None, proposal_id=None, infiles=None, output_dir="./data", crop=
# Smoothing
smoothing_function = 'combine' # gaussian_after, weighted_gaussian_after, gaussian, weighted_gaussian or combine
smoothing_FWHM = 0.2 # If None, no smoothing is done
smoothing_FWHM = 0.10 # If None, no smoothing is done
smoothing_scale = 'arcsec' # pixel or arcsec
# Rotation
@@ -90,7 +89,7 @@ def main(target=None, proposal_id=None, infiles=None, output_dir="./data", crop=
plots_folder = "."
if not path_exists(plots_folder):
system("mkdir -p {0:s} ".format(plots_folder))
infiles = [p[1] for p in prod] # if p[1] not in ['x2rp0202t_c0f.fits', 'x2rp0302t_c0f.fits']]
infiles = [p[1] for p in prod]
data_array, headers = proj_fits.get_obs_data(infiles, data_folder=data_folder, compute_flux=True)
figname = "_".join([target, "FOC"])
@@ -117,13 +116,9 @@ def main(target=None, proposal_id=None, infiles=None, output_dir="./data", crop=
# Estimate error from data background, estimated from sub-image of desired sub_shape.
background = None
data_array, error_array, headers, background = proj_red.get_error(data_array, headers, error_array, sub_type=error_sub_type, subtract_error=subtract_error, display=display_error, savename="_".join([
data_array, error_array, headers, background = proj_red.get_error(data_array, headers, error_array, sub_type=error_sub_type, subtract_error=subtract_error, display=display_bkg, savename="_".join([
figname, "errors"]), plots_folder=plots_folder, return_background=True)
if display_bkg:
proj_plots.plot_obs(data_array, headers, vmin=data_array[data_array > 0.].min(
)*headers[0]['photflam'], vmax=data_array[data_array > 0.].max()*headers[0]['photflam'], savename="_".join([figname, "bkg"]), plots_folder=plots_folder)
# Align and rescale images with oversampling.
data_array, error_array, headers, data_mask = proj_red.align_data(
data_array, headers, error_array=error_array, background=background, upsample_factor=10, ref_center=align_center, return_shifts=False)