Tibeuleu/FOC_Reduction
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modifications to add raw image display

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Thibault Barnouin
2025-04-07 17:20:00 +02:00
parent 4b104d79d4
commit cebf4df8a4
4 changed files with 21 additions and 18 deletions
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10
package/FOC_reduction.py
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@@ -46,8 +46,8 @@ def main(target=None, proposal_id=None, infiles=None, output_dir="./data", crop=
display_bkg = False
# Data binning
pxsize = 4
pxscale = "px" # pixel, arcsec or full
pxsize = 0.10
pxscale = "arcsec" # pixel, arcsec or full
rebin_operation = "sum" # sum or average
# Alignement
@@ -60,8 +60,8 @@ 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 = 1.5 # If None, no smoothing is done
smoothing_scale = "px" # pixel or arcsec
smoothing_FWHM = 0.150 # If None, no smoothing is done
smoothing_scale = "arcsec" # pixel or arcsec
# Rotation
rotate_data = False
@@ -71,7 +71,7 @@ def main(target=None, proposal_id=None, infiles=None, output_dir="./data", crop=
P_cut = 3 # if >=1.0 cut on the signal-to-noise else cut on the confidence level in Q, U
SNRi_cut = 1.0 # I measurments with SNR>30, which implies an uncertainty in P of 4.7%.
flux_lim = None # lowest and highest flux displayed on plot, defaults to bkg and maximum in cut if None
scale_vec = 3
scale_vec = 5
step_vec = 1 # plot all vectors in the array. if step_vec = 2, then every other vector will be plotted if step_vec = 0 then all vectors are displayed at full length
# Pipeline start

2
package/__init__.py
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@@ -1,2 +1,2 @@
from .lib import *
from . import FOC_reduction
from .FOC_reduction import main

3
package/lib/background.py
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@@ -18,7 +18,6 @@ import matplotlib.dates as mdates
import matplotlib.pyplot as plt
import numpy as np
from astropy.time import Time
from lib.plots import plot_obs
from matplotlib.colors import LogNorm
from matplotlib.patches import Rectangle
from scipy.optimize import curve_fit
@@ -136,6 +135,8 @@ def display_bkg(data, background, std_bkg, headers, histograms=None, binning=Non
fig2.subplots_adjust(hspace=0, wspace=0, right=1.0)
fig2.colorbar(im2, ax=ax2, location="right", shrink=0.60, aspect=50, pad=0.025, label=r"Flux [$ergs \cdot cm^{-2} \cdot s^{-1} \cdot \AA^{-1}$]")
from .plots import plot_obs
if savename is not None:
this_savename = deepcopy(savename)
if savename[-4:] not in [".png", ".jpg", ".pdf"]:

24
package/lib/plots.py
View File

@@ -440,7 +440,7 @@ def polarization_map(
im = ax.imshow(
imflux, transform=ax.get_transform(WCS(Stokes[0].header).celestial), norm=LogNorm(vmin, vmax), aspect="equal", cmap=kwargs["cmap"], alpha=1.0
)
fig.colorbar(im, ax=ax, aspect=50, shrink=0.60, pad=0.025, label=r"$F_{\lambda}$ [$ergs \cdot cm^{-2} \cdot s^{-1} \cdot \AA$]")
fig.colorbar(im, ax=ax, aspect=50, shrink=0.60, pad=0.015, fraction=0.03, label=r"$F_{\lambda}$ [$ergs \cdot cm^{-2} \cdot s^{-1} \cdot \AA$]")
levelsF = np.array([0.8, 2.0, 5.0, 10.0, 20.0, 50.0]) / 100.0 * vmax
print("Flux density contour levels : ", levelsF)
ax.contour(flux, levels=levelsF, transform=ax.get_transform(WCS(Stokes[0].header).celestial), colors="grey", linewidths=0.5)
@@ -457,7 +457,7 @@ def polarization_map(
vmin, vmax = 1.0 / 2.0 * np.median(np.sqrt(stk_cov[0, 0][stkI > 0.0]) * convert_flux), np.max(stkI[stkI > 0.0] * convert_flux)
im = ax.imshow(stkI * convert_flux, norm=LogNorm(vmin, vmax), aspect="equal", cmap=kwargs["cmap"], alpha=1.0)
ax.plot(*WCS(Stokes[1]).wcs.crpix, "g+")
fig.colorbar(im, ax=ax, aspect=50, shrink=0.60, pad=0.025, label=r"$F_{\lambda}$ [$ergs \cdot cm^{-2} \cdot s^{-1} \cdot \AA^{-1}$]")
fig.colorbar(im, ax=ax, aspect=50, shrink=0.60, pad=0.015, fraction=0.03, label=r"$F_{\lambda}$ [$ergs \cdot cm^{-2} \cdot s^{-1} \cdot \AA^{-1}$]")
# levelsI = np.array([0.8, 2.0, 5.0, 10.0, 20.0, 50.0]) / 100.0 * vmax
# print("Stokes I contour levels : ", levelsI)
# ax.contour(stkI * convert_flux, levels=levelsI, colors="grey", linewidths=0.5)
@@ -476,7 +476,9 @@ def polarization_map(
vmin, vmax = 1.0 / 2.0 * np.median(np.sqrt(stk_cov[0, 0][stkI > 0.0]) * convert_flux), np.max(stkI[stkI > 0.0] * convert_flux)
pfmax = (stkI[stkI > 0.0] * pol[stkI > 0.0] * convert_flux).max()
im = ax.imshow(stkI * convert_flux * pol, norm=LogNorm(vmin, vmax), aspect="equal", cmap=kwargs["cmap"], alpha=1.0)
fig.colorbar(im, ax=ax, aspect=50, shrink=0.60, pad=0.025, label=r"$F_{\lambda} \cdot P$ [$ergs \cdot cm^{-2} \cdot s^{-1} \cdot \AA^{-1}$]")
fig.colorbar(
im, ax=ax, aspect=50, shrink=0.60, pad=0.015, fraction=0.03, label=r"$F_{\lambda} \cdot P$ [$ergs \cdot cm^{-2} \cdot s^{-1} \cdot \AA^{-1}$]"
)
# levelsPf = np.linspace(0.0.60, 0.50, 5) * pfmax
levelsPf = np.array([1.73, 13.0, 33.0, 66.0]) / 100.0 * pfmax
print("Polarized flux density contour levels : ", levelsPf)
@@ -486,13 +488,13 @@ def polarization_map(
display = "p"
vmin, vmax = 0.0, 100.0
im = ax.imshow(pol * 100.0, vmin=vmin, vmax=vmax, aspect="equal", cmap=kwargs["cmap"], alpha=1.0)
fig.colorbar(im, ax=ax, aspect=50, shrink=0.60, pad=0.025, label=r"$P$ [%]")
fig.colorbar(im, ax=ax, aspect=50, shrink=0.60, pad=0.015, fraction=0.03, label=r"$P$ [%]")
elif display.lower() in ["pa", "pang", "pol_ang"]:
# Display polarization degree map
display = "pa"
vmin, vmax = 0.0, 180.0
im = ax.imshow(princ_angle(pang), vmin=vmin, vmax=vmax, aspect="equal", cmap=kwargs["cmap"], alpha=1.0)
fig.colorbar(im, ax=ax, aspect=50, shrink=0.60, pad=0.025, label=r"$\theta_P$ [°]")
fig.colorbar(im, ax=ax, aspect=50, shrink=0.60, pad=0.015, fraction=0.03, label=r"$\theta_P$ [°]")
elif display.lower() in ["s_p", "pol_err", "pol_deg_err"]:
# Display polarization degree error map
display = "s_p"
@@ -502,7 +504,7 @@ def polarization_map(
else:
vmin, vmax = 0.0, 100.0
im = ax.imshow(pol_err * 100.0, vmin=vmin, vmax=vmax, aspect="equal", cmap="inferno_r", alpha=1.0)
fig.colorbar(im, ax=ax, aspect=50, shrink=0.60, pad=0.025, label=r"$\sigma_P$ [%]")
fig.colorbar(im, ax=ax, aspect=50, shrink=0.60, pad=0.015, fraction=0.03, label=r"$\sigma_P$ [%]")
elif display.lower() in ["s_i", "i_err"]:
# Display intensity error map
display = "s_i"
@@ -514,7 +516,7 @@ def polarization_map(
im = ax.imshow(np.sqrt(stk_cov[0, 0]) * convert_flux, norm=LogNorm(vmin, vmax), aspect="equal", cmap="inferno_r", alpha=1.0)
else:
im = ax.imshow(np.sqrt(stk_cov[0, 0]) * convert_flux, aspect="equal", cmap=kwargs["cmap"], alpha=1.0)
fig.colorbar(im, ax=ax, aspect=50, shrink=0.60, pad=0.025, label=r"$\sigma_I$ [$ergs \cdot cm^{-2} \cdot s^{-1} \cdot \AA^{-1}$]")
fig.colorbar(im, ax=ax, aspect=50, shrink=0.60, pad=0.015, fraction=0.03, label=r"$\sigma_I$ [$ergs \cdot cm^{-2} \cdot s^{-1} \cdot \AA^{-1}$]")
elif display.lower() in ["snri"]:
# Display I_stokes signal-to-noise map
display = "snri"
@@ -526,7 +528,7 @@ def polarization_map(
ax.contour(SNRi, levels=levelsSNRi, colors="grey", linewidths=0.5)
else:
im = ax.imshow(SNRi, aspect="equal", cmap=kwargs["cmap"], alpha=1.0)
fig.colorbar(im, ax=ax, aspect=50, shrink=0.60, pad=0.025, label=r"$I_{Stokes}/\sigma_{I}$")
fig.colorbar(im, ax=ax, aspect=50, shrink=0.60, pad=0.015, fraction=0.03, label=r"$I_{Stokes}/\sigma_{I}$")
elif display.lower() in ["snr", "snrp"]:
# Display polarization degree signal-to-noise map
display = "snrp"
@@ -538,7 +540,7 @@ def polarization_map(
ax.contour(SNRp, levels=levelsSNRp, colors="grey", linewidths=0.5)
else:
im = ax.imshow(SNRp, aspect="equal", cmap=kwargs["cmap"], alpha=1.0)
fig.colorbar(im, ax=ax, aspect=50, shrink=0.60, pad=0.025, label=r"$P/\sigma_{P}$")
fig.colorbar(im, ax=ax, aspect=50, shrink=0.60, pad=0.015, fraction=0.03, label=r"$P/\sigma_{P}$")
elif display.lower() in ["conf", "confp"]:
# Display polarization degree signal-to-noise map
display = "confp"
@@ -547,7 +549,7 @@ def polarization_map(
levelsconfp = np.array([0.500, 0.900, 0.990, 0.999])
print("confp contour levels : ", levelsconfp)
ax.contour(confP, levels=levelsconfp, colors="grey", linewidths=0.5)
fig.colorbar(im, ax=ax, aspect=50, shrink=0.60, pad=0.025, label=r"$Conf_{P}$")
fig.colorbar(im, ax=ax, aspect=50, shrink=0.60, pad=0.015, fraction=0.03, label=r"$Conf_{P}$")
else:
# Defaults to intensity map
if flux_lim is not None:
@@ -562,7 +564,7 @@ def polarization_map(
cmap=kwargs["cmap"],
alpha=1.0,
)
fig.colorbar(im, ax=ax, aspect=50, shrink=0.60, pad=0.025, label=r"$F_{\lambda}$ [$ergs \cdot cm^{-2} \cdot s^{-1} \cdot \AA$]")
fig.colorbar(im, ax=ax, aspect=50, shrink=0.60, pad=0.015, fraction=0.03, label=r"$F_{\lambda}$ [$ergs \cdot cm^{-2} \cdot s^{-1} \cdot \AA$]")
I_diluted, I_diluted_err = np.sum(flux[flux_mask]), np.sqrt(np.sum(flux_error[flux_mask] ** 2))
plt.rcParams.update({"font.size": 11})