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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20
src/lib/plots.py
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@@ -129,6 +129,7 @@ def polarization_map(Stokes, SNRp_cut=3., SNRi_cut=30., step_vec=1,
stk_cov = Stokes[np.argmax([Stokes[i].header['datatype']=='IQU_cov_matrix' for i in range(len(Stokes))])]
pol = Stokes[np.argmax([Stokes[i].header['datatype']=='Pol_deg' for i in range(len(Stokes))])]
pol_err = Stokes[np.argmax([Stokes[i].header['datatype']=='Pol_deg_err' for i in range(len(Stokes))])]
#pol_err_Poisson = Stokes[np.argmax([Stokes[i].header['datatype']=='Pol_deg_err_Poisson_noise' for i in range(len(Stokes))])]
pang = Stokes[np.argmax([Stokes[i].header['datatype']=='Pol_ang' for i in range(len(Stokes))])]
pang_err = Stokes[np.argmax([Stokes[i].header['datatype']=='Pol_ang_err' for i in range(len(Stokes))])]
@@ -138,6 +139,7 @@ def polarization_map(Stokes, SNRp_cut=3., SNRi_cut=30., step_vec=1,
#Compute SNR and apply cuts
pol.data[pol.data == 0.] = np.nan
SNRp = pol.data/pol_err.data
#SNRp = pol.data/pol_err_Poisson.data
pol.data[SNRp < SNRp_cut] = np.nan
SNRi = stkI.data/np.sqrt(stk_cov.data[0,0])
pol.data[SNRi < SNRi_cut] = np.nan
@@ -163,6 +165,8 @@ def polarization_map(Stokes, SNRp_cut=3., SNRi_cut=30., step_vec=1,
vmin, vmax = 0., np.max(stkI.data[stkI.data > 0.])
im = ax.imshow(stkI.data,extent=[-stkI.data.shape[1]/2.,stkI.data.shape[1]/2.,-stkI.data.shape[0]/2.,stkI.data.shape[0]/2.], vmin=vmin, vmax=vmax, aspect='auto', cmap='inferno', alpha=1.)
cbar = plt.colorbar(im, cax=cbar_ax, label=r"$F_{\lambda}$ [$ergs \cdot cm^{-2} \cdot s^{-1} \cdot \AA^{-1}$]")
levelsI = np.linspace(SNRi_cut, np.max(SNRi[SNRi > 0.]), 10)
cont = ax.contour(SNRi, extent=[-SNRi.shape[1]/2.,SNRi.shape[1]/2.,-SNRi.shape[0]/2.,SNRi.shape[0]/2.], levels=levelsI, colors='grey', linewidths=0.5)
elif display.lower() in ['p','pol','pol_deg']:
# Display polarization degree map
vmin, vmax = 0., 100.
@@ -173,10 +177,26 @@ def polarization_map(Stokes, SNRp_cut=3., SNRi_cut=30., step_vec=1,
vmin, vmax = 0., 5.
im = ax.imshow(pol_err.data,extent=[-pol_err.data.shape[1]/2.,pol_err.data.shape[1]/2.,-pol_err.data.shape[0]/2.,pol_err.data.shape[0]/2.], vmin=vmin, vmax=vmax, aspect='auto', cmap='inferno', alpha=1.)
cbar = plt.colorbar(im, cax=cbar_ax, label=r"$\sigma_P$ [%]")
elif display.lower() in ['snr','snri']:
# Display I_stokes signal-to-noise map
vmin, vmax = 0., np.max(SNRi[SNRi > 0.])
im = ax.imshow(SNRi, extent=[-SNRi.shape[1]/2.,SNRi.shape[1]/2.,-SNRi.shape[0]/2.,SNRi.shape[0]/2.], vmin=vmin, vmax=vmax, aspect='auto', cmap='inferno', alpha=1.)
cbar = plt.colorbar(im, cax=cbar_ax, label=r"$I_{Stokes}/\sigma_{I}$")
levelsI = np.linspace(SNRi_cut, np.max(SNRi[SNRi > 0.]), 10)
cont = ax.contour(SNRi, extent=[-SNRi.shape[1]/2.,SNRi.shape[1]/2.,-SNRi.shape[0]/2.,SNRi.shape[0]/2.], levels=levelsI, colors='grey', linewidths=0.5)
elif display.lower() in ['snrp']:
# Display polarization degree signal-to-noise map
vmin, vmax = SNRp_cut, np.max(SNRp[SNRp > 0.])
im = ax.imshow(SNRp, extent=[-SNRp.shape[1]/2.,SNRp.shape[1]/2.,-SNRp.shape[0]/2.,SNRp.shape[0]/2.], vmin=vmin, vmax=vmax, aspect='auto', cmap='inferno', alpha=1.)
cbar = plt.colorbar(im, cax=cbar_ax, label=r"$P/\sigma_{P}$")
levelsP = np.linspace(SNRp_cut, np.max(SNRp[SNRp > 0.]), 10)
cont = ax.contour(SNRp, extent=[-SNRp.shape[1]/2.,SNRp.shape[1]/2.,-SNRp.shape[0]/2.,SNRp.shape[0]/2.], levels=levelsP, colors='grey', linewidths=0.5)
else:
# Defaults to intensity map
vmin, vmax = 0., np.max(stkI.data[stkI.data > 0.])
im = ax.imshow(stkI.data,extent=[-stkI.data.shape[1]/2.,stkI.data.shape[1]/2.,-stkI.data.shape[0]/2.,stkI.data.shape[0]/2.], vmin=vmin, vmax=vmax, aspect='auto', cmap='inferno', alpha=1.)
levelsI = np.linspace(SNRi_cut, SNRi.max(), 10)
cont = ax.contour(SNRi, extent=[-SNRi.shape[1]/2.,SNRi.shape[1]/2.,-SNRi.shape[0]/2.,SNRi.shape[0]/2.], levels=levelsI, colors='grey', linewidths=0.5)
cbar = plt.colorbar(im, cax=cbar_ax, label=r"$F_{\lambda}$ [$ergs \cdot cm^{-2} \cdot s^{-1} \cdot \AA$]")
px_size = wcs.wcs.get_cdelt()[0]