Tibeuleu/FOC_Reduction
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allow to play with background estimation

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Tibeuleu
2023-02-10 17:01:25 +01:00
parent 22758be11a
commit 001759556d
6 changed files with 57 additions and 35 deletions
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10
src/lib/plots.py
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@@ -316,7 +316,7 @@ def polarization_map(Stokes, data_mask=None, rectangle=None, SNRp_cut=3., SNRi_c
if display.lower() in ['intensity']:
# If no display selected, show intensity map
display='i'
vmin, vmax = 1/10*np.median(stkI.data[stkI.data > 0.]*convert_flux), np.max(stkI.data[stkI.data > 0.]*convert_flux)
vmin, vmax = 3.*np.mean(np.sqrt(stk_cov.data[0,0][mask])*convert_flux), np.max(stkI.data[stkI.data > 0.]*convert_flux)
im = ax.imshow(stkI.data*convert_flux, norm=LogNorm(vmin,vmax), aspect='equal', 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(vmax*0.01, vmax*0.99, 10)
@@ -327,7 +327,7 @@ def polarization_map(Stokes, data_mask=None, rectangle=None, SNRp_cut=3., SNRi_c
# Display polarisation flux
display='pf'
pf_mask = (stkI.data > 0.) * (pol.data > 0.)
vmin, vmax = 1/10*np.median(stkI.data[stkI.data > 0.]*convert_flux), np.max(stkI.data[stkI.data > 0.]*convert_flux)
vmin, vmax = 3.*np.mean(np.sqrt(stk_cov.data[0,0][mask])*convert_flux), np.max(stkI.data[stkI.data > 0.]*convert_flux)
im = ax.imshow(stkI.data*convert_flux*pol.data, norm=LogNorm(vmin,vmax), aspect='equal', cmap='inferno', alpha=1.)
cbar = plt.colorbar(im, cax=cbar_ax, label=r"$F_{\lambda} \cdot P$ [$ergs \cdot cm^{-2} \cdot s^{-1} \cdot \AA^{-1}$]")
levelsPf = np.linspace(vmax*0.01, vmax*0.99, 10)
@@ -382,7 +382,7 @@ def polarization_map(Stokes, data_mask=None, rectangle=None, SNRp_cut=3., SNRi_c
#ax.clabel(cont,inline=True,fontsize=6)
else:
# Defaults to intensity map
vmin, vmax = 1/10*np.median(stkI.data[stkI.data > 0.]*convert_flux), np.max(stkI.data[stkI.data > 0.]*convert_flux)
vmin, vmax = 3.*np.mean(np.sqrt(stk_cov.data[0,0][mask])*convert_flux), np.max(stkI.data[stkI.data > 0.]*convert_flux)
#im = ax.imshow(stkI.data*convert_flux, vmin=vmin, vmax=vmax, aspect='equal', cmap='inferno', alpha=1.)
#cbar = plt.colorbar(im, cax=cbar_ax, label=r"$F_{\lambda}$ [$ergs \cdot cm^{-2} \cdot s^{-1} \cdot \AA$]")
im = ax.imshow(stkI.data*convert_flux, norm=LogNorm(vmin,vmax), aspect='equal', cmap='inferno', alpha=1.)
@@ -1745,12 +1745,12 @@ class pol_map(object):
self.display_selection = "total_flux"
if self.display_selection.lower() in ['total_flux']:
self.data = self.I*self.convert_flux
vmin, vmax = 1/10.*np.median(self.data[self.data > 0.]), np.max(self.data[self.data > 0.])
vmin, vmax = 1/2.0*np.median(self.data[self.data > 0.]), np.max(self.data[self.data > 0.])
norm = LogNorm(vmin, vmax)
label = r"$F_{\lambda}$ [$ergs \cdot cm^{-2} \cdot s^{-1} \cdot \AA^{-1}$]"
elif self.display_selection.lower() in ['pol_flux']:
self.data = self.I*self.convert_flux*self.P
vmin, vmax = 1/10.*np.median(self.I[self.I > 0.]*self.convert_flux), np.max(self.I[self.I > 0.]*self.convert_flux)
vmin, vmax = 1/2.0*np.median(self.I[self.I > 0.]*self.convert_flux), np.max(self.I[self.I > 0.]*self.convert_flux)
norm = LogNorm(vmin, vmax)
label = r"$F_{\lambda} \cdot P$ [$ergs \cdot cm^{-2} \cdot s^{-1} \cdot \AA^{-1}$]"
elif self.display_selection.lower() in ['pol_deg']: