diff --git a/src/lib/reduction.py b/src/lib/reduction.py
index 2c194b4..0e74d5a 100755
--- a/src/lib/reduction.py
+++ b/src/lib/reduction.py
@@ -308,8 +308,8 @@ def crop_array(data_array, headers, error_array=None, data_mask=None, step=5, nu
         fig.colorbar(im, ax=ax, label=r"Flux [$ergs \cdot cm^{-2} \cdot s^{-1} \cdot \AA^{-1}$]")
 
         if savename is not None:
-            fig.savefig("/".join([plots_folder, savename+'_'+filt+'_crop_region.png']),
-                        bbox_inches='tight')
+            fig.savefig("/".join([plots_folder, savename+'_'+filt+'_crop_region.pdf']),
+                        bbox_inches='tight', dpi=200)
             plot_obs(data_array, headers, vmin=convert_flux*data_array[data_array > 0.].mean()/5.,
                      vmax=convert_flux*data_array[data_array > 0.].max(), rectangle=[rectangle,]*len(headers),
                      savename=savename+'_crop_region', plots_folder=plots_folder)
@@ -1228,10 +1228,12 @@ def compute_Stokes(data_array, error_array, data_mask, headers, FWHM=None, scale
         QU_diluted_err = np.sqrt(np.sum(Stokes_cov[1, 2][mask]**2))
 
         P_diluted = np.sqrt(Q_diluted**2+U_diluted**2)/I_diluted
-        P_diluted_err = (1./I_diluted)*np.sqrt((Q_diluted**2*Q_diluted_err**2 + U_diluted**2*U_diluted_err**2 + 2.*Q_diluted*U_diluted*QU_diluted_err)/(Q_diluted**2 + U_diluted**2) + ((Q_diluted/I_diluted)**2 + (U_diluted/I_diluted)**2)*I_diluted_err**2 - 2.*(Q_diluted/I_diluted)*IQ_diluted_err - 2.*(U_diluted/I_diluted)*IU_diluted_err)
+        P_diluted_err = (1./I_diluted)*np.sqrt((Q_diluted**2*Q_diluted_err**2 + U_diluted**2*U_diluted_err**2 + 2.*Q_diluted*U_diluted*QU_diluted_err)/(Q_diluted**2 + U_diluted **
+                                                                                                                                                        2) + ((Q_diluted/I_diluted)**2 + (U_diluted/I_diluted)**2)*I_diluted_err**2 - 2.*(Q_diluted/I_diluted)*IQ_diluted_err - 2.*(U_diluted/I_diluted)*IU_diluted_err)
 
         PA_diluted = princ_angle((90./np.pi)*np.arctan2(U_diluted, Q_diluted))
-        PA_diluted_err = (90./(np.pi*(Q_diluted**2 + U_diluted**2)))*np.sqrt(U_diluted**2*Q_diluted_err**2 + Q_diluted**2*U_diluted_err**2 - 2.*Q_diluted*U_diluted*QU_diluted_err)
+        PA_diluted_err = (90./(np.pi*(Q_diluted**2 + U_diluted**2)))*np.sqrt(U_diluted**2*Q_diluted_err **
+                                                                             2 + Q_diluted**2*U_diluted_err**2 - 2.*Q_diluted*U_diluted*QU_diluted_err)
 
         for header in headers:
             header['P_int'] = (P_diluted, 'Integrated polarisation degree')
@@ -1487,10 +1489,12 @@ def rotate_Stokes(I_stokes, Q_stokes, U_stokes, Stokes_cov, data_mask, headers,
     QU_diluted_err = np.sqrt(np.sum(new_Stokes_cov[1, 2][mask]**2))
 
     P_diluted = np.sqrt(Q_diluted**2+U_diluted**2)/I_diluted
-    P_diluted_err = (1./I_diluted)*np.sqrt((Q_diluted**2*Q_diluted_err**2 + U_diluted**2*U_diluted_err**2 + 2.*Q_diluted*U_diluted*QU_diluted_err)/(Q_diluted**2 + U_diluted**2) + ((Q_diluted/I_diluted)**2 + (U_diluted/I_diluted)**2)*I_diluted_err**2 - 2.*(Q_diluted/I_diluted)*IQ_diluted_err - 2.*(U_diluted/I_diluted)*IU_diluted_err)
+    P_diluted_err = (1./I_diluted)*np.sqrt((Q_diluted**2*Q_diluted_err**2 + U_diluted**2*U_diluted_err**2 + 2.*Q_diluted*U_diluted*QU_diluted_err)/(Q_diluted**2 + U_diluted **
+                                                                                                                                                    2) + ((Q_diluted/I_diluted)**2 + (U_diluted/I_diluted)**2)*I_diluted_err**2 - 2.*(Q_diluted/I_diluted)*IQ_diluted_err - 2.*(U_diluted/I_diluted)*IU_diluted_err)
 
     PA_diluted = princ_angle((90./np.pi)*np.arctan2(U_diluted, Q_diluted))
-    PA_diluted_err = (90./(np.pi*(Q_diluted**2 + U_diluted**2)))*np.sqrt(U_diluted**2*Q_diluted_err**2 + Q_diluted**2*U_diluted_err**2 - 2.*Q_diluted*U_diluted*QU_diluted_err)
+    PA_diluted_err = (90./(np.pi*(Q_diluted**2 + U_diluted**2)))*np.sqrt(U_diluted**2*Q_diluted_err **
+                                                                         2 + Q_diluted**2*U_diluted_err**2 - 2.*Q_diluted*U_diluted*QU_diluted_err)
 
     for header in new_headers:
         header['P_int'] = (P_diluted, 'Integrated polarisation degree')
diff --git a/src/overplot_MRK463E.py b/src/overplot_MRK463E.py
index e2070df..79de0ca 100755
--- a/src/overplot_MRK463E.py
+++ b/src/overplot_MRK463E.py
@@ -6,7 +6,7 @@ from matplotlib.colors import LogNorm
 
 Stokes_UV = fits.open("./data/MRK463E/5960/MRK463E_FOC_b0.05arcsec_c0.10arcsec.fits")
 Stokes_IR = fits.open("./data/MRK463E/WFPC2/IR_rot_crop.fits")
-Stokes_Xr = fits.open("./data/MRK463E/Chandra/4913/primary/acisf04913N004_cntr_img2.fits")
+Stokes_Xr = fits.open("./data/MRK463E/Chandra/X_ray_crop.fits")
 
 levels = np.geomspace(1., 99., 7)
 
@@ -14,12 +14,13 @@ levels = np.geomspace(1., 99., 7)
 # A.plot(levels=levels, SNRp_cut=3.0, SNRi_cut=20.0, zoom=1, savename='./plots/MRK463E/Chandra_overplot.pdf')
 
 B = overplot_chandra(Stokes_UV, Stokes_Xr, norm=LogNorm())
-B.plot(levels=levels, SNRp_cut=3.0, SNRi_cut=30.0, vec_scale=3, zoom=1, savename='./plots/MRK463E/Chandra_overplot_forced.pdf')
+B.plot(levels=levels, SNRp_cut=3.0, SNRi_cut=3.0, vec_scale=5, zoom=1, savename='./plots/MRK463E/Chandra_overplot_forced.pdf')
 B.write_to(path1="./data/MRK463E/FOC_data_Chandra.fits", path2="./data/MRK463E/Chandra_data.fits", suffix="aligned")
 
 # C = overplot_pol(Stokes_UV, Stokes_IR)
 # C.plot(SNRp_cut=3.0, SNRi_cut=20.0, savename='./plots/MRK463E/IR_overplot.pdf')
 
+levels = np.array([0.8, 2, 5, 10, 20, 50])/100.*Stokes_UV[0].header['photflam']
 D = overplot_pol(Stokes_UV, Stokes_IR, norm=LogNorm())
-D.plot(SNRp_cut=3.0, SNRi_cut=30.0, vec_scale=3, norm=LogNorm(1e-18, 1e-15), savename='./plots/MRK463E/IR_overplot_forced.pdf')
+D.plot(levels=levels, SNRp_cut=3.0, SNRi_cut=3.0, vec_scale=5, norm=LogNorm(8.5e-18, 2.5e-15), savename='./plots/MRK463E/IR_overplot_forced.pdf')
 D.write_to(path1="./data/MRK463E/FOC_data_WFPC.fits", path2="./data/MRK463E/WFPC_data.fits", suffix="aligned")