M matrix plots

DiffractionGratings/grating3D_postplot_Mmatrix.py

 import numpy as np
 import matplotlib.pyplot as plt
 import matplotlib as mpl
+plt.rcParams.update({"text.usetex": True})
 
 def add_colorbar(mappable):
     from mpl_toolkits.axes_grid1 import make_axes_locatable
@@ -22,9 +23,10 @@ def load_getdp_integral(fname):
         return temp[:,1]+1j*temp[:,2]
 
 nb_lam = 100
-nb_phi = 50
+nb_phi = 51
 FLAG_TOT = 0
-respath  = 'res_Matrix_nb_phi50_total%g/'%(FLAG_TOT)
+# respath  = 'res_Matrix_nb_phi50_total%g/'%(FLAG_TOT)
+respath  = 'res_Matrix_nb_phi50_total0_bermu1/'
 rpp = np.zeros((nb_lam,nb_phi),dtype=complex)
 rps = np.zeros((nb_lam,nb_phi),dtype=complex)
 rsp = np.zeros((nb_lam,nb_phi),dtype=complex)
@@ -55,7 +57,8 @@ M = np.zeros((4,4,len(tab_lam),len(tab_phi)),dtype=complex)
 # rps : send Es_inc (s-in), project the reflected field along p (p-out)
 
 for i in range(nb_lam):
-    for j in range(nb_phi):
+    for j in range(nb_phi-1):
+        print(i,j)
         rpp[i,j] = load_getdp_integral(respath+'r_pin_pout_lam%g_phi%g.out'%(i,j))
         rss[i,j] = load_getdp_integral(respath+'r_sin_sout_lam%g_phi%g.out'%(i,j))
         rps[i,j] = load_getdp_integral(respath+'r_sin_pout_lam%g_phi%g.out'%(i,j))
@@ -71,6 +74,12 @@ for i in range(nb_lam):
         effr2_sin[:,i,j] = load_getdp_integral(respath+'eff_r2_lam%g_phi%g_psi1.out'%(i,j))
         Qscat_sin[i,j]   = np.real(load_getdp_integral(respath+'Q_scat_lam%g_phi%g_psi1.out'%(i,j)))
 
+## replicate data for phi=2\pi from phi=0 
+rpp[:,-1] = rpp[:,0]
+rss[:,-1] = rss[:,0]
+rps[:,-1] = rps[:,0]
+rsp[:,-1] = rsp[:,0]
+
 T1_sin = np.sum(efft1_sin,axis=0)
 T2_sin = np.sum(efft2_sin,axis=0)
 R1_sin = np.sum(effr1_sin,axis=0)
@@ -101,8 +110,6 @@ M[4-1,2-1,:,:] =-np.imag(rpp*np.conj(rsp)-rps*np.conj(rss))
 M[4-1,3-1,:,:] =-np.imag(rpp*np.conj(rss)+rps*np.conj(rsp))
 M[4-1,4-1,:,:] = np.real(rpp*np.conj(rss)-rps*np.conj(rsp))
 
-
-
 # ### Energy balance
 # fig, axes = plt.subplots(2, 2, figsize=(12,12))
 # L,P = np.meshgrid(tab_lam,tab_phi,indexing='ij')
@@ -126,7 +133,7 @@ M[4-1,4-1,:,:] = np.real(rpp*np.conj(rss)-rps*np.conj(rsp))
 
 fig, axes = plt.subplots(4, 4, subplot_kw=dict(projection='polar') ,figsize=(12,12))
 flag_lam = True
-rlabel =  r"$\lambda$ (nm)"
+rlabel =  r"$\lambda_0$ (nm)"
 which_r =  tab_lam
 which_orig = 0  if not flag_lam else 350
 for i in range(4):
@@ -137,18 +144,20 @@ for i in range(4):
             ax.text(0. , 1. , r"$M_{%d%d}$"%(i+1,j+1) , fontsize=16 , transform=ax.transAxes)
             ax.set_xticks([])
             ax.set_yticks([])
-            plt.colorbar(sm, ax=ax)
+            cbar = plt.colorbar(sm, ax=ax, fraction=0.046, pad=0.04)
+            cbar.ax.locator_params(nbins=5)
         else:
             p00 = ax.contourf(tab_phi*np.pi/180,which_r,M[i,j]/M[0,0]-1,cmap=plt.cm.bwr,vmin=-1,vmax=1)
             label_position=ax.get_rlabel_position()
             ax.text(np.radians(label_position+30),ax.get_rmax()/1.3,rlabel,
                     rotation=label_position,ha='center',va='center',fontsize=16)
-            ax.text(np.radians(-15),tab_lam.max()*1.01,r"$\varphi$",fontsize=16)
+            ax.text(np.radians(-15),tab_lam.max()*1.01,r"$\varphi_0$",fontsize=16)
             norm = mpl.colors.Normalize(vmin=-1,vmax=1)
             sm = mpl.cm.ScalarMappable(cmap=plt.cm.bwr, norm=norm)
             sm.set_array([])
         ax.set_rorigin(which_orig)
 plt.subplots_adjust(top=0.92, bottom=0.08, left=0.10, right=0.95, hspace=0.25,wspace=0.35)
 plt.savefig('Mmatrix.jpg')
+plt.savefig('Mmatrix.pdf', bbox_inches='tight', pad_inches=0)
 plt.show()