update python postplot

DiffractionGratings/grating2D.pro

@@ -443,7 +443,7 @@ PostOperation {
   { Name postop_energy; NameOfPostProcessing postpro_energy ;
     Operation {
       If (flag_Hparallel==1)
-        Print[ lambda_step, OnPoint{0,0,0}, Format Table, File StrCat[myDir, "temp_lambda_step.txt"], SendToServer "GetDP/Lambda_step" ] ;
+        Print[ lambda_step, OnPoint{0,0,0}, Format Table, File > StrCat[myDir, "temp_lambda_step.txt"], SendToServer "GetDP/Lambda_step" ] ;
         For i In {0:2*nb_orders}
           Print[ s_r~{i}[SurfCutSuper1], OnGlobal, Store i                , Format Table , File > StrCat[myDir, Sprintf("temp_s_r_%g.txt", i-nb_orders)]];
           Print[ s_t~{i}[SurfCutSubs1] , OnGlobal, Store (2*nb_orders+1+i), Format Table , File > StrCat[myDir, Sprintf("temp_s_t_%g.txt", i-nb_orders)]];

DiffractionGratings/grating2D_postplot.py

@@ -5,24 +5,14 @@ import subprocess
 import numpy as np
 import scipy as sc
 import matplotlib
-matplotlib.use('Agg')
 import pylab as pl
 pi=np.pi
-pl.rc('font', family='serif',size=20)
-pl.rc('legend',fontsize=20)
-# pl.rc('text', usetex=True)
-# pl.rc('figure', **{'autolayout': True})
-#### scaling the problem (*10^12)
-nm	     = 1.e3
-ep0 = 8.854187817e-3*nm
-mu0      = 400.*pi*nm
-cel      = 1.0/(np.sqrt(ep0 * mu0))
-####
+
 nb_orders  = int(int(subprocess.check_output("ls ./run_results/efficiency_r_* | grep -c efficiency_r_", shell=True))/2)
 nb_rods    = int(int(subprocess.check_output("ls ./run_results/absorption-Q_rod_* | grep -c absorption-Q_rod_", shell=True))-1)
 zerotol = 0.001
 if len(np.loadtxt('./run_results/efficiency_r_0.txt').shape)==2:
-    tab_lambdas = cel/nm/np.loadtxt('./run_results/efficiency_r_0.txt')[:,0]
+    tab_lambdas = np.loadtxt('./run_results/temp_lambda_step.txt')[:,8]
     nb_lambdas  = tab_lambdas.shape[0]
     R = np.zeros((nb_lambdas,2*nb_orders+1),dtype=complex)
     T = np.zeros((nb_lambdas,2*nb_orders+1),dtype=complex)
@@ -46,9 +36,9 @@ if len(np.loadtxt('./run_results/efficiency_r_0.txt').shape)==2:
 
     pl.savez('last_run_RTA.npz',R0=R0,T0=T0,A=A)
 
-    pl.figure(figsize=(12,8));ax = pl.subplot(111)
-    ax.plot(tab_lambdas,Rtot,'g',label='$R_{tot}$') #R_0
-    ax.plot(tab_lambdas,Ttot,'b',label='$T_{tot}$') #T_0
+    pl.figure();ax = pl.subplot(111)
+    ax.plot(tab_lambdas,Rtot,'g',label='$R_{tot}=\sum_k R_k$') #R_0
+    ax.plot(tab_lambdas,Ttot,'b',label='$T_{tot}=\sum_k T_k$') #T_0
     ax.plot(tab_lambdas, A  ,'r',label='$A$')
     ax.plot(tab_lambdas, Rtot+Ttot+A,'k',label='$R_{tot}+T_{tot}+A$')
     ax.set_ylim([-0.07,1.07])
@@ -56,10 +46,10 @@ if len(np.loadtxt('./run_results/efficiency_r_0.txt').shape)==2:
     ax.grid()
     box = ax.get_position()
     ax.set_position([box.x0, box.y0, box.width * 0.8, box.height])
-    ax.legend(loc='center left', bbox_to_anchor=(1, 0.5),fontsize=16)
+    ax.legend(loc='center left', bbox_to_anchor=(1, 0.5))
     pl.savefig('energy_balance_global.pdf')
 
-    pl.figure(figsize=(12,8));ax = pl.subplot(111)
+    pl.figure();ax = pl.subplot(111)
     absorption_list=[A_rod_out,A_layer_cov,A_layer_dep,A_sub]
     absorption_list_label=['$A_{rod_{out}}$','$A_{layer_{cov}}$','$A_{layer_{dep}}$','$A_{sub}$']
     count=0
@@ -93,7 +83,7 @@ if len(np.loadtxt('./run_results/efficiency_r_0.txt').shape)==2:
         if not np.all(np.isclose(tran.real,np.zeros_like(tran),atol=zerotol)):
             if(k==0):ax.plot(tab_lambdas,tran.real ,lw=3, c=next(color),label='$T_{%g}$'%(k))
             else:ax.plot(tab_lambdas,tran.real ,lw=1, c=next(color),label='$T_{%g}$'%(k))
-    pl.title('details : diffraction orders (>%.0fpercent for clarity)'%(zerotol*100.))
+    pl.title('details : diffraction orders (>%.0f%% for clarity)'%(zerotol*100.))
     ax.set_ylim([-0.07,1.07])
     ax.set_xlim([tab_lambdas.min(),tab_lambdas.max()])
     ax.grid()
@@ -103,7 +93,7 @@ if len(np.loadtxt('./run_results/efficiency_r_0.txt').shape)==2:
     pl.savefig('energy_balance_detailed.pdf')
     pl.show()
 elif len(np.loadtxt('./run_results/efficiency_r_0.txt').shape)==1:
-    lambdas=cel/nm/np.loadtxt('./run_results/efficiency_r_0.txt')[0]
+    lambdas=np.loadtxt('./run_results/efficiency_r_0.txt')[0]
     R = np.zeros(2*nb_orders+1,dtype=complex)
     T = np.zeros(2*nb_orders+1,dtype=complex)
     angle_r = np.zeros(2*nb_orders+1)