add energy scaling to PlotLocalEnergy

experiment/perforated-bilayer/PolarPlotLocalEnergy.py

@@ -9,7 +9,7 @@ import numpy as np
 import matplotlib.pyplot as plt
 import matplotlib.colors as colors
 import codecs
-
+import re
 
 
 def energy(kappa,alpha,Q,B)  :
@@ -49,7 +49,10 @@ def ReadEffectiveQuantities(QFilePath, BFilePath):
     return Q, B
 
 # Number of experiments / folders
-number=4
+number=7
+show_plot = False
+
+
 kappa=np.zeros(number)
 for n in range(0,number):
     #   Read from Date
@@ -58,21 +61,28 @@ for n in range(0,number):
     DataPath = './experiment/perforated-bilayer/results/'+str(n)
     QFilePath = DataPath + '/QMatrix.txt'
     BFilePath = DataPath + '/BMatrix.txt'
+    ParameterPath = DataPath + '/parameter.txt'
+
+    # Read Thickness from parameter file (needed for energy scaling)
+    with open(ParameterPath , 'r') as file:
+        parameterFile  = file.read()
+    thickness = float(re.findall(r'(?m)h = (\d?\d?\d?\.?\d+[Ee]?[+\-]?\d?\d?)',parameterFile)[0])
+
     Q, B = ReadEffectiveQuantities(QFilePath,BFilePath)
     # Q=0.5*(np.transpose(Q)+Q) # symmetrize
     B=np.transpose([B])
     # 
     
-    N=300
+    N=500
     length=12
     r, theta = np.meshgrid(np.linspace(0,length,N),np.radians(np.linspace(0, 360, N)))
     E=np.zeros(np.shape(r))
     for i in range(0,N): 
         for j in range(0,N):     
             if theta[i,j]<np.pi:
-                E[i,j]=energy(r[i,j],theta[i,j],Q,B)
+                E[i,j]=energy(r[i,j],theta[i,j],Q,B) * (thickness**2)
             else:
-                E[i,j]=energy(-r[i,j],theta[i,j],Q,B)
+                E[i,j]=energy(-r[i,j],theta[i,j],Q,B) * (thickness**2)
             
     # Compute Minimizer
     [imin,jmin]=np.unravel_index(E.argmin(),(N,N))
@@ -85,8 +95,16 @@ for n in range(0,number):
     ax.set_xticks([0,np.pi/2])
     ax.set_yticks([kappamin])
     colorbarticks=np.linspace(E.min(),E.max(),6)
-    plt.colorbar(pcm, extend='max', ticks=colorbarticks, pad=0.1)
-    plt.show()
+    cbar = plt.colorbar(pcm, extend='max', ticks=colorbarticks, pad=0.1)
+    cbar.ax.tick_params(labelsize=6)
+    if (show_plot):
+        plt.show()
+    # Save Figure as .pdf
+    width = 5.79 
+    height = width / 1.618 # The golden ratio.
+    fig.set_size_inches(width, height)
+    fig.savefig('Plot_PerforatedBilayer.pdf')
+
 
 f = open("./experiment/perforated-bilayer/results/kappa_simulation.txt", "w")
 f.write(str(kappa))         

experiment/perforated-bilayer/perfBilayer_test.py

@@ -107,8 +107,8 @@ def eval_energy(kappa,alpha,Q,B)  :
 # pythonPath = '/home/klaus/Desktop/Dune_release/dune-microstructure/experiment/wood-bilayer'
 path = os.getcwd() + '/experiment/perforated-bilayer/results/'
 pythonPath = os.getcwd() + '/experiment/perforated-bilayer'
-# pythonModule = "perforated_wood_upper"
-pythonModule = "perforated_wood_lower"
+pythonModule = "perforated_wood_upper"
+# pythonModule = "perforated_wood_lower"
 executable = os.getcwd() + '/build-cmake/src/Cell-Problem'
 # ---------------------------------
 # Setup Experiment
@@ -127,11 +127,12 @@ gamma = 1.0
 #Experiment: Perforate "active" bilayer phase 
 materialFunctionParameter=[
     [0.22, 0.0053,  17.17547062, 8.959564147, 0.0, 0.0 ],
+    [0.22, 0.0053,  17.17547062, 8.959564147, 0.0, 0.05 ],
     [0.22, 0.0053,  17.17547062, 8.959564147, 0.0, 0.1 ],
+    [0.22, 0.0053,  17.17547062, 8.959564147, 0.0, 0.15 ],
     [0.22, 0.0053,  17.17547062, 8.959564147, 0.0, 0.2 ],
+    [0.22, 0.0053,  17.17547062, 8.959564147, 0.0, 0.25 ],
     [0.22, 0.0053,  17.17547062, 8.959564147, 0.0, 0.3 ]
-    # [0.22, 0.0053,  17.17547062, 8.959564147, 0.0, 0.4 ],
-    # [0.22, 0.0053,  17.17547062, 8.959564147, 0.0, 0.5 ]
 ]
 
 # ------ Loops through Parameters for Material Function -----------

experiment/wood-bilayer/PolarPlotLocalEnergy.py

@@ -9,7 +9,7 @@ import numpy as np
 import matplotlib.pyplot as plt
 import matplotlib.colors as colors
 import codecs
-
+import re
 
 
 def energy(kappa,alpha,Q,B)  :
@@ -55,7 +55,8 @@ def ReadEffectiveQuantities(QFilePath, BFilePath):
 number=7
 show_plot = False
 
-dataset_numbers = [0, 1, 2, 3, 4, 5]
+# dataset_numbers = [0, 1, 2, 3, 4, 5]
+dataset_numbers = [0]
 
 for dataset_number in dataset_numbers:
 
@@ -66,6 +67,13 @@ for dataset_number in dataset_numbers:
         DataPath = './experiment/wood-bilayer/results_'+ str(dataset_number) + '/' +str(n)
         QFilePath = DataPath + '/QMatrix.txt'
         BFilePath = DataPath + '/BMatrix.txt'
+        ParameterPath = DataPath + '/parameter.txt'
+
+        # Read Thickness from parameter file (needed for energy scaling)
+        with open(ParameterPath , 'r') as file:
+            parameterFile  = file.read()
+        thickness = float(re.findall(r'(?m)h = (\d?\d?\d?\.?\d+[Ee]?[+\-]?\d?\d?)',parameterFile)[0])
+
         Q, B = ReadEffectiveQuantities(QFilePath,BFilePath)
         # Q=0.5*(np.transpose(Q)+Q) # symmetrize
         B=np.transpose([B])
@@ -78,9 +86,9 @@ for dataset_number in dataset_numbers:
         for i in range(0,N): 
             for j in range(0,N):     
                 if theta[i,j]<np.pi:
-                    E[i,j]=energy(r[i,j],theta[i,j],Q,B)
+                    E[i,j]=energy(r[i,j],theta[i,j],Q,B) * (thickness**2)
                 else:
-                    E[i,j]=energy(-r[i,j],theta[i,j],Q,B)
+                    E[i,j]=energy(-r[i,j],theta[i,j],Q,B) * (thickness**2)
                 
         # Compute Minimizer
         [imin,jmin]=np.unravel_index(E.argmin(),(N,N))
@@ -93,11 +101,12 @@ for dataset_number in dataset_numbers:
         ax.set_xticks([0,np.pi/2])
         ax.set_yticks([kappamin])
         colorbarticks=np.linspace(E.min(),E.max(),6)
-        plt.colorbar(pcm, extend='max', ticks=colorbarticks, pad=0.1)
+        cbar = plt.colorbar(pcm, extend='max', ticks=colorbarticks, pad=0.1)
+        cbar.ax.tick_params(labelsize=6)
         if (show_plot):
             plt.show()
         # Save Figure as .pdf
-        width = 5.79
+        width = 5.79 
         height = width / 1.618 # The golden ratio.
         fig.set_size_inches(width, height)
         fig.savefig('Plot_dataset_' +str(dataset_number) + '_exp' +str(n) + '.pdf')