Update & Add Prestrain Plot Methods in python

src/Plot_Angle_Lemma1.4.py

@@ -165,7 +165,7 @@ lambda1 = 0.0
 gamma = 1.0/4.0
 
 gamma = 'infinity'  #Elliptic Setting
-gamma = '0'       #Hyperbolic Setting
+# gamma = '0'       #Hyperbolic Setting
 # gamma = 0.5
 
 

src/Plot_CurvatureLemma1.4.py

@@ -14,6 +14,11 @@ import matplotlib.ticker as ticker
 # from subprocess import Popen, PIPE
 #import sys
 
+import matplotlib.ticker as tickers
+import matplotlib as mpl
+from matplotlib.ticker import MultipleLocator,FormatStrFormatter,MaxNLocator
+import pandas as pd
+
 ###################### makePlot.py #########################
 #  Generalized Plot-Script giving the option to define
 #  quantity of interest and the parameter it depends on
@@ -165,7 +170,7 @@ xmax = 0.4
 
 
 
-numPoints = 100
+numPoints = 200
 X_Values = np.linspace(xmin, xmax, num=numPoints)
 print(X_Values)
 
@@ -297,77 +302,90 @@ print('y_rest:', y_rest)
 print('np.nonzero(X_Values>x_plotValues[1]', np.nonzero(X_Values>x_plotValues[1]) )
 
 
-# ---------------- Create Plot -------------------
-plt.figure()
-
-f,ax=plt.subplots(1)
-
-# plt.title(r''+ yName + '-Plot')
-# plt.plot(X_Values, Y_Values,linewidth=2, '.k')
-# plt.plot(X_Values, Y_Values,'.k',markersize=1)
-# plt.plot(X_Values, Y_Values,'.',markersize=0.8)
-
-# plt.plot(X_Values, Y_Values)
-
-# ax.plot([[0],X_Values[-1]], [Y_Values[0],Y_Values[-1]])
-# ax.plot([x_plotValues[0],x_plotValues[1]], [y_plotValues[0],y_plotValues[1]] , 'b')
-# ax.plot(x_rest, y_rest, 'b')
-
-
-
-# ax.plot(X_Values, Y_Values)
-# ax.scatter(X_Values, Y_Values)
-# plt.plot(x_plotValues, y_plotValues,'.')
-# plt.scatter(X_Values, Y_Values, alpha=0.3)
-# plt.scatter(X_Values, Y_Values)
-# plt.plot(X_Values, Y_Values,'.')
-
-
-# plt.plot([X_Values[0],X_Values[-1]], [Y_Values[0],Y_Values[-1]])
-# plt.axis([0, 6, 0, 20])
+# --- Convert to numpy array
+Y_Values = np.array(Y_Values)
+X_Values = np.array(X_Values)
 
-ax.plot(X_Values[X_Values>jump_xValues[0]], Y_Values[X_Values>jump_xValues[0]] ,'b')
-ax.plot(X_Values[X_Values<jump_xValues[0]], Y_Values[X_Values<jump_xValues[0]], 'b')
 
-plt.xlabel(xName)
+# ---------------- Create Plot -------------------
+mpl.rcParams['text.usetex'] = True
+mpl.rcParams["font.family"] = "serif"
+mpl.rcParams["font.size"] = "9"
+# width as measured in inkscape
+width = 6.28 *0.5
+height = width / 1.618
+fig = plt.figure()
+ax = plt.axes((0.15,0.18,0.8,0.8))
+ax.tick_params(axis='x',which='major', direction='out',pad=3)
+ax.tick_params(axis='y',which='major', length=3, width=1, direction='out',pad=3)
+ax.xaxis.set_major_locator(MultipleLocator(0.05))
+ax.xaxis.set_minor_locator(MultipleLocator(0.025))
+ax.grid(True,which='major',axis='both',alpha=0.3)
+# plt.figure()
+# f,ax=plt.subplots(1)
+
+
+ax.set_xlabel(r"volume fraction $\theta$")
+ax.set_ylabel(r"curvature $\kappa$")
+# plt.xlabel(xName)
 # plt.ylabel(yName)
-
-plt.ylabel('$\kappa$')
-
-# ax.yaxis.set_major_formatter(ticker.FormatStrFormatter('%g $\pi$'))
-# ax.yaxis.set_major_locator(ticker.MultipleLocator(base=0.1))
-
-
-
-
-ax.grid(True)
-
-# # if angle PLOT :
-# ax.yaxis.set_major_locator(plt.MultipleLocator(np.pi / 2))
-# ax.yaxis.set_minor_locator(plt.MultipleLocator(np.pi / 12))
-#
-# ax.yaxis.set_major_formatter(plt.FuncFormatter(format_func))
-#
-# # Plot every other line.. not the jumps...
-# tmp = 1
-# for idx, x in enumerate(x_plotValues):
-#     if idx > 0 and tmp == 1:
-#         # plt.plot([x_plotValues[idx-1],x_plotValues[idx]] ,[y_plotValues[idx-1],y_plotValues[idx]] )
-#         ax.plot([x_plotValues[idx-1],x_plotValues[idx]] ,[y_plotValues[idx-1],y_plotValues[idx]] ,'b')
-#         tmp = 0
-#     else:
-#         tmp = 1
-
-# plt.plot([x_plotValues[0],x_plotValues[1]] ,[y_plotValues[0],y_plotValues[1]] )
-# plt.plot([x_plotValues[2],x_plotValues[3]] ,[y_plotValues[2],y_plotValues[3]] )
-# plt.plot([x_plotValues[4],x_plotValues[5]] ,[y_plotValues[4],y_plotValues[5]] )
-# plt.plot([x_plotValues[6],x_plotValues[7]] ,[y_plotValues[6],y_plotValues[7]] )
-
-
-for x in jump_xValues:
-    plt.axvline(x,ymin=0, ymax= 1, color = 'g',alpha=0.5, linestyle = 'dashed')
-
-# plt.axvline(x_plotValues[1],ymin=0, ymax= 1, color = 'g',alpha=0.5, linestyle = 'dashed')
+# plt.ylabel('$\kappa$')
+# ax.grid(True)
+
+# Add transition Points
+if gamma == '0':
+    transition_point1 =  0.13663316582914573
+    transition_point2 =  0.20899497487437185
+    plt.axvline(transition_point1,ymin=0, ymax= 1, color = 'orange',alpha=0.5, linestyle = 'dashed', linewidth=1)
+    plt.axvline(transition_point2,ymin=0, ymax= 1, color = 'orange',alpha=0.5, linestyle = 'dashed', linewidth=1)
+
+    ax.plot(X_Values[X_Values<jump_xValues[0]], Y_Values[X_Values<jump_xValues[0]], 'royalblue')
+    ax.plot(X_Values[np.where(np.logical_and(X_Values>jump_xValues[0], X_Values<jump_xValues[1])) ], Y_Values[np.where(np.logical_and(X_Values>jump_xValues[0] ,X_Values<jump_xValues[1] ))] ,'royalblue')
+    ax.plot(X_Values[X_Values>jump_xValues[1]], Y_Values[X_Values>jump_xValues[1]], 'royalblue')
+    # ax.plot(x_plotValues,y_plotValues, 'royalblue')
+    ax.scatter([transition_point1, transition_point2],[jump_yValues[0], jump_yValues[1]],s=6, marker='o', cmap=None, norm=None, facecolor = 'black',
+                              edgecolor = 'black', vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+
+    ax.text(transition_point1-0.02 , jump_yValues[0]-0.02, r"$4$", size=6, bbox=dict(boxstyle="circle",facecolor='white', alpha=1.0, pad=0.1, linewidth=0.5)
+                       )
+
+    ax.text(transition_point2+0.012 , jump_yValues[1]+0.02, r"$5$", size=6, bbox=dict(boxstyle="circle",facecolor='white', alpha=1.0, pad=0.1, linewidth=0.5)
+                   )
+
+if gamma == 'infinity':
+    transition_point1 = 0.13663316582914573
+    transition_point2 = 0.1929145728643216
+    transition_point3 = 0.24115577889447234
+    plt.axvline(transition_point1,ymin=0, ymax= 1, color = 'orange',alpha=0.5, linestyle = 'dashed', linewidth=1)
+    plt.axvline(transition_point2,ymin=0, ymax= 1, color = 'orange',alpha=0.5, linestyle = 'dashed', linewidth=1)
+    plt.axvline(transition_point3,ymin=0, ymax= 1, color = 'orange',alpha=0.5, linestyle = 'dashed', linewidth=1)
+    ax.plot(X_Values[X_Values<jump_xValues[0]], Y_Values[X_Values<jump_xValues[0]], 'royalblue')
+    ax.plot(X_Values[X_Values>jump_xValues[0]], Y_Values[X_Values>jump_xValues[0]], 'royalblue')
+
+    idx1 = find_nearestIdx(X_Values, transition_point1)
+    idx2 = find_nearestIdx(X_Values, transition_point2)
+    print('idx1', idx1)
+    print('idx2', idx2)
+    Y_TP1 = Y_Values[idx1]
+    Y_TP2 = Y_Values[idx2]
+    print('Y_TP1', Y_TP1)
+    print('Y_TP2', Y_TP2)
+
+
+    ax.scatter([transition_point1, transition_point2],[Y_TP1, Y_TP2],s=6, marker='o', cmap=None, norm=None, facecolor = 'black',
+                              edgecolor = 'black', vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+
+    ax.text(transition_point1-0.02 , Y_TP1-0.02, r"$6$", size=6, bbox=dict(boxstyle="circle",facecolor='white', alpha=1.0, pad=0.1, linewidth=0.5)
+                       )
+
+    ax.text(transition_point2+0.015 , Y_TP2+0.020, r"$7$", size=6, bbox=dict(boxstyle="circle",facecolor='white', alpha=1.0, pad=0.1, linewidth=0.5))
+# for x in jump_xValues:
+#     plt.axvline(x,ymin=0, ymax= 1, color = 'g',alpha=0.5, linestyle = 'dashed')
+
+
+
+fig.set_size_inches(width, height)
+fig.savefig('Plot-Curvature-Theta.pdf')
 
 # plt.axhline(y = 1.90476, color = 'b', linestyle = ':', label='$q_1$')
 # plt.axhline(y = 2.08333, color = 'r', linestyle = 'dashed', label='$q_2$')