diff --git a/src/HelperFunctions.py b/src/HelperFunctions.py
index 426c87a2e7710f5b7d557a6bc5bfe18f7347ce3e..578fcfdbb7115d783b3ebe31babbf0a95db4a4fd 100644
--- a/src/HelperFunctions.py
+++ b/src/HelperFunctions.py
@@ -62,6 +62,63 @@ def RunCellProblem(alpha,beta,theta,gamma,mu1,rho1, InputFilePath = os.path.dirn
+
+# unabhängig von alpha...
+def GetMuGamma(beta,theta,gamma,mu1,rho1, InputFilePath = os.path.dirname(os.getcwd()) +"/inputs/computeMuGamma.parset"):
+ # ------------------------------------ get mu_gamma ------------------------------
+ # ---Scenario 1.1: extreme regimes
+ if gamma == '0':
+ print('extreme regime: gamma = 0')
+ mu_gamma = (1.0/6.0)*arithmeticMean(mu1, beta, theta) # = q2
+ print("mu_gamma:", mu_gamma)
+ elif gamma == 'infinity':
+ print('extreme regime: gamma = infinity')
+ mu_gamma = (1.0/6.0)*harmonicMean(mu1, beta, theta) # = q1
+ print("mu_gamma:", mu_gamma)
+ else:
+ # --- Scenario 1.2: compute mu_gamma with 'Compute_MuGamma' (much faster than running full Cell-Problem)
+ # print("Run computeMuGamma for Gamma = ", gamma)
+ with open(InputFilePath, 'r') as file:
+ filedata = file.read()
+ filedata = re.sub('(?m)^gamma=.*','gamma='+str(gamma),filedata)
+ # filedata = re.sub('(?m)^alpha=.*','alpha='+str(alpha),filedata)
+ filedata = re.sub('(?m)^beta=.*','beta='+str(beta),filedata)
+ filedata = re.sub('(?m)^theta=.*','theta='+str(theta),filedata)
+ filedata = re.sub('(?m)^mu1=.*','mu1='+str(mu1),filedata)
+ filedata = re.sub('(?m)^rho1=.*','rho1='+str(rho1),filedata)
+ f = open(InputFilePath,'w')
+ f.write(filedata)
+ f.close()
+ # --- Run Cell-Problem
+
+ # Check Time
+ # t = time.time()
+ # subprocess.run(['./build-cmake/src/Cell-Problem', './inputs/cellsolver.parset'],
+ # capture_output=True, text=True)
+ # --- Run Cell-Problem_muGama -> faster
+ # subprocess.run(['./build-cmake/src/Cell-Problem_muGamma', './inputs/cellsolver.parset'],
+ # capture_output=True, text=True)
+ # --- Run Compute_muGamma (2D Problem much much faster)
+
+ subprocess.run(['./build-cmake/src/Compute_MuGamma', './inputs/computeMuGamma.parset'],
+ capture_output=True, text=True)
+ # print('elapsed time:', time.time() - t)
+
+ #Extract mu_gamma from Output-File TODO: GENERALIZED THIS FOR QUANTITIES OF INTEREST
+ with open(OutputFilePath, 'r') as file:
+ output = file.read()
+ tmp = re.search(r'(?m)^mu_gamma=.*',output).group() # Not necessary for Intention of Program t output Minimizer etc.....
+ s = re.findall(r"[-+]?\d*\.\d+|\d+", tmp)
+ mu_gamma = float(s[0])
+ # print("mu_gamma:", mu_gammaValue)
+ # --------------------------------------------------------------------------------------
+ return mu_gamma
+
+
+
+
+
+
def Compare_Classification(alpha,beta,theta,gamma,mu1,rho1, InputFilePath = os.path.dirname(os.getcwd()) +"/inputs/computeMuGamma.parset"):
# ---------------------------------------------------------------
# Comparison of the analytical Classification 'ClassifyMin'
@@ -93,7 +150,7 @@ def Compare_Classification(alpha,beta,theta,gamma,mu1,rho1, InputFilePath = os.p
# 3. --- Run Matlab symbolic minimization program: 'symMinimization'
eng = matlab.engine.start_matlab()
# s = eng.genpath(path + '/Matlab-Programs')
- s = eng.genpath(path)
+ s = eng.genpath(os.path.dirname(os.getcwd()))
eng.addpath(s, nargout=0)
# print('current Matlab folder:', eng.pwd(nargout=1))
eng.cd('Matlab-Programs', nargout=0) #switch to Matlab-Programs folder
@@ -123,13 +180,13 @@ def Compare_Classification(alpha,beta,theta,gamma,mu1,rho1, InputFilePath = os.p
b1 = B[0]
b2 = B[1]
b3 = B[2]
- # print("q1:", q1)
- # print("q2:", q2)
- # print("q3:", q3)
- # print("q12:", q12)
- # print("b1:", b1)
- # print("b2:", b2)
- # print("b3:", b3)
+ print("q1:", q1)
+ print("q2:", q2)
+ print("q3:", q3)
+ print("q12:", q12)
+ print("b1:", b1)
+ print("b2:", b2)
+ print("b3:", b3)
# --- Check Assumptions:
# Assumption of Classification-Lemma1.6: [b3 == 0] & [Q orthotropic]
@@ -141,11 +198,11 @@ def Compare_Classification(alpha,beta,theta,gamma,mu1,rho1, InputFilePath = os.p
# 5. --- Get output from the analytical Classification 'ClassifyMin'
G_ana, angle_ana, type_ana, kappa_ana = classifyMin(q1, q2, q3, q12, b1, b2)
- # print('Minimizer G_ana:')
- # print(G_ana)
- # print('angle_ana:', angle_ana)
- # print('type_ana:', type_ana )
- # print('curvature_ana:', kappa_ana)
+ print('Minimizer G_ana:')
+ print(G_ana)
+ print('angle_ana:', angle_ana)
+ print('type_ana:', type_ana )
+ print('curvature_ana:', kappa_ana)
# 6. Compare
# print('DifferenceMatrix:', G_ana - G )
@@ -167,6 +224,8 @@ def Compare_Classification(alpha,beta,theta,gamma,mu1,rho1, InputFilePath = os.p
if comparison_successful:
print('Comparison successful')
+ else:
+ print('Comparison unsuccessful')
return comparison_successful
diff --git a/src/makePlot.py b/src/makePlot.py
new file mode 100644
index 0000000000000000000000000000000000000000..b73422667bafad7cd4b39c25ce46d72b30a9d74c
--- /dev/null
+++ b/src/makePlot.py
@@ -0,0 +1,236 @@
+import numpy as np
+import matplotlib.pyplot as plt
+import sympy as sym
+import math
+import os
+import subprocess
+import fileinput
+import re
+import matlab.engine
+from HelperFunctions import *
+# from subprocess import Popen, PIPE
+#import sys
+
+###################### makePlot.py #########################
+# Generalized Plot-Script giving the option to define
+# quantity of interest and the parameter it depends on
+# to create a plot
+#
+# Input: Define y & x for "x-y plot" as Strings
+# - Run the 'Cell-Problem' for the different Parameter-Points
+# (alternatively run 'Compute_MuGamma' if quantity of interest
+# is q3=muGamma for a significant Speedup)
+
+###########################################################
+
+# TODO
+# - Fallunterscheidung (Speedup) falls gesuchter value mu_gamma = q3
+# - Also Add option to plot Minimization Output
+
+
+# ----- Setup Paths -----
+InputFile = "/inputs/cellsolver.parset"
+OutputFile = "/outputs/output.txt"
+# path = os.getcwd()
+# InputFilePath = os.getcwd()+InputFile
+# OutputFilePath = os.getcwd()+OutputFile
+# --------- Run from src folder:
+path_parent = os.path.dirname(os.getcwd())
+os.chdir(path_parent)
+path = os.getcwd()
+print(path)
+InputFilePath = os.getcwd()+InputFile
+OutputFilePath = os.getcwd()+OutputFile
+print("InputFilepath: ", InputFilePath)
+print("OutputFilepath: ", OutputFilePath)
+print("Path: ", path)
+
+#---------------------------------------------------------------
+
+print('---- Input parameters: -----')
+mu1 = 10.0
+lambda1 = 10.0
+rho1 = 1.0
+alpha = 2.8
+beta = 2.0
+theta = 1.0/4.0
+gamma = 0.75
+
+print('mu1: ', mu1)
+print('rho1: ', rho1)
+print('alpha: ', alpha)
+print('beta: ', beta)
+print('theta: ', theta)
+print('gamma:', gamma)
+print('----------------------------')
+
+
+# TODO? : Ask User for Input ...
+# function = input("Enter value you want to plot (y-value):\n")
+# print(f'You entered {function}')
+# parameter = input("Enter Parameter this value depends on (x-value) :\n")
+# print(f'You entered {parameter}')
+
+# Add Option to change NumberOfElements used for computation of Cell-Problem
+
+
+# --- Define Quantity of interest:
+# Options: 'q1', 'q2', 'q3', 'q12' ,'q21', 'q31', 'q13' , 'q23', 'q32' , 'b1', 'b2' ,'b3'
+# TODO: EXTRA (MInimization Output) 'Minimizer (norm?)' 'angle', 'type', 'curvature'
+yName = 'q12'
+# yName = 'b1'
+yName = 'q3'
+yName = 'angle'
+
+# --- Define Parameter this function/quantity depends on:
+# Options: mu1 ,lambda1, rho1 , alpha, beta, theta, gamma
+# xName = 'theta'
+xName = 'gamma'
+# xName = 'lambda1'
+
+# --- define Interval of x-values:
+# xmin = 0.0
+# xmax = 10.0
+xmin = 0.01
+xmax = 3.0
+numPoints = 3
+X_Values = np.linspace(xmin, xmax, num=numPoints)
+print(X_Values)
+
+
+Y_Values = []
+
+
+
+# --- Options
+RUN = True
+# RUN = False
+# make_Plot = False
+make_Plot = True
+
+if RUN:
+ for x in X_Values:
+
+ if yName =='q3' or yName == 'mu_gamma':
+ with open(path+"/inputs/computeMuGamma.parset", 'r') as file:
+ filedata = file.read()
+ filedata = re.sub('(?m)^'+xName+'=.*',xName+'='+str(x),filedata)
+ f = open(path+"/inputs/computeMuGamma.parset",'w')
+ f.write(filedata)
+ f.close()
+ #Run Compute_MuGamma since its much faster
+ print("Run Compute_MuGamma for " + xName + " =" , x)
+ subprocess.run(['./build-cmake/src/Compute_MuGamma', './inputs/computeMuGamma.parset'],
+ capture_output=True, text=True)
+ #Extract mu_gamma from Output-File
+ with open(path + '/outputs/outputMuGamma.txt', 'r') as file:
+ output = file.read()
+ tmp = re.search(r'(?m)^mu_gamma=.*',output).group() # Not necessary for Intention of Program t output Minimizer etc.....
+ s = re.findall(r"[-+]?\d*\.\d+|\d+", tmp)
+ Y_Values.append(float(s[0]))
+ else :
+ with open(InputFilePath, 'r') as file:
+ filedata = file.read()
+ filedata = re.sub('(?m)^'+xName+'=.*',xName+'='+str(x),filedata)
+ f = open(InputFilePath,'w')
+ f.write(filedata)
+ f.close()
+ # Run Cell-Problem
+ print("Run Cell-Problem for " + xName + " =" , x)
+ subprocess.run(['./build-cmake/src/Cell-Problem', './inputs/cellsolver.parset'],
+ capture_output=True, text=True)
+ #Extract quantity from Output-File
+ Q, B = ReadEffectiveQuantities()
+ if yName == 'q1': # TODO: Better use dictionary?...
+ print('q1 used')
+ Y_Values.append(Q[0][0])
+ elif yName =='q2':
+ print('q2 used')
+ Y_Values.append(Q[1][1])
+ # elif yName =='q3':
+ # print('q3 used')
+ # Y_Values.append(Q[0][0])
+ elif yName =='q12':
+ print('q12 used')
+ Y_Values.append(Q[0][1])
+ elif yName =='q21':
+ print('q21 used')
+ Y_Values.append(Q[1][0])
+ elif yName =='q13':
+ print('q13 used')
+ Y_Values.append(Q[0][2])
+ elif yName =='q31':
+ print('q31 used')
+ Y_Values.append(Q[2][0])
+ elif yName =='q23':
+ print('q23 used')
+ Y_Values.append(Q[1][2])
+ elif yName =='q32':
+ print('q32 used')
+ Y_Values.append(Q[2][1])
+ elif yName =='b1':
+ print('b1 used')
+ Y_Values.append(B[0])
+ elif yName =='b2':
+ print('b2 used')
+ Y_Values.append(B[1])
+ elif yName =='b3':
+ print('b3 used')
+ Y_Values.append(B[2])
+ elif yName == 'angle' or yName =='type' or yName =='curvature':
+ # ------------- Run Matlab symbolic minimization program 'symMinimization'
+ eng = matlab.engine.start_matlab()
+ # s = eng.genpath(path + '/Matlab-Programs')
+ s = eng.genpath(path)
+ eng.addpath(s, nargout=0)
+ # print('current Matlab folder:', eng.pwd(nargout=1))
+ eng.cd('Matlab-Programs', nargout=0) #switch to Matlab-Programs folder
+ # print('current Matlab folder:', eng.pwd(nargout=1))
+ Inp = False
+ Inp_T = True
+ print('Run symbolic Minimization...')
+ #Arguments: symMinization(print_Input,print_statPoint,print_Output,make_FunctionPlot, InputPath)
+ G, angle, type, kappa = eng.symMinimization(Inp,Inp,Inp,Inp, nargout=4) #Name of program:symMinimization
+ # G, angle, type, kappa = eng.symMinimization(Inp,Inp,Inp,Inp,path + "/outputs", nargout=4) #Optional: add Path
+ G = np.asarray(G) #cast Matlab Outout to numpy array
+ # --- print Output ---
+ print('Minimizer G:')
+ print(G)
+ print('angle:', angle)
+ print('type:', type )
+ print('curvature:', kappa)
+ if yName =='angle':
+ print('angle used')
+ Y_Values.append(angle)
+ if yName =='type':
+ print('angle used')
+ Y_Values.append(angle)
+ if yName =='kappa':
+ print('angle used')
+ Y_Values.append(angle)
+ # ------------end of for-loop -----------------
+ print("(Output) Values of " + yName + ": ", Y_Values)
+# ----------------end of if-statement -------------
+
+
+
+
+
+
+
+
+# ---------------- Create Plot -------------------
+plt.figure()
+# plt.title(r''+ yName + '-Plot')
+plt.plot(X_Values, Y_Values)
+plt.scatter(X_Values, Y_Values)
+# plt.axis([0, 6, 0, 20])
+plt.xlabel(xName)
+plt.ylabel(yName)
+
+
+# plt.axhline(y = 1.90476, color = 'b', linestyle = ':', label='$q_1$')
+# plt.axhline(y = 2.08333, color = 'r', linestyle = 'dashed', label='$q_2$')
+# plt.legend()
+plt.show()
+# #---------------------------------------------------------------