From 706b6d499991f3e43cb9df98ccea6259bb4aa2c8 Mon Sep 17 00:00:00 2001
From: Klaus <klaus.boehnlein@tu-dresden.de>
Date: Tue, 19 Oct 2021 18:37:14 +0200
Subject: [PATCH] Update & remove old Files
---
src/Plotq3-Angle.py | 298 ------------------------------------
src/Plotq3-Angle2.py | 339 -----------------------------------------
src/Plotq3-AngleOld.py | 246 ------------------------------
src/Plotq3-AngleV1.py | 147 ------------------
src/plot-q3-gamma.py | 6 +-
5 files changed, 4 insertions(+), 1032 deletions(-)
delete mode 100644 src/Plotq3-Angle.py
delete mode 100644 src/Plotq3-Angle2.py
delete mode 100644 src/Plotq3-AngleOld.py
delete mode 100644 src/Plotq3-AngleV1.py
diff --git a/src/Plotq3-Angle.py b/src/Plotq3-Angle.py
deleted file mode 100644
index 0d3b277b..00000000
--- a/src/Plotq3-Angle.py
+++ /dev/null
@@ -1,298 +0,0 @@
-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
-import sys
-from ClassifyMin import *
-from HelperFunctions import *
-# from CellScript import *
-from mpl_toolkits.mplot3d import Axes3D
-import matplotlib.cm as cm
-from vtk.util import numpy_support
-from pyevtk.hl import gridToVTK
-import time
-import matplotlib.ticker as ticker
-
-# from matplotlib import rc
-# rc('text', usetex=True) # Use LaTeX font
-#
-# import seaborn as sns
-# sns.set(color_codes=True)
-
-
-def format_func(value, tick_number):
- # find number of multiples of pi/2
- N = int(np.round(2 * value / np.pi))
- if N == 0:
- return "0"
- elif N == 1:
- return r"$\pi/2$"
- elif N == 2:
- return r"$\pi$"
- elif N % 2 > 0:
- return r"${0}\pi/2$".format(N)
- else:
- return r"${0}\pi$".format(N // 2)
-
-
-
-
-def find_nearest(array, value):
- array = np.asarray(array)
- idx = (np.abs(array - value)).argmin()
- return array[idx]
-
-
-def find_nearestIdx(array, value):
- array = np.asarray(array)
- idx = (np.abs(array - value)).argmin()
- return idx
-
-
-InputFile = "/inputs/computeMuGamma.parset"
-OutputFile = "/outputs/outputMuGamma.txt"
-# --------- 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
-# rho1 = 1.0
-# alpha = 2.56140350877193 #2.56140350877193, 4.0852130325814535
-# beta = 2.0 #5.0
-# theta = 1.0/4.0
-# theta = 1.0/8.0 # 0.5
-# theta = 0.075 # 0.5
-# mu1 = 10.0
-# rho1 = 1.0
-# alpha = 10
-# beta = 40.0
-# theta = 0.125
-
-
-
-mu1 = 10.0
-rho1 = 1.0
-alpha = 10.0
-beta = 2.0 #5.0
-theta = 1.0/8.0
-#
-
-
-# mu1 = 10.0
-# rho1 = 1.0
-# # alpha = 10.02021333
-# alpha = 10.0
-# beta = 2.0
-# theta = 0.125
-
-
-
-# mu1 = 10.0
-# rho1 = 1.0
-# # alpha = 10.02021333
-# alpha = 9.0
-# beta = 2.0
-# theta = 0.075
-
-#
-# mu1 = 10.0
-# rho1 = 1.0
-# alpha = 4.0
-# beta = 10.0
-# theta = 1.0/4.0
-
-# alpha = 10 #1.05263158
-# beta = 40.0 #5.0
-# # theta = 1.0/4.0
-# theta = 1.0/8.0 # 0.5
-#
-#
-# alpha = 2.0
-# beta = 2.0 #5.0
-# theta = 1/4.0
-# rho1 = 1.0
-# mu1 = 10.0
-
-# InterestingParameterSet :
-# mu1 = 10.0
-# rho1 = 1.0
-# alpha = 10
-# beta = 40.0
-
-
-# theta = 0.124242
-# gamma = 0.75
-#set gamma either to 1. '0' 2. 'infinity' or 3. a numerical positive value
-# gamma = '0'
-# gamma = 'infinity'
-# gamma = 0.5
-# gamma = 0.25
-
-print('mu1: ', mu1)
-print('rho1: ', rho1)
-print('alpha: ', alpha)
-print('beta: ', beta)
-print('theta: ', theta)
-# print('gamma:', gamma)
-print('----------------------------')
-
-# ----------------------------------------------------------------
-
-
-gamma_min = 0.01
-gamma_max = 3.0
-Gamma_Values = np.linspace(gamma_min, gamma_max, num=100) # TODO variable Input Parameters...alpha,beta...
-print('(Input) Gamma_Values:', Gamma_Values)
-# mu_gamma = []
-
-# Gamma_Values = '0'
-
-# # --- Options
-# # make_Plot = False
-make_Plot = True
-
-# Get values for mu_Gamma
-GetMuGammaVec = np.vectorize(GetMuGamma)
-muGammas = GetMuGammaVec(beta,theta,Gamma_Values,mu1,rho1, InputFilePath ,OutputFilePath )
-print('muGammas:', muGammas)
-
-q12 = 0.0
-q1 = (1.0/6.0)*harmonicMean(mu1, beta, theta)
-q2 = (1.0/6.0)*arithmeticMean(mu1, beta, theta)
-print('q1: ', q1)
-print('q2: ', q2)
-b1 = prestrain_b1(rho1, beta, alpha,theta)
-b2 = prestrain_b2(rho1, beta, alpha,theta)
-q3_star = math.sqrt(q1*q2)
-print('q3_star:', q3_star)
-
-# TODO these have to be compatible with input parameters!!!
-# compute certain ParameterValues that this makes sense
-# b1 = q3_star
-# b2 = q1
-print('b1: ', b1)
-print('b2: ', b2)
-
-# return classifyMin(q1, q2, q3, q12, b1, b2, print_Cases, print_Output)
-
-
-
-# classifyMin_anaVec = np.vectorize(classifyMin_ana)
-# G, angles, Types, curvature = classifyMin_anaVec(alpha, beta, theta, muGammas, mu1, rho1)
-classifyMin_anaVec = np.vectorize(classifyMin_ana)
-G, angles, Types, curvature = classifyMin_anaVec(alpha, beta, theta, muGammas, mu1, rho1)
-
-# _,angles,_,_ = classifyMin_anaVec(alpha, beta, theta, muGammas, mu1, rho1)
-
-print('angles:', angles)
-
-
-
-
-# idx = find_nearestIdx(muGammas, q3_star)
-# print('GammaValue Idx closest to q_3^*', idx)
-# gammaClose = Gamma_Values[idx]
-# print('GammaValue(Idx) with mu_gamma closest to q_3^*', gammaClose)
-
-
-
-
-
-
-# Make Plot
-if make_Plot:
- # plt.figure()
- #
- #
- #
- #
- # # plt.title(r'angle$-\mu_\gamma(\gamma)$-Plot')
- # # plt.title(r'angle$-\gamma$-Plot')
- # # plt.plot(Gamma_Values, angles)
- # # plt.scatter(Gamma_Values, angles)
- # plt.plot(muGammas, angles)
- # plt.scatter(muGammas, angles)
- # # plt.axis([0, 6, 0, 20])
- # # plt.axhline(y = 1.90476, color = 'b', linestyle = ':', label='$q_1$')
- # # plt.axhline(y = 2.08333, color = 'r', linestyle = 'dashed', label='$q_2$')
- # plt.axvline(x = q1, color = 'b', linestyle = ':', label='$q_1$')
- # plt.axvline(x = q2, color = 'r', linestyle = 'dashed', label='$q_2$')
- # # plt.axvline(x = q3_star, color = 'r', linestyle = 'dashed', label='$\gamma^*$')
-
-
-
- f,ax=plt.subplots(1)
- ax.plot(muGammas, angles)
- ax.scatter(muGammas, angles)
- plt.xlabel("$q_3$")
- plt.ylabel("angle")
- ax.grid(True)
- # ax.yaxis.set_major_locator(plt.MultipleLocator(np.pi / 2))
- # ax.yaxis.set_minor_locator(plt.MultipleLocator(np.pi / 12))
-
- # ax.yaxis.set_major_locator(plt.MultipleLocator(np.pi / 4))
- # ax.yaxis.set_minor_locator(plt.MultipleLocator(np.pi / 12))
- # ax.yaxis.set_major_formatter(plt.FuncFormatter(format_func))
-
- # ax.yaxis.set_major_formatter(ticker.FormatStrFormatter('%g $\pi$'))
- # ax.yaxis.set_major_locator(ticker.MultipleLocator(base=0.25))
-
-
- # ax.yaxis.set_major_formatter(ticker.FuncFormatter(
- # lambda val,pos: '{:.0g}$\pi$'.format(2*val/np.pi) if val !=0 else '0'))
- # ax.yaxis.set_major_locator(ticker.MultipleLocator(base=0.5*np.pi))
-
-
- ax.axvline(x = q1, color = 'b', linestyle = ':', label='$q_1$')
- ax.axvline(x = q2, color = 'r', linestyle = 'dashed', label='$q_2$')
- ax.legend()
- # ax.set(xlim=(1.750, 1.880), ylim=(0, math.pi/2.0))
- ax.set(xlim=(1.760, 1.880), ylim=(-0.1, np.pi/4.0))
- # ax.set_yticks([0, np.pi/4 ,np.pi/2])
- # labels = ['$0$', r'$\pi/4$', r'$\pi/2$']
- ax.set_yticks([0, np.pi/8, np.pi/4 ])
- labels = ['$0$',r'$\pi/8$', r'$\pi/4$']
- ax.set_yticklabels(labels)
-
- # Plot Gamma Value that is closest to q3_star
- # plt.axvline(x = gammaClose, color = 'b', linestyle = 'dashed', label='$\gamma^*$')
- # plt.axvspan(gamma_min, gammaClose, color='red', alpha=0.5)
- # plt.axvspan(gammaClose, gamma_max, color='green', alpha=0.5)
-
- plt.xlabel("$q_3(\gamma)$")
- # plt.xlabel("$\gamma$")
- plt.ylabel("angle")
- plt.legend(loc='upper center')
-
- plt.show()
-
-
-
-
- # plt.figure()
- # plt.title(r'angle$-\mu_\gamma(\gamma)$-Plot')
- # plt.plot(muGammas, angles)
- # plt.scatter(muGammas, angles)
- # # plt.axis([0, 6, 0, 20])
- # # plt.axhline(y = 1.90476, color = 'b', linestyle = ':', label='$q_1$')
- # # plt.axhline(y = 2.08333, color = 'r', linestyle = 'dashed', label='$q_2$')
- # plt.axvline(x = 1.90476, color = 'b', linestyle = ':', label='$q_1$')
- # plt.axvline(x = 2.08333, color = 'r', linestyle = 'dashed', label='$q_2$')
- # plt.xlabel("$\mu_\gamma$")
- # plt.ylabel("angle")
- # plt.legend()
- # plt.show()
- #
diff --git a/src/Plotq3-Angle2.py b/src/Plotq3-Angle2.py
deleted file mode 100644
index 9e25264d..00000000
--- a/src/Plotq3-Angle2.py
+++ /dev/null
@@ -1,339 +0,0 @@
-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
-import sys
-from ClassifyMin import *
-from HelperFunctions import *
-# from CellScript import *
-from mpl_toolkits.mplot3d import Axes3D
-import matplotlib.cm as cm
-from vtk.util import numpy_support
-from pyevtk.hl import gridToVTK
-import time
-import matplotlib.ticker as ticker
-
-# from matplotlib import rc
-# rc('text', usetex=True) # Use LaTeX font
-#
-# import seaborn as sns
-# sns.set(color_codes=True)
-
-
-def format_func(value, tick_number):
- # find number of multiples of pi/2
- N = int(np.round(2 * value / np.pi))
- if N == 0:
- return "0"
- elif N == 1:
- return r"$\pi/2$"
- elif N == 2:
- return r"$\pi$"
- elif N % 2 > 0:
- return r"${0}\pi/2$".format(N)
- else:
- return r"${0}\pi$".format(N // 2)
-
-
-
-
-def find_nearest(array, value):
- array = np.asarray(array)
- idx = (np.abs(array - value)).argmin()
- return array[idx]
-
-
-def find_nearestIdx(array, value):
- array = np.asarray(array)
- idx = (np.abs(array - value)).argmin()
- return idx
-
-
-InputFile = "/inputs/computeMuGamma.parset"
-OutputFile = "/outputs/outputMuGamma.txt"
-# --------- 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
-# rho1 = 1.0
-# alpha = 2.56140350877193 #2.56140350877193, 4.0852130325814535
-# beta = 2.0 #5.0
-# theta = 1.0/4.0
-# theta = 1.0/8.0 # 0.5
-# theta = 0.075 # 0.5
-# mu1 = 10.0
-# rho1 = 1.0
-alpha = 10
-# beta = 40.0
-# theta = 0.125
-
-mu1 = 10.0
-rho1 = 1.0
-# alpha = 2.0
-beta = 2.0 #5.0
-# theta = 1.0/4.0
-theta = 1.0/8.0
-#
-
-
-
-# mu1 = 10.0
-# rho1 = 1.0
-# alpha = 10.0
-# beta = 2.0 #5.0
-# theta = 1.0/8.0
-# #
-
-
-# mu1 = 10.0
-# rho1 = 1.0
-# # alpha = 10.02021333
-# alpha = 10.0
-# beta = 2.0
-# theta = 0.125
-
-
-
-# mu1 = 10.0
-# rho1 = 1.0
-# # alpha = 10.02021333
-# alpha = 9.0
-# beta = 2.0
-# theta = 0.075
-
-#
-# mu1 = 10.0
-# rho1 = 1.0
-# alpha = 4.0
-# beta = 10.0
-# theta = 1.0/4.0
-
-# alpha = 10 #1.05263158
-# beta = 40.0 #5.0
-# # theta = 1.0/4.0
-# theta = 1.0/8.0 # 0.5
-#
-#
-# alpha = 2.0
-# beta = 2.0 #5.0
-# theta = 1/4.0
-# rho1 = 1.0
-# mu1 = 10.0
-
-# InterestingParameterSet :
-# mu1 = 10.0
-# rho1 = 1.0
-# alpha = 10
-# beta = 40.0
-
-
-# theta = 0.124242
-# gamma = 0.75
-#set gamma either to 1. '0' 2. 'infinity' or 3. a numerical positive value
-# gamma = '0'
-# gamma = 'infinity'
-# gamma = 0.5
-# gamma = 0.25
-
-print('mu1: ', mu1)
-print('rho1: ', rho1)
-print('alpha: ', alpha)
-print('beta: ', beta)
-print('theta: ', theta)
-# print('gamma:', gamma)
-print('----------------------------')
-
-# ----------------------------------------------------------------
-
-
-gamma_min = 0.01
-gamma_max = 1.0
-Gamma_Values = np.linspace(gamma_min, gamma_max, num=100) # TODO variable Input Parameters...alpha,beta...
-print('(Input) Gamma_Values:', Gamma_Values)
-# mu_gamma = []
-
-# Gamma_Values = '0'
-
-# # --- Options
-# # make_Plot = False
-make_Plot = True
-
-# Get values for mu_Gamma
-GetMuGammaVec = np.vectorize(GetMuGamma)
-muGammas = GetMuGammaVec(beta,theta,Gamma_Values,mu1,rho1, InputFilePath ,OutputFilePath )
-print('muGammas:', muGammas)
-
-q12 = 0.0
-q1 = (1.0/6.0)*harmonicMean(mu1, beta, theta)
-q2 = (1.0/6.0)*arithmeticMean(mu1, beta, theta)
-print('q1: ', q1)
-print('q2: ', q2)
-b1 = prestrain_b1(rho1, beta, alpha,theta)
-b2 = prestrain_b2(rho1, beta, alpha,theta)
-q3_star = math.sqrt(q1*q2)
-print('q3_star:', q3_star)
-
-# TODO these have to be compatible with input parameters!!!
-# compute certain ParameterValues that this makes sense
-# b1 = q3_star
-# b2 = q1
-print('b1: ', b1)
-print('b2: ', b2)
-
-# return classifyMin(q1, q2, q3, q12, b1, b2, print_Cases, print_Output)
-
-
-
-# classifyMin_anaVec = np.vectorize(classifyMin_ana)
-# G, angles, Types, curvature = classifyMin_anaVec(alpha, beta, theta, muGammas, mu1, rho1)
-classifyMin_anaVec = np.vectorize(classifyMin_ana)
-G, angles, Types, curvature = classifyMin_anaVec(alpha, beta, theta, muGammas, mu1, rho1)
-
-# _,angles,_,_ = classifyMin_anaVec(alpha, beta, theta, muGammas, mu1, rho1)
-
-print('angles:', angles)
-
-
-
-
-idx = find_nearestIdx(muGammas, q3_star)
-print('GammaValue Idx closest to q_3^*', idx)
-gammaClose = Gamma_Values[idx]
-print('GammaValue(Idx) with mu_gamma closest to q_3^*', gammaClose)
-
-
-
-determinantVec = np.vectorize(determinant)
-
-detValues = determinantVec(q1,q2,muGammas,q12)
-print('detValues:', detValues)
-
-
-detZeroidx = find_nearestIdx(detValues, 0)
-print('idx where det nearest to zero', idx)
-gammaClose = Gamma_Values[detZeroidx]
-print('gammaClose:', gammaClose)
-
-
-# Make Plot
-if make_Plot:
- # plt.figure()
- #
- #
- #
- #
- # # plt.title(r'angle$-\mu_\gamma(\gamma)$-Plot')
- # # plt.title(r'angle$-\gamma$-Plot')
- plt.plot(Gamma_Values, angles)
- plt.scatter(Gamma_Values, angles)
- # plt.plot(muGammas, angles)
- # plt.scatter(muGammas, angles)
- # # plt.axis([0, 6, 0, 20])
- # # plt.axhline(y = 1.90476, color = 'b', linestyle = ':', label='$q_1$')
- # # plt.axhline(y = 2.08333, color = 'r', linestyle = 'dashed', label='$q_2$')
- # plt.axvline(x = q1, color = 'b', linestyle = ':', label='$q_1$')
- # plt.axvline(x = q2, color = 'r', linestyle = 'dashed', label='$q_2$')
- # # plt.axvline(x = q3_star, color = 'r', linestyle = 'dashed', label='$\gamma^*$')
-
-
-
- f,ax=plt.subplots(1)
- # ax.plot(muGammas, angles)
- # ax.scatter(muGammas, angles)
-
- ax.plot(Gamma_Values, angles)
- ax.scatter(Gamma_Values, angles)
-
-
- plt.xlabel("$q_3$")
- plt.xlabel("$\gamma$")
- plt.ylabel("angle")
- ax.grid(True)
-
-
- # ax.yaxis.set_major_locator(plt.MultipleLocator(np.pi / 2))
- # ax.yaxis.set_minor_locator(plt.MultipleLocator(np.pi / 12))
-
- # ax.yaxis.set_major_locator(plt.MultipleLocator(np.pi / 4))
- # ax.yaxis.set_minor_locator(plt.MultipleLocator(np.pi / 12))
- # ax.yaxis.set_major_formatter(plt.FuncFormatter(format_func))
-
- # ax.yaxis.set_major_formatter(ticker.FormatStrFormatter('%g $\pi$'))
- # ax.yaxis.set_major_locator(ticker.MultipleLocator(base=0.25))
-
-
- # ax.yaxis.set_major_formatter(ticker.FuncFormatter(
- # lambda val,pos: '{:.0g}$\pi$'.format(2*val/np.pi) if val !=0 else '0'))
- # ax.yaxis.set_major_locator(ticker.MultipleLocator(base=0.5*np.pi))
-
- # ---------------------------- show pi values ------------------------------------
- # ax.axvline(x = q1, color = 'b', linestyle = ':', label='$q_1$')
- # ax.axvline(x = q2, color = 'r', linestyle = 'dashed', label='$q_2$')
- # ax.legend()
- # # ax.set(xlim=(1.750, 1.880), ylim=(0, math.pi/2.0))
- # ax.set(xlim=(1.760, 1.880), ylim=(-0.1, np.pi/4.0))
- # # ax.set_yticks([0, np.pi/4 ,np.pi/2])
- # # labels = ['$0$', r'$\pi/4$', r'$\pi/2$']
- # ax.set_yticks([0, np.pi/8, np.pi/4 ])
- # labels = ['$0$',r'$\pi/8$', r'$\pi/4$']
- # ax.set_yticklabels(labels)
- # ---------------------------------------------------------------
-
- ax.legend()
- # ax.set(xlim=(1.750, 1.880), ylim=(0, math.pi/2.0))
-
- # ax.set(xlim=(1.760, 1.880), ylim=(-0.1, np.pi/4.0))
- # ax.set(xlim=(1.760, 1.880), ylim=(-0.1, np.pi/4.0))
- # ax.set_yticks([0, np.pi/4 ,np.pi/2])
- # labels = ['$0$', r'$\pi/4$', r'$\pi/2$']
- ax.set_yticks([0, np.pi/8, np.pi/4 ])
- labels = ['$0$',r'$\pi/8$', r'$\pi/4$']
- ax.set_yticklabels(labels)
-
-
- # Plot Gamma Value that is closest to q3_star
- ax.axvline(x = gammaClose, color = 'b', linestyle = 'dashed', label='$\gamma^*$')
- ax.axvspan(gamma_min, gammaClose, color='red', alpha=0.5)
- ax.axvspan(gammaClose, gamma_max, color='green', alpha=0.5)
-
-
-
-
- # plt.xlabel("$q_3(\gamma)$")
- plt.xlabel("$\gamma$")
- plt.ylabel("angle")
- plt.legend(loc='upper center')
-
- plt.show()
-
-
-
-
- # plt.figure()
- # plt.title(r'angle$-\mu_\gamma(\gamma)$-Plot')
- # plt.plot(muGammas, angles)
- # plt.scatter(muGammas, angles)
- # # plt.axis([0, 6, 0, 20])
- # # plt.axhline(y = 1.90476, color = 'b', linestyle = ':', label='$q_1$')
- # # plt.axhline(y = 2.08333, color = 'r', linestyle = 'dashed', label='$q_2$')
- # plt.axvline(x = 1.90476, color = 'b', linestyle = ':', label='$q_1$')
- # plt.axvline(x = 2.08333, color = 'r', linestyle = 'dashed', label='$q_2$')
- # plt.xlabel("$\mu_\gamma$")
- # plt.ylabel("angle")
- # plt.legend()
- # plt.show()
- #
diff --git a/src/Plotq3-AngleOld.py b/src/Plotq3-AngleOld.py
deleted file mode 100644
index b46195d8..00000000
--- a/src/Plotq3-AngleOld.py
+++ /dev/null
@@ -1,246 +0,0 @@
-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
-import sys
-from ClassifyMin import *
-# from CellScript import *
-from mpl_toolkits.mplot3d import Axes3D
-import matplotlib.cm as cm
-from vtk.util import numpy_support
-from pyevtk.hl import gridToVTK
-import time
-# from subprocess import Popen, PIPE
-#import sys
-
-# 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
-
-
-
-
-InputFile = "/inputs/computeMuGamma.parset"
-OutputFile = "/outputs/outputMuGamma.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)
-
-
-#1. Define Inputs Gamma-Array..
-#2. for(i=0; i<length(array)) ..compute Q_hom, B_eff from Cell-Problem
-#3
-
-# matrix = np.loadtxt(path + 'Qmatrix.txt', usecols=range(3))
-# print(matrix)
-
-# Use Shell Commands:
-# subprocess.run('ls', shell=True)
-
-
-#---------------------------------------------------------------
-
-# -------------------------- Input Parameters --------------------
-mu1 = 10.0
-rho1 = 1.0
-alpha = 10 #1.05263158
-beta = 40.0 #5.0
-# theta = 1.0/4.0
-theta = 1.0/8.0 # 0.5
-
-# InterestingParameterSet :
-# mu1 = 10.0
-# rho1 = 1.0
-# alpha = 10
-# beta = 40.0
-# theta = 1.0/8.0
-
-
-#set gamma either to 1. '0' 2. 'infinity' or 3. a numerical positive value
-# gamma = '0'
-# gamma = 'infinity'
-# gamma = 0.5
-
-print('---- Input parameters: -----')
-print('mu1: ', mu1)
-print('rho1: ', rho1)
-print('alpha: ', alpha)
-print('beta: ', beta)
-print('theta: ', theta)
-# print('gamma:', gamma)
-print('----------------------------')
-# ----------------------------------------------------------------
-
-
-
-
-
-Gamma_Values = np.linspace(0.01, 5, num=20) # TODO variable Input Parameters...alpha,beta...
-print('(Input) Gamma_Values:', Gamma_Values)
-# mu_gamma = []
-
-
-#
-# # --- Options
-# RUN = True
-# # RUN = False
-# # make_Plot = False
-make_Plot = True # vll besser : Plot_muGamma
-#
-# if RUN:
-# for gamma in Gamma_Values:
-# print("Run Cell-Problem for Gamma = ", gamma)
-# # print('gamma='+str(gamma))
-# with open(InputFilePath, 'r') as file:
-# filedata = file.read()
-# filedata = re.sub('(?m)^gamma=.*','gamma='+str(gamma),filedata)
-# f = open(InputFilePath,'w')
-# f.write(filedata)
-# f.close()
-# # --- Run Cell-Problem
-# 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_gammaValue = float(s[0])
-# print("mu_gamma:", mu_gammaValue)
-# mu_gamma.append(mu_gammaValue)
-# # ------------end of for-loop -----------------
-# print("(Output) Values of mu_gamma: ", mu_gamma)
-# # ----------------end of if-statement -------------
-#
-# # mu_gamma=[2.06099, 1.90567, 1.905]
-# # mu_gamma=[2.08306, 1.905, 1.90482, 1.90479, 1.90478, 1.90477]
-#
-# ##Gamma_Values = np.linspace(0.01, 20, num=12) :
-# #mu_gamma= [2.08306, 1.91108, 1.90648, 1.90554, 1.90521, 1.90505, 1.90496, 1.90491, 1.90487, 1.90485, 1.90483, 1.90482]
-#
-# ##Gamma_Values = np.linspace(0.01, 2.5, num=12)
-# # mu_gamma=[2.08306, 2.01137, 1.96113, 1.93772, 1.92592, 1.91937, 1.91541, 1.91286, 1.91112, 1.90988, 1.90897, 1.90828]
-#
-# # Gamma_Values = np.linspace(0.01, 2.5, num=6)
-# # mu_gamma=[2.08306, 1.95497, 1.92287, 1.91375, 1.9101, 1.90828]
-
-
-GetMuGammaVec = np.vectorize(GetMuGamma)
-muGammas = GetMuGammaVec(beta,theta,Gamma_Values,mu1,rho1)
-
-
-classifyMin_anaVec = np.vectorize(classifyMin_ana)
-
-G, angles, Types, curvature = classifyMin_anaVec(alpha, beta, theta, muGammas, mu1, rho1)
-# _,angles,_,_ = classifyMin_anaVec(alpha, beta, theta, muGammas, mu1, rho1)
-
-print('angles:', angles)
-
-# Make Plot
-if make_Plot:
- plt.figure()
- plt.title(r'angle$-\mu_\gamma(\gamma)$-Plot')
- plt.plot(muGammas, angles)
- plt.scatter(muGammas, angles)
- # plt.axis([0, 6, 0, 20])
- # plt.axhline(y = 1.90476, color = 'b', linestyle = ':', label='$q_1$')
- # plt.axhline(y = 2.08333, color = 'r', linestyle = 'dashed', label='$q_2$')
- plt.axvline(x = 1.90476, color = 'b', linestyle = ':', label='$q_1$')
- plt.axvline(x = 2.08333, color = 'r', linestyle = 'dashed', label='$q_2$')
- plt.xlabel("$\mu_\gamma$")
- plt.ylabel("angle")
- plt.legend()
- plt.show()
-
-#
-# # ------------- RUN Matlab symbolic minimization program
-# 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
-# print('Run symbolic Minimization...')
-# 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)
diff --git a/src/Plotq3-AngleV1.py b/src/Plotq3-AngleV1.py
deleted file mode 100644
index cd07176c..00000000
--- a/src/Plotq3-AngleV1.py
+++ /dev/null
@@ -1,147 +0,0 @@
-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
-import sys
-from ClassifyMin import *
-from HelperFunctions import *
-# from CellScript import *
-from mpl_toolkits.mplot3d import Axes3D
-import matplotlib.cm as cm
-from vtk.util import numpy_support
-from pyevtk.hl import gridToVTK
-import time
-
-
-
-
-InputFile = "/inputs/computeMuGamma.parset"
-OutputFile = "/outputs/outputMuGamma.txt"
-# --------- 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
-rho1 = 1.0
-alpha = 2.8
-beta = 2.0
-theta = 1.0/4.0
-# gamma = 0.75
-#set gamma either to 1. '0' 2. 'infinity' or 3. a numerical positive value
-# gamma = '0'
-# gamma = 'infinity'
-# gamma = 0.5
-
-
-print('mu1: ', mu1)
-print('rho1: ', rho1)
-print('alpha: ', alpha)
-print('beta: ', beta)
-print('theta: ', theta)
-# print('gamma:', gamma)
-print('----------------------------')
-
-# ----------------------------------------------------------------
-
-
-
-
-
-Gamma_Values = np.linspace(0.01, 5, num=15) # TODO variable Input Parameters...alpha,beta...
-print('(Input) Gamma_Values:', Gamma_Values)
-# mu_gamma = []
-
-
-#
-# # --- Options
-# RUN = True
-# # RUN = False
-# # make_Plot = False
-make_Plot = True # vll besser : Plot_muGamma
-#
-# if RUN:
-# for gamma in Gamma_Values:
-# print("Run Cell-Problem for Gamma = ", gamma)
-# # print('gamma='+str(gamma))
-# with open(InputFilePath, 'r') as file:
-# filedata = file.read()
-# filedata = re.sub('(?m)^gamma=.*','gamma='+str(gamma),filedata)
-# f = open(InputFilePath,'w')
-# f.write(filedata)
-# f.close()
-# # --- Run Cell-Problem
-# 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_gammaValue = float(s[0])
-# print("mu_gamma:", mu_gammaValue)
-# mu_gamma.append(mu_gammaValue)
-# # ------------end of for-loop -----------------
-# print("(Output) Values of mu_gamma: ", mu_gamma)
-# # ----------------end of if-statement -------------
-#
-# # mu_gamma=[2.06099, 1.90567, 1.905]
-# # mu_gamma=[2.08306, 1.905, 1.90482, 1.90479, 1.90478, 1.90477]
-#
-# ##Gamma_Values = np.linspace(0.01, 20, num=12) :
-# #mu_gamma= [2.08306, 1.91108, 1.90648, 1.90554, 1.90521, 1.90505, 1.90496, 1.90491, 1.90487, 1.90485, 1.90483, 1.90482]
-#
-# ##Gamma_Values = np.linspace(0.01, 2.5, num=12)
-# # mu_gamma=[2.08306, 2.01137, 1.96113, 1.93772, 1.92592, 1.91937, 1.91541, 1.91286, 1.91112, 1.90988, 1.90897, 1.90828]
-#
-# # Gamma_Values = np.linspace(0.01, 2.5, num=6)
-# # mu_gamma=[2.08306, 1.95497, 1.92287, 1.91375, 1.9101, 1.90828]
-
-
-GetMuGammaVec = np.vectorize(GetMuGamma)
-muGammas = GetMuGammaVec(beta,theta,Gamma_Values,mu1,rho1)
-
-
-classifyMin_anaVec = np.vectorize(classifyMin_ana)
-
-G, angles, Types, curvature = classifyMin_anaVec(alpha, beta, theta, muGammas, mu1, rho1)
-# _,angles,_,_ = classifyMin_anaVec(alpha, beta, theta, muGammas, mu1, rho1)
-
-print('angles:', angles)
-
-# Make Plot
-if make_Plot:
- plt.figure()
- plt.title(r'angle$-\mu_\gamma(\gamma)$-Plot')
- plt.plot(muGammas, angles)
- plt.scatter(muGammas, angles)
- # plt.axis([0, 6, 0, 20])
- # plt.axhline(y = 1.90476, color = 'b', linestyle = ':', label='$q_1$')
- # plt.axhline(y = 2.08333, color = 'r', linestyle = 'dashed', label='$q_2$')
- plt.axvline(x = 1.90476, color = 'b', linestyle = ':', label='$q_1$')
- plt.axvline(x = 2.08333, color = 'r', linestyle = 'dashed', label='$q_2$')
- plt.xlabel("$\mu_\gamma$")
- plt.ylabel("angle")
- plt.legend()
- plt.show()
diff --git a/src/plot-q3-gamma.py b/src/plot-q3-gamma.py
index 9d44bdf7..616f2f67 100644
--- a/src/plot-q3-gamma.py
+++ b/src/plot-q3-gamma.py
@@ -127,7 +127,8 @@ mpl.rcParams["font.size"] = "9"
width = 6.28 *0.5
height = width / 1.618
fig = plt.figure()
-ax = plt.axes((0.15,0.18,0.8,0.8))
+# ax = plt.axes((0.15,0.18,0.8,0.8))
+ax = plt.axes((0.15,0.21 ,0.8,0.75))
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(0.5))
@@ -141,7 +142,8 @@ markerfacecolor='orange', # marker facecolor
markeredgecolor='black', # marker edgecolor
markeredgewidth=1, # marker edge width
# linestyle='--', # line style will be dash line
-linewidth=1) # line width
+linewidth=1,
+zorder=3) # line width
ax.set_xlabel(r"$\gamma$")
--
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