Matlab-Programs/resources/metadata.xml

+<?xml version="1.0" encoding="UTF-8"?>
+<addOn>
+  <identifier>e5698820-4a80-11e4-9553-005056977bd0</identifier>
+  <displayType>Function</displayType>
+  <translatedDisplayType>
+    <en_US>Function</en_US>
+    <ja_JP>関数</ja_JP>
+    <ko_KR>함수</ko_KR>
+    <zh_CN>函数</zh_CN>
+  </translatedDisplayType>
+  <name>Red Blue Colormap</name>
+  <author>Adam Auton</author>
+  <version>1.0.0.0</version>
+  <downloadUrl>https://www.mathworks.com/matlabcentral/mlc-downloads/downloads/submissions/25536/versions/1/download/zip?src=addons_ml_desktop_install&amp;profile_id=14169257&amp;license=40758619&amp;release_family=R2020b</downloadUrl>
+  <licenseUrl>https://addons.mathworks.com/registry/v1/e5698820-4a80-11e4-9553-005056977bd0/1.0.0.0/-/license</licenseUrl>
+  <previewImageUrl>https://www.mathworks.com/responsive_image/160/120/0/0/0/cache/matlabcentral/mlc-downloads/downloads/submissions/25536/versions/1/screenshot.png</previewImageUrl>
+  <releaseNotesUrl>https://www.mathworks.com/add-ons/e5698820-4a80-11e4-9553-005056977bd0/d1034754-ea44-08f8-b658-22b590dfae7e/releaseNotes</releaseNotesUrl>
+  <installationFolder>Functions</installationFolder>
+</addOn>

Matlab-Programs/symMinimization.m

+
+function [G, angle, Type, kappa] = symMinimization(print_Input,print_statPoint,print_Output,make_FunctionPlot, InputPath) %(Q_hom,B_eff)
+
+
+syms v1 v2 q1 q2 q3 q12 b1 b2 b3
+
+
+% -------- Options ----------
+% % print_Input = false;  %effective quantities
+% print_Input = true;
+% % print_statPoint = false;
+% print_statPoint = true;
+% print_Minimizer = true;
+% % make_FunctionPlot = false;
+% make_FunctionPlot = true;
+
+print_Uniqueness = false;         
+check_StationaryPoints = false;   % could be added to Input-Parameters..
+compare_with_Classification = false;  %maybe added later --- 
+
+
+%fprintf('Functions to be minimized:')
+f_plus(v1,v2,q1,q2,q3,q12,b1,b2,b3) = q1*v1^4 + q2*v2^4+2*q3*v1^2*v2^2-2*(q1*b1*v1^2+ q2*b2*v2^2+sqrt(2)*q3*b3*v1*v2)...
+                                        + q12*(v1^2*v2^2-b2*v1^2-b1*v2^2+b1*b2);
+f_minus(v1,v2,q1,q2,q3,q12,b1,b2,b3) = q1*v1^4 + q2*v2^4+2*q3*v1^2*v2^2+2*(q1*b1*v1^2+ q2*b2*v2^2+sqrt(2)*q3*b3*v1*v2)...
+                                        + q12*(v1^2*v2^2+b2*v1^2+b1*v2^2+b1*b2);
+
+
+% ---- Fix parameters
+
+
+% Epsilon used:
+epsilon = 1e-8;
+
+
+if ~exist('InputPath','var')
+     % third parameter does not exist, so default it to something
+      absPath = "/home/klaus/Desktop/DUNE/dune-microstructure/outputs";
+ end
+
+
+% 1. Import effective quantities from CellSolver-Code:
+%read as sparse Matrix...
+try %absolutePath
+    Qmat = spconvert(load(absPath + '' + "/QMatrix.txt"));
+    Bmat = spconvert(load(absPath + '' + "/BMatrix.txt"));
+%     fprintf('Use absolute Path')
+catch ME  % use relativePath
+    Qmat = spconvert(load('../outputs/QMatrix.txt'));
+    Bmat = spconvert(load('../outputs/BMatrix.txt'));
+%     fprintf('Use relative Path')
+end
+%convert to full matrix... 
+Qmat = full(Qmat);
+Bmat = full(Bmat);
+
+
+
+
+% --- TODO CHECK: assert if Q is orthotropic ???  check ifq13=q31=q23=q32= 0 ?
+
+
+if print_Input
+    fprintf('effective quadratic form:')
+    Qmat
+    fprintf('effective prestrain')
+    Bmat
+    
+    % check if Q is (close to..) symmetric
+    % könnte Anti-symmetric part berechnen und schauen dass dieser klein?
+    % Test: issymmetric(Qmat) does not work for float matrices?
+    % symmetric part 0.5*(Qmat+Qmat')
+    % anti-symmetric part 0.5*(Qmat-Qmat')
+    if norm(0.5*(Qmat-Qmat'),'fro') < 1e-8
+        fprintf('Qmat (close to) symmetric \n')
+        norm(0.5*(Qmat-Qmat'),'fro') % TEST
+    else
+        fprintf('Qmat not symmetric \n')
+    end
+    
+    
+    % Check if B_eff is diagonal this is equivalent to b3 == 0
+    if abs(Bmat(3)) < 1e-8
+        fprintf('B_eff is diagonal (b3 == 0) \n')
+    else
+        fprintf('B_eff is  NOT diagonal (b3 != 0)  \n')
+    end
+end
+
+
+
+
+% CAST VALUES TO SYM FIRST? This is done anyway..
+% % Substitute effective quantitites      
+f_plus = subs(f_plus,{q1, q2, q3, q12, b1, b2, b3}, {Qmat(1,1), Qmat(2,2), Qmat(3,3), Qmat(1,2), ...
+                                                     Bmat(1), Bmat(2), Bmat(3)});
+
+f_minus = subs(f_minus,{q1, q2, q3, q12, b1, b2, b3}, {Qmat(1,1), Qmat(2,2), Qmat(3,3), Qmat(1,2), ...
+                                                     Bmat(1), Bmat(2), Bmat(3)});
+
+
+% Compute the Gradients 
+df_plusx = diff(f_plus,v1);
+df_plusy = diff(f_plus,v2);
+df_minusx = diff(f_minus,v1);
+df_minusy = diff(f_minus,v2);
+
+% Setup Equations Grad(f) = 0 
+eq1 = df_plusx == 0;
+eq2 = df_plusy == 0;
+eqns_plus = [eq1, eq2];
+eq3 = df_minusx == 0;
+eq4 = df_minusy == 0;
+eqns_minus = [eq3, eq4];
+
+% -------  Symbolically Solve Equations: 
+% More robust (works even for values b_3 ~ 1e-08 ): 
+S_plus = solve(eqns_plus,v1,v2,'MaxDegree' , 5);  
+S_minus = solve(eqns_minus,v1,v2,'MaxDegree' , 5);
+
+A_plus = S_plus.v1;
+B_plus = S_plus.v2;
+A_minus = S_minus.v1;
+B_minus = S_minus.v2;
+
+if check_StationaryPoints
+    %---------- TEST if Grad(f) = 0 ---------------------
+    fprintf('Testing equation grad(f) = 0  with stationary points')
+    for i = 1:size(A_plus,1)
+        fprintf('Testing %d.point (f_plus): ',i )
+        [ double(subs(subs(df_plusx,v1,A_plus(i)),v2,B_plus(i))), double(subs(subs(df_plusy,v1,A_plus(i)),v2,B_plus(i))) ]
+    end
+    for i = 1:size(A_minus,1)
+        fprintf('Testing %d.point (f_minus): ',i )
+        [double(subs(subs(df_minusx,v1,A_minus(i)),v2,B_minus(i))), double(subs(subs(df_minusy,v1,A_minus(i)),v2,B_minus(i)))]
+    end
+    % ------------------------------------
+end
+
+% --- Extract only Real-Solutions
+% fprintf('real stationary points of f_plus:')
+tmp1 = A_plus(imag(double(A_plus))==0 & imag(double(B_plus)) == 0);
+tmp2 = B_plus(imag(double(A_plus))==0 & imag(double(B_plus)) == 0);
+A_plus = tmp1;
+B_plus = tmp2;
+SP_plus = [A_plus,B_plus];
+
+% fprintf('real stationary points of f_minus:')
+tmp1 = A_minus(imag(double(A_minus))==0 & imag(double(B_minus)) == 0);
+tmp2 = B_minus(imag(double(A_minus))==0 & imag(double(B_minus)) == 0);
+A_minus = tmp1;
+B_minus = tmp2;
+SP_minus = [A_minus,B_minus];
+
+% TODO one should use f_plus.subs(A_plus..) to compute function value symbolically?
+% in the end only the stationaryPoints are used.. should be ok to compare function values numerically
+
+% Determine global Minimizer from stationary points:
+% fprintf('function values at stationary points (f_plus):')
+T_plus = arrayfun(@(v1,v2) double(f_plus(v1,v2,q1,q2,q3,q12,b1,b2,b3)),A_plus,B_plus,'UniformOutput', false);
+T_plus = cell2mat(T_plus);
+
+%Test: use Substitution
+% subs(f_plus,{v1, v2}, {A_plus,B_plus})
+
+% fprintf('function values at stationary points (f_minus):')
+T_minus = arrayfun(@(v1,v2) double(f_minus(v1,v2,q1,q2,q3,q12,b1,b2,b3)),A_minus,B_minus,'UniformOutput', false);
+T_minus = cell2mat(T_minus);
+
+%Test: use Substitution
+% T_minus = subs(f_minus,{v1, v2}, {A_minus,B_minus})
+% double(T_minus)
+
+if print_statPoint
+    fprintf('real stationary points of f_plus: ')
+%     SP_Plus     %alternative: output as symbolic (can be unwieldy)
+    double(SP_plus)
+    fprintf('real stationary points of f_minus:')
+%     SP_Minus     %alternative: output as symbolic (can be unwieldy)
+    double(SP_minus)
+    fprintf('function values at stationary points (f_plus):')
+    T_plus
+    fprintf('function values at stationary points (f_minus):')
+    T_minus
+end
+
+% --- Find Stationary Point(s) with minimum Value 
+[Min_plus,MinIdx_plus] = min(T_plus, [], 'all', 'linear');    %find one min...
+[Min_minus,MinIdx_minus] = min(T_minus, [], 'all', 'linear');
+% [Min_minus,MinIdx_minus] = min(T_minus)                     % works with symbolic too
+
+% Compare Minimizers of f_plus & f_minus
+[globalMinimizerValue,GlobalIdx] = min([Min_plus,Min_minus]); 
+
+if GlobalIdx == 1     %Min_plus   % i.e. Global Minimizer is given by f_plus
+    GlobalMinimizer = SP_plus(MinIdx_plus,:);
+    sign = 1.0;
+elseif GlobalIdx == 2  %Min_minus % i.e. Global Minimizer is given by f_minus
+    GlobalMinimizer = SP_minus(MinIdx_minus,:);
+    sign = -1.0; 
+end
+
+% ------ Check if there are more SP with the same value...
+ MinIndices_minus = find(T_minus(:) == globalMinimizerValue);    % Find indices of All Minima
+ MinIndices_plus  = find(T_plus(:) == globalMinimizerValue);    % Find indices of All Minima                   
+ numMinSP_minus = size(MinIndices_minus,1);   % One of these is always >= 2 due to the structure of the roots..
+ numMinSP_plus  = size(MinIndices_plus,1);
+    
+%     AllMinSP_minus = SP_minus(MinIndices_minus,:)
+%     AllMinSP_minus = double(SP_minus(MinIndices_minus,:))
+%     AllMin = T_minus(MinIndices)  %bereits klar dass diese selben funktionswert haben..
+      
+    Minimizer = sign*(GlobalMinimizer'*GlobalMinimizer);  % global minimizing Matrix G*
+    MinimizerCount = 1;
+    % different Stationary Points might correspond to the same minimizing
+    % Matrix G*... check this: 
+    
+    % Compare only with other StationaryPoints/Minimizers
+    % remove Index of Minimizer
+    if GlobalIdx == 1     
+        MinIndices_plus = MinIndices_plus(MinIndices_plus~=MinIdx_plus);
+    elseif GlobalIdx == 2  
+        MinIndices_minus = MinIndices_minus(MinIndices_minus~=MinIdx_minus);
+    end
+    
+    MinIndices = cat(1,MinIndices_plus,MinIndices_minus);  %[Minimizers-Indices f_plus, Minimizer-Indices f_minus]
+    
+    for i = 1:(numMinSP_minus+numMinSP_plus-1)  % -1: dont count Minimizer itself.. 
+        idx = MinIndices(i);   
+        
+        if i > numMinSP_plus
+            SP = SP_minus(idx,:);
+        else
+            SP = SP_plus(idx,:); 
+        end
+        
+%         SP_value = T_minus(idx) % not needed? 
+        Matrix = sign*(SP'*SP);
+
+        if norm(double(Matrix-Minimizer),'fro') < 1e-8   %check is this sufficient here?
+%             fprintf('both StationaryPoints correspond to the same(Matrix-)Minimizer')
+        else
+%             fprintf('StationaryPoint corresponds to a different (Matrix-)Minimizer')
+            MinimizerCount = MinimizerCount + 1;
+        end
+    end
+% ----------------------------------------------------------------------------------------------------------------
+
+
+
+% Output Uniqueness of Minimizers:
+if print_Uniqueness
+    if MinimizerCount == 1
+        fprintf('Unique Minimzier')
+    elseif MinimizerCount == 2
+        fprintf('Two Minimziers')
+    else
+        fprintf('1-Parameter family of Minimziers')
+    end
+end
+
+
+
+
+
+% --- determine the angle of the Minimizer
+% a1 = Minimizer(1,1)
+% a2 = Minimizer(2,2)
+a1 = double(Minimizer(1,1));
+a2 = double(Minimizer(2,2));
+
+% compute the angle <(e,e_1) where Minimizer = kappa* (e (x) e)
+e = [sqrt((a1/(a1+a2))), sqrt((a2/(a1+a2)))];    % always positive under sqrt here .. basically takes absolute value here
+angle = atan2(e(2), e(1)); 
+
+% compute curvature kappa
+kappa = (a1 + a2);
+
+% % CHeck off diagonal entries:
+% sqrt(a1*a2);
+% double(Minimizer);
+
+G = double(Minimizer);
+
+
+
+% --- "Classification" / Determine the TYPE of Minimizer by using 
+% the number of solutions (Uniqueness?)
+% the angle (axial- or non-axial Minimizer)
+
+% (Alternative compute det[GlobalMinimizer' e1']  where e1 = [1 0] ?)
+
+% Check Uniqueness -- Options: unique/twoMinimizers/1-ParameterFamily
+if MinimizerCount == 1
+%     fprintf('Unique Minimzier')
+    % Check if Minimizer is axial or non-axial:
+    if (abs(angle-pi/2) < 1e-8 || abs(angle) < 1e-8) % axial Minimizer
+     Type = 3;
+    else % non-axial Minimizer   
+     Type = 1;
+    end
+elseif MinimizerCount == 2
+%     fprintf('Two Minimziers')
+    % Check if Minimizer is axial or non-axial:
+    if (abs(angle-pi/2) < 1e-8 || abs(angle) < 1e-8) % axial Minimizer
+        Type = 3;
+    else % non-axial Minimizer   
+        fprintf('ERROR: Two non-axial Minimizers cannot happen!')
+    end
+else
+%     fprintf('1-Parameter family of Minimziers')
+    % Check if Minimizer is axial or non-axial:
+    if (abs(angle-pi/2) < 1e-8 || abs(angle) < 1e-8) % axial Minimizer
+%         fprintf('ERROR: axial Minimizers cannot happen for 1-Parameter Family!')
+    else % non-axial Minimizer   
+        Type = 2;
+    end
+end
+% ------------------------------------------------------------------------------------------------------
+
+
+
+
+if print_Output
+    fprintf(' --------- Output symMinimization --------')
+    fprintf('Global Minimizer v: (%d,%d) \n', GlobalMinimizer(1),GlobalMinimizer(2) )
+    fprintf('Global Minimizer Value f(v): %d \n', sym(globalMinimizerValue) ) %cast to symbolic
+    %     fprintf('Global Minimizer Value : %d', globalMinimizerValue )
+    
+    fprintf('Global Minimizer G: \n' )
+    G 
+    fprintf("Angle = %d \n", angle)
+    fprintf("Curvature = %d \n", kappa)
+    fprintf("Type = %i \n", Type)
+    fprintf(' --------- -------------------- --------')
+end
+
+
+
+if make_FunctionPlot  
+    fsurf(@(x,y) f_plus(x,y,q1,q2,q3,q12,b1,b2,b3)) % Plot functions
+    hold on
+    plot3(double(A_plus),double(B_plus),T_plus,'g*')
+    %Plot GlobalMinimizer:
+    hold on
+    plot3(double(GlobalMinimizer(1)),double(GlobalMinimizer(2)),globalMinimizerValue, 'o', 'Color','c')
+    % view(90,0)
+    % view(2)
+
+    figure
+    fsurf(@(x,y) f_minus(x,y,q1,q2,q3,q12,b1,b2,b3))
+    hold on
+    plot3(double(A_minus),double(B_minus),T_minus,'g*')
+    hold on
+    plot3(double(GlobalMinimizer(1)), double(GlobalMinimizer(2)),globalMinimizerValue, 'o', 'Color','c')
+end
+
+
+return 
+
+
+% Write symbolic solution to txt-File in Latex format
+% fileID = fopen('txt.txt','w');
+% fprintf(fileID,'%s' , latex(S_plus.v1));
+% fclose(fileID);
+
+
+
+
+
+
+

Matlab-Programs/symSolveSystem.m

+
+
+syms q1 q2 q3 q12 b1 b2  a1 a2 
+
+% eqn1 = q1 * a1 + (q3 + (q12/2)) *a2 == -2*q1*b1 - q12*b2
+% 
+% eqn2 = (q3 + (q12/2)) * a1 + q2 *a2 == -2*q2*b2 - q12*b1
+
+
+eqn1 = q1 * a1 + (q3 + (q12/2)) *a2 == q1*b1 + (q12*b2/2)
+
+eqn2 = (q3 + (q12/2)) * a1 + q2 *a2 == q2*b2 + (q12*b1/2)
+
+
+
+[A,B] = equationsToMatrix([eqn1, eqn2], [a1,a2])
+
+X = linsolve(A,B)
+
+
+% check special case
+fprintf('special case q12 = 0 ') 
+subs(X,q12,0)
\ No newline at end of file

Paraview-Scripts/ParaViewSettings.txt

+
+Colormap: Cool-to-Warm
+
+Representation: Point-Gaussian
+Opacity: 0.01
+PointSize: 2
+Gaussian-radius: 0.0075
+Shader-Preset: Plain-Circle

Python-Scripts/1-ParameterFamily-Minimizers.py

+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 matplotlib.ticker as tickers
+import matplotlib as mpl
+from matplotlib.ticker import MultipleLocator,FormatStrFormatter,MaxNLocator
+from mpl_toolkits.mplot3d import Axes3D
+import pandas as pd
+import matplotlib.colors as mcolors
+from matplotlib import cm
+
+from mpl_toolkits.mplot3d.proj3d import proj_transform
+# from mpl_toolkits.mplot3d.axes3d import Axes3D
+from matplotlib.text import Annotation
+from matplotlib.patches import FancyArrowPatch
+
+# Extra packages :
+# from HelperFunctions import *
+# from ClassifyMin import *
+# from subprocess import Popen, PIPE
+#import sys
+
+###################### Documentation #########################
+
+#..... add description here
+
+###########################################################
+
+
+def rot(v,alpha):
+
+#rotate about axis v with degree deg in radians:
+
+
+    tmp = np.array([ [v[0]**2*(1-np.cos(alpha))+np.cos(alpha), v[0]*v[1]*(1-np.cos(alpha))-v[2]*np.sin(alpha), v[0]*v[2]*(1-np.cos(alpha))+ v[1]*np.sin(alpha) ],
+         [v[0]*v[1]*(1-np.cos(alpha))+v[2]*np.sin(alpha), v[1]**2*(1-np.cos(alpha))+np.cos(alpha), v[1]*v[2]*(1-np.cos(alpha))+v[0]*np.sin(alpha) ],
+         [v[2]*v[0]*(1-np.cos(alpha))-v[1]*np.sin(alpha), v[2]*v[1]*(1-np.cos(alpha))+v[0]*np.sin(alpha) , v[2]**2*(1-np.cos(alpha))+np.cos(alpha) ] ])
+
+    return tmp
+
+
+
+def rotate_data(X, R):
+#rotate about axis v with degree deg in radians:
+# X : DataSet
+# R : RotationMatrix
+    print('ROTATE DATA FUNCTION ---------------')
+
+    rot_matrix = R
+    # print('rot_matrix:', rot_matrix)
+    # print('rot_matrix.shape:', rot_matrix.shape)
+    # print('X', X)
+    # print('shape of X[0]', X.shape[0])
+    B = np.dot(rot_matrix, X.reshape(rot_matrix.shape[1],-1))
+    # print('shape of B', B.shape)
+    # print('B',B)
+    # print('B[0,:]', B[0,:])
+    # print('B[0,:].shape', B[0,:].shape)
+    Out = np.array([B[0,:].reshape(X.shape[1],X.shape[2]), B[1,:].reshape(X.shape[1],X.shape[2]), B[2,:].reshape(X.shape[1],X.shape[2])])
+    print('shape of Out', Out.shape)
+
+    return Out
+
+# def rotate_data(X, v,alpha): #(Old Version)
+# #rotate about axis v with degree deg in radians:
+# # X : DataSet
+#     print('ROTATE DATA FUNCTION ---------------')
+#     # v = np.array([1,0,0])
+#     # rotM = rot(v,np.pi/2)
+#     # print('rotM:', rotM)
+#     rot_matrix = rot(v,alpha)
+#     # print('rot_matrix:', rot_matrix)
+#     # print('rot_matrix.shape:', rot_matrix.shape)
+#
+#     # print('X', X)
+#     # print('shape of X[0]', X.shape[0])
+#     B = np.dot(rot_matrix, X.reshape(rot_matrix.shape[1],-1))
+#
+#     # print('shape of B', B.shape)
+#     # print('B',B)
+#     # print('B[0,:]', B[0,:])
+#     # print('B[0,:].shape', B[0,:].shape)
+#     Out = np.array([B[0,:].reshape(X.shape[1],X.shape[2]), B[1,:].reshape(X.shape[1],X.shape[2]), B[2,:].reshape(X.shape[1],X.shape[2])])
+#     print('shape of Out', Out.shape)
+#
+#     return Out
+
+
+# def translate_data(X, v):  ...
+# #rotate about axis v with degree deg in radians:
+# # X : DataSet
+#     print('ROTATE DATA FUNCTION ---------------')
+#     # v = np.array([1,0,0])
+#     # rotM = rot(v,np.pi/2)
+#     # print('rotM:', rotM)
+#
+#     print('X', X)
+#     print('shape of X[0]', X.shape[0])
+#
+#     Out = X + v
+#     return Out
+
+
+def u(x,kappa,e):
+
+    tmp = (x.dot(e))*kappa
+    # print('tmp for u',tmp)
+    if kappa == 0 :
+        tmp = np.array([0*x[0],  x[0]*e[0] + x[1]*e[1], x[1]*e[0] - x[0]*e[1] ])
+    else :
+        tmp = np.array([-(1/kappa)*np.cos(tmp)+(1/kappa),  (1/kappa)*np.sin(tmp), -x[0]*e[1]+x[1]*e[0] ])
+    return tmp
+
+
+
+
+def grad_u(x,kappa,e):
+
+    tmp = (x.dot(e))*kappa
+    # print('tmp',tmp)
+
+    grad_u = np.array([ [np.sin(tmp)*e[0], np.sin(tmp)*e[1]], [np.cos(tmp)*e[0], np.cos(tmp)*e[1]], [-e[1], e[0]] ])
+    # print('produkt', grad_u.dot(e) )
+    mapped_e = grad_u.dot(e)
+    # print('mapped_e:', mapped_e)
+    # print('siize of mapped_e', mapped_e.shape)
+    # mapped_e = mapped_e.transpose()
+    # print('mapped_e:', mapped_e)
+    # print('siize of mapped_e', mapped_e.shape)
+    return mapped_e
+
+def compute_normal(x,kappa,e):
+    tmp = (x.dot(e))*kappa
+    partial1_u = np.array([ np.sin(tmp)*e[0] ,np.cos(tmp)*e[0], -e[1] ])
+    partial2_u = np.array([ np.sin(tmp)*e[1], np.cos(tmp)*e[1], e[0]      ])
+    normal = np.cross(partial1_u,partial2_u)
+    # print('normal=',normal)
+    return normal
+
+
+
+class Annotation3D(Annotation):
+    def __init__(self, text, xyz, *args, **kwargs):
+        super().__init__(text, xy=(0, 0), *args, **kwargs)
+        self._xyz = xyz
+
+    def draw(self, renderer):
+        x2, y2, z2 = proj_transform(*self._xyz, self.axes.M)
+        self.xy = (x2, y2)
+        super().draw(renderer)
+
+def _annotate3D(ax, text, xyz, *args, **kwargs):
+    '''Add anotation `text` to an `Axes3d` instance.'''
+
+    annotation = Annotation3D(text, xyz, *args, **kwargs)
+    ax.add_artist(annotation)
+
+setattr(Axes3D, 'annotate3D', _annotate3D)
+
+class Arrow3D(FancyArrowPatch):
+
+    def __init__(self, x, y, z, dx, dy, dz, *args, **kwargs):
+        super().__init__((0, 0), (0, 0), *args, **kwargs)
+        self._xyz = (x, y, z)
+        self._dxdydz = (dx, dy, dz)
+
+    def draw(self, renderer):
+        x1, y1, z1 = self._xyz
+        dx, dy, dz = self._dxdydz
+        x2, y2, z2 = (x1 + dx, y1 + dy, z1 + dz)
+
+        xs, ys, zs = proj_transform((x1, x2), (y1, y2), (z1, z2), self.axes.M)
+        self.set_positions((xs[0], ys[0]), (xs[1], ys[1]))
+        super().draw(renderer)
+
+
+def _arrow3D(ax, x, y, z, dx, dy, dz, *args, **kwargs):
+    '''Add an 3d arrow to an `Axes3D` instance.'''
+
+    arrow = Arrow3D(x, y, z, dx, dy, dz, *args, **kwargs)
+    ax.add_artist(arrow)
+
+setattr(Axes3D, 'arrow3D', _arrow3D)
+################################################################################################################
+################################################################################################################
+################################################################################################################
+
+
+
+q1=1;
+q2=2;
+q12=1/2;
+q3=((4*q1*q2)**0.5-q12)/2;
+# H=[2*q1,q12+2*q3;q12+2*q3,2*q2];
+
+H = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+A = np.array([[q1,1/2*q12], [1/2*q12,q2] ])
+abar = np.array([q12+2*q3, 2*q2])
+abar = (1.0/math.sqrt((q12+2*q3)**2+(2*q2)**2))*abar
+
+print('abar:',abar)
+
+b = np.linalg.lstsq(A, abar)[0]
+print('b',b)
+
+
+# print('abar:',np.shape(abar))
+# print('np.transpose(abar):',np.shape(np.transpose(abar)))
+sstar = (1/(q1+q2))*abar.dot(A.dot(b))
+# sstar = (1/(q1+q2))*abar.dot(tmp)
+print('sstar', sstar)
+abarperp= np.array([abar[1],-abar[0]])
+print('abarperp:',abarperp)
+
+print('----------------------------')
+
+# ----------------------------------------------------------------
+
+N=1000;
+T = np.linspace(-sstar*(q12+2*q3)/(2*q2), sstar*(2*q2)/(q12+2*q3), num=N)
+print('T:', T)
+
+kappas = []
+alphas = []
+# G.append(float(s[0]))
+
+G_container = []
+abar_container = []
+e_container = []
+
+
+for t in T :
+
+    abar_current = sstar*abar+t*abarperp;
+    # print('abar_current', abar_current)
+    abar_current[abar_current < 1e-10] = 0
+    # print('abar_current', abar_current)
+    # G = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+    G = [abar_current[0], abar_current[1] , (2*abar_current[0]*abar_current[1])**0.5 ]
+    G_container.append(G)
+    abar_container.append(abar_current)
+    e = [(abar_current[0]/(abar_current[0]+abar_current[1]))**0.5, (abar_current[1]/(abar_current[0]+abar_current[1]))**0.5]
+    e_container.append(e)
+    kappa = abar_current[0]+abar_current[1]
+    alpha = math.atan2(e[1], e[0])
+    # print('angle current:', alpha)
+    kappas.append(kappa)
+    alphas.append(alpha)
+
+
+G_container = np.array(G_container)
+abar_container = np.array(abar_container)
+
+e_container = np.array(e_container)
+
+print('G_container', G_container)
+print('G_container.shape', G_container.shape)
+
+# idx_1 = np.where(alphas == np.pi/4)
+idx_1 = np.where(np.round(alphas,2) == round(np.pi/3,2))
+idx_2 = np.where(np.round(alphas,2) == 0.0)
+idx_3 = np.where(np.round(alphas,2) == round(np.pi/4,2))
+
+# idx_3 = np.where(alphas == 0)
+
+print('Index idx_1:', idx_1)
+print('Index idx_2:', idx_2)
+print('Index idx_3:', idx_3)
+print('Index idx_1[0][0]:', idx_1[0][0])
+print('Index idx_2[0][0]:', idx_2[0][0])
+print('Index idx_3[0][0]:', idx_3[0][0])
+
+alphas = np.array(alphas)
+kappas = np.array(kappas)
+
+
+# print('kappas:',kappas)
+# print('alphas:',alphas)
+print('min alpha:', min(alphas))
+print('min kappa:', min(kappas))
+
+
+print('G_container[idx_1[0][0]]', G_container[idx_1[0][0]])
+print('G_container[idx_2[0][0]]', G_container[idx_2[0][0]])
+print('G_container[idx_3[0][0]]', G_container[idx_3[0][0]])
+
+
+print('e_container[idx_1[0][0]]', e_container[idx_1[0][0]])
+print('e_container[idx_2[0][0]]', e_container[idx_2[0][0]])
+print('e_container[idx_3[0][0]]', e_container[idx_3[0][0]])
+
+
+idx = 2
+
+e = e_container[idx_1[0][0]]
+e = e_container[idx_2[0][0]]
+# e = e_container[idx_3[0][0]]
+kappa = kappas[idx_1[0][0]]
+kappa = kappas[idx_2[0][0]]
+# kappa = kappas[idx_3[0][0]]
+
+angle = alphas[idx_1[0][0]]
+angle = alphas[idx_2[0][0]]
+# angle = alphas[idx_3[0][0]]
+
+
+# kappa = kappa*2
+
+print('kappa:',kappa)
+print('angle:',angle)
+
+#### TEST apply reflection
+#
+# G_tmp = G_container[idx_1[0][0]]
+#
+# print('G_tmp', G_tmp)
+#
+# # Basis:
+# G_1 = np.array([[1.0,0.0], [0.0,0.0]])
+# G_2 = np.array([[0.0,0.0], [0.0,1.0]])
+# G_3 = (1/np.sqrt(2))*np.array([[0.0,1.0], [1.0,0.0]])
+# print('G_1', G_1)
+# print('G_2', G_2)
+# print('G_3', G_3)
+#
+# G = G_tmp[0] * G_1 + G_tmp[1]*G_2 + G_tmp[2]*G_3
+# print('G:', G )
+#
+# T = np.array([[1.0 , -1.0] , [-1.0,1.0]])
+#
+# TG = np.multiply(T,G)
+# print('TG', TG)
+#
+#
+#
+# v = np.array([np.sqrt(TG[0][0]),np.sqrt(TG[1][1]) ])
+# print('v', v)
+# print('norm(v):', np.linalg.norm(v))
+# norm_v = np.linalg.norm(v)
+#
+# kappa = norm_v**2
+#
+# e = (1/norm_v)*v
+# print('e:', e)
+# print('kappa:', kappa)
+
+
+
+
+
+
+
+
+reflected_e = np.array([e[0], -1*e[1]])
+e = reflected_e                                         # Correct?! Reflect e on x-Axis ??!
+print('reflected_e:', reflected_e)
+
+
+############################################################################################################################################
+####################################################################### KAPPA NEGATIVE ####################################################
+############################################################################################################################################
+# kappa = -2
+num_Points = 200
+num_Points = 100
+
+
+# e = np.array([1,0])
+# e = np.array([0,1])
+# e = np.array([1/np.sqrt(2),1/np.sqrt(2)])
+# e = np.array([1/2,np.sqrt(3)/2])
+# e = np.array([np.sqrt(3)/2,1/2])
+# e = np.array([-1,0])
+# e = np.array([0,-1])
+
+###--- Creating dataset
+x = np.linspace(-2,2,num_Points)
+x = np.linspace(-3,3,num_Points)
+# x = np.linspace(-4,4,num_Points)
+
+# x = np.linspace(-1.5,1.5,num_Points)
+# x = np.linspace(-1,1,num_Points)
+y = np.linspace(-1/2,1/2,num_Points)
+y = np.linspace(-1/4,1/4,num_Points)
+
+print('type of x', type(x))
+print('max of x:', max(x))
+print('max of y:', max(y))
+# print('x:', x)
+
+x1, x2 = np.meshgrid(x,y)
+zero = 0*x1
+
+if kappa == 0 :
+    u1 = 0*x1
+    u2 = x1*e[0] + x2*e[1]
+    u3 = x2*e[0] - x1*e[1]
+
+else :
+    u1 = -(1/kappa)*np.cos(kappa*(x1*e[0]+x2*e[1])) + (1/kappa)
+    u2 = (1/kappa)*np.sin(kappa*(x1*e[0]+x2*e[1]))
+    u3 = x2*e[0] -x1*e[1]
+
+# print('np.size(u1)',np.size(u1))
+# print('u1.shape',u1.shape)
+# colorfunction=(u1**2+u2**2)
+# print('colofunction',colorfunction)
+
+# print('u1.size:',np.size(u1))
+# tmp = np.ones(np.size(u1))*kappa
+# print('np.size(tmp)',np.size(tmp))
+B = np.full_like(u1, 1)
+# colorfunction=(u3)                                              # TODO Color by angle
+# colorfunction=(np.ones(np.size(u1))*kappa)
+colorfunction=(B*kappa)
+# print('colofunction',colorfunction)
+norm=mcolors.Normalize(colorfunction.min(),colorfunction.max())
+
+
+# -----------------------------------------------------
+# Display the mesh
+fig = plt.figure()
+
+
+width = 6.28 *0.5
+width = 6.28 * 0.333
+height = width / 1.618
+height = width / 2.5
+height = width
+
+
+
+ax = plt.axes(projection ='3d', adjustable='box')
+
+
+###---TEST MAP e-vectprs!
+# e1 = np.array([1,0])
+# e2 = np.array([0,1])
+# e3 = np.array([1/np.sqrt(2),1/np.sqrt(2)])
+# e1 = np.array([0,1])
+# e2 = np.array([-1,0])
+# e3 = np.array([-1/np.sqrt(2),1/np.sqrt(2)])
+# e1_mapped = u(e1,kappa,e1)
+# e2_mapped = u(e2,kappa,e2)
+# e3_mapped = u(e3,kappa,e3)
+# print('e1 mapped:',e1_mapped)
+# print('e2 mapped:',e2_mapped)
+# print('e3 mapped:',e3_mapped)
+### -----------------------------------
+
+#--e1 :
+# Rotation_angle = -np.pi/2
+# Rotation_vector = np.array([0,1,0])
+
+#--e2:
+Rotation_angle = np.pi/2
+Rotation_vector = np.array([1,0,0])
+
+###--e = np.array([1/np.sqrt(2),1/np.sqrt(2)])
+# Rotation_angle = -np.pi/2
+# Rotation_vector = np.array([1,0,0])
+# #2te rotation :
+# Rotation_angle = np.pi/4
+# Rotation_vector = np.array([0,0,1])
+
+
+
+Rotation_angle = -np.pi/2
+Rotation_angle = 0
+# Rotation_angle = np.pi/2
+Rotation_vector = np.array([0,1,0])
+Rotation_vector = np.array([1,0,0])
+
+# rot(np.array([0,1,0]),np.pi/2)
+
+# ZERO ROTATION
+Rotation = rot(np.array([0,1,0]),0)
+
+
+
+# TEST :
+
+#DETERMINE ANGLE:
+angle = math.atan2(e[1], e[0])
+print('angle:', angle)
+
+## GENERAL TRANSFORMATION / ROTATION:
+Rotation = rot(np.array([0,0,1]),angle).dot(rot(np.array([0,1,0]),-np.pi/2))
+
+# Rotation = rot(np.array([0,0,1]),+np.pi/4).dot(Rotation)
+# Rotation = rot(np.array([0,0,1]),+np.pi/16).dot(Rotation)
+
+
+
+### if e1:
+# Rotation = rot(np.array([0,0,1]),-np.pi/4).dot(Rotation)
+# Rotation = rot(np.array([0,0,1]),+np.pi/16).dot(Rotation)
+
+# Add another rotation around z-axis:
+# Rotation = rot(np.array([0,0,1]),+np.pi).dot(Rotation)
+# Rotation = rot(np.array([0,0,1]),+np.pi/4).dot(Rotation)
+
+
+# Rotation = rot(np.array([0,0,1]),+np.pi/8).dot(Rotation)
+
+#e3 :
+# Rotation = rot(np.array([0,1,0]),-np.pi/2)
+# Rotation = rot(np.array([0,0,1]),np.pi/4).dot(rot(np.array([0,1,0]),-np.pi/2))
+
+# Rotation = rot(np.array([0,0,1]),np.pi/4)
+# Rotation = rot(np.array([1,0,0]),np.pi/4)
+#### if e1 :
+# Rotation = rot(np.array([0,1,0]),-np.pi/2)
+#### if e2:
+# Rotation = rot(np.array([0,1,0]),-np.pi/2).dot(rot(np.array([1,0,0]),-np.pi/2))
+# # #### if e3 :
+# zufall dass np.pi/4 genau dem Winkel angle alpha entspricht?:
+# (würde) bei e_2 keinen Unterschied machen um z achse zu rotieren?!
+
+# Rotation = rot(np.array([0,0,1]),np.pi/4).dot(rot(np.array([0,1,0]),-np.pi/2).dot(rot(np.array([1,0,0]),-np.pi/2)))
+# Rotation = rot(np.array([0,0,1]),np.pi/2).dot(rot(np.array([0,1,0]),-np.pi/2).dot(rot(np.array([1,0,0]),-np.pi/2)))
+
+# Rotation = rot(np.array([1,0,0]),np.pi/2)
+
+# Rotation_vector = e3_mapped  #TEST
+# Rotation_vector = np.array([-1/np.sqrt(2),1/np.sqrt(2)])
+# Rotation_vector = np.array([0,0,1])
+
+# v = np.array([1,0,0])
+# X = np.array([u1,u2,u3])
+
+
+
+
+# T = rotate_data(np.array([u1,u2,u3]),Rotation_vector,Rotation_angle)
+T = rotate_data(np.array([u1,u2,u3]),Rotation)
+
+# ax.plot_surface(T[0], T[1], T[2], color = 'w', rstride = 2, cstride = 2, facecolors=cm.brg(colorfunction), alpha=.4, zorder=4)
+# ax.plot_surface(T[0], T[1], T[2], color = 'w', rstride = 1, cstride = 1, facecolors=cm.viridis(colorfunction), alpha=.4, zorder=4)
+
+
+###---- PLOT PARAMETER-PLANE:
+# ax.plot_surface(x1,x2,zero,color = 'w', rstride = 1, cstride = 1 )
+
+
+print('------------------ Kappa : ', kappa)
+
+#midpoint:
+midpoint = np.array([(max(x)+min(x))/2,(max(y)+min(y))/2])
+print('midpoint',midpoint)
+
+# Map midpoint:
+midpoint_mapped = u(midpoint,kappa,e)
+print('mapped midpoint', midpoint_mapped)
+
+#map origin
+origin = np.array([0,0])
+origin_mapped = u(origin,kappa,e)
+
+
+mapped_e = grad_u(midpoint,kappa,e)
+normal = compute_normal(midpoint,kappa,e)
+
+print('mapped_e', mapped_e)
+print('normal',normal )
+
+#
+# mapped_e = Rotation.dot(mapped_e)
+# normal = Rotation.dot(normal)
+
+
+# Plot Mapped_midPoint
+# ax.plot(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],    # data
+# marker='o',     # each marker will be rendered as a circle
+# markersize=4,   # marker size
+# markerfacecolor='orange',   # marker facecolor
+# markeredgecolor='black',  # marker edgecolor
+# markeredgewidth=1,       # marker edge width
+# linewidth=1,
+# zorder=4)          # line width
+
+# ax.quiver([midpoint_mapped[0]], [midpoint_mapped[1]], [midpoint_mapped[2]], [mapped_e[0]], [mapped_e[1]], [mapped_e[2]], color="red")
+# ax.quiver([midpoint_mapped[0]], [midpoint_mapped[1]], [midpoint_mapped[2]], [normal[0]], [normal[1]], [normal[2]], color="blue")
+
+# ax.arrow3D(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],
+#            mapped_e[0],mapped_e[1],mapped_e[2],
+#            mutation_scale=15,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='green',
+#            lw = 2,
+#            ec ='green',
+#            zorder=3)
+#
+# ax.arrow3D(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],
+#            normal[0],normal[1],normal[2],
+#            mutation_scale=15,
+#             lw = 2,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='blue',
+#            ec ='blue',
+#            zorder = 3)
+
+
+###-- TEST Rotation :
+# v = np.array([1,0,0])
+# t = np.array([0,1,0])
+#
+# ax.arrow3D(0,0,0,
+#            t[0],t[1],t[2],
+#            mutation_scale=10,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='blue',
+#            ec ='blue')
+#
+# # e_extend
+#
+# rotM = rot(v,np.pi/2)
+#
+# print('rotM:', rotM)
+#
+# rot_t = rotM.dot(t)
+#
+# print('rot_t:', rot_t)
+#
+# ax.arrow3D(0,0,0,
+#            rot_t[0],rot_t[1],rot_t[2],
+#            mutation_scale=10,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='blue',
+#            ec ='blue')
+
+### -------------------------------------------
+
+############################################################################################################################################
+####################################################################### KAPPA POSITIVE  ####################################################
+############################################################################################################################################
+
+# kappa = (-1)*kappa
+
+if kappa == 0 :
+    u1 = 0*x1
+    u2 = x1*e[0] + x2*e[1]
+    u3 = x2*e[0] - x1*e[1]
+else :
+    u1 = -(1/kappa)*np.cos(kappa*(x1*e[0]+x2*e[1])) + (1/kappa)
+    u2 = (1/kappa)*np.sin(kappa*(x1*e[0]+x2*e[1]))
+    u3 = x2*e[0] -x1*e[1]
+# ax.plot_surface(u1, u2, u3, color = 'w', rstride = 1, cstride = 1, facecolors=cm.autumn(colorfunction), alpha=.3)  ##This one!
+
+
+# T = rotate_data(X,Rotation_vector,Rotation_angle)
+
+T = rotate_data(np.array([u1,u2,u3]),Rotation)
+# T = rotate_data(T,np.array([0,1,0]),Rotation_angle)
+# T = rotate_data(T,np.array([0,0,1]),-1*Rotation_angle/2)
+
+# ax.plot_surface(T[0], T[1], T[2], rstride = 1, cstride = 1, facecolors=cm.autumn(colorfunction), alpha=.4, zorder=4, antialiased=False)
+# ax.plot_surface(T[0], T[1], T[2], rstride = 1, cstride = 1, facecolors=cm.autumn(colorfunction), alpha=.4, zorder=4, antialiased=True)
+# ax.plot_surface(T[0], T[1], T[2], rstride = 2, cstride = 2, facecolors=cm.autumn(colorfunction), alpha=.4, zorder=4)
+# ax.plot_surface(T[0], T[1], T[2], rstride = 10, cstride = 10, facecolors=cm.brg(colorfunction), alpha=.8, zorder=4)
+ax.plot_surface(T[0], T[1], T[2], rstride = 5, cstride = 5, color='orange', alpha=.8, zorder=4)
+# ax.plot_surface(T[0], T[1], T[2], rstride = 10, cstride = 10, color='blue', alpha=.8, zorder=4, shade=True)
+# ax.plot_surface(T[0], T[1], T[2], rstride = 1, cstride = 1, facecolors=cm.autumn(colorfunction), alpha=.4, zorder=4, shade=True)
+# ax.plot_surface(T[0], T[1], T[2], color = 'w', rstride = 1, cstride = 1, facecolors=cm.autumn(colorfunction), alpha=0.8, zorder=4)
+# ax.plot_surface(T[0], T[1], T[2],  rstride = 1, cstride = 1, facecolors=cm.autumn(colorfunction), alpha=1, zorde5r=5)
+
+# midpoint = np.array([(max(x)+min(x))/2,(max(y)+min(y))/2])
+# print('midpoint',midpoint)
+print('------------------ Kappa : ', kappa)
+# Map midpoint:
+midpoint_mapped = u(midpoint,kappa,e)
+print('mapped midpoint', midpoint_mapped)
+
+#map origin
+origin = np.array([0,0])
+origin_mapped = u(origin,kappa,e)
+
+
+mapped_e = grad_u(midpoint,kappa,e)
+normal = compute_normal(midpoint,kappa,e)
+
+print('mapped_e', mapped_e)
+print('normal',normal )
+
+
+#
+mapped_e = Rotation.dot(mapped_e)
+normal = Rotation.dot(normal)
+
+
+# Plot MIDPOINT:
+# ax.plot(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],    # data
+# marker='o',     # each marker will be rendered as a circle
+# markersize=4,   # marker size
+# markerfacecolor='orange',   # marker facecolor
+# markeredgecolor='black',  # marker edgecolor
+# markeredgewidth=1,       # marker edge width
+# linewidth=1,
+# zorder=5)          # line width
+
+
+
+# mapped_e = grad_u(midpoint,kappa,e)
+# normal = compute_normal(midpoint,kappa,e)
+
+
+# ax.arrow3D(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],
+#            mapped_e[0],mapped_e[1],mapped_e[2],
+#            mutation_scale=15,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='green',
+#            lw = 1.5,
+#            ec ='green',
+#            zorder=5)
+#
+# ax.arrow3D(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],
+#            normal[0],normal[1],normal[2],
+#            mutation_scale=15,
+#             lw = 1.5,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='blue',
+#            ec ='blue',
+#            zorder = 5)
+
+
+############################################################################################################################################
+####################################################################### KAPPA ZERO #########################################################
+############################################################################################################################################
+kappa = 0
+
+if kappa == 0 :
+    u1 = 0*x1
+    u2 = x1*e[0] + x2*e[1]
+    u3 = x2*e[0] - x1*e[1]
+else :
+    u1 = -(1/kappa)*np.cos(kappa*(x1*e[0]+x2*e[1])) + (1/kappa)
+    u2 = (1/kappa)*np.sin(kappa*(x1*e[0]+x2*e[1]))
+    u3 = x2*e[0] -x1*e[1]
+# ax.plot_surface(u1, u2, u3,  rstride = 1, cstride = 1, color = 'white', alpha=0.85)
+
+# T = rotate_data(np.array([u1,u2,u3]),Rotation_vector,Rotation_angle)
+
+T = rotate_data(np.array([u1,u2,u3]),Rotation)
+# T = rotate_data(T,np.array([0,1,0]),Rotation_angle)
+# T = rotate_data(T,np.array([0,0,1]),-1*Rotation_angle/2)
+
+
+# ax.plot_surface(T[0], T[1], T[2],  rstride = 1, cstride = 1, color = 'white', alpha=0.55, zorder=2, antialiased=True)
+# ax.plot_surface(T[0], T[1], T[2],  rstride =1 , cstride = 1, color = 'white', alpha=0.55, zorder=3)
+
+# ax.plot_surface(T[0], T[1], T[2],  rstride = 1, cstride = 1, color = 'white', alpha=0.55, zorder=2)
+# ax.plot_surface(T[0], T[1], T[2],  rstride = 1, cstride = 1, color = 'white', alpha=0.5, zorder=2, antialiased=True)
+# ax.plot_surface(T[0], T[1], T[2],  rstride = 10, cstride = 10, color = 'white', alpha=0.55, zorder=2)
+ax.plot_surface(T[0], T[1], T[2],  rstride = 20, cstride = 20, color = 'gray', alpha=0.35, zorder=1, shade=True)
+# ax.plot_surface(T[0], T[1], T[2], color = 'white', alpha=0.55, zorder=2)
+
+# midpoint = np.array([(max(x)+min(x))/2,(max(y)+min(y))/2])
+mapped_e = grad_u(midpoint,kappa,e)
+normal_zeroCurv = compute_normal(midpoint,kappa,e)
+
+# Map midpoint:
+midpoint_mapped = u(midpoint,kappa,e)
+print('mapped midpoint', midpoint_mapped)
+
+##-----  PLOT MAPPED MIDPOINT :::
+
+# ax.plot(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],    # data
+# marker='o',     # each marker will be rendered as a circle
+# markersize=4,   # marker size
+# markerfacecolor='orange',   # marker facecolor
+# markeredgecolor='black',  # marker edgecolor
+# markeredgewidth=1,       # marker edge width
+# # linestyle='--',            # line style will be dash line
+# linewidth=1,
+# zorder=5)
+
+# ax.arrow3D(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],
+#            mapped_e[0],mapped_e[1],mapped_e[2],
+#            mutation_scale=10,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='red',
+#            ec ='red')
+#
+# ax.arrow3D(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],
+#            normal_zeroCurv[0],normal_zeroCurv[1],normal_zeroCurv[2],
+#            mutation_scale=10,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='blue',
+#            ec ='blue')
+
+
+##----------  PLOT MAPPED ORIGIN :::
+# origin = np.array([0,0])
+# origin_mapped = u(origin,kappa,e)
+# print('origin_mapped', origin_mapped)
+#
+# ax.plot(origin_mapped[0],origin_mapped[1],origin_mapped[2],    # data
+# marker='o',     # each marker will be rendered as a circle
+# markersize=4,   # marker size
+# markerfacecolor='green',   # marker facecolor
+# markeredgecolor='black',  # marker edgecolor
+# markeredgewidth=1,       # marker edge width
+# linewidth=1,
+# zorder=5)          # line width
+#
+# # rotate mapped origin
+# # v = np.array([1,0,0])
+# # alpha  = Rotation_angle
+#
+# rotM = rot(Rotation_vector,Rotation_angle)
+# # origin_mRot = rotate_data(origin_mapped,v,alpha)
+# origin_mRot = rotM.dot(origin_mapped)
+# print('origin_mapped Rotated', origin_mRot)
+#
+# # --- Compute Distance to Origin 3D
+# origin_3D=np.array([0,0,0])
+# distance = origin_mapped-origin_3D
+# print('distance', distance)
+
+## --------------------------------------------------------
+
+# COMPUTE ANGLE WITH Z AXIS
+z = np.array([0,0,1])
+print('test', normal_zeroCurv*z)
+angle_z = np.arccos(normal_zeroCurv.dot(z) /( (np.linalg.norm(z)*np.linalg.norm(normal_zeroCurv) ) ))
+print('angle between normal and z-axis', angle_z)
+
+## unfinished...
+
+
+
+
+###-------------------------------------  PLOT :
+plt.axis('off')
+# plt.axis('tight')
+
+# ADD colorbar
+# scamap = plt.cm.ScalarMappable(cmap='inferno')
+# fig.colorbar(scamap)
+
+# ax.colorbar()
+# ax.axis('auto')
+# ax.set_title(r'Cylindrical minimizer_$\kappa$='+ str(kappa)+ '_$e$=' +  str(e))
+# ax.set_title(r'Cylindrical minimizer' + '_$e$=' +  str(e))
+ax.set_xlabel(r"x-axis")
+ax.set_ylabel(r"y-axis")
+ax.set_zlabel(r"z-axis")
+
+# TEST :
+# ax.annotate3D('point 1', (0, 0, 0), xytext=(3, 3), textcoords='offset points')
+# ax.annotate3D('point 2', (0, 1, 0),
+#               xytext=(-30, -30),
+#               textcoords='offset points',
+#               arrowprops=dict(ec='black', fc='white', shrink=2.5))
+# ax.annotate3D('point 3', (0, 0, 1),
+#               xytext=(30, -30),
+#               textcoords='offset points',
+#               bbox=dict(boxstyle="round", fc="lightyellow"),
+#               arrowprops=dict(arrowstyle="-|>", ec='black', fc='white', lw=5))
+
+#######################################################################################################################
+
+u1 = T[0]
+u2 = T[1]
+u3 = T[2]
+
+# max_range = np.array([u1.max()-u1.min(), u2.max()-u2.min(), u3.max()-u3.min()]).max() /3
+max_range = np.array([u1.max()-u1.min(), u2.max()-u2.min(), u3.max()-u3.min()]).max() /12
+# max_range = np.array([u1.max()-u1.min(), u2.max()-u2.min(), u3.max()-u3.min()]).max() /8
+# max_range = np.array([u1.max()-u1.min(), u2.max()-u2.min(), u3.max()-u3.min()]).max() /6
+# max_range = np.array([u1.max()-u1.min(), u2.max()-u2.min(), u3.max()-u3.min()]).max() /2
+mid_u1 = (u1.max()+u1.min()) * 0.5
+mid_u2 = (u2.max()+u2.min()) * 0.5
+mid_u3 = (u3.max()+u3.min()) * 0.5
+
+
+ax.set_xlim(mid_u1 - max_range, mid_u1 + max_range)
+ax.set_ylim(mid_u2 - max_range, mid_u2 + max_range)
+ax.set_zlim(mid_u3 - max_range, mid_u3 + max_range)
+
+ax.set_ylim((mid_u2 - max_range)-2, (mid_u2 + max_range)+2)
+# ax.set_ylim((mid_u2 - max_range)-1.5, (mid_u2 + max_range)+1.5)
+# ax.autoscale(tight=True)
+
+
+
+
+##----- CHANGE CAMERA POSITION:
+# ax.view_init(elev=10., azim=0)
+# ax.view_init(elev=38, azim=90)
+# ax.view_init(elev=38, azim=120)
+# ax.view_init(elev=38)
+
+# if e1 ::
+# ax.view_init(elev=44)
+# ax.view_init(elev=38, azim=-90)
+# ax.view_init(elev=38, azim=0)
+ax.view_init(elev=25, azim=-30)
+
+# if e3 ::
+# ax.view_init(elev=25)
+
+# ax.set_xlim3d(-2, 2)
+# ax.set_ylim3d(-1.0,3.0)
+# ax.set_zlim3d(-1.5,2.5)
+
+# ax.set_ylim3d(-10,10)
+# ax.set_xlim(mid_u1 - max_range-0.2, mid_u1 + max_range+0.2)
+# ax.set_zlim(mid_u3 - max_range-0.2, mid_u3 + max_range+0.2)
+# ax.set_ylim(mid_u2 - max_range-0.2, mid_u2 + max_range+0.2)
+
+# width = 6.28 *0.5
+# height = width / 1.618
+# # height = width / 2.5
+# fig.set_size_inches(width, height)
+# fig.savefig('Test-Cylindrical.pdf')
+
+# Figurename = r'Cylindrical minimizer_$\kappa$='+ str(kappa)+ '_$e$=' +  str(e)
+# Figurename = r'Cylindrical minimizer' + '_$e$=' +  str(e)
+Figurename = r'1-ParFamMinimizer_idx' + str(idx)
+# plt.savefig("test.png", bbox_inches='tight')
+# plt.figure().set_size_inches(width, height)
+# plt.set_size_inches(width, height)
+
+
+fig.set_size_inches(width, height)
+fig.savefig(Figurename+".pdf")
+
+plt.savefig(Figurename+".png", bbox_inches='tight')
+# plt.savefig(Figurename+".png")
+plt.show()
+
+
+
+# #---------------------------------------------------------------

Python-Scripts/1-ParameterFamily-MinimizersTest.py

+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 matplotlib.ticker as tickers
+import matplotlib as mpl
+from matplotlib.ticker import MultipleLocator,FormatStrFormatter,MaxNLocator
+from mpl_toolkits.mplot3d import Axes3D
+import pandas as pd
+import matplotlib.colors as mcolors
+from matplotlib import cm
+
+from mpl_toolkits.mplot3d.proj3d import proj_transform
+# from mpl_toolkits.mplot3d.axes3d import Axes3D
+from matplotlib.text import Annotation
+from matplotlib.patches import FancyArrowPatch
+
+# Extra packages :
+# from HelperFunctions import *
+# from ClassifyMin import *
+# from subprocess import Popen, PIPE
+#import sys
+
+###################### Documentation #########################
+
+#..... add description here
+
+###########################################################
+
+
+def rot(v,alpha):
+
+#rotate about axis v with degree deg in radians:
+
+
+    tmp = np.array([ [v[0]**2*(1-np.cos(alpha))+np.cos(alpha), v[0]*v[1]*(1-np.cos(alpha))-v[2]*np.sin(alpha), v[0]*v[2]*(1-np.cos(alpha))+ v[1]*np.sin(alpha) ],
+         [v[0]*v[1]*(1-np.cos(alpha))+v[2]*np.sin(alpha), v[1]**2*(1-np.cos(alpha))+np.cos(alpha), v[1]*v[2]*(1-np.cos(alpha))+v[0]*np.sin(alpha) ],
+         [v[2]*v[0]*(1-np.cos(alpha))-v[1]*np.sin(alpha), v[2]*v[1]*(1-np.cos(alpha))+v[0]*np.sin(alpha) , v[2]**2*(1-np.cos(alpha))+np.cos(alpha) ] ])
+
+    return tmp
+
+
+
+def rotate_data(X, R):
+#rotate about axis v with degree deg in radians:
+# X : DataSet
+# R : RotationMatrix
+    print('ROTATE DATA FUNCTION ---------------')
+
+    rot_matrix = R
+    # print('rot_matrix:', rot_matrix)
+    # print('rot_matrix.shape:', rot_matrix.shape)
+    # print('X', X)
+    # print('shape of X[0]', X.shape[0])
+    B = np.dot(rot_matrix, X.reshape(rot_matrix.shape[1],-1))
+    # print('shape of B', B.shape)
+    # print('B',B)
+    # print('B[0,:]', B[0,:])
+    # print('B[0,:].shape', B[0,:].shape)
+    Out = np.array([B[0,:].reshape(X.shape[1],X.shape[2]), B[1,:].reshape(X.shape[1],X.shape[2]), B[2,:].reshape(X.shape[1],X.shape[2])])
+    print('shape of Out', Out.shape)
+
+    return Out
+
+# def rotate_data(X, v,alpha): #(Old Version)
+# #rotate about axis v with degree deg in radians:
+# # X : DataSet
+#     print('ROTATE DATA FUNCTION ---------------')
+#     # v = np.array([1,0,0])
+#     # rotM = rot(v,np.pi/2)
+#     # print('rotM:', rotM)
+#     rot_matrix = rot(v,alpha)
+#     # print('rot_matrix:', rot_matrix)
+#     # print('rot_matrix.shape:', rot_matrix.shape)
+#
+#     # print('X', X)
+#     # print('shape of X[0]', X.shape[0])
+#     B = np.dot(rot_matrix, X.reshape(rot_matrix.shape[1],-1))
+#
+#     # print('shape of B', B.shape)
+#     # print('B',B)
+#     # print('B[0,:]', B[0,:])
+#     # print('B[0,:].shape', B[0,:].shape)
+#     Out = np.array([B[0,:].reshape(X.shape[1],X.shape[2]), B[1,:].reshape(X.shape[1],X.shape[2]), B[2,:].reshape(X.shape[1],X.shape[2])])
+#     print('shape of Out', Out.shape)
+#
+#     return Out
+
+
+# def translate_data(X, v):  ...
+# #rotate about axis v with degree deg in radians:
+# # X : DataSet
+#     print('ROTATE DATA FUNCTION ---------------')
+#     # v = np.array([1,0,0])
+#     # rotM = rot(v,np.pi/2)
+#     # print('rotM:', rotM)
+#
+#     print('X', X)
+#     print('shape of X[0]', X.shape[0])
+#
+#     Out = X + v
+#     return Out
+
+
+def u(x,kappa,e):
+
+    tmp = (x.dot(e))*kappa
+    # print('tmp for u',tmp)
+    if kappa == 0 :
+        tmp = np.array([0*x[0],  x[0]*e[0] + x[1]*e[1], x[1]*e[0] - x[0]*e[1] ])
+    else :
+        tmp = np.array([-(1/kappa)*np.cos(tmp)+(1/kappa),  (1/kappa)*np.sin(tmp), -x[0]*e[1]+x[1]*e[0] ])
+    return tmp
+
+
+
+
+def grad_u(x,kappa,e):
+
+    tmp = (x.dot(e))*kappa
+    # print('tmp',tmp)
+
+    grad_u = np.array([ [np.sin(tmp)*e[0], np.sin(tmp)*e[1]], [np.cos(tmp)*e[0], np.cos(tmp)*e[1]], [-e[1], e[0]] ])
+    # print('produkt', grad_u.dot(e) )
+    mapped_e = grad_u.dot(e)
+    # print('mapped_e:', mapped_e)
+    # print('siize of mapped_e', mapped_e.shape)
+    # mapped_e = mapped_e.transpose()
+    # print('mapped_e:', mapped_e)
+    # print('siize of mapped_e', mapped_e.shape)
+    return mapped_e
+
+def compute_normal(x,kappa,e):
+    tmp = (x.dot(e))*kappa
+    partial1_u = np.array([ np.sin(tmp)*e[0] ,np.cos(tmp)*e[0], -e[1] ])
+    partial2_u = np.array([ np.sin(tmp)*e[1], np.cos(tmp)*e[1], e[0]      ])
+    normal = np.cross(partial1_u,partial2_u)
+    # print('normal=',normal)
+    return normal
+
+
+
+class Annotation3D(Annotation):
+    def __init__(self, text, xyz, *args, **kwargs):
+        super().__init__(text, xy=(0, 0), *args, **kwargs)
+        self._xyz = xyz
+
+    def draw(self, renderer):
+        x2, y2, z2 = proj_transform(*self._xyz, self.axes.M)
+        self.xy = (x2, y2)
+        super().draw(renderer)
+
+def _annotate3D(ax, text, xyz, *args, **kwargs):
+    '''Add anotation `text` to an `Axes3d` instance.'''
+
+    annotation = Annotation3D(text, xyz, *args, **kwargs)
+    ax.add_artist(annotation)
+
+setattr(Axes3D, 'annotate3D', _annotate3D)
+
+class Arrow3D(FancyArrowPatch):
+
+    def __init__(self, x, y, z, dx, dy, dz, *args, **kwargs):
+        super().__init__((0, 0), (0, 0), *args, **kwargs)
+        self._xyz = (x, y, z)
+        self._dxdydz = (dx, dy, dz)
+
+    def draw(self, renderer):
+        x1, y1, z1 = self._xyz
+        dx, dy, dz = self._dxdydz
+        x2, y2, z2 = (x1 + dx, y1 + dy, z1 + dz)
+
+        xs, ys, zs = proj_transform((x1, x2), (y1, y2), (z1, z2), self.axes.M)
+        self.set_positions((xs[0], ys[0]), (xs[1], ys[1]))
+        super().draw(renderer)
+
+
+def _arrow3D(ax, x, y, z, dx, dy, dz, *args, **kwargs):
+    '''Add an 3d arrow to an `Axes3D` instance.'''
+
+    arrow = Arrow3D(x, y, z, dx, dy, dz, *args, **kwargs)
+    ax.add_artist(arrow)
+
+setattr(Axes3D, 'arrow3D', _arrow3D)
+################################################################################################################
+################################################################################################################
+################################################################################################################
+
+
+
+q1=1;
+q2=2;
+q12=1/2;
+q3=((4*q1*q2)**0.5-q12)/2;
+# H=[2*q1,q12+2*q3;q12+2*q3,2*q2];
+
+H = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+A = np.array([[q1,1/2*q12], [1/2*q12,q2] ])
+abar = np.array([q12+2*q3, 2*q2])
+abar = (1.0/math.sqrt((q12+2*q3)**2+(2*q2)**2))*abar
+
+print('abar:',abar)
+
+b = np.linalg.lstsq(A, abar)[0]
+print('b',b)
+
+
+# print('abar:',np.shape(abar))
+# print('np.transpose(abar):',np.shape(np.transpose(abar)))
+sstar = (1/(q1+q2))*abar.dot(A.dot(b))
+# sstar = (1/(q1+q2))*abar.dot(tmp)
+print('sstar', sstar)
+abarperp= np.array([abar[1],-abar[0]])
+print('abarperp:',abarperp)
+
+print('----------------------------')
+
+# ----------------------------------------------------------------
+
+N=1000;
+T = np.linspace(-sstar*(q12+2*q3)/(2*q2), sstar*(2*q2)/(q12+2*q3), num=N)
+print('T:', T)
+
+kappas = []
+alphas = []
+# G.append(float(s[0]))
+
+G_container = []
+abar_container = []
+e_container = []
+
+
+for t in T :
+
+    abar_current = sstar*abar+t*abarperp;
+    # print('abar_current', abar_current)
+    abar_current[abar_current < 1e-10] = 0
+    # print('abar_current', abar_current)
+    # G = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+    G = [abar_current[0], abar_current[1] , (2*abar_current[0]*abar_current[1])**0.5 ]
+    G_container.append(G)
+    abar_container.append(abar_current)
+    e = [(abar_current[0]/(abar_current[0]+abar_current[1]))**0.5, (abar_current[1]/(abar_current[0]+abar_current[1]))**0.5]
+    e_container.append(e)
+    kappa = abar_current[0]+abar_current[1]
+    alpha = math.atan2(e[1], e[0])
+    # print('angle current:', alpha)
+    kappas.append(kappa)
+    alphas.append(alpha)
+
+
+G_container = np.array(G_container)
+abar_container = np.array(abar_container)
+
+e_container = np.array(e_container)
+
+print('G_container', G_container)
+print('G_container.shape', G_container.shape)
+
+# idx_1 = np.where(alphas == np.pi/4)
+idx_1 = np.where(np.round(alphas,2) == round(np.pi/3,2))
+idx_2 = np.where(np.round(alphas,2) == 0.0)
+idx_3 = np.where(np.round(alphas,2) == round(np.pi/4,2))
+
+# idx_3 = np.where(alphas == 0)
+
+print('Index idx_1:', idx_1)
+print('Index idx_2:', idx_2)
+print('Index idx_3:', idx_3)
+print('Index idx_1[0][0]:', idx_1[0][0])
+print('Index idx_2[0][0]:', idx_2[0][0])
+print('Index idx_3[0][0]:', idx_3[0][0])
+
+alphas = np.array(alphas)
+kappas = np.array(kappas)
+
+
+# print('kappas:',kappas)
+# print('alphas:',alphas)
+print('min alpha:', min(alphas))
+print('min kappa:', min(kappas))
+
+
+print('G_container[idx_1[0][0]]', G_container[idx_1[0][0]])
+print('G_container[idx_2[0][0]]', G_container[idx_2[0][0]])
+print('G_container[idx_3[0][0]]', G_container[idx_3[0][0]])
+
+
+print('e_container[idx_1[0][0]]', e_container[idx_1[0][0]])
+print('e_container[idx_2[0][0]]', e_container[idx_2[0][0]])
+print('e_container[idx_3[0][0]]', e_container[idx_3[0][0]])
+
+
+idx = 2
+
+e = e_container[idx_1[0][0]]
+e = e_container[idx_2[0][0]]
+# e = e_container[idx_3[0][0]]
+kappa = kappas[idx_1[0][0]]
+kappa = kappas[idx_2[0][0]]
+# kappa = kappas[idx_3[0][0]]
+
+angle = alphas[idx_1[0][0]]
+angle = alphas[idx_2[0][0]]
+# angle = alphas[idx_3[0][0]]
+
+
+# kappa = kappa*2
+
+print('kappa:',kappa)
+print('angle:',angle)
+
+#### TEST apply reflection
+#
+# G_tmp = G_container[idx_1[0][0]]
+#
+# print('G_tmp', G_tmp)
+#
+# # Basis:
+# G_1 = np.array([[1.0,0.0], [0.0,0.0]])
+# G_2 = np.array([[0.0,0.0], [0.0,1.0]])
+# G_3 = (1/np.sqrt(2))*np.array([[0.0,1.0], [1.0,0.0]])
+# print('G_1', G_1)
+# print('G_2', G_2)
+# print('G_3', G_3)
+#
+# G = G_tmp[0] * G_1 + G_tmp[1]*G_2 + G_tmp[2]*G_3
+# print('G:', G )
+#
+# T = np.array([[1.0 , -1.0] , [-1.0,1.0]])
+#
+# TG = np.multiply(T,G)
+# print('TG', TG)
+#
+#
+#
+# v = np.array([np.sqrt(TG[0][0]),np.sqrt(TG[1][1]) ])
+# print('v', v)
+# print('norm(v):', np.linalg.norm(v))
+# norm_v = np.linalg.norm(v)
+#
+# kappa = norm_v**2
+#
+# e = (1/norm_v)*v
+# print('e:', e)
+# print('kappa:', kappa)
+
+
+
+
+
+
+
+
+reflected_e = np.array([e[0], -1*e[1]])
+e = reflected_e                                         # Correct?! Reflect e on x-Axis ??!
+print('reflected_e:', reflected_e)
+
+
+############################################################################################################################################
+####################################################################### KAPPA NEGATIVE ####################################################
+############################################################################################################################################
+# kappa = -2
+num_Points = 200
+num_Points = 100
+
+
+# e = np.array([1,0])
+# e = np.array([0,1])
+# e = np.array([1/np.sqrt(2),1/np.sqrt(2)])
+# e = np.array([1/2,np.sqrt(3)/2])
+# e = np.array([np.sqrt(3)/2,1/2])
+# e = np.array([-1,0])
+# e = np.array([0,-1])
+
+###--- Creating dataset
+x = np.linspace(-2,2,num_Points)
+x = np.linspace(-3,3,num_Points)
+# x = np.linspace(-4,4,num_Points)
+
+# x = np.linspace(-1.5,1.5,num_Points)
+# x = np.linspace(-1,1,num_Points)
+y = np.linspace(-1/2,1/2,num_Points)
+y = np.linspace(-1/4,1/4,num_Points)
+
+print('type of x', type(x))
+print('max of x:', max(x))
+print('max of y:', max(y))
+# print('x:', x)
+
+x1, x2 = np.meshgrid(x,y)
+zero = 0*x1
+
+if kappa == 0 :
+    u1 = 0*x1
+    u2 = x1*e[0] + x2*e[1]
+    u3 = x2*e[0] - x1*e[1]
+
+else :
+    u1 = -(1/kappa)*np.cos(kappa*(x1*e[0]+x2*e[1])) + (1/kappa)
+    u2 = (1/kappa)*np.sin(kappa*(x1*e[0]+x2*e[1]))
+    u3 = x2*e[0] -x1*e[1]
+
+# print('np.size(u1)',np.size(u1))
+# print('u1.shape',u1.shape)
+# colorfunction=(u1**2+u2**2)
+# print('colofunction',colorfunction)
+
+# print('u1.size:',np.size(u1))
+# tmp = np.ones(np.size(u1))*kappa
+# print('np.size(tmp)',np.size(tmp))
+B = np.full_like(u1, 1)
+# colorfunction=(u3)                                              # TODO Color by angle
+# colorfunction=(np.ones(np.size(u1))*kappa)
+colorfunction=(B*kappa)
+# print('colofunction',colorfunction)
+norm=mcolors.Normalize(colorfunction.min(),colorfunction.max())
+
+
+# -----------------------------------------------------
+# Display the mesh
+fig = plt.figure()
+
+
+width = 6.28 *0.5
+width = 6.28 * 0.333
+height = width / 1.618
+height = width / 2.5
+height = width
+
+
+
+ax = plt.axes(projection ='3d', adjustable='box')
+
+
+###---TEST MAP e-vectprs!
+# e1 = np.array([1,0])
+# e2 = np.array([0,1])
+# e3 = np.array([1/np.sqrt(2),1/np.sqrt(2)])
+# e1 = np.array([0,1])
+# e2 = np.array([-1,0])
+# e3 = np.array([-1/np.sqrt(2),1/np.sqrt(2)])
+# e1_mapped = u(e1,kappa,e1)
+# e2_mapped = u(e2,kappa,e2)
+# e3_mapped = u(e3,kappa,e3)
+# print('e1 mapped:',e1_mapped)
+# print('e2 mapped:',e2_mapped)
+# print('e3 mapped:',e3_mapped)
+### -----------------------------------
+
+#--e1 :
+# Rotation_angle = -np.pi/2
+# Rotation_vector = np.array([0,1,0])
+
+#--e2:
+Rotation_angle = np.pi/2
+Rotation_vector = np.array([1,0,0])
+
+###--e = np.array([1/np.sqrt(2),1/np.sqrt(2)])
+# Rotation_angle = -np.pi/2
+# Rotation_vector = np.array([1,0,0])
+# #2te rotation :
+# Rotation_angle = np.pi/4
+# Rotation_vector = np.array([0,0,1])
+
+
+
+Rotation_angle = -np.pi/2
+Rotation_angle = 0
+# Rotation_angle = np.pi/2
+Rotation_vector = np.array([0,1,0])
+Rotation_vector = np.array([1,0,0])
+
+# rot(np.array([0,1,0]),np.pi/2)
+
+# ZERO ROTATION
+Rotation = rot(np.array([0,1,0]),0)
+
+
+
+# TEST :
+
+#DETERMINE ANGLE:
+angle = math.atan2(e[1], e[0])
+print('angle:', angle)
+
+## GENERAL TRANSFORMATION / ROTATION:
+Rotation = rot(np.array([0,0,1]),angle).dot(rot(np.array([0,1,0]),-np.pi/2))
+
+# Rotation = rot(np.array([0,0,1]),+np.pi/4).dot(Rotation)
+# Rotation = rot(np.array([0,0,1]),+np.pi/16).dot(Rotation)
+
+
+
+### if e1:
+# Rotation = rot(np.array([0,0,1]),-np.pi/4).dot(Rotation)
+# Rotation = rot(np.array([0,0,1]),+np.pi/16).dot(Rotation)
+
+# Add another rotation around z-axis:
+# Rotation = rot(np.array([0,0,1]),+np.pi).dot(Rotation)
+# Rotation = rot(np.array([0,0,1]),+np.pi/4).dot(Rotation)
+
+
+# Rotation = rot(np.array([0,0,1]),+np.pi/8).dot(Rotation)
+
+#e3 :
+# Rotation = rot(np.array([0,1,0]),-np.pi/2)
+# Rotation = rot(np.array([0,0,1]),np.pi/4).dot(rot(np.array([0,1,0]),-np.pi/2))
+
+# Rotation = rot(np.array([0,0,1]),np.pi/4)
+# Rotation = rot(np.array([1,0,0]),np.pi/4)
+#### if e1 :
+# Rotation = rot(np.array([0,1,0]),-np.pi/2)
+#### if e2:
+# Rotation = rot(np.array([0,1,0]),-np.pi/2).dot(rot(np.array([1,0,0]),-np.pi/2))
+# # #### if e3 :
+# zufall dass np.pi/4 genau dem Winkel angle alpha entspricht?:
+# (würde) bei e_2 keinen Unterschied machen um z achse zu rotieren?!
+
+# Rotation = rot(np.array([0,0,1]),np.pi/4).dot(rot(np.array([0,1,0]),-np.pi/2).dot(rot(np.array([1,0,0]),-np.pi/2)))
+# Rotation = rot(np.array([0,0,1]),np.pi/2).dot(rot(np.array([0,1,0]),-np.pi/2).dot(rot(np.array([1,0,0]),-np.pi/2)))
+
+# Rotation = rot(np.array([1,0,0]),np.pi/2)
+
+# Rotation_vector = e3_mapped  #TEST
+# Rotation_vector = np.array([-1/np.sqrt(2),1/np.sqrt(2)])
+# Rotation_vector = np.array([0,0,1])
+
+# v = np.array([1,0,0])
+# X = np.array([u1,u2,u3])
+
+
+
+
+# T = rotate_data(np.array([u1,u2,u3]),Rotation_vector,Rotation_angle)
+T = rotate_data(np.array([u1,u2,u3]),Rotation)
+
+# ax.plot_surface(T[0], T[1], T[2], color = 'w', rstride = 2, cstride = 2, facecolors=cm.brg(colorfunction), alpha=.4, zorder=4)
+# ax.plot_surface(T[0], T[1], T[2], color = 'w', rstride = 1, cstride = 1, facecolors=cm.viridis(colorfunction), alpha=.4, zorder=4)
+
+
+###---- PLOT PARAMETER-PLANE:
+# ax.plot_surface(x1,x2,zero,color = 'w', rstride = 1, cstride = 1 )
+
+
+print('------------------ Kappa : ', kappa)
+
+#midpoint:
+midpoint = np.array([(max(x)+min(x))/2,(max(y)+min(y))/2])
+print('midpoint',midpoint)
+
+# Map midpoint:
+midpoint_mapped = u(midpoint,kappa,e)
+print('mapped midpoint', midpoint_mapped)
+
+#map origin
+origin = np.array([0,0])
+origin_mapped = u(origin,kappa,e)
+
+
+mapped_e = grad_u(midpoint,kappa,e)
+normal = compute_normal(midpoint,kappa,e)
+
+print('mapped_e', mapped_e)
+print('normal',normal )
+
+#
+# mapped_e = Rotation.dot(mapped_e)
+# normal = Rotation.dot(normal)
+
+
+# Plot Mapped_midPoint
+# ax.plot(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],    # data
+# marker='o',     # each marker will be rendered as a circle
+# markersize=4,   # marker size
+# markerfacecolor='orange',   # marker facecolor
+# markeredgecolor='black',  # marker edgecolor
+# markeredgewidth=1,       # marker edge width
+# linewidth=1,
+# zorder=4)          # line width
+
+# ax.quiver([midpoint_mapped[0]], [midpoint_mapped[1]], [midpoint_mapped[2]], [mapped_e[0]], [mapped_e[1]], [mapped_e[2]], color="red")
+# ax.quiver([midpoint_mapped[0]], [midpoint_mapped[1]], [midpoint_mapped[2]], [normal[0]], [normal[1]], [normal[2]], color="blue")
+
+# ax.arrow3D(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],
+#            mapped_e[0],mapped_e[1],mapped_e[2],
+#            mutation_scale=15,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='green',
+#            lw = 2,
+#            ec ='green',
+#            zorder=3)
+#
+# ax.arrow3D(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],
+#            normal[0],normal[1],normal[2],
+#            mutation_scale=15,
+#             lw = 2,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='blue',
+#            ec ='blue',
+#            zorder = 3)
+
+
+###-- TEST Rotation :
+# v = np.array([1,0,0])
+# t = np.array([0,1,0])
+#
+# ax.arrow3D(0,0,0,
+#            t[0],t[1],t[2],
+#            mutation_scale=10,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='blue',
+#            ec ='blue')
+#
+# # e_extend
+#
+# rotM = rot(v,np.pi/2)
+#
+# print('rotM:', rotM)
+#
+# rot_t = rotM.dot(t)
+#
+# print('rot_t:', rot_t)
+#
+# ax.arrow3D(0,0,0,
+#            rot_t[0],rot_t[1],rot_t[2],
+#            mutation_scale=10,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='blue',
+#            ec ='blue')
+
+### -------------------------------------------
+
+############################################################################################################################################
+####################################################################### KAPPA POSITIVE  ####################################################
+############################################################################################################################################
+
+# kappa = (-1)*kappa
+
+if kappa == 0 :
+    u1 = 0*x1
+    u2 = x1*e[0] + x2*e[1]
+    u3 = x2*e[0] - x1*e[1]
+else :
+    u1 = -(1/kappa)*np.cos(kappa*(x1*e[0]+x2*e[1])) + (1/kappa)
+    u2 = (1/kappa)*np.sin(kappa*(x1*e[0]+x2*e[1]))
+    u3 = x2*e[0] -x1*e[1]
+# ax.plot_surface(u1, u2, u3, color = 'w', rstride = 1, cstride = 1, facecolors=cm.autumn(colorfunction), alpha=.3)  ##This one!
+
+
+# T = rotate_data(X,Rotation_vector,Rotation_angle)
+
+T = rotate_data(np.array([u1,u2,u3]),Rotation)
+# T = rotate_data(T,np.array([0,1,0]),Rotation_angle)
+# T = rotate_data(T,np.array([0,0,1]),-1*Rotation_angle/2)
+
+# ax.plot_surface(T[0], T[1], T[2], rstride = 1, cstride = 1, facecolors=cm.autumn(colorfunction), alpha=.4, zorder=4, antialiased=False)
+# ax.plot_surface(T[0], T[1], T[2], rstride = 1, cstride = 1, facecolors=cm.autumn(colorfunction), alpha=.4, zorder=4, antialiased=True)
+# ax.plot_surface(T[0], T[1], T[2], rstride = 2, cstride = 2, facecolors=cm.autumn(colorfunction), alpha=.4, zorder=4)
+# ax.plot_surface(T[0], T[1], T[2], rstride = 10, cstride = 10, facecolors=cm.brg(colorfunction), alpha=.8, zorder=4)
+ax.plot_surface(T[0], T[1], T[2], rstride = 5, cstride = 5, color='orange', alpha=.8, zorder=4)
+# ax.plot_surface(T[0], T[1], T[2], rstride = 10, cstride = 10, color='blue', alpha=.8, zorder=4, shade=True)
+# ax.plot_surface(T[0], T[1], T[2], rstride = 1, cstride = 1, facecolors=cm.autumn(colorfunction), alpha=.4, zorder=4, shade=True)
+# ax.plot_surface(T[0], T[1], T[2], color = 'w', rstride = 1, cstride = 1, facecolors=cm.autumn(colorfunction), alpha=0.8, zorder=4)
+# ax.plot_surface(T[0], T[1], T[2],  rstride = 1, cstride = 1, facecolors=cm.autumn(colorfunction), alpha=1, zorde5r=5)
+
+# midpoint = np.array([(max(x)+min(x))/2,(max(y)+min(y))/2])
+# print('midpoint',midpoint)
+print('------------------ Kappa : ', kappa)
+# Map midpoint:
+midpoint_mapped = u(midpoint,kappa,e)
+print('mapped midpoint', midpoint_mapped)
+
+#map origin
+origin = np.array([0,0])
+origin_mapped = u(origin,kappa,e)
+
+
+mapped_e = grad_u(midpoint,kappa,e)
+normal = compute_normal(midpoint,kappa,e)
+
+print('mapped_e', mapped_e)
+print('normal',normal )
+
+
+#
+mapped_e = Rotation.dot(mapped_e)
+normal = Rotation.dot(normal)
+
+
+# Plot MIDPOINT:
+# ax.plot(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],    # data
+# marker='o',     # each marker will be rendered as a circle
+# markersize=4,   # marker size
+# markerfacecolor='orange',   # marker facecolor
+# markeredgecolor='black',  # marker edgecolor
+# markeredgewidth=1,       # marker edge width
+# linewidth=1,
+# zorder=5)          # line width
+
+
+
+# mapped_e = grad_u(midpoint,kappa,e)
+# normal = compute_normal(midpoint,kappa,e)
+
+
+# ax.arrow3D(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],
+#            mapped_e[0],mapped_e[1],mapped_e[2],
+#            mutation_scale=15,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='green',
+#            lw = 1.5,
+#            ec ='green',
+#            zorder=5)
+#
+# ax.arrow3D(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],
+#            normal[0],normal[1],normal[2],
+#            mutation_scale=15,
+#             lw = 1.5,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='blue',
+#            ec ='blue',
+#            zorder = 5)
+
+
+############################################################################################################################################
+####################################################################### KAPPA ZERO #########################################################
+############################################################################################################################################
+kappa = 0
+
+if kappa == 0 :
+    u1 = 0*x1
+    u2 = x1*e[0] + x2*e[1]
+    u3 = x2*e[0] - x1*e[1]
+else :
+    u1 = -(1/kappa)*np.cos(kappa*(x1*e[0]+x2*e[1])) + (1/kappa)
+    u2 = (1/kappa)*np.sin(kappa*(x1*e[0]+x2*e[1]))
+    u3 = x2*e[0] -x1*e[1]
+# ax.plot_surface(u1, u2, u3,  rstride = 1, cstride = 1, color = 'white', alpha=0.85)
+
+# T = rotate_data(np.array([u1,u2,u3]),Rotation_vector,Rotation_angle)
+
+T = rotate_data(np.array([u1,u2,u3]),Rotation)
+# T = rotate_data(T,np.array([0,1,0]),Rotation_angle)
+# T = rotate_data(T,np.array([0,0,1]),-1*Rotation_angle/2)
+
+
+# ax.plot_surface(T[0], T[1], T[2],  rstride = 1, cstride = 1, color = 'white', alpha=0.55, zorder=2, antialiased=True)
+# ax.plot_surface(T[0], T[1], T[2],  rstride =1 , cstride = 1, color = 'white', alpha=0.55, zorder=3)
+
+# ax.plot_surface(T[0], T[1], T[2],  rstride = 1, cstride = 1, color = 'white', alpha=0.55, zorder=2)
+# ax.plot_surface(T[0], T[1], T[2],  rstride = 1, cstride = 1, color = 'white', alpha=0.5, zorder=2, antialiased=True)
+# ax.plot_surface(T[0], T[1], T[2],  rstride = 10, cstride = 10, color = 'white', alpha=0.55, zorder=2)
+ax.plot_surface(T[0], T[1], T[2],  rstride = 20, cstride = 20, color = 'gray', alpha=0.35, zorder=1, shade=True)
+# ax.plot_surface(T[0], T[1], T[2], color = 'white', alpha=0.55, zorder=2)
+
+# midpoint = np.array([(max(x)+min(x))/2,(max(y)+min(y))/2])
+mapped_e = grad_u(midpoint,kappa,e)
+normal_zeroCurv = compute_normal(midpoint,kappa,e)
+
+# Map midpoint:
+midpoint_mapped = u(midpoint,kappa,e)
+print('mapped midpoint', midpoint_mapped)
+
+##-----  PLOT MAPPED MIDPOINT :::
+
+# ax.plot(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],    # data
+# marker='o',     # each marker will be rendered as a circle
+# markersize=4,   # marker size
+# markerfacecolor='orange',   # marker facecolor
+# markeredgecolor='black',  # marker edgecolor
+# markeredgewidth=1,       # marker edge width
+# # linestyle='--',            # line style will be dash line
+# linewidth=1,
+# zorder=5)
+
+# ax.arrow3D(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],
+#            mapped_e[0],mapped_e[1],mapped_e[2],
+#            mutation_scale=10,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='red',
+#            ec ='red')
+#
+# ax.arrow3D(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],
+#            normal_zeroCurv[0],normal_zeroCurv[1],normal_zeroCurv[2],
+#            mutation_scale=10,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='blue',
+#            ec ='blue')
+
+
+##----------  PLOT MAPPED ORIGIN :::
+# origin = np.array([0,0])
+# origin_mapped = u(origin,kappa,e)
+# print('origin_mapped', origin_mapped)
+#
+# ax.plot(origin_mapped[0],origin_mapped[1],origin_mapped[2],    # data
+# marker='o',     # each marker will be rendered as a circle
+# markersize=4,   # marker size
+# markerfacecolor='green',   # marker facecolor
+# markeredgecolor='black',  # marker edgecolor
+# markeredgewidth=1,       # marker edge width
+# linewidth=1,
+# zorder=5)          # line width
+#
+# # rotate mapped origin
+# # v = np.array([1,0,0])
+# # alpha  = Rotation_angle
+#
+# rotM = rot(Rotation_vector,Rotation_angle)
+# # origin_mRot = rotate_data(origin_mapped,v,alpha)
+# origin_mRot = rotM.dot(origin_mapped)
+# print('origin_mapped Rotated', origin_mRot)
+#
+# # --- Compute Distance to Origin 3D
+# origin_3D=np.array([0,0,0])
+# distance = origin_mapped-origin_3D
+# print('distance', distance)
+
+## --------------------------------------------------------
+
+# COMPUTE ANGLE WITH Z AXIS
+z = np.array([0,0,1])
+print('test', normal_zeroCurv*z)
+angle_z = np.arccos(normal_zeroCurv.dot(z) /( (np.linalg.norm(z)*np.linalg.norm(normal_zeroCurv) ) ))
+print('angle between normal and z-axis', angle_z)
+
+## unfinished...
+
+
+
+
+###-------------------------------------  PLOT :
+plt.axis('off')
+# plt.axis('tight')
+
+# ADD colorbar
+# scamap = plt.cm.ScalarMappable(cmap='inferno')
+# fig.colorbar(scamap)
+
+# ax.colorbar()
+# ax.axis('auto')
+# ax.set_title(r'Cylindrical minimizer_$\kappa$='+ str(kappa)+ '_$e$=' +  str(e))
+# ax.set_title(r'Cylindrical minimizer' + '_$e$=' +  str(e))
+ax.set_xlabel(r"x-axis")
+ax.set_ylabel(r"y-axis")
+ax.set_zlabel(r"z-axis")
+
+# TEST :
+# ax.annotate3D('point 1', (0, 0, 0), xytext=(3, 3), textcoords='offset points')
+# ax.annotate3D('point 2', (0, 1, 0),
+#               xytext=(-30, -30),
+#               textcoords='offset points',
+#               arrowprops=dict(ec='black', fc='white', shrink=2.5))
+# ax.annotate3D('point 3', (0, 0, 1),
+#               xytext=(30, -30),
+#               textcoords='offset points',
+#               bbox=dict(boxstyle="round", fc="lightyellow"),
+#               arrowprops=dict(arrowstyle="-|>", ec='black', fc='white', lw=5))
+
+#######################################################################################################################
+
+u1 = T[0]
+u2 = T[1]
+u3 = T[2]
+
+# max_range = np.array([u1.max()-u1.min(), u2.max()-u2.min(), u3.max()-u3.min()]).max() /3
+max_range = np.array([u1.max()-u1.min(), u2.max()-u2.min(), u3.max()-u3.min()]).max() /12
+# max_range = np.array([u1.max()-u1.min(), u2.max()-u2.min(), u3.max()-u3.min()]).max() /8
+# max_range = np.array([u1.max()-u1.min(), u2.max()-u2.min(), u3.max()-u3.min()]).max() /6
+# max_range = np.array([u1.max()-u1.min(), u2.max()-u2.min(), u3.max()-u3.min()]).max() /2
+mid_u1 = (u1.max()+u1.min()) * 0.5
+mid_u2 = (u2.max()+u2.min()) * 0.5
+mid_u3 = (u3.max()+u3.min()) * 0.5
+
+
+ax.set_xlim(mid_u1 - max_range, mid_u1 + max_range)
+ax.set_ylim(mid_u2 - max_range, mid_u2 + max_range)
+ax.set_zlim(mid_u3 - max_range, mid_u3 + max_range)
+
+ax.set_ylim((mid_u2 - max_range)-2, (mid_u2 + max_range)+2)
+# ax.set_ylim((mid_u2 - max_range)-1.5, (mid_u2 + max_range)+1.5)
+# ax.autoscale(tight=True)
+
+
+
+
+##----- CHANGE CAMERA POSITION:
+# ax.view_init(elev=10., azim=0)
+# ax.view_init(elev=38, azim=90)
+# ax.view_init(elev=38, azim=120)
+# ax.view_init(elev=38)
+
+# if e1 ::
+# ax.view_init(elev=44)
+# ax.view_init(elev=38, azim=-90)
+# ax.view_init(elev=38, azim=0)
+ax.view_init(elev=25, azim=-30)
+
+# if e3 ::
+# ax.view_init(elev=25)
+
+# ax.set_xlim3d(-2, 2)
+# ax.set_ylim3d(-1.0,3.0)
+# ax.set_zlim3d(-1.5,2.5)
+
+# ax.set_ylim3d(-10,10)
+# ax.set_xlim(mid_u1 - max_range-0.2, mid_u1 + max_range+0.2)
+# ax.set_zlim(mid_u3 - max_range-0.2, mid_u3 + max_range+0.2)
+# ax.set_ylim(mid_u2 - max_range-0.2, mid_u2 + max_range+0.2)
+
+# width = 6.28 *0.5
+# height = width / 1.618
+# # height = width / 2.5
+# fig.set_size_inches(width, height)
+# fig.savefig('Test-Cylindrical.pdf')
+
+# Figurename = r'Cylindrical minimizer_$\kappa$='+ str(kappa)+ '_$e$=' +  str(e)
+# Figurename = r'Cylindrical minimizer' + '_$e$=' +  str(e)
+Figurename = r'1-ParFamMinimizer_idx' + str(idx)
+# plt.savefig("test.png", bbox_inches='tight')
+# plt.figure().set_size_inches(width, height)
+# plt.set_size_inches(width, height)
+
+
+fig.set_size_inches(width, height)
+fig.savefig(Figurename+".pdf")
+
+plt.savefig(Figurename+".png", bbox_inches='tight')
+# plt.savefig(Figurename+".png")
+plt.show()
+
+
+
+# #---------------------------------------------------------------

Python-Scripts/1-ParameterFamily-Minimizers_Test.py

+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 matplotlib.ticker as tickers
+import matplotlib as mpl
+from matplotlib.ticker import MultipleLocator,FormatStrFormatter,MaxNLocator
+from mpl_toolkits.mplot3d import Axes3D
+import pandas as pd
+import matplotlib.colors as mcolors
+from matplotlib import cm
+
+from mpl_toolkits.mplot3d.proj3d import proj_transform
+# from mpl_toolkits.mplot3d.axes3d import Axes3D
+from matplotlib.text import Annotation
+from matplotlib.patches import FancyArrowPatch
+
+# Extra packages :
+# from HelperFunctions import *
+# from ClassifyMin import *
+# from subprocess import Popen, PIPE
+#import sys
+
+###################### Documentation #########################
+
+#..... add description here
+
+###########################################################
+
+
+def rot(v,alpha):
+
+#rotate about axis v with degree deg in radians:
+
+
+    tmp = np.array([ [v[0]**2*(1-np.cos(alpha))+np.cos(alpha), v[0]*v[1]*(1-np.cos(alpha))-v[2]*np.sin(alpha), v[0]*v[2]*(1-np.cos(alpha))+ v[1]*np.sin(alpha) ],
+         [v[0]*v[1]*(1-np.cos(alpha))+v[2]*np.sin(alpha), v[1]**2*(1-np.cos(alpha))+np.cos(alpha), v[1]*v[2]*(1-np.cos(alpha))+v[0]*np.sin(alpha) ],
+         [v[2]*v[0]*(1-np.cos(alpha))-v[1]*np.sin(alpha), v[2]*v[1]*(1-np.cos(alpha))+v[0]*np.sin(alpha) , v[2]**2*(1-np.cos(alpha))+np.cos(alpha) ] ])
+
+    return tmp
+
+
+
+def rotate_data(X, R):
+#rotate about axis v with degree deg in radians:
+# X : DataSet
+# R : RotationMatrix
+    print('ROTATE DATA FUNCTION ---------------')
+
+    rot_matrix = R
+    # print('rot_matrix:', rot_matrix)
+    # print('rot_matrix.shape:', rot_matrix.shape)
+    # print('X', X)
+    # print('shape of X[0]', X.shape[0])
+    B = np.dot(rot_matrix, X.reshape(rot_matrix.shape[1],-1))
+    # print('shape of B', B.shape)
+    # print('B',B)
+    # print('B[0,:]', B[0,:])
+    # print('B[0,:].shape', B[0,:].shape)
+    Out = np.array([B[0,:].reshape(X.shape[1],X.shape[2]), B[1,:].reshape(X.shape[1],X.shape[2]), B[2,:].reshape(X.shape[1],X.shape[2])])
+    print('shape of Out', Out.shape)
+
+    return Out
+
+# def rotate_data(X, v,alpha): #(Old Version)
+# #rotate about axis v with degree deg in radians:
+# # X : DataSet
+#     print('ROTATE DATA FUNCTION ---------------')
+#     # v = np.array([1,0,0])
+#     # rotM = rot(v,np.pi/2)
+#     # print('rotM:', rotM)
+#     rot_matrix = rot(v,alpha)
+#     # print('rot_matrix:', rot_matrix)
+#     # print('rot_matrix.shape:', rot_matrix.shape)
+#
+#     # print('X', X)
+#     # print('shape of X[0]', X.shape[0])
+#     B = np.dot(rot_matrix, X.reshape(rot_matrix.shape[1],-1))
+#
+#     # print('shape of B', B.shape)
+#     # print('B',B)
+#     # print('B[0,:]', B[0,:])
+#     # print('B[0,:].shape', B[0,:].shape)
+#     Out = np.array([B[0,:].reshape(X.shape[1],X.shape[2]), B[1,:].reshape(X.shape[1],X.shape[2]), B[2,:].reshape(X.shape[1],X.shape[2])])
+#     print('shape of Out', Out.shape)
+#
+#     return Out
+
+
+# def translate_data(X, v):  ...
+# #rotate about axis v with degree deg in radians:
+# # X : DataSet
+#     print('ROTATE DATA FUNCTION ---------------')
+#     # v = np.array([1,0,0])
+#     # rotM = rot(v,np.pi/2)
+#     # print('rotM:', rotM)
+#
+#     print('X', X)
+#     print('shape of X[0]', X.shape[0])
+#
+#     Out = X + v
+#     return Out
+
+#
+# def u(x,kappa,e):
+#
+#     tmp = (x.dot(e))*kappa
+#     # print('tmp for u',tmp)
+#     if kappa == 0 :
+#         tmp = np.array([0*x[0],  x[0]*e[0] + x[1]*e[1], x[1]*e[0] - x[0]*e[1] ])
+#     else :
+#         tmp = np.array([-(1/kappa)*np.cos(tmp)+(1/kappa),  (1/kappa)*np.sin(tmp), -x[0]*e[1]+x[1]*e[0] ])
+#     return tmp
+#
+#
+#
+#
+# def grad_u(x,kappa,e):
+#
+#     tmp = (x.dot(e))*kappa
+#     # print('tmp',tmp)
+#
+#     grad_u = np.array([ [np.sin(tmp)*e[0], np.sin(tmp)*e[1]], [np.cos(tmp)*e[0], np.cos(tmp)*e[1]], [-e[1], e[0]] ])
+#     # print('produkt', grad_u.dot(e) )
+#     mapped_e = grad_u.dot(e)
+#     # print('mapped_e:', mapped_e)
+#     # print('siize of mapped_e', mapped_e.shape)
+#     # mapped_e = mapped_e.transpose()
+#     # print('mapped_e:', mapped_e)
+#     # print('siize of mapped_e', mapped_e.shape)
+#     return mapped_e
+#
+# def compute_normal(x,kappa,e):
+#     tmp = (x.dot(e))*kappa
+#     partial1_u = np.array([ np.sin(tmp)*e[0] ,np.cos(tmp)*e[0], -e[1] ])
+#     partial2_u = np.array([ np.sin(tmp)*e[1], np.cos(tmp)*e[1], e[0]      ])
+#     normal = np.cross(partial1_u,partial2_u)
+#     # print('normal=',normal)
+#     return normal
+
+
+
+def u(x,kappa,e):
+
+    tmp = (x.dot(e))*((-1)*kappa)
+    # print('tmp for u',tmp)
+    if kappa == 0 :
+        tmp = np.array([x[0]*e[0] + x[1]*e[1], x[1]*e[0] - x[0]*e[1], 0*x[0]  ])
+    else :
+        tmp = np.array([ -(1/kappa)*np.sin(tmp), -x[0]*e[1]+x[1]*e[0], (1/kappa)*np.cos(tmp)-(1/kappa)   ])
+    return tmp
+
+
+
+# def grad_u(x,kappa,e):
+#
+#     tmp = (x.dot(e))*kappa
+#     # print('tmp',tmp)
+#
+#     grad_u = np.array([ [np.sin(tmp)*e[0], np.sin(tmp)*e[1]], [np.cos(tmp)*e[0], np.cos(tmp)*e[1]], [-e[1], e[0]] ])
+#     # print('produkt', grad_u.dot(e) )
+#     mapped_e = grad_u.dot(e)
+#     # print('mapped_e:', mapped_e)
+#     # print('siize of mapped_e', mapped_e.shape)
+#     # mapped_e = mapped_e.transpose()
+#     # print('mapped_e:', mapped_e)
+#     # print('siize of mapped_e', mapped_e.shape)
+#     return mapped_e
+#
+
+
+def grad_u(x,kappa,e):
+
+    tmp = (x.dot(e))*(-1)*kappa
+    # print('tmp',tmp)
+
+    grad_u = np.array([  [np.cos(tmp)*e[0], np.cos(tmp)*e[1]], [-e[1], e[0]], [np.sin(tmp)*e[0], np.sin(tmp)*e[1]] ])
+    # print('produkt', grad_u.dot(e) )
+    mapped_e = grad_u.dot(e)
+    # print('mapped_e:', mapped_e)
+    # print('siize of mapped_e', mapped_e.shape)
+    # mapped_e = mapped_e.transpose()
+    # print('mapped_e:', mapped_e)
+    # print('siize of mapped_e', mapped_e.shape)
+    return mapped_e
+
+
+def compute_normal(x,kappa,e):
+    tmp = (x.dot(e))*(-1)*kappa
+    partial1_u = np.array([ np.cos(tmp)*e[0], -e[1],np.sin(tmp)*e[0]  ])
+    partial2_u = np.array([ np.cos(tmp)*e[1], e[0], np.sin(tmp)*e[1]  ])
+    normal = np.cross(partial1_u,partial2_u)
+    # print('normal=',normal)
+    return normal
+
+
+
+class Annotation3D(Annotation):
+    def __init__(self, text, xyz, *args, **kwargs):
+        super().__init__(text, xy=(0, 0), *args, **kwargs)
+        self._xyz = xyz
+
+    def draw(self, renderer):
+        x2, y2, z2 = proj_transform(*self._xyz, self.axes.M)
+        self.xy = (x2, y2)
+        super().draw(renderer)
+
+def _annotate3D(ax, text, xyz, *args, **kwargs):
+    '''Add anotation `text` to an `Axes3d` instance.'''
+
+    annotation = Annotation3D(text, xyz, *args, **kwargs)
+    ax.add_artist(annotation)
+
+setattr(Axes3D, 'annotate3D', _annotate3D)
+
+class Arrow3D(FancyArrowPatch):
+
+    def __init__(self, x, y, z, dx, dy, dz, *args, **kwargs):
+        super().__init__((0, 0), (0, 0), *args, **kwargs)
+        self._xyz = (x, y, z)
+        self._dxdydz = (dx, dy, dz)
+
+    def draw(self, renderer):
+        x1, y1, z1 = self._xyz
+        dx, dy, dz = self._dxdydz
+        x2, y2, z2 = (x1 + dx, y1 + dy, z1 + dz)
+
+        xs, ys, zs = proj_transform((x1, x2), (y1, y2), (z1, z2), self.axes.M)
+        self.set_positions((xs[0], ys[0]), (xs[1], ys[1]))
+        super().draw(renderer)
+
+
+def _arrow3D(ax, x, y, z, dx, dy, dz, *args, **kwargs):
+    '''Add an 3d arrow to an `Axes3D` instance.'''
+
+    arrow = Arrow3D(x, y, z, dx, dy, dz, *args, **kwargs)
+    ax.add_artist(arrow)
+
+setattr(Axes3D, 'arrow3D', _arrow3D)
+################################################################################################################
+################################################################################################################
+################################################################################################################
+
+
+
+q1=1;
+q2=2;
+q12=1/2;
+q3=((4*q1*q2)**0.5-q12)/2;
+# H=[2*q1,q12+2*q3;q12+2*q3,2*q2];
+
+H = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+A = np.array([[q1,1/2*q12], [1/2*q12,q2] ])
+abar = np.array([q12+2*q3, 2*q2])
+abar = (1.0/math.sqrt((q12+2*q3)**2+(2*q2)**2))*abar
+
+print('abar:',abar)
+
+b = np.linalg.lstsq(A, abar)[0]
+print('b',b)
+
+
+# print('abar:',np.shape(abar))
+# print('np.transpose(abar):',np.shape(np.transpose(abar)))
+sstar = (1/(q1+q2))*abar.dot(A.dot(b))
+# sstar = (1/(q1+q2))*abar.dot(tmp)
+print('sstar', sstar)
+abarperp= np.array([abar[1],-abar[0]])
+print('abarperp:',abarperp)
+
+print('----------------------------')
+
+# ----------------------------------------------------------------
+
+N=1000;
+T = np.linspace(-sstar*(q12+2*q3)/(2*q2), sstar*(2*q2)/(q12+2*q3), num=N)
+print('T:', T)
+
+kappas = []
+alphas = []
+# G.append(float(s[0]))
+
+G_container = []
+abar_container = []
+e_container = []
+
+
+for t in T :
+
+    abar_current = sstar*abar+t*abarperp;
+    # print('abar_current', abar_current)
+    abar_current[abar_current < 1e-10] = 0
+    # print('abar_current', abar_current)
+    # G = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+    G = [abar_current[0], abar_current[1] , (2*abar_current[0]*abar_current[1])**0.5 ]
+    G_container.append(G)
+    abar_container.append(abar_current)
+    e = [(abar_current[0]/(abar_current[0]+abar_current[1]))**0.5, (abar_current[1]/(abar_current[0]+abar_current[1]))**0.5]
+    e_container.append(e)
+    kappa = abar_current[0]+abar_current[1]
+    alpha = math.atan2(e[1], e[0])
+    # print('angle current:', alpha)
+    kappas.append(kappa)
+    alphas.append(alpha)
+
+
+G_container = np.array(G_container)
+abar_container = np.array(abar_container)
+
+e_container = np.array(e_container)
+
+print('G_container', G_container)
+print('G_container.shape', G_container.shape)
+
+# idx_1 = np.where(alphas == np.pi/4)
+idx_1 = np.where(np.round(alphas,2) == round(np.pi/3,2))
+idx_2 = np.where(np.round(alphas,2) == 0.0)
+idx_3 = np.where(np.round(alphas,2) == round(np.pi/4,2))
+
+# idx_3 = np.where(alphas == 0)
+
+print('Index idx_1:', idx_1)
+print('Index idx_2:', idx_2)
+print('Index idx_3:', idx_3)
+print('Index idx_1[0][0]:', idx_1[0][0])
+print('Index idx_2[0][0]:', idx_2[0][0])
+print('Index idx_3[0][0]:', idx_3[0][0])
+
+alphas = np.array(alphas)
+kappas = np.array(kappas)
+
+
+# print('kappas:',kappas)
+# print('alphas:',alphas)
+print('min alpha:', min(alphas))
+print('min kappa:', min(kappas))
+
+
+print('G_container[idx_1[0][0]]', G_container[idx_1[0][0]])
+print('G_container[idx_2[0][0]]', G_container[idx_2[0][0]])
+print('G_container[idx_3[0][0]]', G_container[idx_3[0][0]])
+
+
+print('e_container[idx_1[0][0]]', e_container[idx_1[0][0]])
+print('e_container[idx_2[0][0]]', e_container[idx_2[0][0]])
+print('e_container[idx_3[0][0]]', e_container[idx_3[0][0]])
+
+
+
+###################################################
+
+reflect = False
+# reflect = True
+
+
+
+idx = 3
+
+if idx == 1 :
+    e = e_container[idx_1[0][0]]
+    kappa = kappas[idx_1[0][0]]
+    angle = alphas[idx_1[0][0]]
+    reflect = True
+
+if idx == 2 :
+    e = e_container[idx_2[0][0]]
+    kappa = kappas[idx_2[0][0]]
+    angle = alphas[idx_2[0][0]]
+
+
+if idx == 3 :
+    e = e_container[idx_3[0][0]]
+    kappa = kappas[idx_3[0][0]]
+    angle = alphas[idx_3[0][0]]
+
+### SCALE ?
+# kappa = kappa*2
+
+
+print('kappa:',kappa)
+print('angle:',angle)
+###################################################
+#### TEST apply reflection
+#
+# G_tmp = G_container[idx_1[0][0]]
+#
+# print('G_tmp', G_tmp)
+#
+# # Basis:
+# G_1 = np.array([[1.0,0.0], [0.0,0.0]])
+# G_2 = np.array([[0.0,0.0], [0.0,1.0]])
+# G_3 = (1/np.sqrt(2))*np.array([[0.0,1.0], [1.0,0.0]])
+# print('G_1', G_1)
+# print('G_2', G_2)
+# print('G_3', G_3)
+#
+# G = G_tmp[0] * G_1 + G_tmp[1]*G_2 + G_tmp[2]*G_3
+# print('G:', G )
+#
+# T = np.array([[1.0 , -1.0] , [-1.0,1.0]])
+#
+# TG = np.multiply(T,G)
+# print('TG', TG)
+#
+#
+#
+# v = np.array([np.sqrt(TG[0][0]),np.sqrt(TG[1][1]) ])
+# print('v', v)
+# print('norm(v):', np.linalg.norm(v))
+# norm_v = np.linalg.norm(v)
+#
+# kappa = norm_v**2
+#
+# e = (1/norm_v)*v
+# print('e:', e)
+# print('kappa:', kappa)
+
+
+
+
+
+
+if reflect == True:
+    reflected_e = np.array([e[0], -1*e[1]])
+    e = reflected_e                                         # Correct?! Reflect e on x-Axis ??!
+    print('reflected_e:', reflected_e)
+
+
+############################################################################################################################################
+####################################################################### KAPPA NEGATIVE ####################################################
+############################################################################################################################################
+# kappa = -2
+num_Points = 200
+# num_Points = 100
+
+
+# e = np.array([1,0])
+# e = np.array([0,1])
+# e = np.array([1/np.sqrt(2),1/np.sqrt(2)])
+# e = np.array([1/2,np.sqrt(3)/2])
+# e = np.array([np.sqrt(3)/2,1/2])
+# e = np.array([-1,0])
+# e = np.array([0,-1])
+
+###--- Creating dataset
+x = np.linspace(-2,2,num_Points)
+x = np.linspace(-2.5,2.5,num_Points)
+x = np.linspace(-3,3,num_Points)
+# x = np.linspace(-4,4,num_Points)
+
+# x = np.linspace(-1.5,1.5,num_Points)
+# x = np.linspace(-1,1,num_Points)
+y = np.linspace(-1/2,1/2,num_Points)
+y = np.linspace(-1/4,1/4,num_Points)
+
+print('type of x', type(x))
+print('max of x:', max(x))
+print('max of y:', max(y))
+# print('x:', x)
+
+x1, x2 = np.meshgrid(x,y)
+zero = 0*x1
+
+if kappa == 0 :
+    u1 = 0*x1
+    u2 = x1*e[0] + x2*e[1]
+    u3 = x2*e[0] - x1*e[1]
+
+else :
+    u1 = -(1/kappa)*np.cos(kappa*(x1*e[0]+x2*e[1])) + (1/kappa)
+    u2 = (1/kappa)*np.sin(kappa*(x1*e[0]+x2*e[1]))
+    u3 = x2*e[0] -x1*e[1]
+
+# print('np.size(u1)',np.size(u1))
+# print('u1.shape',u1.shape)
+# colorfunction=(u1**2+u2**2)
+# print('colofunction',colorfunction)
+
+# print('u1.size:',np.size(u1))
+# tmp = np.ones(np.size(u1))*kappa
+# print('np.size(tmp)',np.size(tmp))
+B = np.full_like(u1, 1)
+# colorfunction=(u3)                                              # TODO Color by angle
+# colorfunction=(np.ones(np.size(u1))*kappa)
+colorfunction=(B*kappa)
+# print('colofunction',colorfunction)
+norm=mcolors.Normalize(colorfunction.min(),colorfunction.max())
+
+
+# -----------------------------------------------------
+# Display the mesh
+fig = plt.figure()
+
+
+width = 6.28 *0.5
+width = 6.28 * 0.333
+height = width / 1.618
+height = width / 2.5
+height = width
+
+
+
+ax = plt.axes(projection ='3d', adjustable='box')
+
+
+###---TEST MAP e-vectprs!
+# e1 = np.array([1,0])
+# e2 = np.array([0,1])
+# e3 = np.array([1/np.sqrt(2),1/np.sqrt(2)])
+# e1 = np.array([0,1])
+# e2 = np.array([-1,0])
+# e3 = np.array([-1/np.sqrt(2),1/np.sqrt(2)])
+# e1_mapped = u(e1,kappa,e1)
+# e2_mapped = u(e2,kappa,e2)
+# e3_mapped = u(e3,kappa,e3)
+# print('e1 mapped:',e1_mapped)
+# print('e2 mapped:',e2_mapped)
+# print('e3 mapped:',e3_mapped)
+### -----------------------------------
+
+#--e1 :
+# Rotation_angle = -np.pi/2
+# Rotation_vector = np.array([0,1,0])
+
+#--e2:
+Rotation_angle = np.pi/2
+Rotation_vector = np.array([1,0,0])
+
+###--e = np.array([1/np.sqrt(2),1/np.sqrt(2)])
+# Rotation_angle = -np.pi/2
+# Rotation_vector = np.array([1,0,0])
+# #2te rotation :
+# Rotation_angle = np.pi/4
+# Rotation_vector = np.array([0,0,1])
+
+
+
+Rotation_angle = -np.pi/2
+Rotation_angle = 0
+# Rotation_angle = np.pi/2
+Rotation_vector = np.array([0,1,0])
+Rotation_vector = np.array([1,0,0])
+
+# rot(np.array([0,1,0]),np.pi/2)
+
+# ZERO ROTATION
+Rotation = rot(np.array([0,1,0]),0)
+
+# if idx == 1:
+# Rotation = rot(np.array([1,0,0]),np.pi)
+# Rotation = rot(np.array([1,0,0]),np.pi).dot(rot(np.array([0,0,1]),angle))
+
+Rotation = rot(np.array([1,0,0]),np.pi)
+
+# TEST :
+
+#DETERMINE ANGLE:
+angle = math.atan2(e[1], e[0])
+print('angle:', angle)
+
+## GENERAL TRANSFORMATION / ROTATION:
+# Rotation = rot(np.array([0,0,1]),angle).dot(Rotation)
+Rotation = rot(np.array([1,0,0]),np.pi).dot(rot(np.array([0,0,1]),angle))
+# Rotation = rot(np.array([0,0,1]),angle).dot(rot(np.array([0,1,0]),-np.pi/2))
+
+# Rotation = rot(np.array([0,0,1]),+np.pi/4).dot(Rotation)
+# Rotation = rot(np.array([0,0,1]),+np.pi/16).dot(Rotation)
+
+
+# Rotation = rot(np.array([0,0,1]),np.pi/2).dot(Rotation)
+
+
+### if e1:
+# Rotation = rot(np.array([0,0,1]),-np.pi/4).dot(Rotation)
+# Rotation = rot(np.array([0,0,1]),+np.pi/16).dot(Rotation)
+
+# Add another rotation around z-axis:
+# Rotation = rot(np.array([0,0,1]),+np.pi).dot(Rotation)
+# Rotation = rot(np.array([0,0,1]),+np.pi/4).dot(Rotation)
+
+
+# Rotation = rot(np.array([0,0,1]),+np.pi/8).dot(Rotation)
+
+#e3 :
+# Rotation = rot(np.array([0,1,0]),-np.pi/2)
+# Rotation = rot(np.array([0,0,1]),np.pi/4).dot(rot(np.array([0,1,0]),-np.pi/2))
+
+# Rotation = rot(np.array([0,0,1]),np.pi/4)
+# Rotation = rot(np.array([1,0,0]),np.pi/4)
+#### if e1 :
+# Rotation = rot(np.array([0,1,0]),-np.pi/2)
+#### if e2:
+# Rotation = rot(np.array([0,1,0]),-np.pi/2).dot(rot(np.array([1,0,0]),-np.pi/2))
+# # #### if e3 :
+# zufall dass np.pi/4 genau dem Winkel angle alpha entspricht?:
+# (würde) bei e_2 keinen Unterschied machen um z achse zu rotieren?!
+
+# Rotation = rot(np.array([0,0,1]),np.pi/4).dot(rot(np.array([0,1,0]),-np.pi/2).dot(rot(np.array([1,0,0]),-np.pi/2)))
+# Rotation = rot(np.array([0,0,1]),np.pi/2).dot(rot(np.array([0,1,0]),-np.pi/2).dot(rot(np.array([1,0,0]),-np.pi/2)))
+
+# Rotation = rot(np.array([1,0,0]),np.pi/2)
+
+# Rotation_vector = e3_mapped  #TEST
+# Rotation_vector = np.array([-1/np.sqrt(2),1/np.sqrt(2)])
+# Rotation_vector = np.array([0,0,1])
+
+# v = np.array([1,0,0])
+# X = np.array([u1,u2,u3])
+
+
+
+
+# T = rotate_data(np.array([u1,u2,u3]),Rotation_vector,Rotation_angle)
+T = rotate_data(np.array([u1,u2,u3]),Rotation)
+
+# ax.plot_surface(T[0], T[1], T[2], color = 'w', rstride = 2, cstride = 2, facecolors=cm.brg(colorfunction), alpha=.4, zorder=4)
+# ax.plot_surface(T[0], T[1], T[2], color = 'w', rstride = 1, cstride = 1, facecolors=cm.viridis(colorfunction), alpha=.4, zorder=4)
+
+
+###---- PLOT PARAMETER-PLANE:
+# ax.plot_surface(x1,x2,zero,color = 'w', rstride = 1, cstride = 1 )
+
+
+print('------------------ Kappa : ', kappa)
+
+#midpoint:
+midpoint = np.array([(max(x)+min(x))/2,(max(y)+min(y))/2])
+print('midpoint',midpoint)
+
+# Map midpoint:
+midpoint_mapped = u(midpoint,kappa,e)
+print('mapped midpoint', midpoint_mapped)
+
+#map origin
+origin = np.array([0,0])
+origin_mapped = u(origin,kappa,e)
+
+
+mapped_e = grad_u(midpoint,kappa,e)
+normal = compute_normal(midpoint,kappa,e)
+
+print('mapped_e', mapped_e)
+print('normal',normal )
+
+#
+# mapped_e = Rotation.dot(mapped_e)
+# normal = Rotation.dot(normal)
+
+
+# Plot Mapped_midPoint
+# ax.plot(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],    # data
+# marker='o',     # each marker will be rendered as a circle
+# markersize=4,   # marker size
+# markerfacecolor='orange',   # marker facecolor
+# markeredgecolor='black',  # marker edgecolor
+# markeredgewidth=1,       # marker edge width
+# linewidth=1,
+# zorder=4)          # line width
+
+# ax.quiver([midpoint_mapped[0]], [midpoint_mapped[1]], [midpoint_mapped[2]], [mapped_e[0]], [mapped_e[1]], [mapped_e[2]], color="red")
+# ax.quiver([midpoint_mapped[0]], [midpoint_mapped[1]], [midpoint_mapped[2]], [normal[0]], [normal[1]], [normal[2]], color="blue")
+
+# ax.arrow3D(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],
+#            mapped_e[0],mapped_e[1],mapped_e[2],
+#            mutation_scale=15,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='green',
+#            lw = 2,
+#            ec ='green',
+#            zorder=3)
+#
+# ax.arrow3D(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],
+#            normal[0],normal[1],normal[2],
+#            mutation_scale=15,
+#             lw = 2,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='blue',
+#            ec ='blue',
+#            zorder = 3)
+
+
+###-- TEST Rotation :
+# v = np.array([1,0,0])
+# t = np.array([0,1,0])
+#
+# ax.arrow3D(0,0,0,
+#            t[0],t[1],t[2],
+#            mutation_scale=10,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='blue',
+#            ec ='blue')
+#
+# # e_extend
+#
+# rotM = rot(v,np.pi/2)
+#
+# print('rotM:', rotM)
+#
+# rot_t = rotM.dot(t)
+#
+# print('rot_t:', rot_t)
+#
+# ax.arrow3D(0,0,0,
+#            rot_t[0],rot_t[1],rot_t[2],
+#            mutation_scale=10,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='blue',
+#            ec ='blue')
+
+### -------------------------------------------
+
+############################################################################################################################################
+####################################################################### KAPPA POSITIVE  ####################################################
+############################################################################################################################################
+
+# kappa = (-1)*kappa
+
+# if kappa == 0 :
+#     u1 = 0*x1
+#     u2 = x1*e[0] + x2*e[1]
+#     u3 = x2*e[0] - x1*e[1]
+# else :
+#     u1 = -(1/kappa)*np.cos(kappa*(x1*e[0]+x2*e[1])) + (1/kappa)
+#     u2 = (1/kappa)*np.sin(kappa*(x1*e[0]+x2*e[1]))
+#     u3 = x2*e[0] -x1*e[1]
+
+if kappa == 0 :
+    # u1 = 0*x1
+    # u2 = x1*e[0] + x2*e[1]
+    # u3 = x2*e[0] - x1*e[1]
+    u1 = x1*e[0] + x2*e[1]
+    u2 = x2*e[0] - x1*e[1]
+    u3 = 0*x1
+
+else :
+    # u1 = -(1/kappa)*np.cos(kappa*(x1*e[0]+x2*e[1])) + (1/kappa)
+    # u2 = (1/kappa)*np.sin(kappa*(x1*e[0]+x2*e[1]))
+    # u3 = x2*e[0] -x1*e[1]
+    u1 = -(1/kappa)*np.sin((-1)*kappa*(x1*e[0]+x2*e[1]))
+    u2 =  x2*e[0] -x1*e[1]
+    u3 = (1/kappa)*np.cos((-1)*kappa*(x1*e[0]+x2*e[1]))-(1/kappa)
+
+
+
+# ax.plot_surface(u1, u2, u3, color = 'w', rstride = 1, cstride = 1, facecolors=cm.autumn(colorfunction), alpha=.3)  ##This one!
+
+
+# T = rotate_data(X,Rotation_vector,Rotation_angle)
+
+T = rotate_data(np.array([u1,u2,u3]),Rotation)
+# T = rotate_data(T,np.array([0,1,0]),Rotation_angle)
+# T = rotate_data(T,np.array([0,0,1]),-1*Rotation_angle/2)
+
+# ax.plot_surface(T[0], T[1], T[2], rstride = 1, cstride = 1, facecolors=cm.autumn(colorfunction), alpha=.4, zorder=4, antialiased=False)
+# ax.plot_surface(T[0], T[1], T[2], rstride = 1, cstride = 1, facecolors=cm.autumn(colorfunction), alpha=.4, zorder=4, antialiased=True)
+# ax.plot_surface(T[0], T[1], T[2], rstride = 2, cstride = 2, facecolors=cm.autumn(colorfunction), alpha=.4, zorder=4)
+# ax.plot_surface(T[0], T[1], T[2], rstride = 10, cstride = 10, facecolors=cm.brg(colorfunction), alpha=.8, zorder=4)
+ax.plot_surface(T[0], T[1], T[2], rstride = 5, cstride = 5, color='orange', alpha=.8, zorder=4)
+# ax.plot_surface(T[0], T[1], T[2], rstride = 10, cstride = 10, color='blue', alpha=.8, zorder=4, shade=True)
+# ax.plot_surface(T[0], T[1], T[2], rstride = 1, cstride = 1, facecolors=cm.autumn(colorfunction), alpha=.4, zorder=4, shade=True)
+# ax.plot_surface(T[0], T[1], T[2], color = 'w', rstride = 1, cstride = 1, facecolors=cm.autumn(colorfunction), alpha=0.8, zorder=4)
+# ax.plot_surface(T[0], T[1], T[2],  rstride = 1, cstride = 1, facecolors=cm.autumn(colorfunction), alpha=1, zorde5r=5)
+
+# midpoint = np.array([(max(x)+min(x))/2,(max(y)+min(y))/2])
+# print('midpoint',midpoint)
+print('------------------ Kappa : ', kappa)
+# Map midpoint:
+midpoint_mapped = u(midpoint,kappa,e)
+print('mapped midpoint', midpoint_mapped)
+
+#map origin
+origin = np.array([0,0])
+origin_mapped = u(origin,kappa,e)
+
+
+mapped_e = grad_u(midpoint,kappa,e)
+normal = compute_normal(midpoint,kappa,e)
+
+print('mapped_e', mapped_e)
+print('normal',normal )
+
+
+#
+mapped_e = Rotation.dot(mapped_e)
+normal = Rotation.dot(normal)
+
+
+
+# Plot MIDPOINT:
+# ax.plot(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],    # data
+# marker='o',     # each marker will be rendered as a circle
+# markersize=4,   # marker size
+# markerfacecolor='orange',   # marker facecolor
+# markeredgecolor='black',  # marker edgecolor
+# markeredgewidth=1,       # marker edge width
+# linewidth=1,
+# zorder=5)          # line width
+
+
+#midpoint:
+endpoint = np.array([min(x),(max(y)+min(y))/2])
+print('endpoint',endpoint)
+
+# Map midpoint:
+endpoint_mapped = u(endpoint,kappa,e)
+print('mapped endpoint', endpoint_mapped)
+
+endpoint_mapped = Rotation.dot(endpoint_mapped)
+
+mapped_e = grad_u(endpoint,kappa,e)
+normal = compute_normal(endpoint,kappa,e)
+
+
+mapped_e = Rotation.dot(mapped_e)
+normal = Rotation.dot(normal)
+
+
+
+
+reverse_normal = np.array([ (-1)*normal[0], (-1)*normal[1], (-1)*normal[2]])
+
+ax.plot(endpoint_mapped[0],endpoint_mapped[1],endpoint_mapped[2],    # data
+marker='o',     # each marker will be rendered as a circle
+markersize=1,   # marker size
+markerfacecolor='black',   # marker facecolor
+markeredgecolor='black',  # marker edgecolor
+markeredgewidth=0.5,       # marker edge width
+linewidth=1,
+zorder=5)          # line width
+
+
+
+# ax.arrow3D(endpoint_mapped[0],endpoint_mapped[1],endpoint_mapped[2],
+#            mapped_e[0],mapped_e[1],mapped_e[2],
+#            mutation_scale=15,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='green',
+#            lw = 1.5,
+#            ec ='green',
+#            zorder=5)
+
+# ax.arrow3D(endpoint_mapped[0],endpoint_mapped[1],endpoint_mapped[2],
+#            normal[0],normal[1],normal[2],
+#            mutation_scale=15,
+#             lw = 1.5,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='blue',
+#            ec ='blue',
+#            zorder = 5)
+
+ax.arrow3D(endpoint_mapped[0],endpoint_mapped[1],endpoint_mapped[2],
+           reverse_normal[0],reverse_normal[1],reverse_normal[2],
+           mutation_scale=10,
+            lw = 1.5,
+           arrowstyle="-|>",
+           linestyle='-',fc='purple', alpha=0.75,
+           ec ='purple',
+           zorder = 5)
+
+
+
+
+# second Endpoint
+endpoint = np.array([max(x),(max(y)+min(y))/2])
+print('endpoint',endpoint)
+
+# Map midpoint:
+endpoint_mapped = u(endpoint,kappa,e)
+print('mapped endpoint', endpoint_mapped)
+
+endpoint_mapped = Rotation.dot(endpoint_mapped)
+
+mapped_e = grad_u(endpoint,kappa,e)
+normal = compute_normal(endpoint,kappa,e)
+
+
+mapped_e = Rotation.dot(mapped_e)
+normal = Rotation.dot(normal)
+
+
+
+
+reverse_normal = np.array([ (-1)*normal[0], (-1)*normal[1], (-1)*normal[2]])
+
+ax.plot(endpoint_mapped[0],endpoint_mapped[1],endpoint_mapped[2],    # data
+marker='o',     # each marker will be rendered as a circle
+markersize=1,   # marker size
+markerfacecolor='black',   # marker facecolor
+markeredgecolor='black',  # marker edgecolor
+markeredgewidth=0.5,       # marker edge width
+linewidth=1,
+zorder=5)          # line width
+
+
+
+# ax.arrow3D(endpoint_mapped[0],endpoint_mapped[1],endpoint_mapped[2],
+#            mapped_e[0],mapped_e[1],mapped_e[2],
+#            mutation_scale=15,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='green',
+#            lw = 1.5,
+#            ec ='green',
+#            zorder=5)
+
+# ax.arrow3D(endpoint_mapped[0],endpoint_mapped[1],endpoint_mapped[2],
+#            normal[0],normal[1],normal[2],
+#            mutation_scale=15,
+#             lw = 1.5,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='blue',
+#            ec ='blue',
+#            zorder = 5)
+
+ax.arrow3D(endpoint_mapped[0],endpoint_mapped[1],endpoint_mapped[2],
+           reverse_normal[0],reverse_normal[1],reverse_normal[2],
+           mutation_scale=10,
+            lw = 1.5,
+           arrowstyle="-|>",
+           linestyle='-',fc='purple', alpha=0.75,
+           ec ='purple',
+           zorder = 5)
+
+
+# ax.arrow3D(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],
+#            mapped_e[0],mapped_e[1],mapped_e[2],
+#            mutation_scale=15,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='green',
+#            lw = 1.5,
+#            ec ='green',
+#            zorder=5)
+#
+# ax.arrow3D(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],
+#            normal[0],normal[1],normal[2],
+#            mutation_scale=15,
+#             lw = 1.5,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='blue',
+#            ec ='blue',
+#            zorder = 5)
+
+
+############################################################################################################################################
+####################################################################### KAPPA ZERO #########################################################
+############################################################################################################################################
+kappa = 0
+
+# if kappa == 0 :
+#     u1 = 0*x1
+#     u2 = x1*e[0] + x2*e[1]
+#     u3 = x2*e[0] - x1*e[1]
+# else :
+#     u1 = -(1/kappa)*np.cos(kappa*(x1*e[0]+x2*e[1])) + (1/kappa)
+#     u2 = (1/kappa)*np.sin(kappa*(x1*e[0]+x2*e[1]))
+#     u3 = x2*e[0] -x1*e[1]
+
+if kappa == 0 :
+    # u1 = 0*x1
+    # u2 = x1*e[0] + x2*e[1]
+    # u3 = x2*e[0] - x1*e[1]
+    u1 = x1*e[0] + x2*e[1]
+    u2 = x2*e[0] - x1*e[1]
+    u3 = 0*x1
+
+else :
+    # u1 = -(1/kappa)*np.cos(kappa*(x1*e[0]+x2*e[1])) + (1/kappa)
+    # u2 = (1/kappa)*np.sin(kappa*(x1*e[0]+x2*e[1]))
+    # u3 = x2*e[0] -x1*e[1]
+    u1 = -(1/kappa)*np.sin((-1)*kappa*(x1*e[0]+x2*e[1]))
+    u2 =  x2*e[0] -x1*e[1]
+    u3 = (1/kappa)*np.cos((-1)*kappa*(x1*e[0]+x2*e[1]))-(1/kappa)
+# ax.plot_surface(u1, u2, u3,  rstride = 1, cstride = 1, color = 'white', alpha=0.85)
+
+# T = rotate_data(np.array([u1,u2,u3]),Rotation_vector,Rotation_angle)
+
+T = rotate_data(np.array([u1,u2,u3]),Rotation)
+# T = rotate_data(T,np.array([0,1,0]),Rotation_angle)
+# T = rotate_data(T,np.array([0,0,1]),-1*Rotation_angle/2)
+
+
+# ax.plot_surface(T[0], T[1], T[2],  rstride = 1, cstride = 1, color = 'white', alpha=0.55, zorder=2, antialiased=True)
+# ax.plot_surface(T[0], T[1], T[2],  rstride =1 , cstride = 1, color = 'white', alpha=0.55, zorder=3)
+
+# ax.plot_surface(T[0], T[1], T[2],  rstride = 1, cstride = 1, color = 'white', alpha=0.55, zorder=2)
+# ax.plot_surface(T[0], T[1], T[2],  rstride = 1, cstride = 1, color = 'white', alpha=0.5, zorder=2, antialiased=True)
+# ax.plot_surface(T[0], T[1], T[2],  rstride = 10, cstride = 10, color = 'white', alpha=0.55, zorder=2)
+ax.plot_surface(T[0], T[1], T[2],  rstride = 20, cstride = 20, color = 'gray', alpha=0.35, zorder=1, shade=True)
+# ax.plot_surface(T[0], T[1], T[2], color = 'white', alpha=0.55, zorder=2)
+
+# midpoint = np.array([(max(x)+min(x))/2,(max(y)+min(y))/2])
+mapped_e = grad_u(midpoint,kappa,e)
+normal_zeroCurv = compute_normal(midpoint,kappa,e)
+
+# Map midpoint:
+midpoint_mapped = u(midpoint,kappa,e)
+print('mapped midpoint', midpoint_mapped)
+
+##-----  PLOT MAPPED MIDPOINT :::
+
+# ax.plot(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],    # data
+# marker='o',     # each marker will be rendered as a circle
+# markersize=4,   # marker size
+# markerfacecolor='orange',   # marker facecolor
+# markeredgecolor='black',  # marker edgecolor
+# markeredgewidth=1,       # marker edge width
+# # linestyle='--',            # line style will be dash line
+# linewidth=1,
+# zorder=5)
+
+# ax.arrow3D(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],
+#            mapped_e[0],mapped_e[1],mapped_e[2],
+#            mutation_scale=10,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='red',
+#            ec ='red')
+#
+# ax.arrow3D(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],
+#            normal_zeroCurv[0],normal_zeroCurv[1],normal_zeroCurv[2],
+#            mutation_scale=10,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='blue',
+#            ec ='blue')
+
+
+##----------  PLOT MAPPED ORIGIN :::
+# origin = np.array([0,0])
+# origin_mapped = u(origin,kappa,e)
+# print('origin_mapped', origin_mapped)
+#
+# ax.plot(origin_mapped[0],origin_mapped[1],origin_mapped[2],    # data
+# marker='o',     # each marker will be rendered as a circle
+# markersize=4,   # marker size
+# markerfacecolor='green',   # marker facecolor
+# markeredgecolor='black',  # marker edgecolor
+# markeredgewidth=1,       # marker edge width
+# linewidth=1,
+# zorder=5)          # line width
+#
+# # rotate mapped origin
+# # v = np.array([1,0,0])
+# # alpha  = Rotation_angle
+#
+# rotM = rot(Rotation_vector,Rotation_angle)
+# # origin_mRot = rotate_data(origin_mapped,v,alpha)
+# origin_mRot = rotM.dot(origin_mapped)
+# print('origin_mapped Rotated', origin_mRot)
+#
+# # --- Compute Distance to Origin 3D
+# origin_3D=np.array([0,0,0])
+# distance = origin_mapped-origin_3D
+# print('distance', distance)
+
+## --------------------------------------------------------
+
+# COMPUTE ANGLE WITH Z AXIS
+z = np.array([0,0,1])
+print('test', normal_zeroCurv*z)
+angle_z = np.arccos(normal_zeroCurv.dot(z) /( (np.linalg.norm(z)*np.linalg.norm(normal_zeroCurv) ) ))
+print('angle between normal and z-axis', angle_z)
+
+## unfinished...
+
+
+
+
+###-------------------------------------  PLOT :
+plt.axis('off')
+# plt.axis('tight')
+
+# ADD colorbar
+# scamap = plt.cm.ScalarMappable(cmap='inferno')
+# fig.colorbar(scamap)
+
+# ax.colorbar()
+# ax.axis('auto')
+# ax.set_title(r'Cylindrical minimizer_$\kappa$='+ str(kappa)+ '_$e$=' +  str(e))
+# ax.set_title(r'Cylindrical minimizer' + '_$e$=' +  str(e))
+ax.set_xlabel(r"x-axis")
+ax.set_ylabel(r"y-axis")
+ax.set_zlabel(r"z-axis")
+
+# TEST :
+# ax.annotate3D('point 1', (0, 0, 0), xytext=(3, 3), textcoords='offset points')
+# ax.annotate3D('point 2', (0, 1, 0),
+#               xytext=(-30, -30),
+#               textcoords='offset points',
+#               arrowprops=dict(ec='black', fc='white', shrink=2.5))
+# ax.annotate3D('point 3', (0, 0, 1),
+#               xytext=(30, -30),
+#               textcoords='offset points',
+#               bbox=dict(boxstyle="round", fc="lightyellow"),
+#               arrowprops=dict(arrowstyle="-|>", ec='black', fc='white', lw=5))
+
+#######################################################################################################################
+
+u1 = T[0]
+u2 = T[1]
+u3 = T[2]
+
+# max_range = np.array([u1.max()-u1.min(), u2.max()-u2.min(), u3.max()-u3.min()]).max() /3
+max_range = np.array([u1.max()-u1.min(), u2.max()-u2.min(), u3.max()-u3.min()]).max() /12
+# max_range = np.array([u1.max()-u1.min(), u2.max()-u2.min(), u3.max()-u3.min()]).max() /8
+# max_range = np.array([u1.max()-u1.min(), u2.max()-u2.min(), u3.max()-u3.min()]).max() /10
+max_range = np.array([u1.max()-u1.min(), u2.max()-u2.min(), u3.max()-u3.min()]).max() /14
+# max_range = np.array([u1.max()-u1.min(), u2.max()-u2.min(), u3.max()-u3.min()]).max() /6
+# max_range = np.array([u1.max()-u1.min(), u2.max()-u2.min(), u3.max()-u3.min()]).max() /2
+mid_u1 = (u1.max()+u1.min()) * 0.5
+mid_u2 = (u2.max()+u2.min()) * 0.5
+mid_u3 = (u3.max()+u3.min()) * 0.5
+
+
+ax.set_xlim(mid_u1 - max_range, mid_u1 + max_range)
+ax.set_ylim(mid_u2 - max_range, mid_u2 + max_range)
+ax.set_zlim(mid_u3 - max_range, mid_u3 + max_range)
+
+ax.set_ylim((mid_u2 - max_range)-2, (mid_u2 + max_range)+2)
+# ax.set_zlim((mid_u2 - max_range), (mid_u2 + max_range)+2)
+# ax.set_ylim((mid_u2 - max_range)-1.5, (mid_u2 + max_range)+1.5)
+# # ax.autoscale(tight=True)
+# ax.set_xlim((mid_u1 - max_range)-1, (mid_u1 + max_range)+1)
+# ax.set_xlim((mid_u1 - max_range)-0.5, (mid_u1 + max_range)+0.5)
+ax.set_xlim((mid_u1 - max_range)-2, (mid_u1 + max_range)+2)
+# ax.set_ylim((mid_u2 - max_range)-2, (mid_u2 + max_range)+2)
+ax.set_zlim((mid_u2 - max_range), (mid_u2 + max_range)+2)
+
+# ax.set_ylim((mid_u2 - max_range)-2, (mid_u2 + max_range)+3)
+# ax.set_zlim((mid_u2 - max_range), (mid_u2 + max_range)+2)
+
+
+##----- CHANGE CAMERA POSITION:
+# ax.view_init(elev=10., azim=0)
+# ax.view_init(elev=38, azim=90)
+# ax.view_init(elev=38, azim=120)
+# ax.view_init(elev=38)
+
+# if e1 ::
+# ax.view_init(elev=44)
+# ax.view_init(elev=38, azim=-90)
+# ax.view_init(elev=38, azim=0)
+# ax.view_init(elev=25, azim=-30)
+# ax.view_init(elev=18, azim=-30)
+ax.view_init(elev=25, azim=-125)
+# ax.view_init(elev=25, azim=150)
+# ax.view_init(elev=25, azim=135)
+
+# ax.view_init(elev=25, azim=125)   #idx2
+
+
+
+# ax.view_init(elev=25, azim=145)
+
+
+# if e3 ::
+# ax.view_init(elev=25)
+
+# ax.set_xlim3d(-2, 2)
+# ax.set_ylim3d(-1.0,3.0)
+# ax.set_zlim3d(-1.5,2.5)
+
+# ax.set_ylim3d(-10,10)
+# ax.set_xlim(mid_u1 - max_range-0.2, mid_u1 + max_range+0.2)
+# ax.set_zlim(mid_u3 - max_range-0.2, mid_u3 + max_range+0.2)
+# ax.set_ylim(mid_u2 - max_range-0.2, mid_u2 + max_range+0.2)
+
+# width = 6.28 *0.5
+# height = width / 1.618
+# # height = width / 2.5
+# fig.set_size_inches(width, height)
+# fig.savefig('Test-Cylindrical.pdf')
+
+# Figurename = r'Cylindrical minimizer_$\kappa$='+ str(kappa)+ '_$e$=' +  str(e)
+# Figurename = r'Cylindrical minimizer' + '_$e$=' +  str(e)
+Figurename = r'1-ParFamMinimizer_idx' + str(idx)
+# plt.savefig("test.png", bbox_inches='tight')
+# plt.figure().set_size_inches(width, height)
+# plt.set_size_inches(width, height)
+
+
+# fig.set_size_inches(width, height) !!!!!
+
+
+
+
+fig.savefig(Figurename+".pdf")
+
+plt.savefig(Figurename+".png", bbox_inches='tight', dpi=300)
+# plt.savefig(Figurename+".png")
+plt.show()
+
+
+
+# #---------------------------------------------------------------

Python-Scripts/1-ParameterFamily-Minimizers_v2.py

+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 matplotlib.ticker as tickers
+import matplotlib as mpl
+from matplotlib.ticker import MultipleLocator,FormatStrFormatter,MaxNLocator
+from mpl_toolkits.mplot3d import Axes3D
+import pandas as pd
+import matplotlib.colors as mcolors
+from matplotlib import cm
+
+from mpl_toolkits.mplot3d.proj3d import proj_transform
+# from mpl_toolkits.mplot3d.axes3d import Axes3D
+from matplotlib.text import Annotation
+from matplotlib.patches import FancyArrowPatch
+
+# Extra packages :
+# from HelperFunctions import *
+# from ClassifyMin import *
+# from subprocess import Popen, PIPE
+#import sys
+
+###################### Documentation #########################
+
+#..... add description here
+
+###########################################################
+
+
+def rot(v,alpha):
+
+#rotate about axis v with degree deg in radians:
+
+
+    tmp = np.array([ [v[0]**2*(1-np.cos(alpha))+np.cos(alpha), v[0]*v[1]*(1-np.cos(alpha))-v[2]*np.sin(alpha), v[0]*v[2]*(1-np.cos(alpha))+ v[1]*np.sin(alpha) ],
+         [v[0]*v[1]*(1-np.cos(alpha))+v[2]*np.sin(alpha), v[1]**2*(1-np.cos(alpha))+np.cos(alpha), v[1]*v[2]*(1-np.cos(alpha))+v[0]*np.sin(alpha) ],
+         [v[2]*v[0]*(1-np.cos(alpha))-v[1]*np.sin(alpha), v[2]*v[1]*(1-np.cos(alpha))+v[0]*np.sin(alpha) , v[2]**2*(1-np.cos(alpha))+np.cos(alpha) ] ])
+
+    return tmp
+
+
+
+def rotate_data(X, R):
+#rotate about axis v with degree deg in radians:
+# X : DataSet
+# R : RotationMatrix
+    print('ROTATE DATA FUNCTION ---------------')
+
+    rot_matrix = R
+    # print('rot_matrix:', rot_matrix)
+    # print('rot_matrix.shape:', rot_matrix.shape)
+    # print('X', X)
+    # print('shape of X[0]', X.shape[0])
+    B = np.dot(rot_matrix, X.reshape(rot_matrix.shape[1],-1))
+    # print('shape of B', B.shape)
+    # print('B',B)
+    # print('B[0,:]', B[0,:])
+    # print('B[0,:].shape', B[0,:].shape)
+    Out = np.array([B[0,:].reshape(X.shape[1],X.shape[2]), B[1,:].reshape(X.shape[1],X.shape[2]), B[2,:].reshape(X.shape[1],X.shape[2])])
+    print('shape of Out', Out.shape)
+
+    return Out
+
+# def rotate_data(X, v,alpha): #(Old Version)
+# #rotate about axis v with degree deg in radians:
+# # X : DataSet
+#     print('ROTATE DATA FUNCTION ---------------')
+#     # v = np.array([1,0,0])
+#     # rotM = rot(v,np.pi/2)
+#     # print('rotM:', rotM)
+#     rot_matrix = rot(v,alpha)
+#     # print('rot_matrix:', rot_matrix)
+#     # print('rot_matrix.shape:', rot_matrix.shape)
+#
+#     # print('X', X)
+#     # print('shape of X[0]', X.shape[0])
+#     B = np.dot(rot_matrix, X.reshape(rot_matrix.shape[1],-1))
+#
+#     # print('shape of B', B.shape)
+#     # print('B',B)
+#     # print('B[0,:]', B[0,:])
+#     # print('B[0,:].shape', B[0,:].shape)
+#     Out = np.array([B[0,:].reshape(X.shape[1],X.shape[2]), B[1,:].reshape(X.shape[1],X.shape[2]), B[2,:].reshape(X.shape[1],X.shape[2])])
+#     print('shape of Out', Out.shape)
+#
+#     return Out
+
+
+# def translate_data(X, v):  ...
+# #rotate about axis v with degree deg in radians:
+# # X : DataSet
+#     print('ROTATE DATA FUNCTION ---------------')
+#     # v = np.array([1,0,0])
+#     # rotM = rot(v,np.pi/2)
+#     # print('rotM:', rotM)
+#
+#     print('X', X)
+#     print('shape of X[0]', X.shape[0])
+#
+#     Out = X + v
+#     return Out
+
+
+def u(x,kappa,e):
+
+    tmp = (x.dot(e))*kappa
+    # print('tmp for u',tmp)
+    if kappa == 0 :
+        tmp = np.array([0*x[0],  x[0]*e[0] + x[1]*e[1], x[1]*e[0] - x[0]*e[1] ])
+    else :
+        tmp = np.array([-(1/kappa)*np.cos(tmp)+(1/kappa),  (1/kappa)*np.sin(tmp), -x[0]*e[1]+x[1]*e[0] ])
+    return tmp
+
+
+
+
+def grad_u(x,kappa,e):
+
+    tmp = (x.dot(e))*kappa
+    # print('tmp',tmp)
+
+    grad_u = np.array([ [np.sin(tmp)*e[0], np.sin(tmp)*e[1]], [np.cos(tmp)*e[0], np.cos(tmp)*e[1]], [-e[1], e[0]] ])
+    # print('produkt', grad_u.dot(e) )
+    mapped_e = grad_u.dot(e)
+    # print('mapped_e:', mapped_e)
+    # print('siize of mapped_e', mapped_e.shape)
+    # mapped_e = mapped_e.transpose()
+    # print('mapped_e:', mapped_e)
+    # print('siize of mapped_e', mapped_e.shape)
+    return mapped_e
+
+def compute_normal(x,kappa,e):
+    tmp = (x.dot(e))*kappa
+    partial1_u = np.array([ np.sin(tmp)*e[0] ,np.cos(tmp)*e[0], -e[1] ])
+    partial2_u = np.array([ np.sin(tmp)*e[1], np.cos(tmp)*e[1], e[0]      ])
+    normal = np.cross(partial1_u,partial2_u)
+    # print('normal=',normal)
+    return normal
+
+
+
+class Annotation3D(Annotation):
+    def __init__(self, text, xyz, *args, **kwargs):
+        super().__init__(text, xy=(0, 0), *args, **kwargs)
+        self._xyz = xyz
+
+    def draw(self, renderer):
+        x2, y2, z2 = proj_transform(*self._xyz, self.axes.M)
+        self.xy = (x2, y2)
+        super().draw(renderer)
+
+def _annotate3D(ax, text, xyz, *args, **kwargs):
+    '''Add anotation `text` to an `Axes3d` instance.'''
+
+    annotation = Annotation3D(text, xyz, *args, **kwargs)
+    ax.add_artist(annotation)
+
+setattr(Axes3D, 'annotate3D', _annotate3D)
+
+class Arrow3D(FancyArrowPatch):
+
+    def __init__(self, x, y, z, dx, dy, dz, *args, **kwargs):
+        super().__init__((0, 0), (0, 0), *args, **kwargs)
+        self._xyz = (x, y, z)
+        self._dxdydz = (dx, dy, dz)
+
+    def draw(self, renderer):
+        x1, y1, z1 = self._xyz
+        dx, dy, dz = self._dxdydz
+        x2, y2, z2 = (x1 + dx, y1 + dy, z1 + dz)
+
+        xs, ys, zs = proj_transform((x1, x2), (y1, y2), (z1, z2), self.axes.M)
+        self.set_positions((xs[0], ys[0]), (xs[1], ys[1]))
+        super().draw(renderer)
+
+
+def _arrow3D(ax, x, y, z, dx, dy, dz, *args, **kwargs):
+    '''Add an 3d arrow to an `Axes3D` instance.'''
+
+    arrow = Arrow3D(x, y, z, dx, dy, dz, *args, **kwargs)
+    ax.add_artist(arrow)
+
+setattr(Axes3D, 'arrow3D', _arrow3D)
+################################################################################################################
+################################################################################################################
+################################################################################################################
+
+
+
+q1=1;
+q2=2;
+q12=1/2;
+q3=((4*q1*q2)**0.5-q12)/2;
+# H=[2*q1,q12+2*q3;q12+2*q3,2*q2];
+
+H = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+A = np.array([[q1,1/2*q12], [1/2*q12,q2] ])
+abar = np.array([q12+2*q3, 2*q2])
+abar = (1.0/math.sqrt((q12+2*q3)**2+(2*q2)**2))*abar
+
+print('abar:',abar)
+
+b = np.linalg.lstsq(A, abar)[0]
+print('b',b)
+
+
+# print('abar:',np.shape(abar))
+# print('np.transpose(abar):',np.shape(np.transpose(abar)))
+sstar = (1/(q1+q2))*abar.dot(A.dot(b))
+# sstar = (1/(q1+q2))*abar.dot(tmp)
+print('sstar', sstar)
+abarperp= np.array([abar[1],-abar[0]])
+print('abarperp:',abarperp)
+
+print('----------------------------')
+
+# ----------------------------------------------------------------
+
+N=1000;
+T = np.linspace(-sstar*(q12+2*q3)/(2*q2), sstar*(2*q2)/(q12+2*q3), num=N)
+print('T:', T)
+
+kappas = []
+alphas = []
+# G.append(float(s[0]))
+
+G_container = []
+abar_container = []
+e_container = []
+
+
+for t in T :
+
+    abar_current = sstar*abar+t*abarperp;
+    # print('abar_current', abar_current)
+    abar_current[abar_current < 1e-10] = 0
+    # print('abar_current', abar_current)
+    # G = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+    G = [abar_current[0], abar_current[1] , (2*abar_current[0]*abar_current[1])**0.5 ]
+    G_container.append(G)
+    abar_container.append(abar_current)
+    e = [(abar_current[0]/(abar_current[0]+abar_current[1]))**0.5, (abar_current[1]/(abar_current[0]+abar_current[1]))**0.5]
+    e_container.append(e)
+    kappa = abar_current[0]+abar_current[1]
+    alpha = math.atan2(e[1], e[0])
+    # print('angle current:', alpha)
+    kappas.append(kappa)
+    alphas.append(alpha)
+
+
+G_container = np.array(G_container)
+abar_container = np.array(abar_container)
+
+e_container = np.array(e_container)
+
+print('G_container', G_container)
+print('G_container.shape', G_container.shape)
+
+# idx_1 = np.where(alphas == np.pi/4)
+idx_1 = np.where(np.round(alphas,2) == round(np.pi/3,2))
+idx_2 = np.where(np.round(alphas,2) == 0.0)
+idx_3 = np.where(np.round(alphas,2) == round(np.pi/4,2))
+
+# idx_3 = np.where(alphas == 0)
+
+print('Index idx_1:', idx_1)
+print('Index idx_2:', idx_2)
+print('Index idx_3:', idx_3)
+print('Index idx_1[0][0]:', idx_1[0][0])
+print('Index idx_2[0][0]:', idx_2[0][0])
+print('Index idx_3[0][0]:', idx_3[0][0])
+
+alphas = np.array(alphas)
+kappas = np.array(kappas)
+
+
+# print('kappas:',kappas)
+# print('alphas:',alphas)
+print('min alpha:', min(alphas))
+print('min kappa:', min(kappas))
+
+
+print('G_container[idx_1[0][0]]', G_container[idx_1[0][0]])
+print('G_container[idx_2[0][0]]', G_container[idx_2[0][0]])
+print('G_container[idx_3[0][0]]', G_container[idx_3[0][0]])
+
+
+print('e_container[idx_1[0][0]]', e_container[idx_1[0][0]])
+print('e_container[idx_2[0][0]]', e_container[idx_2[0][0]])
+print('e_container[idx_3[0][0]]', e_container[idx_3[0][0]])
+
+
+
+###################################################
+
+reflect = False
+# reflect = True
+
+
+
+idx = 1
+
+if idx == 1 :
+    e = e_container[idx_1[0][0]]
+    kappa = kappas[idx_1[0][0]]
+    angle = alphas[idx_1[0][0]]
+    reflect = True
+
+if idx == 2 :
+    e = e_container[idx_2[0][0]]
+    kappa = kappas[idx_2[0][0]]
+    angle = alphas[idx_2[0][0]]
+
+
+if idx == 3 :
+    e = e_container[idx_3[0][0]]
+    kappa = kappas[idx_3[0][0]]
+    angle = alphas[idx_3[0][0]]
+
+### SCALE ?
+# kappa = kappa*2
+
+
+print('kappa:',kappa)
+print('angle:',angle)
+###################################################
+#### TEST apply reflection
+#
+# G_tmp = G_container[idx_1[0][0]]
+#
+# print('G_tmp', G_tmp)
+#
+# # Basis:
+# G_1 = np.array([[1.0,0.0], [0.0,0.0]])
+# G_2 = np.array([[0.0,0.0], [0.0,1.0]])
+# G_3 = (1/np.sqrt(2))*np.array([[0.0,1.0], [1.0,0.0]])
+# print('G_1', G_1)
+# print('G_2', G_2)
+# print('G_3', G_3)
+#
+# G = G_tmp[0] * G_1 + G_tmp[1]*G_2 + G_tmp[2]*G_3
+# print('G:', G )
+#
+# T = np.array([[1.0 , -1.0] , [-1.0,1.0]])
+#
+# TG = np.multiply(T,G)
+# print('TG', TG)
+#
+#
+#
+# v = np.array([np.sqrt(TG[0][0]),np.sqrt(TG[1][1]) ])
+# print('v', v)
+# print('norm(v):', np.linalg.norm(v))
+# norm_v = np.linalg.norm(v)
+#
+# kappa = norm_v**2
+#
+# e = (1/norm_v)*v
+# print('e:', e)
+# print('kappa:', kappa)
+
+
+
+
+
+
+if reflect == True:
+    reflected_e = np.array([e[0], -1*e[1]])
+    e = reflected_e                                         # Correct?! Reflect e on x-Axis ??!
+    print('reflected_e:', reflected_e)
+
+
+############################################################################################################################################
+####################################################################### KAPPA NEGATIVE ####################################################
+############################################################################################################################################
+# kappa = -2
+num_Points = 200
+num_Points = 100
+
+
+# e = np.array([1,0])
+# e = np.array([0,1])
+# e = np.array([1/np.sqrt(2),1/np.sqrt(2)])
+# e = np.array([1/2,np.sqrt(3)/2])
+# e = np.array([np.sqrt(3)/2,1/2])
+# e = np.array([-1,0])
+# e = np.array([0,-1])
+
+###--- Creating dataset
+x = np.linspace(-2,2,num_Points)
+x = np.linspace(-3,3,num_Points)
+x = np.linspace(-4,4,num_Points)
+
+# x = np.linspace(-1.5,1.5,num_Points)
+# x = np.linspace(-1,1,num_Points)
+y = np.linspace(-1/2,1/2,num_Points)
+y = np.linspace(-1/4,1/4,num_Points)
+
+print('type of x', type(x))
+print('max of x:', max(x))
+print('max of y:', max(y))
+# print('x:', x)
+
+x1, x2 = np.meshgrid(x,y)
+zero = 0*x1
+
+if kappa == 0 :
+    u1 = 0*x1
+    u2 = x1*e[0] + x2*e[1]
+    u3 = x2*e[0] - x1*e[1]
+
+else :
+    u1 = -(1/kappa)*np.cos(kappa*(x1*e[0]+x2*e[1])) + (1/kappa)
+    u2 = (1/kappa)*np.sin(kappa*(x1*e[0]+x2*e[1]))
+    u3 = x2*e[0] -x1*e[1]
+
+# print('np.size(u1)',np.size(u1))
+# print('u1.shape',u1.shape)
+# colorfunction=(u1**2+u2**2)
+# print('colofunction',colorfunction)
+
+# print('u1.size:',np.size(u1))
+# tmp = np.ones(np.size(u1))*kappa
+# print('np.size(tmp)',np.size(tmp))
+B = np.full_like(u1, 1)
+# colorfunction=(u3)                                              # TODO Color by angle
+# colorfunction=(np.ones(np.size(u1))*kappa)
+colorfunction=(B*kappa)
+# print('colofunction',colorfunction)
+norm=mcolors.Normalize(colorfunction.min(),colorfunction.max())
+
+
+# -----------------------------------------------------
+# Display the mesh
+fig = plt.figure()
+
+
+width = 6.28 *0.5
+width = 6.28 * 0.333
+height = width / 1.618
+height = width / 2.5
+height = width
+
+
+
+ax = plt.axes(projection ='3d', adjustable='box')
+
+
+###---TEST MAP e-vectprs!
+# e1 = np.array([1,0])
+# e2 = np.array([0,1])
+# e3 = np.array([1/np.sqrt(2),1/np.sqrt(2)])
+# e1 = np.array([0,1])
+# e2 = np.array([-1,0])
+# e3 = np.array([-1/np.sqrt(2),1/np.sqrt(2)])
+# e1_mapped = u(e1,kappa,e1)
+# e2_mapped = u(e2,kappa,e2)
+# e3_mapped = u(e3,kappa,e3)
+# print('e1 mapped:',e1_mapped)
+# print('e2 mapped:',e2_mapped)
+# print('e3 mapped:',e3_mapped)
+### -----------------------------------
+
+#--e1 :
+# Rotation_angle = -np.pi/2
+# Rotation_vector = np.array([0,1,0])
+
+#--e2:
+Rotation_angle = np.pi/2
+Rotation_vector = np.array([1,0,0])
+
+###--e = np.array([1/np.sqrt(2),1/np.sqrt(2)])
+# Rotation_angle = -np.pi/2
+# Rotation_vector = np.array([1,0,0])
+# #2te rotation :
+# Rotation_angle = np.pi/4
+# Rotation_vector = np.array([0,0,1])
+
+
+
+Rotation_angle = -np.pi/2
+Rotation_angle = 0
+# Rotation_angle = np.pi/2
+Rotation_vector = np.array([0,1,0])
+Rotation_vector = np.array([1,0,0])
+
+# rot(np.array([0,1,0]),np.pi/2)
+
+# ZERO ROTATION
+Rotation = rot(np.array([0,1,0]),0)
+
+
+
+# TEST :
+
+#DETERMINE ANGLE:
+angle = math.atan2(e[1], e[0])
+print('angle:', angle)
+
+## GENERAL TRANSFORMATION / ROTATION:
+Rotation = rot(np.array([0,0,1]),angle).dot(rot(np.array([0,1,0]),-np.pi/2))
+
+# Rotation = rot(np.array([0,0,1]),+np.pi/4).dot(Rotation)
+# Rotation = rot(np.array([0,0,1]),+np.pi/16).dot(Rotation)
+
+
+
+### if e1:
+# Rotation = rot(np.array([0,0,1]),-np.pi/4).dot(Rotation)
+# Rotation = rot(np.array([0,0,1]),+np.pi/16).dot(Rotation)
+
+# Add another rotation around z-axis:
+# Rotation = rot(np.array([0,0,1]),+np.pi).dot(Rotation)
+# Rotation = rot(np.array([0,0,1]),+np.pi/4).dot(Rotation)
+
+
+# Rotation = rot(np.array([0,0,1]),+np.pi/8).dot(Rotation)
+
+#e3 :
+# Rotation = rot(np.array([0,1,0]),-np.pi/2)
+# Rotation = rot(np.array([0,0,1]),np.pi/4).dot(rot(np.array([0,1,0]),-np.pi/2))
+
+# Rotation = rot(np.array([0,0,1]),np.pi/4)
+# Rotation = rot(np.array([1,0,0]),np.pi/4)
+#### if e1 :
+# Rotation = rot(np.array([0,1,0]),-np.pi/2)
+#### if e2:
+# Rotation = rot(np.array([0,1,0]),-np.pi/2).dot(rot(np.array([1,0,0]),-np.pi/2))
+# # #### if e3 :
+# zufall dass np.pi/4 genau dem Winkel angle alpha entspricht?:
+# (würde) bei e_2 keinen Unterschied machen um z achse zu rotieren?!
+
+# Rotation = rot(np.array([0,0,1]),np.pi/4).dot(rot(np.array([0,1,0]),-np.pi/2).dot(rot(np.array([1,0,0]),-np.pi/2)))
+# Rotation = rot(np.array([0,0,1]),np.pi/2).dot(rot(np.array([0,1,0]),-np.pi/2).dot(rot(np.array([1,0,0]),-np.pi/2)))
+
+# Rotation = rot(np.array([1,0,0]),np.pi/2)
+
+# Rotation_vector = e3_mapped  #TEST
+# Rotation_vector = np.array([-1/np.sqrt(2),1/np.sqrt(2)])
+# Rotation_vector = np.array([0,0,1])
+
+# v = np.array([1,0,0])
+# X = np.array([u1,u2,u3])
+
+
+
+
+# T = rotate_data(np.array([u1,u2,u3]),Rotation_vector,Rotation_angle)
+T = rotate_data(np.array([u1,u2,u3]),Rotation)
+
+# ax.plot_surface(T[0], T[1], T[2], color = 'w', rstride = 2, cstride = 2, facecolors=cm.brg(colorfunction), alpha=.4, zorder=4)
+# ax.plot_surface(T[0], T[1], T[2], color = 'w', rstride = 1, cstride = 1, facecolors=cm.viridis(colorfunction), alpha=.4, zorder=4)
+
+
+###---- PLOT PARAMETER-PLANE:
+# ax.plot_surface(x1,x2,zero,color = 'w', rstride = 1, cstride = 1 )
+
+
+print('------------------ Kappa : ', kappa)
+
+#midpoint:
+midpoint = np.array([(max(x)+min(x))/2,(max(y)+min(y))/2])
+print('midpoint',midpoint)
+
+# Map midpoint:
+midpoint_mapped = u(midpoint,kappa,e)
+print('mapped midpoint', midpoint_mapped)
+
+#map origin
+origin = np.array([0,0])
+origin_mapped = u(origin,kappa,e)
+
+
+mapped_e = grad_u(midpoint,kappa,e)
+normal = compute_normal(midpoint,kappa,e)
+
+print('mapped_e', mapped_e)
+print('normal',normal )
+
+#
+# mapped_e = Rotation.dot(mapped_e)
+# normal = Rotation.dot(normal)
+
+
+# Plot Mapped_midPoint
+# ax.plot(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],    # data
+# marker='o',     # each marker will be rendered as a circle
+# markersize=4,   # marker size
+# markerfacecolor='orange',   # marker facecolor
+# markeredgecolor='black',  # marker edgecolor
+# markeredgewidth=1,       # marker edge width
+# linewidth=1,
+# zorder=4)          # line width
+
+# ax.quiver([midpoint_mapped[0]], [midpoint_mapped[1]], [midpoint_mapped[2]], [mapped_e[0]], [mapped_e[1]], [mapped_e[2]], color="red")
+# ax.quiver([midpoint_mapped[0]], [midpoint_mapped[1]], [midpoint_mapped[2]], [normal[0]], [normal[1]], [normal[2]], color="blue")
+
+# ax.arrow3D(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],
+#            mapped_e[0],mapped_e[1],mapped_e[2],
+#            mutation_scale=15,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='green',
+#            lw = 2,
+#            ec ='green',
+#            zorder=3)
+#
+# ax.arrow3D(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],
+#            normal[0],normal[1],normal[2],
+#            mutation_scale=15,
+#             lw = 2,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='blue',
+#            ec ='blue',
+#            zorder = 3)
+
+
+###-- TEST Rotation :
+# v = np.array([1,0,0])
+# t = np.array([0,1,0])
+#
+# ax.arrow3D(0,0,0,
+#            t[0],t[1],t[2],
+#            mutation_scale=10,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='blue',
+#            ec ='blue')
+#
+# # e_extend
+#
+# rotM = rot(v,np.pi/2)
+#
+# print('rotM:', rotM)
+#
+# rot_t = rotM.dot(t)
+#
+# print('rot_t:', rot_t)
+#
+# ax.arrow3D(0,0,0,
+#            rot_t[0],rot_t[1],rot_t[2],
+#            mutation_scale=10,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='blue',
+#            ec ='blue')
+
+### -------------------------------------------
+
+############################################################################################################################################
+####################################################################### KAPPA POSITIVE  ####################################################
+############################################################################################################################################
+
+# kappa = (-1)*kappa
+
+if kappa == 0 :
+    u1 = 0*x1
+    u2 = x1*e[0] + x2*e[1]
+    u3 = x2*e[0] - x1*e[1]
+else :
+    u1 = -(1/kappa)*np.cos(kappa*(x1*e[0]+x2*e[1])) + (1/kappa)
+    u2 = (1/kappa)*np.sin(kappa*(x1*e[0]+x2*e[1]))
+    u3 = x2*e[0] -x1*e[1]
+# ax.plot_surface(u1, u2, u3, color = 'w', rstride = 1, cstride = 1, facecolors=cm.autumn(colorfunction), alpha=.3)  ##This one!
+
+
+# T = rotate_data(X,Rotation_vector,Rotation_angle)
+
+T = rotate_data(np.array([u1,u2,u3]),Rotation)
+# T = rotate_data(T,np.array([0,1,0]),Rotation_angle)
+# T = rotate_data(T,np.array([0,0,1]),-1*Rotation_angle/2)
+
+# ax.plot_surface(T[0], T[1], T[2], rstride = 1, cstride = 1, facecolors=cm.autumn(colorfunction), alpha=.4, zorder=4, antialiased=False)
+# ax.plot_surface(T[0], T[1], T[2], rstride = 1, cstride = 1, facecolors=cm.autumn(colorfunction), alpha=.4, zorder=4, antialiased=True)
+# ax.plot_surface(T[0], T[1], T[2], rstride = 2, cstride = 2, facecolors=cm.autumn(colorfunction), alpha=.4, zorder=4)
+# ax.plot_surface(T[0], T[1], T[2], rstride = 10, cstride = 10, facecolors=cm.brg(colorfunction), alpha=.8, zorder=4)
+ax.plot_surface(T[0], T[1], T[2], rstride = 5, cstride = 5, color='orange', alpha=.8, zorder=4)
+# ax.plot_surface(T[0], T[1], T[2], rstride = 10, cstride = 10, color='blue', alpha=.8, zorder=4, shade=True)
+# ax.plot_surface(T[0], T[1], T[2], rstride = 1, cstride = 1, facecolors=cm.autumn(colorfunction), alpha=.4, zorder=4, shade=True)
+# ax.plot_surface(T[0], T[1], T[2], color = 'w', rstride = 1, cstride = 1, facecolors=cm.autumn(colorfunction), alpha=0.8, zorder=4)
+# ax.plot_surface(T[0], T[1], T[2],  rstride = 1, cstride = 1, facecolors=cm.autumn(colorfunction), alpha=1, zorde5r=5)
+
+# midpoint = np.array([(max(x)+min(x))/2,(max(y)+min(y))/2])
+# print('midpoint',midpoint)
+print('------------------ Kappa : ', kappa)
+# Map midpoint:
+midpoint_mapped = u(midpoint,kappa,e)
+print('mapped midpoint', midpoint_mapped)
+
+#map origin
+origin = np.array([0,0])
+origin_mapped = u(origin,kappa,e)
+
+
+mapped_e = grad_u(midpoint,kappa,e)
+normal = compute_normal(midpoint,kappa,e)
+
+print('mapped_e', mapped_e)
+print('normal',normal )
+
+
+#
+mapped_e = Rotation.dot(mapped_e)
+normal = Rotation.dot(normal)
+
+
+
+# Plot MIDPOINT:
+# ax.plot(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],    # data
+# marker='o',     # each marker will be rendered as a circle
+# markersize=4,   # marker size
+# markerfacecolor='orange',   # marker facecolor
+# markeredgecolor='black',  # marker edgecolor
+# markeredgewidth=1,       # marker edge width
+# linewidth=1,
+# zorder=5)          # line width
+
+
+#midpoint:
+endpoint = np.array([min(x),(max(y)+min(y))/2])
+print('endpoint',endpoint)
+
+# Map midpoint:
+endpoint_mapped = u(endpoint,kappa,e)
+print('mapped endpoint', endpoint_mapped)
+
+endpoint_mapped = Rotation.dot(endpoint_mapped)
+
+mapped_e = grad_u(endpoint,kappa,e)
+normal = compute_normal(endpoint,kappa,e)
+
+
+mapped_e = Rotation.dot(mapped_e)
+normal = Rotation.dot(normal)
+
+
+
+
+# ax.arrow3D(endpoint_mapped[0],endpoint_mapped[1],endpoint_mapped[2],
+#            mapped_e[0],mapped_e[1],mapped_e[2],
+#            mutation_scale=15,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='green',
+#            lw = 1.5,
+#            ec ='green',
+#            zorder=5)
+#
+# ax.arrow3D(endpoint_mapped[0],endpoint_mapped[1],endpoint_mapped[2],
+#            normal[0],normal[1],normal[2],
+#            mutation_scale=15,
+#             lw = 1.5,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='blue',
+#            ec ='blue',
+#            zorder = 5)
+
+
+# ax.arrow3D(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],
+#            mapped_e[0],mapped_e[1],mapped_e[2],
+#            mutation_scale=15,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='green',
+#            lw = 1.5,
+#            ec ='green',
+#            zorder=5)
+#
+# ax.arrow3D(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],
+#            normal[0],normal[1],normal[2],
+#            mutation_scale=15,
+#             lw = 1.5,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='blue',
+#            ec ='blue',
+#            zorder = 5)
+
+
+############################################################################################################################################
+####################################################################### KAPPA ZERO #########################################################
+############################################################################################################################################
+kappa = 0
+
+if kappa == 0 :
+    u1 = 0*x1
+    u2 = x1*e[0] + x2*e[1]
+    u3 = x2*e[0] - x1*e[1]
+else :
+    u1 = -(1/kappa)*np.cos(kappa*(x1*e[0]+x2*e[1])) + (1/kappa)
+    u2 = (1/kappa)*np.sin(kappa*(x1*e[0]+x2*e[1]))
+    u3 = x2*e[0] -x1*e[1]
+# ax.plot_surface(u1, u2, u3,  rstride = 1, cstride = 1, color = 'white', alpha=0.85)
+
+# T = rotate_data(np.array([u1,u2,u3]),Rotation_vector,Rotation_angle)
+
+T = rotate_data(np.array([u1,u2,u3]),Rotation)
+# T = rotate_data(T,np.array([0,1,0]),Rotation_angle)
+# T = rotate_data(T,np.array([0,0,1]),-1*Rotation_angle/2)
+
+
+# ax.plot_surface(T[0], T[1], T[2],  rstride = 1, cstride = 1, color = 'white', alpha=0.55, zorder=2, antialiased=True)
+# ax.plot_surface(T[0], T[1], T[2],  rstride =1 , cstride = 1, color = 'white', alpha=0.55, zorder=3)
+
+# ax.plot_surface(T[0], T[1], T[2],  rstride = 1, cstride = 1, color = 'white', alpha=0.55, zorder=2)
+# ax.plot_surface(T[0], T[1], T[2],  rstride = 1, cstride = 1, color = 'white', alpha=0.5, zorder=2, antialiased=True)
+# ax.plot_surface(T[0], T[1], T[2],  rstride = 10, cstride = 10, color = 'white', alpha=0.55, zorder=2)
+ax.plot_surface(T[0], T[1], T[2],  rstride = 20, cstride = 20, color = 'gray', alpha=0.35, zorder=1, shade=True)
+# ax.plot_surface(T[0], T[1], T[2], color = 'white', alpha=0.55, zorder=2)
+
+# midpoint = np.array([(max(x)+min(x))/2,(max(y)+min(y))/2])
+mapped_e = grad_u(midpoint,kappa,e)
+normal_zeroCurv = compute_normal(midpoint,kappa,e)
+
+# Map midpoint:
+midpoint_mapped = u(midpoint,kappa,e)
+print('mapped midpoint', midpoint_mapped)
+
+##-----  PLOT MAPPED MIDPOINT :::
+
+# ax.plot(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],    # data
+# marker='o',     # each marker will be rendered as a circle
+# markersize=4,   # marker size
+# markerfacecolor='orange',   # marker facecolor
+# markeredgecolor='black',  # marker edgecolor
+# markeredgewidth=1,       # marker edge width
+# # linestyle='--',            # line style will be dash line
+# linewidth=1,
+# zorder=5)
+
+# ax.arrow3D(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],
+#            mapped_e[0],mapped_e[1],mapped_e[2],
+#            mutation_scale=10,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='red',
+#            ec ='red')
+#
+# ax.arrow3D(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],
+#            normal_zeroCurv[0],normal_zeroCurv[1],normal_zeroCurv[2],
+#            mutation_scale=10,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='blue',
+#            ec ='blue')
+
+
+##----------  PLOT MAPPED ORIGIN :::
+# origin = np.array([0,0])
+# origin_mapped = u(origin,kappa,e)
+# print('origin_mapped', origin_mapped)
+#
+# ax.plot(origin_mapped[0],origin_mapped[1],origin_mapped[2],    # data
+# marker='o',     # each marker will be rendered as a circle
+# markersize=4,   # marker size
+# markerfacecolor='green',   # marker facecolor
+# markeredgecolor='black',  # marker edgecolor
+# markeredgewidth=1,       # marker edge width
+# linewidth=1,
+# zorder=5)          # line width
+#
+# # rotate mapped origin
+# # v = np.array([1,0,0])
+# # alpha  = Rotation_angle
+#
+# rotM = rot(Rotation_vector,Rotation_angle)
+# # origin_mRot = rotate_data(origin_mapped,v,alpha)
+# origin_mRot = rotM.dot(origin_mapped)
+# print('origin_mapped Rotated', origin_mRot)
+#
+# # --- Compute Distance to Origin 3D
+# origin_3D=np.array([0,0,0])
+# distance = origin_mapped-origin_3D
+# print('distance', distance)
+
+## --------------------------------------------------------
+
+# COMPUTE ANGLE WITH Z AXIS
+z = np.array([0,0,1])
+print('test', normal_zeroCurv*z)
+angle_z = np.arccos(normal_zeroCurv.dot(z) /( (np.linalg.norm(z)*np.linalg.norm(normal_zeroCurv) ) ))
+print('angle between normal and z-axis', angle_z)
+
+## unfinished...
+
+
+
+
+###-------------------------------------  PLOT :
+plt.axis('off')
+# plt.axis('tight')
+
+# ADD colorbar
+# scamap = plt.cm.ScalarMappable(cmap='inferno')
+# fig.colorbar(scamap)
+
+# ax.colorbar()
+# ax.axis('auto')
+# ax.set_title(r'Cylindrical minimizer_$\kappa$='+ str(kappa)+ '_$e$=' +  str(e))
+# ax.set_title(r'Cylindrical minimizer' + '_$e$=' +  str(e))
+ax.set_xlabel(r"x-axis")
+ax.set_ylabel(r"y-axis")
+ax.set_zlabel(r"z-axis")
+
+# TEST :
+# ax.annotate3D('point 1', (0, 0, 0), xytext=(3, 3), textcoords='offset points')
+# ax.annotate3D('point 2', (0, 1, 0),
+#               xytext=(-30, -30),
+#               textcoords='offset points',
+#               arrowprops=dict(ec='black', fc='white', shrink=2.5))
+# ax.annotate3D('point 3', (0, 0, 1),
+#               xytext=(30, -30),
+#               textcoords='offset points',
+#               bbox=dict(boxstyle="round", fc="lightyellow"),
+#               arrowprops=dict(arrowstyle="-|>", ec='black', fc='white', lw=5))
+
+#######################################################################################################################
+
+u1 = T[0]
+u2 = T[1]
+u3 = T[2]
+
+# max_range = np.array([u1.max()-u1.min(), u2.max()-u2.min(), u3.max()-u3.min()]).max() /3
+# max_range = np.array([u1.max()-u1.min(), u2.max()-u2.min(), u3.max()-u3.min()]).max() /12
+# max_range = np.array([u1.max()-u1.min(), u2.max()-u2.min(), u3.max()-u3.min()]).max() /8
+# max_range = np.array([u1.max()-u1.min(), u2.max()-u2.min(), u3.max()-u3.min()]).max() /10
+max_range = np.array([u1.max()-u1.min(), u2.max()-u2.min(), u3.max()-u3.min()]).max() /14
+# max_range = np.array([u1.max()-u1.min(), u2.max()-u2.min(), u3.max()-u3.min()]).max() /6
+# max_range = np.array([u1.max()-u1.min(), u2.max()-u2.min(), u3.max()-u3.min()]).max() /2
+mid_u1 = (u1.max()+u1.min()) * 0.5
+mid_u2 = (u2.max()+u2.min()) * 0.5
+mid_u3 = (u3.max()+u3.min()) * 0.5
+
+
+ax.set_xlim(mid_u1 - max_range, mid_u1 + max_range)
+ax.set_ylim(mid_u2 - max_range, mid_u2 + max_range)
+ax.set_zlim(mid_u3 - max_range, mid_u3 + max_range)
+
+ax.set_ylim((mid_u2 - max_range)-2, (mid_u2 + max_range)+2)
+ax.set_zlim((mid_u2 - max_range), (mid_u2 + max_range)+2)
+# ax.set_ylim((mid_u2 - max_range)-1.5, (mid_u2 + max_range)+1.5)
+# ax.autoscale(tight=True)
+ax.set_xlim((mid_u1 - max_range)-1, (mid_u1 + max_range)+1)
+ax.set_ylim((mid_u2 - max_range)-2, (mid_u2 + max_range)+2)
+ax.set_zlim((mid_u2 - max_range), (mid_u2 + max_range)+2)
+
+# ax.set_ylim((mid_u2 - max_range)-2, (mid_u2 + max_range)+3)
+# ax.set_zlim((mid_u2 - max_range), (mid_u2 + max_range)+2)
+
+
+##----- CHANGE CAMERA POSITION:
+# ax.view_init(elev=10., azim=0)
+# ax.view_init(elev=38, azim=90)
+# ax.view_init(elev=38, azim=120)
+# ax.view_init(elev=38)
+
+# if e1 ::
+# ax.view_init(elev=44)
+# ax.view_init(elev=38, azim=-90)
+# ax.view_init(elev=38, azim=0)
+# ax.view_init(elev=25, azim=-30)
+ax.view_init(elev=18, azim=-30)
+
+# if e3 ::
+# ax.view_init(elev=25)
+
+# ax.set_xlim3d(-2, 2)
+# ax.set_ylim3d(-1.0,3.0)
+# ax.set_zlim3d(-1.5,2.5)
+
+# ax.set_ylim3d(-10,10)
+# ax.set_xlim(mid_u1 - max_range-0.2, mid_u1 + max_range+0.2)
+# ax.set_zlim(mid_u3 - max_range-0.2, mid_u3 + max_range+0.2)
+# ax.set_ylim(mid_u2 - max_range-0.2, mid_u2 + max_range+0.2)
+
+# width = 6.28 *0.5
+# height = width / 1.618
+# # height = width / 2.5
+# fig.set_size_inches(width, height)
+# fig.savefig('Test-Cylindrical.pdf')
+
+# Figurename = r'Cylindrical minimizer_$\kappa$='+ str(kappa)+ '_$e$=' +  str(e)
+# Figurename = r'Cylindrical minimizer' + '_$e$=' +  str(e)
+Figurename = r'1-ParFamMinimizer_idx' + str(idx)
+# plt.savefig("test.png", bbox_inches='tight')
+# plt.figure().set_size_inches(width, height)
+# plt.set_size_inches(width, height)
+
+
+fig.set_size_inches(width, height)
+fig.savefig(Figurename+".pdf")
+
+plt.savefig(Figurename+".png", bbox_inches='tight')
+# plt.savefig(Figurename+".png")
+plt.show()
+
+
+
+# #---------------------------------------------------------------

Python-Scripts/1-ParameterFamily-Minimizers_v3.py

+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 matplotlib.ticker as tickers
+import matplotlib as mpl
+from matplotlib.ticker import MultipleLocator,FormatStrFormatter,MaxNLocator
+from mpl_toolkits.mplot3d import Axes3D
+import pandas as pd
+import matplotlib.colors as mcolors
+from matplotlib import cm
+
+from mpl_toolkits.mplot3d.proj3d import proj_transform
+# from mpl_toolkits.mplot3d.axes3d import Axes3D
+from matplotlib.text import Annotation
+from matplotlib.patches import FancyArrowPatch
+
+# Extra packages :
+# from HelperFunctions import *
+# from ClassifyMin import *
+# from subprocess import Popen, PIPE
+#import sys
+
+###################### Documentation #########################
+
+#..... add description here
+
+###########################################################
+
+
+def rot(v,alpha):
+
+#rotate about axis v with degree deg in radians:
+
+
+    tmp = np.array([ [v[0]**2*(1-np.cos(alpha))+np.cos(alpha), v[0]*v[1]*(1-np.cos(alpha))-v[2]*np.sin(alpha), v[0]*v[2]*(1-np.cos(alpha))+ v[1]*np.sin(alpha) ],
+         [v[0]*v[1]*(1-np.cos(alpha))+v[2]*np.sin(alpha), v[1]**2*(1-np.cos(alpha))+np.cos(alpha), v[1]*v[2]*(1-np.cos(alpha))+v[0]*np.sin(alpha) ],
+         [v[2]*v[0]*(1-np.cos(alpha))-v[1]*np.sin(alpha), v[2]*v[1]*(1-np.cos(alpha))+v[0]*np.sin(alpha) , v[2]**2*(1-np.cos(alpha))+np.cos(alpha) ] ])
+
+    return tmp
+
+
+
+def rotate_data(X, R):
+#rotate about axis v with degree deg in radians:
+# X : DataSet
+# R : RotationMatrix
+    print('ROTATE DATA FUNCTION ---------------')
+
+    rot_matrix = R
+    # print('rot_matrix:', rot_matrix)
+    # print('rot_matrix.shape:', rot_matrix.shape)
+    # print('X', X)
+    # print('shape of X[0]', X.shape[0])
+    B = np.dot(rot_matrix, X.reshape(rot_matrix.shape[1],-1))
+    # print('shape of B', B.shape)
+    # print('B',B)
+    # print('B[0,:]', B[0,:])
+    # print('B[0,:].shape', B[0,:].shape)
+    Out = np.array([B[0,:].reshape(X.shape[1],X.shape[2]), B[1,:].reshape(X.shape[1],X.shape[2]), B[2,:].reshape(X.shape[1],X.shape[2])])
+    print('shape of Out', Out.shape)
+
+    return Out
+
+# def rotate_data(X, v,alpha): #(Old Version)
+# #rotate about axis v with degree deg in radians:
+# # X : DataSet
+#     print('ROTATE DATA FUNCTION ---------------')
+#     # v = np.array([1,0,0])
+#     # rotM = rot(v,np.pi/2)
+#     # print('rotM:', rotM)
+#     rot_matrix = rot(v,alpha)
+#     # print('rot_matrix:', rot_matrix)
+#     # print('rot_matrix.shape:', rot_matrix.shape)
+#
+#     # print('X', X)
+#     # print('shape of X[0]', X.shape[0])
+#     B = np.dot(rot_matrix, X.reshape(rot_matrix.shape[1],-1))
+#
+#     # print('shape of B', B.shape)
+#     # print('B',B)
+#     # print('B[0,:]', B[0,:])
+#     # print('B[0,:].shape', B[0,:].shape)
+#     Out = np.array([B[0,:].reshape(X.shape[1],X.shape[2]), B[1,:].reshape(X.shape[1],X.shape[2]), B[2,:].reshape(X.shape[1],X.shape[2])])
+#     print('shape of Out', Out.shape)
+#
+#     return Out
+
+
+# def translate_data(X, v):  ...
+# #rotate about axis v with degree deg in radians:
+# # X : DataSet
+#     print('ROTATE DATA FUNCTION ---------------')
+#     # v = np.array([1,0,0])
+#     # rotM = rot(v,np.pi/2)
+#     # print('rotM:', rotM)
+#
+#     print('X', X)
+#     print('shape of X[0]', X.shape[0])
+#
+#     Out = X + v
+#     return Out
+
+
+def u(x,kappa,e):
+
+    tmp = (x.dot(e))*kappa
+    # print('tmp for u',tmp)
+    if kappa == 0 :
+        tmp = np.array([0*x[0],  x[0]*e[0] + x[1]*e[1], x[1]*e[0] - x[0]*e[1] ])
+    else :
+        tmp = np.array([-(1/kappa)*np.cos(tmp)+(1/kappa),  (1/kappa)*np.sin(tmp), -x[0]*e[1]+x[1]*e[0] ])
+    return tmp
+
+
+
+
+def grad_u(x,kappa,e):
+
+    tmp = (x.dot(e))*kappa
+    # print('tmp',tmp)
+
+    grad_u = np.array([ [np.sin(tmp)*e[0], np.sin(tmp)*e[1]], [np.cos(tmp)*e[0], np.cos(tmp)*e[1]], [-e[1], e[0]] ])
+    # print('produkt', grad_u.dot(e) )
+    mapped_e = grad_u.dot(e)
+    # print('mapped_e:', mapped_e)
+    # print('siize of mapped_e', mapped_e.shape)
+    # mapped_e = mapped_e.transpose()
+    # print('mapped_e:', mapped_e)
+    # print('siize of mapped_e', mapped_e.shape)
+    return mapped_e
+
+def compute_normal(x,kappa,e):
+    tmp = (x.dot(e))*kappa
+    partial1_u = np.array([ np.sin(tmp)*e[0] ,np.cos(tmp)*e[0], -e[1] ])
+    partial2_u = np.array([ np.sin(tmp)*e[1], np.cos(tmp)*e[1], e[0]      ])
+    normal = np.cross(partial1_u,partial2_u)
+    # print('normal=',normal)
+    return normal
+
+
+
+class Annotation3D(Annotation):
+    def __init__(self, text, xyz, *args, **kwargs):
+        super().__init__(text, xy=(0, 0), *args, **kwargs)
+        self._xyz = xyz
+
+    def draw(self, renderer):
+        x2, y2, z2 = proj_transform(*self._xyz, self.axes.M)
+        self.xy = (x2, y2)
+        super().draw(renderer)
+
+def _annotate3D(ax, text, xyz, *args, **kwargs):
+    '''Add anotation `text` to an `Axes3d` instance.'''
+
+    annotation = Annotation3D(text, xyz, *args, **kwargs)
+    ax.add_artist(annotation)
+
+setattr(Axes3D, 'annotate3D', _annotate3D)
+
+class Arrow3D(FancyArrowPatch):
+
+    def __init__(self, x, y, z, dx, dy, dz, *args, **kwargs):
+        super().__init__((0, 0), (0, 0), *args, **kwargs)
+        self._xyz = (x, y, z)
+        self._dxdydz = (dx, dy, dz)
+
+    def draw(self, renderer):
+        x1, y1, z1 = self._xyz
+        dx, dy, dz = self._dxdydz
+        x2, y2, z2 = (x1 + dx, y1 + dy, z1 + dz)
+
+        xs, ys, zs = proj_transform((x1, x2), (y1, y2), (z1, z2), self.axes.M)
+        self.set_positions((xs[0], ys[0]), (xs[1], ys[1]))
+        super().draw(renderer)
+
+
+def _arrow3D(ax, x, y, z, dx, dy, dz, *args, **kwargs):
+    '''Add an 3d arrow to an `Axes3D` instance.'''
+
+    arrow = Arrow3D(x, y, z, dx, dy, dz, *args, **kwargs)
+    ax.add_artist(arrow)
+
+setattr(Axes3D, 'arrow3D', _arrow3D)
+################################################################################################################
+################################################################################################################
+################################################################################################################
+
+
+
+q1=1;
+q2=2;
+q12=1/2;
+q3=((4*q1*q2)**0.5-q12)/2;
+# H=[2*q1,q12+2*q3;q12+2*q3,2*q2];
+
+H = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+A = np.array([[q1,1/2*q12], [1/2*q12,q2] ])
+abar = np.array([q12+2*q3, 2*q2])
+abar = (1.0/math.sqrt((q12+2*q3)**2+(2*q2)**2))*abar
+
+print('abar:',abar)
+
+b = np.linalg.lstsq(A, abar)[0]
+print('b',b)
+
+
+# print('abar:',np.shape(abar))
+# print('np.transpose(abar):',np.shape(np.transpose(abar)))
+sstar = (1/(q1+q2))*abar.dot(A.dot(b))
+# sstar = (1/(q1+q2))*abar.dot(tmp)
+print('sstar', sstar)
+abarperp= np.array([abar[1],-abar[0]])
+print('abarperp:',abarperp)
+
+print('----------------------------')
+
+# ----------------------------------------------------------------
+
+N=1000;
+T = np.linspace(-sstar*(q12+2*q3)/(2*q2), sstar*(2*q2)/(q12+2*q3), num=N)
+print('T:', T)
+
+kappas = []
+alphas = []
+# G.append(float(s[0]))
+
+G_container = []
+abar_container = []
+e_container = []
+
+
+for t in T :
+
+    abar_current = sstar*abar+t*abarperp;
+    # print('abar_current', abar_current)
+    abar_current[abar_current < 1e-10] = 0
+    # print('abar_current', abar_current)
+    # G = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+    G = [abar_current[0], abar_current[1] , (2*abar_current[0]*abar_current[1])**0.5 ]
+    G_container.append(G)
+    abar_container.append(abar_current)
+    e = [(abar_current[0]/(abar_current[0]+abar_current[1]))**0.5, (abar_current[1]/(abar_current[0]+abar_current[1]))**0.5]
+    e_container.append(e)
+    kappa = abar_current[0]+abar_current[1]
+    alpha = math.atan2(e[1], e[0])
+    # print('angle current:', alpha)
+    kappas.append(kappa)
+    alphas.append(alpha)
+
+
+G_container = np.array(G_container)
+abar_container = np.array(abar_container)
+
+e_container = np.array(e_container)
+
+print('G_container', G_container)
+print('G_container.shape', G_container.shape)
+
+# idx_1 = np.where(alphas == np.pi/4)
+idx_1 = np.where(np.round(alphas,2) == round(np.pi/3,2))
+idx_2 = np.where(np.round(alphas,2) == 0.0)
+idx_3 = np.where(np.round(alphas,2) == round(np.pi/4,2))
+
+# idx_3 = np.where(alphas == 0)
+
+print('Index idx_1:', idx_1)
+print('Index idx_2:', idx_2)
+print('Index idx_3:', idx_3)
+print('Index idx_1[0][0]:', idx_1[0][0])
+print('Index idx_2[0][0]:', idx_2[0][0])
+print('Index idx_3[0][0]:', idx_3[0][0])
+
+alphas = np.array(alphas)
+kappas = np.array(kappas)
+
+
+# print('kappas:',kappas)
+# print('alphas:',alphas)
+print('min alpha:', min(alphas))
+print('min kappa:', min(kappas))
+
+
+print('G_container[idx_1[0][0]]', G_container[idx_1[0][0]])
+print('G_container[idx_2[0][0]]', G_container[idx_2[0][0]])
+print('G_container[idx_3[0][0]]', G_container[idx_3[0][0]])
+
+
+print('e_container[idx_1[0][0]]', e_container[idx_1[0][0]])
+print('e_container[idx_2[0][0]]', e_container[idx_2[0][0]])
+print('e_container[idx_3[0][0]]', e_container[idx_3[0][0]])
+
+
+
+###################################################
+
+reflect = False
+# reflect = True
+
+
+
+idx = 1
+
+if idx == 1 :
+    e = e_container[idx_1[0][0]]
+    kappa = kappas[idx_1[0][0]]
+    angle = alphas[idx_1[0][0]]
+    reflect = True
+
+if idx == 2 :
+    e = e_container[idx_2[0][0]]
+    kappa = kappas[idx_2[0][0]]
+    angle = alphas[idx_2[0][0]]
+
+
+if idx == 3 :
+    e = e_container[idx_3[0][0]]
+    kappa = kappas[idx_3[0][0]]
+    angle = alphas[idx_3[0][0]]
+
+### SCALE ?
+# kappa = kappa*2
+
+
+print('kappa:',kappa)
+print('angle:',angle)
+###################################################
+#### TEST apply reflection
+#
+# G_tmp = G_container[idx_1[0][0]]
+#
+# print('G_tmp', G_tmp)
+#
+# # Basis:
+# G_1 = np.array([[1.0,0.0], [0.0,0.0]])
+# G_2 = np.array([[0.0,0.0], [0.0,1.0]])
+# G_3 = (1/np.sqrt(2))*np.array([[0.0,1.0], [1.0,0.0]])
+# print('G_1', G_1)
+# print('G_2', G_2)
+# print('G_3', G_3)
+#
+# G = G_tmp[0] * G_1 + G_tmp[1]*G_2 + G_tmp[2]*G_3
+# print('G:', G )
+#
+# T = np.array([[1.0 , -1.0] , [-1.0,1.0]])
+#
+# TG = np.multiply(T,G)
+# print('TG', TG)
+#
+#
+#
+# v = np.array([np.sqrt(TG[0][0]),np.sqrt(TG[1][1]) ])
+# print('v', v)
+# print('norm(v):', np.linalg.norm(v))
+# norm_v = np.linalg.norm(v)
+#
+# kappa = norm_v**2
+#
+# e = (1/norm_v)*v
+# print('e:', e)
+# print('kappa:', kappa)
+
+
+
+
+
+
+if reflect == True:
+    reflected_e = np.array([e[0], -1*e[1]])
+    e = reflected_e                                         # Correct?! Reflect e on x-Axis ??!
+    print('reflected_e:', reflected_e)
+
+
+############################################################################################################################################
+####################################################################### KAPPA NEGATIVE ####################################################
+############################################################################################################################################
+# kappa = -2
+num_Points = 200
+num_Points = 100
+
+
+# e = np.array([1,0])
+# e = np.array([0,1])
+# e = np.array([1/np.sqrt(2),1/np.sqrt(2)])
+# e = np.array([1/2,np.sqrt(3)/2])
+# e = np.array([np.sqrt(3)/2,1/2])
+# e = np.array([-1,0])
+# e = np.array([0,-1])
+
+###--- Creating dataset
+x = np.linspace(-2,2,num_Points)
+x = np.linspace(-3,3,num_Points)
+x = np.linspace(-4,4,num_Points)
+
+# x = np.linspace(-1.5,1.5,num_Points)
+# x = np.linspace(-1,1,num_Points)
+y = np.linspace(-1/2,1/2,num_Points)
+y = np.linspace(-1/4,1/4,num_Points)
+
+print('type of x', type(x))
+print('max of x:', max(x))
+print('max of y:', max(y))
+# print('x:', x)
+
+x1, x2 = np.meshgrid(x,y)
+zero = 0*x1
+
+if kappa == 0 :
+    u1 = 0*x1
+    u2 = x1*e[0] + x2*e[1]
+    u3 = x2*e[0] - x1*e[1]
+
+else :
+    u1 = -(1/kappa)*np.cos(kappa*(x1*e[0]+x2*e[1])) + (1/kappa)
+    u2 = (1/kappa)*np.sin(kappa*(x1*e[0]+x2*e[1]))
+    u3 = x2*e[0] -x1*e[1]
+
+# print('np.size(u1)',np.size(u1))
+# print('u1.shape',u1.shape)
+# colorfunction=(u1**2+u2**2)
+# print('colofunction',colorfunction)
+
+# print('u1.size:',np.size(u1))
+# tmp = np.ones(np.size(u1))*kappa
+# print('np.size(tmp)',np.size(tmp))
+B = np.full_like(u1, 1)
+# colorfunction=(u3)                                              # TODO Color by angle
+# colorfunction=(np.ones(np.size(u1))*kappa)
+colorfunction=(B*kappa)
+# print('colofunction',colorfunction)
+norm=mcolors.Normalize(colorfunction.min(),colorfunction.max())
+
+
+# -----------------------------------------------------
+# Display the mesh
+fig = plt.figure()
+
+
+width = 6.28 *0.5
+width = 6.28 * 0.333
+height = width / 1.618
+height = width / 2.5
+height = width
+
+
+
+ax = plt.axes(projection ='3d', adjustable='box')
+
+
+###---TEST MAP e-vectprs!
+# e1 = np.array([1,0])
+# e2 = np.array([0,1])
+# e3 = np.array([1/np.sqrt(2),1/np.sqrt(2)])
+# e1 = np.array([0,1])
+# e2 = np.array([-1,0])
+# e3 = np.array([-1/np.sqrt(2),1/np.sqrt(2)])
+# e1_mapped = u(e1,kappa,e1)
+# e2_mapped = u(e2,kappa,e2)
+# e3_mapped = u(e3,kappa,e3)
+# print('e1 mapped:',e1_mapped)
+# print('e2 mapped:',e2_mapped)
+# print('e3 mapped:',e3_mapped)
+### -----------------------------------
+
+#--e1 :
+# Rotation_angle = -np.pi/2
+# Rotation_vector = np.array([0,1,0])
+
+#--e2:
+Rotation_angle = np.pi/2
+Rotation_vector = np.array([1,0,0])
+
+###--e = np.array([1/np.sqrt(2),1/np.sqrt(2)])
+# Rotation_angle = -np.pi/2
+# Rotation_vector = np.array([1,0,0])
+# #2te rotation :
+# Rotation_angle = np.pi/4
+# Rotation_vector = np.array([0,0,1])
+
+
+
+Rotation_angle = -np.pi/2
+Rotation_angle = 0
+# Rotation_angle = np.pi/2
+Rotation_vector = np.array([0,1,0])
+Rotation_vector = np.array([1,0,0])
+
+# rot(np.array([0,1,0]),np.pi/2)
+
+# ZERO ROTATION
+Rotation = rot(np.array([0,1,0]),0)
+
+
+
+# TEST :
+
+#DETERMINE ANGLE:
+angle = math.atan2(e[1], e[0])
+print('angle:', angle)
+
+## GENERAL TRANSFORMATION / ROTATION:
+Rotation = rot(np.array([0,0,1]),angle).dot(rot(np.array([0,1,0]),-np.pi/2))
+
+# Rotation = rot(np.array([0,0,1]),+np.pi/4).dot(Rotation)
+# Rotation = rot(np.array([0,0,1]),+np.pi/16).dot(Rotation)
+
+
+
+### if e1:
+# Rotation = rot(np.array([0,0,1]),-np.pi/4).dot(Rotation)
+# Rotation = rot(np.array([0,0,1]),+np.pi/16).dot(Rotation)
+
+# Add another rotation around z-axis:
+# Rotation = rot(np.array([0,0,1]),+np.pi).dot(Rotation)
+# Rotation = rot(np.array([0,0,1]),+np.pi/4).dot(Rotation)
+
+
+# Rotation = rot(np.array([0,0,1]),+np.pi/8).dot(Rotation)
+
+#e3 :
+# Rotation = rot(np.array([0,1,0]),-np.pi/2)
+# Rotation = rot(np.array([0,0,1]),np.pi/4).dot(rot(np.array([0,1,0]),-np.pi/2))
+
+# Rotation = rot(np.array([0,0,1]),np.pi/4)
+# Rotation = rot(np.array([1,0,0]),np.pi/4)
+#### if e1 :
+# Rotation = rot(np.array([0,1,0]),-np.pi/2)
+#### if e2:
+# Rotation = rot(np.array([0,1,0]),-np.pi/2).dot(rot(np.array([1,0,0]),-np.pi/2))
+# # #### if e3 :
+# zufall dass np.pi/4 genau dem Winkel angle alpha entspricht?:
+# (würde) bei e_2 keinen Unterschied machen um z achse zu rotieren?!
+
+# Rotation = rot(np.array([0,0,1]),np.pi/4).dot(rot(np.array([0,1,0]),-np.pi/2).dot(rot(np.array([1,0,0]),-np.pi/2)))
+# Rotation = rot(np.array([0,0,1]),np.pi/2).dot(rot(np.array([0,1,0]),-np.pi/2).dot(rot(np.array([1,0,0]),-np.pi/2)))
+
+# Rotation = rot(np.array([1,0,0]),np.pi/2)
+
+# Rotation_vector = e3_mapped  #TEST
+# Rotation_vector = np.array([-1/np.sqrt(2),1/np.sqrt(2)])
+# Rotation_vector = np.array([0,0,1])
+
+# v = np.array([1,0,0])
+# X = np.array([u1,u2,u3])
+
+
+
+
+# T = rotate_data(np.array([u1,u2,u3]),Rotation_vector,Rotation_angle)
+T = rotate_data(np.array([u1,u2,u3]),Rotation)
+
+# ax.plot_surface(T[0], T[1], T[2], color = 'w', rstride = 2, cstride = 2, facecolors=cm.brg(colorfunction), alpha=.4, zorder=4)
+# ax.plot_surface(T[0], T[1], T[2], color = 'w', rstride = 1, cstride = 1, facecolors=cm.viridis(colorfunction), alpha=.4, zorder=4)
+
+
+###---- PLOT PARAMETER-PLANE:
+# ax.plot_surface(x1,x2,zero,color = 'w', rstride = 1, cstride = 1 )
+
+
+print('------------------ Kappa : ', kappa)
+
+#midpoint:
+midpoint = np.array([(max(x)+min(x))/2,(max(y)+min(y))/2])
+print('midpoint',midpoint)
+
+# Map midpoint:
+midpoint_mapped = u(midpoint,kappa,e)
+print('mapped midpoint', midpoint_mapped)
+
+#map origin
+origin = np.array([0,0])
+origin_mapped = u(origin,kappa,e)
+
+
+mapped_e = grad_u(midpoint,kappa,e)
+normal = compute_normal(midpoint,kappa,e)
+
+print('mapped_e', mapped_e)
+print('normal',normal )
+
+#
+# mapped_e = Rotation.dot(mapped_e)
+# normal = Rotation.dot(normal)
+
+
+# Plot Mapped_midPoint
+# ax.plot(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],    # data
+# marker='o',     # each marker will be rendered as a circle
+# markersize=4,   # marker size
+# markerfacecolor='orange',   # marker facecolor
+# markeredgecolor='black',  # marker edgecolor
+# markeredgewidth=1,       # marker edge width
+# linewidth=1,
+# zorder=4)          # line width
+
+# ax.quiver([midpoint_mapped[0]], [midpoint_mapped[1]], [midpoint_mapped[2]], [mapped_e[0]], [mapped_e[1]], [mapped_e[2]], color="red")
+# ax.quiver([midpoint_mapped[0]], [midpoint_mapped[1]], [midpoint_mapped[2]], [normal[0]], [normal[1]], [normal[2]], color="blue")
+
+# ax.arrow3D(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],
+#            mapped_e[0],mapped_e[1],mapped_e[2],
+#            mutation_scale=15,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='green',
+#            lw = 2,
+#            ec ='green',
+#            zorder=3)
+#
+# ax.arrow3D(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],
+#            normal[0],normal[1],normal[2],
+#            mutation_scale=15,
+#             lw = 2,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='blue',
+#            ec ='blue',
+#            zorder = 3)
+
+
+###-- TEST Rotation :
+# v = np.array([1,0,0])
+# t = np.array([0,1,0])
+#
+# ax.arrow3D(0,0,0,
+#            t[0],t[1],t[2],
+#            mutation_scale=10,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='blue',
+#            ec ='blue')
+#
+# # e_extend
+#
+# rotM = rot(v,np.pi/2)
+#
+# print('rotM:', rotM)
+#
+# rot_t = rotM.dot(t)
+#
+# print('rot_t:', rot_t)
+#
+# ax.arrow3D(0,0,0,
+#            rot_t[0],rot_t[1],rot_t[2],
+#            mutation_scale=10,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='blue',
+#            ec ='blue')
+
+### -------------------------------------------
+
+############################################################################################################################################
+####################################################################### KAPPA POSITIVE  ####################################################
+############################################################################################################################################
+
+# kappa = (-1)*kappa
+
+if kappa == 0 :
+    u1 = 0*x1
+    u2 = x1*e[0] + x2*e[1]
+    u3 = x2*e[0] - x1*e[1]
+else :
+    u1 = -(1/kappa)*np.cos(kappa*(x1*e[0]+x2*e[1])) + (1/kappa)
+    u2 = (1/kappa)*np.sin(kappa*(x1*e[0]+x2*e[1]))
+    u3 = x2*e[0] -x1*e[1]
+# ax.plot_surface(u1, u2, u3, color = 'w', rstride = 1, cstride = 1, facecolors=cm.autumn(colorfunction), alpha=.3)  ##This one!
+
+
+# T = rotate_data(X,Rotation_vector,Rotation_angle)
+
+T = rotate_data(np.array([u1,u2,u3]),Rotation)
+# T = rotate_data(T,np.array([0,1,0]),Rotation_angle)
+# T = rotate_data(T,np.array([0,0,1]),-1*Rotation_angle/2)
+
+# ax.plot_surface(T[0], T[1], T[2], rstride = 1, cstride = 1, facecolors=cm.autumn(colorfunction), alpha=.4, zorder=4, antialiased=False)
+# ax.plot_surface(T[0], T[1], T[2], rstride = 1, cstride = 1, facecolors=cm.autumn(colorfunction), alpha=.4, zorder=4, antialiased=True)
+# ax.plot_surface(T[0], T[1], T[2], rstride = 2, cstride = 2, facecolors=cm.autumn(colorfunction), alpha=.4, zorder=4)
+# ax.plot_surface(T[0], T[1], T[2], rstride = 10, cstride = 10, facecolors=cm.brg(colorfunction), alpha=.8, zorder=4)
+ax.plot_surface(T[0], T[1], T[2], rstride = 5, cstride = 5, color='orange', alpha=.8, zorder=4)
+# ax.plot_surface(T[0], T[1], T[2], rstride = 10, cstride = 10, color='blue', alpha=.8, zorder=4, shade=True)
+# ax.plot_surface(T[0], T[1], T[2], rstride = 1, cstride = 1, facecolors=cm.autumn(colorfunction), alpha=.4, zorder=4, shade=True)
+# ax.plot_surface(T[0], T[1], T[2], color = 'w', rstride = 1, cstride = 1, facecolors=cm.autumn(colorfunction), alpha=0.8, zorder=4)
+# ax.plot_surface(T[0], T[1], T[2],  rstride = 1, cstride = 1, facecolors=cm.autumn(colorfunction), alpha=1, zorde5r=5)
+
+# midpoint = np.array([(max(x)+min(x))/2,(max(y)+min(y))/2])
+# print('midpoint',midpoint)
+print('------------------ Kappa : ', kappa)
+# Map midpoint:
+midpoint_mapped = u(midpoint,kappa,e)
+print('mapped midpoint', midpoint_mapped)
+
+#map origin
+origin = np.array([0,0])
+origin_mapped = u(origin,kappa,e)
+
+
+mapped_e = grad_u(midpoint,kappa,e)
+normal = compute_normal(midpoint,kappa,e)
+
+print('mapped_e', mapped_e)
+print('normal',normal )
+
+
+#
+mapped_e = Rotation.dot(mapped_e)
+normal = Rotation.dot(normal)
+
+
+
+# Plot MIDPOINT:
+# ax.plot(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],    # data
+# marker='o',     # each marker will be rendered as a circle
+# markersize=4,   # marker size
+# markerfacecolor='orange',   # marker facecolor
+# markeredgecolor='black',  # marker edgecolor
+# markeredgewidth=1,       # marker edge width
+# linewidth=1,
+# zorder=5)          # line width
+
+
+#midpoint:
+endpoint = np.array([min(x),(max(y)+min(y))/2])
+print('endpoint',endpoint)
+
+# Map midpoint:
+endpoint_mapped = u(endpoint,kappa,e)
+print('mapped endpoint', endpoint_mapped)
+
+endpoint_mapped = Rotation.dot(endpoint_mapped)
+
+mapped_e = grad_u(endpoint,kappa,e)
+normal = compute_normal(endpoint,kappa,e)
+
+
+mapped_e = Rotation.dot(mapped_e)
+normal = Rotation.dot(normal)
+
+
+
+
+# ax.arrow3D(endpoint_mapped[0],endpoint_mapped[1],endpoint_mapped[2],
+#            mapped_e[0],mapped_e[1],mapped_e[2],
+#            mutation_scale=15,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='green',
+#            lw = 1.5,
+#            ec ='green',
+#            zorder=5)
+#
+# ax.arrow3D(endpoint_mapped[0],endpoint_mapped[1],endpoint_mapped[2],
+#            normal[0],normal[1],normal[2],
+#            mutation_scale=15,
+#             lw = 1.5,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='blue',
+#            ec ='blue',
+#            zorder = 5)
+
+
+# ax.arrow3D(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],
+#            mapped_e[0],mapped_e[1],mapped_e[2],
+#            mutation_scale=15,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='green',
+#            lw = 1.5,
+#            ec ='green',
+#            zorder=5)
+#
+# ax.arrow3D(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],
+#            normal[0],normal[1],normal[2],
+#            mutation_scale=15,
+#             lw = 1.5,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='blue',
+#            ec ='blue',
+#            zorder = 5)
+
+
+############################################################################################################################################
+####################################################################### KAPPA ZERO #########################################################
+############################################################################################################################################
+kappa = 0
+
+if kappa == 0 :
+    u1 = 0*x1
+    u2 = x1*e[0] + x2*e[1]
+    u3 = x2*e[0] - x1*e[1]
+else :
+    u1 = -(1/kappa)*np.cos(kappa*(x1*e[0]+x2*e[1])) + (1/kappa)
+    u2 = (1/kappa)*np.sin(kappa*(x1*e[0]+x2*e[1]))
+    u3 = x2*e[0] -x1*e[1]
+# ax.plot_surface(u1, u2, u3,  rstride = 1, cstride = 1, color = 'white', alpha=0.85)
+
+# T = rotate_data(np.array([u1,u2,u3]),Rotation_vector,Rotation_angle)
+
+T = rotate_data(np.array([u1,u2,u3]),Rotation)
+# T = rotate_data(T,np.array([0,1,0]),Rotation_angle)
+# T = rotate_data(T,np.array([0,0,1]),-1*Rotation_angle/2)
+
+
+# ax.plot_surface(T[0], T[1], T[2],  rstride = 1, cstride = 1, color = 'white', alpha=0.55, zorder=2, antialiased=True)
+# ax.plot_surface(T[0], T[1], T[2],  rstride =1 , cstride = 1, color = 'white', alpha=0.55, zorder=3)
+
+# ax.plot_surface(T[0], T[1], T[2],  rstride = 1, cstride = 1, color = 'white', alpha=0.55, zorder=2)
+# ax.plot_surface(T[0], T[1], T[2],  rstride = 1, cstride = 1, color = 'white', alpha=0.5, zorder=2, antialiased=True)
+# ax.plot_surface(T[0], T[1], T[2],  rstride = 10, cstride = 10, color = 'white', alpha=0.55, zorder=2)
+ax.plot_surface(T[0], T[1], T[2],  rstride = 20, cstride = 20, color = 'gray', alpha=0.35, zorder=1, shade=True)
+# ax.plot_surface(T[0], T[1], T[2], color = 'white', alpha=0.55, zorder=2)
+
+# midpoint = np.array([(max(x)+min(x))/2,(max(y)+min(y))/2])
+mapped_e = grad_u(midpoint,kappa,e)
+normal_zeroCurv = compute_normal(midpoint,kappa,e)
+
+# Map midpoint:
+midpoint_mapped = u(midpoint,kappa,e)
+print('mapped midpoint', midpoint_mapped)
+
+##-----  PLOT MAPPED MIDPOINT :::
+
+# ax.plot(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],    # data
+# marker='o',     # each marker will be rendered as a circle
+# markersize=4,   # marker size
+# markerfacecolor='orange',   # marker facecolor
+# markeredgecolor='black',  # marker edgecolor
+# markeredgewidth=1,       # marker edge width
+# # linestyle='--',            # line style will be dash line
+# linewidth=1,
+# zorder=5)
+
+# ax.arrow3D(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],
+#            mapped_e[0],mapped_e[1],mapped_e[2],
+#            mutation_scale=10,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='red',
+#            ec ='red')
+#
+# ax.arrow3D(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],
+#            normal_zeroCurv[0],normal_zeroCurv[1],normal_zeroCurv[2],
+#            mutation_scale=10,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='blue',
+#            ec ='blue')
+
+
+##----------  PLOT MAPPED ORIGIN :::
+# origin = np.array([0,0])
+# origin_mapped = u(origin,kappa,e)
+# print('origin_mapped', origin_mapped)
+#
+# ax.plot(origin_mapped[0],origin_mapped[1],origin_mapped[2],    # data
+# marker='o',     # each marker will be rendered as a circle
+# markersize=4,   # marker size
+# markerfacecolor='green',   # marker facecolor
+# markeredgecolor='black',  # marker edgecolor
+# markeredgewidth=1,       # marker edge width
+# linewidth=1,
+# zorder=5)          # line width
+#
+# # rotate mapped origin
+# # v = np.array([1,0,0])
+# # alpha  = Rotation_angle
+#
+# rotM = rot(Rotation_vector,Rotation_angle)
+# # origin_mRot = rotate_data(origin_mapped,v,alpha)
+# origin_mRot = rotM.dot(origin_mapped)
+# print('origin_mapped Rotated', origin_mRot)
+#
+# # --- Compute Distance to Origin 3D
+# origin_3D=np.array([0,0,0])
+# distance = origin_mapped-origin_3D
+# print('distance', distance)
+
+## --------------------------------------------------------
+
+# COMPUTE ANGLE WITH Z AXIS
+z = np.array([0,0,1])
+print('test', normal_zeroCurv*z)
+angle_z = np.arccos(normal_zeroCurv.dot(z) /( (np.linalg.norm(z)*np.linalg.norm(normal_zeroCurv) ) ))
+print('angle between normal and z-axis', angle_z)
+
+## unfinished...
+
+
+
+
+###-------------------------------------  PLOT :
+plt.axis('off')
+# plt.axis('tight')
+
+# ADD colorbar
+# scamap = plt.cm.ScalarMappable(cmap='inferno')
+# fig.colorbar(scamap)
+
+# ax.colorbar()
+# ax.axis('auto')
+# ax.set_title(r'Cylindrical minimizer_$\kappa$='+ str(kappa)+ '_$e$=' +  str(e))
+# ax.set_title(r'Cylindrical minimizer' + '_$e$=' +  str(e))
+ax.set_xlabel(r"x-axis")
+ax.set_ylabel(r"y-axis")
+ax.set_zlabel(r"z-axis")
+
+# TEST :
+# ax.annotate3D('point 1', (0, 0, 0), xytext=(3, 3), textcoords='offset points')
+# ax.annotate3D('point 2', (0, 1, 0),
+#               xytext=(-30, -30),
+#               textcoords='offset points',
+#               arrowprops=dict(ec='black', fc='white', shrink=2.5))
+# ax.annotate3D('point 3', (0, 0, 1),
+#               xytext=(30, -30),
+#               textcoords='offset points',
+#               bbox=dict(boxstyle="round", fc="lightyellow"),
+#               arrowprops=dict(arrowstyle="-|>", ec='black', fc='white', lw=5))
+
+#######################################################################################################################
+
+u1 = T[0]
+u2 = T[1]
+u3 = T[2]
+
+# max_range = np.array([u1.max()-u1.min(), u2.max()-u2.min(), u3.max()-u3.min()]).max() /3
+max_range = np.array([u1.max()-u1.min(), u2.max()-u2.min(), u3.max()-u3.min()]).max() /12
+# max_range = np.array([u1.max()-u1.min(), u2.max()-u2.min(), u3.max()-u3.min()]).max() /8
+# max_range = np.array([u1.max()-u1.min(), u2.max()-u2.min(), u3.max()-u3.min()]).max() /10
+max_range = np.array([u1.max()-u1.min(), u2.max()-u2.min(), u3.max()-u3.min()]).max() /14
+# max_range = np.array([u1.max()-u1.min(), u2.max()-u2.min(), u3.max()-u3.min()]).max() /6
+# max_range = np.array([u1.max()-u1.min(), u2.max()-u2.min(), u3.max()-u3.min()]).max() /2
+mid_u1 = (u1.max()+u1.min()) * 0.5
+mid_u2 = (u2.max()+u2.min()) * 0.5
+mid_u3 = (u3.max()+u3.min()) * 0.5
+
+
+ax.set_xlim(mid_u1 - max_range, mid_u1 + max_range)
+ax.set_ylim(mid_u2 - max_range, mid_u2 + max_range)
+ax.set_zlim(mid_u3 - max_range, mid_u3 + max_range)
+
+ax.set_ylim((mid_u2 - max_range)-2, (mid_u2 + max_range)+2)
+# ax.set_zlim((mid_u2 - max_range), (mid_u2 + max_range)+2)
+# ax.set_ylim((mid_u2 - max_range)-1.5, (mid_u2 + max_range)+1.5)
+# # ax.autoscale(tight=True)
+ax.set_xlim((mid_u1 - max_range)-1, (mid_u1 + max_range)+1)
+ax.set_xlim((mid_u1 - max_range)-0.5, (mid_u1 + max_range)+0.5)
+# ax.set_ylim((mid_u2 - max_range)-2, (mid_u2 + max_range)+2)
+ax.set_zlim((mid_u2 - max_range), (mid_u2 + max_range)+2)
+
+# ax.set_ylim((mid_u2 - max_range)-2, (mid_u2 + max_range)+3)
+# ax.set_zlim((mid_u2 - max_range), (mid_u2 + max_range)+2)
+
+
+##----- CHANGE CAMERA POSITION:
+# ax.view_init(elev=10., azim=0)
+# ax.view_init(elev=38, azim=90)
+# ax.view_init(elev=38, azim=120)
+# ax.view_init(elev=38)
+
+# if e1 ::
+# ax.view_init(elev=44)
+# ax.view_init(elev=38, azim=-90)
+# ax.view_init(elev=38, azim=0)
+ax.view_init(elev=25, azim=-30)
+# ax.view_init(elev=18, azim=-30)
+
+# if e3 ::
+# ax.view_init(elev=25)
+
+# ax.set_xlim3d(-2, 2)
+# ax.set_ylim3d(-1.0,3.0)
+# ax.set_zlim3d(-1.5,2.5)
+
+# ax.set_ylim3d(-10,10)
+# ax.set_xlim(mid_u1 - max_range-0.2, mid_u1 + max_range+0.2)
+# ax.set_zlim(mid_u3 - max_range-0.2, mid_u3 + max_range+0.2)
+# ax.set_ylim(mid_u2 - max_range-0.2, mid_u2 + max_range+0.2)
+
+# width = 6.28 *0.5
+# height = width / 1.618
+# # height = width / 2.5
+# fig.set_size_inches(width, height)
+# fig.savefig('Test-Cylindrical.pdf')
+
+# Figurename = r'Cylindrical minimizer_$\kappa$='+ str(kappa)+ '_$e$=' +  str(e)
+# Figurename = r'Cylindrical minimizer' + '_$e$=' +  str(e)
+Figurename = r'1-ParFamMinimizer_idx' + str(idx)
+# plt.savefig("test.png", bbox_inches='tight')
+# plt.figure().set_size_inches(width, height)
+# plt.set_size_inches(width, height)
+
+
+# fig.set_size_inches(width, height) !!!!!
+
+
+
+
+fig.savefig(Figurename+".pdf")
+
+plt.savefig(Figurename+".png", bbox_inches='tight')
+# plt.savefig(Figurename+".png")
+plt.show()
+
+
+
+# #---------------------------------------------------------------

Python-Scripts/1-ParameterFamily_G+.py

+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 ClassifyMin_New 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
+
+import matplotlib as mpl
+from matplotlib.ticker import MultipleLocator,FormatStrFormatter,MaxNLocator
+import pandas as pd
+
+import seaborn as sns
+import matplotlib.colors as mcolors
+
+
+from mpl_toolkits.mplot3d.proj3d import proj_transform
+# from mpl_toolkits.mplot3d.axes3d import Axes3D
+from matplotlib.text import Annotation
+from matplotlib.patches import FancyArrowPatch
+# from matplotlib import rc
+# rc('text', usetex=True) # Use LaTeX font
+#
+# import seaborn as sns
+# sns.set(color_codes=True)
+
+# set the colormap and centre the colorbar
+class MidpointNormalize(mcolors.Normalize):
+	"""
+	Normalise the colorbar so that diverging bars work there way either side from a prescribed midpoint value)
+
+	e.g. im=ax1.imshow(array, norm=MidpointNormalize(midpoint=0.,vmin=-100, vmax=100))
+	"""
+	def __init__(self, vmin=None, vmax=None, midpoint=None, clip=False):
+		self.midpoint = midpoint
+		mcolors.Normalize.__init__(self, vmin, vmax, clip)
+
+	def __call__(self, value, clip=None):
+		# I'm ignoring masked values and all kinds of edge cases to make a
+		# simple example...
+		x, y = [self.vmin, self.midpoint, self.vmax], [0, 0.5, 1]
+		return np.ma.masked_array(np.interp(value, x, y), np.isnan(value))
+
+
+
+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 == -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)
+    ##find number of multiples of pi/2
+    N = int(np.round(4 * value / np.pi))
+    if N == 0:
+        return "0"
+    elif N == 1:
+        return r"$\pi/4$"
+    elif N == -1:
+        return r"$-\pi/4$"
+    elif N == 2:
+        return r"$\pi/2$"
+    elif N == -2:
+        return r"$-\pi/2$"
+    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
+
+
+
+def energy(a1,a2,q1,q2,q12,q3,b1,b2):
+
+
+    a = np.array([a1,a2])
+    b = np.array([b1,b2])
+    H = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+    A = np.array([[q1,1/2*q12], [1/2*q12,q2] ])
+
+
+    tmp = H.dot(a)
+
+    # print('H',H)
+    # print('A',A)
+    # print('b',b)
+    # print('a',a)
+    # print('tmp',tmp)
+
+    tmp = (1/2)*a.dot(tmp)
+    # print('tmp',tmp)
+
+    tmp2 = A.dot(b)
+    # print('tmp2',tmp2)
+    tmp2 = 2*a.dot(tmp2)
+
+    # print('tmp2',tmp2)
+    energy = tmp - tmp2
+    # print('energy',energy)
+
+
+    # energy_axial1.append(energy_1)
+
+    return energy
+
+
+
+def evaluate(x,y):
+
+	# (abar[0,:]*abar[1,:])**0.5
+
+	return np.sqrt(x*y)
+
+
+# def energy(a1,a2,q1,q2,q12,q3,b1,b2):
+#
+#
+#     b = np.array([b1,b2])
+#     H = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+#     A = np.array([[q1,1/2*q12], [1/2*q12,q2] ])
+#
+#
+#     tmp = H.dot(a)
+#
+#     print('H',H)
+#     print('A',A)
+#     print('b',b)
+#     print('a',a)
+#     print('tmp',tmp)
+#
+#     tmp = (1/2)*a.dot(tmp)
+#     print('tmp',tmp)
+#
+#     tmp2 = A.dot(b)
+#     print('tmp2',tmp2)
+#     tmp2 = 2*a.dot(tmp2)
+#
+#     print('tmp2',tmp2)
+#     energy = tmp - tmp2
+#     print('energy',energy)
+#
+#
+#     # energy_axial1.append(energy_1)
+#
+#     return energy
+#
+
+def add_arrow(line, position=None, direction='right', size=15, color=None):
+    """
+    add an arrow to a line.
+
+    line:       Line2D object
+    position:   x-position of the arrow. If None, mean of xdata is taken
+    direction:  'left' or 'right'
+    size:       size of the arrow in fontsize points
+    color:      if None, line color is taken.
+    """
+    if color is None:
+        color = line.get_color()
+
+    xdata = line.get_xdata()
+    ydata = line.get_ydata()
+
+    if position is None:
+        position = xdata.mean()
+    # find closest index
+    start_ind = np.argmin(np.absolute(xdata - position))
+    if direction == 'right':
+        end_ind = start_ind + 1
+    else:
+        end_ind = start_ind - 1
+
+    line.axes.annotate('',
+        xytext=(xdata[start_ind], ydata[start_ind]),
+        xy=(xdata[end_ind], ydata[end_ind]),
+        arrowprops=dict(arrowstyle="->", color=color),
+        size=size
+    )
+
+
+
+class Annotation3D(Annotation):
+    def __init__(self, text, xyz, *args, **kwargs):
+        super().__init__(text, xy=(0, 0), *args, **kwargs)
+        self._xyz = xyz
+
+    def draw(self, renderer):
+        x2, y2, z2 = proj_transform(*self._xyz, self.axes.M)
+        self.xy = (x2, y2)
+        super().draw(renderer)
+
+def _annotate3D(ax, text, xyz, *args, **kwargs):
+    '''Add anotation `text` to an `Axes3d` instance.'''
+
+    annotation = Annotation3D(text, xyz, *args, **kwargs)
+    ax.add_artist(annotation)
+
+setattr(Axes3D, 'annotate3D', _annotate3D)
+
+class Arrow3D(FancyArrowPatch):
+
+    def __init__(self, x, y, z, dx, dy, dz, *args, **kwargs):
+        super().__init__((0, 0), (0, 0), *args, **kwargs)
+        self._xyz = (x, y, z)
+        self._dxdydz = (dx, dy, dz)
+
+    def draw(self, renderer):
+        x1, y1, z1 = self._xyz
+        dx, dy, dz = self._dxdydz
+        x2, y2, z2 = (x1 + dx, y1 + dy, z1 + dz)
+
+        xs, ys, zs = proj_transform((x1, x2), (y1, y2), (z1, z2), self.axes.M)
+        self.set_positions((xs[0], ys[0]), (xs[1], ys[1]))
+        super().draw(renderer)
+
+
+def _arrow3D(ax, x, y, z, dx, dy, dz, *args, **kwargs):
+    '''Add an 3d arrow to an `Axes3D` instance.'''
+
+    arrow = Arrow3D(x, y, z, dx, dy, dz, *args, **kwargs)
+    ax.add_artist(arrow)
+
+setattr(Axes3D, 'arrow3D', _arrow3D)
+
+################################################################################################################
+################################################################################################################
+################################################################################################################
+
+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: -----')
+
+# q1=1;
+# q2=2;
+# q12=1/2;
+# q3=((4*q1*q2)**0.5-q12)/2;
+# # H=[2*q1,q12+2*q3;q12+2*q3,2*q2];
+#
+# H = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+# A = np.array([[q1,1/2*q12], [1/2*q12,q2] ])
+# abar = np.array([q12+2*q3, 2*q2])
+# abar = (1.0/math.sqrt((q12+2*q3)**2+(2*q2)**2))*abar
+#
+# print('abar:',abar)
+#
+# b = np.linalg.lstsq(A, abar)[0]
+# print('b',b)
+#
+#
+# # print('abar:',np.shape(abar))
+# # print('np.transpose(abar):',np.shape(np.transpose(abar)))
+# sstar = (1/(q1+q2))*abar.dot(A.dot(b))
+# # sstar = (1/(q1+q2))*abar.dot(tmp)
+# print('sstar', sstar)
+# abarperp= np.array([abar[1],-abar[0]])
+# print('abarperp:',abarperp)
+
+
+# -------------------------- Input Parameters --------------------
+
+mu1 = 1.0
+rho1 = 1.0
+alpha = 5.0
+theta = 1.0/2
+# theta= 0.1
+beta = 5.0
+
+
+
+# mu1 = 1.0
+# rho1 = 1.0
+# alpha = 2.0
+# theta = 1.0/2
+# # theta= 0.1
+# beta = 5.0
+
+
+#Figure3:
+# mu1 = 1.0
+# rho1 = 1.0
+# alpha = 2.0
+# theta = 1.0/8
+# # theta= 0.1
+# beta = 2.0
+
+
+# alpha= -5
+
+
+#set gamma either to 1. '0' 2. 'infinity' or 3. a numerical positive value
+gamma = '0'
+gamma = 'infinity'
+
+
+lambda1 = 0.0
+
+
+print('---- Input parameters: -----')
+print('mu1: ', mu1)
+print('rho1: ', rho1)
+# print('alpha: ', alpha)
+print('beta: ', beta)
+# print('theta: ', theta)
+print('gamma:', gamma)
+
+print('lambda1: ', lambda1)
+print('----------------------------')
+# ----------------------------------------------------------------
+print('----------------------------')
+
+# ----------------------------------------------------------------
+
+
+
+
+
+
+q1 = (1.0/6.0)*harmonicMean(mu1, beta, theta)
+q2 = (1.0/6.0)*arithmeticMean(mu1, beta, theta)
+q12 = 0.0
+q3 = GetMuGamma(beta, theta,gamma,mu1,rho1,InputFilePath ,OutputFilePath )
+b1 = prestrain_b1(rho1,beta, alpha, theta )
+b2 = prestrain_b2(rho1,beta, alpha, theta )
+
+
+# 1-ParameterFamilyCase:
+
+q1=1;
+q2=2;
+q12=1/2;
+q3=((4*q1*q2)**0.5-q12)/2;
+# H=[2*q1,q12+2*q3;q12+2*q3,2*q2];
+
+H = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+A = np.array([[q1,1/2*q12], [1/2*q12,q2] ])
+abar = np.array([q12+2*q3, 2*q2])
+abar = (1.0/math.sqrt((q12+2*q3)**2+(2*q2)**2))*abar
+
+print('abar:',abar)
+
+b = np.linalg.lstsq(A, abar)[0]
+print('b',b)
+
+b1=b[0]
+b2=b[1]
+
+
+# print('abar:',np.shape(abar))
+# print('np.transpose(abar):',np.shape(np.transpose(abar)))
+sstar = (1/(q1+q2))*abar.dot(A.dot(b))
+# sstar = (1/(q1+q2))*abar.dot(tmp)
+print('sstar', sstar)
+abarperp= np.array([abar[1],-abar[0]])
+print('abarperp:',abarperp)
+
+print('----------------------------')
+
+# ----------------------------------------------------------------
+
+N=1000;
+scale_domain = 5
+
+translate_startpoint = -5
+
+# T = np.linspace(-sstar*(q12+2*q3)/(2*q2), sstar*(2*q2)/(q12+2*q3), num=N)
+T = np.linspace(-sstar*(q12+2*q3)/(2*q2)*scale_domain + translate_startpoint, sstar*(2*q2)/(q12+2*q3)*scale_domain , num=N)
+# T = np.linspace(-2,2, num=N)
+# print('T:', T)
+
+print('T.min():', T.min())
+print('T.max():', T.max())
+
+kappas = []
+alphas = []
+# G.append(float(s[0]))
+
+G_container = []
+abar_container = []
+
+
+abar_tmp = abar
+
+for t in T :
+	abar_current = sstar*abar+t*abarperp;
+    # print('abar_current', abar_current)
+	abar_current[abar_current < 1e-10] = 0
+	# print('abar_current', abar_current)
+	# G = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+	G = [abar_current[0], abar_current[1] , (2*abar_current[0]*abar_current[1])**0.5 ]
+	# print('type of G', type(G))
+	# print('G', G)
+	G_container.append(G)
+	abar_container.append(abar_current)
+	e = [(abar_current[0]/(abar_current[0]+abar_current[1]))**0.5, (abar_current[1]/(abar_current[0]+abar_current[1]))**0.5]
+	kappa = abar_current[0]+abar_current[1]
+	alpha = math.atan2(e[1], e[0])
+	# print('angle current:', alpha)
+	kappas.append(kappa)
+	alphas.append(alpha)
+
+
+alphas = np.array(alphas)
+kappas = np.array(kappas)
+
+# print('G_container', G_container)
+G = np.array(G_container)
+abar = np.array(abar_container)
+
+print('G', G)
+print('abar', abar)
+print('abar.shape',abar.shape)
+
+
+
+
+
+print('q1 = ', q1)
+print('q2 = ', q2)
+print('q3 = ', q3)
+print('q12 = ', q12)
+print('b1 = ', b1)
+print('b2 = ', b2)
+
+num_Points = 20
+num_Points = 50
+
+
+# Creating dataset
+x = np.linspace(-5,5,num_Points)
+y = np.linspace(-5,5,num_Points)
+
+x = np.linspace(-20,20,num_Points)
+y = np.linspace(-20,20,num_Points)
+
+# x = np.linspace(-10,10,num_Points)
+# y = np.linspace(-10,10,num_Points)
+
+# x = np.linspace(-60,60,num_Points)
+# y = np.linspace(-60,60,num_Points)
+#
+#
+# x = np.linspace(-40,40,num_Points)
+# y = np.linspace(-40,40,num_Points)
+
+
+range = 2
+
+x_1 = np.linspace(0,range,num_Points)
+y_1 = np.linspace(0,range,num_Points)
+x_2 = np.linspace(-range,0,num_Points)
+y_2 = np.linspace(-range,0,num_Points)
+
+
+X_1,Y_1 = np.meshgrid(x_1,y_1)
+X_2,Y_2 = np.meshgrid(x_2,y_2)
+
+
+a1, a2 = np.meshgrid(x,y)
+
+# geyser = sns.load_dataset("geyser")
+# print('type of geyser:', type(geyser))
+# print('geyser:',geyser)
+
+ContourRange=20
+
+x_in = np.linspace(-ContourRange,ContourRange,num_Points)
+y_in = np.linspace(-ContourRange,ContourRange,num_Points)
+a1_in, a2_in = np.meshgrid(x_in,y_in)
+
+# print('a1:', a1)
+# print('a2:',a2 )
+#
+# print('a1.shape', a1.shape)
+
+#-- FILTER OUT VALUES for G+ :
+
+tmp1 = a1[np.where(a1*a2 >= 0)]
+tmp2 = a2[np.where(a1*a2 >= 0)]
+
+# tmp1 = a1[a1*a2 >= 0]
+# tmp2 = a2[a1*a2 >= 0]
+
+# tmp1 = a1[np.where(a1>=0 and a2 >= 0)]
+# tmp2 = a2[np.where(a1>=0 and a2 >= 0)]
+
+
+# tmp1 = tmp1[np.where(a1 >= 0)]
+# tmp2 = tmp2[np.where(a1 >= 0)]
+
+# tmp1_pos = a1[np.where(a1*a2 >= 0)]
+# tmp2_neg = a2[np.where(a1*a2 >= 0)]
+
+
+
+print('tmp1.shape',tmp1.shape)
+print('tmp1.shape[0]',tmp1.shape[0])
+print('tmp2.shape',tmp2.shape)
+print('tmp2.shape[0]',tmp2.shape[0])
+
+
+
+tmp1 = tmp1.reshape(-1,int(tmp1.shape[0]/2))
+tmp2 = tmp2.reshape(-1,int(tmp2.shape[0]/2))
+
+print('tmp1.shape',tmp1.shape)
+print('tmp1.shape[0]',tmp1.shape[0])
+print('tmp2.shape',tmp2.shape)
+print('tmp2.shape[0]',tmp2.shape[0])
+
+# np.take(a, np.where(a>100)[0], axis=0)
+# tmp1 = np.take(a1, np.where(a1*a2 >= 0)[0], axis=0)
+# tmp2 = np.take(a1, np.where(a1*a2 >= 0)[0], axis=0)
+# tmp2 = a2[np.where(a1*a2 >= 0)]
+
+# tmp1 = a1[a1*a2 >= 0]
+# tmp2 = a2[a1*a2 >= 0]
+
+
+# tmp1_pos = a1[np.where(a1*a2 >= 0) ]
+# tmp2_pos = a2[np.where(a1*a2 >= 0) ]
+# tmp1_pos = tmp1_pos[np.where(tmp1_pos  >= 0)]
+# tmp2_pos = tmp2_pos[np.where(tmp2_pos  >= 0)]
+
+# tmp1_neg = a1[a1*a2 >= 0 ]
+# tmp2_neg = a2[a1*a2 >= 0 ]
+# tmp1_neg = tmp1_neg[tmp1_neg  < 0]
+# tmp2_neg = tmp2_neg[tmp2_neg  < 0]
+# a1 = tmp1
+# a2 = tmp2
+#
+# a1 = a1.reshape(-1,5)
+# a2 = a2.reshape(-1,5)
+
+# tmp1_pos = tmp1_pos.reshape(-1,5)
+# tmp2_pos = tmp2_pos.reshape(-1,5)
+# tmp1_neg = tmp1_neg.reshape(-1,5)
+# tmp2_neg = tmp2_neg.reshape(-1,5)
+
+
+# print('a1:', a1)
+# print('a2:',a2 )
+# print('a1.shape', a1.shape)
+
+
+
+
+
+energyVec = np.vectorize(energy)
+
+# Z = energyVec(np.array([a1,a2]),q1,q2,q12,q3,b1,b2)
+# Z = energyVec(a1,a2,q1,q2,q12,q3,b1,b2)
+#
+# Z_in = energyVec(a1_in,a2_in,q1,q2,q12,q3,b1,b2)
+
+
+
+
+# Z = (tmp2**2)/tmp1
+Z = np.sqrt(tmp1*tmp2)
+
+
+Z1 = np.sqrt(X_1*Y_1)
+Z2 = np.sqrt(X_2*Y_2)
+
+# Z_bar = np.sqrt(abar[0,:]*abar[1,:])
+Z_bar = (abar[0,:]*abar[1,:])**0.5*abar
+
+abar = abar.T
+
+
+
+v1 = abar[0,:]
+v2 = abar[1,:]
+
+# print('a1:', a1)
+# print('a2:',a2 )
+# print('a1.shape', a1.shape)
+
+
+evaluateVec = np.vectorize(evaluate)
+Z_bar = evaluateVec(abar[0,:],abar[1,:])
+# Z = np.sqrt(np.multiply(tmp1,tmp2))
+# Z = np.sqrt(a1*a2)
+
+
+print('v1.shape', v1.shape)
+print('v1', v1)
+
+
+
+
+print('Z:', Z)
+print('Z_bar:', Z_bar)
+# print('any', np.any(Z<0))
+
+#
+
+
+# negZ_a1 = a1[np.where(Z<0)]
+# negZ_a2 = a2[np.where(Z<0)]
+# negativeValues = Z[np.where(Z<0)]
+# print('negativeValues:',negativeValues)
+#
+# print('negZ_a1',negZ_a1)
+# print('negZ_a2',negZ_a2)
+#
+#
+# negZ_a1 = negZ_a1.reshape(-1,5)
+# negZ_a2 = negZ_a2.reshape(-1,5)
+# negativeValues = negativeValues.reshape(-1,5)
+#
+# Z_pos =  energyVec(tmp1_pos,tmp2_pos,q1,q2,q12,q3,b1,b2)
+# Z_neg = energyVec(tmp1_neg,tmp2_neg,q1,q2,q12,q3,b1,b2)
+
+
+
+
+
+# print('Test energy:' , energy(np.array([1,1]),q1,q2,q12,q3,b1,b2))
+
+
+
+
+# print('Z_pos.shape', Z_pos.shape)
+
+
+
+
+
+
+
+## -- PLOT :
+mpl.rcParams['text.usetex'] = True
+mpl.rcParams["font.family"] = "serif"
+mpl.rcParams["font.size"] = "9"
+
+label_size = 8
+mpl.rcParams['xtick.labelsize'] = label_size
+mpl.rcParams['ytick.labelsize'] = label_size
+
+# plt.style.use('seaborn')
+plt.style.use('seaborn-whitegrid')
+# sns.set()
+# plt.style.use('seaborn-whitegrid')
+
+label_size = 9
+mpl.rcParams['xtick.labelsize'] = label_size
+mpl.rcParams['ytick.labelsize'] = label_size
+
+width = 6.28 *0.5
+width = 6.28
+height = width / 1.618
+fig = plt.figure()
+
+ax = plt.axes(projection ='3d', adjustable='box')
+# ax = plt.axes((0.17,0.21 ,0.75,0.75))
+# ax = plt.axes((0.15,0.18,0.8,0.8))
+# ax.tick_params(axis='x',which='major', direction='out',pad=5)
+# ax.tick_params(axis='y',which='major', length=3, width=1, direction='out',pad=3)
+# ax.xaxis.set_major_locator(MultipleLocator(0.1))
+# ax.xaxis.set_minor_locator(MultipleLocator(0.05))
+# ax.xaxis.set_major_locator(plt.MultipleLocator(np.pi / 8))
+# ax.xaxis.set_minor_locator(plt.MultipleLocator(np.pi / 16))
+# ax.xaxis.set_major_locator(plt.MultipleLocator(np.pi / 2))
+# ax.xaxis.set_minor_locator(plt.MultipleLocator(np.pi / 4))
+# ax.xaxis.set_major_formatter(plt.FuncFormatter(format_func))
+ax.grid(True,which='major',axis='both',alpha=0.3)
+
+# colorfunction=(B*kappa)
+# print('colofunction',colorfunction)
+
+#translate Data
+# Z = Z - (Z.max()-Z.min())/2
+# Z = Z - 50
+# Z = Z - 500
+#
+# Z = Z.T
+
+
+# Substract constant:
+# c = (b1**2)*q1+b1*b2*q12+(b2**2)*q2
+# Z = Z-c
+
+# print('Value of c:', c)
+
+
+
+# print('Z.min()', Z.min())
+# print('Z.max()', Z.max())
+# norm=mcolors.Normalize(Z.min(),Z.max())
+# facecolors=cm.brg(norm)
+
+
+# print('norm:', norm)
+# print('type of norm', type(norm))
+# print('norm(0):', norm(0))
+# print('norm(Z):', norm(Z))
+
+# ax.plot(theta_rho, theta_values, 'royalblue', zorder=3, )
+
+# ax.scatter(a1,a2, s=0.5)
+
+# ax.scatter(tmp1_pos,tmp2_pos, s=0.5)
+# ax.scatter(tmp1_neg,tmp2_neg, s=0.5)
+
+# CS = ax.contour(a1, a2, Z,10, cmap=plt.cm.gnuplot, levels=100 )
+# CS = ax.contour(a1, a2, Z,10, cmap=plt.cm.gnuplot,  levels=20 )
+
+
+# sns.kdeplot(np.array([a1, a2, Z]))
+# sns.kdeplot(tmp1_pos,tmp2_pos,Z_pos)
+
+# levels = [-5.0, -4, -3, 0.0, 1.5, 2.5, 3.5]
+# CS = ax.contour(a1, a2, Z,10, cmap=plt.cm.gnuplot, corner_mask=True,levels=levels)
+# CS = ax.contour(a1, a2, Z, cmap=plt.cm.gnuplot(norm(Z)), corner_mask=True)
+# CS = ax.contour(a1, a2, Z, cm.brg(norm(Z)), levels=20)
+# CS = ax.contour(a1, a2, Z, cmap=plt.cm.gnuplot, levels=20)
+# CS = ax.contour(a1, a2, Z, colors='k', levels=14,  linewidths=(0.5,))
+# CS = ax.contour(a1, a2, Z, colors='k', levels=18,  linewidths=(0.5,))
+
+# ax.contour(negZ_a1, negZ_a2, negativeValues, colors='k',  linewidths=(0.5,))
+# CS =  ax.contour(a1_in, a2_in, Z_in, colors='k',  linewidths=(0.5,))
+
+
+
+# df = pd.DataFrame(data=Z_in, columns=a1_in, index=a2_in)
+# df2 = pd.DataFrame(np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]),
+#                    columns=['a', 'b', 'c'])
+
+
+
+
+# sns.kdeplot(data=df2, x="waiting", y="duration")
+# sns.kdeplot(data=df2)
+
+# CS = ax.contour(a1, a2, Z, colors='k',   linewidths=(0.5,))
+
+# CS = ax.contour(a1, a2, Z,10, cmap=plt.cm.gnuplot, extend='both', levels=50)
+# CS = ax.contourf(a1, a2, Z,10, colors='k', extend='both', levels=50)
+# CS = ax.contourf(a1, a2, Z,10, colors='k')
+#
+# # CS = ax.contour(tmp1_pos,tmp2_pos, Z_pos,10, cmap=plt.cm.gnuplot, levels=10 )
+# # CS = ax.contour(tmp1_pos,tmp2_pos, Z_pos,10, cmap=plt.cm.gnuplot, corner_mask=True)
+#
+# CS = ax.contour(a1, a2, Z,10,  colors = 'k')
+# ax.clabel(CS, inline=True, fontsize=4)
+
+
+# cmap = cm.brg(norm(Z))
+#
+# C_map = cm.inferno(norm(Z))
+
+# ax.imshow(Z, cmap=C_map, extent=[-20, 20, -20, 20], origin='lower', alpha=0.5)
+
+# ax.imshow(norm(Z), extent=[-20, 20, -20, 20], origin='lower',
+#                   cmap='bwr', alpha=0.8)
+
+# ax.imshow(norm(Z), extent=[-20, 20, -20, 20],origin='lower', vmin=Z.min(), vmax=Z.max(),
+#                   cmap='bwr', alpha=0.6)
+
+# ax.imshow(norm(Z), extent=[-20, 20, -20, 20],origin='lower', norm = norm,
+#                   cmap='coolwarm', alpha=0.6)
+
+
+cmap=mpl.cm.RdBu_r
+# cmap=mpl.cm.viridis_r
+cmap=mpl.cm.bwr
+# # cmap=mpl.cm.coolwarm
+# # cmap=mpl.cm.gnuplot
+# cmap=mpl.cm.viridis
+# cmap=mpl.cm.inferno
+# # # cmap=mpl.cm.Blues
+# cmap=mpl.cm.magma
+cmap=mpl.cm.cividis
+# cmap=mpl.cm.gnuplot
+# cmap=mpl.cm.gnuplot
+
+
+# cmap = cm.brg(Z)
+# divnorm=mcolors.TwoSlopeNorm(vmin=Z.min(), vcenter=0., vmax=Z.max())
+
+# ax.imshow(Z, extent=[-20, 20, -20, 20],origin='lower', norm = norm,
+#                   cmap='coolwarm', alpha=0.6)
+
+# ax.imshow(Z, extent=[-20, 20, -20, 20],origin='lower',
+#                   cmap='coolwarm', alpha=0.6)
+# ax.imshow(Z, extent=[-20, 20, -20, 20],origin='lower',
+#                   cmap=cmap, alpha=0.6)
+
+# divnorm=mcolors.TwoSlopeNorm(vmin=Z.min(), vcenter=0., vmax=Z.max())
+# plt.imshow(Z, extent=[x.min(), x.max(), y.min(), y.max()],origin='lower',
+#                   cmap=cmap, alpha=0.6)
+
+# plt.imshow(Z, extent=[x.min(), x.max(), y.min(), y.max()],origin='lower', norm = divnorm,
+#                   cmap=cmap, alpha=0.6)
+
+
+
+
+# COLORBAR :
+# cbar = plt.colorbar()
+# cbar.ax.tick_params(labelsize=8)
+
+
+
+
+# ##----- ADD RECTANGLE TO COVER QUADRANT :
+# epsilon = 0.4
+# epsilon = 0.1
+# # ax.axvspan(0, x.max(), y.min(), 0, alpha=1, color='yellow', zorder=5)#yellow
+# # ax.fill_between([0, x.max()], y.min(), 0, alpha=0.3, color='yellow', zorder=5)#yellow
+# # ax.fill_between([x.min(), 0], 0, y.max(), alpha=0.3, color='yellow', zorder=5)#yellow
+# ax.fill_between([0+epsilon, x.max()], y.min(), 0-epsilon, alpha=0.7, color='gray', zorder=5)#yellow
+# ax.fill_between([x.min(), 0-epsilon], 0+epsilon, y.max(), alpha=0.7, color='gray', zorder=5)#yellow
+
+
+# ax.plot_surface(a1,a2, Z, cmap=cm.coolwarm,
+#                        linewidth=0, antialiased=False)
+
+# ax.plot_surface(tmp1,tmp2, Z, cmap=cm.coolwarm,
+#                        linewidth=0, antialiased=False)
+
+# ax.scatter(X_1,Y_1,Z1, s=0.2)
+# ax.scatter(X_2,Y_2,Z2, s=0.2)
+
+# ax.plot_surface(X_1,Y_1,Z1 ,cmap=cmap,
+#                        linewidth=0, antialiased=False,alpha=1, zorder=5)
+ax.plot_surface(X_1,Y_1,Z1 ,cmap=cmap,
+                       linewidth=0, antialiased=True,alpha=1, zorder=5)
+
+ax.plot_surface(X_2,Y_2,Z2 ,cmap=cmap,
+                       linewidth=0, antialiased=True,alpha=1, zorder=5)
+
+
+# ax.plot(G[0,:],G[1,:],G[2,:])
+# ax.plot(abar[0,:],abar[1,:],Z_bar, linewidth=2, color='yellow', linestyle='--')
+# ax.scatter(abar[0,:],abar[1,:],Z_bar,  color='purple', zorder=5)
+# ax.plot(abar[0,:],abar[1,:],Z_bar, linewidth=2, color='royalblue', linestyle='--')
+# ax.plot(abar[0,:],abar[1,:],Z_bar, linewidth=3, color='dodgerblue', linestyle='--')
+# ax.plot(abar[0,:],abar[1,:],Z_bar, linewidth=3, color='cornflowerblue', linestyle='--')
+# ax.plot(abar[0,:],abar[1,:],Z_bar, linewidth=3, color='darkorange', linestyle='--')
+# ax.plot(abar[0,:],abar[1,:],Z_bar, linewidth=3, color='yellow', linestyle='--')
+# line = ax.plot(abar[0,:],abar[1,:],Z_bar, linewidth=1, color='coral', linestyle='--', zorder=3)
+line = ax.plot(abar[0,:],abar[1,:],Z_bar, linewidth=2, color='coral', zorder=2)
+# CS = ax.contour(X_1,Y_1,Z1, colors='k', levels=18,  linewidths=(0.5,))
+
+start = np.array([abar[0,499],abar[1,499],Z_bar[499]])
+end = np.array([abar[0,500],abar[1,500],Z_bar[500]])
+
+# plot starting point:
+# ax.scatter(abar[0,0],abar[1,0],Z_bar[0], marker='^',  s=30, color='black', zorder=5)
+#
+#
+# ax.scatter(abar[0,500],abar[1,500],Z_bar[500], marker='^',  s=30, color='purple', zorder=5)
+
+# ax.scatter(start[0],start[1],start[2], marker='^',  s=30, color='purple', zorder=5)
+# ax.scatter(end[0],end[1],end[2], marker='^',  s=30, color='purple', zorder=5)
+
+print('start:', start)
+print('end:', end)
+
+
+dir = end-start
+# ax.arrow()
+
+# ax.arrow3D(start[0],start[1],start[2],
+#            dir[0],dir[1],dir[2],
+#            mutation_scale=10,
+#            arrowstyle="->",
+#            linestyle='dashed',fc='coral',
+#            lw = 1,
+#            ec ='coral',
+#            zorder=3)
+
+# ax.arrow3D(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],
+#            normal[0],normal[1],normal[2],
+#            mutation_scale=15,
+#             lw = 1.5,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='blue',
+#            ec ='blue',
+#            zorder = 5)
+
+# Check proof:
+# value at t = 0:
+abar_zero= sstar*abar_tmp
+# value_0 = [abar_zero[0], abar_zero[1] , (2*abar_zero[0]*abar_zero[1])**0.5 ]
+value_0 = evaluate(abar_zero[0], abar_zero[1])
+print('value_0', value_0)
+# ax.scatter(value_0[0],value_0[1],value_0[2], marker='x',  s=20, color='dodgerblue', zorder=5)
+# ax.scatter(abar_zero[0], abar_zero[1],value_0, marker='o',  s=30, color='dodgerblue', zorder=5)
+## -----------------------------
+
+
+
+
+
+
+
+
+
+
+# ax.scatter(tmp1,tmp2, Z, cmap=cm.coolwarm,
+#                        linewidth=0, antialiased=False)
+# ax.plot_surface(tmp1,Z, tmp2, cmap=cm.coolwarm,
+#                        linewidth=0, antialiased=False)
+# ax.plot_trisurf(tmp1,tmp2, Z, cmap=cm.coolwarm,
+#                        linewidth=0, antialiased=False)
+
+
+# ax.plot(theta_rho, energy_axial1, 'royalblue', zorder=3, label=r"axialMin1")
+# ax.plot(theta_rho, energy_axial2, 'forestgreen', zorder=3, label=r"axialMin2")
+# ax.plot(-1.0*alphas, kappas, 'red', zorder=3, )
+
+
+
+
+# lg = ax.legend(bbox_to_anchor=(0.0, 0.75), loc='upper left')
+
+
+
+### PLot x and y- Axes
+# ax.plot(ax.get_xlim(),[0,0],'k--', linewidth=0.5)
+# ax.plot([0,0],ax.get_ylim(), 'k--', linewidth=0.5)
+ax.plot(ax.get_xlim(),[0,0],'k--', linewidth=1)
+ax.plot([0,0],ax.get_ylim(), 'k--', linewidth=1)
+
+
+
+ax.set_xlabel(r"$a_1$", fontsize=10 ,labelpad=0)
+ax.set_ylabel(r"$a_2$", fontsize=10 ,labelpad=0)
+# ax.set_ylabel(r"energy")
+
+
+# ax.set_xticks([-np.pi/2, -np.pi/4  ,0,  np.pi/4,  np.pi/2 ])
+# labels = ['$0$',r'$\pi/8$', r'$\pi/4$' ,r'$3\pi/8$' , r'$\pi/2$']
+# ax.set_yticklabels(labels)
+
+
+
+
+
+# ax.legend(loc='upper right')
+
+
+
+fig.set_size_inches(width, height)
+fig.savefig('1-ParameterFamily_G+.pdf')
+
+plt.show()
+
+
+#
+#
+#
+# # Curve parametrised by \theta_rho = alpha in parameter space
+# N=100;
+# theta_rho = np.linspace(1, 3, num=N)
+# print('theta_rho:', theta_rho)
+#
+#
+# theta_values = []
+#
+#
+# for t in theta_rho:
+#
+#         s = (1.0/10.0)*t+0.1
+#         theta_values.append(s)
+#
+#
+#
+#
+#
+# theta_rho = np.array(theta_rho)
+# theta_values = np.array(theta_values)
+#
+# betas_ = 2.0
+#
+
+# alphas, betas, thetas = np.meshgrid(theta_rho, betas_, theta_values, indexing='ij')
+#
+#
+# harmonicMeanVec = np.vectorize(harmonicMean)
+# arithmeticMeanVec = np.vectorize(arithmeticMean)
+# prestrain_b1Vec = np.vectorize(prestrain_b1)
+# prestrain_b2Vec = np.vectorize(prestrain_b2)
+#
+# GetMuGammaVec = np.vectorize(GetMuGamma)
+# muGammas = GetMuGammaVec(betas,thetas,gamma,mu1,rho1,InputFilePath ,OutputFilePath )
+#
+# q1_vec = harmonicMeanVec(mu1, betas, thetas)
+# q2_vec = arithmeticMeanVec(mu1, betas, thetas)
+#
+# b1_vec = prestrain_b1Vec(rho1, betas, alphas, thetas)
+# b2_vec = prestrain_b2Vec(rho1, betas, alphas, thetas)
+
+# special case: q12 == 0!! .. braucht eigentlich nur b1 & b2 ...
+
+# print('type b1_values:', type(b1_values))
+
+
+
+# print('size(q1)',q1.shape)
+#
+#
+# energy_axial1 = []
+# energy_axial2 = []
+#
+# # for b1 in b1_values:
+# for i in range(len(theta_rho)):
+#     print('index i:', i)
+#
+#     print('theta_rho[i]',theta_rho[i])
+#     print('theta_values[i]',theta_values[i])
+#
+#     q1 = (1.0/6.0)*harmonicMean(mu1, beta, theta_values[i])
+#     q2 = (1.0/6.0)*arithmeticMean(mu1, beta, theta_values[i])
+#     q12 = 0.0
+#     q3 = GetMuGamma(beta, theta_values[i],gamma,mu1,rho1,InputFilePath ,OutputFilePath )
+#     b1 = prestrain_b1(rho1,beta, theta_rho[i],theta_values[i] )
+#     b2 = prestrain_b2(rho1,beta, theta_rho[i],theta_values[i] )
+#
+#
+#     # q2_vec = arithmeticMean(mu1, betas, thetas)
+#     #
+#     # b1_vec = prestrain_b1Vec(rho1, betas, alphas, thetas)
+#     # b2_vec = prestrain_b2Vec(rho1, betas, alphas, thetas)
+#     print('q1[i]',q1)
+#     print('q2[i]',q2)
+#     print('q3[i]',q3)
+#     print('b1[i]',b1)
+#     print('b2[i]',b2)
+#     # print('q1[i]',q1[0][i])
+#     # print('q2[i]',q2[i])
+#     # print('b1[i]',b1[i])
+#     # print('b2[i]',b2[i])
+#     #compute axial energy #1 ...
+#
+#     a_axial1 = np.array([b1,0])
+#     a_axial2 = np.array([0,b2])
+#     b = np.array([b1,b2])
+#
+#     H = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+#     A = np.array([[q1,1/2*q12], [1/2*q12,q2] ])
+#
+#
+#     tmp = H.dot(a_axial1)
+#
+#     print('H',H)
+#     print('A',A)
+#     print('b',b)
+#     print('a_axial1',a_axial1)
+#     print('tmp',tmp)
+#
+#     tmp = (1/2)*a_axial1.dot(tmp)
+#     print('tmp',tmp)
+#
+#     tmp2 = A.dot(b)
+#     print('tmp2',tmp2)
+#     tmp2 = 2*a_axial1.dot(tmp2)
+#
+#     print('tmp2',tmp2)
+#     energy_1 = tmp - tmp2
+#     print('energy_1',energy_1)
+#
+#
+#     energy_axial1.append(energy_1)
+#
+#
+#     tmp = H.dot(a_axial2)
+#
+#     print('H',H)
+#     print('A',A)
+#     print('b',b)
+#     print('a_axial2',a_axial2)
+#     print('tmp',tmp)
+#
+#     tmp = (1/2)*a_axial2.dot(tmp)
+#     print('tmp',tmp)
+#
+#     tmp2 = A.dot(b)
+#     print('tmp2',tmp2)
+#     tmp2 = 2*a_axial2.dot(tmp2)
+#
+#     print('tmp2',tmp2)
+#     energy_2 = tmp - tmp2
+#     print('energy_2',energy_2)
+#
+#
+#     energy_axial2.append(energy_2)
+#
+#
+#
+#
+#
+# print('theta_values', theta_values)
+#
+#
+#
+
+
+#
+#
+#
+#
+# kappas = []
+# alphas = []
+# # G.append(float(s[0]))
+#
+#
+#
+#
+# for t in T :
+#
+#     abar_current = sstar*abar+t*abarperp;
+#     # print('abar_current', abar_current)
+#     abar_current[abar_current < 1e-10] = 0
+#     # print('abar_current', abar_current)
+#
+#     # G = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+#     G = [abar_current[0], abar_current[1] , (2*abar_current[0]*abar_current[1])**0.5 ]
+#
+#     e = [(abar_current[0]/(abar_current[0]+abar_current[1]))**0.5, (abar_current[1]/(abar_current[0]+abar_current[1]))**0.5]
+#     kappa = abar_current[0]+abar_current[1]
+#     alpha = math.atan2(e[1], e[0])
+#
+#     print('angle current:', alpha)
+#
+#     kappas.append(kappa)
+#     alphas.append(alpha)
+#
+#
+#
+# alphas = np.array(alphas)
+# kappas = np.array(kappas)
+#
+#
+# print('kappas:',kappas)
+# print('alphas:',alphas)
+# print('min alpha:', min(alphas))
+# print('min kappa:', min(kappas))
+#
+# mpl.rcParams['text.usetex'] = True
+# mpl.rcParams["font.family"] = "serif"
+# mpl.rcParams["font.size"] = "9"
+# width = 6.28 *0.5
+# height = width / 1.618
+# fig = plt.figure()
+# # ax = plt.axes((0.15,0.21 ,0.75,0.75))
+# ax = plt.axes((0.15,0.21 ,0.8,0.75))
+# ax.tick_params(axis='x',which='major', direction='out',pad=5)
+# ax.tick_params(axis='y',which='major', length=3, width=1, direction='out',pad=3)
+# # ax.xaxis.set_major_locator(MultipleLocator(0.1))
+# # ax.xaxis.set_minor_locator(MultipleLocator(0.05))
+# # ax.xaxis.set_major_locator(plt.MultipleLocator(np.pi / 8))
+# # ax.xaxis.set_minor_locator(plt.MultipleLocator(np.pi / 16))
+# ax.xaxis.set_major_locator(plt.MultipleLocator(np.pi / 2))
+# ax.xaxis.set_minor_locator(plt.MultipleLocator(np.pi / 4))
+# ax.xaxis.set_major_formatter(plt.FuncFormatter(format_func))
+# ax.grid(True,which='major',axis='both',alpha=0.3)
+#
+#
+#
+#
+# ax.plot(alphas, kappas, 'royalblue', zorder=3, )
+# ax.plot(-1.0*alphas, kappas, 'red', zorder=3, )

Python-Scripts/1-ParameterFamily_G+_Flat.py

+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
+
+import matplotlib as mpl
+from matplotlib.ticker import MultipleLocator,FormatStrFormatter,MaxNLocator
+import pandas as pd
+
+import seaborn as sns
+import matplotlib.colors as mcolors
+
+from chart_studio import plotly
+import plotly.graph_objs as go
+import plotly.express as px
+import plotly.colors
+# from matplotlib import rc
+# rc('text', usetex=True) # Use LaTeX font
+#
+# import seaborn as sns
+# sns.set(color_codes=True)
+
+
+def show(fig):
+    import io
+    import plotly.io as pio
+    from PIL import Image
+    buf = io.BytesIO()
+    pio.write_image(fig, buf)
+    img = Image.open(buf)
+    img.show()
+
+
+
+
+def add_arrow(line, position=None, direction='right', size=15, color=None):
+    """
+    add an arrow to a line.
+
+    line:       Line2D object
+    position:   x-position of the arrow. If None, mean of xdata is taken
+    direction:  'left' or 'right'
+    size:       size of the arrow in fontsize points
+    color:      if None, line color is taken.
+    """
+    if color is None:
+        color = line.get_color()
+
+    xdata = line.get_xdata()
+    ydata = line.get_ydata()
+
+    if position is None:
+        position = xdata.mean()
+    # find closest index
+    start_ind = np.argmin(np.absolute(xdata - position))
+    if direction == 'right':
+        end_ind = start_ind + 1
+    else:
+        end_ind = start_ind - 1
+
+    line.axes.annotate('',
+        xytext=(xdata[start_ind], ydata[start_ind]),
+        xy=(xdata[end_ind], ydata[end_ind]),
+        arrowprops=dict(arrowstyle="->", color=color),
+        size=size
+    )
+
+
+# set the colormap and centre the colorbar
+class MidpointNormalize(mcolors.Normalize):
+	"""
+	Normalise the colorbar so that diverging bars work there way either side from a prescribed midpoint value)
+
+	e.g. im=ax1.imshow(array, norm=MidpointNormalize(midpoint=0.,vmin=-100, vmax=100))
+	"""
+	def __init__(self, vmin=None, vmax=None, midpoint=None, clip=False):
+		self.midpoint = midpoint
+		mcolors.Normalize.__init__(self, vmin, vmax, clip)
+
+	def __call__(self, value, clip=None):
+		# I'm ignoring masked values and all kinds of edge cases to make a
+		# simple example...
+		x, y = [self.vmin, self.midpoint, self.vmax], [0, 0.5, 1]
+		return np.ma.masked_array(np.interp(value, x, y), np.isnan(value))
+
+
+
+def set_size(width, fraction=1):
+    """Set figure dimensions to avoid scaling in LaTeX.
+
+    Parameters
+    ----------
+    width: float
+            Document textwidth or columnwidth in pts
+    fraction: float, optional
+            Fraction of the width which you wish the figure to occupy
+
+    Returns
+    -------
+    fig_dim: tuple
+            Dimensions of figure in inches
+    """
+    # Width of figure (in pts)
+    fig_width_pt = width * fraction
+
+    # Convert from pt to inches
+    inches_per_pt = 1 / 72.27
+
+    # Golden ratio to set aesthetic figure height
+    # https://disq.us/p/2940ij3
+    golden_ratio = (5**.5 - 1) / 2
+
+    # Figure width in inches
+    fig_width_in = fig_width_pt * inches_per_pt
+    # Figure height in inches
+    fig_height_in = fig_width_in * golden_ratio
+
+    fig_dim = (fig_width_in, fig_height_in)
+
+    return fig_dim
+
+
+
+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 == -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)
+    ##find number of multiples of pi/2
+    N = int(np.round(4 * value / np.pi))
+    if N == 0:
+        return "0"
+    elif N == 1:
+        return r"$\pi/4$"
+    elif N == -1:
+        return r"$-\pi/4$"
+    elif N == 2:
+        return r"$\pi/2$"
+    elif N == -2:
+        return r"$-\pi/2$"
+    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
+
+
+
+def energy(a1,a2,q1,q2,q12,q3,b1,b2):
+
+
+    a = np.array([a1,a2])
+    b = np.array([b1,b2])
+    H = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+    A = np.array([[q1,1/2*q12], [1/2*q12,q2] ])
+
+
+    tmp = H.dot(a)
+
+    # print('H',H)
+    # print('A',A)
+    # print('b',b)
+    # print('a',a)
+    # print('tmp',tmp)
+
+    tmp = (1/2)*a.dot(tmp)
+    # print('tmp',tmp)
+
+    tmp2 = A.dot(b)
+    # print('tmp2',tmp2)
+    tmp2 = 2*a.dot(tmp2)
+
+    # print('tmp2',tmp2)
+    energy = tmp - tmp2
+    # print('energy',energy)
+
+
+    # energy_axial1.append(energy_1)
+
+    return energy
+
+
+
+# def energy(a1,a2,q1,q2,q12,q3,b1,b2):
+#
+#
+#     b = np.array([b1,b2])
+#     H = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+#     A = np.array([[q1,1/2*q12], [1/2*q12,q2] ])
+#
+#
+#     tmp = H.dot(a)
+#
+#     print('H',H)
+#     print('A',A)
+#     print('b',b)
+#     print('a',a)
+#     print('tmp',tmp)
+#
+#     tmp = (1/2)*a.dot(tmp)
+#     print('tmp',tmp)
+#
+#     tmp2 = A.dot(b)
+#     print('tmp2',tmp2)
+#     tmp2 = 2*a.dot(tmp2)
+#
+#     print('tmp2',tmp2)
+#     energy = tmp - tmp2
+#     print('energy',energy)
+#
+#
+#     # energy_axial1.append(energy_1)
+#
+#     return energy
+#
+
+
+
+
+
+################################################################################################################
+################################################################################################################
+################################################################################################################
+
+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: -----')
+
+# q1=1;
+# q2=2;
+# q12=1/2;
+# q3=((4*q1*q2)**0.5-q12)/2;
+# # H=[2*q1,q12+2*q3;q12+2*q3,2*q2];
+#
+# H = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+# A = np.array([[q1,1/2*q12], [1/2*q12,q2] ])
+# abar = np.array([q12+2*q3, 2*q2])
+# abar = (1.0/math.sqrt((q12+2*q3)**2+(2*q2)**2))*abar
+#
+# print('abar:',abar)
+#
+# b = np.linalg.lstsq(A, abar)[0]
+# print('b',b)
+#
+#
+# # print('abar:',np.shape(abar))
+# # print('np.transpose(abar):',np.shape(np.transpose(abar)))
+# sstar = (1/(q1+q2))*abar.dot(A.dot(b))
+# # sstar = (1/(q1+q2))*abar.dot(tmp)
+# print('sstar', sstar)
+# abarperp= np.array([abar[1],-abar[0]])
+# print('abarperp:',abarperp)
+
+
+# -------------------------- Input Parameters --------------------
+
+mu1 = 1.0
+rho1 = 1.0
+alpha = 5.0
+theta = 1.0/2
+# theta= 0.1
+beta = 5.0
+
+
+
+
+# mu1 = 1.0
+# rho1 = 1.0
+# alpha = -0.75
+# theta = 1.0/2
+# # theta= 0.1
+# beta = 5.0
+
+
+# mu1 = 1.0
+# rho1 = 1.0
+# alpha = 2.0
+# theta = 1.0/2
+# # theta= 0.1
+# beta = 5.0
+
+
+#Figure3:
+# mu1 = 1.0
+# rho1 = 1.0
+# alpha = 2.0
+# theta = 1.0/8
+# # theta= 0.1
+# beta = 2.0
+
+
+# alpha= -5
+
+
+#set gamma either to 1. '0' 2. 'infinity' or 3. a numerical positive value
+gamma = '0'
+# gamma = 'infinity'
+
+
+lambda1 = 0.0
+
+
+print('---- Input parameters: -----')
+print('mu1: ', mu1)
+print('rho1: ', rho1)
+# print('alpha: ', alpha)
+print('beta: ', beta)
+# print('theta: ', theta)
+print('gamma:', gamma)
+
+print('lambda1: ', lambda1)
+print('----------------------------')
+# ----------------------------------------------------------------
+print('----------------------------')
+
+# ----------------------------------------------------------------
+
+
+
+
+
+
+q1 = (1.0/6.0)*harmonicMean(mu1, beta, theta)
+q2 = (1.0/6.0)*arithmeticMean(mu1, beta, theta)
+q12 = 0.0
+q3 = GetMuGamma(beta, theta,gamma,mu1,rho1,InputFilePath ,OutputFilePath )
+b1 = prestrain_b1(rho1,beta, alpha, theta )
+b2 = prestrain_b2(rho1,beta, alpha, theta )
+
+
+## ---- 1-ParameterFamilyCase:
+# q1=1;
+# q2=2;
+# q12=1/2;
+# q3=((4*q1*q2)**0.5-q12)/2;
+# # H=[2*q1,q12+2*q3;q12+2*q3,2*q2];
+# H = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+# A = np.array([[q1,1/2*q12], [1/2*q12,q2] ])
+# abar = np.array([q12+2*q3, 2*q2])
+# abar = (1.0/math.sqrt((q12+2*q3)**2+(2*q2)**2))*abar
+# print('abar:',abar)
+# b = np.linalg.lstsq(A, abar)[0]
+# print('b',b)
+# b1=b[0]
+# b2=b[1]
+## ---------------
+
+
+
+
+
+########################################
+
+# 1-ParameterFamilyCase:
+
+q1=1;
+q2=2;
+q12=1/2;
+q3=((4*q1*q2)**0.5-q12)/2;
+# H=[2*q1,q12+2*q3;q12+2*q3,2*q2];
+
+H = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+A = np.array([[q1,1/2*q12], [1/2*q12,q2] ])
+abar = np.array([q12+2*q3, 2*q2])
+abar = (1.0/math.sqrt((q12+2*q3)**2+(2*q2)**2))*abar
+
+print('abar:',abar)
+
+b = np.linalg.lstsq(A, abar)[0]
+print('b',b)
+
+b1=b[0]
+b2=b[1]
+
+
+##----------------------
+print('q1 = ', q1)
+print('q2 = ', q2)
+print('q3 = ', q3)
+print('q12 = ', q12)
+print('b1 = ', b1)
+print('b2 = ', b2)
+##--------------
+
+
+# print('abar:',np.shape(abar))
+# print('np.transpose(abar):',np.shape(np.transpose(abar)))
+sstar = (1/(q1+q2))*abar.dot(A.dot(b))
+# sstar = (1/(q1+q2))*abar.dot(tmp)
+print('sstar', sstar)
+abarperp= np.array([abar[1],-abar[0]])
+print('abarperp:',abarperp)
+
+print('sstar*abar:', sstar*abar)
+# print('np.dot(sstar*abar):', np.dot(sstar*abar))
+print('----------------------------')
+
+
+N=1000;
+# N=10;
+scale_domain = 5
+
+translate_startpoint = -1.8
+
+T = np.linspace(-sstar*(q12+2*q3)/(2*q2), sstar*(2*q2)/(q12+2*q3), num=N)
+# T = np.linspace(-sstar*(q12+2*q3)/(2*q2)*scale_domain + translate_startpoint, sstar*(2*q2)/(q12+2*q3)*scale_domain , num=N)
+# T = np.linspace(-2,2, num=N)
+# print('T:', T)
+
+print('T.min():', T.min())
+print('T.max():', T.max())
+
+kappas = []
+alphas = []
+# G.append(float(s[0]))
+
+G_container = []
+abar_container = []
+
+test = sstar*abar
+
+
+abar_tmp = abar
+
+for t in T :
+    abar_current = sstar*abar+t*abarperp;
+    # abar_current[abar_current < 1e-10] = 0   # Projection onto x-y-axis!!
+    print('abar_current', abar_current)
+    G = [abar_current[0], abar_current[1] , (2*abar_current[0]*abar_current[1])**0.5 ]
+    G_container.append(G)
+    abar_container.append(abar_current)
+    e = [(abar_current[0]/(abar_current[0]+abar_current[1]))**0.5, (abar_current[1]/(abar_current[0]+abar_current[1]))**0.5]
+    kappa = abar_current[0]+abar_current[1]
+    alpha = math.atan2(e[1], e[0])
+	# print('angle current:', alpha)
+    kappas.append(kappa)
+    alphas.append(alpha)
+
+
+alphas = np.array(alphas)
+kappas = np.array(kappas)
+
+# print('G_container', G_container)
+G = np.array(G_container)
+abar = np.array(abar_container)
+
+print('G', G)
+print('abar', abar)
+print('abar.shape',abar.shape)
+
+
+
+
+
+
+
+
+
+
+######################################
+
+
+
+num_Points = 400
+num_Points = 200
+# num_Points = 20
+
+
+# Creating dataset
+x = np.linspace(-5,5,num_Points)
+y = np.linspace(-5,5,num_Points)
+
+x = np.linspace(-20,20,num_Points)
+y = np.linspace(-20,20,num_Points)
+
+
+x = np.linspace(-2,2,num_Points)
+y = np.linspace(-2,2,num_Points)
+
+# x = np.linspace(-10,10,num_Points)
+# y = np.linspace(-10,10,num_Points)
+
+# x = np.linspace(-60,60,num_Points)
+# y = np.linspace(-60,60,num_Points)
+#
+#
+# x = np.linspace(-40,40,num_Points)
+# y = np.linspace(-40,40,num_Points)
+
+
+a1, a2 = np.meshgrid(x,y)
+
+# geyser = sns.load_dataset("geyser")
+# print('type of geyser:', type(geyser))
+# print('geyser:',geyser)
+
+ContourRange=20
+
+x_in = np.linspace(-ContourRange,ContourRange,num_Points)
+y_in = np.linspace(-ContourRange,ContourRange,num_Points)
+a1_in, a2_in = np.meshgrid(x_in,y_in)
+
+print('a1:', a1)
+print('a2:',a2 )
+
+print('a1.shape', a1.shape)
+
+#-- FILTER OUT VALUES for G+ :
+
+# tmp1 = a1[np.where(a1*a2 >= 0)]
+# tmp2 = a2[np.where(a1*a2 >= 0)]
+#
+# np.take(a, np.where(a>100)[0], axis=0)
+# tmp1 = np.take(a1, np.where(a1*a2 >= 0)[0], axis=0)
+# tmp2 = np.take(a1, np.where(a1*a2 >= 0)[0], axis=0)
+# tmp2 = a2[np.where(a1*a2 >= 0)]
+
+tmp1 = a1[a1*a2 >= 0]
+tmp2 = a2[a1*a2 >= 0]
+tmp1 = tmp1.reshape(-1,5)
+tmp2 = tmp2.reshape(-1,5)
+
+
+# tmp1_pos = a1[np.where(a1*a2 >= 0) ]
+# tmp2_pos = a2[np.where(a1*a2 >= 0) ]
+# tmp1_pos = tmp1_pos[np.where(tmp1_pos  >= 0)]
+# tmp2_pos = tmp2_pos[np.where(tmp2_pos  >= 0)]
+#
+# tmp1_neg = a1[a1*a2 >= 0 ]
+# tmp2_neg = a2[a1*a2 >= 0 ]
+# tmp1_neg = tmp1_neg[tmp1_neg  < 0]
+# tmp2_neg = tmp2_neg[tmp2_neg  < 0]
+# a1 = tmp1
+# a2 = tmp2
+#
+# a1 = a1.reshape(-1,5)
+# a2 = a2.reshape(-1,5)
+#
+# tmp1_pos = tmp1_pos.reshape(-1,5)
+# tmp2_pos = tmp2_pos.reshape(-1,5)
+# tmp1_neg = tmp1_neg.reshape(-1,5)
+# tmp2_neg = tmp2_neg.reshape(-1,5)
+
+
+print('a1:', a1)
+print('a2:',a2 )
+print('a1.shape', a1.shape)
+
+
+
+
+
+energyVec = np.vectorize(energy)
+
+# Z = energyVec(np.array([a1,a2]),q1,q2,q12,q3,b1,b2)
+Z = energyVec(a1,a2,q1,q2,q12,q3,b1,b2)
+
+Z_in = energyVec(a1_in,a2_in,q1,q2,q12,q3,b1,b2)
+
+
+
+
+print('Z:', Z)
+
+print('any', np.any(Z<0))
+
+#
+
+
+# negZ_a1 = a1[np.where(Z<0)]
+# negZ_a2 = a2[np.where(Z<0)]
+# negativeValues = Z[np.where(Z<0)]
+# print('negativeValues:',negativeValues)
+#
+# print('negZ_a1',negZ_a1)
+# print('negZ_a2',negZ_a2)
+#
+#
+# negZ_a1 = negZ_a1.reshape(-1,5)
+# negZ_a2 = negZ_a2.reshape(-1,5)
+# negativeValues = negativeValues.reshape(-1,5)
+#
+# Z_pos =  energyVec(tmp1_pos,tmp2_pos,q1,q2,q12,q3,b1,b2)
+# Z_neg = energyVec(tmp1_neg,tmp2_neg,q1,q2,q12,q3,b1,b2)
+
+
+
+
+
+# print('Test energy:' , energy(np.array([1,1]),q1,q2,q12,q3,b1,b2))
+
+
+
+
+# print('Z_pos.shape', Z_pos.shape)
+
+
+
+
+
+
+
+## -- PLOT :
+mpl.rcParams['text.usetex'] = True
+mpl.rcParams["font.family"] = "serif"
+mpl.rcParams["font.size"] = "9"
+
+label_size = 8
+mpl.rcParams['xtick.labelsize'] = label_size
+mpl.rcParams['ytick.labelsize'] = label_size
+
+plt.style.use('seaborn')
+# plt.style.use('seaborn-whitegrid')
+# sns.set()
+# plt.style.use('seaborn-whitegrid')
+
+label_size = 9
+mpl.rcParams['xtick.labelsize'] = label_size
+mpl.rcParams['ytick.labelsize'] = label_size
+
+width = 6.28 *0.5
+# width = 6.28 *0.33
+# width = 6.28
+height = width #/ 1.618
+
+# width = 452.9579/2
+# size= set_size(width, fraction=0.5)
+# print('set_size(width, fraction=0.5)', set_size(width, fraction=1))
+# print('size[0]',size[0])
+
+f_size = 10
+# fig= plt.figure()
+fig, ax = plt.subplots()
+# fig.set_size_inches(width, height)
+# fig.set_size_inches(set_size(width, fraction=0.5))
+# ax = plt.axes(projection ='3d', adjustable='box')
+# ax = plt.axes((0.17,0.21 ,0.75,0.75))
+
+# ax = plt.axes((0.17,0.23 ,0.7,0.7))
+# ax = plt.axes((0.17,0.23 ,1.0,1.0))
+# ax=plt.axes()
+# ax = plt.axes((0.15,0.18,0.8,0.8))
+# ax.tick_params(axis='x',which='major', direction='out',pad=5)
+# ax.tick_params(axis='y',which='major', length=3, width=1, direction='out',pad=3)
+# ax.xaxis.set_major_locator(MultipleLocator(0.1))
+# ax.xaxis.set_minor_locator(MultipleLocator(0.05))
+# ax.xaxis.set_major_locator(plt.MultipleLocator(np.pi / 8))
+# ax.xaxis.set_minor_locator(plt.MultipleLocator(np.pi / 16))
+# ax.xaxis.set_major_locator(plt.MultipleLocator(np.pi / 2))
+# ax.xaxis.set_minor_locator(plt.MultipleLocator(np.pi / 4))
+# ax.xaxis.set_major_formatter(plt.FuncFormatter(format_func))
+ax.grid(True,which='major',axis='both',alpha=0.3)
+
+# Substract constant:
+# c = (b1**2)*q1+b1*b2*q12+(b2**2)*q2
+# Z = Z-c
+#
+# print('Value of c:', c)
+
+
+
+print('Z.min()', Z.min())
+print('Z.max()', Z.max())
+norm=mcolors.Normalize(Z.min(),Z.max())
+# facecolors=cm.brg(norm)
+
+
+
+
+cmap=mpl.cm.RdBu_r
+cmap=mpl.cm.viridis_r
+# cmap=mpl.cm.bwr
+cmap=mpl.cm.coolwarm
+# cmap=mpl.cm.gnuplot
+cmap=mpl.cm.magma_r
+# cmap=mpl.cm.inferno_r
+# cmap=mpl.cm.plasma
+# cmap=mpl.cm.plasma_r
+# cmap=mpl.cm.cividis_r
+# cmap = mpl.colors.LinearSegmentedColormap.from_list("", ["blue","violet","red"])
+# cmap = mpl.colors.LinearSegmentedColormap.from_list("", ["blue","orange"])
+
+# cmap = mpl.colors.LinearSegmentedColormap.from_list("", [(0,"red"), (.1,"violet"), (.5, "blue"), (1.0, "green")])
+# make a colormap that has land and ocean clearly delineated and of the
+# same length (256 + 256)
+#
+# colors_undersea = plt.cm.terrain(np.linspace(0, 0.17, 256))
+# colors_land = plt.cm.terrain(np.linspace(0.25, 1, 256))
+# all_colors = np.vstack((colors_undersea, colors_land))
+# # cmap = mcolors.LinearSegmentedColormap.from_list(
+# #     'terrain_map', all_colors)
+
+
+# cmap = px.colors.sequential.agsunset
+# cmap = plotly.colors.PLOTLY_SCALES["Viridis"]
+
+
+
+
+# cmap = cm.brg(Z)
+divnorm=mcolors.TwoSlopeNorm(vmin=Z.min(), vcenter=0., vmax=Z.max())
+divnorm=mcolors.TwoSlopeNorm(vmin=Z.min(), vcenter=(Z.max()+Z.min())/2, vmax=Z.max())
+# divnorm=mcolors.TwoSlopeNorm(vmin=-500, vcenter=0, vmax=Z.max())
+
+# divnorm=mcolors.TwoSlopeNorm(vmin=-10, vcenter=0. ,vmax=10)
+# divnorm=mcolors.TwoSlopeNorm(vmin=-10, vcenter=0., vmax=Z.max())
+
+# divnorm=mcolors.LogNorm(vmin=Z.min(),  vmax=Z.max())  #Test LogNorm
+
+# cmap = cm.brg(divnorm(Z))
+
+# ax.imshow(Z, extent=[-20, 20, -20, 20],origin='lower', norm = norm,
+#                   cmap='coolwarm', alpha=0.6)
+
+# ax.imshow(Z, extent=[-20, 20, -20, 20],origin='lower',
+#                   cmap='coolwarm', alpha=0.6)
+# ax.imshow(Z, extent=[-20, 20, -20, 20],origin='lower',
+#                   cmap=cmap, alpha=0.6)
+
+# divnorm=mcolors.TwoSlopeNorm(vmin=Z.min(), vcenter=0., vmax=Z.max())
+# plt.imshow(Z, extent=[x.min(), x.max(), y.min(), y.max()],origin='lower',
+#                   cmap=cmap, alpha=0.6)
+
+# I = plt.imshow(Z, extent=[x.min(), x.max(), y.min(), y.max()],origin='lower', norm = divnorm,
+#                   cmap=cmap, alpha=0.6)
+# plt.imshow(Z, extent=[x.min(), x.max(), y.min(), y.max()],origin='lower', norm = divnorm,
+#                   cmap=cmap, alpha=0.9)
+# plt.imshow(Z, extent=[x.min(), x.max(), y.min(), y.max()],origin='lower', norm = divnorm,
+#                   cmap=cmap, alpha=0.6)
+
+
+# I = plt.imshow(Z, extent=[x.min(), x.max(), y.min(), y.max()],origin='lower',
+                  # cmap=cmap, alpha=0.6)
+
+
+# I = plt.imshow(Z, extent=[x.min(), x.max(), y.min(), y.max()],origin='lower', norm = mcolors.CenteredNorm(),
+#                   cmap=cmap, alpha=0.6)
+
+
+
+# COLORBAR :
+# cbar = plt.colorbar()
+# cbar.ax.tick_params(labelsize=f_size)
+# fig.colorbar(I)
+
+
+
+##----- ADD RECTANGLE TO COVER QUADRANT :
+# epsilon = 0.4
+epsilon = 0.001
+# ax.axvspan(0, x.max(), y.min(), 0, alpha=1, color='yellow', zorder=5)#yellow
+# ax.fill_between([0, x.max()], y.min(), 0, alpha=0.3, color='yellow', zorder=5)#yellow
+# ax.fill_between([x.min(), 0], 0, y.max(), alpha=0.3, color='yellow', zorder=5)#yellow
+
+fillcolor = 'royalblue'
+# ax.fill_between([0+epsilon, x.max()], y.min(), 0-epsilon, alpha=0.7, color=fillcolor, zorder=4)#yellow
+# ax.fill_between([x.min(), 0-epsilon], 0+epsilon, y.max(), alpha=0.7, color=fillcolor, zorder=4)#yellow
+# ax.fill_between([0+epsilon, x.max()], y.min(), 0-epsilon, alpha=1.0, color=fillcolor, zorder=4)#yellow
+# ax.fill_between([x.min(), 0-epsilon], 0+epsilon, y.max(), alpha=1.0, color=fillcolor, zorder=4)#yellow
+
+
+## FILL
+ax.fill_between([x.min(), 0-epsilon], y.min(), 0-epsilon, alpha=.25, color=fillcolor, zorder=4)#yellow
+ax.fill_between([0+epsilon, x.max()], 0+epsilon, y.max(), alpha=.25, color=fillcolor, zorder=4)#yellow
+
+
+ax.text(1,1, r"$\mathcal{G}^+_{\mathbf{R}^2}$", color='royalblue', size=15)
+
+# ax.text(0.25,0.25, r"$\mathcal{S}$", color='darkorange', size=15)
+
+# PLOT 1-PARAMETER FAMILY
+
+print('abar:', abar)
+print('abar[0,:]:', abar[0,:])
+print('abar[1,:]:', abar[1,:])
+
+line = ax.plot(abar[:,0],abar[:,1], linewidth=2, color='darkorange', linestyle='-', zorder=4)
+
+# plt.arrow(x=1, y=0, dx=0.5, dy=0, )
+# ax.arrow(1, 0, 0.5, 0, head_width=0.05, head_length=0.1, fc='k', ec='k', zorder=5)
+# plt.arrow(1, 0, 0.8, 0,  shape='full', lw=0, length_includes_head=True, head_width=.15, zorder=5, color='purple')
+
+
+## PLOT ARROW:
+# plt.arrow(1, 0, 0.5, 0,  shape='full', lw=0, length_includes_head=True, head_width=.20, zorder=5, color='darkorange')
+# plt.arrow(0, 1.8, 0, -0.8,  shape='full', lw=0, length_includes_head=True, head_width=.20, zorder=5, color='darkorange')
+
+
+# plt.arrow(0, 1.8, 0, -0.8, lw=0,  head_width=.12, zorder=5, color='darkorange')
+# plt.arrow(0, 2, 0, -0.5,  shape='full', lw=0, length_includes_head=True, head_width=.12, zorder=5, color='darkorange')
+# add_arrow(line, color='darkorange')
+
+
+
+
+# ax.plot_surface(a1,a2, Z, cmap=cm.coolwarm,
+#                        linewidth=0, antialiased=False)
+
+
+
+# ax.plot(theta_rho, energy_axial1, 'royalblue', zorder=3, label=r"axialMin1")
+# ax.plot(theta_rho, energy_axial2, 'forestgreen', zorder=3, label=r"axialMin2")
+# ax.plot(-1.0*alphas, kappas, 'red', zorder=3, )
+
+
+# print('test:',test)
+# ax.scatter(test[0],test[1])
+# ax.arrow(test[0],test[1],abarperp[0],abarperp[1])
+
+# lg = ax.legend(bbox_to_anchor=(0.0, 0.75), loc='upper left')
+
+
+
+### PLot x and y- Axes
+ax.plot(ax.get_xlim(),[0,0],'k--', linewidth=0.5)
+ax.plot([0,0],ax.get_ylim(), 'k--', linewidth=0.5)
+
+
+
+ax.set_xlabel(r"$a_1$", fontsize=f_size ,labelpad=0)
+ax.set_ylabel(r"$a_2$", fontsize=f_size ,labelpad=0)
+# ax.set_ylabel(r"energy")
+ax.tick_params(axis='both', which='major', labelsize=f_size)
+ax.tick_params(axis='both', which='minor', labelsize=f_size)
+
+
+
+# ax.set_xticks([-np.pi/2, -np.pi/4  ,0,  np.pi/4,  np.pi/2 ])
+# labels = ['$0$',r'$\pi/8$', r'$\pi/4$' ,r'$3\pi/8$' , r'$\pi/2$']
+# ax.set_yticklabels(labels)
+
+print('x.max()',x.max())
+print('y.max()',y.max())
+ax.set_xlim(x.min(),x.max())
+ax.set_xlim(y.min(),y.max())
+
+
+
+# ax.legend(loc='upper right')
+
+
+
+fig.set_size_inches(width, height)
+# fig.set_size_inches(set_size(width, fraction=0.33))
+fig.savefig('Energy_ContourG+_Flat.pdf')
+
+plt.show()
+
+
+#
+#
+#
+# # Curve parametrised by \theta_rho = alpha in parameter space
+# N=100;
+# theta_rho = np.linspace(1, 3, num=N)
+# print('theta_rho:', theta_rho)
+#
+#
+# theta_values = []
+#
+#
+# for t in theta_rho:
+#
+#         s = (1.0/10.0)*t+0.1
+#         theta_values.append(s)
+#
+#
+#
+#
+#
+# theta_rho = np.array(theta_rho)
+# theta_values = np.array(theta_values)
+#
+# betas_ = 2.0
+#
+
+# alphas, betas, thetas = np.meshgrid(theta_rho, betas_, theta_values, indexing='ij')
+#
+#
+# harmonicMeanVec = np.vectorize(harmonicMean)
+# arithmeticMeanVec = np.vectorize(arithmeticMean)
+# prestrain_b1Vec = np.vectorize(prestrain_b1)
+# prestrain_b2Vec = np.vectorize(prestrain_b2)
+#
+# GetMuGammaVec = np.vectorize(GetMuGamma)
+# muGammas = GetMuGammaVec(betas,thetas,gamma,mu1,rho1,InputFilePath ,OutputFilePath )
+#
+# q1_vec = harmonicMeanVec(mu1, betas, thetas)
+# q2_vec = arithmeticMeanVec(mu1, betas, thetas)
+#
+# b1_vec = prestrain_b1Vec(rho1, betas, alphas, thetas)
+# b2_vec = prestrain_b2Vec(rho1, betas, alphas, thetas)
+
+# special case: q12 == 0!! .. braucht eigentlich nur b1 & b2 ...
+
+# print('type b1_values:', type(b1_values))
+
+
+
+# print('size(q1)',q1.shape)
+#
+#
+# energy_axial1 = []
+# energy_axial2 = []
+#
+# # for b1 in b1_values:
+# for i in range(len(theta_rho)):
+#     print('index i:', i)
+#
+#     print('theta_rho[i]',theta_rho[i])
+#     print('theta_values[i]',theta_values[i])
+#
+#     q1 = (1.0/6.0)*harmonicMean(mu1, beta, theta_values[i])
+#     q2 = (1.0/6.0)*arithmeticMean(mu1, beta, theta_values[i])
+#     q12 = 0.0
+#     q3 = GetMuGamma(beta, theta_values[i],gamma,mu1,rho1,InputFilePath ,OutputFilePath )
+#     b1 = prestrain_b1(rho1,beta, theta_rho[i],theta_values[i] )
+#     b2 = prestrain_b2(rho1,beta, theta_rho[i],theta_values[i] )
+#
+#
+#     # q2_vec = arithmeticMean(mu1, betas, thetas)
+#     #
+#     # b1_vec = prestrain_b1Vec(rho1, betas, alphas, thetas)
+#     # b2_vec = prestrain_b2Vec(rho1, betas, alphas, thetas)
+#     print('q1[i]',q1)
+#     print('q2[i]',q2)
+#     print('q3[i]',q3)
+#     print('b1[i]',b1)
+#     print('b2[i]',b2)
+#     # print('q1[i]',q1[0][i])
+#     # print('q2[i]',q2[i])
+#     # print('b1[i]',b1[i])
+#     # print('b2[i]',b2[i])
+#     #compute axial energy #1 ...
+#
+#     a_axial1 = np.array([b1,0])
+#     a_axial2 = np.array([0,b2])
+#     b = np.array([b1,b2])
+#
+#     H = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+#     A = np.array([[q1,1/2*q12], [1/2*q12,q2] ])
+#
+#
+#     tmp = H.dot(a_axial1)
+#
+#     print('H',H)
+#     print('A',A)
+#     print('b',b)
+#     print('a_axial1',a_axial1)
+#     print('tmp',tmp)
+#
+#     tmp = (1/2)*a_axial1.dot(tmp)
+#     print('tmp',tmp)
+#
+#     tmp2 = A.dot(b)
+#     print('tmp2',tmp2)
+#     tmp2 = 2*a_axial1.dot(tmp2)
+#
+#     print('tmp2',tmp2)
+#     energy_1 = tmp - tmp2
+#     print('energy_1',energy_1)
+#
+#
+#     energy_axial1.append(energy_1)
+#
+#
+#     tmp = H.dot(a_axial2)
+#
+#     print('H',H)
+#     print('A',A)
+#     print('b',b)
+#     print('a_axial2',a_axial2)
+#     print('tmp',tmp)
+#
+#     tmp = (1/2)*a_axial2.dot(tmp)
+#     print('tmp',tmp)
+#
+#     tmp2 = A.dot(b)
+#     print('tmp2',tmp2)
+#     tmp2 = 2*a_axial2.dot(tmp2)
+#
+#     print('tmp2',tmp2)
+#     energy_2 = tmp - tmp2
+#     print('energy_2',energy_2)
+#
+#
+#     energy_axial2.append(energy_2)
+#
+#
+#
+#
+#
+# print('theta_values', theta_values)
+#
+#
+#
+
+
+#
+#
+#
+#
+# kappas = []
+# alphas = []
+# # G.append(float(s[0]))
+#
+#
+#
+#
+# for t in T :
+#
+#     abar_current = sstar*abar+t*abarperp;
+#     # print('abar_current', abar_current)
+#     abar_current[abar_current < 1e-10] = 0
+#     # print('abar_current', abar_current)
+#
+#     # G = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+#     G = [abar_current[0], abar_current[1] , (2*abar_current[0]*abar_current[1])**0.5 ]
+#
+#     e = [(abar_current[0]/(abar_current[0]+abar_current[1]))**0.5, (abar_current[1]/(abar_current[0]+abar_current[1]))**0.5]
+#     kappa = abar_current[0]+abar_current[1]
+#     alpha = math.atan2(e[1], e[0])
+#
+#     print('angle current:', alpha)
+#
+#     kappas.append(kappa)
+#     alphas.append(alpha)
+#
+#
+#
+# alphas = np.array(alphas)
+# kappas = np.array(kappas)
+#
+#
+# print('kappas:',kappas)
+# print('alphas:',alphas)
+# print('min alpha:', min(alphas))
+# print('min kappa:', min(kappas))
+#
+# mpl.rcParams['text.usetex'] = True
+# mpl.rcParams["font.family"] = "serif"
+# mpl.rcParams["font.size"] = "9"
+# width = 6.28 *0.5
+# height = width / 1.618
+# fig = plt.figure()
+# # ax = plt.axes((0.15,0.21 ,0.75,0.75))
+# ax = plt.axes((0.15,0.21 ,0.8,0.75))
+# ax.tick_params(axis='x',which='major', direction='out',pad=5)
+# ax.tick_params(axis='y',which='major', length=3, width=1, direction='out',pad=3)
+# # ax.xaxis.set_major_locator(MultipleLocator(0.1))
+# # ax.xaxis.set_minor_locator(MultipleLocator(0.05))
+# # ax.xaxis.set_major_locator(plt.MultipleLocator(np.pi / 8))
+# # ax.xaxis.set_minor_locator(plt.MultipleLocator(np.pi / 16))
+# ax.xaxis.set_major_locator(plt.MultipleLocator(np.pi / 2))
+# ax.xaxis.set_minor_locator(plt.MultipleLocator(np.pi / 4))
+# ax.xaxis.set_major_formatter(plt.FuncFormatter(format_func))
+# ax.grid(True,which='major',axis='both',alpha=0.3)
+#
+#
+#
+#
+# ax.plot(alphas, kappas, 'royalblue', zorder=3, )
+# ax.plot(-1.0*alphas, kappas, 'red', zorder=3, )

Python-Scripts/1-ParameterFamily_G+_Flat_v2.py

+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
+
+import matplotlib as mpl
+from matplotlib.ticker import MultipleLocator,FormatStrFormatter,MaxNLocator
+import pandas as pd
+
+import seaborn as sns
+import matplotlib.colors as mcolors
+
+from chart_studio import plotly
+import plotly.graph_objs as go
+import plotly.express as px
+import plotly.colors
+# from matplotlib import rc
+# rc('text', usetex=True) # Use LaTeX font
+#
+# import seaborn as sns
+# sns.set(color_codes=True)
+
+
+def show(fig):
+    import io
+    import plotly.io as pio
+    from PIL import Image
+    buf = io.BytesIO()
+    pio.write_image(fig, buf)
+    img = Image.open(buf)
+    img.show()
+
+
+
+
+def add_arrow(line, position=None, direction='right', size=15, color=None):
+    """
+    add an arrow to a line.
+
+    line:       Line2D object
+    position:   x-position of the arrow. If None, mean of xdata is taken
+    direction:  'left' or 'right'
+    size:       size of the arrow in fontsize points
+    color:      if None, line color is taken.
+    """
+    if color is None:
+        color = line.get_color()
+
+    xdata = line.get_xdata()
+    ydata = line.get_ydata()
+
+    if position is None:
+        position = xdata.mean()
+    # find closest index
+    start_ind = np.argmin(np.absolute(xdata - position))
+    if direction == 'right':
+        end_ind = start_ind + 1
+    else:
+        end_ind = start_ind - 1
+
+    line.axes.annotate('',
+        xytext=(xdata[start_ind], ydata[start_ind]),
+        xy=(xdata[end_ind], ydata[end_ind]),
+        arrowprops=dict(arrowstyle="->", color=color),
+        size=size
+    )
+
+
+# set the colormap and centre the colorbar
+class MidpointNormalize(mcolors.Normalize):
+	"""
+	Normalise the colorbar so that diverging bars work there way either side from a prescribed midpoint value)
+
+	e.g. im=ax1.imshow(array, norm=MidpointNormalize(midpoint=0.,vmin=-100, vmax=100))
+	"""
+	def __init__(self, vmin=None, vmax=None, midpoint=None, clip=False):
+		self.midpoint = midpoint
+		mcolors.Normalize.__init__(self, vmin, vmax, clip)
+
+	def __call__(self, value, clip=None):
+		# I'm ignoring masked values and all kinds of edge cases to make a
+		# simple example...
+		x, y = [self.vmin, self.midpoint, self.vmax], [0, 0.5, 1]
+		return np.ma.masked_array(np.interp(value, x, y), np.isnan(value))
+
+
+
+def set_size(width, fraction=1):
+    """Set figure dimensions to avoid scaling in LaTeX.
+
+    Parameters
+    ----------
+    width: float
+            Document textwidth or columnwidth in pts
+    fraction: float, optional
+            Fraction of the width which you wish the figure to occupy
+
+    Returns
+    -------
+    fig_dim: tuple
+            Dimensions of figure in inches
+    """
+    # Width of figure (in pts)
+    fig_width_pt = width * fraction
+
+    # Convert from pt to inches
+    inches_per_pt = 1 / 72.27
+
+    # Golden ratio to set aesthetic figure height
+    # https://disq.us/p/2940ij3
+    golden_ratio = (5**.5 - 1) / 2
+
+    # Figure width in inches
+    fig_width_in = fig_width_pt * inches_per_pt
+    # Figure height in inches
+    fig_height_in = fig_width_in * golden_ratio
+
+    fig_dim = (fig_width_in, fig_height_in)
+
+    return fig_dim
+
+
+
+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 == -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)
+    ##find number of multiples of pi/2
+    N = int(np.round(4 * value / np.pi))
+    if N == 0:
+        return "0"
+    elif N == 1:
+        return r"$\pi/4$"
+    elif N == -1:
+        return r"$-\pi/4$"
+    elif N == 2:
+        return r"$\pi/2$"
+    elif N == -2:
+        return r"$-\pi/2$"
+    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
+
+
+
+def energy(a1,a2,q1,q2,q12,q3,b1,b2):
+
+
+    a = np.array([a1,a2])
+    b = np.array([b1,b2])
+    H = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+    A = np.array([[q1,1/2*q12], [1/2*q12,q2] ])
+
+
+    tmp = H.dot(a)
+
+    # print('H',H)
+    # print('A',A)
+    # print('b',b)
+    # print('a',a)
+    # print('tmp',tmp)
+
+    tmp = (1/2)*a.dot(tmp)
+    # print('tmp',tmp)
+
+    tmp2 = A.dot(b)
+    # print('tmp2',tmp2)
+    tmp2 = 2*a.dot(tmp2)
+
+    # print('tmp2',tmp2)
+    energy = tmp - tmp2
+    # print('energy',energy)
+
+
+    # energy_axial1.append(energy_1)
+
+    return energy
+
+
+
+# def energy(a1,a2,q1,q2,q12,q3,b1,b2):
+#
+#
+#     b = np.array([b1,b2])
+#     H = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+#     A = np.array([[q1,1/2*q12], [1/2*q12,q2] ])
+#
+#
+#     tmp = H.dot(a)
+#
+#     print('H',H)
+#     print('A',A)
+#     print('b',b)
+#     print('a',a)
+#     print('tmp',tmp)
+#
+#     tmp = (1/2)*a.dot(tmp)
+#     print('tmp',tmp)
+#
+#     tmp2 = A.dot(b)
+#     print('tmp2',tmp2)
+#     tmp2 = 2*a.dot(tmp2)
+#
+#     print('tmp2',tmp2)
+#     energy = tmp - tmp2
+#     print('energy',energy)
+#
+#
+#     # energy_axial1.append(energy_1)
+#
+#     return energy
+#
+
+
+
+
+
+################################################################################################################
+################################################################################################################
+################################################################################################################
+
+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: -----')
+
+# q1=1;
+# q2=2;
+# q12=1/2;
+# q3=((4*q1*q2)**0.5-q12)/2;
+# # H=[2*q1,q12+2*q3;q12+2*q3,2*q2];
+#
+# H = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+# A = np.array([[q1,1/2*q12], [1/2*q12,q2] ])
+# abar = np.array([q12+2*q3, 2*q2])
+# abar = (1.0/math.sqrt((q12+2*q3)**2+(2*q2)**2))*abar
+#
+# print('abar:',abar)
+#
+# b = np.linalg.lstsq(A, abar)[0]
+# print('b',b)
+#
+#
+# # print('abar:',np.shape(abar))
+# # print('np.transpose(abar):',np.shape(np.transpose(abar)))
+# sstar = (1/(q1+q2))*abar.dot(A.dot(b))
+# # sstar = (1/(q1+q2))*abar.dot(tmp)
+# print('sstar', sstar)
+# abarperp= np.array([abar[1],-abar[0]])
+# print('abarperp:',abarperp)
+
+
+# -------------------------- Input Parameters --------------------
+
+mu1 = 1.0
+rho1 = 1.0
+alpha = 5.0
+theta = 1.0/2
+# theta= 0.1
+beta = 5.0
+
+
+
+
+# mu1 = 1.0
+# rho1 = 1.0
+# alpha = -0.75
+# theta = 1.0/2
+# # theta= 0.1
+# beta = 5.0
+
+
+# mu1 = 1.0
+# rho1 = 1.0
+# alpha = 2.0
+# theta = 1.0/2
+# # theta= 0.1
+# beta = 5.0
+
+
+#Figure3:
+# mu1 = 1.0
+# rho1 = 1.0
+# alpha = 2.0
+# theta = 1.0/8
+# # theta= 0.1
+# beta = 2.0
+
+
+# alpha= -5
+
+
+#set gamma either to 1. '0' 2. 'infinity' or 3. a numerical positive value
+gamma = '0'
+# gamma = 'infinity'
+
+
+lambda1 = 0.0
+
+
+print('---- Input parameters: -----')
+print('mu1: ', mu1)
+print('rho1: ', rho1)
+# print('alpha: ', alpha)
+print('beta: ', beta)
+# print('theta: ', theta)
+print('gamma:', gamma)
+
+print('lambda1: ', lambda1)
+print('----------------------------')
+# ----------------------------------------------------------------
+print('----------------------------')
+
+# ----------------------------------------------------------------
+
+
+
+
+
+
+q1 = (1.0/6.0)*harmonicMean(mu1, beta, theta)
+q2 = (1.0/6.0)*arithmeticMean(mu1, beta, theta)
+q12 = 0.0
+q3 = GetMuGamma(beta, theta,gamma,mu1,rho1,InputFilePath ,OutputFilePath )
+b1 = prestrain_b1(rho1,beta, alpha, theta )
+b2 = prestrain_b2(rho1,beta, alpha, theta )
+
+
+## ---- 1-ParameterFamilyCase:
+# q1=1;
+# q2=2;
+# q12=1/2;
+# q3=((4*q1*q2)**0.5-q12)/2;
+# # H=[2*q1,q12+2*q3;q12+2*q3,2*q2];
+# H = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+# A = np.array([[q1,1/2*q12], [1/2*q12,q2] ])
+# abar = np.array([q12+2*q3, 2*q2])
+# abar = (1.0/math.sqrt((q12+2*q3)**2+(2*q2)**2))*abar
+# print('abar:',abar)
+# b = np.linalg.lstsq(A, abar)[0]
+# print('b',b)
+# b1=b[0]
+# b2=b[1]
+## ---------------
+
+
+
+
+
+########################################
+
+# 1-ParameterFamilyCase:
+
+q1=1;
+q2=2;
+q12=1/2;
+q3=((4*q1*q2)**0.5-q12)/2;
+# H=[2*q1,q12+2*q3;q12+2*q3,2*q2];
+
+H = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+A = np.array([[q1,1/2*q12], [1/2*q12,q2] ])
+abar = np.array([q12+2*q3, 2*q2])
+abar = (1.0/math.sqrt((q12+2*q3)**2+(2*q2)**2))*abar
+
+print('abar:',abar)
+
+b = np.linalg.lstsq(A, abar)[0]
+print('b',b)
+
+b1=b[0]
+b2=b[1]
+
+
+##----------------------
+print('q1 = ', q1)
+print('q2 = ', q2)
+print('q3 = ', q3)
+print('q12 = ', q12)
+print('b1 = ', b1)
+print('b2 = ', b2)
+##--------------
+
+
+# print('abar:',np.shape(abar))
+# print('np.transpose(abar):',np.shape(np.transpose(abar)))
+sstar = (1/(q1+q2))*abar.dot(A.dot(b))
+# sstar = (1/(q1+q2))*abar.dot(tmp)
+print('sstar', sstar)
+abarperp= np.array([abar[1],-abar[0]])
+print('abarperp:',abarperp)
+
+print('sstar*abar:', sstar*abar)
+# print('np.dot(sstar*abar):', np.dot(sstar*abar))
+print('----------------------------')
+
+
+N=1000;
+N=10;
+scale_domain = 5
+translate_startpoint = -1.8
+T_line = np.linspace(-sstar*(q12+2*q3)/(2*q2)*scale_domain + translate_startpoint, sstar*(2*q2)/(q12+2*q3)*scale_domain , num=N)
+line_values = []
+for t in T_line :
+    print('sstar*abar+t*abarperp', sstar*abar+t*abarperp)
+    line_values.append(sstar*abar+t*abarperp)
+
+
+
+
+T = np.linspace(-sstar*(q12+2*q3)/(2*q2), sstar*(2*q2)/(q12+2*q3), num=N)
+
+# T = np.linspace(-2,2, num=N)
+# print('T:', T)
+
+print('T.min():', T.min())
+print('T.max():', T.max())
+
+kappas = []
+alphas = []
+# G.append(float(s[0]))
+
+G_container = []
+abar_container = []
+
+test = sstar*abar
+
+
+abar_tmp = abar
+
+for t in T :
+    abar_current = sstar*abar+t*abarperp;
+    abar_current[abar_current < 1e-10] = 0   # Projection onto x-y-axis!!
+    print('abar_current', abar_current)
+    G = [abar_current[0], abar_current[1] , (2*abar_current[0]*abar_current[1])**0.5 ]
+    G_container.append(G)
+    abar_container.append(abar_current)
+    e = [(abar_current[0]/(abar_current[0]+abar_current[1]))**0.5, (abar_current[1]/(abar_current[0]+abar_current[1]))**0.5]
+    kappa = abar_current[0]+abar_current[1]
+    alpha = math.atan2(e[1], e[0])
+	# print('angle current:', alpha)
+    kappas.append(kappa)
+    alphas.append(alpha)
+
+
+alphas = np.array(alphas)
+kappas = np.array(kappas)
+
+# print('G_container', G_container)
+G = np.array(G_container)
+abar = np.array(abar_container)
+
+print('G', G)
+print('abar', abar)
+print('abar.shape',abar.shape)
+
+
+
+
+
+
+
+
+
+
+######################################
+
+
+
+num_Points = 400
+num_Points = 200
+# num_Points = 20
+
+
+# Creating dataset
+x = np.linspace(-5,5,num_Points)
+y = np.linspace(-5,5,num_Points)
+
+x = np.linspace(-20,20,num_Points)
+y = np.linspace(-20,20,num_Points)
+
+
+x = np.linspace(-2,2,num_Points)
+y = np.linspace(-2,2,num_Points)
+
+# x = np.linspace(-10,10,num_Points)
+# y = np.linspace(-10,10,num_Points)
+
+# x = np.linspace(-60,60,num_Points)
+# y = np.linspace(-60,60,num_Points)
+#
+#
+# x = np.linspace(-40,40,num_Points)
+# y = np.linspace(-40,40,num_Points)
+
+
+a1, a2 = np.meshgrid(x,y)
+
+# geyser = sns.load_dataset("geyser")
+# print('type of geyser:', type(geyser))
+# print('geyser:',geyser)
+
+ContourRange=20
+
+x_in = np.linspace(-ContourRange,ContourRange,num_Points)
+y_in = np.linspace(-ContourRange,ContourRange,num_Points)
+a1_in, a2_in = np.meshgrid(x_in,y_in)
+
+print('a1:', a1)
+print('a2:',a2 )
+
+print('a1.shape', a1.shape)
+
+#-- FILTER OUT VALUES for G+ :
+
+# tmp1 = a1[np.where(a1*a2 >= 0)]
+# tmp2 = a2[np.where(a1*a2 >= 0)]
+#
+# np.take(a, np.where(a>100)[0], axis=0)
+# tmp1 = np.take(a1, np.where(a1*a2 >= 0)[0], axis=0)
+# tmp2 = np.take(a1, np.where(a1*a2 >= 0)[0], axis=0)
+# tmp2 = a2[np.where(a1*a2 >= 0)]
+
+tmp1 = a1[a1*a2 >= 0]
+tmp2 = a2[a1*a2 >= 0]
+tmp1 = tmp1.reshape(-1,5)
+tmp2 = tmp2.reshape(-1,5)
+
+
+# tmp1_pos = a1[np.where(a1*a2 >= 0) ]
+# tmp2_pos = a2[np.where(a1*a2 >= 0) ]
+# tmp1_pos = tmp1_pos[np.where(tmp1_pos  >= 0)]
+# tmp2_pos = tmp2_pos[np.where(tmp2_pos  >= 0)]
+#
+# tmp1_neg = a1[a1*a2 >= 0 ]
+# tmp2_neg = a2[a1*a2 >= 0 ]
+# tmp1_neg = tmp1_neg[tmp1_neg  < 0]
+# tmp2_neg = tmp2_neg[tmp2_neg  < 0]
+# a1 = tmp1
+# a2 = tmp2
+#
+# a1 = a1.reshape(-1,5)
+# a2 = a2.reshape(-1,5)
+#
+# tmp1_pos = tmp1_pos.reshape(-1,5)
+# tmp2_pos = tmp2_pos.reshape(-1,5)
+# tmp1_neg = tmp1_neg.reshape(-1,5)
+# tmp2_neg = tmp2_neg.reshape(-1,5)
+
+
+print('a1:', a1)
+print('a2:',a2 )
+print('a1.shape', a1.shape)
+
+
+
+
+
+energyVec = np.vectorize(energy)
+
+# Z = energyVec(np.array([a1,a2]),q1,q2,q12,q3,b1,b2)
+Z = energyVec(a1,a2,q1,q2,q12,q3,b1,b2)
+
+Z_in = energyVec(a1_in,a2_in,q1,q2,q12,q3,b1,b2)
+
+
+
+
+print('Z:', Z)
+
+print('any', np.any(Z<0))
+
+#
+
+
+# negZ_a1 = a1[np.where(Z<0)]
+# negZ_a2 = a2[np.where(Z<0)]
+# negativeValues = Z[np.where(Z<0)]
+# print('negativeValues:',negativeValues)
+#
+# print('negZ_a1',negZ_a1)
+# print('negZ_a2',negZ_a2)
+#
+#
+# negZ_a1 = negZ_a1.reshape(-1,5)
+# negZ_a2 = negZ_a2.reshape(-1,5)
+# negativeValues = negativeValues.reshape(-1,5)
+#
+# Z_pos =  energyVec(tmp1_pos,tmp2_pos,q1,q2,q12,q3,b1,b2)
+# Z_neg = energyVec(tmp1_neg,tmp2_neg,q1,q2,q12,q3,b1,b2)
+
+
+
+
+
+# print('Test energy:' , energy(np.array([1,1]),q1,q2,q12,q3,b1,b2))
+
+
+
+
+# print('Z_pos.shape', Z_pos.shape)
+
+
+
+
+
+
+
+## -- PLOT :
+# mpl.rcParams['text.usetex'] = True
+# mpl.rcParams["font.family"] = "serif"
+# mpl.rcParams["font.size"] = "9"
+#
+# label_size = 8
+# mpl.rcParams['xtick.labelsize'] = label_size
+# mpl.rcParams['ytick.labelsize'] = label_size
+#
+# plt.style.use('seaborn')
+# # plt.style.use('seaborn-whitegrid')
+# # sns.set()
+# # plt.style.use('seaborn-whitegrid')
+#
+# label_size = 9
+# mpl.rcParams['xtick.labelsize'] = label_size
+# mpl.rcParams['ytick.labelsize'] = label_size
+
+# # plt.style.use("seaborn-darkgrid")
+# plt.style.use("seaborn-whitegrid")
+plt.style.use("seaborn")
+# plt.style.use("seaborn-paper")
+# plt.style.use('ggplot')
+# plt.rcParams["font.family"] = "Avenir"
+# plt.rcParams["font.size"] = 16
+
+# plt.style.use("seaborn-darkgrid")
+mpl.rcParams['text.usetex'] = True
+mpl.rcParams["font.family"] = "serif"
+mpl.rcParams["font.size"] = "10"
+# mpl.rcParams['xtick.labelsize'] = 16mpl.rcParams['xtick.major.size'] = 2.5
+# mpl.rcParams['xtick.bottom'] = True
+# mpl.rcParams['ticks'] = True
+mpl.rcParams['xtick.bottom'] = True
+mpl.rcParams['xtick.major.size'] = 3
+mpl.rcParams['xtick.minor.size'] = 1.5
+mpl.rcParams['xtick.major.width'] = 0.75
+mpl.rcParams['ytick.left'] = True
+mpl.rcParams['ytick.major.size'] = 3
+mpl.rcParams['ytick.minor.size'] = 1.5
+mpl.rcParams['ytick.major.width'] = 0.75
+
+mpl.rcParams.update({'font.size': 10})
+mpl.rcParams['axes.labelpad'] = 3.0
+
+width = 6.28 *0.5
+# width = 6.28 *0.33
+# width = 6.28
+height = width #/ 1.618
+
+# width = 452.9579/2
+# size= set_size(width, fraction=0.5)
+# print('set_size(width, fraction=0.5)', set_size(width, fraction=1))
+# print('size[0]',size[0])
+
+f_size = 10
+# fig= plt.figure()
+fig, ax = plt.subplots()
+# fig.set_size_inches(width, height)
+# fig.set_size_inches(set_size(width, fraction=0.5))
+# ax = plt.axes(projection ='3d', adjustable='box')
+# ax = plt.axes((0.17,0.21 ,0.75,0.75))
+
+# ax = plt.axes((0.17,0.23 ,0.7,0.7))
+# ax = plt.axes((0.17,0.23 ,1.0,1.0))
+# ax=plt.axes()
+# ax = plt.axes((0.15,0.18,0.8,0.8))
+# ax.tick_params(axis='x',which='major', direction='out',pad=5)
+# ax.tick_params(axis='y',which='major', length=3, width=1, direction='out',pad=3)
+# ax.xaxis.set_major_locator(MultipleLocator(0.1))
+# ax.xaxis.set_minor_locator(MultipleLocator(0.05))
+# ax.xaxis.set_major_locator(plt.MultipleLocator(np.pi / 8))
+# ax.xaxis.set_minor_locator(plt.MultipleLocator(np.pi / 16))
+# ax.xaxis.set_major_locator(plt.MultipleLocator(np.pi / 2))
+# ax.xaxis.set_minor_locator(plt.MultipleLocator(np.pi / 4))
+# ax.xaxis.set_major_formatter(plt.FuncFormatter(format_func))
+ax.grid(True,which='major',axis='both',alpha=0.3)
+
+# Substract constant:
+# c = (b1**2)*q1+b1*b2*q12+(b2**2)*q2
+# Z = Z-c
+#
+# print('Value of c:', c)
+
+
+
+print('Z.min()', Z.min())
+print('Z.max()', Z.max())
+norm=mcolors.Normalize(Z.min(),Z.max())
+# facecolors=cm.brg(norm)
+
+
+
+
+cmap=mpl.cm.RdBu_r
+cmap=mpl.cm.viridis_r
+# cmap=mpl.cm.bwr
+cmap=mpl.cm.coolwarm
+# cmap=mpl.cm.gnuplot
+cmap=mpl.cm.magma_r
+# cmap=mpl.cm.inferno_r
+# cmap=mpl.cm.plasma
+# cmap=mpl.cm.plasma_r
+# cmap=mpl.cm.cividis_r
+# cmap = mpl.colors.LinearSegmentedColormap.from_list("", ["blue","violet","red"])
+# cmap = mpl.colors.LinearSegmentedColormap.from_list("", ["blue","orange"])
+
+# cmap = mpl.colors.LinearSegmentedColormap.from_list("", [(0,"red"), (.1,"violet"), (.5, "blue"), (1.0, "green")])
+# make a colormap that has land and ocean clearly delineated and of the
+# same length (256 + 256)
+#
+# colors_undersea = plt.cm.terrain(np.linspace(0, 0.17, 256))
+# colors_land = plt.cm.terrain(np.linspace(0.25, 1, 256))
+# all_colors = np.vstack((colors_undersea, colors_land))
+# # cmap = mcolors.LinearSegmentedColormap.from_list(
+# #     'terrain_map', all_colors)
+
+
+# cmap = px.colors.sequential.agsunset
+# cmap = plotly.colors.PLOTLY_SCALES["Viridis"]
+
+
+
+
+# cmap = cm.brg(Z)
+divnorm=mcolors.TwoSlopeNorm(vmin=Z.min(), vcenter=0., vmax=Z.max())
+divnorm=mcolors.TwoSlopeNorm(vmin=Z.min(), vcenter=(Z.max()+Z.min())/2, vmax=Z.max())
+# divnorm=mcolors.TwoSlopeNorm(vmin=-500, vcenter=0, vmax=Z.max())
+
+# divnorm=mcolors.TwoSlopeNorm(vmin=-10, vcenter=0. ,vmax=10)
+# divnorm=mcolors.TwoSlopeNorm(vmin=-10, vcenter=0., vmax=Z.max())
+
+# divnorm=mcolors.LogNorm(vmin=Z.min(),  vmax=Z.max())  #Test LogNorm
+
+# cmap = cm.brg(divnorm(Z))
+
+# ax.imshow(Z, extent=[-20, 20, -20, 20],origin='lower', norm = norm,
+#                   cmap='coolwarm', alpha=0.6)
+
+# ax.imshow(Z, extent=[-20, 20, -20, 20],origin='lower',
+#                   cmap='coolwarm', alpha=0.6)
+# ax.imshow(Z, extent=[-20, 20, -20, 20],origin='lower',
+#                   cmap=cmap, alpha=0.6)
+
+# divnorm=mcolors.TwoSlopeNorm(vmin=Z.min(), vcenter=0., vmax=Z.max())
+# plt.imshow(Z, extent=[x.min(), x.max(), y.min(), y.max()],origin='lower',
+#                   cmap=cmap, alpha=0.6)
+
+# I = plt.imshow(Z, extent=[x.min(), x.max(), y.min(), y.max()],origin='lower', norm = divnorm,
+#                   cmap=cmap, alpha=0.6)
+# plt.imshow(Z, extent=[x.min(), x.max(), y.min(), y.max()],origin='lower', norm = divnorm,
+#                   cmap=cmap, alpha=0.9)
+# plt.imshow(Z, extent=[x.min(), x.max(), y.min(), y.max()],origin='lower', norm = divnorm,
+#                   cmap=cmap, alpha=0.6)
+
+
+# I = plt.imshow(Z, extent=[x.min(), x.max(), y.min(), y.max()],origin='lower',
+                  # cmap=cmap, alpha=0.6)
+
+
+# I = plt.imshow(Z, extent=[x.min(), x.max(), y.min(), y.max()],origin='lower', norm = mcolors.CenteredNorm(),
+#                   cmap=cmap, alpha=0.6)
+
+
+
+# COLORBAR :
+# cbar = plt.colorbar()
+# cbar.ax.tick_params(labelsize=f_size)
+# fig.colorbar(I)
+
+
+
+##----- ADD RECTANGLE TO COVER QUADRANT :
+# epsilon = 0.4
+epsilon = 0.001
+# ax.axvspan(0, x.max(), y.min(), 0, alpha=1, color='yellow', zorder=5)#yellow
+# ax.fill_between([0, x.max()], y.min(), 0, alpha=0.3, color='yellow', zorder=5)#yellow
+# ax.fill_between([x.min(), 0], 0, y.max(), alpha=0.3, color='yellow', zorder=5)#yellow
+
+fillcolor = 'royalblue'
+# ax.fill_between([0+epsilon, x.max()], y.min(), 0-epsilon, alpha=0.7, color=fillcolor, zorder=4)#yellow
+# ax.fill_between([x.min(), 0-epsilon], 0+epsilon, y.max(), alpha=0.7, color=fillcolor, zorder=4)#yellow
+# ax.fill_between([0+epsilon, x.max()], y.min(), 0-epsilon, alpha=1.0, color=fillcolor, zorder=4)#yellow
+# ax.fill_between([x.min(), 0-epsilon], 0+epsilon, y.max(), alpha=1.0, color=fillcolor, zorder=4)#yellow
+
+
+## FILL
+ax.fill_between([x.min(), 0-epsilon], y.min(), 0-epsilon, alpha=.25, color=fillcolor, zorder=4)#yellow
+ax.fill_between([0+epsilon, x.max()], 0+epsilon, y.max(), alpha=.25, color=fillcolor, zorder=4)#yellow
+
+
+ax.text(1,1, r"$\mathcal{G}^+_{\mathbf{R}^2}$", color='royalblue', size=15)
+
+# ax.text(0.25,0.25, r"$\mathcal{S}$", color='darkorange', size=15)
+
+# PLOT 1-PARAMETER FAMILY
+
+print('abar:', abar)
+print('abar[0,:]:', abar[0,:])
+print('abar[1,:]:', abar[1,:])
+
+line = ax.plot(abar[:,0],abar[:,1], linewidth=1.5, color='darkorange', linestyle='-', zorder=4)
+
+# plt.arrow(x=1, y=0, dx=0.5, dy=0, )
+# ax.arrow(1, 0, 0.5, 0, head_width=0.05, head_length=0.1, fc='k', ec='k', zorder=5)
+# plt.arrow(1, 0, 0.8, 0,  shape='full', lw=0, length_includes_head=True, head_width=.15, zorder=5, color='purple')
+
+
+## PLOT ARROW:
+# plt.arrow(1, 0, 0.5, 0,  shape='full', lw=0, length_includes_head=True, head_width=.20, zorder=5, color='darkorange')
+# plt.arrow(0, 1.8, 0, -0.8,  shape='full', lw=0, length_includes_head=True, head_width=.20, zorder=5, color='darkorange')
+
+
+# plt.arrow(0, 1.8, 0, -0.8, lw=0,  head_width=.12, zorder=5, color='darkorange')
+# plt.arrow(0, 2, 0, -0.5,  shape='full', lw=0, length_includes_head=True, head_width=.12, zorder=5, color='darkorange')
+# add_arrow(line, color='darkorange')
+
+
+
+
+# ax.plot_surface(a1,a2, Z, cmap=cm.coolwarm,
+#                        linewidth=0, antialiased=False)
+
+
+
+# ax.plot(theta_rho, energy_axial1, 'royalblue', zorder=3, label=r"axialMin1")
+# ax.plot(theta_rho, energy_axial2, 'forestgreen', zorder=3, label=r"axialMin2")
+# ax.plot(-1.0*alphas, kappas, 'red', zorder=3, )
+
+
+# print('test:',test)
+# ax.scatter(test[0],test[1])
+# ax.arrow(test[0],test[1],abarperp[0],abarperp[1])
+line_values= np.array(line_values)
+
+ax.plot(line_values[:,0],line_values[:,1],'k--', linewidth=1,color='orange',alpha=0.5)
+
+# lg = ax.legend(bbox_to_anchor=(0.0, 0.75), loc='upper left')
+
+
+
+### PLot x and y- Axes
+ax.plot(ax.get_xlim(),[0,0],'k--', linewidth=0.5)
+ax.plot([0,0],ax.get_ylim(), 'k--', linewidth=0.5)
+
+
+
+ax.set_xlabel(r"$a_1$", fontsize=f_size ,labelpad=0)
+ax.set_ylabel(r"$a_2$", fontsize=f_size ,labelpad=0, rotation=0)
+# ax.set_ylabel(r"energy")
+ax.tick_params(axis='both', which='major', labelsize=f_size)
+ax.tick_params(axis='both', which='minor', labelsize=f_size)
+
+
+
+ax.set_ylim(-2,2)
+
+# ax.set_xticks([-np.pi/2, -np.pi/4  ,0,  np.pi/4,  np.pi/2 ])
+# labels = ['$0$',r'$\pi/8$', r'$\pi/4$' ,r'$3\pi/8$' , r'$\pi/2$']
+# ax.set_yticklabels(labels)
+
+print('x.max()',x.max())
+print('y.max()',y.max())
+ax.set_xlim(x.min(),x.max())
+ax.set_xlim(y.min(),y.max())
+
+plt.subplots_adjust(bottom=0.15)
+plt.subplots_adjust(left=0.2)
+
+
+
+# ax.legend(loc='upper right')
+
+
+
+fig.set_size_inches(width, height)
+# fig.set_size_inches(set_size(width, fraction=0.33))
+fig.savefig('Energy_ContourG+_Flat.pdf')
+
+plt.show()
+
+
+#
+#
+#
+# # Curve parametrised by \theta_rho = alpha in parameter space
+# N=100;
+# theta_rho = np.linspace(1, 3, num=N)
+# print('theta_rho:', theta_rho)
+#
+#
+# theta_values = []
+#
+#
+# for t in theta_rho:
+#
+#         s = (1.0/10.0)*t+0.1
+#         theta_values.append(s)
+#
+#
+#
+#
+#
+# theta_rho = np.array(theta_rho)
+# theta_values = np.array(theta_values)
+#
+# betas_ = 2.0
+#
+
+# alphas, betas, thetas = np.meshgrid(theta_rho, betas_, theta_values, indexing='ij')
+#
+#
+# harmonicMeanVec = np.vectorize(harmonicMean)
+# arithmeticMeanVec = np.vectorize(arithmeticMean)
+# prestrain_b1Vec = np.vectorize(prestrain_b1)
+# prestrain_b2Vec = np.vectorize(prestrain_b2)
+#
+# GetMuGammaVec = np.vectorize(GetMuGamma)
+# muGammas = GetMuGammaVec(betas,thetas,gamma,mu1,rho1,InputFilePath ,OutputFilePath )
+#
+# q1_vec = harmonicMeanVec(mu1, betas, thetas)
+# q2_vec = arithmeticMeanVec(mu1, betas, thetas)
+#
+# b1_vec = prestrain_b1Vec(rho1, betas, alphas, thetas)
+# b2_vec = prestrain_b2Vec(rho1, betas, alphas, thetas)
+
+# special case: q12 == 0!! .. braucht eigentlich nur b1 & b2 ...
+
+# print('type b1_values:', type(b1_values))
+
+
+
+# print('size(q1)',q1.shape)
+#
+#
+# energy_axial1 = []
+# energy_axial2 = []
+#
+# # for b1 in b1_values:
+# for i in range(len(theta_rho)):
+#     print('index i:', i)
+#
+#     print('theta_rho[i]',theta_rho[i])
+#     print('theta_values[i]',theta_values[i])
+#
+#     q1 = (1.0/6.0)*harmonicMean(mu1, beta, theta_values[i])
+#     q2 = (1.0/6.0)*arithmeticMean(mu1, beta, theta_values[i])
+#     q12 = 0.0
+#     q3 = GetMuGamma(beta, theta_values[i],gamma,mu1,rho1,InputFilePath ,OutputFilePath )
+#     b1 = prestrain_b1(rho1,beta, theta_rho[i],theta_values[i] )
+#     b2 = prestrain_b2(rho1,beta, theta_rho[i],theta_values[i] )
+#
+#
+#     # q2_vec = arithmeticMean(mu1, betas, thetas)
+#     #
+#     # b1_vec = prestrain_b1Vec(rho1, betas, alphas, thetas)
+#     # b2_vec = prestrain_b2Vec(rho1, betas, alphas, thetas)
+#     print('q1[i]',q1)
+#     print('q2[i]',q2)
+#     print('q3[i]',q3)
+#     print('b1[i]',b1)
+#     print('b2[i]',b2)
+#     # print('q1[i]',q1[0][i])
+#     # print('q2[i]',q2[i])
+#     # print('b1[i]',b1[i])
+#     # print('b2[i]',b2[i])
+#     #compute axial energy #1 ...
+#
+#     a_axial1 = np.array([b1,0])
+#     a_axial2 = np.array([0,b2])
+#     b = np.array([b1,b2])
+#
+#     H = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+#     A = np.array([[q1,1/2*q12], [1/2*q12,q2] ])
+#
+#
+#     tmp = H.dot(a_axial1)
+#
+#     print('H',H)
+#     print('A',A)
+#     print('b',b)
+#     print('a_axial1',a_axial1)
+#     print('tmp',tmp)
+#
+#     tmp = (1/2)*a_axial1.dot(tmp)
+#     print('tmp',tmp)
+#
+#     tmp2 = A.dot(b)
+#     print('tmp2',tmp2)
+#     tmp2 = 2*a_axial1.dot(tmp2)
+#
+#     print('tmp2',tmp2)
+#     energy_1 = tmp - tmp2
+#     print('energy_1',energy_1)
+#
+#
+#     energy_axial1.append(energy_1)
+#
+#
+#     tmp = H.dot(a_axial2)
+#
+#     print('H',H)
+#     print('A',A)
+#     print('b',b)
+#     print('a_axial2',a_axial2)
+#     print('tmp',tmp)
+#
+#     tmp = (1/2)*a_axial2.dot(tmp)
+#     print('tmp',tmp)
+#
+#     tmp2 = A.dot(b)
+#     print('tmp2',tmp2)
+#     tmp2 = 2*a_axial2.dot(tmp2)
+#
+#     print('tmp2',tmp2)
+#     energy_2 = tmp - tmp2
+#     print('energy_2',energy_2)
+#
+#
+#     energy_axial2.append(energy_2)
+#
+#
+#
+#
+#
+# print('theta_values', theta_values)
+#
+#
+#
+
+
+#
+#
+#
+#
+# kappas = []
+# alphas = []
+# # G.append(float(s[0]))
+#
+#
+#
+#
+# for t in T :
+#
+#     abar_current = sstar*abar+t*abarperp;
+#     # print('abar_current', abar_current)
+#     abar_current[abar_current < 1e-10] = 0
+#     # print('abar_current', abar_current)
+#
+#     # G = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+#     G = [abar_current[0], abar_current[1] , (2*abar_current[0]*abar_current[1])**0.5 ]
+#
+#     e = [(abar_current[0]/(abar_current[0]+abar_current[1]))**0.5, (abar_current[1]/(abar_current[0]+abar_current[1]))**0.5]
+#     kappa = abar_current[0]+abar_current[1]
+#     alpha = math.atan2(e[1], e[0])
+#
+#     print('angle current:', alpha)
+#
+#     kappas.append(kappa)
+#     alphas.append(alpha)
+#
+#
+#
+# alphas = np.array(alphas)
+# kappas = np.array(kappas)
+#
+#
+# print('kappas:',kappas)
+# print('alphas:',alphas)
+# print('min alpha:', min(alphas))
+# print('min kappa:', min(kappas))
+#
+# mpl.rcParams['text.usetex'] = True
+# mpl.rcParams["font.family"] = "serif"
+# mpl.rcParams["font.size"] = "9"
+# width = 6.28 *0.5
+# height = width / 1.618
+# fig = plt.figure()
+# # ax = plt.axes((0.15,0.21 ,0.75,0.75))
+# ax = plt.axes((0.15,0.21 ,0.8,0.75))
+# ax.tick_params(axis='x',which='major', direction='out',pad=5)
+# ax.tick_params(axis='y',which='major', length=3, width=1, direction='out',pad=3)
+# # ax.xaxis.set_major_locator(MultipleLocator(0.1))
+# # ax.xaxis.set_minor_locator(MultipleLocator(0.05))
+# # ax.xaxis.set_major_locator(plt.MultipleLocator(np.pi / 8))
+# # ax.xaxis.set_minor_locator(plt.MultipleLocator(np.pi / 16))
+# ax.xaxis.set_major_locator(plt.MultipleLocator(np.pi / 2))
+# ax.xaxis.set_minor_locator(plt.MultipleLocator(np.pi / 4))
+# ax.xaxis.set_major_formatter(plt.FuncFormatter(format_func))
+# ax.grid(True,which='major',axis='both',alpha=0.3)
+#
+#
+#
+#
+# ax.plot(alphas, kappas, 'royalblue', zorder=3, )
+# ax.plot(-1.0*alphas, kappas, 'red', zorder=3, )

Python-Scripts/1-ParameterFamily_G+_v2.py

+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
+
+import matplotlib as mpl
+from matplotlib.ticker import MultipleLocator,FormatStrFormatter,MaxNLocator
+import pandas as pd
+
+import seaborn as sns
+import matplotlib.colors as mcolors
+
+
+from mpl_toolkits.mplot3d.proj3d import proj_transform
+# from mpl_toolkits.mplot3d.axes3d import Axes3D
+from matplotlib.text import Annotation
+from matplotlib.patches import FancyArrowPatch
+# from matplotlib import rc
+# rc('text', usetex=True) # Use LaTeX font
+#
+# import seaborn as sns
+# sns.set(color_codes=True)
+
+# set the colormap and centre the colorbar
+class MidpointNormalize(mcolors.Normalize):
+	"""
+	Normalise the colorbar so that diverging bars work there way either side from a prescribed midpoint value)
+
+	e.g. im=ax1.imshow(array, norm=MidpointNormalize(midpoint=0.,vmin=-100, vmax=100))
+	"""
+	def __init__(self, vmin=None, vmax=None, midpoint=None, clip=False):
+		self.midpoint = midpoint
+		mcolors.Normalize.__init__(self, vmin, vmax, clip)
+
+	def __call__(self, value, clip=None):
+		# I'm ignoring masked values and all kinds of edge cases to make a
+		# simple example...
+		x, y = [self.vmin, self.midpoint, self.vmax], [0, 0.5, 1]
+		return np.ma.masked_array(np.interp(value, x, y), np.isnan(value))
+
+
+
+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 == -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)
+    ##find number of multiples of pi/2
+    N = int(np.round(4 * value / np.pi))
+    if N == 0:
+        return "0"
+    elif N == 1:
+        return r"$\pi/4$"
+    elif N == -1:
+        return r"$-\pi/4$"
+    elif N == 2:
+        return r"$\pi/2$"
+    elif N == -2:
+        return r"$-\pi/2$"
+    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
+
+
+
+def energy(a1,a2,q1,q2,q12,q3,b1,b2):
+
+
+    a = np.array([a1,a2])
+    b = np.array([b1,b2])
+    H = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+    A = np.array([[q1,1/2*q12], [1/2*q12,q2] ])
+
+
+    tmp = H.dot(a)
+
+    # print('H',H)
+    # print('A',A)
+    # print('b',b)
+    # print('a',a)
+    # print('tmp',tmp)
+
+    tmp = (1/2)*a.dot(tmp)
+    # print('tmp',tmp)
+
+    tmp2 = A.dot(b)
+    # print('tmp2',tmp2)
+    tmp2 = 2*a.dot(tmp2)
+
+    # print('tmp2',tmp2)
+    energy = tmp - tmp2
+    # print('energy',energy)
+
+
+    # energy_axial1.append(energy_1)
+
+    return energy
+
+
+
+def evaluate(x,y):
+
+	# (abar[0,:]*abar[1,:])**0.5
+
+	return np.sqrt(x*y)
+
+
+# def energy(a1,a2,q1,q2,q12,q3,b1,b2):
+#
+#
+#     b = np.array([b1,b2])
+#     H = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+#     A = np.array([[q1,1/2*q12], [1/2*q12,q2] ])
+#
+#
+#     tmp = H.dot(a)
+#
+#     print('H',H)
+#     print('A',A)
+#     print('b',b)
+#     print('a',a)
+#     print('tmp',tmp)
+#
+#     tmp = (1/2)*a.dot(tmp)
+#     print('tmp',tmp)
+#
+#     tmp2 = A.dot(b)
+#     print('tmp2',tmp2)
+#     tmp2 = 2*a.dot(tmp2)
+#
+#     print('tmp2',tmp2)
+#     energy = tmp - tmp2
+#     print('energy',energy)
+#
+#
+#     # energy_axial1.append(energy_1)
+#
+#     return energy
+#
+
+def add_arrow(line, position=None, direction='right', size=15, color=None):
+    """
+    add an arrow to a line.
+
+    line:       Line2D object
+    position:   x-position of the arrow. If None, mean of xdata is taken
+    direction:  'left' or 'right'
+    size:       size of the arrow in fontsize points
+    color:      if None, line color is taken.
+    """
+    if color is None:
+        color = line.get_color()
+
+    xdata = line.get_xdata()
+    ydata = line.get_ydata()
+
+    if position is None:
+        position = xdata.mean()
+    # find closest index
+    start_ind = np.argmin(np.absolute(xdata - position))
+    if direction == 'right':
+        end_ind = start_ind + 1
+    else:
+        end_ind = start_ind - 1
+
+    line.axes.annotate('',
+        xytext=(xdata[start_ind], ydata[start_ind]),
+        xy=(xdata[end_ind], ydata[end_ind]),
+        arrowprops=dict(arrowstyle="->", color=color),
+        size=size
+    )
+
+
+
+class Annotation3D(Annotation):
+    def __init__(self, text, xyz, *args, **kwargs):
+        super().__init__(text, xy=(0, 0), *args, **kwargs)
+        self._xyz = xyz
+
+    def draw(self, renderer):
+        x2, y2, z2 = proj_transform(*self._xyz, self.axes.M)
+        self.xy = (x2, y2)
+        super().draw(renderer)
+
+def _annotate3D(ax, text, xyz, *args, **kwargs):
+    '''Add anotation `text` to an `Axes3d` instance.'''
+
+    annotation = Annotation3D(text, xyz, *args, **kwargs)
+    ax.add_artist(annotation)
+
+setattr(Axes3D, 'annotate3D', _annotate3D)
+
+class Arrow3D(FancyArrowPatch):
+
+    def __init__(self, x, y, z, dx, dy, dz, *args, **kwargs):
+        super().__init__((0, 0), (0, 0), *args, **kwargs)
+        self._xyz = (x, y, z)
+        self._dxdydz = (dx, dy, dz)
+
+    def draw(self, renderer):
+        x1, y1, z1 = self._xyz
+        dx, dy, dz = self._dxdydz
+        x2, y2, z2 = (x1 + dx, y1 + dy, z1 + dz)
+
+        xs, ys, zs = proj_transform((x1, x2), (y1, y2), (z1, z2), self.axes.M)
+        self.set_positions((xs[0], ys[0]), (xs[1], ys[1]))
+        super().draw(renderer)
+
+
+def _arrow3D(ax, x, y, z, dx, dy, dz, *args, **kwargs):
+    '''Add an 3d arrow to an `Axes3D` instance.'''
+
+    arrow = Arrow3D(x, y, z, dx, dy, dz, *args, **kwargs)
+    ax.add_artist(arrow)
+
+setattr(Axes3D, 'arrow3D', _arrow3D)
+
+################################################################################################################
+################################################################################################################
+################################################################################################################
+
+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: -----')
+
+# q1=1;
+# q2=2;
+# q12=1/2;
+# q3=((4*q1*q2)**0.5-q12)/2;
+# # H=[2*q1,q12+2*q3;q12+2*q3,2*q2];
+#
+# H = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+# A = np.array([[q1,1/2*q12], [1/2*q12,q2] ])
+# abar = np.array([q12+2*q3, 2*q2])
+# abar = (1.0/math.sqrt((q12+2*q3)**2+(2*q2)**2))*abar
+#
+# print('abar:',abar)
+#
+# b = np.linalg.lstsq(A, abar)[0]
+# print('b',b)
+#
+#
+# # print('abar:',np.shape(abar))
+# # print('np.transpose(abar):',np.shape(np.transpose(abar)))
+# sstar = (1/(q1+q2))*abar.dot(A.dot(b))
+# # sstar = (1/(q1+q2))*abar.dot(tmp)
+# print('sstar', sstar)
+# abarperp= np.array([abar[1],-abar[0]])
+# print('abarperp:',abarperp)
+
+
+# -------------------------- Input Parameters --------------------
+
+mu1 = 1.0
+rho1 = 1.0
+alpha = 5.0
+theta = 1.0/2
+# theta= 0.1
+beta = 5.0
+
+
+
+# mu1 = 1.0
+# rho1 = 1.0
+# alpha = 2.0
+# theta = 1.0/2
+# # theta= 0.1
+# beta = 5.0
+
+
+#Figure3:
+# mu1 = 1.0
+# rho1 = 1.0
+# alpha = 2.0
+# theta = 1.0/8
+# # theta= 0.1
+# beta = 2.0
+
+
+# alpha= -5
+
+
+#set gamma either to 1. '0' 2. 'infinity' or 3. a numerical positive value
+gamma = '0'
+gamma = 'infinity'
+
+
+lambda1 = 0.0
+
+
+print('---- Input parameters: -----')
+print('mu1: ', mu1)
+print('rho1: ', rho1)
+# print('alpha: ', alpha)
+print('beta: ', beta)
+# print('theta: ', theta)
+print('gamma:', gamma)
+
+print('lambda1: ', lambda1)
+print('----------------------------')
+# ----------------------------------------------------------------
+print('----------------------------')
+
+# ----------------------------------------------------------------
+
+
+
+
+
+
+q1 = (1.0/6.0)*harmonicMean(mu1, beta, theta)
+q2 = (1.0/6.0)*arithmeticMean(mu1, beta, theta)
+q12 = 0.0
+q3 = GetMuGamma(beta, theta,gamma,mu1,rho1,InputFilePath ,OutputFilePath )
+b1 = prestrain_b1(rho1,beta, alpha, theta )
+b2 = prestrain_b2(rho1,beta, alpha, theta )
+
+
+# 1-ParameterFamilyCase:
+
+q1=1;
+q2=2;
+q12=1/2;
+q3=((4*q1*q2)**0.5-q12)/2;
+# H=[2*q1,q12+2*q3;q12+2*q3,2*q2];
+
+H = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+A = np.array([[q1,1/2*q12], [1/2*q12,q2] ])
+abar = np.array([q12+2*q3, 2*q2])
+abar = (1.0/math.sqrt((q12+2*q3)**2+(2*q2)**2))*abar
+
+print('abar:',abar)
+
+b = np.linalg.lstsq(A, abar)[0]
+print('b',b)
+
+b1=b[0]
+b2=b[1]
+
+
+# print('abar:',np.shape(abar))
+# print('np.transpose(abar):',np.shape(np.transpose(abar)))
+sstar = (1/(q1+q2))*abar.dot(A.dot(b))
+# sstar = (1/(q1+q2))*abar.dot(tmp)
+print('sstar', sstar)
+abarperp= np.array([abar[1],-abar[0]])
+print('abarperp:',abarperp)
+
+print('----------------------------')
+
+# ----------------------------------------------------------------
+
+N=1000;
+scale_domain = 5
+
+translate_startpoint = -5
+
+# T = np.linspace(-sstar*(q12+2*q3)/(2*q2), sstar*(2*q2)/(q12+2*q3), num=N)
+T = np.linspace(-sstar*(q12+2*q3)/(2*q2)*scale_domain + translate_startpoint, sstar*(2*q2)/(q12+2*q3)*scale_domain , num=N)
+# T = np.linspace(-2,2, num=N)
+# print('T:', T)
+
+print('T.min():', T.min())
+print('T.max():', T.max())
+
+kappas = []
+alphas = []
+# G.append(float(s[0]))
+
+G_container = []
+abar_container = []
+
+
+abar_tmp = abar
+
+for t in T :
+	abar_current = sstar*abar+t*abarperp;
+    # print('abar_current', abar_current)
+	abar_current[abar_current < 1e-10] = 0
+	# print('abar_current', abar_current)
+	# G = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+	G = [abar_current[0], abar_current[1] , (2*abar_current[0]*abar_current[1])**0.5 ]
+	# print('type of G', type(G))
+	# print('G', G)
+	G_container.append(G)
+	abar_container.append(abar_current)
+	e = [(abar_current[0]/(abar_current[0]+abar_current[1]))**0.5, (abar_current[1]/(abar_current[0]+abar_current[1]))**0.5]
+	kappa = abar_current[0]+abar_current[1]
+	alpha = math.atan2(e[1], e[0])
+	# print('angle current:', alpha)
+	kappas.append(kappa)
+	alphas.append(alpha)
+
+
+alphas = np.array(alphas)
+kappas = np.array(kappas)
+
+# print('G_container', G_container)
+G = np.array(G_container)
+abar = np.array(abar_container)
+
+print('G', G)
+print('abar', abar)
+print('abar.shape',abar.shape)
+
+
+
+
+
+print('q1 = ', q1)
+print('q2 = ', q2)
+print('q3 = ', q3)
+print('q12 = ', q12)
+print('b1 = ', b1)
+print('b2 = ', b2)
+
+num_Points = 20
+num_Points = 50
+num_Points = 200
+
+# Creating dataset
+x = np.linspace(-5,5,num_Points)
+y = np.linspace(-5,5,num_Points)
+
+x = np.linspace(-20,20,num_Points)
+y = np.linspace(-20,20,num_Points)
+
+# x = np.linspace(-10,10,num_Points)
+# y = np.linspace(-10,10,num_Points)
+
+# x = np.linspace(-60,60,num_Points)
+# y = np.linspace(-60,60,num_Points)
+#
+#
+# x = np.linspace(-40,40,num_Points)
+# y = np.linspace(-40,40,num_Points)
+
+
+range = 2
+
+x_1 = np.linspace(0,range,num_Points)
+y_1 = np.linspace(0,range,num_Points)
+x_2 = np.linspace(-range,0,num_Points)
+y_2 = np.linspace(-range,0,num_Points)
+
+
+X_1,Y_1 = np.meshgrid(x_1,y_1)
+X_2,Y_2 = np.meshgrid(x_2,y_2)
+
+
+a1, a2 = np.meshgrid(x,y)
+
+# geyser = sns.load_dataset("geyser")
+# print('type of geyser:', type(geyser))
+# print('geyser:',geyser)
+
+ContourRange=20
+
+x_in = np.linspace(-ContourRange,ContourRange,num_Points)
+y_in = np.linspace(-ContourRange,ContourRange,num_Points)
+a1_in, a2_in = np.meshgrid(x_in,y_in)
+
+# print('a1:', a1)
+# print('a2:',a2 )
+#
+# print('a1.shape', a1.shape)
+
+#-- FILTER OUT VALUES for G+ :
+
+tmp1 = a1[np.where(a1*a2 >= 0)]
+tmp2 = a2[np.where(a1*a2 >= 0)]
+
+# tmp1 = a1[a1*a2 >= 0]
+# tmp2 = a2[a1*a2 >= 0]
+
+# tmp1 = a1[np.where(a1>=0 and a2 >= 0)]
+# tmp2 = a2[np.where(a1>=0 and a2 >= 0)]
+
+
+# tmp1 = tmp1[np.where(a1 >= 0)]
+# tmp2 = tmp2[np.where(a1 >= 0)]
+
+# tmp1_pos = a1[np.where(a1*a2 >= 0)]
+# tmp2_neg = a2[np.where(a1*a2 >= 0)]
+
+
+
+print('tmp1.shape',tmp1.shape)
+print('tmp1.shape[0]',tmp1.shape[0])
+print('tmp2.shape',tmp2.shape)
+print('tmp2.shape[0]',tmp2.shape[0])
+
+
+
+tmp1 = tmp1.reshape(-1,int(tmp1.shape[0]/2))
+tmp2 = tmp2.reshape(-1,int(tmp2.shape[0]/2))
+
+print('tmp1.shape',tmp1.shape)
+print('tmp1.shape[0]',tmp1.shape[0])
+print('tmp2.shape',tmp2.shape)
+print('tmp2.shape[0]',tmp2.shape[0])
+
+# np.take(a, np.where(a>100)[0], axis=0)
+# tmp1 = np.take(a1, np.where(a1*a2 >= 0)[0], axis=0)
+# tmp2 = np.take(a1, np.where(a1*a2 >= 0)[0], axis=0)
+# tmp2 = a2[np.where(a1*a2 >= 0)]
+
+# tmp1 = a1[a1*a2 >= 0]
+# tmp2 = a2[a1*a2 >= 0]
+
+
+# tmp1_pos = a1[np.where(a1*a2 >= 0) ]
+# tmp2_pos = a2[np.where(a1*a2 >= 0) ]
+# tmp1_pos = tmp1_pos[np.where(tmp1_pos  >= 0)]
+# tmp2_pos = tmp2_pos[np.where(tmp2_pos  >= 0)]
+
+# tmp1_neg = a1[a1*a2 >= 0 ]
+# tmp2_neg = a2[a1*a2 >= 0 ]
+# tmp1_neg = tmp1_neg[tmp1_neg  < 0]
+# tmp2_neg = tmp2_neg[tmp2_neg  < 0]
+# a1 = tmp1
+# a2 = tmp2
+#
+# a1 = a1.reshape(-1,5)
+# a2 = a2.reshape(-1,5)
+
+# tmp1_pos = tmp1_pos.reshape(-1,5)
+# tmp2_pos = tmp2_pos.reshape(-1,5)
+# tmp1_neg = tmp1_neg.reshape(-1,5)
+# tmp2_neg = tmp2_neg.reshape(-1,5)
+
+
+# print('a1:', a1)
+# print('a2:',a2 )
+# print('a1.shape', a1.shape)
+
+
+
+
+
+energyVec = np.vectorize(energy)
+
+# Z = energyVec(np.array([a1,a2]),q1,q2,q12,q3,b1,b2)
+# Z = energyVec(a1,a2,q1,q2,q12,q3,b1,b2)
+#
+# Z_in = energyVec(a1_in,a2_in,q1,q2,q12,q3,b1,b2)
+
+
+
+
+# Z = (tmp2**2)/tmp1
+Z = np.sqrt(tmp1*tmp2)
+
+
+Z1 = np.sqrt(X_1*Y_1)
+Z2 = np.sqrt(X_2*Y_2)
+
+# Z_bar = np.sqrt(abar[0,:]*abar[1,:])
+Z_bar = (abar[0,:]*abar[1,:])**0.5*abar
+
+abar = abar.T
+
+
+
+v1 = abar[0,:]
+v2 = abar[1,:]
+
+# print('a1:', a1)
+# print('a2:',a2 )
+# print('a1.shape', a1.shape)
+
+
+evaluateVec = np.vectorize(evaluate)
+Z_bar = evaluateVec(abar[0,:],abar[1,:])
+# Z = np.sqrt(np.multiply(tmp1,tmp2))
+# Z = np.sqrt(a1*a2)
+
+
+print('v1.shape', v1.shape)
+print('v1', v1)
+
+
+
+
+print('Z:', Z)
+print('Z_bar:', Z_bar)
+# print('any', np.any(Z<0))
+
+#
+
+
+# negZ_a1 = a1[np.where(Z<0)]
+# negZ_a2 = a2[np.where(Z<0)]
+# negativeValues = Z[np.where(Z<0)]
+# print('negativeValues:',negativeValues)
+#
+# print('negZ_a1',negZ_a1)
+# print('negZ_a2',negZ_a2)
+#
+#
+# negZ_a1 = negZ_a1.reshape(-1,5)
+# negZ_a2 = negZ_a2.reshape(-1,5)
+# negativeValues = negativeValues.reshape(-1,5)
+#
+# Z_pos =  energyVec(tmp1_pos,tmp2_pos,q1,q2,q12,q3,b1,b2)
+# Z_neg = energyVec(tmp1_neg,tmp2_neg,q1,q2,q12,q3,b1,b2)
+
+
+
+
+
+# print('Test energy:' , energy(np.array([1,1]),q1,q2,q12,q3,b1,b2))
+
+
+
+
+# print('Z_pos.shape', Z_pos.shape)
+
+
+
+
+
+
+
+## -- PLOT :
+mpl.rcParams['text.usetex'] = True
+mpl.rcParams["font.family"] = "serif"
+mpl.rcParams["font.size"] = "9"
+
+label_size = 8
+mpl.rcParams['xtick.labelsize'] = label_size
+mpl.rcParams['ytick.labelsize'] = label_size
+
+# plt.style.use('seaborn')
+plt.style.use('seaborn-whitegrid')
+# sns.set()
+# plt.style.use('seaborn-whitegrid')
+
+label_size = 9
+mpl.rcParams['xtick.labelsize'] = label_size
+mpl.rcParams['ytick.labelsize'] = label_size
+
+width = 6.28 *0.5
+width = 6.28
+height = width / 1.618
+fig = plt.figure()
+
+ax = plt.axes(projection ='3d', adjustable='box')
+# ax = plt.axes((0.17,0.21 ,0.75,0.75))
+# ax = plt.axes((0.15,0.18,0.8,0.8))
+# ax.tick_params(axis='x',which='major', direction='out',pad=5)
+# ax.tick_params(axis='y',which='major', length=3, width=1, direction='out',pad=3)
+# ax.xaxis.set_major_locator(MultipleLocator(0.1))
+# ax.xaxis.set_minor_locator(MultipleLocator(0.05))
+# ax.xaxis.set_major_locator(plt.MultipleLocator(np.pi / 8))
+# ax.xaxis.set_minor_locator(plt.MultipleLocator(np.pi / 16))
+# ax.xaxis.set_major_locator(plt.MultipleLocator(np.pi / 2))
+# ax.xaxis.set_minor_locator(plt.MultipleLocator(np.pi / 4))
+# ax.xaxis.set_major_formatter(plt.FuncFormatter(format_func))
+ax.grid(True,which='major',axis='both',alpha=0.3)
+
+# colorfunction=(B*kappa)
+# print('colofunction',colorfunction)
+
+#translate Data
+# Z = Z - (Z.max()-Z.min())/2
+# Z = Z - 50
+# Z = Z - 500
+#
+# Z = Z.T
+
+
+# Substract constant:
+# c = (b1**2)*q1+b1*b2*q12+(b2**2)*q2
+# Z = Z-c
+
+# print('Value of c:', c)
+
+
+
+# print('Z.min()', Z.min())
+# print('Z.max()', Z.max())
+# norm=mcolors.Normalize(Z.min(),Z.max())
+# facecolors=cm.brg(norm)
+
+
+# print('norm:', norm)
+# print('type of norm', type(norm))
+# print('norm(0):', norm(0))
+# print('norm(Z):', norm(Z))
+
+# ax.plot(theta_rho, theta_values, 'royalblue', zorder=3, )
+
+# ax.scatter(a1,a2, s=0.5)
+
+# ax.scatter(tmp1_pos,tmp2_pos, s=0.5)
+# ax.scatter(tmp1_neg,tmp2_neg, s=0.5)
+
+# CS = ax.contour(a1, a2, Z,10, cmap=plt.cm.gnuplot, levels=100 )
+# CS = ax.contour(a1, a2, Z,10, cmap=plt.cm.gnuplot,  levels=20 )
+
+
+# sns.kdeplot(np.array([a1, a2, Z]))
+# sns.kdeplot(tmp1_pos,tmp2_pos,Z_pos)
+
+# levels = [-5.0, -4, -3, 0.0, 1.5, 2.5, 3.5]
+# CS = ax.contour(a1, a2, Z,10, cmap=plt.cm.gnuplot, corner_mask=True,levels=levels)
+# CS = ax.contour(a1, a2, Z, cmap=plt.cm.gnuplot(norm(Z)), corner_mask=True)
+# CS = ax.contour(a1, a2, Z, cm.brg(norm(Z)), levels=20)
+# CS = ax.contour(a1, a2, Z, cmap=plt.cm.gnuplot, levels=20)
+# CS = ax.contour(a1, a2, Z, colors='k', levels=14,  linewidths=(0.5,))
+# CS = ax.contour(a1, a2, Z, colors='k', levels=18,  linewidths=(0.5,))
+
+# ax.contour(negZ_a1, negZ_a2, negativeValues, colors='k',  linewidths=(0.5,))
+# CS =  ax.contour(a1_in, a2_in, Z_in, colors='k',  linewidths=(0.5,))
+
+
+
+# df = pd.DataFrame(data=Z_in, columns=a1_in, index=a2_in)
+# df2 = pd.DataFrame(np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]),
+#                    columns=['a', 'b', 'c'])
+
+
+
+
+# sns.kdeplot(data=df2, x="waiting", y="duration")
+# sns.kdeplot(data=df2)
+
+# CS = ax.contour(a1, a2, Z, colors='k',   linewidths=(0.5,))
+
+# CS = ax.contour(a1, a2, Z,10, cmap=plt.cm.gnuplot, extend='both', levels=50)
+# CS = ax.contourf(a1, a2, Z,10, colors='k', extend='both', levels=50)
+# CS = ax.contourf(a1, a2, Z,10, colors='k')
+#
+# # CS = ax.contour(tmp1_pos,tmp2_pos, Z_pos,10, cmap=plt.cm.gnuplot, levels=10 )
+# # CS = ax.contour(tmp1_pos,tmp2_pos, Z_pos,10, cmap=plt.cm.gnuplot, corner_mask=True)
+#
+# CS = ax.contour(a1, a2, Z,10,  colors = 'k')
+# ax.clabel(CS, inline=True, fontsize=4)
+
+
+# cmap = cm.brg(norm(Z))
+#
+# C_map = cm.inferno(norm(Z))
+
+# ax.imshow(Z, cmap=C_map, extent=[-20, 20, -20, 20], origin='lower', alpha=0.5)
+
+# ax.imshow(norm(Z), extent=[-20, 20, -20, 20], origin='lower',
+#                   cmap='bwr', alpha=0.8)
+
+# ax.imshow(norm(Z), extent=[-20, 20, -20, 20],origin='lower', vmin=Z.min(), vmax=Z.max(),
+#                   cmap='bwr', alpha=0.6)
+
+# ax.imshow(norm(Z), extent=[-20, 20, -20, 20],origin='lower', norm = norm,
+#                   cmap='coolwarm', alpha=0.6)
+
+
+cmap=mpl.cm.RdBu_r
+# cmap=mpl.cm.viridis_r
+cmap=mpl.cm.bwr
+# # cmap=mpl.cm.coolwarm
+# # cmap=mpl.cm.gnuplot
+# cmap=mpl.cm.viridis
+# cmap=mpl.cm.inferno
+cmap=mpl.cm.Blues
+# cmap=mpl.cm.magma
+# cmap=mpl.cm.cividis
+# cmap=mpl.cm.gnuplot
+# cmap=mpl.cm.gnuplot
+cmap = mpl.colors.ListedColormap(["royalblue"], name='from_list', N=None)
+# m = cm.ScalarMappable(norm=norm, cmap=cmap)
+# m = cm.ScalarMappable(cmap=cmap)
+
+# cmap = cm.brg(Z)
+# divnorm=mcolors.TwoSlopeNorm(vmin=Z.min(), vcenter=0., vmax=Z.max())
+
+# ax.imshow(Z, extent=[-20, 20, -20, 20],origin='lower', norm = norm,
+#                   cmap='coolwarm', alpha=0.6)
+
+# ax.imshow(Z, extent=[-20, 20, -20, 20],origin='lower',
+#                   cmap='coolwarm', alpha=0.6)
+# ax.imshow(Z, extent=[-20, 20, -20, 20],origin='lower',
+#                   cmap=cmap, alpha=0.6)
+
+# divnorm=mcolors.TwoSlopeNorm(vmin=Z.min(), vcenter=0., vmax=Z.max())
+# plt.imshow(Z, extent=[x.min(), x.max(), y.min(), y.max()],origin='lower',
+#                   cmap=cmap, alpha=0.6)
+
+# plt.imshow(Z, extent=[x.min(), x.max(), y.min(), y.max()],origin='lower', norm = divnorm,
+#                   cmap=cmap, alpha=0.6)
+
+
+
+
+# COLORBAR :
+# cbar = plt.colorbar()
+# cbar.ax.tick_params(labelsize=8)
+
+
+
+
+# ##----- ADD RECTANGLE TO COVER QUADRANT :
+# epsilon = 0.4
+# epsilon = 0.1
+# # ax.axvspan(0, x.max(), y.min(), 0, alpha=1, color='yellow', zorder=5)#yellow
+# # ax.fill_between([0, x.max()], y.min(), 0, alpha=0.3, color='yellow', zorder=5)#yellow
+# # ax.fill_between([x.min(), 0], 0, y.max(), alpha=0.3, color='yellow', zorder=5)#yellow
+# ax.fill_between([0+epsilon, x.max()], y.min(), 0-epsilon, alpha=0.7, color='gray', zorder=5)#yellow
+# ax.fill_between([x.min(), 0-epsilon], 0+epsilon, y.max(), alpha=0.7, color='gray', zorder=5)#yellow
+
+
+
+line = ax.plot(abar[0,:],abar[1,:],Z_bar, linewidth=2, color='coral', zorder=2)
+# CS = ax.contour(X_1,Y_1,Z1, colors='k', levels=18,  linewidths=(0.5,))
+
+start = np.array([abar[0,499],abar[1,499],Z_bar[499]])
+end = np.array([abar[0,500],abar[1,500],Z_bar[500]])
+
+
+# ax.plot_surface(a1,a2, Z, cmap=cm.coolwarm,
+#                        linewidth=0, antialiased=False)
+
+# ax.plot_surface(tmp1,tmp2, Z, cmap=cm.coolwarm,
+#                        linewidth=0, antialiased=False)
+
+# ax.scatter(X_1,Y_1,Z1, s=0.2)
+# ax.scatter(X_2,Y_2,Z2, s=0.2)
+
+
+# X = np.concatenate((X_1, X_2), axis=0)
+# Y = np.concatenate((Y_1, Y_2), axis=0)
+# Z = np.concatenate((Z1, Z2), axis=0)
+# ax.plot_surface(X,Y,Z)
+
+
+ax.plot_surface(X_1,Y_1,Z1 ,cmap=cmap,
+                       linewidth=0, antialiased=True,alpha=.75, zorder=5)
+ax.plot_surface(X_2,Y_2,Z2 ,cmap=cmap,
+                       linewidth=0, antialiased=True,alpha=.75, zorder=5)
+# ax.plot_surface(X_1,Y_1,Z1 , facecolor = 'lightblue',     #cmap=cmap,
+#                        linewidth=0, antialiased=True, alpha=1, zorder=5)
+# ax.plot_surface(X_2,Y_2,Z2 , facecolor = 'lightblue', edgecolor='none',    #cmap=cmap,
+#                        linewidth=0, antialiased=True, alpha=1, zorder=5)
+
+# ax.plot_surface(X_1,Y_1,Z1 , #color='C0',
+# 							rstride=1, cstride=1,linewidth=0, antialiased=True, alpha=1, zorder=5)
+
+
+
+
+# ax.plot_surface(X_2,Y_2,Z2 , #color='C0',
+# 							rstride=1, cstride=1,linewidth=0,  alpha=0.8, zorder=5, shade=True)
+# ax.plot_surface(X_2,Y_2,Z2)
+
+# X_2 = X_2.reshape(-1,1).flatten()
+# Y_2 = Y_2.reshape(-1,1).flatten()
+# Z2 = Z2.reshape(-1,1).flatten()
+# #
+# ax.plot_trisurf(X_2,Y_2,Z2, color='blue' )
+#
+#
+# X_1 = X_1.reshape(-1,1).flatten()
+# Y_1 = Y_1.reshape(-1,1).flatten()
+# Z1 = Z1.reshape(-1,1).flatten()
+# ax.plot_trisurf(X_1,Y_1,Z1 , color='blue')
+
+# ax.plot_surface(X_1,Y_1,Z1 , cmap=cmap,
+#                        linewidth=0, antialiased=False,alpha=1, zorder=5)
+# ax.plot_surface(X_2,Y_2,Z2 , cmap=cmap,
+#                        linewidth=0, antialiased=True,alpha=1, zorder=5)
+
+# ax.plot_surface(X_2,Y_2,Z2 , color = 'lightblue',     #cmap=cmap,
+#                        linewidth=0, antialiased=True, alpha=1, zorder=5)
+
+
+# ax.plot(G[0,:],G[1,:],G[2,:])
+# ax.plot(abar[0,:],abar[1,:],Z_bar, linewidth=2, color='yellow', linestyle='--')
+# ax.scatter(abar[0,:],abar[1,:],Z_bar,  color='purple', zorder=5)
+# ax.plot(abar[0,:],abar[1,:],Z_bar, linewidth=2, color='royalblue', linestyle='--')
+# ax.plot(abar[0,:],abar[1,:],Z_bar, linewidth=3, color='dodgerblue', linestyle='--')
+# ax.plot(abar[0,:],abar[1,:],Z_bar, linewidth=3, color='cornflowerblue', linestyle='--')
+# ax.plot(abar[0,:],abar[1,:],Z_bar, linewidth=3, color='darkorange', linestyle='--')
+# ax.plot(abar[0,:],abar[1,:],Z_bar, linewidth=3, color='yellow', linestyle='--')
+# line = ax.plot(abar[0,:],abar[1,:],Z_bar, linewidth=1, color='coral', linestyle='--', zorder=3)
+
+
+# plot starting point:
+# ax.scatter(abar[0,0],abar[1,0],Z_bar[0], marker='^',  s=30, color='black', zorder=5)
+#
+#
+# ax.scatter(abar[0,500],abar[1,500],Z_bar[500], marker='^',  s=30, color='purple', zorder=5)
+
+# ax.scatter(start[0],start[1],start[2], marker='^',  s=30, color='purple', zorder=5)
+# ax.scatter(end[0],end[1],end[2], marker='^',  s=30, color='purple', zorder=5)
+
+print('start:', start)
+print('end:', end)
+
+
+dir = end-start
+# ax.arrow()
+
+# ax.arrow3D(start[0],start[1],start[2],
+#            dir[0],dir[1],dir[2],
+#            mutation_scale=10,
+#            arrowstyle="->",
+#            linestyle='dashed',fc='coral',
+#            lw = 1,
+#            ec ='coral',
+#            zorder=3)
+
+# ax.arrow3D(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],
+#            normal[0],normal[1],normal[2],
+#            mutation_scale=15,
+#             lw = 1.5,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='blue',
+#            ec ='blue',
+#            zorder = 5)
+
+# Check proof:
+# value at t = 0:
+abar_zero= sstar*abar_tmp
+# value_0 = [abar_zero[0], abar_zero[1] , (2*abar_zero[0]*abar_zero[1])**0.5 ]
+value_0 = evaluate(abar_zero[0], abar_zero[1])
+print('value_0', value_0)
+# ax.scatter(value_0[0],value_0[1],value_0[2], marker='x',  s=20, color='dodgerblue', zorder=5)
+# ax.scatter(abar_zero[0], abar_zero[1],value_0, marker='o',  s=30, color='dodgerblue', zorder=5)
+## -----------------------------
+
+
+
+
+
+
+
+
+
+
+# ax.scatter(tmp1,tmp2, Z, cmap=cm.coolwarm,
+#                        linewidth=0, antialiased=False)
+# ax.plot_surface(tmp1,Z, tmp2, cmap=cm.coolwarm,
+#                        linewidth=0, antialiased=False)
+# ax.plot_trisurf(tmp1,tmp2, Z, cmap=cm.coolwarm,
+#                        linewidth=0, antialiased=False)
+
+
+# ax.plot(theta_rho, energy_axial1, 'royalblue', zorder=3, label=r"axialMin1")
+# ax.plot(theta_rho, energy_axial2, 'forestgreen', zorder=3, label=r"axialMin2")
+# ax.plot(-1.0*alphas, kappas, 'red', zorder=3, )
+
+
+
+
+# lg = ax.legend(bbox_to_anchor=(0.0, 0.75), loc='upper left')
+
+
+
+### PLot x and y- Axes
+# ax.plot(ax.get_xlim(),[0,0],'k--', linewidth=0.5)
+# ax.plot([0,0],ax.get_ylim(), 'k--', linewidth=0.5)
+ax.plot(ax.get_xlim(),[0,0],'k--', linewidth=1)
+ax.plot([0,0],ax.get_ylim(), 'k--', linewidth=1)
+
+
+
+ax.set_xlabel(r"$a_1$", fontsize=10 ,labelpad=0)
+ax.set_ylabel(r"$a_2$", fontsize=10 ,labelpad=0)
+# ax.set_ylabel(r"energy")
+
+
+# ax.set_xticks([-np.pi/2, -np.pi/4  ,0,  np.pi/4,  np.pi/2 ])
+# labels = ['$0$',r'$\pi/8$', r'$\pi/4$' ,r'$3\pi/8$' , r'$\pi/2$']
+# ax.set_yticklabels(labels)
+
+
+
+
+
+# ax.legend(loc='upper right')
+
+
+
+fig.set_size_inches(width, height)
+fig.savefig('1-ParameterFamily_G+.pdf')
+
+plt.show()
+
+
+#
+#
+#
+# # Curve parametrised by \theta_rho = alpha in parameter space
+# N=100;
+# theta_rho = np.linspace(1, 3, num=N)
+# print('theta_rho:', theta_rho)
+#
+#
+# theta_values = []
+#
+#
+# for t in theta_rho:
+#
+#         s = (1.0/10.0)*t+0.1
+#         theta_values.append(s)
+#
+#
+#
+#
+#
+# theta_rho = np.array(theta_rho)
+# theta_values = np.array(theta_values)
+#
+# betas_ = 2.0
+#
+
+# alphas, betas, thetas = np.meshgrid(theta_rho, betas_, theta_values, indexing='ij')
+#
+#
+# harmonicMeanVec = np.vectorize(harmonicMean)
+# arithmeticMeanVec = np.vectorize(arithmeticMean)
+# prestrain_b1Vec = np.vectorize(prestrain_b1)
+# prestrain_b2Vec = np.vectorize(prestrain_b2)
+#
+# GetMuGammaVec = np.vectorize(GetMuGamma)
+# muGammas = GetMuGammaVec(betas,thetas,gamma,mu1,rho1,InputFilePath ,OutputFilePath )
+#
+# q1_vec = harmonicMeanVec(mu1, betas, thetas)
+# q2_vec = arithmeticMeanVec(mu1, betas, thetas)
+#
+# b1_vec = prestrain_b1Vec(rho1, betas, alphas, thetas)
+# b2_vec = prestrain_b2Vec(rho1, betas, alphas, thetas)
+
+# special case: q12 == 0!! .. braucht eigentlich nur b1 & b2 ...
+
+# print('type b1_values:', type(b1_values))
+
+
+
+# print('size(q1)',q1.shape)
+#
+#
+# energy_axial1 = []
+# energy_axial2 = []
+#
+# # for b1 in b1_values:
+# for i in range(len(theta_rho)):
+#     print('index i:', i)
+#
+#     print('theta_rho[i]',theta_rho[i])
+#     print('theta_values[i]',theta_values[i])
+#
+#     q1 = (1.0/6.0)*harmonicMean(mu1, beta, theta_values[i])
+#     q2 = (1.0/6.0)*arithmeticMean(mu1, beta, theta_values[i])
+#     q12 = 0.0
+#     q3 = GetMuGamma(beta, theta_values[i],gamma,mu1,rho1,InputFilePath ,OutputFilePath )
+#     b1 = prestrain_b1(rho1,beta, theta_rho[i],theta_values[i] )
+#     b2 = prestrain_b2(rho1,beta, theta_rho[i],theta_values[i] )
+#
+#
+#     # q2_vec = arithmeticMean(mu1, betas, thetas)
+#     #
+#     # b1_vec = prestrain_b1Vec(rho1, betas, alphas, thetas)
+#     # b2_vec = prestrain_b2Vec(rho1, betas, alphas, thetas)
+#     print('q1[i]',q1)
+#     print('q2[i]',q2)
+#     print('q3[i]',q3)
+#     print('b1[i]',b1)
+#     print('b2[i]',b2)
+#     # print('q1[i]',q1[0][i])
+#     # print('q2[i]',q2[i])
+#     # print('b1[i]',b1[i])
+#     # print('b2[i]',b2[i])
+#     #compute axial energy #1 ...
+#
+#     a_axial1 = np.array([b1,0])
+#     a_axial2 = np.array([0,b2])
+#     b = np.array([b1,b2])
+#
+#     H = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+#     A = np.array([[q1,1/2*q12], [1/2*q12,q2] ])
+#
+#
+#     tmp = H.dot(a_axial1)
+#
+#     print('H',H)
+#     print('A',A)
+#     print('b',b)
+#     print('a_axial1',a_axial1)
+#     print('tmp',tmp)
+#
+#     tmp = (1/2)*a_axial1.dot(tmp)
+#     print('tmp',tmp)
+#
+#     tmp2 = A.dot(b)
+#     print('tmp2',tmp2)
+#     tmp2 = 2*a_axial1.dot(tmp2)
+#
+#     print('tmp2',tmp2)
+#     energy_1 = tmp - tmp2
+#     print('energy_1',energy_1)
+#
+#
+#     energy_axial1.append(energy_1)
+#
+#
+#     tmp = H.dot(a_axial2)
+#
+#     print('H',H)
+#     print('A',A)
+#     print('b',b)
+#     print('a_axial2',a_axial2)
+#     print('tmp',tmp)
+#
+#     tmp = (1/2)*a_axial2.dot(tmp)
+#     print('tmp',tmp)
+#
+#     tmp2 = A.dot(b)
+#     print('tmp2',tmp2)
+#     tmp2 = 2*a_axial2.dot(tmp2)
+#
+#     print('tmp2',tmp2)
+#     energy_2 = tmp - tmp2
+#     print('energy_2',energy_2)
+#
+#
+#     energy_axial2.append(energy_2)
+#
+#
+#
+#
+#
+# print('theta_values', theta_values)
+#
+#
+#
+
+
+#
+#
+#
+#
+# kappas = []
+# alphas = []
+# # G.append(float(s[0]))
+#
+#
+#
+#
+# for t in T :
+#
+#     abar_current = sstar*abar+t*abarperp;
+#     # print('abar_current', abar_current)
+#     abar_current[abar_current < 1e-10] = 0
+#     # print('abar_current', abar_current)
+#
+#     # G = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+#     G = [abar_current[0], abar_current[1] , (2*abar_current[0]*abar_current[1])**0.5 ]
+#
+#     e = [(abar_current[0]/(abar_current[0]+abar_current[1]))**0.5, (abar_current[1]/(abar_current[0]+abar_current[1]))**0.5]
+#     kappa = abar_current[0]+abar_current[1]
+#     alpha = math.atan2(e[1], e[0])
+#
+#     print('angle current:', alpha)
+#
+#     kappas.append(kappa)
+#     alphas.append(alpha)
+#
+#
+#
+# alphas = np.array(alphas)
+# kappas = np.array(kappas)
+#
+#
+# print('kappas:',kappas)
+# print('alphas:',alphas)
+# print('min alpha:', min(alphas))
+# print('min kappa:', min(kappas))
+#
+# mpl.rcParams['text.usetex'] = True
+# mpl.rcParams["font.family"] = "serif"
+# mpl.rcParams["font.size"] = "9"
+# width = 6.28 *0.5
+# height = width / 1.618
+# fig = plt.figure()
+# # ax = plt.axes((0.15,0.21 ,0.75,0.75))
+# ax = plt.axes((0.15,0.21 ,0.8,0.75))
+# ax.tick_params(axis='x',which='major', direction='out',pad=5)
+# ax.tick_params(axis='y',which='major', length=3, width=1, direction='out',pad=3)
+# # ax.xaxis.set_major_locator(MultipleLocator(0.1))
+# # ax.xaxis.set_minor_locator(MultipleLocator(0.05))
+# # ax.xaxis.set_major_locator(plt.MultipleLocator(np.pi / 8))
+# # ax.xaxis.set_minor_locator(plt.MultipleLocator(np.pi / 16))
+# ax.xaxis.set_major_locator(plt.MultipleLocator(np.pi / 2))
+# ax.xaxis.set_minor_locator(plt.MultipleLocator(np.pi / 4))
+# ax.xaxis.set_major_formatter(plt.FuncFormatter(format_func))
+# ax.grid(True,which='major',axis='both',alpha=0.3)
+#
+#
+#
+#
+# ax.plot(alphas, kappas, 'royalblue', zorder=3, )
+# ax.plot(-1.0*alphas, kappas, 'red', zorder=3, )

Python-Scripts/1-ParameterFamily_G+_v3.py

+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
+
+import matplotlib as mpl
+from matplotlib.ticker import MultipleLocator,FormatStrFormatter,MaxNLocator
+import pandas as pd
+
+import seaborn as sns
+import matplotlib.colors as mcolors
+
+
+from mpl_toolkits.mplot3d.proj3d import proj_transform
+from mpl_toolkits.mplot3d import proj3d
+# from mpl_toolkits.mplot3d.axes3d import Axes3D
+from matplotlib.text import Annotation
+from matplotlib.patches import FancyArrowPatch
+
+
+import mayavi.mlab as mlab
+from mayavi.api import OffScreenEngine
+mlab.options.offscreen = True
+
+from chart_studio import plotly
+import plotly.graph_objs as go
+# from matplotlib import rc
+# rc('text', usetex=True) # Use LaTeX font
+#
+# import seaborn as sns
+# sns.set(color_codes=True)
+
+# set the colormap and centre the colorbar
+class MidpointNormalize(mcolors.Normalize):
+	"""
+	Normalise the colorbar so that diverging bars work there way either side from a prescribed midpoint value)
+
+	e.g. im=ax1.imshow(array, norm=MidpointNormalize(midpoint=0.,vmin=-100, vmax=100))
+	"""
+	def __init__(self, vmin=None, vmax=None, midpoint=None, clip=False):
+		self.midpoint = midpoint
+		mcolors.Normalize.__init__(self, vmin, vmax, clip)
+
+	def __call__(self, value, clip=None):
+		# I'm ignoring masked values and all kinds of edge cases to make a
+		# simple example...
+		x, y = [self.vmin, self.midpoint, self.vmax], [0, 0.5, 1]
+		return np.ma.masked_array(np.interp(value, x, y), np.isnan(value))
+
+
+
+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 == -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)
+    ##find number of multiples of pi/2
+    N = int(np.round(4 * value / np.pi))
+    if N == 0:
+        return "0"
+    elif N == 1:
+        return r"$\pi/4$"
+    elif N == -1:
+        return r"$-\pi/4$"
+    elif N == 2:
+        return r"$\pi/2$"
+    elif N == -2:
+        return r"$-\pi/2$"
+    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
+
+
+
+def energy(a1,a2,q1,q2,q12,q3,b1,b2):
+
+
+    a = np.array([a1,a2])
+    b = np.array([b1,b2])
+    H = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+    A = np.array([[q1,1/2*q12], [1/2*q12,q2] ])
+
+
+    tmp = H.dot(a)
+
+    # print('H',H)
+    # print('A',A)
+    # print('b',b)
+    # print('a',a)
+    # print('tmp',tmp)
+
+    tmp = (1/2)*a.dot(tmp)
+    # print('tmp',tmp)
+
+    tmp2 = A.dot(b)
+    # print('tmp2',tmp2)
+    tmp2 = 2*a.dot(tmp2)
+
+    # print('tmp2',tmp2)
+    energy = tmp - tmp2
+    # print('energy',energy)
+
+
+    # energy_axial1.append(energy_1)
+
+    return energy
+
+
+
+def evaluate(x,y):
+
+	# (abar[0,:]*abar[1,:])**0.5
+
+	return np.sqrt(x*y)
+
+
+# def energy(a1,a2,q1,q2,q12,q3,b1,b2):
+#
+#
+#     b = np.array([b1,b2])
+#     H = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+#     A = np.array([[q1,1/2*q12], [1/2*q12,q2] ])
+#
+#
+#     tmp = H.dot(a)
+#
+#     print('H',H)
+#     print('A',A)
+#     print('b',b)
+#     print('a',a)
+#     print('tmp',tmp)
+#
+#     tmp = (1/2)*a.dot(tmp)
+#     print('tmp',tmp)
+#
+#     tmp2 = A.dot(b)
+#     print('tmp2',tmp2)
+#     tmp2 = 2*a.dot(tmp2)
+#
+#     print('tmp2',tmp2)
+#     energy = tmp - tmp2
+#     print('energy',energy)
+#
+#
+#     # energy_axial1.append(energy_1)
+#
+#     return energy
+#
+
+def add_arrow(line, position=None, direction='right', size=15, color=None):
+    """
+    add an arrow to a line.
+
+    line:       Line2D object
+    position:   x-position of the arrow. If None, mean of xdata is taken
+    direction:  'left' or 'right'
+    size:       size of the arrow in fontsize points
+    color:      if None, line color is taken.
+    """
+    if color is None:
+        color = line.get_color()
+
+    xdata = line.get_xdata()
+    ydata = line.get_ydata()
+
+    if position is None:
+        position = xdata.mean()
+    # find closest index
+    start_ind = np.argmin(np.absolute(xdata - position))
+    if direction == 'right':
+        end_ind = start_ind + 1
+    else:
+        end_ind = start_ind - 1
+
+    line.axes.annotate('',
+        xytext=(xdata[start_ind], ydata[start_ind]),
+        xy=(xdata[end_ind], ydata[end_ind]),
+        arrowprops=dict(arrowstyle="->", color=color),
+        size=size
+    )
+
+
+
+class Annotation3D(Annotation):
+    def __init__(self, text, xyz, *args, **kwargs):
+        super().__init__(text, xy=(0, 0), *args, **kwargs)
+        self._xyz = xyz
+
+    def draw(self, renderer):
+        x2, y2, z2 = proj_transform(*self._xyz, self.axes.M)
+        self.xy = (x2, y2)
+        super().draw(renderer)
+
+def _annotate3D(ax, text, xyz, *args, **kwargs):
+    '''Add anotation `text` to an `Axes3d` instance.'''
+
+    annotation = Annotation3D(text, xyz, *args, **kwargs)
+    ax.add_artist(annotation)
+
+setattr(Axes3D, 'annotate3D', _annotate3D)
+
+
+
+class Arrow3D(FancyArrowPatch):
+    def __init__(self, xs, ys, zs, *args, **kwargs):
+        FancyArrowPatch.__init__(self, (0,0), (0,0), *args, **kwargs)
+        self._verts3d = xs, ys, zs
+
+    def draw(self, renderer):
+        xs3d, ys3d, zs3d = self._verts3d
+        xs, ys, zs = proj3d.proj_transform(xs3d, ys3d, zs3d, renderer.M)
+        self.set_positions((xs[0],ys[0]),(xs[1],ys[1]))
+        FancyArrowPatch.draw(self, renderer)
+
+
+def _arrow3D(ax, x, y, z, dx, dy, dz, *args, **kwargs):
+    '''Add an 3d arrow to an `Axes3D` instance.'''
+
+    arrow = Arrow3D(x, y, z, dx, dy, dz, *args, **kwargs)
+    ax.add_artist(arrow)
+
+setattr(Axes3D, 'arrow3D', _arrow3D)
+
+################################################################################################################
+################################################################################################################
+################################################################################################################
+
+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: -----')
+
+# q1=1;
+# q2=2;
+# q12=1/2;
+# q3=((4*q1*q2)**0.5-q12)/2;
+# # H=[2*q1,q12+2*q3;q12+2*q3,2*q2];
+#
+# H = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+# A = np.array([[q1,1/2*q12], [1/2*q12,q2] ])
+# abar = np.array([q12+2*q3, 2*q2])
+# abar = (1.0/math.sqrt((q12+2*q3)**2+(2*q2)**2))*abar
+#
+# print('abar:',abar)
+#
+# b = np.linalg.lstsq(A, abar)[0]
+# print('b',b)
+#
+#
+# # print('abar:',np.shape(abar))
+# # print('np.transpose(abar):',np.shape(np.transpose(abar)))
+# sstar = (1/(q1+q2))*abar.dot(A.dot(b))
+# # sstar = (1/(q1+q2))*abar.dot(tmp)
+# print('sstar', sstar)
+# abarperp= np.array([abar[1],-abar[0]])
+# print('abarperp:',abarperp)
+
+
+# -------------------------- Input Parameters --------------------
+
+mu1 = 1.0
+rho1 = 1.0
+alpha = 5.0
+theta = 1.0/2
+# theta= 0.1
+beta = 5.0
+
+
+
+# mu1 = 1.0
+# rho1 = 1.0
+# alpha = 2.0
+# theta = 1.0/2
+# # theta= 0.1
+# beta = 5.0
+
+
+#Figure3:
+# mu1 = 1.0
+# rho1 = 1.0
+# alpha = 2.0
+# theta = 1.0/8
+# # theta= 0.1
+# beta = 2.0
+
+
+# alpha= -5
+
+
+#set gamma either to 1. '0' 2. 'infinity' or 3. a numerical positive value
+gamma = '0'
+gamma = 'infinity'
+
+
+lambda1 = 0.0
+
+
+print('---- Input parameters: -----')
+print('mu1: ', mu1)
+print('rho1: ', rho1)
+# print('alpha: ', alpha)
+print('beta: ', beta)
+# print('theta: ', theta)
+print('gamma:', gamma)
+
+print('lambda1: ', lambda1)
+print('----------------------------')
+# ----------------------------------------------------------------
+print('----------------------------')
+
+# ----------------------------------------------------------------
+
+
+
+
+
+
+q1 = (1.0/6.0)*harmonicMean(mu1, beta, theta)
+q2 = (1.0/6.0)*arithmeticMean(mu1, beta, theta)
+q12 = 0.0
+q3 = GetMuGamma(beta, theta,gamma,mu1,rho1,InputFilePath ,OutputFilePath )
+b1 = prestrain_b1(rho1,beta, alpha, theta )
+b2 = prestrain_b2(rho1,beta, alpha, theta )
+
+
+# 1-ParameterFamilyCase:
+
+q1=1;
+q2=2;
+q12=1/2;
+q3=((4*q1*q2)**0.5-q12)/2;
+# H=[2*q1,q12+2*q3;q12+2*q3,2*q2];
+
+H = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+A = np.array([[q1,1/2*q12], [1/2*q12,q2] ])
+abar = np.array([q12+2*q3, 2*q2])
+abar = (1.0/math.sqrt((q12+2*q3)**2+(2*q2)**2))*abar
+
+print('abar:',abar)
+
+b = np.linalg.lstsq(A, abar)[0]
+print('b',b)
+
+b1=b[0]
+b2=b[1]
+
+
+# print('abar:',np.shape(abar))
+# print('np.transpose(abar):',np.shape(np.transpose(abar)))
+sstar = (1/(q1+q2))*abar.dot(A.dot(b))
+# sstar = (1/(q1+q2))*abar.dot(tmp)
+print('sstar', sstar)
+abarperp= np.array([abar[1],-abar[0]])
+print('abarperp:',abarperp)
+
+print('----------------------------')
+
+# ----------------------------------------------------------------
+
+N=1000;
+# scale_domain = 5
+# translate_startpoint = -5
+
+scale_domain = 5
+translate_startpoint = -1.8
+
+
+# T = np.linspace(-sstar*(q12+2*q3)/(2*q2), sstar*(2*q2)/(q12+2*q3), num=N)
+T = np.linspace(-sstar*(q12+2*q3)/(2*q2)*scale_domain + translate_startpoint, sstar*(2*q2)/(q12+2*q3)*scale_domain , num=N)
+# T = np.linspace(-2,2, num=N)
+# print('T:', T)
+
+print('T.min():', T.min())
+print('T.max():', T.max())
+
+kappas = []
+alphas = []
+# G.append(float(s[0]))
+
+G_container = []
+abar_container = []
+
+
+abar_tmp = abar
+
+for t in T :
+	abar_current = sstar*abar+t*abarperp;
+    # print('abar_current', abar_current)
+	abar_current[abar_current < 1e-10] = 0
+	# print('abar_current', abar_current)
+	# G = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+	G = [abar_current[0], abar_current[1] , (2*abar_current[0]*abar_current[1])**0.5 ]
+	# print('type of G', type(G))
+	# print('G', G)
+	G_container.append(G)
+	abar_container.append(abar_current)
+	e = [(abar_current[0]/(abar_current[0]+abar_current[1]))**0.5, (abar_current[1]/(abar_current[0]+abar_current[1]))**0.5]
+	kappa = abar_current[0]+abar_current[1]
+	alpha = math.atan2(e[1], e[0])
+	# print('angle current:', alpha)
+	kappas.append(kappa)
+	alphas.append(alpha)
+
+
+alphas = np.array(alphas)
+kappas = np.array(kappas)
+
+# print('G_container', G_container)
+G = np.array(G_container)
+abar = np.array(abar_container)
+
+print('G', G)
+print('abar', abar)
+print('abar.shape',abar.shape)
+
+
+
+
+
+print('q1 = ', q1)
+print('q2 = ', q2)
+print('q3 = ', q3)
+print('q12 = ', q12)
+print('b1 = ', b1)
+print('b2 = ', b2)
+
+num_Points = 20
+num_Points = 50
+num_Points = 200
+
+# Creating dataset
+x = np.linspace(-5,5,num_Points)
+y = np.linspace(-5,5,num_Points)
+
+x = np.linspace(-20,20,num_Points)
+y = np.linspace(-20,20,num_Points)
+
+# x = np.linspace(-10,10,num_Points)
+# y = np.linspace(-10,10,num_Points)
+
+# x = np.linspace(-60,60,num_Points)
+# y = np.linspace(-60,60,num_Points)
+#
+#
+# x = np.linspace(-40,40,num_Points)
+# y = np.linspace(-40,40,num_Points)
+
+
+range = 2
+
+x_1 = np.linspace(0,range,num_Points)
+y_1 = np.linspace(0,range,num_Points)
+x_2 = np.linspace(-range,0,num_Points)
+y_2 = np.linspace(-range,0,num_Points)
+
+
+X_1,Y_1 = np.meshgrid(x_1,y_1)
+X_2,Y_2 = np.meshgrid(x_2,y_2)
+
+
+a1, a2 = np.meshgrid(x,y)
+
+# geyser = sns.load_dataset("geyser")
+# print('type of geyser:', type(geyser))
+# print('geyser:',geyser)
+
+ContourRange=20
+
+x_in = np.linspace(-ContourRange,ContourRange,num_Points)
+y_in = np.linspace(-ContourRange,ContourRange,num_Points)
+a1_in, a2_in = np.meshgrid(x_in,y_in)
+
+# print('a1:', a1)
+# print('a2:',a2 )
+#
+# print('a1.shape', a1.shape)
+
+#-- FILTER OUT VALUES for G+ :
+
+tmp1 = a1[np.where(a1*a2 >= 0)]
+tmp2 = a2[np.where(a1*a2 >= 0)]
+
+# tmp1 = a1[a1*a2 >= 0]
+# tmp2 = a2[a1*a2 >= 0]
+
+# tmp1 = a1[np.where(a1>=0 and a2 >= 0)]
+# tmp2 = a2[np.where(a1>=0 and a2 >= 0)]
+
+
+# tmp1 = tmp1[np.where(a1 >= 0)]
+# tmp2 = tmp2[np.where(a1 >= 0)]
+
+# tmp1_pos = a1[np.where(a1*a2 >= 0)]
+# tmp2_neg = a2[np.where(a1*a2 >= 0)]
+
+
+
+print('tmp1.shape',tmp1.shape)
+print('tmp1.shape[0]',tmp1.shape[0])
+print('tmp2.shape',tmp2.shape)
+print('tmp2.shape[0]',tmp2.shape[0])
+
+
+
+tmp1 = tmp1.reshape(-1,int(tmp1.shape[0]/2))
+tmp2 = tmp2.reshape(-1,int(tmp2.shape[0]/2))
+
+print('tmp1.shape',tmp1.shape)
+print('tmp1.shape[0]',tmp1.shape[0])
+print('tmp2.shape',tmp2.shape)
+print('tmp2.shape[0]',tmp2.shape[0])
+
+# np.take(a, np.where(a>100)[0], axis=0)
+# tmp1 = np.take(a1, np.where(a1*a2 >= 0)[0], axis=0)
+# tmp2 = np.take(a1, np.where(a1*a2 >= 0)[0], axis=0)
+# tmp2 = a2[np.where(a1*a2 >= 0)]
+
+# tmp1 = a1[a1*a2 >= 0]
+# tmp2 = a2[a1*a2 >= 0]
+
+
+# tmp1_pos = a1[np.where(a1*a2 >= 0) ]
+# tmp2_pos = a2[np.where(a1*a2 >= 0) ]
+# tmp1_pos = tmp1_pos[np.where(tmp1_pos  >= 0)]
+# tmp2_pos = tmp2_pos[np.where(tmp2_pos  >= 0)]
+
+# tmp1_neg = a1[a1*a2 >= 0 ]
+# tmp2_neg = a2[a1*a2 >= 0 ]
+# tmp1_neg = tmp1_neg[tmp1_neg  < 0]
+# tmp2_neg = tmp2_neg[tmp2_neg  < 0]
+# a1 = tmp1
+# a2 = tmp2
+#
+# a1 = a1.reshape(-1,5)
+# a2 = a2.reshape(-1,5)
+
+# tmp1_pos = tmp1_pos.reshape(-1,5)
+# tmp2_pos = tmp2_pos.reshape(-1,5)
+# tmp1_neg = tmp1_neg.reshape(-1,5)
+# tmp2_neg = tmp2_neg.reshape(-1,5)
+
+
+# print('a1:', a1)
+# print('a2:',a2 )
+# print('a1.shape', a1.shape)
+
+
+
+
+
+energyVec = np.vectorize(energy)
+
+# Z = energyVec(np.array([a1,a2]),q1,q2,q12,q3,b1,b2)
+# Z = energyVec(a1,a2,q1,q2,q12,q3,b1,b2)
+#
+# Z_in = energyVec(a1_in,a2_in,q1,q2,q12,q3,b1,b2)
+
+
+
+
+# Z = (tmp2**2)/tmp1
+Z = np.sqrt(tmp1*tmp2)
+
+
+Z1 = np.sqrt(X_1*Y_1)
+Z2 = np.sqrt(X_2*Y_2)
+
+# Z_bar = np.sqrt(abar[0,:]*abar[1,:])
+Z_bar = (abar[0,:]*abar[1,:])**0.5*abar
+
+abar = abar.T
+
+
+
+v1 = abar[0,:]
+v2 = abar[1,:]
+
+# print('a1:', a1)
+# print('a2:',a2 )
+# print('a1.shape', a1.shape)
+
+
+evaluateVec = np.vectorize(evaluate)
+Z_bar = evaluateVec(abar[0,:],abar[1,:])
+# Z = np.sqrt(np.multiply(tmp1,tmp2))
+# Z = np.sqrt(a1*a2)
+
+
+print('v1.shape', v1.shape)
+print('v1', v1)
+
+
+
+
+print('Z:', Z)
+print('Z_bar:', Z_bar)
+# print('any', np.any(Z<0))
+
+#
+
+
+# negZ_a1 = a1[np.where(Z<0)]
+# negZ_a2 = a2[np.where(Z<0)]
+# negativeValues = Z[np.where(Z<0)]
+# print('negativeValues:',negativeValues)
+#
+# print('negZ_a1',negZ_a1)
+# print('negZ_a2',negZ_a2)
+#
+#
+# negZ_a1 = negZ_a1.reshape(-1,5)
+# negZ_a2 = negZ_a2.reshape(-1,5)
+# negativeValues = negativeValues.reshape(-1,5)
+#
+# Z_pos =  energyVec(tmp1_pos,tmp2_pos,q1,q2,q12,q3,b1,b2)
+# Z_neg = energyVec(tmp1_neg,tmp2_neg,q1,q2,q12,q3,b1,b2)
+
+
+
+
+
+# print('Test energy:' , energy(np.array([1,1]),q1,q2,q12,q3,b1,b2))
+
+
+
+
+# print('Z_pos.shape', Z_pos.shape)
+
+
+
+
+
+
+
+## -- PLOT :
+mpl.rcParams['text.usetex'] = True
+mpl.rcParams["font.family"] = "serif"
+mpl.rcParams["font.size"] = "9"
+
+label_size = 8
+mpl.rcParams['xtick.labelsize'] = label_size
+mpl.rcParams['ytick.labelsize'] = label_size
+
+# plt.style.use('seaborn')
+plt.style.use('seaborn-whitegrid')
+# sns.set()
+# plt.style.use('seaborn-whitegrid')
+
+label_size = 9
+mpl.rcParams['xtick.labelsize'] = label_size
+mpl.rcParams['ytick.labelsize'] = label_size
+
+width = 6.28 *0.5
+# width = 6.28
+height = width / 1.618
+height = width
+fig = plt.figure()
+
+ax = plt.axes(projection ='3d', adjustable='box')
+# ax = plt.axes((0.17,0.21 ,0.75,0.75))
+# ax = plt.axes((0.15,0.18,0.8,0.8))
+# ax.tick_params(axis='x',which='major', direction='out',pad=5)
+# ax.tick_params(axis='y',which='major', length=3, width=1, direction='out',pad=3)
+# ax.xaxis.set_major_locator(MultipleLocator(0.1))
+# ax.xaxis.set_minor_locator(MultipleLocator(0.05))
+# ax.xaxis.set_major_locator(plt.MultipleLocator(np.pi / 8))
+# ax.xaxis.set_minor_locator(plt.MultipleLocator(np.pi / 16))
+# ax.xaxis.set_major_locator(plt.MultipleLocator(np.pi / 2))
+# ax.xaxis.set_minor_locator(plt.MultipleLocator(np.pi / 4))
+# ax.xaxis.set_major_formatter(plt.FuncFormatter(format_func))
+# ax.grid(True,which='major',axis='both',alpha=0.3)
+ax.grid(True,which='major',axis='xy',alpha=0.3)
+# ax.grid(False,which='major',alpha=0.3)
+# Hide grid lines
+# ax.grid(False)
+
+
+
+# colorfunction=(B*kappa)
+# print('colofunction',colorfunction)
+
+#translate Data
+# Z = Z - (Z.max()-Z.min())/2
+# Z = Z - 50
+# Z = Z - 500
+#
+# Z = Z.T
+
+
+# Substract constant:
+# c = (b1**2)*q1+b1*b2*q12+(b2**2)*q2
+# Z = Z-c
+
+# print('Value of c:', c)
+
+
+
+# print('Z.min()', Z.min())
+# print('Z.max()', Z.max())
+# norm=mcolors.Normalize(Z.min(),Z.max())
+# facecolors=cm.brg(norm)
+
+
+# print('norm:', norm)
+# print('type of norm', type(norm))
+# print('norm(0):', norm(0))
+# print('norm(Z):', norm(Z))
+
+# ax.plot(theta_rho, theta_values, 'royalblue', zorder=3, )
+
+# ax.scatter(a1,a2, s=0.5)
+
+# ax.scatter(tmp1_pos,tmp2_pos, s=0.5)
+# ax.scatter(tmp1_neg,tmp2_neg, s=0.5)
+
+# CS = ax.contour(a1, a2, Z,10, cmap=plt.cm.gnuplot, levels=100 )
+# CS = ax.contour(a1, a2, Z,10, cmap=plt.cm.gnuplot,  levels=20 )
+
+
+# sns.kdeplot(np.array([a1, a2, Z]))
+# sns.kdeplot(tmp1_pos,tmp2_pos,Z_pos)
+
+# levels = [-5.0, -4, -3, 0.0, 1.5, 2.5, 3.5]
+# CS = ax.contour(a1, a2, Z,10, cmap=plt.cm.gnuplot, corner_mask=True,levels=levels)
+# CS = ax.contour(a1, a2, Z, cmap=plt.cm.gnuplot(norm(Z)), corner_mask=True)
+# CS = ax.contour(a1, a2, Z, cm.brg(norm(Z)), levels=20)
+# CS = ax.contour(a1, a2, Z, cmap=plt.cm.gnuplot, levels=20)
+# CS = ax.contour(a1, a2, Z, colors='k', levels=14,  linewidths=(0.5,))
+# CS = ax.contour(a1, a2, Z, colors='k', levels=18,  linewidths=(0.5,))
+
+# ax.contour(negZ_a1, negZ_a2, negativeValues, colors='k',  linewidths=(0.5,))
+# CS =  ax.contour(a1_in, a2_in, Z_in, colors='k',  linewidths=(0.5,))
+
+
+
+# df = pd.DataFrame(data=Z_in, columns=a1_in, index=a2_in)
+# df2 = pd.DataFrame(np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]),
+#                    columns=['a', 'b', 'c'])
+
+
+
+
+# sns.kdeplot(data=df2, x="waiting", y="duration")
+# sns.kdeplot(data=df2)
+
+# CS = ax.contour(a1, a2, Z, colors='k',   linewidths=(0.5,))
+
+# CS = ax.contour(a1, a2, Z,10, cmap=plt.cm.gnuplot, extend='both', levels=50)
+# CS = ax.contourf(a1, a2, Z,10, colors='k', extend='both', levels=50)
+# CS = ax.contourf(a1, a2, Z,10, colors='k')
+#
+# # CS = ax.contour(tmp1_pos,tmp2_pos, Z_pos,10, cmap=plt.cm.gnuplot, levels=10 )
+# # CS = ax.contour(tmp1_pos,tmp2_pos, Z_pos,10, cmap=plt.cm.gnuplot, corner_mask=True)
+#
+# CS = ax.contour(a1, a2, Z,10,  colors = 'k')
+# ax.clabel(CS, inline=True, fontsize=4)
+
+
+# cmap = cm.brg(norm(Z))
+#
+# C_map = cm.inferno(norm(Z))
+
+# ax.imshow(Z, cmap=C_map, extent=[-20, 20, -20, 20], origin='lower', alpha=0.5)
+
+# ax.imshow(norm(Z), extent=[-20, 20, -20, 20], origin='lower',
+#                   cmap='bwr', alpha=0.8)
+
+# ax.imshow(norm(Z), extent=[-20, 20, -20, 20],origin='lower', vmin=Z.min(), vmax=Z.max(),
+#                   cmap='bwr', alpha=0.6)
+
+# ax.imshow(norm(Z), extent=[-20, 20, -20, 20],origin='lower', norm = norm,
+#                   cmap='coolwarm', alpha=0.6)
+
+
+cmap=mpl.cm.RdBu_r
+# cmap=mpl.cm.viridis_r
+cmap=mpl.cm.bwr
+# # cmap=mpl.cm.coolwarm
+# # cmap=mpl.cm.gnuplot
+# cmap=mpl.cm.viridis
+# cmap=mpl.cm.inferno
+cmap=mpl.cm.Blues
+# cmap=mpl.cm.magma
+# cmap=mpl.cm.cividis
+# cmap=mpl.cm.gnuplot
+# cmap=mpl.cm.gnuplot
+cmap = mpl.colors.ListedColormap(["royalblue"], name='from_list', N=None)
+# m = cm.ScalarMappable(norm=norm, cmap=cmap)
+# m = cm.ScalarMappable(cmap=cmap)
+
+# cmap = cm.brg(Z)
+# divnorm=mcolors.TwoSlopeNorm(vmin=Z.min(), vcenter=0., vmax=Z.max())
+
+# ax.imshow(Z, extent=[-20, 20, -20, 20],origin='lower', norm = norm,
+#                   cmap='coolwarm', alpha=0.6)
+
+# ax.imshow(Z, extent=[-20, 20, -20, 20],origin='lower',
+#                   cmap='coolwarm', alpha=0.6)
+# ax.imshow(Z, extent=[-20, 20, -20, 20],origin='lower',
+#                   cmap=cmap, alpha=0.6)
+
+# divnorm=mcolors.TwoSlopeNorm(vmin=Z.min(), vcenter=0., vmax=Z.max())
+# plt.imshow(Z, extent=[x.min(), x.max(), y.min(), y.max()],origin='lower',
+#                   cmap=cmap, alpha=0.6)
+
+# plt.imshow(Z, extent=[x.min(), x.max(), y.min(), y.max()],origin='lower', norm = divnorm,
+#                   cmap=cmap, alpha=0.6)
+
+
+
+
+# COLORBAR :
+# cbar = plt.colorbar()
+# cbar.ax.tick_params(labelsize=8)
+
+
+
+
+# ##----- ADD RECTANGLE TO COVER QUADRANT :
+# epsilon = 0.4
+# epsilon = 0.1
+# # ax.axvspan(0, x.max(), y.min(), 0, alpha=1, color='yellow', zorder=5)#yellow
+# # ax.fill_between([0, x.max()], y.min(), 0, alpha=0.3, color='yellow', zorder=5)#yellow
+# # ax.fill_between([x.min(), 0], 0, y.max(), alpha=0.3, color='yellow', zorder=5)#yellow
+# ax.fill_between([0+epsilon, x.max()], y.min(), 0-epsilon, alpha=0.7, color='gray', zorder=5)#yellow
+# ax.fill_between([x.min(), 0-epsilon], 0+epsilon, y.max(), alpha=0.7, color='gray', zorder=5)#yellow
+
+
+
+
+print('abar', abar)
+print('abar.shape',abar.shape)
+
+line = ax.plot(abar[0,:],abar[1,:],Z_bar, linewidth=2, color='coral', zorder=1)
+# CS = ax.contour(X_1,Y_1,Z1, colors='k', levels=18,  linewidths=(0.5,))
+
+start = np.array([abar[0,499],abar[1,499],Z_bar[499]])
+end = np.array([abar[0,500],abar[1,500],Z_bar[500]])
+
+
+
+
+
+# idx = np.where(np.round(Z_bar,3) == np.round( 0.03581463,3) )
+idx = np.where(np.round(Z_bar,3) == np.round( 0.02823972,3) )
+print('idx[0][0]', idx[0][0])
+
+# abar_1 = abar[0,0:idx[0][0]]
+# abar_2 = abar[1,0:idx[0][0]]
+line = ax.plot(abar[0,idx[0][0]:-1],abar[1,idx[0][0]:-1],Z_bar[idx[0][0]:-1], linewidth=2, color='coral', zorder=5)
+
+# ax.plot_surface(a1,a2, Z, cmap=cm.coolwarm,
+#                        linewidth=0, antialiased=False)
+
+# ax.plot_surface(tmp1,tmp2, Z, cmap=cm.coolwarm,
+#                        linewidth=0, antialiased=False)
+
+# ax.scatter(X_1,Y_1,Z1, s=0.2)
+# ax.scatter(X_2,Y_2,Z2, s=0.2)
+
+
+# X = np.concatenate((X_1, X_2), axis=0)
+# Y = np.concatenate((Y_1, Y_2), axis=0)
+# Z = np.concatenate((Z1, Z2), axis=0)
+# ax.plot_surface(X,Y,Z)
+
+
+ax.plot_surface(X_1,Y_1,Z1 ,cmap=cmap,
+                       linewidth=0, antialiased=True,alpha=.35, zorder=5)
+ax.plot_surface(X_2,Y_2,Z2 ,cmap=cmap,
+                       linewidth=0, antialiased=True,alpha=.35, zorder=5)
+# ax.plot_surface(X_1,Y_1,Z1 , facecolor = 'lightblue',     #cmap=cmap,
+#                        linewidth=0, antialiased=True, alpha=1, zorder=5)
+# ax.plot_surface(X_2,Y_2,Z2 , facecolor = 'lightblue', edgecolor='none',    #cmap=cmap,
+#                        linewidth=0, antialiased=True, alpha=1, zorder=5)
+
+# ax.plot_surface(X_1,Y_1,Z1 , #color='C0',
+# 							rstride=1, cstride=1,linewidth=0, antialiased=True, alpha=1, zorder=5)
+
+
+
+
+# ax.plot_surface(X_2,Y_2,Z2 , #color='C0',
+# 							rstride=1, cstride=1,linewidth=0,  alpha=0.8, zorder=5, shade=True)
+# ax.plot_surface(X_2,Y_2,Z2)
+
+# X_2 = X_2.reshape(-1,1).flatten()
+# Y_2 = Y_2.reshape(-1,1).flatten()
+# Z2 = Z2.reshape(-1,1).flatten()
+#
+# ax.plot_trisurf(X_2,Y_2,Z2, color='blue' )
+
+
+# X_1 = X_1.reshape(-1,1).flatten()
+# Y_1 = Y_1.reshape(-1,1).flatten()
+# Z1 = Z1.reshape(-1,1).flatten()
+# ax.plot_trisurf(X_1,Y_1,Z1 , color='blue')
+
+
+### MAYAVI TEST
+# mlab.figure(bgcolor=(1.0, 1.0, 1.0), size=(1000,1000))
+# mlab.view(azimuth=90, elevation=125)
+# mlab.view(azimuth=100, elevation=115)
+# axes = mlab.axes(color=(0, 0, 0), nb_labels=5)
+# mlab.orientation_axes()
+# mlab.mesh(X_1, Y_1,Z1, color=(0,0,1) ,  transparent=True )
+# mlab.plot3d(abar[0,:],abar[1,:],Z_bar, line_width=1)
+# mlab.mesh(X_2, Y_2,Z2)
+# mlab.savefig("./example.png")
+### --------------------------------------------
+
+
+
+# ax.plot_surface(X_1,Y_1,Z1 , cmap=cmap,
+#                        linewidth=0, antialiased=False,alpha=1, zorder=5)
+# ax.plot_surface(X_2,Y_2,Z2 , cmap=cmap,
+#                        linewidth=0, antialiased=True,alpha=1, zorder=5)
+
+# ax.plot_surface(X_2,Y_2,Z2 , color = 'lightblue',     #cmap=cmap,
+#                        linewidth=0, antialiased=True, alpha=1, zorder=5)
+
+
+# ax.plot(G[0,:],G[1,:],G[2,:])
+# ax.plot(abar[0,:],abar[1,:],Z_bar, linewidth=2, color='yellow', linestyle='--')
+# ax.scatter(abar[0,:],abar[1,:],Z_bar,  color='purple', zorder=5)
+# ax.plot(abar[0,:],abar[1,:],Z_bar, linewidth=2, color='royalblue', linestyle='--')
+# ax.plot(abar[0,:],abar[1,:],Z_bar, linewidth=3, color='dodgerblue', linestyle='--')
+# ax.plot(abar[0,:],abar[1,:],Z_bar, linewidth=3, color='cornflowerblue', linestyle='--')
+# ax.plot(abar[0,:],abar[1,:],Z_bar, linewidth=3, color='darkorange', linestyle='--')
+# ax.plot(abar[0,:],abar[1,:],Z_bar, linewidth=3, color='yellow', linestyle='--')
+# line = ax.plot(abar[0,:],abar[1,:],Z_bar, linewidth=1, color='coral', linestyle='--', zorder=3)
+
+
+# plot starting point:
+# ax.scatter(abar[0,0],abar[1,0],Z_bar[0], marker='^',  s=30, color='black', zorder=5)
+#
+#
+# ax.scatter(abar[0,500],abar[1,500],Z_bar[500], marker='^',  s=30, color='purple', zorder=5)
+
+# ax.scatter(start[0],start[1],start[2], marker='^',  s=30, color='purple', zorder=5)
+# ax.scatter(end[0],end[1],end[2], marker='^',  s=30, color='purple', zorder=5)
+
+
+# define origin
+o = np.array([0,0,0])
+
+start = np.array([1,0,0])
+end = np.array([2.5,0,0])
+
+
+print('start:', start)
+print('end:', end)
+
+
+dir = end-start
+print('dir:', dir)
+# ax.arrow()
+
+# ax.arrow3D(start[0],start[1],start[2],
+#            dir[0],dir[1],dir[2],
+#            mutation_scale=10,
+#            arrowstyle="->",
+#            linestyle='dashed',fc='coral',
+#            lw = 1,
+#            ec ='coral',
+#            zorder=3)
+
+# ax.arrow3D(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],
+#            normal[0],normal[1],normal[2],
+#            mutation_scale=15,
+#             lw = 1.5,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='blue',
+#            ec ='blue',
+#            zorder = 5)
+
+
+# ax.arrow3D(start[0],start[1],start[2],
+#            dir[0],dir[1],dir[2],
+#            mutation_scale=20,
+#            arrowstyle="->",
+#            fc='coral',
+#            lw = 1,
+#            ec ='coral',
+#            zorder=3)
+# ax.arrow3D(start[0],start[1],start[2],
+#            dir[0],dir[1],dir[2],
+#            mutation_scale=20,
+#            arrowstyle="->",
+#            fc='coral',
+#            lw = 1,
+#            ec ='coral',
+#            zorder=3)
+
+arrow_prop_dict = dict(mutation_scale=20, arrowstyle='-|>', color='k', shrinkA=0, shrinkB=0)
+# style = ArrowStyle('Fancy', head_length=1, head_width=1.5, tail_width=0.5)
+
+
+# ADD ARROW:
+# a = Arrow3D([start[0], end[0]], [start[1], end[1]], [start[2], end[2]], mutation_scale=15, arrowstyle='-|>', color='darkorange')
+# ax.add_artist(a)
+
+## ADD Annotation
+ax.text(0, 0, 1.5, r"$\mathcal G^+$", color='royalblue', size=12)
+# ax.text(0.5, 0.5, "Test")
+# ax.text(9, 0, 0, "red", color='red')
+
+### ---- Check proof:
+# value at t = 0:
+abar_zero= sstar*abar_tmp
+# value_0 = [abar_zero[0], abar_zero[1] , (2*abar_zero[0]*abar_zero[1])**0.5 ]
+value_0 = evaluate(abar_zero[0], abar_zero[1])
+print('value_0', value_0)
+# ax.scatter(value_0[0],value_0[1],value_0[2], marker='x',  s=20, color='dodgerblue', zorder=5)
+# ax.scatter(abar_zero[0], abar_zero[1],value_0, marker='o',  s=30, color='dodgerblue', zorder=5)
+## -----------------------------
+
+
+
+
+
+
+
+
+
+
+# ax.scatter(tmp1,tmp2, Z, cmap=cm.coolwarm,
+#                        linewidth=0, antialiased=False)
+# ax.plot_surface(tmp1,Z, tmp2, cmap=cm.coolwarm,
+#                        linewidth=0, antialiased=False)
+# ax.plot_trisurf(tmp1,tmp2, Z, cmap=cm.coolwarm,
+#                        linewidth=0, antialiased=False)
+
+
+# ax.plot(theta_rho, energy_axial1, 'royalblue', zorder=3, label=r"axialMin1")
+# ax.plot(theta_rho, energy_axial2, 'forestgreen', zorder=3, label=r"axialMin2")
+# ax.plot(-1.0*alphas, kappas, 'red', zorder=3, )
+
+
+
+
+# lg = ax.legend(bbox_to_anchor=(0.0, 0.75), loc='upper left')
+
+
+
+
+### PLOT X AND Y AXIS:
+# ax.plot(ax.get_xlim(),[0,0],'k--', linewidth=0.5)
+# ax.plot([0,0],ax.get_ylim(), 'k--', linewidth=0.5)
+ax.plot(ax.get_xlim(),[0,0],'k--', linewidth=1 ,zorder=5)
+ax.plot([0,0],ax.get_ylim(), 'k--', linewidth=1)
+
+
+ax.set_xlabel(r"$a_1$", fontsize=10 ,labelpad=0)
+ax.set_ylabel(r"$a_2$", fontsize=10 ,labelpad=0)
+
+
+# ax.get_xaxis().set_visible(False)
+# ax = plt.gca(projection="3d")
+# ax._axis3don = False
+ZL = ax.get_zgridlines()
+
+# ax.set_ylabel(r"energy")
+
+
+# ax.set_xticks([-np.pi/2, -np.pi/4  ,0,  np.pi/4,  np.pi/2 ])
+# labels = ['$0$',r'$\pi/8$', r'$\pi/4$' ,r'$3\pi/8$' , r'$\pi/2$']
+# ax.set_yticklabels(labels)
+
+
+
+
+
+# ax.legend(loc='upper right')
+
+
+
+fig.set_size_inches(width, height)
+fig.savefig('1-ParameterFamily_G+.pdf')
+
+plt.show()

Python-Scripts/1-ParameterFamily_G+_v4.py

+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
+
+import matplotlib as mpl
+from matplotlib.ticker import MultipleLocator,FormatStrFormatter,MaxNLocator
+import pandas as pd
+
+import seaborn as sns
+import matplotlib.colors as mcolors
+
+
+from mpl_toolkits.mplot3d.proj3d import proj_transform
+from mpl_toolkits.mplot3d import proj3d
+# from mpl_toolkits.mplot3d.axes3d import Axes3D
+from matplotlib.text import Annotation
+from matplotlib.patches import FancyArrowPatch
+
+
+import mayavi.mlab as mlab
+from mayavi.api import OffScreenEngine
+mlab.options.offscreen = True
+
+from chart_studio import plotly
+import plotly.graph_objs as go
+# from matplotlib import rc
+# rc('text', usetex=True) # Use LaTeX font
+#
+# import seaborn as sns
+# sns.set(color_codes=True)
+
+# set the colormap and centre the colorbar
+class MidpointNormalize(mcolors.Normalize):
+	"""
+	Normalise the colorbar so that diverging bars work there way either side from a prescribed midpoint value)
+
+	e.g. im=ax1.imshow(array, norm=MidpointNormalize(midpoint=0.,vmin=-100, vmax=100))
+	"""
+	def __init__(self, vmin=None, vmax=None, midpoint=None, clip=False):
+		self.midpoint = midpoint
+		mcolors.Normalize.__init__(self, vmin, vmax, clip)
+
+	def __call__(self, value, clip=None):
+		# I'm ignoring masked values and all kinds of edge cases to make a
+		# simple example...
+		x, y = [self.vmin, self.midpoint, self.vmax], [0, 0.5, 1]
+		return np.ma.masked_array(np.interp(value, x, y), np.isnan(value))
+
+
+
+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 == -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)
+    ##find number of multiples of pi/2
+    N = int(np.round(4 * value / np.pi))
+    if N == 0:
+        return "0"
+    elif N == 1:
+        return r"$\pi/4$"
+    elif N == -1:
+        return r"$-\pi/4$"
+    elif N == 2:
+        return r"$\pi/2$"
+    elif N == -2:
+        return r"$-\pi/2$"
+    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
+
+
+
+def energy(a1,a2,q1,q2,q12,q3,b1,b2):
+
+
+    a = np.array([a1,a2])
+    b = np.array([b1,b2])
+    H = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+    A = np.array([[q1,1/2*q12], [1/2*q12,q2] ])
+
+
+    tmp = H.dot(a)
+
+    # print('H',H)
+    # print('A',A)
+    # print('b',b)
+    # print('a',a)
+    # print('tmp',tmp)
+
+    tmp = (1/2)*a.dot(tmp)
+    # print('tmp',tmp)
+
+    tmp2 = A.dot(b)
+    # print('tmp2',tmp2)
+    tmp2 = 2*a.dot(tmp2)
+
+    # print('tmp2',tmp2)
+    energy = tmp - tmp2
+    # print('energy',energy)
+
+
+    # energy_axial1.append(energy_1)
+
+    return energy
+
+
+
+def evaluate(x,y):
+
+	# (abar[0,:]*abar[1,:])**0.5
+
+	return np.sqrt(x*y)
+
+
+# def energy(a1,a2,q1,q2,q12,q3,b1,b2):
+#
+#
+#     b = np.array([b1,b2])
+#     H = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+#     A = np.array([[q1,1/2*q12], [1/2*q12,q2] ])
+#
+#
+#     tmp = H.dot(a)
+#
+#     print('H',H)
+#     print('A',A)
+#     print('b',b)
+#     print('a',a)
+#     print('tmp',tmp)
+#
+#     tmp = (1/2)*a.dot(tmp)
+#     print('tmp',tmp)
+#
+#     tmp2 = A.dot(b)
+#     print('tmp2',tmp2)
+#     tmp2 = 2*a.dot(tmp2)
+#
+#     print('tmp2',tmp2)
+#     energy = tmp - tmp2
+#     print('energy',energy)
+#
+#
+#     # energy_axial1.append(energy_1)
+#
+#     return energy
+#
+
+def add_arrow(line, position=None, direction='right', size=15, color=None):
+    """
+    add an arrow to a line.
+
+    line:       Line2D object
+    position:   x-position of the arrow. If None, mean of xdata is taken
+    direction:  'left' or 'right'
+    size:       size of the arrow in fontsize points
+    color:      if None, line color is taken.
+    """
+    if color is None:
+        color = line.get_color()
+
+    xdata = line.get_xdata()
+    ydata = line.get_ydata()
+
+    if position is None:
+        position = xdata.mean()
+    # find closest index
+    start_ind = np.argmin(np.absolute(xdata - position))
+    if direction == 'right':
+        end_ind = start_ind + 1
+    else:
+        end_ind = start_ind - 1
+
+    line.axes.annotate('',
+        xytext=(xdata[start_ind], ydata[start_ind]),
+        xy=(xdata[end_ind], ydata[end_ind]),
+        arrowprops=dict(arrowstyle="->", color=color),
+        size=size
+    )
+
+
+
+class Annotation3D(Annotation):
+    def __init__(self, text, xyz, *args, **kwargs):
+        super().__init__(text, xy=(0, 0), *args, **kwargs)
+        self._xyz = xyz
+
+    def draw(self, renderer):
+        x2, y2, z2 = proj_transform(*self._xyz, self.axes.M)
+        self.xy = (x2, y2)
+        super().draw(renderer)
+
+def _annotate3D(ax, text, xyz, *args, **kwargs):
+    '''Add anotation `text` to an `Axes3d` instance.'''
+
+    annotation = Annotation3D(text, xyz, *args, **kwargs)
+    ax.add_artist(annotation)
+
+setattr(Axes3D, 'annotate3D', _annotate3D)
+
+
+
+class Arrow3D(FancyArrowPatch):
+    def __init__(self, xs, ys, zs, *args, **kwargs):
+        FancyArrowPatch.__init__(self, (0,0), (0,0), *args, **kwargs)
+        self._verts3d = xs, ys, zs
+
+    def draw(self, renderer):
+        xs3d, ys3d, zs3d = self._verts3d
+        xs, ys, zs = proj3d.proj_transform(xs3d, ys3d, zs3d, renderer.M)
+        self.set_positions((xs[0],ys[0]),(xs[1],ys[1]))
+        FancyArrowPatch.draw(self, renderer)
+
+
+def _arrow3D(ax, x, y, z, dx, dy, dz, *args, **kwargs):
+    '''Add an 3d arrow to an `Axes3D` instance.'''
+
+    arrow = Arrow3D(x, y, z, dx, dy, dz, *args, **kwargs)
+    ax.add_artist(arrow)
+
+setattr(Axes3D, 'arrow3D', _arrow3D)
+
+################################################################################################################
+################################################################################################################
+################################################################################################################
+
+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: -----')
+
+# q1=1;
+# q2=2;
+# q12=1/2;
+# q3=((4*q1*q2)**0.5-q12)/2;
+# # H=[2*q1,q12+2*q3;q12+2*q3,2*q2];
+#
+# H = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+# A = np.array([[q1,1/2*q12], [1/2*q12,q2] ])
+# abar = np.array([q12+2*q3, 2*q2])
+# abar = (1.0/math.sqrt((q12+2*q3)**2+(2*q2)**2))*abar
+#
+# print('abar:',abar)
+#
+# b = np.linalg.lstsq(A, abar)[0]
+# print('b',b)
+#
+#
+# # print('abar:',np.shape(abar))
+# # print('np.transpose(abar):',np.shape(np.transpose(abar)))
+# sstar = (1/(q1+q2))*abar.dot(A.dot(b))
+# # sstar = (1/(q1+q2))*abar.dot(tmp)
+# print('sstar', sstar)
+# abarperp= np.array([abar[1],-abar[0]])
+# print('abarperp:',abarperp)
+
+
+# -------------------------- Input Parameters --------------------
+
+mu1 = 1.0
+rho1 = 1.0
+alpha = 5.0
+theta = 1.0/2
+# theta= 0.1
+beta = 5.0
+
+
+
+# mu1 = 1.0
+# rho1 = 1.0
+# alpha = 2.0
+# theta = 1.0/2
+# # theta= 0.1
+# beta = 5.0
+
+
+#Figure3:
+# mu1 = 1.0
+# rho1 = 1.0
+# alpha = 2.0
+# theta = 1.0/8
+# # theta= 0.1
+# beta = 2.0
+
+
+# alpha= -5
+
+
+#set gamma either to 1. '0' 2. 'infinity' or 3. a numerical positive value
+gamma = '0'
+gamma = 'infinity'
+
+
+lambda1 = 0.0
+
+
+print('---- Input parameters: -----')
+print('mu1: ', mu1)
+print('rho1: ', rho1)
+# print('alpha: ', alpha)
+print('beta: ', beta)
+# print('theta: ', theta)
+print('gamma:', gamma)
+
+print('lambda1: ', lambda1)
+print('----------------------------')
+# ----------------------------------------------------------------
+print('----------------------------')
+
+# ----------------------------------------------------------------
+
+
+
+
+
+
+q1 = (1.0/6.0)*harmonicMean(mu1, beta, theta)
+q2 = (1.0/6.0)*arithmeticMean(mu1, beta, theta)
+q12 = 0.0
+q3 = GetMuGamma(beta, theta,gamma,mu1,rho1,InputFilePath ,OutputFilePath )
+b1 = prestrain_b1(rho1,beta, alpha, theta )
+b2 = prestrain_b2(rho1,beta, alpha, theta )
+
+
+# 1-ParameterFamilyCase:
+
+q1=1;
+q2=2;
+q12=1/2;
+q3=((4*q1*q2)**0.5-q12)/2;
+# H=[2*q1,q12+2*q3;q12+2*q3,2*q2];
+
+H = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+A = np.array([[q1,1/2*q12], [1/2*q12,q2] ])
+abar = np.array([q12+2*q3, 2*q2])
+abar = (1.0/math.sqrt((q12+2*q3)**2+(2*q2)**2))*abar
+
+print('abar:',abar)
+
+b = np.linalg.lstsq(A, abar)[0]
+print('b',b)
+
+b1=b[0]
+b2=b[1]
+
+
+# print('abar:',np.shape(abar))
+# print('np.transpose(abar):',np.shape(np.transpose(abar)))
+sstar = (1/(q1+q2))*abar.dot(A.dot(b))
+# sstar = (1/(q1+q2))*abar.dot(tmp)
+print('sstar', sstar)
+abarperp= np.array([abar[1],-abar[0]])
+print('abarperp:',abarperp)
+
+print('----------------------------')
+
+# ----------------------------------------------------------------
+
+N=1000;
+# scale_domain = 5
+# translate_startpoint = -5
+
+# scale_domain = 5
+# translate_startpoint = -1.8
+
+
+scale_domain = 5
+translate_startpoint = -1.8
+T_line = np.linspace(-sstar*(q12+2*q3)/(2*q2)*scale_domain + translate_startpoint, sstar*(2*q2)/(q12+2*q3)*scale_domain , num=N)
+line_values = []
+for t in T_line :
+    print('sstar*abar+t*abarperp', sstar*abar+t*abarperp)
+    line_values.append(sstar*abar+t*abarperp)
+
+
+
+
+T = np.linspace(-sstar*(q12+2*q3)/(2*q2), sstar*(2*q2)/(q12+2*q3), num=N)
+# T = np.linspace(-sstar*(q12+2*q3)/(2*q2)*scale_domain + translate_startpoint, sstar*(2*q2)/(q12+2*q3)*scale_domain , num=N)
+# T = np.linspace(-2,2, num=N)
+# print('T:', T)
+
+print('T.min():', T.min())
+print('T.max():', T.max())
+
+kappas = []
+alphas = []
+# G.append(float(s[0]))
+
+G_container = []
+abar_container = []
+
+
+abar_tmp = abar
+
+for t in T :
+	abar_current = sstar*abar+t*abarperp;
+    # print('abar_current', abar_current)
+	abar_current[abar_current < 1e-10] = 0
+	# print('abar_current', abar_current)
+	# G = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+	G = [abar_current[0], abar_current[1] , (2*abar_current[0]*abar_current[1])**0.5 ]
+	# print('type of G', type(G))
+	# print('G', G)
+	G_container.append(G)
+	abar_container.append(abar_current)
+	e = [(abar_current[0]/(abar_current[0]+abar_current[1]))**0.5, (abar_current[1]/(abar_current[0]+abar_current[1]))**0.5]
+	kappa = abar_current[0]+abar_current[1]
+	alpha = math.atan2(e[1], e[0])
+	# print('angle current:', alpha)
+	kappas.append(kappa)
+	alphas.append(alpha)
+
+
+alphas = np.array(alphas)
+kappas = np.array(kappas)
+
+# print('G_container', G_container)
+G = np.array(G_container)
+abar = np.array(abar_container)
+
+print('G', G)
+print('abar', abar)
+print('abar.shape',abar.shape)
+
+
+
+
+
+print('q1 = ', q1)
+print('q2 = ', q2)
+print('q3 = ', q3)
+print('q12 = ', q12)
+print('b1 = ', b1)
+print('b2 = ', b2)
+
+num_Points = 20
+num_Points = 50
+num_Points = 200
+
+# Creating dataset
+x = np.linspace(-5,5,num_Points)
+y = np.linspace(-5,5,num_Points)
+
+x = np.linspace(-20,20,num_Points)
+y = np.linspace(-20,20,num_Points)
+
+# x = np.linspace(-10,10,num_Points)
+# y = np.linspace(-10,10,num_Points)
+
+# x = np.linspace(-60,60,num_Points)
+# y = np.linspace(-60,60,num_Points)
+#
+#
+# x = np.linspace(-40,40,num_Points)
+# y = np.linspace(-40,40,num_Points)
+
+
+range = 2
+
+x_1 = np.linspace(0,range,num_Points)
+y_1 = np.linspace(0,range,num_Points)
+x_2 = np.linspace(-range,0,num_Points)
+y_2 = np.linspace(-range,0,num_Points)
+
+
+X_1,Y_1 = np.meshgrid(x_1,y_1)
+X_2,Y_2 = np.meshgrid(x_2,y_2)
+
+
+a1, a2 = np.meshgrid(x,y)
+
+# geyser = sns.load_dataset("geyser")
+# print('type of geyser:', type(geyser))
+# print('geyser:',geyser)
+
+ContourRange=20
+
+x_in = np.linspace(-ContourRange,ContourRange,num_Points)
+y_in = np.linspace(-ContourRange,ContourRange,num_Points)
+a1_in, a2_in = np.meshgrid(x_in,y_in)
+
+# print('a1:', a1)
+# print('a2:',a2 )
+#
+# print('a1.shape', a1.shape)
+
+#-- FILTER OUT VALUES for G+ :
+
+tmp1 = a1[np.where(a1*a2 >= 0)]
+tmp2 = a2[np.where(a1*a2 >= 0)]
+
+# tmp1 = a1[a1*a2 >= 0]
+# tmp2 = a2[a1*a2 >= 0]
+
+# tmp1 = a1[np.where(a1>=0 and a2 >= 0)]
+# tmp2 = a2[np.where(a1>=0 and a2 >= 0)]
+
+
+# tmp1 = tmp1[np.where(a1 >= 0)]
+# tmp2 = tmp2[np.where(a1 >= 0)]
+
+# tmp1_pos = a1[np.where(a1*a2 >= 0)]
+# tmp2_neg = a2[np.where(a1*a2 >= 0)]
+
+
+
+print('tmp1.shape',tmp1.shape)
+print('tmp1.shape[0]',tmp1.shape[0])
+print('tmp2.shape',tmp2.shape)
+print('tmp2.shape[0]',tmp2.shape[0])
+
+
+
+tmp1 = tmp1.reshape(-1,int(tmp1.shape[0]/2))
+tmp2 = tmp2.reshape(-1,int(tmp2.shape[0]/2))
+
+print('tmp1.shape',tmp1.shape)
+print('tmp1.shape[0]',tmp1.shape[0])
+print('tmp2.shape',tmp2.shape)
+print('tmp2.shape[0]',tmp2.shape[0])
+
+# np.take(a, np.where(a>100)[0], axis=0)
+# tmp1 = np.take(a1, np.where(a1*a2 >= 0)[0], axis=0)
+# tmp2 = np.take(a1, np.where(a1*a2 >= 0)[0], axis=0)
+# tmp2 = a2[np.where(a1*a2 >= 0)]
+
+# tmp1 = a1[a1*a2 >= 0]
+# tmp2 = a2[a1*a2 >= 0]
+
+
+# tmp1_pos = a1[np.where(a1*a2 >= 0) ]
+# tmp2_pos = a2[np.where(a1*a2 >= 0) ]
+# tmp1_pos = tmp1_pos[np.where(tmp1_pos  >= 0)]
+# tmp2_pos = tmp2_pos[np.where(tmp2_pos  >= 0)]
+
+# tmp1_neg = a1[a1*a2 >= 0 ]
+# tmp2_neg = a2[a1*a2 >= 0 ]
+# tmp1_neg = tmp1_neg[tmp1_neg  < 0]
+# tmp2_neg = tmp2_neg[tmp2_neg  < 0]
+# a1 = tmp1
+# a2 = tmp2
+#
+# a1 = a1.reshape(-1,5)
+# a2 = a2.reshape(-1,5)
+
+# tmp1_pos = tmp1_pos.reshape(-1,5)
+# tmp2_pos = tmp2_pos.reshape(-1,5)
+# tmp1_neg = tmp1_neg.reshape(-1,5)
+# tmp2_neg = tmp2_neg.reshape(-1,5)
+
+
+# print('a1:', a1)
+# print('a2:',a2 )
+# print('a1.shape', a1.shape)
+
+
+
+
+
+energyVec = np.vectorize(energy)
+
+# Z = energyVec(np.array([a1,a2]),q1,q2,q12,q3,b1,b2)
+# Z = energyVec(a1,a2,q1,q2,q12,q3,b1,b2)
+#
+# Z_in = energyVec(a1_in,a2_in,q1,q2,q12,q3,b1,b2)
+
+
+
+
+# Z = (tmp2**2)/tmp1
+Z = np.sqrt(tmp1*tmp2)
+
+
+Z1 = np.sqrt(X_1*Y_1)
+Z2 = np.sqrt(X_2*Y_2)
+
+# Z_bar = np.sqrt(abar[0,:]*abar[1,:])
+Z_bar = (abar[0,:]*abar[1,:])**0.5*abar
+
+abar = abar.T
+
+
+
+v1 = abar[0,:]
+v2 = abar[1,:]
+
+# print('a1:', a1)
+# print('a2:',a2 )
+# print('a1.shape', a1.shape)
+
+
+evaluateVec = np.vectorize(evaluate)
+Z_bar = evaluateVec(abar[0,:],abar[1,:])
+# Z = np.sqrt(np.multiply(tmp1,tmp2))
+# Z = np.sqrt(a1*a2)
+
+
+print('v1.shape', v1.shape)
+print('v1', v1)
+
+
+
+
+print('Z:', Z)
+print('Z_bar:', Z_bar)
+# print('any', np.any(Z<0))
+
+#
+
+
+# negZ_a1 = a1[np.where(Z<0)]
+# negZ_a2 = a2[np.where(Z<0)]
+# negativeValues = Z[np.where(Z<0)]
+# print('negativeValues:',negativeValues)
+#
+# print('negZ_a1',negZ_a1)
+# print('negZ_a2',negZ_a2)
+#
+#
+# negZ_a1 = negZ_a1.reshape(-1,5)
+# negZ_a2 = negZ_a2.reshape(-1,5)
+# negativeValues = negativeValues.reshape(-1,5)
+#
+# Z_pos =  energyVec(tmp1_pos,tmp2_pos,q1,q2,q12,q3,b1,b2)
+# Z_neg = energyVec(tmp1_neg,tmp2_neg,q1,q2,q12,q3,b1,b2)
+
+
+
+
+
+# print('Test energy:' , energy(np.array([1,1]),q1,q2,q12,q3,b1,b2))
+
+
+
+
+# print('Z_pos.shape', Z_pos.shape)
+
+
+
+
+
+
+
+## -- PLOT :
+mpl.rcParams['text.usetex'] = True
+mpl.rcParams["font.family"] = "serif"
+mpl.rcParams["font.size"] = "9"
+
+label_size = 8
+mpl.rcParams['xtick.labelsize'] = label_size
+mpl.rcParams['ytick.labelsize'] = label_size
+
+# plt.style.use('seaborn')
+plt.style.use('seaborn-whitegrid')
+# sns.set()
+# plt.style.use('seaborn-whitegrid')
+
+label_size = 9
+mpl.rcParams['xtick.labelsize'] = label_size
+mpl.rcParams['ytick.labelsize'] = label_size
+
+width = 6.28 *0.5
+# width = 6.28
+height = width / 1.618
+height = width
+fig = plt.figure()
+
+ax = plt.axes(projection ='3d', adjustable='box')
+# ax = plt.axes((0.17,0.21 ,0.75,0.75))
+# ax = plt.axes((0.15,0.18,0.8,0.8))
+# ax.tick_params(axis='x',which='major', direction='out',pad=5)
+# ax.tick_params(axis='y',which='major', length=3, width=1, direction='out',pad=3)
+# ax.xaxis.set_major_locator(MultipleLocator(0.1))
+# ax.xaxis.set_minor_locator(MultipleLocator(0.05))
+# ax.xaxis.set_major_locator(plt.MultipleLocator(np.pi / 8))
+# ax.xaxis.set_minor_locator(plt.MultipleLocator(np.pi / 16))
+# ax.xaxis.set_major_locator(plt.MultipleLocator(np.pi / 2))
+# ax.xaxis.set_minor_locator(plt.MultipleLocator(np.pi / 4))
+# ax.xaxis.set_major_formatter(plt.FuncFormatter(format_func))
+# ax.grid(True,which='major',axis='both',alpha=0.3)
+ax.grid(True,which='major',axis='xy',alpha=0.3)
+# ax.grid(False,which='major',alpha=0.3)
+# Hide grid lines
+# ax.grid(False)
+
+
+
+# colorfunction=(B*kappa)
+# print('colofunction',colorfunction)
+
+#translate Data
+# Z = Z - (Z.max()-Z.min())/2
+# Z = Z - 50
+# Z = Z - 500
+#
+# Z = Z.T
+
+
+# Substract constant:
+# c = (b1**2)*q1+b1*b2*q12+(b2**2)*q2
+# Z = Z-c
+
+# print('Value of c:', c)
+
+
+
+# print('Z.min()', Z.min())
+# print('Z.max()', Z.max())
+# norm=mcolors.Normalize(Z.min(),Z.max())
+# facecolors=cm.brg(norm)
+
+
+# print('norm:', norm)
+# print('type of norm', type(norm))
+# print('norm(0):', norm(0))
+# print('norm(Z):', norm(Z))
+
+# ax.plot(theta_rho, theta_values, 'royalblue', zorder=3, )
+
+# ax.scatter(a1,a2, s=0.5)
+
+# ax.scatter(tmp1_pos,tmp2_pos, s=0.5)
+# ax.scatter(tmp1_neg,tmp2_neg, s=0.5)
+
+# CS = ax.contour(a1, a2, Z,10, cmap=plt.cm.gnuplot, levels=100 )
+# CS = ax.contour(a1, a2, Z,10, cmap=plt.cm.gnuplot,  levels=20 )
+
+
+# sns.kdeplot(np.array([a1, a2, Z]))
+# sns.kdeplot(tmp1_pos,tmp2_pos,Z_pos)
+
+# levels = [-5.0, -4, -3, 0.0, 1.5, 2.5, 3.5]
+# CS = ax.contour(a1, a2, Z,10, cmap=plt.cm.gnuplot, corner_mask=True,levels=levels)
+# CS = ax.contour(a1, a2, Z, cmap=plt.cm.gnuplot(norm(Z)), corner_mask=True)
+# CS = ax.contour(a1, a2, Z, cm.brg(norm(Z)), levels=20)
+# CS = ax.contour(a1, a2, Z, cmap=plt.cm.gnuplot, levels=20)
+# CS = ax.contour(a1, a2, Z, colors='k', levels=14,  linewidths=(0.5,))
+# CS = ax.contour(a1, a2, Z, colors='k', levels=18,  linewidths=(0.5,))
+
+# ax.contour(negZ_a1, negZ_a2, negativeValues, colors='k',  linewidths=(0.5,))
+# CS =  ax.contour(a1_in, a2_in, Z_in, colors='k',  linewidths=(0.5,))
+
+
+
+# df = pd.DataFrame(data=Z_in, columns=a1_in, index=a2_in)
+# df2 = pd.DataFrame(np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]),
+#                    columns=['a', 'b', 'c'])
+
+
+
+
+# sns.kdeplot(data=df2, x="waiting", y="duration")
+# sns.kdeplot(data=df2)
+
+# CS = ax.contour(a1, a2, Z, colors='k',   linewidths=(0.5,))
+
+# CS = ax.contour(a1, a2, Z,10, cmap=plt.cm.gnuplot, extend='both', levels=50)
+# CS = ax.contourf(a1, a2, Z,10, colors='k', extend='both', levels=50)
+# CS = ax.contourf(a1, a2, Z,10, colors='k')
+#
+# # CS = ax.contour(tmp1_pos,tmp2_pos, Z_pos,10, cmap=plt.cm.gnuplot, levels=10 )
+# # CS = ax.contour(tmp1_pos,tmp2_pos, Z_pos,10, cmap=plt.cm.gnuplot, corner_mask=True)
+#
+# CS = ax.contour(a1, a2, Z,10,  colors = 'k')
+# ax.clabel(CS, inline=True, fontsize=4)
+
+
+# cmap = cm.brg(norm(Z))
+#
+# C_map = cm.inferno(norm(Z))
+
+# ax.imshow(Z, cmap=C_map, extent=[-20, 20, -20, 20], origin='lower', alpha=0.5)
+
+# ax.imshow(norm(Z), extent=[-20, 20, -20, 20], origin='lower',
+#                   cmap='bwr', alpha=0.8)
+
+# ax.imshow(norm(Z), extent=[-20, 20, -20, 20],origin='lower', vmin=Z.min(), vmax=Z.max(),
+#                   cmap='bwr', alpha=0.6)
+
+# ax.imshow(norm(Z), extent=[-20, 20, -20, 20],origin='lower', norm = norm,
+#                   cmap='coolwarm', alpha=0.6)
+
+
+cmap=mpl.cm.RdBu_r
+# cmap=mpl.cm.viridis_r
+cmap=mpl.cm.bwr
+# # cmap=mpl.cm.coolwarm
+# # cmap=mpl.cm.gnuplot
+# cmap=mpl.cm.viridis
+# cmap=mpl.cm.inferno
+cmap=mpl.cm.Blues
+# cmap=mpl.cm.magma
+# cmap=mpl.cm.cividis
+# cmap=mpl.cm.gnuplot
+# cmap=mpl.cm.gnuplot
+cmap = mpl.colors.ListedColormap(["royalblue"], name='from_list', N=None)
+# m = cm.ScalarMappable(norm=norm, cmap=cmap)
+# m = cm.ScalarMappable(cmap=cmap)
+
+# cmap = cm.brg(Z)
+# divnorm=mcolors.TwoSlopeNorm(vmin=Z.min(), vcenter=0., vmax=Z.max())
+
+# ax.imshow(Z, extent=[-20, 20, -20, 20],origin='lower', norm = norm,
+#                   cmap='coolwarm', alpha=0.6)
+
+# ax.imshow(Z, extent=[-20, 20, -20, 20],origin='lower',
+#                   cmap='coolwarm', alpha=0.6)
+# ax.imshow(Z, extent=[-20, 20, -20, 20],origin='lower',
+#                   cmap=cmap, alpha=0.6)
+
+# divnorm=mcolors.TwoSlopeNorm(vmin=Z.min(), vcenter=0., vmax=Z.max())
+# plt.imshow(Z, extent=[x.min(), x.max(), y.min(), y.max()],origin='lower',
+#                   cmap=cmap, alpha=0.6)
+
+# plt.imshow(Z, extent=[x.min(), x.max(), y.min(), y.max()],origin='lower', norm = divnorm,
+#                   cmap=cmap, alpha=0.6)
+
+
+
+
+# COLORBAR :
+# cbar = plt.colorbar()
+# cbar.ax.tick_params(labelsize=8)
+
+
+
+
+# ##----- ADD RECTANGLE TO COVER QUADRANT :
+# epsilon = 0.4
+# epsilon = 0.1
+# # ax.axvspan(0, x.max(), y.min(), 0, alpha=1, color='yellow', zorder=5)#yellow
+# # ax.fill_between([0, x.max()], y.min(), 0, alpha=0.3, color='yellow', zorder=5)#yellow
+# # ax.fill_between([x.min(), 0], 0, y.max(), alpha=0.3, color='yellow', zorder=5)#yellow
+# ax.fill_between([0+epsilon, x.max()], y.min(), 0-epsilon, alpha=0.7, color='gray', zorder=5)#yellow
+# ax.fill_between([x.min(), 0-epsilon], 0+epsilon, y.max(), alpha=0.7, color='gray', zorder=5)#yellow
+
+
+
+#### LINE SEGMENTS :
+line = ax.plot(abar[0,:],abar[1,:],Z_bar, linewidth=2, color='coral', zorder=5)
+# line = ax.plot(abar[0,:],abar[1,:],Z_bar, linewidth=2, color='coral', zorder=1)
+# print('abar', abar)
+# print('abar.shape',abar.shape)
+# start = np.array([abar[0,499],abar[1,499],Z_bar[499]])
+# end = np.array([abar[0,500],abar[1,500],Z_bar[500]])
+# idx = np.where(np.round(Z_bar,3) == np.round( 0.02823972,3) )
+# print('idx[0][0]', idx[0][0])
+# line = ax.plot(abar[0,idx[0][0]:-1],abar[1,idx[0][0]:-1],Z_bar[idx[0][0]:-1], linewidth=2, color='coral', zorder=5)
+### -----------------------------------
+
+
+
+
+
+# ax.plot_surface(a1,a2, Z, cmap=cm.coolwarm,
+#                        linewidth=0, antialiased=False)
+
+# ax.plot_surface(tmp1,tmp2, Z, cmap=cm.coolwarm,
+#                        linewidth=0, antialiased=False)
+
+# ax.scatter(X_1,Y_1,Z1, s=0.2)
+# ax.scatter(X_2,Y_2,Z2, s=0.2)
+
+
+# X = np.concatenate((X_1, X_2), axis=0)
+# Y = np.concatenate((Y_1, Y_2), axis=0)
+# Z = np.concatenate((Z1, Z2), axis=0)
+# ax.plot_surface(X,Y,Z)
+
+
+ax.plot_surface(X_1,Y_1,Z1 ,cmap=cmap,
+                       linewidth=0, antialiased=True,alpha=.35, zorder=5)
+ax.plot_surface(X_2,Y_2,Z2 ,cmap=cmap,
+                       linewidth=0, antialiased=True,alpha=.35, zorder=5)
+# ax.plot_surface(X_1,Y_1,Z1 , facecolor = 'lightblue',     #cmap=cmap,
+#                        linewidth=0, antialiased=True, alpha=1, zorder=5)
+# ax.plot_surface(X_2,Y_2,Z2 , facecolor = 'lightblue', edgecolor='none',    #cmap=cmap,
+#                        linewidth=0, antialiased=True, alpha=1, zorder=5)
+
+# ax.plot_surface(X_1,Y_1,Z1 , #color='C0',
+# 							rstride=1, cstride=1,linewidth=0, antialiased=True, alpha=1, zorder=5)
+
+
+
+
+# ax.plot_surface(X_2,Y_2,Z2 , #color='C0',
+# 							rstride=1, cstride=1,linewidth=0,  alpha=0.8, zorder=5, shade=True)
+# ax.plot_surface(X_2,Y_2,Z2)
+
+# X_2 = X_2.reshape(-1,1).flatten()
+# Y_2 = Y_2.reshape(-1,1).flatten()
+# Z2 = Z2.reshape(-1,1).flatten()
+#
+# ax.plot_trisurf(X_2,Y_2,Z2, color='blue' )
+
+
+# X_1 = X_1.reshape(-1,1).flatten()
+# Y_1 = Y_1.reshape(-1,1).flatten()
+# Z1 = Z1.reshape(-1,1).flatten()
+# ax.plot_trisurf(X_1,Y_1,Z1 , color='blue')
+
+
+### MAYAVI TEST
+# mlab.figure(bgcolor=(1.0, 1.0, 1.0), size=(1000,1000))
+# mlab.view(azimuth=90, elevation=125)
+# mlab.view(azimuth=100, elevation=115)
+# axes = mlab.axes(color=(0, 0, 0), nb_labels=5)
+# mlab.orientation_axes()
+# mlab.mesh(X_1, Y_1,Z1, color=(0,0,1) ,  transparent=True )
+# mlab.plot3d(abar[0,:],abar[1,:],Z_bar, line_width=1)
+# mlab.mesh(X_2, Y_2,Z2)
+# mlab.savefig("./example.png")
+### --------------------------------------------
+
+
+
+# ax.plot_surface(X_1,Y_1,Z1 , cmap=cmap,
+#                        linewidth=0, antialiased=False,alpha=1, zorder=5)
+# ax.plot_surface(X_2,Y_2,Z2 , cmap=cmap,
+#                        linewidth=0, antialiased=True,alpha=1, zorder=5)
+
+# ax.plot_surface(X_2,Y_2,Z2 , color = 'lightblue',     #cmap=cmap,
+#                        linewidth=0, antialiased=True, alpha=1, zorder=5)
+
+
+# ax.plot(G[0,:],G[1,:],G[2,:])
+# ax.plot(abar[0,:],abar[1,:],Z_bar, linewidth=2, color='yellow', linestyle='--')
+# ax.scatter(abar[0,:],abar[1,:],Z_bar,  color='purple', zorder=5)
+# ax.plot(abar[0,:],abar[1,:],Z_bar, linewidth=2, color='royalblue', linestyle='--')
+# ax.plot(abar[0,:],abar[1,:],Z_bar, linewidth=3, color='dodgerblue', linestyle='--')
+# ax.plot(abar[0,:],abar[1,:],Z_bar, linewidth=3, color='cornflowerblue', linestyle='--')
+# ax.plot(abar[0,:],abar[1,:],Z_bar, linewidth=3, color='darkorange', linestyle='--')
+# ax.plot(abar[0,:],abar[1,:],Z_bar, linewidth=3, color='yellow', linestyle='--')
+# line = ax.plot(abar[0,:],abar[1,:],Z_bar, linewidth=1, color='coral', linestyle='--', zorder=3)
+
+
+# plot starting point:
+# ax.scatter(abar[0,0],abar[1,0],Z_bar[0], marker='^',  s=30, color='black', zorder=5)
+#
+#
+# ax.scatter(abar[0,500],abar[1,500],Z_bar[500], marker='^',  s=30, color='purple', zorder=5)
+
+# ax.scatter(start[0],start[1],start[2], marker='^',  s=30, color='purple', zorder=5)
+# ax.scatter(end[0],end[1],end[2], marker='^',  s=30, color='purple', zorder=5)
+
+
+# define origin
+o = np.array([0,0,0])
+
+start = np.array([1,0,0])
+end = np.array([2.5,0,0])
+
+
+print('start:', start)
+print('end:', end)
+
+
+dir = end-start
+print('dir:', dir)
+# ax.arrow()
+
+# ax.arrow3D(start[0],start[1],start[2],
+#            dir[0],dir[1],dir[2],
+#            mutation_scale=10,
+#            arrowstyle="->",
+#            linestyle='dashed',fc='coral',
+#            lw = 1,
+#            ec ='coral',
+#            zorder=3)
+
+# ax.arrow3D(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],
+#            normal[0],normal[1],normal[2],
+#            mutation_scale=15,
+#             lw = 1.5,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='blue',
+#            ec ='blue',
+#            zorder = 5)
+
+
+# ax.arrow3D(start[0],start[1],start[2],
+#            dir[0],dir[1],dir[2],
+#            mutation_scale=20,
+#            arrowstyle="->",
+#            fc='coral',
+#            lw = 1,
+#            ec ='coral',
+#            zorder=3)
+# ax.arrow3D(start[0],start[1],start[2],
+#            dir[0],dir[1],dir[2],
+#            mutation_scale=20,
+#            arrowstyle="->",
+#            fc='coral',
+#            lw = 1,
+#            ec ='coral',
+#            zorder=3)
+
+arrow_prop_dict = dict(mutation_scale=20, arrowstyle='-|>', color='k', shrinkA=0, shrinkB=0)
+# style = ArrowStyle('Fancy', head_length=1, head_width=1.5, tail_width=0.5)
+
+
+# ADD ARROW:
+# a = Arrow3D([start[0], end[0]], [start[1], end[1]], [start[2], end[2]], mutation_scale=15, arrowstyle='-|>', color='darkorange')
+# ax.add_artist(a)
+
+## ADD Annotation
+# ax.text(0, 0, 1.5, r"$\mathcal G^+$", color='royalblue', size=12)
+ax.text(0, 0, 1.5, r"$\mathcal G^+$", color='royalblue', size=15)
+# ax.text(0.5, 0.5, "Test")
+# ax.text(9, 0, 0, "red", color='red')
+
+### ---- Check proof:
+# value at t = 0:
+abar_zero= sstar*abar_tmp
+# value_0 = [abar_zero[0], abar_zero[1] , (2*abar_zero[0]*abar_zero[1])**0.5 ]
+value_0 = evaluate(abar_zero[0], abar_zero[1])
+print('value_0', value_0)
+# ax.scatter(value_0[0],value_0[1],value_0[2], marker='x',  s=20, color='dodgerblue', zorder=5)
+# ax.scatter(abar_zero[0], abar_zero[1],value_0, marker='o',  s=30, color='dodgerblue', zorder=5)
+## -----------------------------
+
+
+
+
+
+
+
+
+
+
+# ax.scatter(tmp1,tmp2, Z, cmap=cm.coolwarm,
+#                        linewidth=0, antialiased=False)
+# ax.plot_surface(tmp1,Z, tmp2, cmap=cm.coolwarm,
+#                        linewidth=0, antialiased=False)
+# ax.plot_trisurf(tmp1,tmp2, Z, cmap=cm.coolwarm,
+#                        linewidth=0, antialiased=False)
+
+
+# ax.plot(theta_rho, energy_axial1, 'royalblue', zorder=3, label=r"axialMin1")
+# ax.plot(theta_rho, energy_axial2, 'forestgreen', zorder=3, label=r"axialMin2")
+# ax.plot(-1.0*alphas, kappas, 'red', zorder=3, )
+
+
+
+
+# lg = ax.legend(bbox_to_anchor=(0.0, 0.75), loc='upper left')
+
+
+
+
+### PLOT X AND Y AXIS:
+# ax.plot(ax.get_xlim(),[0,0],'k--', linewidth=0.5)
+# ax.plot([0,0],ax.get_ylim(), 'k--', linewidth=0.5)
+ax.plot(ax.get_xlim(),[0,0],'k--', linewidth=1 ,zorder=5)
+ax.plot([0,0],ax.get_ylim(), 'k--', linewidth=1)
+
+
+
+# Plot 1-Parameter Line
+line_values= np.array(line_values)
+ax.plot(line_values[:,0],line_values[:,1],'k--', linewidth=1,color='orange',alpha=0.8)
+
+
+ax.set_xlabel(r"$a_1$", fontsize=10 ,labelpad=0)
+ax.set_ylabel(r"$a_2$", fontsize=10 ,labelpad=0)
+
+
+plt.subplots_adjust(left=0.0)
+plt.subplots_adjust(bottom=0.25)
+
+# ax.get_xaxis().set_visible(False)
+# ax = plt.gca(projection="3d")
+# ax._axis3don = False
+ZL = ax.get_zgridlines()
+
+# ax.set_ylabel(r"energy")
+
+
+# ax.set_xticks([-np.pi/2, -np.pi/4  ,0,  np.pi/4,  np.pi/2 ])
+# labels = ['$0$',r'$\pi/8$', r'$\pi/4$' ,r'$3\pi/8$' , r'$\pi/2$']
+# ax.set_yticklabels(labels)
+
+
+
+
+
+# ax.legend(loc='upper right')
+
+
+
+fig.set_size_inches(width, height)
+fig.savefig('1-ParameterFamily_G+.pdf')
+
+plt.show()

Python-Scripts/1-ParameterFamily_G+_v5.py

+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 ClassifyMin_New 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
+
+import matplotlib as mpl
+from matplotlib.ticker import MultipleLocator,FormatStrFormatter,MaxNLocator
+import pandas as pd
+
+import seaborn as sns
+import matplotlib.colors as mcolors
+
+
+from mpl_toolkits.mplot3d.proj3d import proj_transform
+from mpl_toolkits.mplot3d import proj3d
+# from mpl_toolkits.mplot3d.axes3d import Axes3D
+from matplotlib.text import Annotation
+from matplotlib.patches import FancyArrowPatch
+
+
+import mayavi.mlab as mlab
+from mayavi.api import OffScreenEngine
+mlab.options.offscreen = True
+
+from chart_studio import plotly
+import plotly.graph_objs as go
+# from matplotlib import rc
+# rc('text', usetex=True) # Use LaTeX font
+#
+# import seaborn as sns
+# sns.set(color_codes=True)
+
+# set the colormap and centre the colorbar
+class MidpointNormalize(mcolors.Normalize):
+	"""
+	Normalise the colorbar so that diverging bars work there way either side from a prescribed midpoint value)
+
+	e.g. im=ax1.imshow(array, norm=MidpointNormalize(midpoint=0.,vmin=-100, vmax=100))
+	"""
+	def __init__(self, vmin=None, vmax=None, midpoint=None, clip=False):
+		self.midpoint = midpoint
+		mcolors.Normalize.__init__(self, vmin, vmax, clip)
+
+	def __call__(self, value, clip=None):
+		# I'm ignoring masked values and all kinds of edge cases to make a
+		# simple example...
+		x, y = [self.vmin, self.midpoint, self.vmax], [0, 0.5, 1]
+		return np.ma.masked_array(np.interp(value, x, y), np.isnan(value))
+
+
+
+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 == -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)
+    ##find number of multiples of pi/2
+    N = int(np.round(4 * value / np.pi))
+    if N == 0:
+        return "0"
+    elif N == 1:
+        return r"$\pi/4$"
+    elif N == -1:
+        return r"$-\pi/4$"
+    elif N == 2:
+        return r"$\pi/2$"
+    elif N == -2:
+        return r"$-\pi/2$"
+    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
+
+
+
+def energy(a1,a2,q1,q2,q12,q3,b1,b2):
+
+
+    a = np.array([a1,a2])
+    b = np.array([b1,b2])
+    H = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+    A = np.array([[q1,1/2*q12], [1/2*q12,q2] ])
+
+
+    tmp = H.dot(a)
+
+    # print('H',H)
+    # print('A',A)
+    # print('b',b)
+    # print('a',a)
+    # print('tmp',tmp)
+
+    tmp = (1/2)*a.dot(tmp)
+    # print('tmp',tmp)
+
+    tmp2 = A.dot(b)
+    # print('tmp2',tmp2)
+    tmp2 = 2*a.dot(tmp2)
+
+    # print('tmp2',tmp2)
+    energy = tmp - tmp2
+    # print('energy',energy)
+
+
+    # energy_axial1.append(energy_1)
+
+    return energy
+
+
+
+def evaluate(x,y):
+
+	# (abar[0,:]*abar[1,:])**0.5
+
+	return np.sqrt(x*y)
+
+
+# def energy(a1,a2,q1,q2,q12,q3,b1,b2):
+#
+#
+#     b = np.array([b1,b2])
+#     H = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+#     A = np.array([[q1,1/2*q12], [1/2*q12,q2] ])
+#
+#
+#     tmp = H.dot(a)
+#
+#     print('H',H)
+#     print('A',A)
+#     print('b',b)
+#     print('a',a)
+#     print('tmp',tmp)
+#
+#     tmp = (1/2)*a.dot(tmp)
+#     print('tmp',tmp)
+#
+#     tmp2 = A.dot(b)
+#     print('tmp2',tmp2)
+#     tmp2 = 2*a.dot(tmp2)
+#
+#     print('tmp2',tmp2)
+#     energy = tmp - tmp2
+#     print('energy',energy)
+#
+#
+#     # energy_axial1.append(energy_1)
+#
+#     return energy
+#
+
+def add_arrow(line, position=None, direction='right', size=15, color=None):
+    """
+    add an arrow to a line.
+
+    line:       Line2D object
+    position:   x-position of the arrow. If None, mean of xdata is taken
+    direction:  'left' or 'right'
+    size:       size of the arrow in fontsize points
+    color:      if None, line color is taken.
+    """
+    if color is None:
+        color = line.get_color()
+
+    xdata = line.get_xdata()
+    ydata = line.get_ydata()
+
+    if position is None:
+        position = xdata.mean()
+    # find closest index
+    start_ind = np.argmin(np.absolute(xdata - position))
+    if direction == 'right':
+        end_ind = start_ind + 1
+    else:
+        end_ind = start_ind - 1
+
+    line.axes.annotate('',
+        xytext=(xdata[start_ind], ydata[start_ind]),
+        xy=(xdata[end_ind], ydata[end_ind]),
+        arrowprops=dict(arrowstyle="->", color=color),
+        size=size
+    )
+
+
+
+class Annotation3D(Annotation):
+    def __init__(self, text, xyz, *args, **kwargs):
+        super().__init__(text, xy=(0, 0), *args, **kwargs)
+        self._xyz = xyz
+
+    def draw(self, renderer):
+        x2, y2, z2 = proj_transform(*self._xyz, self.axes.M)
+        self.xy = (x2, y2)
+        super().draw(renderer)
+
+def _annotate3D(ax, text, xyz, *args, **kwargs):
+    '''Add anotation `text` to an `Axes3d` instance.'''
+
+    annotation = Annotation3D(text, xyz, *args, **kwargs)
+    ax.add_artist(annotation)
+
+setattr(Axes3D, 'annotate3D', _annotate3D)
+
+
+
+class Arrow3D(FancyArrowPatch):
+    def __init__(self, xs, ys, zs, *args, **kwargs):
+        FancyArrowPatch.__init__(self, (0,0), (0,0), *args, **kwargs)
+        self._verts3d = xs, ys, zs
+
+    def draw(self, renderer):
+        xs3d, ys3d, zs3d = self._verts3d
+        xs, ys, zs = proj3d.proj_transform(xs3d, ys3d, zs3d, renderer.M)
+        self.set_positions((xs[0],ys[0]),(xs[1],ys[1]))
+        FancyArrowPatch.draw(self, renderer)
+
+
+def _arrow3D(ax, x, y, z, dx, dy, dz, *args, **kwargs):
+    '''Add an 3d arrow to an `Axes3D` instance.'''
+
+    arrow = Arrow3D(x, y, z, dx, dy, dz, *args, **kwargs)
+    ax.add_artist(arrow)
+
+setattr(Axes3D, 'arrow3D', _arrow3D)
+
+################################################################################################################
+################################################################################################################
+################################################################################################################
+
+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: -----')
+
+# q1=1;
+# q2=2;
+# q12=1/2;
+# q3=((4*q1*q2)**0.5-q12)/2;
+# # H=[2*q1,q12+2*q3;q12+2*q3,2*q2];
+#
+# H = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+# A = np.array([[q1,1/2*q12], [1/2*q12,q2] ])
+# abar = np.array([q12+2*q3, 2*q2])
+# abar = (1.0/math.sqrt((q12+2*q3)**2+(2*q2)**2))*abar
+#
+# print('abar:',abar)
+#
+# b = np.linalg.lstsq(A, abar)[0]
+# print('b',b)
+#
+#
+# # print('abar:',np.shape(abar))
+# # print('np.transpose(abar):',np.shape(np.transpose(abar)))
+# sstar = (1/(q1+q2))*abar.dot(A.dot(b))
+# # sstar = (1/(q1+q2))*abar.dot(tmp)
+# print('sstar', sstar)
+# abarperp= np.array([abar[1],-abar[0]])
+# print('abarperp:',abarperp)
+
+
+# -------------------------- Input Parameters --------------------
+
+mu1 = 1.0
+rho1 = 1.0
+alpha = 5.0
+theta = 1.0/2
+# theta= 0.1
+beta = 5.0
+
+
+
+# mu1 = 1.0
+# rho1 = 1.0
+# alpha = 2.0
+# theta = 1.0/2
+# # theta= 0.1
+# beta = 5.0
+
+
+#Figure3:
+# mu1 = 1.0
+# rho1 = 1.0
+# alpha = 2.0
+# theta = 1.0/8
+# # theta= 0.1
+# beta = 2.0
+
+
+# alpha= -5
+
+
+#set gamma either to 1. '0' 2. 'infinity' or 3. a numerical positive value
+gamma = '0'
+gamma = 'infinity'
+
+
+lambda1 = 0.0
+
+
+print('---- Input parameters: -----')
+print('mu1: ', mu1)
+print('rho1: ', rho1)
+# print('alpha: ', alpha)
+print('beta: ', beta)
+# print('theta: ', theta)
+print('gamma:', gamma)
+
+print('lambda1: ', lambda1)
+print('----------------------------')
+# ----------------------------------------------------------------
+print('----------------------------')
+
+# ----------------------------------------------------------------
+
+
+
+
+
+
+q1 = (1.0/6.0)*harmonicMean(mu1, beta, theta)
+q2 = (1.0/6.0)*arithmeticMean(mu1, beta, theta)
+q12 = 0.0
+q3 = GetMuGamma(beta, theta,gamma,mu1,rho1,InputFilePath ,OutputFilePath )
+b1 = prestrain_b1(rho1,beta, alpha, theta )
+b2 = prestrain_b2(rho1,beta, alpha, theta )
+
+
+# 1-ParameterFamilyCase:
+
+q1=1;
+q2=2;
+q12=1/2;
+q3=((4*q1*q2)**0.5-q12)/2;
+# H=[2*q1,q12+2*q3;q12+2*q3,2*q2];
+
+H = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+A = np.array([[q1,1/2*q12], [1/2*q12,q2] ])
+abar = np.array([q12+2*q3, 2*q2])
+abar = (1.0/math.sqrt((q12+2*q3)**2+(2*q2)**2))*abar
+
+print('abar:',abar)
+
+b = np.linalg.lstsq(A, abar)[0]
+print('b',b)
+
+b1=b[0]
+b2=b[1]
+
+
+# print('abar:',np.shape(abar))
+# print('np.transpose(abar):',np.shape(np.transpose(abar)))
+sstar = (1/(q1+q2))*abar.dot(A.dot(b))
+# sstar = (1/(q1+q2))*abar.dot(tmp)
+print('sstar', sstar)
+abarperp= np.array([abar[1],-abar[0]])
+print('abarperp:',abarperp)
+
+print('----------------------------')
+
+# ----------------------------------------------------------------
+
+N=1000;
+# scale_domain = 5
+# translate_startpoint = -5
+
+# scale_domain = 5
+# translate_startpoint = -1.8
+
+
+scale_domain = 5
+translate_startpoint = -1.8
+T_line = np.linspace(-sstar*(q12+2*q3)/(2*q2)*scale_domain + translate_startpoint, sstar*(2*q2)/(q12+2*q3)*scale_domain , num=N)
+line_values = []
+for t in T_line :
+    print('sstar*abar+t*abarperp', sstar*abar+t*abarperp)
+    line_values.append(sstar*abar+t*abarperp)
+
+
+
+
+T = np.linspace(-sstar*(q12+2*q3)/(2*q2), sstar*(2*q2)/(q12+2*q3), num=N)
+# T = np.linspace(-sstar*(q12+2*q3)/(2*q2)*scale_domain + translate_startpoint, sstar*(2*q2)/(q12+2*q3)*scale_domain , num=N)
+# T = np.linspace(-2,2, num=N)
+# print('T:', T)
+
+print('T.min():', T.min())
+print('T.max():', T.max())
+
+kappas = []
+alphas = []
+# G.append(float(s[0]))
+
+G_container = []
+abar_container = []
+
+
+abar_tmp = abar
+
+for t in T :
+	abar_current = sstar*abar+t*abarperp;
+    # print('abar_current', abar_current)
+	abar_current[abar_current < 1e-10] = 0
+	# print('abar_current', abar_current)
+	# G = np.array([[2*q1, q12+2*q3], [q12+2*q3,2*q2] ])
+	G = [abar_current[0], abar_current[1] , (2*abar_current[0]*abar_current[1])**0.5 ]
+	# print('type of G', type(G))
+	# print('G', G)
+	G_container.append(G)
+	abar_container.append(abar_current)
+	e = [(abar_current[0]/(abar_current[0]+abar_current[1]))**0.5, (abar_current[1]/(abar_current[0]+abar_current[1]))**0.5]
+	kappa = abar_current[0]+abar_current[1]
+	alpha = math.atan2(e[1], e[0])
+	# print('angle current:', alpha)
+	kappas.append(kappa)
+	alphas.append(alpha)
+
+
+alphas = np.array(alphas)
+kappas = np.array(kappas)
+
+# print('G_container', G_container)
+G = np.array(G_container)
+abar = np.array(abar_container)
+
+print('G', G)
+print('abar', abar)
+print('abar.shape',abar.shape)
+
+
+
+
+
+print('q1 = ', q1)
+print('q2 = ', q2)
+print('q3 = ', q3)
+print('q12 = ', q12)
+print('b1 = ', b1)
+print('b2 = ', b2)
+
+num_Points = 20
+num_Points = 50
+num_Points = 200
+
+# Creating dataset
+x = np.linspace(-5,5,num_Points)
+y = np.linspace(-5,5,num_Points)
+
+x = np.linspace(-20,20,num_Points)
+y = np.linspace(-20,20,num_Points)
+
+# x = np.linspace(-10,10,num_Points)
+# y = np.linspace(-10,10,num_Points)
+
+# x = np.linspace(-60,60,num_Points)
+# y = np.linspace(-60,60,num_Points)
+#
+#
+# x = np.linspace(-40,40,num_Points)
+# y = np.linspace(-40,40,num_Points)
+
+
+range = 2
+
+x_1 = np.linspace(0,range,num_Points)
+y_1 = np.linspace(0,range,num_Points)
+x_2 = np.linspace(-range,0,num_Points)
+y_2 = np.linspace(-range,0,num_Points)
+
+
+X_1,Y_1 = np.meshgrid(x_1,y_1)
+X_2,Y_2 = np.meshgrid(x_2,y_2)
+
+
+a1, a2 = np.meshgrid(x,y)
+
+# geyser = sns.load_dataset("geyser")
+# print('type of geyser:', type(geyser))
+# print('geyser:',geyser)
+
+ContourRange=20
+
+x_in = np.linspace(-ContourRange,ContourRange,num_Points)
+y_in = np.linspace(-ContourRange,ContourRange,num_Points)
+a1_in, a2_in = np.meshgrid(x_in,y_in)
+
+# print('a1:', a1)
+# print('a2:',a2 )
+#
+# print('a1.shape', a1.shape)
+
+#-- FILTER OUT VALUES for G+ :
+
+tmp1 = a1[np.where(a1*a2 >= 0)]
+tmp2 = a2[np.where(a1*a2 >= 0)]
+
+# tmp1 = a1[a1*a2 >= 0]
+# tmp2 = a2[a1*a2 >= 0]
+
+# tmp1 = a1[np.where(a1>=0 and a2 >= 0)]
+# tmp2 = a2[np.where(a1>=0 and a2 >= 0)]
+
+
+# tmp1 = tmp1[np.where(a1 >= 0)]
+# tmp2 = tmp2[np.where(a1 >= 0)]
+
+# tmp1_pos = a1[np.where(a1*a2 >= 0)]
+# tmp2_neg = a2[np.where(a1*a2 >= 0)]
+
+
+
+print('tmp1.shape',tmp1.shape)
+print('tmp1.shape[0]',tmp1.shape[0])
+print('tmp2.shape',tmp2.shape)
+print('tmp2.shape[0]',tmp2.shape[0])
+
+
+
+tmp1 = tmp1.reshape(-1,int(tmp1.shape[0]/2))
+tmp2 = tmp2.reshape(-1,int(tmp2.shape[0]/2))
+
+print('tmp1.shape',tmp1.shape)
+print('tmp1.shape[0]',tmp1.shape[0])
+print('tmp2.shape',tmp2.shape)
+print('tmp2.shape[0]',tmp2.shape[0])
+
+# np.take(a, np.where(a>100)[0], axis=0)
+# tmp1 = np.take(a1, np.where(a1*a2 >= 0)[0], axis=0)
+# tmp2 = np.take(a1, np.where(a1*a2 >= 0)[0], axis=0)
+# tmp2 = a2[np.where(a1*a2 >= 0)]
+
+# tmp1 = a1[a1*a2 >= 0]
+# tmp2 = a2[a1*a2 >= 0]
+
+
+# tmp1_pos = a1[np.where(a1*a2 >= 0) ]
+# tmp2_pos = a2[np.where(a1*a2 >= 0) ]
+# tmp1_pos = tmp1_pos[np.where(tmp1_pos  >= 0)]
+# tmp2_pos = tmp2_pos[np.where(tmp2_pos  >= 0)]
+
+# tmp1_neg = a1[a1*a2 >= 0 ]
+# tmp2_neg = a2[a1*a2 >= 0 ]
+# tmp1_neg = tmp1_neg[tmp1_neg  < 0]
+# tmp2_neg = tmp2_neg[tmp2_neg  < 0]
+# a1 = tmp1
+# a2 = tmp2
+#
+# a1 = a1.reshape(-1,5)
+# a2 = a2.reshape(-1,5)
+
+# tmp1_pos = tmp1_pos.reshape(-1,5)
+# tmp2_pos = tmp2_pos.reshape(-1,5)
+# tmp1_neg = tmp1_neg.reshape(-1,5)
+# tmp2_neg = tmp2_neg.reshape(-1,5)
+
+
+# print('a1:', a1)
+# print('a2:',a2 )
+# print('a1.shape', a1.shape)
+
+
+
+
+
+energyVec = np.vectorize(energy)
+
+# Z = energyVec(np.array([a1,a2]),q1,q2,q12,q3,b1,b2)
+# Z = energyVec(a1,a2,q1,q2,q12,q3,b1,b2)
+#
+# Z_in = energyVec(a1_in,a2_in,q1,q2,q12,q3,b1,b2)
+
+
+
+
+# Z = (tmp2**2)/tmp1
+Z = np.sqrt(tmp1*tmp2)
+
+
+Z1 = np.sqrt(X_1*Y_1)
+Z2 = np.sqrt(X_2*Y_2)
+
+# Z_bar = np.sqrt(abar[0,:]*abar[1,:])
+Z_bar = (abar[0,:]*abar[1,:])**0.5*abar
+
+abar = abar.T
+
+
+
+v1 = abar[0,:]
+v2 = abar[1,:]
+
+# print('a1:', a1)
+# print('a2:',a2 )
+# print('a1.shape', a1.shape)
+
+
+evaluateVec = np.vectorize(evaluate)
+Z_bar = evaluateVec(abar[0,:],abar[1,:])
+# Z = np.sqrt(np.multiply(tmp1,tmp2))
+# Z = np.sqrt(a1*a2)
+
+
+print('v1.shape', v1.shape)
+print('v1', v1)
+
+
+
+
+print('Z:', Z)
+print('Z_bar:', Z_bar)
+# print('any', np.any(Z<0))
+
+#
+
+
+# negZ_a1 = a1[np.where(Z<0)]
+# negZ_a2 = a2[np.where(Z<0)]
+# negativeValues = Z[np.where(Z<0)]
+# print('negativeValues:',negativeValues)
+#
+# print('negZ_a1',negZ_a1)
+# print('negZ_a2',negZ_a2)
+#
+#
+# negZ_a1 = negZ_a1.reshape(-1,5)
+# negZ_a2 = negZ_a2.reshape(-1,5)
+# negativeValues = negativeValues.reshape(-1,5)
+#
+# Z_pos =  energyVec(tmp1_pos,tmp2_pos,q1,q2,q12,q3,b1,b2)
+# Z_neg = energyVec(tmp1_neg,tmp2_neg,q1,q2,q12,q3,b1,b2)
+
+
+
+
+
+# print('Test energy:' , energy(np.array([1,1]),q1,q2,q12,q3,b1,b2))
+
+
+
+
+# print('Z_pos.shape', Z_pos.shape)
+
+
+
+
+
+
+
+## -- PLOT :
+mpl.rcParams['text.usetex'] = True
+mpl.rcParams["font.family"] = "serif"
+mpl.rcParams["font.size"] = "9"
+
+label_size = 8
+mpl.rcParams['xtick.labelsize'] = label_size
+mpl.rcParams['ytick.labelsize'] = label_size
+
+# plt.style.use('seaborn')
+plt.style.use('seaborn-whitegrid')
+# sns.set()
+# plt.style.use('seaborn-whitegrid')
+
+label_size = 9
+mpl.rcParams['xtick.labelsize'] = label_size
+mpl.rcParams['ytick.labelsize'] = label_size
+
+mpl.rcParams["font.size"] =10
+
+width = 6.28 *0.5
+# width = 6.28
+height = width / 1.618
+height = width
+fig = plt.figure()
+
+ax = plt.axes(projection ='3d', adjustable='box')
+# ax = plt.axes((0.17,0.21 ,0.75,0.75))
+# ax = plt.axes((0.15,0.18,0.8,0.8))
+# ax.tick_params(axis='x',which='major', direction='out',pad=5)
+# ax.tick_params(axis='y',which='major', length=3, width=1, direction='out',pad=3)
+# ax.xaxis.set_major_locator(MultipleLocator(0.1))
+# ax.xaxis.set_minor_locator(MultipleLocator(0.05))
+# ax.xaxis.set_major_locator(plt.MultipleLocator(np.pi / 8))
+# ax.xaxis.set_minor_locator(plt.MultipleLocator(np.pi / 16))
+# ax.xaxis.set_major_locator(plt.MultipleLocator(np.pi / 2))
+# ax.xaxis.set_minor_locator(plt.MultipleLocator(np.pi / 4))
+# ax.xaxis.set_major_formatter(plt.FuncFormatter(format_func))
+# ax.grid(True,which='major',axis='both',alpha=0.3)
+ax.grid(True,which='major',axis='xy',alpha=0.3)
+# ax.grid(False,which='major',alpha=0.3)
+# Hide grid lines
+# ax.grid(False)
+
+
+
+# colorfunction=(B*kappa)
+# print('colofunction',colorfunction)
+
+#translate Data
+# Z = Z - (Z.max()-Z.min())/2
+# Z = Z - 50
+# Z = Z - 500
+#
+# Z = Z.T
+
+
+# Substract constant:
+# c = (b1**2)*q1+b1*b2*q12+(b2**2)*q2
+# Z = Z-c
+
+# print('Value of c:', c)
+
+
+
+# print('Z.min()', Z.min())
+# print('Z.max()', Z.max())
+# norm=mcolors.Normalize(Z.min(),Z.max())
+# facecolors=cm.brg(norm)
+
+
+# print('norm:', norm)
+# print('type of norm', type(norm))
+# print('norm(0):', norm(0))
+# print('norm(Z):', norm(Z))
+
+# ax.plot(theta_rho, theta_values, 'royalblue', zorder=3, )
+
+# ax.scatter(a1,a2, s=0.5)
+
+# ax.scatter(tmp1_pos,tmp2_pos, s=0.5)
+# ax.scatter(tmp1_neg,tmp2_neg, s=0.5)
+
+# CS = ax.contour(a1, a2, Z,10, cmap=plt.cm.gnuplot, levels=100 )
+# CS = ax.contour(a1, a2, Z,10, cmap=plt.cm.gnuplot,  levels=20 )
+
+
+# sns.kdeplot(np.array([a1, a2, Z]))
+# sns.kdeplot(tmp1_pos,tmp2_pos,Z_pos)
+
+# levels = [-5.0, -4, -3, 0.0, 1.5, 2.5, 3.5]
+# CS = ax.contour(a1, a2, Z,10, cmap=plt.cm.gnuplot, corner_mask=True,levels=levels)
+# CS = ax.contour(a1, a2, Z, cmap=plt.cm.gnuplot(norm(Z)), corner_mask=True)
+# CS = ax.contour(a1, a2, Z, cm.brg(norm(Z)), levels=20)
+# CS = ax.contour(a1, a2, Z, cmap=plt.cm.gnuplot, levels=20)
+# CS = ax.contour(a1, a2, Z, colors='k', levels=14,  linewidths=(0.5,))
+# CS = ax.contour(a1, a2, Z, colors='k', levels=18,  linewidths=(0.5,))
+
+# ax.contour(negZ_a1, negZ_a2, negativeValues, colors='k',  linewidths=(0.5,))
+# CS =  ax.contour(a1_in, a2_in, Z_in, colors='k',  linewidths=(0.5,))
+
+
+
+# df = pd.DataFrame(data=Z_in, columns=a1_in, index=a2_in)
+# df2 = pd.DataFrame(np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]),
+#                    columns=['a', 'b', 'c'])
+
+
+
+
+# sns.kdeplot(data=df2, x="waiting", y="duration")
+# sns.kdeplot(data=df2)
+
+# CS = ax.contour(a1, a2, Z, colors='k',   linewidths=(0.5,))
+
+# CS = ax.contour(a1, a2, Z,10, cmap=plt.cm.gnuplot, extend='both', levels=50)
+# CS = ax.contourf(a1, a2, Z,10, colors='k', extend='both', levels=50)
+# CS = ax.contourf(a1, a2, Z,10, colors='k')
+#
+# # CS = ax.contour(tmp1_pos,tmp2_pos, Z_pos,10, cmap=plt.cm.gnuplot, levels=10 )
+# # CS = ax.contour(tmp1_pos,tmp2_pos, Z_pos,10, cmap=plt.cm.gnuplot, corner_mask=True)
+#
+# CS = ax.contour(a1, a2, Z,10,  colors = 'k')
+# ax.clabel(CS, inline=True, fontsize=4)
+
+
+# cmap = cm.brg(norm(Z))
+#
+# C_map = cm.inferno(norm(Z))
+
+# ax.imshow(Z, cmap=C_map, extent=[-20, 20, -20, 20], origin='lower', alpha=0.5)
+
+# ax.imshow(norm(Z), extent=[-20, 20, -20, 20], origin='lower',
+#                   cmap='bwr', alpha=0.8)
+
+# ax.imshow(norm(Z), extent=[-20, 20, -20, 20],origin='lower', vmin=Z.min(), vmax=Z.max(),
+#                   cmap='bwr', alpha=0.6)
+
+# ax.imshow(norm(Z), extent=[-20, 20, -20, 20],origin='lower', norm = norm,
+#                   cmap='coolwarm', alpha=0.6)
+
+
+cmap=mpl.cm.RdBu_r
+# cmap=mpl.cm.viridis_r
+cmap=mpl.cm.bwr
+# # cmap=mpl.cm.coolwarm
+# # cmap=mpl.cm.gnuplot
+# cmap=mpl.cm.viridis
+# cmap=mpl.cm.inferno
+cmap=mpl.cm.Blues
+# cmap=mpl.cm.magma
+# cmap=mpl.cm.cividis
+# cmap=mpl.cm.gnuplot
+# cmap=mpl.cm.gnuplot
+cmap = mpl.colors.ListedColormap(["royalblue"], name='from_list', N=None)
+# m = cm.ScalarMappable(norm=norm, cmap=cmap)
+# m = cm.ScalarMappable(cmap=cmap)
+
+# cmap = cm.brg(Z)
+# divnorm=mcolors.TwoSlopeNorm(vmin=Z.min(), vcenter=0., vmax=Z.max())
+
+# ax.imshow(Z, extent=[-20, 20, -20, 20],origin='lower', norm = norm,
+#                   cmap='coolwarm', alpha=0.6)
+
+# ax.imshow(Z, extent=[-20, 20, -20, 20],origin='lower',
+#                   cmap='coolwarm', alpha=0.6)
+# ax.imshow(Z, extent=[-20, 20, -20, 20],origin='lower',
+#                   cmap=cmap, alpha=0.6)
+
+# divnorm=mcolors.TwoSlopeNorm(vmin=Z.min(), vcenter=0., vmax=Z.max())
+# plt.imshow(Z, extent=[x.min(), x.max(), y.min(), y.max()],origin='lower',
+#                   cmap=cmap, alpha=0.6)
+
+# plt.imshow(Z, extent=[x.min(), x.max(), y.min(), y.max()],origin='lower', norm = divnorm,
+#                   cmap=cmap, alpha=0.6)
+
+
+
+
+# COLORBAR :
+# cbar = plt.colorbar()
+# cbar.ax.tick_params(labelsize=8)
+
+
+
+
+# ##----- ADD RECTANGLE TO COVER QUADRANT :
+# epsilon = 0.4
+# epsilon = 0.1
+# # ax.axvspan(0, x.max(), y.min(), 0, alpha=1, color='yellow', zorder=5)#yellow
+# # ax.fill_between([0, x.max()], y.min(), 0, alpha=0.3, color='yellow', zorder=5)#yellow
+# # ax.fill_between([x.min(), 0], 0, y.max(), alpha=0.3, color='yellow', zorder=5)#yellow
+# ax.fill_between([0+epsilon, x.max()], y.min(), 0-epsilon, alpha=0.7, color='gray', zorder=5)#yellow
+# ax.fill_between([x.min(), 0-epsilon], 0+epsilon, y.max(), alpha=0.7, color='gray', zorder=5)#yellow
+
+
+
+#### LINE SEGMENTS :
+line = ax.plot(abar[0,:],abar[1,:],Z_bar, linewidth=2, color='coral', zorder=5)
+# line = ax.plot(abar[0,:],abar[1,:],Z_bar, linewidth=2, color='coral', zorder=1)
+# print('abar', abar)
+# print('abar.shape',abar.shape)
+# start = np.array([abar[0,499],abar[1,499],Z_bar[499]])
+# end = np.array([abar[0,500],abar[1,500],Z_bar[500]])
+# idx = np.where(np.round(Z_bar,3) == np.round( 0.02823972,3) )
+# print('idx[0][0]', idx[0][0])
+# line = ax.plot(abar[0,idx[0][0]:-1],abar[1,idx[0][0]:-1],Z_bar[idx[0][0]:-1], linewidth=2, color='coral', zorder=5)
+### -----------------------------------
+
+
+
+
+
+# ax.plot_surface(a1,a2, Z, cmap=cm.coolwarm,
+#                        linewidth=0, antialiased=False)
+
+# ax.plot_surface(tmp1,tmp2, Z, cmap=cm.coolwarm,
+#                        linewidth=0, antialiased=False)
+
+# ax.scatter(X_1,Y_1,Z1, s=0.2)
+# ax.scatter(X_2,Y_2,Z2, s=0.2)
+
+
+# X = np.concatenate((X_1, X_2), axis=0)
+# Y = np.concatenate((Y_1, Y_2), axis=0)
+# Z = np.concatenate((Z1, Z2), axis=0)
+# ax.plot_surface(X,Y,Z)
+
+
+ax.plot_surface(X_1,Y_1,Z1 ,cmap=cmap,
+                       linewidth=0, antialiased=True,alpha=.35, zorder=5)
+ax.plot_surface(X_2,Y_2,Z2 ,cmap=cmap,
+                       linewidth=0, antialiased=True,alpha=.35, zorder=5)
+# ax.plot_surface(X_1,Y_1,Z1 , facecolor = 'lightblue',     #cmap=cmap,
+#                        linewidth=0, antialiased=True, alpha=1, zorder=5)
+# ax.plot_surface(X_2,Y_2,Z2 , facecolor = 'lightblue', edgecolor='none',    #cmap=cmap,
+#                        linewidth=0, antialiased=True, alpha=1, zorder=5)
+
+# ax.plot_surface(X_1,Y_1,Z1 , #color='C0',
+# 							rstride=1, cstride=1,linewidth=0, antialiased=True, alpha=1, zorder=5)
+
+
+
+
+# ax.plot_surface(X_2,Y_2,Z2 , #color='C0',
+# 							rstride=1, cstride=1,linewidth=0,  alpha=0.8, zorder=5, shade=True)
+# ax.plot_surface(X_2,Y_2,Z2)
+
+# X_2 = X_2.reshape(-1,1).flatten()
+# Y_2 = Y_2.reshape(-1,1).flatten()
+# Z2 = Z2.reshape(-1,1).flatten()
+#
+# ax.plot_trisurf(X_2,Y_2,Z2, color='blue' )
+
+
+# X_1 = X_1.reshape(-1,1).flatten()
+# Y_1 = Y_1.reshape(-1,1).flatten()
+# Z1 = Z1.reshape(-1,1).flatten()
+# ax.plot_trisurf(X_1,Y_1,Z1 , color='blue')
+
+
+### MAYAVI TEST
+# mlab.figure(bgcolor=(1.0, 1.0, 1.0), size=(1000,1000))
+# mlab.view(azimuth=90, elevation=125)
+# mlab.view(azimuth=100, elevation=115)
+# axes = mlab.axes(color=(0, 0, 0), nb_labels=5)
+# mlab.orientation_axes()
+# mlab.mesh(X_1, Y_1,Z1, color=(0,0,1) ,  transparent=True )
+# mlab.plot3d(abar[0,:],abar[1,:],Z_bar, line_width=1)
+# mlab.mesh(X_2, Y_2,Z2)
+# mlab.savefig("./example.png")
+### --------------------------------------------
+
+
+
+# ax.plot_surface(X_1,Y_1,Z1 , cmap=cmap,
+#                        linewidth=0, antialiased=False,alpha=1, zorder=5)
+# ax.plot_surface(X_2,Y_2,Z2 , cmap=cmap,
+#                        linewidth=0, antialiased=True,alpha=1, zorder=5)
+
+# ax.plot_surface(X_2,Y_2,Z2 , color = 'lightblue',     #cmap=cmap,
+#                        linewidth=0, antialiased=True, alpha=1, zorder=5)
+
+
+# ax.plot(G[0,:],G[1,:],G[2,:])
+# ax.plot(abar[0,:],abar[1,:],Z_bar, linewidth=2, color='yellow', linestyle='--')
+# ax.scatter(abar[0,:],abar[1,:],Z_bar,  color='purple', zorder=5)
+# ax.plot(abar[0,:],abar[1,:],Z_bar, linewidth=2, color='royalblue', linestyle='--')
+# ax.plot(abar[0,:],abar[1,:],Z_bar, linewidth=3, color='dodgerblue', linestyle='--')
+# ax.plot(abar[0,:],abar[1,:],Z_bar, linewidth=3, color='cornflowerblue', linestyle='--')
+# ax.plot(abar[0,:],abar[1,:],Z_bar, linewidth=3, color='darkorange', linestyle='--')
+# ax.plot(abar[0,:],abar[1,:],Z_bar, linewidth=3, color='yellow', linestyle='--')
+# line = ax.plot(abar[0,:],abar[1,:],Z_bar, linewidth=1, color='coral', linestyle='--', zorder=3)
+
+
+# plot starting point:
+# ax.scatter(abar[0,0],abar[1,0],Z_bar[0], marker='^',  s=30, color='black', zorder=5)
+#
+#
+# ax.scatter(abar[0,500],abar[1,500],Z_bar[500], marker='^',  s=30, color='purple', zorder=5)
+
+# ax.scatter(start[0],start[1],start[2], marker='^',  s=30, color='purple', zorder=5)
+# ax.scatter(end[0],end[1],end[2], marker='^',  s=30, color='purple', zorder=5)
+
+
+# define origin
+o = np.array([0,0,0])
+
+start = np.array([1,0,0])
+end = np.array([2.5,0,0])
+
+
+print('start:', start)
+print('end:', end)
+
+
+dir = end-start
+print('dir:', dir)
+# ax.arrow()
+
+# ax.arrow3D(start[0],start[1],start[2],
+#            dir[0],dir[1],dir[2],
+#            mutation_scale=10,
+#            arrowstyle="->",
+#            linestyle='dashed',fc='coral',
+#            lw = 1,
+#            ec ='coral',
+#            zorder=3)
+
+# ax.arrow3D(midpoint_mapped[0],midpoint_mapped[1],midpoint_mapped[2],
+#            normal[0],normal[1],normal[2],
+#            mutation_scale=15,
+#             lw = 1.5,
+#            arrowstyle="-|>",
+#            linestyle='dashed',fc='blue',
+#            ec ='blue',
+#            zorder = 5)
+
+
+# ax.arrow3D(start[0],start[1],start[2],
+#            dir[0],dir[1],dir[2],
+#            mutation_scale=20,
+#            arrowstyle="->",
+#            fc='coral',
+#            lw = 1,
+#            ec ='coral',
+#            zorder=3)
+# ax.arrow3D(start[0],start[1],start[2],
+#            dir[0],dir[1],dir[2],
+#            mutation_scale=20,
+#            arrowstyle="->",
+#            fc='coral',
+#            lw = 1,
+#            ec ='coral',
+#            zorder=3)
+
+arrow_prop_dict = dict(mutation_scale=20, arrowstyle='-|>', color='k', shrinkA=0, shrinkB=0)
+# style = ArrowStyle('Fancy', head_length=1, head_width=1.5, tail_width=0.5)
+
+
+# ADD ARROW:
+# a = Arrow3D([start[0], end[0]], [start[1], end[1]], [start[2], end[2]], mutation_scale=15, arrowstyle='-|>', color='darkorange')
+# ax.add_artist(a)
+
+## ADD Annotation
+# ax.text(0, 0, 1.5, r"$\mathcal G^+$", color='royalblue', size=12)
+# ax.text(0, 0, 1.5, r"$\mathcal G^+$", color='royalblue', size=15)
+ax.text(0, 0, 1.5, r"$\mathcal G^+$", color='royalblue', size=13)
+# ax.text(0.5, 0.5, "Test")
+# ax.text(9, 0, 0, "red", color='red')
+
+### ---- Check proof:
+# value at t = 0:
+abar_zero= sstar*abar_tmp
+# value_0 = [abar_zero[0], abar_zero[1] , (2*abar_zero[0]*abar_zero[1])**0.5 ]
+value_0 = evaluate(abar_zero[0], abar_zero[1])
+print('value_0', value_0)
+# ax.scatter(value_0[0],value_0[1],value_0[2], marker='x',  s=20, color='dodgerblue', zorder=5)
+# ax.scatter(abar_zero[0], abar_zero[1],value_0, marker='o',  s=30, color='dodgerblue', zorder=5)
+## -----------------------------
+
+
+
+
+
+
+
+
+
+
+# ax.scatter(tmp1,tmp2, Z, cmap=cm.coolwarm,
+#                        linewidth=0, antialiased=False)
+# ax.plot_surface(tmp1,Z, tmp2, cmap=cm.coolwarm,
+#                        linewidth=0, antialiased=False)
+# ax.plot_trisurf(tmp1,tmp2, Z, cmap=cm.coolwarm,
+#                        linewidth=0, antialiased=False)
+
+
+# ax.plot(theta_rho, energy_axial1, 'royalblue', zorder=3, label=r"axialMin1")
+# ax.plot(theta_rho, energy_axial2, 'forestgreen', zorder=3, label=r"axialMin2")
+# ax.plot(-1.0*alphas, kappas, 'red', zorder=3, )
+
+
+
+
+# lg = ax.legend(bbox_to_anchor=(0.0, 0.75), loc='upper left')
+
+
+
+
+### PLOT X AND Y AXIS:
+# ax.plot(ax.get_xlim(),[0,0],'k--', linewidth=0.5)
+# ax.plot([0,0],ax.get_ylim(), 'k--', linewidth=0.5)
+ax.plot(ax.get_xlim(),[0,0],'k--', linewidth=1 ,zorder=5)
+ax.plot([0,0],ax.get_ylim(), 'k--', linewidth=1)
+
+
+
+# Plot 1-Parameter Line
+line_values= np.array(line_values)
+ax.plot(line_values[:,0],line_values[:,1],'k--', linewidth=1,color='orange',alpha=0.8)
+
+
+ax.set_xlabel(r"$a_1$", fontsize=10 ,labelpad=0)
+ax.set_ylabel(r"$a_2$", fontsize=10 ,labelpad=0)
+
+
+
+# ax.margins(x=0.5, y=-0.25)   # Values in (-0.5, 0.0) zooms in to center
+# ax.margins(x=0.5, y=0)   # Values in (-0.5, 0.0) zooms in to center
+
+
+plt.subplots_adjust(left=0.0)
+plt.subplots_adjust(bottom=0.1)
+
+plt.rcParams["figure.autolayout"] = True
+
+# ax.get_xaxis().set_visible(False)
+# ax = plt.gca(projection="3d")
+# ax._axis3don = False
+ZL = ax.get_zgridlines()
+
+# ax.set_ylabel(r"energy")
+
+
+# ax.set_xticks([-np.pi/2, -np.pi/4  ,0,  np.pi/4,  np.pi/2 ])
+# labels = ['$0$',r'$\pi/8$', r'$\pi/4$' ,r'$3\pi/8$' , r'$\pi/2$']
+# ax.set_yticklabels(labels)
+
+
+
+# ax.view_init(elev=30, azim=-65)
+
+# ax.legend(loc='upper right')
+
+# plt.tight_layout()
+# fig.tight_layout()
+
+fig.set_size_inches(width, height)
+fig.savefig('1-ParameterFamily_G+.pdf')
+
+plt.show()