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  • s7603593/dune-microstructure
  • s7603593/dune-microstructure-backup
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.gitignore 0 → 100644
View file @ 41316745
# ignore all build folders
/build*/
build/
# ignore backup files
*~
# ignore python files
#*.pyc
# ignore pdfs
*.pdf
#ignore log
*.log
# ignore vts
*.vts
*.vtu
# ignore png
*.png
#ignore kdevelop files
*.kdev4
.gitlab-ci.yml 0 → 100644
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---
# Install external dependencies
before_script:
- duneci-install-module https://gitlab.dune-project.org/fufem/dune-matrix-vector.git
- duneci-install-module https://git.imp.fu-berlin.de/agnumpde/dune-solvers.git
- duneci-install-module https://gitlab.dune-project.org/fufem/dune-fufem.git
dune:2.9 debian-11 gcc-10 C++20:
variables:
DUNECI_BRANCH: releases/2.9
image: registry.dune-project.org/docker/ci/dune:2.9-debian-11-gcc-10-20
before_script:
script: duneci-standard-test
dune:git ubuntu-20-04 clang-10 C++20:
image: registry.dune-project.org/docker/ci/dune:git-ubuntu-20.04-clang-10-20
script: duneci-standard-test
dune:git debian-11 gcc-10 C++20:
image: registry.dune-project.org/docker/ci/dune:git-debian-11-gcc-10-20
script: duneci-standard-test
CMakeLists.txt 0 → 100644
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# We require CMake version 3.1 to prevent issues
# with dune_enable_all_packages and older CMake versions.
cmake_minimum_required(VERSION 3.1)
project(dune-microstructure CXX)
if(NOT (dune-common_DIR OR dune-common_ROOT OR
"${CMAKE_PREFIX_PATH}" MATCHES ".*dune-common.*"))
string(REPLACE ${CMAKE_PROJECT_NAME} dune-common dune-common_DIR
${PROJECT_BINARY_DIR})
endif()
#find dune-common and set the module path
find_package(dune-common REQUIRED)
list(APPEND CMAKE_MODULE_PATH "${PROJECT_SOURCE_DIR}/cmake/modules"
${dune-common_MODULE_PATH})
#include the dune macros
include(DuneMacros)
# start a dune project with information from dune.module
dune_project()
dune_enable_all_packages()
add_subdirectory(src)
add_subdirectory(dune)
add_subdirectory(doc)
add_subdirectory(cmake/modules)
# finalize the dune project, e.g. generating config.h etc.
finalize_dune_project(GENERATE_CONFIG_H_CMAKE)
HowTo-DefineMaterial.txt 0 → 100644
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1. Define new material, prestrain and indicator function @ /dune/microstructure/materialDefinitions.hh
2. Add Case (Materialname) to "setupMaterial" method @ /dune/prestrainedMaterial.hh
3. set new materialname parameter @ /inputs/cellsolver.parset
Matlab-Programs/BMatrix.txt 0 → 100644
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1 1 -0.612883927868050238
1 2 -0.599999999999977551
1 3 -0.000197872958097770234
Matlab-Programs/MatlabDuneImport.m 0 → 100644
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new_mat = spconvert(load('matlab.txt')); %Sparse Matrix type
new_mat = full(new_mat)
Matlab-Programs/Minimization.mlx 0 → 100644
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File added
Matlab-Programs/Minimization_Script.m 0 → 100644
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clear all
clc
% status = system('mkdir mynew')
% command = './build-cmake/src/dune-microstructure ./inputs/cellsolver.parset';
% system(['set PATH=' '/home/klaus/Desktop/DUNE/dune-microstructure' ';' command ]);
% --- Change PolynomialDisplayStyle ----
% sympref('PolynomialDisplayStyle','ascend');
% sympref('AbbreviateOutput',false);
syms f_plus(v1,v2,q1,q2,q3,b1,b2,b3)
assume( q1 > 0)
assume( q2 > 0)
assume( q3 > 0)
assume( q3 >= q1)
assume( q2 >= q3)
v = [v1; v2];
%should be sqrt(2) instead of 2
fprintf('Functions to be minimized \n')
f_plus(v1,v2,q1,q2,q3,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);
f_minus(v1,v2,q1,q2,q3,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);
% ---- Fix parameters
absPath = "/home/klaus/Desktop/DUNE/dune-microstructure/outputs";
% 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)
% Substitute effective quantitites
f_plus = subs(f_plus,q1,Qmat(1,1));
f_plus = subs(f_plus,q3,Qmat(3,3));
f_plus = subs(f_plus,q2,Qmat(2,2));
f_plus = subs(f_plus,b1,Bmat(1));
f_plus = subs(f_plus,b2,Bmat(2));
f_plus = subs(f_plus,b3,Bmat(3));
% f_plus = subs(f_plus,b3,0);
%
f_minus = subs(f_minus,q1,Qmat(1,1));
f_minus = subs(f_minus,q3,Qmat(3,3));
f_minus = subs(f_minus,q2,Qmat(2,2));
f_minus = subs(f_minus,b1,Bmat(1));
f_minus = subs(f_minus,b2,Bmat(2));
f_minus = subs(f_minus,b3,Bmat(3));
% % f_minus = subs(f_minus,b3,0);
% 2. Substitute specific values:
%%%Compare with 'ClassifyMin-Code'
% % Compare with 'ClassifyMin-Code'
% mu_1 = 1;
% rho_1 = 1;
% % --- type 1 Situation:
% % beta = 2;
% % alpha = 2;
% % theta = 1/4;
% % --- type 2 Situation:
% % beta = 3.0714;
% % alpha = -20;
% % theta = 0.3;
% % --- type 3 Situation:
% % beta = 2.2857;
% % alpha = -20;
% % theta = 0.3;
%
% % interesting:
% alpha = 18.3673;
% beta = 8.57143;
% theta= 0.913265;
%
% % alpha = 2.85714;
% % beta = 7;
% % theta= 0.3;
%
%
%
% set_mu_gamma = 'q1';
% % set_mu_gamma = 'q2';
% print_output = false;
%
% q1i = mu_1.*(beta./(theta+(1-theta).*beta))
% q2i = mu_1.*((1-theta)+theta.*beta)
% q3i = q1i
% % b1i = (mu_1*rho_1/4).*(beta./(theta+(1-theta).*beta)).*(1-theta.*(1+alpha))
% % b2i = mu_1.*(rho_1/8).*(1-theta.*(1+beta.*alpha))
% b3i = 0
%
% %TEST (new)
% b1i = (3*rho_1/2).*beta.*(1-theta.*(1+alpha));
% b2i = (3*rho_1/(4*((1-theta)+theta.*beta))).*(1-theta.*(1+beta.*alpha));
%
% f_plus = subs(f_plus,q1,q1i);
% f_plus = subs(f_plus,q3,q3i);
% f_plus = subs(f_plus,q2,q2i);
% f_plus = subs(f_plus,b1,b1i);
% f_plus = subs(f_plus,b2,b2i);
% f_plus = subs(f_plus,b3,b3i)
%
% f_minus = subs(f_minus,q1,q1i);
% f_minus = subs(f_minus,q3,q3i);
% f_minus = subs(f_minus,q2,q2i);
% f_minus = subs(f_minus,b1,b1i);
% f_minus = subs(f_minus,b2,b2i);
% f_minus = subs(f_minus,b3,b3i)
%
%
%
% [A,angle,V] = classifyMIN(mu_1,rho_1,alpha,beta,theta,set_mu_gamma,print_output)
% Substitute random values...
% rndm1 = randi([1 20],1,1);
% rndm2 = randi([1 20],1,1);
% rndm3 = randi([1 20],1,1);
% f_plus = subs(f_plus,b1,rndm1);
% f_plus = subs(f_plus,b2,rndm2);
% f_plus = subs(f_plus,b3,rndm3);
% 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 = [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 = solve(eqns,v1,v2,'MaxDegree' , 5);
S_minus = solve(eqns_minus,v1,v2,'MaxDegree' , 5);
%Tests:
% S = solve(eqns,v1,v2,'MaxDegree' , 5, 'Real', true);
% S_minus = solve(eqns_minus,v1,v2,'MaxDegree' , 5, 'Real', true);
% S = solve(eqns,v1,v2,'MaxDegree' , 5, 'IgnoreAnalyticConstraints',true);
% S = solve(eqns,v1,v2,'MaxDegree' , 5, 'IgnoreAnalyticConstraints',true, 'Real', true);
% S = solve(eqns)
A = S.v1;
B = S.v2;
A_minus = S_minus.v1;
B_minus = S_minus.v2;
% A = simplify(A);
% B = simplify(B)
%---------- TEST if Grad(f) = 0 ---------------------
% fprintf('Testing equation grad(f) = 0 with stationary points')
%
% for i = 1:size(A,1)
% fprintf('Testing %d.point (f_plus): ',i )
% [ double(subs(subs(df_plusx,v1,A(i)),v2,B(i))), double(subs(subs(df_plusy,v1,A(i)),v2,B(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
% ------------------------------------
fprintf('stationary points of f_plus:')
A = double(A); %safe symbolic values
B = double(B);
fprintf('stationary points of f_minus:')
A_minus = double(A_minus);
B_minus = double(B_minus);
% Extract only Real-Solutions
fprintf('real stationary points of f_plus:')
tmp1 = A(imag(A)==0 & imag(B) == 0);
tmp2 = B(imag(A)==0 & imag(B) == 0);
A = tmp1;
B = tmp2;
% A(abs(imag(A)) <1e-3 & abs(imag(B)) <1e-3 )
SP_Plus = [A,B]
fprintf('real stationary points of f_minus:')
tmp1 = A_minus(imag(A_minus)==0 & imag(B_minus) == 0);
tmp2 = B_minus(imag(A_minus)==0 & imag(B_minus) == 0);
A_minus = tmp1;
B_minus = tmp2;
% A_minus(abs(imag(A_minus)) <1e-3 & abs(imag(B_minus)) <1e-3 )
SP_Minus = [A_minus,B_minus]
% Determine global Minimizer from stationary points:
fprintf('function values at stationary points (f_plus):')
T = arrayfun(@(v1,v2) double(f_plus(v1,v2,q1,q2,q3,b1,b2,b3)),A,B,'UniformOutput', false)
T = cell2mat(T);
% Min_plus = min(T, [], 'all')
[Min_plus,MinIdx_plus] = min(T, [], 'all', 'linear');
fprintf('function values at stationary points (f_minus):')
T_minus = arrayfun(@(v1,v2) double(f_minus(v1,v2,q1,q2,q3,b1,b2,b3)),A_minus,B_minus,'UniformOutput', false)
T_minus = cell2mat(T_minus);
% Min_minus = min(T_minus, [], 'all')
[Min_minus,MinIdx_minus] = min(T_minus, [], 'all', 'linear');
[globalMinimizerValue,GlobalIdx] = min([Min_plus,Min_minus]);
if GlobalIdx == 1 %Min_plus
GlobalMinimizer = SP_Plus(MinIdx_plus,:);
sign = 1.0;
elseif GlobalIdx == 2 %Min_minus
GlobalMinimizer = SP_Minus(MinIdx_minus,:);
sign = -1.0;
end
fprintf('Global Minimizer:(%d,%d)', GlobalMinimizer(1),GlobalMinimizer(2) )
fprintf('Global Minimizer Value : %d', globalMinimizerValue )
% Plot functions
fsurf(@(x,y) f_plus(x,y,q1,q2,q3,b1,b2,b3))
hold on
plot3(A,B,T,'g*')
%Plot GlobalMinimizer:
hold on
plot3(GlobalMinimizer(1),GlobalMinimizer(2),globalMinimizerValue, 'o', 'Color','c')
% view(90,0)
% view(2)
figure
fsurf(@(x,y) f_minus(x,y,q1,q2,q3,b1,b2,b3))
hold on
plot3(A_minus,B_minus,T_minus,'g*')
hold on
plot3(GlobalMinimizer(1),GlobalMinimizer(2),globalMinimizerValue, 'o', 'Color','c')
%Write to txt-File
fileID = fopen('txt.txt','w');
fprintf(fileID,'%s' , latex(S.v1));
fclose(fileID);
%%%Compare with 'ClassifyMin-Code'
fprintf('----------------compare with ClassifyMIN----------------')
fprintf('Output Minimizer Matrix from symbolic Minimization')
sign*GlobalMinimizer'*GlobalMinimizer %sign correct? should do this with symbolic Values! TODO
% GlobalMinimizer'*GlobalMinimizer
%check with higher Precision:
% vpa(GlobalMinimizer'*GlobalMinimizer)
% %
% % %Output from Classify Min:
% % [A,angle,type,K] = classifyMIN(mu_1,rho_1,alpha,beta,theta,set_mu_gamma,print_output);
% % fprintf('Output Minimizer Matrix from ClassifyMIN')
% %
% % % [A(1) sign*sqrt(A(1)*A(2)) ; sign*sqrt(A(1)*A(2)) A(2)] %sign correct?
% % [A(1) sqrt(A(1)*A(2)) ; sqrt(A(1)*A(2)) A(2)] %sign correct?
% %
% % %check with higher Precision:
% % % vpa([A(1) sqrt(A(1)*A(2)) ; sqrt(A(1)*A(2)) A(2)])
% %
% %
% % e = [sqrt(A(1)), sqrt(A(2))]; %TODO .. this might be complex?!
% %
% % norm = sqrt((A(1)+A(2)));
% %
% % e = e./norm;
% %
% % K*(e'*e)
% %
% % % e'*e
% % % K
% %
% % fprintf('angle: %d', angle)
% % fprintf('Type: %d', type)
%% Compare with "Task2"
% fprintf('----------------compare with Task2----------------')
%
% B = [b1i b3i; b3i b2i];
% x = 0:0.01:2*pi;
%
% y1 = arrayfun(@(alpha)compute_F(alpha,B,q1i,q2i,q3i),x,'UniformOutput', false);
% y1 = cell2mat(y1);
%
%
% figure
% plot(x,y1,'b')
% hold on
%
% fun = @(a) compute_F(a,B,q1i,q2i,q3i);
% [alphaMin,f] = fminunc(fun,0)
% [alphaMin,f] = fminunc(fun,3) % Different initial value
% plot(alphaMin,f,'*')
%
% %compute radius
% rMin = compute_r(alphaMin,B,q1i,q2i,q3i)
%
% %compute Minimizer:
% v_alpha = [cos(alphaMin);sin(alphaMin)];
%
%
%
% G = rMin.*(v_alpha*v_alpha')
%%Determine Minimizer Type (in general case)
% % T = [GlobalMinimizer' e1']
% % det(T) % also works?
% %
% %
% % % symbolically :
% %
% % if GlobalIdx == 1 %Min_plus
% % A_sym = S.v1;
% % B_sym = S.v2
% % Index = MinIdx_plus;
% % elseif GlobalIdx == 2 %Min_minus
% % A_sym = S_minus.v1;
% % B_sym = S_minus.v2;
% % Index = MinIdx_minus;
% % end
% %
% % % Check Determinant symbolically?!?!
% %
% % g_sym = [A_sym(Index) B_sym(Index)]
% % G_sym = g_sym'*g_sym
% %
% % e1 = [1 0];
% % e2 = [0 1];
% %
% % % check alignment with e1
% % % if ....
% % det([g_sym' e1'])
% % % ... bending in e1 direction
% % % check alignment with e2
% % % if..
% % det([g_sym' e2'])
% % double(det([g_sym' e2']))
% % % bending in e2 direction
% % %Else
% % %....
Matlab-Programs/Minimization_abstract.mlx 0 → 100755
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Matlab-Programs/Minimization_compare.mlx 0 → 100644
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Matlab-Programs/PD.py 0 → 100644
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# state file generated using paraview version 5.7.0
# ----------------------------------------------------------------
# setup views used in the visualization
# ----------------------------------------------------------------
# trace generated using paraview version 5.7.0
#
# To ensure correct image size when batch processing, please search
# for and uncomment the line `# renderView*.ViewSize = [*,*]`
#### import the simple module from the paraview
from paraview.simple import *
#### disable automatic camera reset on 'Show'
paraview.simple._DisableFirstRenderCameraReset()
# Create a new 'Render View'
renderView1 = CreateView('RenderView')
renderView1.ViewSize = [964, 795]
renderView1.AxesGrid = 'GridAxes3DActor'
renderView1.CenterOfRotation = [20.0, 25.25, 19.999999225139618]
renderView1.StereoType = 'Crystal Eyes'
renderView1.CameraPosition = [19.716196756133453, -140.19818563854574, 19.725993950408547]
renderView1.CameraFocalPoint = [19.716196756133453, 4.1990335064686235, 19.725993950408554]
renderView1.CameraViewUp = [0.0, 0.0, 1.0]
renderView1.CameraFocalDisk = 1.0
renderView1.CameraParallelScale = 37.37275037457204
renderView1.Background = [0.32, 0.34, 0.43]
SetActiveView(None)
# ----------------------------------------------------------------
# setup view layouts
# ----------------------------------------------------------------
# create new layout object 'Layout #1'
layout1 = CreateLayout(name='Layout #1')
layout1.AssignView(0, renderView1)
# ----------------------------------------------------------------
# restore active view
SetActiveView(renderView1)
# ----------------------------------------------------------------
# ----------------------------------------------------------------
# setup the data processing pipelines
# ----------------------------------------------------------------
# create a new 'Legacy VTK Reader'
phaseDiagramvtk = LegacyVTKReader(FileNames=['/home/klaus/Desktop/DUNE/dune-microstructure/Matlab-Programs/PhaseDiagram.vtk'])
# create a new 'Legacy VTK Reader'
phaseDiagramvtk_1 = LegacyVTKReader(FileNames=['/home/klaus/Desktop/DUNE/dune-microstructure/Matlab-Programs/PhaseDiagram.vtk'])
# create a new 'Legacy VTK Reader'
phaseDiagramvtk_2 = LegacyVTKReader(FileNames=['/home/klaus/Desktop/DUNE/dune-microstructure/Matlab-Programs/PhaseDiagram.vtk'])
# create a new 'Legacy VTK Reader'
legacyVTKReader1 = LegacyVTKReader(FileNames=['/home/klaus/Desktop/DUNE/dune-microstructure/Matlab-Programs/wind.vtk'])
# create a new 'Transform'
transform1 = Transform(Input=phaseDiagramvtk_2)
transform1.Transform = 'Transform'
# init the 'Transform' selected for 'Transform'
transform1.Transform.Scale = [1.0, 1.0, 40.0]
# create a new 'Legacy VTK Reader'
phaseDiagramvtk_3 = LegacyVTKReader(FileNames=['/home/klaus/Desktop/DUNE/dune-microstructure/Matlab-Programs/PhaseDiagram.vtk'])
# create a new 'Legacy VTK Reader'
phaseDiagramvtk_4 = LegacyVTKReader(FileNames=['/home/klaus/Desktop/DUNE/dune-microstructure/Matlab-Programs/PhaseDiagram.vtk'])
# ----------------------------------------------------------------
# setup the visualization in view 'renderView1'
# ----------------------------------------------------------------
# show data from transform1
transform1Display = Show(transform1, renderView1)
# get color transfer function/color map for 'type'
typeLUT = GetColorTransferFunction('type')
typeLUT.RGBPoints = [0.0, 0.0, 0.0, 1.0, 0.0, 0.17254901960784313, 0.043137254901960784, 0.9215686274509803, 0.0, 0.785929, 0.247056, 0.295477, 0.0, 0.17254901960784313, 0.043137254901960784, 0.9215686274509803, 0.5332077132980828, 0.41568627450980394, 0.00392156862745098, 0.9686274509803922, 0.8393082088494452, 0.48627450980392156, 0.0, 0.9725490196078431, 1.5502514522630406, 1.0, 0.5215686274509804, 0.9607843137254902, 2.4093082613015326, 1.0, 0.043137254901960784, 0.5529411764705883, 3.140000104904175, 1.0, 0.0, 0.01568627450980392]
typeLUT.ColorSpace = 'Lab'
typeLUT.NanColor = [0.0, 1.0, 0.0]
typeLUT.NumberOfTableValues = 593
typeLUT.ScalarRangeInitialized = 1.0
# get opacity transfer function/opacity map for 'type'
typePWF = GetOpacityTransferFunction('type')
typePWF.Points = [0.0, 1.0, 0.5, 0.0, 1.0269182920455933, 0.36764705181121826, 0.5, 0.0, 1.6292452668398216, 0.08088235557079315, 0.5, 0.0, 2.3500630855560303, 0.3602941334247589, 0.5, 0.0, 2.804276943206787, 0.6176470518112183, 0.5, 0.0, 3.140000104904175, 1.0, 0.5, 0.0]
typePWF.ScalarRangeInitialized = 1
# trace defaults for the display properties.
transform1Display.Representation = 'Points'
transform1Display.ColorArrayName = ['POINTS', 'type']
transform1Display.LookupTable = typeLUT
transform1Display.OSPRayScaleArray = 'type'
transform1Display.OSPRayScaleFunction = 'PiecewiseFunction'
transform1Display.SelectOrientationVectors = 'None'
transform1Display.ScaleFactor = 4.95
transform1Display.SelectScaleArray = 'type'
transform1Display.GlyphType = 'Arrow'
transform1Display.GlyphTableIndexArray = 'type'
transform1Display.GaussianRadius = 0.2475
transform1Display.SetScaleArray = ['POINTS', 'type']
transform1Display.ScaleTransferFunction = 'PiecewiseFunction'
transform1Display.OpacityArray = ['POINTS', 'type']
transform1Display.OpacityTransferFunction = 'PiecewiseFunction'
transform1Display.DataAxesGrid = 'GridAxesRepresentation'
transform1Display.PolarAxes = 'PolarAxesRepresentation'
transform1Display.ScalarOpacityFunction = typePWF
transform1Display.ScalarOpacityUnitDistance = 0.7474550074914409
# init the 'PiecewiseFunction' selected for 'OSPRayScaleFunction'
transform1Display.OSPRayScaleFunction.Points = [1.0, 0.8602941036224365, 0.5, 0.0, 1.213836476688135, 0.625, 0.5, 0.0, 1.3616352081298828, 0.6691176295280457, 0.5, 0.0, 1.6666333299996667, 0.8676470518112183, 0.5, 0.0, 1.7358490228652954, 0.6911764740943909, 0.5, 0.0, 2.0, 0.8014705777168274, 0.5, 0.0]
# init the 'PiecewiseFunction' selected for 'ScaleTransferFunction'
transform1Display.ScaleTransferFunction.Points = [0.0, 0.8602941036224365, 0.5, 0.0, 0.6714465592330834, 0.625, 0.5, 0.0, 1.1355345914648751, 0.6691176295280457, 0.5, 0.0, 2.093228726131573, 0.8676470518112183, 0.5, 0.0, 2.310566008990662, 0.6911764740943909, 0.5, 0.0, 3.140000104904175, 0.8014705777168274, 0.5, 0.0]
# init the 'PiecewiseFunction' selected for 'OpacityTransferFunction'
transform1Display.OpacityTransferFunction.Points = [0.0, 0.8602941036224365, 0.5, 0.0, 0.6714465592330834, 0.625, 0.5, 0.0, 1.1355345914648751, 0.6691176295280457, 0.5, 0.0, 2.093228726131573, 0.8676470518112183, 0.5, 0.0, 2.310566008990662, 0.6911764740943909, 0.5, 0.0, 3.140000104904175, 0.8014705777168274, 0.5, 0.0]
# setup the color legend parameters for each legend in this view
# get color legend/bar for typeLUT in view renderView1
typeLUTColorBar = GetScalarBar(typeLUT, renderView1)
typeLUTColorBar.Position = [0.8796680497925311, 0.01509433962264151]
typeLUTColorBar.Title = 'type'
typeLUTColorBar.ComponentTitle = ''
# set color bar visibility
typeLUTColorBar.Visibility = 1
# show color legend
transform1Display.SetScalarBarVisibility(renderView1, True)
# ----------------------------------------------------------------
# setup color maps and opacity mapes used in the visualization
# note: the Get..() functions create a new object, if needed
# ----------------------------------------------------------------
# ----------------------------------------------------------------
# finally, restore active source
SetActiveSource(phaseDiagramvtk_2)
# ----------------------------------------------------------------
\ No newline at end of file
Matlab-Programs/PhaseDiagram.vtk 0 → 100644
View file @ 41316745
# vtk DataFile Version 2.0
VTK from Matlab
ASCII
DATASET STRUCTURED_GRID
DIMENSIONS 1 30 30
POINTS 900 float
0.00 2.00 0.01 0.34 2.00 0.01 0.69 2.00 0.01 1.03 2.00 0.01 1.38 2.00 0.01 1.72 2.00 0.01 2.07 2.00 0.01 2.41 2.00 0.01 2.76 2.00 0.01 3.10 2.00 0.01 3.45 2.00 0.01 3.79 2.00 0.01 4.14 2.00 0.01 4.48 2.00 0.01 4.83 2.00 0.01 5.17 2.00 0.01 5.52 2.00 0.01 5.86 2.00 0.01 6.21 2.00 0.01 6.55 2.00 0.01 6.90 2.00 0.01 7.24 2.00 0.01 7.59 2.00 0.01 7.93 2.00 0.01 8.28 2.00 0.01 8.62 2.00 0.01 8.97 2.00 0.01 9.31 2.00 0.01 9.66 2.00 0.01 10.00 2.00 0.01 0.00 2.00 0.04 0.34 2.00 0.04 0.69 2.00 0.04 1.03 2.00 0.04 1.38 2.00 0.04 1.72 2.00 0.04 2.07 2.00 0.04 2.41 2.00 0.04 2.76 2.00 0.04 3.10 2.00 0.04 3.45 2.00 0.04 3.79 2.00 0.04 4.14 2.00 0.04 4.48 2.00 0.04 4.83 2.00 0.04 5.17 2.00 0.04 5.52 2.00 0.04 5.86 2.00 0.04 6.21 2.00 0.04 6.55 2.00 0.04 6.90 2.00 0.04 7.24 2.00 0.04 7.59 2.00 0.04 7.93 2.00 0.04 8.28 2.00 0.04 8.62 2.00 0.04 8.97 2.00 0.04 9.31 2.00 0.04 9.66 2.00 0.04 10.00 2.00 0.04 0.00 2.00 0.08 0.34 2.00 0.08 0.69 2.00 0.08 1.03 2.00 0.08 1.38 2.00 0.08 1.72 2.00 0.08 2.07 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0.15 4.48 2.00 0.15 4.83 2.00 0.15 5.17 2.00 0.15 5.52 2.00 0.15 5.86 2.00 0.15 6.21 2.00 0.15 6.55 2.00 0.15 6.90 2.00 0.15 7.24 2.00 0.15 7.59 2.00 0.15 7.93 2.00 0.15 8.28 2.00 0.15 8.62 2.00 0.15 8.97 2.00 0.15 9.31 2.00 0.15 9.66 2.00 0.15 10.00 2.00 0.15 0.00 2.00 0.18 0.34 2.00 0.18 0.69 2.00 0.18 1.03 2.00 0.18 1.38 2.00 0.18 1.72 2.00 0.18 2.07 2.00 0.18 2.41 2.00 0.18 2.76 2.00 0.18 3.10 2.00 0.18 3.45 2.00 0.18 3.79 2.00 0.18 4.14 2.00 0.18 4.48 2.00 0.18 4.83 2.00 0.18 5.17 2.00 0.18 5.52 2.00 0.18 5.86 2.00 0.18 6.21 2.00 0.18 6.55 2.00 0.18 6.90 2.00 0.18 7.24 2.00 0.18 7.59 2.00 0.18 7.93 2.00 0.18 8.28 2.00 0.18 8.62 2.00 0.18 8.97 2.00 0.18 9.31 2.00 0.18 9.66 2.00 0.18 10.00 2.00 0.18 0.00 2.00 0.21 0.34 2.00 0.21 0.69 2.00 0.21 1.03 2.00 0.21 1.38 2.00 0.21 1.72 2.00 0.21 2.07 2.00 0.21 2.41 2.00 0.21 2.76 2.00 0.21 3.10 2.00 0.21 3.45 2.00 0.21 3.79 2.00 0.21 4.14 2.00 0.21 4.48 2.00 0.21 4.83 2.00 0.21 5.17 2.00 0.21 5.52 2.00 0.21 5.86 2.00 0.21 6.21 2.00 0.21 6.55 2.00 0.21 6.90 2.00 0.21 7.24 2.00 0.21 7.59 2.00 0.21 7.93 2.00 0.21 8.28 2.00 0.21 8.62 2.00 0.21 8.97 2.00 0.21 9.31 2.00 0.21 9.66 2.00 0.21 10.00 2.00 0.21 0.00 2.00 0.25 0.34 2.00 0.25 0.69 2.00 0.25 1.03 2.00 0.25 1.38 2.00 0.25 1.72 2.00 0.25 2.07 2.00 0.25 2.41 2.00 0.25 2.76 2.00 0.25 3.10 2.00 0.25 3.45 2.00 0.25 3.79 2.00 0.25 4.14 2.00 0.25 4.48 2.00 0.25 4.83 2.00 0.25 5.17 2.00 0.25 5.52 2.00 0.25 5.86 2.00 0.25 6.21 2.00 0.25 6.55 2.00 0.25 6.90 2.00 0.25 7.24 2.00 0.25 7.59 2.00 0.25 7.93 2.00 0.25 8.28 2.00 0.25 8.62 2.00 0.25 8.97 2.00 0.25 9.31 2.00 0.25 9.66 2.00 0.25 10.00 2.00 0.25 0.00 2.00 0.28 0.34 2.00 0.28 0.69 2.00 0.28 1.03 2.00 0.28 1.38 2.00 0.28 1.72 2.00 0.28 2.07 2.00 0.28 2.41 2.00 0.28 2.76 2.00 0.28 3.10 2.00 0.28 3.45 2.00 0.28 3.79 2.00 0.28 4.14 2.00 0.28 4.48 2.00 0.28 4.83 2.00 0.28 5.17 2.00 0.28 5.52 2.00 0.28 5.86 2.00 0.28 6.21 2.00 0.28 6.55 2.00 0.28 6.90 2.00 0.28 7.24 2.00 0.28 7.59 2.00 0.28 7.93 2.00 0.28 8.28 2.00 0.28 8.62 2.00 0.28 8.97 2.00 0.28 9.31 2.00 0.28 9.66 2.00 0.28 10.00 2.00 0.28 0.00 2.00 0.31 0.34 2.00 0.31 0.69 2.00 0.31 1.03 2.00 0.31 1.38 2.00 0.31 1.72 2.00 0.31 2.07 2.00 0.31 2.41 2.00 0.31 2.76 2.00 0.31 3.10 2.00 0.31 3.45 2.00 0.31 3.79 2.00 0.31 4.14 2.00 0.31 4.48 2.00 0.31 4.83 2.00 0.31 5.17 2.00 0.31 5.52 2.00 0.31 5.86 2.00 0.31 6.21 2.00 0.31 6.55 2.00 0.31 6.90 2.00 0.31 7.24 2.00 0.31 7.59 2.00 0.31 7.93 2.00 0.31 8.28 2.00 0.31 8.62 2.00 0.31 8.97 2.00 0.31 9.31 2.00 0.31 9.66 2.00 0.31 10.00 2.00 0.31 0.00 2.00 0.35 0.34 2.00 0.35 0.69 2.00 0.35 1.03 2.00 0.35 1.38 2.00 0.35 1.72 2.00 0.35 2.07 2.00 0.35 2.41 2.00 0.35 2.76 2.00 0.35 3.10 2.00 0.35 3.45 2.00 0.35 3.79 2.00 0.35 4.14 2.00 0.35 4.48 2.00 0.35 4.83 2.00 0.35 5.17 2.00 0.35 5.52 2.00 0.35 5.86 2.00 0.35 6.21 2.00 0.35 6.55 2.00 0.35 6.90 2.00 0.35 7.24 2.00 0.35 7.59 2.00 0.35 7.93 2.00 0.35 8.28 2.00 0.35 8.62 2.00 0.35 8.97 2.00 0.35 9.31 2.00 0.35 9.66 2.00 0.35 10.00 2.00 0.35 0.00 2.00 0.38 0.34 2.00 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2.76 2.00 0.45 3.10 2.00 0.45 3.45 2.00 0.45 3.79 2.00 0.45 4.14 2.00 0.45 4.48 2.00 0.45 4.83 2.00 0.45 5.17 2.00 0.45 5.52 2.00 0.45 5.86 2.00 0.45 6.21 2.00 0.45 6.55 2.00 0.45 6.90 2.00 0.45 7.24 2.00 0.45 7.59 2.00 0.45 7.93 2.00 0.45 8.28 2.00 0.45 8.62 2.00 0.45 8.97 2.00 0.45 9.31 2.00 0.45 9.66 2.00 0.45 10.00 2.00 0.45 0.00 2.00 0.48 0.34 2.00 0.48 0.69 2.00 0.48 1.03 2.00 0.48 1.38 2.00 0.48 1.72 2.00 0.48 2.07 2.00 0.48 2.41 2.00 0.48 2.76 2.00 0.48 3.10 2.00 0.48 3.45 2.00 0.48 3.79 2.00 0.48 4.14 2.00 0.48 4.48 2.00 0.48 4.83 2.00 0.48 5.17 2.00 0.48 5.52 2.00 0.48 5.86 2.00 0.48 6.21 2.00 0.48 6.55 2.00 0.48 6.90 2.00 0.48 7.24 2.00 0.48 7.59 2.00 0.48 7.93 2.00 0.48 8.28 2.00 0.48 8.62 2.00 0.48 8.97 2.00 0.48 9.31 2.00 0.48 9.66 2.00 0.48 10.00 2.00 0.48 0.00 2.00 0.52 0.34 2.00 0.52 0.69 2.00 0.52 1.03 2.00 0.52 1.38 2.00 0.52 1.72 2.00 0.52 2.07 2.00 0.52 2.41 2.00 0.52 2.76 2.00 0.52 3.10 2.00 0.52 3.45 2.00 0.52 3.79 2.00 0.52 4.14 2.00 0.52 4.48 2.00 0.52 4.83 2.00 0.52 5.17 2.00 0.52 5.52 2.00 0.52 5.86 2.00 0.52 6.21 2.00 0.52 6.55 2.00 0.52 6.90 2.00 0.52 7.24 2.00 0.52 7.59 2.00 0.52 7.93 2.00 0.52 8.28 2.00 0.52 8.62 2.00 0.52 8.97 2.00 0.52 9.31 2.00 0.52 9.66 2.00 0.52 10.00 2.00 0.52 0.00 2.00 0.55 0.34 2.00 0.55 0.69 2.00 0.55 1.03 2.00 0.55 1.38 2.00 0.55 1.72 2.00 0.55 2.07 2.00 0.55 2.41 2.00 0.55 2.76 2.00 0.55 3.10 2.00 0.55 3.45 2.00 0.55 3.79 2.00 0.55 4.14 2.00 0.55 4.48 2.00 0.55 4.83 2.00 0.55 5.17 2.00 0.55 5.52 2.00 0.55 5.86 2.00 0.55 6.21 2.00 0.55 6.55 2.00 0.55 6.90 2.00 0.55 7.24 2.00 0.55 7.59 2.00 0.55 7.93 2.00 0.55 8.28 2.00 0.55 8.62 2.00 0.55 8.97 2.00 0.55 9.31 2.00 0.55 9.66 2.00 0.55 10.00 2.00 0.55 0.00 2.00 0.58 0.34 2.00 0.58 0.69 2.00 0.58 1.03 2.00 0.58 1.38 2.00 0.58 1.72 2.00 0.58 2.07 2.00 0.58 2.41 2.00 0.58 2.76 2.00 0.58 3.10 2.00 0.58 3.45 2.00 0.58 3.79 2.00 0.58 4.14 2.00 0.58 4.48 2.00 0.58 4.83 2.00 0.58 5.17 2.00 0.58 5.52 2.00 0.58 5.86 2.00 0.58 6.21 2.00 0.58 6.55 2.00 0.58 6.90 2.00 0.58 7.24 2.00 0.58 7.59 2.00 0.58 7.93 2.00 0.58 8.28 2.00 0.58 8.62 2.00 0.58 8.97 2.00 0.58 9.31 2.00 0.58 9.66 2.00 0.58 10.00 2.00 0.58 0.00 2.00 0.62 0.34 2.00 0.62 0.69 2.00 0.62 1.03 2.00 0.62 1.38 2.00 0.62 1.72 2.00 0.62 2.07 2.00 0.62 2.41 2.00 0.62 2.76 2.00 0.62 3.10 2.00 0.62 3.45 2.00 0.62 3.79 2.00 0.62 4.14 2.00 0.62 4.48 2.00 0.62 4.83 2.00 0.62 5.17 2.00 0.62 5.52 2.00 0.62 5.86 2.00 0.62 6.21 2.00 0.62 6.55 2.00 0.62 6.90 2.00 0.62 7.24 2.00 0.62 7.59 2.00 0.62 7.93 2.00 0.62 8.28 2.00 0.62 8.62 2.00 0.62 8.97 2.00 0.62 9.31 2.00 0.62 9.66 2.00 0.62 10.00 2.00 0.62 0.00 2.00 0.65 0.34 2.00 0.65 0.69 2.00 0.65 1.03 2.00 0.65 1.38 2.00 0.65 1.72 2.00 0.65 2.07 2.00 0.65 2.41 2.00 0.65 2.76 2.00 0.65 3.10 2.00 0.65 3.45 2.00 0.65 3.79 2.00 0.65 4.14 2.00 0.65 4.48 2.00 0.65 4.83 2.00 0.65 5.17 2.00 0.65 5.52 2.00 0.65 5.86 2.00 0.65 6.21 2.00 0.65 6.55 2.00 0.65 6.90 2.00 0.65 7.24 2.00 0.65 7.59 2.00 0.65 7.93 2.00 0.65 8.28 2.00 0.65 8.62 2.00 0.65 8.97 2.00 0.65 9.31 2.00 0.65 9.66 2.00 0.65 10.00 2.00 0.65 0.00 2.00 0.69 0.34 2.00 0.69 0.69 2.00 0.69 1.03 2.00 0.69 1.38 2.00 0.69 1.72 2.00 0.69 2.07 2.00 0.69 2.41 2.00 0.69 2.76 2.00 0.69 3.10 2.00 0.69 3.45 2.00 0.69 3.79 2.00 0.69 4.14 2.00 0.69 4.48 2.00 0.69 4.83 2.00 0.69 5.17 2.00 0.69 5.52 2.00 0.69 5.86 2.00 0.69 6.21 2.00 0.69 6.55 2.00 0.69 6.90 2.00 0.69 7.24 2.00 0.69 7.59 2.00 0.69 7.93 2.00 0.69 8.28 2.00 0.69 8.62 2.00 0.69 8.97 2.00 0.69 9.31 2.00 0.69 9.66 2.00 0.69 10.00 2.00 0.69 0.00 2.00 0.72 0.34 2.00 0.72 0.69 2.00 0.72 1.03 2.00 0.72 1.38 2.00 0.72 1.72 2.00 0.72 2.07 2.00 0.72 2.41 2.00 0.72 2.76 2.00 0.72 3.10 2.00 0.72 3.45 2.00 0.72 3.79 2.00 0.72 4.14 2.00 0.72 4.48 2.00 0.72 4.83 2.00 0.72 5.17 2.00 0.72 5.52 2.00 0.72 5.86 2.00 0.72 6.21 2.00 0.72 6.55 2.00 0.72 6.90 2.00 0.72 7.24 2.00 0.72 7.59 2.00 0.72 7.93 2.00 0.72 8.28 2.00 0.72 8.62 2.00 0.72 8.97 2.00 0.72 9.31 2.00 0.72 9.66 2.00 0.72 10.00 2.00 0.72 0.00 2.00 0.75 0.34 2.00 0.75 0.69 2.00 0.75 1.03 2.00 0.75 1.38 2.00 0.75 1.72 2.00 0.75 2.07 2.00 0.75 2.41 2.00 0.75 2.76 2.00 0.75 3.10 2.00 0.75 3.45 2.00 0.75 3.79 2.00 0.75 4.14 2.00 0.75 4.48 2.00 0.75 4.83 2.00 0.75 5.17 2.00 0.75 5.52 2.00 0.75 5.86 2.00 0.75 6.21 2.00 0.75 6.55 2.00 0.75 6.90 2.00 0.75 7.24 2.00 0.75 7.59 2.00 0.75 7.93 2.00 0.75 8.28 2.00 0.75 8.62 2.00 0.75 8.97 2.00 0.75 9.31 2.00 0.75 9.66 2.00 0.75 10.00 2.00 0.75 0.00 2.00 0.79 0.34 2.00 0.79 0.69 2.00 0.79 1.03 2.00 0.79 1.38 2.00 0.79 1.72 2.00 0.79 2.07 2.00 0.79 2.41 2.00 0.79 2.76 2.00 0.79 3.10 2.00 0.79 3.45 2.00 0.79 3.79 2.00 0.79 4.14 2.00 0.79 4.48 2.00 0.79 4.83 2.00 0.79 5.17 2.00 0.79 5.52 2.00 0.79 5.86 2.00 0.79 6.21 2.00 0.79 6.55 2.00 0.79 6.90 2.00 0.79 7.24 2.00 0.79 7.59 2.00 0.79 7.93 2.00 0.79 8.28 2.00 0.79 8.62 2.00 0.79 8.97 2.00 0.79 9.31 2.00 0.79 9.66 2.00 0.79 10.00 2.00 0.79 0.00 2.00 0.82 0.34 2.00 0.82 0.69 2.00 0.82 1.03 2.00 0.82 1.38 2.00 0.82 1.72 2.00 0.82 2.07 2.00 0.82 2.41 2.00 0.82 2.76 2.00 0.82 3.10 2.00 0.82 3.45 2.00 0.82 3.79 2.00 0.82 4.14 2.00 0.82 4.48 2.00 0.82 4.83 2.00 0.82 5.17 2.00 0.82 5.52 2.00 0.82 5.86 2.00 0.82 6.21 2.00 0.82 6.55 2.00 0.82 6.90 2.00 0.82 7.24 2.00 0.82 7.59 2.00 0.82 7.93 2.00 0.82 8.28 2.00 0.82 8.62 2.00 0.82 8.97 2.00 0.82 9.31 2.00 0.82 9.66 2.00 0.82 10.00 2.00 0.82 0.00 2.00 0.85 0.34 2.00 0.85 0.69 2.00 0.85 1.03 2.00 0.85 1.38 2.00 0.85 1.72 2.00 0.85 2.07 2.00 0.85 2.41 2.00 0.85 2.76 2.00 0.85 3.10 2.00 0.85 3.45 2.00 0.85 3.79 2.00 0.85 4.14 2.00 0.85 4.48 2.00 0.85 4.83 2.00 0.85 5.17 2.00 0.85 5.52 2.00 0.85 5.86 2.00 0.85 6.21 2.00 0.85 6.55 2.00 0.85 6.90 2.00 0.85 7.24 2.00 0.85 7.59 2.00 0.85 7.93 2.00 0.85 8.28 2.00 0.85 8.62 2.00 0.85 8.97 2.00 0.85 9.31 2.00 0.85 9.66 2.00 0.85 10.00 2.00 0.85 0.00 2.00 0.89 0.34 2.00 0.89 0.69 2.00 0.89 1.03 2.00 0.89 1.38 2.00 0.89 1.72 2.00 0.89 2.07 2.00 0.89 2.41 2.00 0.89 2.76 2.00 0.89 3.10 2.00 0.89 3.45 2.00 0.89 3.79 2.00 0.89 4.14 2.00 0.89 4.48 2.00 0.89 4.83 2.00 0.89 5.17 2.00 0.89 5.52 2.00 0.89 5.86 2.00 0.89 6.21 2.00 0.89 6.55 2.00 0.89 6.90 2.00 0.89 7.24 2.00 0.89 7.59 2.00 0.89 7.93 2.00 0.89 8.28 2.00 0.89 8.62 2.00 0.89 8.97 2.00 0.89 9.31 2.00 0.89 9.66 2.00 0.89 10.00 2.00 0.89 0.00 2.00 0.92 0.34 2.00 0.92 0.69 2.00 0.92 1.03 2.00 0.92 1.38 2.00 0.92 1.72 2.00 0.92 2.07 2.00 0.92 2.41 2.00 0.92 2.76 2.00 0.92 3.10 2.00 0.92 3.45 2.00 0.92 3.79 2.00 0.92 4.14 2.00 0.92 4.48 2.00 0.92 4.83 2.00 0.92 5.17 2.00 0.92 5.52 2.00 0.92 5.86 2.00 0.92 6.21 2.00 0.92 6.55 2.00 0.92 6.90 2.00 0.92 7.24 2.00 0.92 7.59 2.00 0.92 7.93 2.00 0.92 8.28 2.00 0.92 8.62 2.00 0.92 8.97 2.00 0.92 9.31 2.00 0.92 9.66 2.00 0.92 10.00 2.00 0.92 0.00 2.00 0.96 0.34 2.00 0.96 0.69 2.00 0.96 1.03 2.00 0.96 1.38 2.00 0.96 1.72 2.00 0.96 2.07 2.00 0.96 2.41 2.00 0.96 2.76 2.00 0.96 3.10 2.00 0.96 3.45 2.00 0.96 3.79 2.00 0.96 4.14 2.00 0.96 4.48 2.00 0.96 4.83 2.00 0.96 5.17 2.00 0.96 5.52 2.00 0.96 5.86 2.00 0.96 6.21 2.00 0.96 6.55 2.00 0.96 6.90 2.00 0.96 7.24 2.00 0.96 7.59 2.00 0.96 7.93 2.00 0.96 8.28 2.00 0.96 8.62 2.00 0.96 8.97 2.00 0.96 9.31 2.00 0.96 9.66 2.00 0.96 10.00 2.00 0.96 0.00 2.00 0.99 0.34 2.00 0.99 0.69 2.00 0.99 1.03 2.00 0.99 1.38 2.00 0.99 1.72 2.00 0.99 2.07 2.00 0.99 2.41 2.00 0.99 2.76 2.00 0.99 3.10 2.00 0.99 3.45 2.00 0.99 3.79 2.00 0.99 4.14 2.00 0.99 4.48 2.00 0.99 4.83 2.00 0.99 5.17 2.00 0.99 5.52 2.00 0.99 5.86 2.00 0.99 6.21 2.00 0.99 6.55 2.00 0.99 6.90 2.00 0.99 7.24 2.00 0.99 7.59 2.00 0.99 7.93 2.00 0.99 8.28 2.00 0.99 8.62 2.00 0.99 8.97 2.00 0.99 9.31 2.00 0.99 9.66 2.00 0.99 10.00 2.00 0.99
POINT_DATA 900
SCALARS type float
LOOKUP_TABLE default
0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.57 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.57 1.57 1.57 1.57 1.57 1.57 1.57 1.57 1.57 1.57 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.57 1.57 1.57 1.57 1.57 1.57 1.57 1.57 1.57 0.86 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.57 1.57 1.57 1.57 1.57 1.57 1.57 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.57 1.57 1.57 1.57 1.57 0.32 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.57 1.57 1.57 1.57 0.90 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.57 1.57 1.57 0.84 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.57 1.57 1.57 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.57 1.57 1.57 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.57 1.57 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.57 1.57 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.57 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.57 0.56 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.57 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.59 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.57 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.57 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.57 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.57 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
\ No newline at end of file
Matlab-Programs/PhaseDiagram2D.vtk 0 → 100644
View file @ 41316745
Source diff could not be displayed: it is too large. Options to address this: view the blob.
Matlab-Programs/PhaseDiagramNew.pvsm 0 → 100644
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Matlab-Programs/PhaseDiagramType.vtk 0 → 100644
View file @ 41316745
# vtk DataFile Version 2.0
VTK from Matlab
ASCII
DATASET STRUCTURED_GRID
DIMENSIONS 1 30 30
POINTS 900 float
0.00 2.00 0.01 0.34 2.00 0.01 0.69 2.00 0.01 1.03 2.00 0.01 1.38 2.00 0.01 1.72 2.00 0.01 2.07 2.00 0.01 2.41 2.00 0.01 2.76 2.00 0.01 3.10 2.00 0.01 3.45 2.00 0.01 3.79 2.00 0.01 4.14 2.00 0.01 4.48 2.00 0.01 4.83 2.00 0.01 5.17 2.00 0.01 5.52 2.00 0.01 5.86 2.00 0.01 6.21 2.00 0.01 6.55 2.00 0.01 6.90 2.00 0.01 7.24 2.00 0.01 7.59 2.00 0.01 7.93 2.00 0.01 8.28 2.00 0.01 8.62 2.00 0.01 8.97 2.00 0.01 9.31 2.00 0.01 9.66 2.00 0.01 10.00 2.00 0.01 0.00 2.00 0.04 0.34 2.00 0.04 0.69 2.00 0.04 1.03 2.00 0.04 1.38 2.00 0.04 1.72 2.00 0.04 2.07 2.00 0.04 2.41 2.00 0.04 2.76 2.00 0.04 3.10 2.00 0.04 3.45 2.00 0.04 3.79 2.00 0.04 4.14 2.00 0.04 4.48 2.00 0.04 4.83 2.00 0.04 5.17 2.00 0.04 5.52 2.00 0.04 5.86 2.00 0.04 6.21 2.00 0.04 6.55 2.00 0.04 6.90 2.00 0.04 7.24 2.00 0.04 7.59 2.00 0.04 7.93 2.00 0.04 8.28 2.00 0.04 8.62 2.00 0.04 8.97 2.00 0.04 9.31 2.00 0.04 9.66 2.00 0.04 10.00 2.00 0.04 0.00 2.00 0.08 0.34 2.00 0.08 0.69 2.00 0.08 1.03 2.00 0.08 1.38 2.00 0.08 1.72 2.00 0.08 2.07 2.00 0.08 2.41 2.00 0.08 2.76 2.00 0.08 3.10 2.00 0.08 3.45 2.00 0.08 3.79 2.00 0.08 4.14 2.00 0.08 4.48 2.00 0.08 4.83 2.00 0.08 5.17 2.00 0.08 5.52 2.00 0.08 5.86 2.00 0.08 6.21 2.00 0.08 6.55 2.00 0.08 6.90 2.00 0.08 7.24 2.00 0.08 7.59 2.00 0.08 7.93 2.00 0.08 8.28 2.00 0.08 8.62 2.00 0.08 8.97 2.00 0.08 9.31 2.00 0.08 9.66 2.00 0.08 10.00 2.00 0.08 0.00 2.00 0.11 0.34 2.00 0.11 0.69 2.00 0.11 1.03 2.00 0.11 1.38 2.00 0.11 1.72 2.00 0.11 2.07 2.00 0.11 2.41 2.00 0.11 2.76 2.00 0.11 3.10 2.00 0.11 3.45 2.00 0.11 3.79 2.00 0.11 4.14 2.00 0.11 4.48 2.00 0.11 4.83 2.00 0.11 5.17 2.00 0.11 5.52 2.00 0.11 5.86 2.00 0.11 6.21 2.00 0.11 6.55 2.00 0.11 6.90 2.00 0.11 7.24 2.00 0.11 7.59 2.00 0.11 7.93 2.00 0.11 8.28 2.00 0.11 8.62 2.00 0.11 8.97 2.00 0.11 9.31 2.00 0.11 9.66 2.00 0.11 10.00 2.00 0.11 0.00 2.00 0.15 0.34 2.00 0.15 0.69 2.00 0.15 1.03 2.00 0.15 1.38 2.00 0.15 1.72 2.00 0.15 2.07 2.00 0.15 2.41 2.00 0.15 2.76 2.00 0.15 3.10 2.00 0.15 3.45 2.00 0.15 3.79 2.00 0.15 4.14 2.00 0.15 4.48 2.00 0.15 4.83 2.00 0.15 5.17 2.00 0.15 5.52 2.00 0.15 5.86 2.00 0.15 6.21 2.00 0.15 6.55 2.00 0.15 6.90 2.00 0.15 7.24 2.00 0.15 7.59 2.00 0.15 7.93 2.00 0.15 8.28 2.00 0.15 8.62 2.00 0.15 8.97 2.00 0.15 9.31 2.00 0.15 9.66 2.00 0.15 10.00 2.00 0.15 0.00 2.00 0.18 0.34 2.00 0.18 0.69 2.00 0.18 1.03 2.00 0.18 1.38 2.00 0.18 1.72 2.00 0.18 2.07 2.00 0.18 2.41 2.00 0.18 2.76 2.00 0.18 3.10 2.00 0.18 3.45 2.00 0.18 3.79 2.00 0.18 4.14 2.00 0.18 4.48 2.00 0.18 4.83 2.00 0.18 5.17 2.00 0.18 5.52 2.00 0.18 5.86 2.00 0.18 6.21 2.00 0.18 6.55 2.00 0.18 6.90 2.00 0.18 7.24 2.00 0.18 7.59 2.00 0.18 7.93 2.00 0.18 8.28 2.00 0.18 8.62 2.00 0.18 8.97 2.00 0.18 9.31 2.00 0.18 9.66 2.00 0.18 10.00 2.00 0.18 0.00 2.00 0.21 0.34 2.00 0.21 0.69 2.00 0.21 1.03 2.00 0.21 1.38 2.00 0.21 1.72 2.00 0.21 2.07 2.00 0.21 2.41 2.00 0.21 2.76 2.00 0.21 3.10 2.00 0.21 3.45 2.00 0.21 3.79 2.00 0.21 4.14 2.00 0.21 4.48 2.00 0.21 4.83 2.00 0.21 5.17 2.00 0.21 5.52 2.00 0.21 5.86 2.00 0.21 6.21 2.00 0.21 6.55 2.00 0.21 6.90 2.00 0.21 7.24 2.00 0.21 7.59 2.00 0.21 7.93 2.00 0.21 8.28 2.00 0.21 8.62 2.00 0.21 8.97 2.00 0.21 9.31 2.00 0.21 9.66 2.00 0.21 10.00 2.00 0.21 0.00 2.00 0.25 0.34 2.00 0.25 0.69 2.00 0.25 1.03 2.00 0.25 1.38 2.00 0.25 1.72 2.00 0.25 2.07 2.00 0.25 2.41 2.00 0.25 2.76 2.00 0.25 3.10 2.00 0.25 3.45 2.00 0.25 3.79 2.00 0.25 4.14 2.00 0.25 4.48 2.00 0.25 4.83 2.00 0.25 5.17 2.00 0.25 5.52 2.00 0.25 5.86 2.00 0.25 6.21 2.00 0.25 6.55 2.00 0.25 6.90 2.00 0.25 7.24 2.00 0.25 7.59 2.00 0.25 7.93 2.00 0.25 8.28 2.00 0.25 8.62 2.00 0.25 8.97 2.00 0.25 9.31 2.00 0.25 9.66 2.00 0.25 10.00 2.00 0.25 0.00 2.00 0.28 0.34 2.00 0.28 0.69 2.00 0.28 1.03 2.00 0.28 1.38 2.00 0.28 1.72 2.00 0.28 2.07 2.00 0.28 2.41 2.00 0.28 2.76 2.00 0.28 3.10 2.00 0.28 3.45 2.00 0.28 3.79 2.00 0.28 4.14 2.00 0.28 4.48 2.00 0.28 4.83 2.00 0.28 5.17 2.00 0.28 5.52 2.00 0.28 5.86 2.00 0.28 6.21 2.00 0.28 6.55 2.00 0.28 6.90 2.00 0.28 7.24 2.00 0.28 7.59 2.00 0.28 7.93 2.00 0.28 8.28 2.00 0.28 8.62 2.00 0.28 8.97 2.00 0.28 9.31 2.00 0.28 9.66 2.00 0.28 10.00 2.00 0.28 0.00 2.00 0.31 0.34 2.00 0.31 0.69 2.00 0.31 1.03 2.00 0.31 1.38 2.00 0.31 1.72 2.00 0.31 2.07 2.00 0.31 2.41 2.00 0.31 2.76 2.00 0.31 3.10 2.00 0.31 3.45 2.00 0.31 3.79 2.00 0.31 4.14 2.00 0.31 4.48 2.00 0.31 4.83 2.00 0.31 5.17 2.00 0.31 5.52 2.00 0.31 5.86 2.00 0.31 6.21 2.00 0.31 6.55 2.00 0.31 6.90 2.00 0.31 7.24 2.00 0.31 7.59 2.00 0.31 7.93 2.00 0.31 8.28 2.00 0.31 8.62 2.00 0.31 8.97 2.00 0.31 9.31 2.00 0.31 9.66 2.00 0.31 10.00 2.00 0.31 0.00 2.00 0.35 0.34 2.00 0.35 0.69 2.00 0.35 1.03 2.00 0.35 1.38 2.00 0.35 1.72 2.00 0.35 2.07 2.00 0.35 2.41 2.00 0.35 2.76 2.00 0.35 3.10 2.00 0.35 3.45 2.00 0.35 3.79 2.00 0.35 4.14 2.00 0.35 4.48 2.00 0.35 4.83 2.00 0.35 5.17 2.00 0.35 5.52 2.00 0.35 5.86 2.00 0.35 6.21 2.00 0.35 6.55 2.00 0.35 6.90 2.00 0.35 7.24 2.00 0.35 7.59 2.00 0.35 7.93 2.00 0.35 8.28 2.00 0.35 8.62 2.00 0.35 8.97 2.00 0.35 9.31 2.00 0.35 9.66 2.00 0.35 10.00 2.00 0.35 0.00 2.00 0.38 0.34 2.00 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POINT_DATA 900
SCALARS type float
LOOKUP_TABLE default
1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 2.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 3.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 2.00 2.00 2.00 2.00 2.00 3.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 2.00 2.00 2.00 2.00 3.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 2.00 2.00 2.00 3.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 2.00 2.00 2.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 2.00 2.00 2.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 2.00 2.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 2.00 2.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 2.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 2.00 3.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 2.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 3.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 2.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 2.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 2.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 2.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
\ No newline at end of file
Matlab-Programs/PhaseDiagramType2D.vtk 0 → 100644
View file @ 41316745
Source diff could not be displayed: it is too large. Options to address this: view the blob.
Matlab-Programs/PhaseDiagrams.mlx 0 → 100644
View file @ 41316745
File added
Matlab-Programs/PhaseDiagramsScript.m 0 → 100644
View file @ 41316745
clear all
clc
% INPUT Parameters
mu_1 = 1;
rho_1 = 1;
theta= 0.3;
alpha = 2;
beta= 2;
fprintf('===========================================================================================================================');
fprintf(' Possible cases for global minimizers: (I) , (II) , (III) , (IV) ')
fprintf('============================================== INPUT PARAMETERS ===========================================================');
fprintf('mu_1: %d rho:1: %d theta: %d', mu_1,rho_1,theta );
fprintf('===========================================================================================================================');
% choose u_gamma = q3 to be either q1, q2 or something in between
% set_mu_gamma = 'q1';
set_mu_gamma = 'q2'; %(hyperbolic-case)
% set_mu_gamma = 'm'; % mean of q1,q2
% print_output = true;
print_output = false;
% Test for fixed value
% [A,angle,type] = classifyMIN(mu_1,rho_1,alpha,beta,theta,set_mu_gamma,print_output);
% PLOT
x = linspace(-20,20,45); %~alpha
y = linspace(1.5,40,45); %~beta
z = linspace(0.05,0.95,45); %~theta
[X1,Y1] = meshgrid(x,y);
[A_2D,angle_2D,V_2D] = arrayfun(@(a,b)classifyMIN(mu_1,rho_1,a,b,theta,set_mu_gamma,print_output),X1,Y1,'UniformOutput', false);
[X,Y,Z] = meshgrid(x,y,z);
[A,angle_3D,V_3D] = arrayfun(@(a,b,theta)classifyMIN(mu_1,rho_1,a,b,theta,set_mu_gamma,print_output),X,Y,Z,'UniformOutput', false);
color_3D = cell2mat(V_3D);
color_2D = cell2mat(V_2D);
angle_2D = cell2mat(angle_2D);
angle_3D = cell2mat(angle_3D);
A = cell2mat(A);
A_2D = cell2mat(A_2D);
X1 = reshape(X1,[],1);
Y1 = reshape(Y1,[],1);
X = reshape(X,[],1);
Y = reshape(Y,[],1);
Z = reshape(Z,[],1);
color_2D = reshape(color_2D,[],1);
color_3D = reshape(color_3D,[],1);
angle_2D = reshape(angle_2D,[],1);
angle_3D = reshape(angle_3D,[],1);
% Structure result depending on Type/Color
% V_2D = reshape(V_2D,[],1);
V_2DT1 = (color_2D == 1);
V_2DT2 = (color_2D == 2);
V_2DT3 = (color_2D == 3);
V_2DT1 = reshape(V_2DT1,[],1);
V_2DT2 = reshape(V_2DT2,[],1);
V_2DT3 = reshape(V_2DT3,[],1);
X1T1 = V_2DT1.*X1;
Y1T1 = V_2DT1.*Y1;
X1T2 = V_2DT2.*X1;
Y1T2 = V_2DT2.*Y1;
X1T3 = V_2DT3.*X1;
Y1T3 = V_2DT3.*Y1;
%%% 2D - Plot (fixed Theta)
cm_2D = redblue(3);
scatter(X1T1,Y1T1,[], 'MarkerFaceColor',[0 0 1 ], 'MarkerEdgeColor','black');
colormap(cm_2D)
hold on
scatter(X1T2,Y1T2,[], 'MarkerFaceColor',[1 0 0], 'MarkerEdgeColor','black');
hold on
% scatter(X1T3,Y1T3,[],'MarkerFaceColor',[0 0 1 ], 'MarkerEdgeColor','black');
scatter(X1T3,Y1T3,[], angle_2D, 'filled','MarkerEdgeColor','black');
colormap(cm_2D)
legend('Type 1', 'Type 2', 'Type 3')
title('Fixed Theta Plot')
xlabel('alpha')
ylabel('beta')
hold off
%%% 3D - Plot
V_3DT1 = (color_3D == 1);
V_3DT2 = (color_3D == 2);
V_3DT3 = (color_3D == 3);
V_3DT1 = reshape(V_3DT1,[],1);
V_3DT2 = reshape(V_3DT2,[],1);
V_3DT3 = reshape(V_3DT3,[],1);
XT1 = V_3DT1.*X;
YT1 = V_3DT1.*Y;
ZT1 = V_3DT1.*Z;
XT2 = V_3DT2.*X;
YT2 = V_3DT2.*Y;
ZT2 = V_3DT2.*Z;
XT3 = V_3DT3.*X;
YT3 = V_3DT3.*Y;
ZT3 = V_3DT3.*Z;
cm = redblue(90);
figure
%fixed Color
% scatter3(XT1,YT1,ZT1, [], 'MarkerFaceColor',[0.75 0 0],'MarkerEdgeColor', 'none');
%variing Color
scatter3(YT1,ZT1,XT1, [], 'MarkerFaceColor',[0 0 1 ], 'MarkerEdgeColor','black');
colormap(cm);
hold on
scatter3(YT2,ZT2,XT2, [], 'MarkerFaceColor',[1 0 0],'MarkerEdgeColor', 'none');
hold on
% scatter3(XT3,YT3,ZT3, [],'MarkerFaceColor',[0 0 1 ],'MarkerEdgeColor', 'none');
scatter3(YT3,ZT3,XT3, [], angle_3D, 'filled');
legend('Type 1', 'Type 2', 'Type 3')
title('Classification of Minimizers, theta:')
% xlabel('alpha')
% ylabel('beta')
% zlabel('theta')
xlabel('beta')
ylabel('theta')
zlabel('alpha')
Matlab-Programs/PythonMatlabTest.py 0 → 100644
View file @ 41316745
import numpy as np
import matplotlib.pyplot as plt
import sympy as sym
import math
import os
import subprocess
import fileinput
import re
#import sys
import matlab.engine
eng = matlab.engine.start_matlab()
# tf = eng.findParabolic
# print(tf)
# eng.findParabolic(nargout=0)
eng.Minimization_Script(nargout=0)
print('Running Python Code')
Matlab-Programs/QMatrix.txt 0 → 100644
View file @ 41316745
1 1 2.07819448498850168
1 2 -9.59442219281886493e-22
1 3 9.20995372360501347e-07
2 1 -9.87702818837798838e-20
2 2 2.08333333333341164
2 3 -9.79796825055082683e-21
3 1 6.10325081515254299e-05
3 2 -1.77052129286940134e-20
3 3 2.08273199371863926