ORTools_example08.m

% *********************************************************************
%             ORTools - Example 8
% *********************************************************************
% Reconstructing the prior beta Ti microstructure from alpha grains
% with the variant graph approach
% The MTEX description for reconstruction is given here:
% https://mtex-toolbox.github.io/TiBetaReconstruction.html
% *********************************************************************
% Dr. Azdiar Gazder, 2023, azdiaratuowdotedudotau
% Dr. Frank Niessen, 2023, contactatfniessendotcom
% (Remove "dot" and "at" to make this email address valid)
% *********************************************************************
home; close all; clear variables;
currentFolder;
set(0, 'DefaultFigureWindowStyle', 'normal');
screenPrint('StartUp', 'ORTools - Example 8 - Variant Graph Approach in Ti');

%% Initialize MTEX
% Startup and set some settings
startup_mtex;
setMTEXpref('xAxisDirection', 'east');
setMTEXpref('zAxisDirection', 'outOfPlane');
setMTEXpref('FontSize', 14);
setInterp2Tex;

% Default directories - Do not modify
Ini.dataPath = [strrep(pwd, '\', '/'), '/data/'];
Ini.cifPath = [Ini.dataPath, 'input/cif/'];
Ini.ebsdPath = [Ini.dataPath, 'input/ebsd/'];
Ini.texturePath = [Ini.dataPath, 'output/texture/'];
Ini.imagePath = [Ini.dataPath, 'output/images/'];

%% Load data
% Load an MTEX dataset into 'ebsd'
mtexDataset = 'alphaBetaTitanium';
screenPrint('SegmentStart', sprintf('Loading MTEX example data ''%s''', mtexDataset));
ebsd = mtexdata(mtexDataset);

%% Compute grains
screenPrint('SegmentStart', 'Computing, filtering and smoothing grains');
% Grains are calculated with a 1.5° threshold
[grains, ebsd] = calcGrains(ebsd('indexed'), 'threshold', 1.5 * degree, ...
                            'removeQuadruplePoints');
%% Rename and recolor phases
screenPrint('SegmentStart', 'Renaming and recoloring phases');
phaseNames = {'Alpha', 'Beta'};
% Rename "Ti (BETA) to "Beta"and "Ti (alpha)" to "Alpha"
ebsd = renamePhases(ebsd, phaseNames);
% Choose your favourite colors
ebsd = recolorPhases(ebsd);
%% Finding the orientation relationship
screenPrint('SegmentStart', 'Finding the orientation relationship(s)');
% Choose Beta as a parent and Alpha as a child phase in the transition
job = setParentGrainReconstructor(ebsd, grains, Ini.cifPath);
% Provide the OR
job.p2c = orientation.Burgers(ebsd('Beta').CS, ebsd('Alpha').CS);
% Let us check the disorientation
% (The disorientation is the misfit between the grain misorientations
% and the misorientation of the OR)
plotHist_OR_misfit(job);
% Plot information about the OR
ORinfo(job.p2c);

%% Plotting (with ORTools functions)
% ... is skipped for this example, check out example 2 for different plots

%% Reconstruct parent microstructure using the variant graph approach
%   - Reconstruct the microstructure with the variant graph based approach
job.calcVariantGraph('threshold', 1.5 * degree);
job.clusterVariantGraph('numIter', 3);
job.calcParentFromVote;
% Plot the reconstructed parent microstructure
figure;
plot(job.parentGrains, job.parentGrains.meanOrientation)

%% Clean reconstructed grains
% Now clean the grains by:
% - merging grains with similar orientation
job.mergeSimilar('threshold', 5 * degree);
% - merging small inclusions
job.mergeInclusions('maxSize', 10);
% This is the cleaned reconstructed parent microstructure
figure;
plot(job.parentGrains, job.parentGrains.meanOrientation);

%% Get parent EBSD data
figure;
parentEBSD = job.ebsd;
plot(parentEBSD('Beta'), parentEBSD('Beta').orientations);
hold on;
plot(job.grains.boundary, 'linewidth', 3);
%% Variant analysis
% Plot the variant pole figure
figure;
plotPDF_variants(job);
% We can calculate variants and packets
job.calcVariants;
% and plot the variant map
plotMap_variants(job, 'linewidth', 3);