Example_Deck_TSL.m

clear;
home;
close all;

%% Import Script for EBSD Data
%
% This script was automatically created by the import wizard. You should
% run the whoole script or parts of it in order to import your data. There
% is no problem in making any changes to this script.

%location of MTEX 5.10.2
%if MTEX loaded this doesn't matter
%if MTEX is not loaded, then this will be used to start MTEX up
mtex_location='C:\Users\ruthb\OneDrive\Documents\MTEX\mtex-5.11.2';
% mtex_location='/MATLAB Drive/mtex-5.10.2';

%start mtex if needed
try EBSD;
catch
    run(fullfile(mtex_location,"startup.m"));
end

%% Specify Crystal and Specimen Symmetries

% crystal symmetry
CS = {... 
  'notIndexed',...
  crystalSymmetry('SpaceId',194, [3.2 3.2 5.2], 'X||a', 'Y||b*', 'Z||c*', 'mineral', 'Magnesium', 'color', [0.53 0.81 0.98])};

%use this mineral for plotting
mineral_name=CS{2}.mineral;

% plotting convention
setMTEXpref('xAxisDirection','east');
setMTEXpref('zAxisDirection','inToPlane');

%% Specify File Names

% path to files
pname = 'C:\Users\ruthb\DocumentsOnLaptop\GitHub\MTEX_Workshop\Data';

% which files to be imported
fname = [pname '\scan1.ang'];

%% Import the Data

% create an EBSD variable containing the data
% ebsd = EBSD.load(fname,CS,'interface','ang',...
%   'convertEuler2SpatialReferenceFrame','setting 1');

ebsd = EBSD.load(fname,CS,'interface','ang',...
  'convertEuler2SpatialReferenceFrame','setting 2');

%% Do some plots

%band contrast
figure;
plot(ebsd,ebsd.prop.iq); colormap('gray');

%% IPF-x, y and z
% compute the colors
% ipfKey = ipfHSVKey(ebsd(mineral_name));
ipfKey = ipfTSLKey(ebsd(mineral_name));

%plot the key
f1=figure;
plot(ipfKey)

% now generate the IPF colour maps
ipfKey.inversePoleFigureDirection = vector3d.X;
colors_X = ipfKey.orientation2color(ebsd(mineral_name).orientations);
ipfKey.inversePoleFigureDirection = vector3d.Y;
colors_Y = ipfKey.orientation2color(ebsd(mineral_name).orientations);
ipfKey.inversePoleFigureDirection = vector3d.Z;
colors_Z = ipfKey.orientation2color(ebsd(mineral_name).orientations);

%now plot the three IPF coloured maps
f2=figure;
plot(ebsd(mineral_name),colors_X,'micronbar','off');
nextAxis
plot(ebsd(mineral_name),colors_Y,'micronbar','off');
nextAxis
plot(ebsd(mineral_name),colors_Z,'micronbar','on');

%% Plot a histogram of the quality data

figure;
subplot(2,1,1);
h1=histogram(ebsd(mineral_name).iq,100);
h1.Normalization='probability';
title('Image Quality');
ylabel('Frequency');
xlabel('Image Quality');

subplot(2,1,2);
h2=histogram(ebsd(mineral_name).ci,100);
h2.Normalization='probability';
title('Confidence Index');
ylabel('Frequency');

%% Filter the data based upon IQ and CI

%from these graphs I can select a threshold value for the phase to be ok
threshold_ci=0.1;
threshold_iq=1300;

%change the phase of the points we do not like to -1 [unindexed]
ebsd_filtered=ebsd;
ebsd_filtered(ebsd_filtered.iq < threshold_iq).phase=-1;
ebsd_filtered(ebsd_filtered.ci < threshold_ci).phase=-1;

figure;
plot(ebsd);
title('Original Data');
nextAxis;
plot(ebsd,ebsd.iq);
title('IQ');
nextAxis;
plot(ebsd,ebsd.ci);
title('CI');
nextAxis;
plot(ebsd_filtered);
title('Filtered Data');

%% Clean up this data
% personally I would rather see maps with data missing where it was
% misindexed
%
% some people prefer that they do some filling in of data 
% - this is data manipulation
% and so if you do not declare this you are committing scientific fraud

% grid this data
ebsd_filtered=gridify(ebsd_filtered);
ebsd_filtered_ok = ebsd_filtered('indexed');

%follow the method here: https://mtex-toolbox.github.io/EBSDFilling.html

% reconstruct the grain structure
[grains,ebsd_filtered_ok.grainId,ebsd_filtered_ok.mis2mean] = calcGrains(ebsd_filtered_ok,'angle',10*degree);

% remove some very small grains
ebsd_filtered_ok(grains(grains.grainSize<5)) = [];

% redo grain segementation
[grains,ebsd_filtered_ok.grainId] = calcGrains(ebsd_filtered_ok,'angle',10*degree);

% smooth grain boundaries
grains = smooth(grains,5);

% fill in data
ebsd_filtered_ok_filled = fill(ebsd_filtered_ok,grains);

%% Plot the map with some unit cells on it
ipfKey = ipfHSVKey(ebsd_filtered_ok(mineral_name));
ipfKey2 = ipfHSVKey(ebsd_filtered_ok_filled(mineral_name));

f1=figure;
plot(ipfKey)

ipfKey.inversePoleFigureDirection = vector3d.Z;
colors_Z = ipfKey.orientation2color(ebsd_filtered_ok(mineral_name).orientations);
colors_Z2 = ipfKey2.orientation2color(ebsd_filtered_ok_filled(mineral_name).orientations);


figure;
% plot the orientation map
plot(ebsd_filtered_ok(mineral_name),colors_Z)

% and on top the grain boundaries
hold on
plot(grains.boundary,'linewidth',1.5)
hold off


nextAxis
plot(ebsd_filtered_ok_filled(mineral_name),colors_Z2)

% and on top the grain boundaries
hold on
plot(grains.boundary,'linewidth',1.5)
hold off

nextAxis
plot(ebsd,ebsd.iq)

% and on top the grain boundaries
hold on
plot(grains.boundary,'linewidth',1.5)
colormap('gray');
hold off

nextAxis
plot(ebsd_filtered_ok_filled(mineral_name),colors_Z2)

% and on top the grain boundaries
hold on
plot(grains.boundary,'linewidth',1.5)


% plot the unit cells
%plot the crystal shape for this point
scaling = 250; % scale the crystal shape to have a nice size
%here we use a hexagon, but you could use a cube for cubic
%crystalShape.cube
cS = crystalShape.hex(grains(mineral_name).CS);
grain_centroids=grains.centroid;
plot(grain_centroids(:,1),grain_centroids(:,2),0, grains.meanOrientation * cS * scaling,'FaceAlpha',0.2); %make the hexagons also transparent so you can see the grains behind
xlim([min(ebsd.prop.x) max(ebsd.prop.x)]);
ylim([min(ebsd.prop.y) max(ebsd.prop.y)]);

%plot with the unit cells above, and scale their size by the grain size
nextAxis
plot(ebsd_filtered_ok_filled(mineral_name),colors_Z2)

% and on top the grain boundaries
hold on
plot(grains.boundary,'linewidth',1.5)
% plot the unit cells
%plot the crystal shape for this point
scaling = 250; % scale the crystal shape to have a nice size
%here we use a hexagon, but you could use a cube for cubic
%crystalShape.cube
cS = crystalShape.hex(grains(mineral_name).CS);
grain_centroids=grains.centroid;
plot(grain_centroids(:,1),grain_centroids(:,2),-max(grains.area), grains.meanOrientation * cS .*sqrt(grains.area./4),'FaceAlpha',0.9); %make the hexagons also transparent so you can see the grains behind
xlim([min(ebsd.prop.x) max(ebsd.prop.x)]);
ylim([min(ebsd.prop.y) max(ebsd.prop.y)]);

%% Measure the misorientation between two points

%first lets use the GUI tools to grab a few (well two) points
figure;
plot(ebsd_filtered_ok_filled(mineral_name),colors_Z2);
%click two points you want to extract
disp('click two points you want to measure the misorientations between')
[x_g,y_g]=ginput(2);

%find the pattern number for each of these points
pattern_number=zeros(size(x_g));
%find the nearest point in the data to this point
for n=1:numel(x_g)
    p_map=(ebsd.prop.x-x_g(n)).^2+(ebsd.prop.y-y_g(n)).^2;
    [mv,pattern_number(n)]=min(p_map);
end

ebsd_points=ebsd(pattern_number);

hold on;
scatter(ebsd_points.prop.x,ebsd_points.prop.y,'k');
scatter(ebsd_points(1).prop.x,ebsd_points(1).prop.y,'filled','w'); %make the first one white
scatter(ebsd_points(end).prop.x,ebsd_points(end).prop.y,'filled','k'); %make the last one black

%now we can calculate the misorientation angle between these two points
mis_angle_degree=angle(ebsd_points(1).orientations,ebsd_points(2).orientations)./degree
mis_axis=axis(ebsd_points(1).orientations,ebsd_points(2).orientations)

% We can also use this line segment to calculate a profile
% https://mtex-toolbox.github.io/EBSDProfile.html
hold on;
line(x_g,y_g,'linewidth',2,'Color','k')
line(x_g,y_g,'linewidth',1,'Color','w')
lineSeg=[x_g,y_g];

ebsd_line = spatialProfile(ebsd,lineSeg);

figure;
% misorientation angle to the first orientation on the line
plot(ebsd_line.y,...
  angle(ebsd_line(1).orientations,ebsd_line.orientations)/degree)

% misorientation gradient
hold all
plot(0.5*(ebsd_line.y(1:end-1)+ebsd_line.y(2:end)),...
  angle(ebsd_line(1:end-1).orientations,ebsd_line(2:end).orientations)/degree)
hold off

xlabel('y'); ylabel('misorientation angle in degree')

legend('to reference orientation','orientation gradient')