kilir

mtexdata sharp
%make sure grain boundaries are not considered
[grains, ebsd.grainId] = ebsd.calcGrains;

% % smooth the data
f = halfQuadraticFilter;
ebsd = smooth(ebsd,f);

% make a single phase, gridified ebsd
ebsd =ebsd('c').gridify;

kilir

% lets's have some data
mtexdata olivine
% Let's take a crop of the data
% This can also be accomplished interactively by:
% plot(ebsd)
% [ebsd,rec] = selectInteractive(ebsd);
ebsd = ebsd(inpolygon(ebsd,[152 296 427 313]))
plot(ebsd)
%% calculating grains
% In mtex, there are currently three different approaches to compute grains

kilir

%% example how to compute inter-phase slip transmission (mprime)
%% get some example data
mtexdata forsterite

%for simplicity restrict phases and fill
[grains, ebsd.grainId] = ebsd.calcGrains;
ebsd(grains(grains.grainSize < 50)) =[];
ebsd = fill(ebsd);
[grains, ebsd.grainId] = ebsd.calcGrains;

kilir

function h = ellipse(r,a,b,varargin)
% annotate an ellipse
%
% Input
%  r        -  @rotation specifying the ellipse position
%  a,b      -  long/short half axes of ellipse in radian
%

h = [];
rho=(0:1:360)*degree;

kilir

function [totfreq, bc, azi]=calcTDF(g,varargin)
% calc circular axis/ trend distribution function of grain long axes
% OR grain boundary segments or from a list of angles for axial data (0:pi)
%
% Syntax:
%  [freq,bc] = calcTDF(smoothgrains.boundary('indexed'))
%  or
%  [freq,bc] = calcTDF(smoothgrains('indexed'))
%

kilir

function [pfTindex, m, pfg_max] = pfIntensity(odf,h)
% calculate pfJ using S2Fun
% input:  
%       odf  -  odf
%       h    -  Miller
% output:
%       pfTindex  - pole figure J index
%       m         - multiplicity (needs to be considered when comparing pfJ of different h)
%       pfmax     - max of pf

kilir

% import demo data
mtexdata forsterite
% prepare some data that might look interesting
[grains, ebsd.grainId, ebsd.mis2mean]=calcGrains(ebsd);
ebsd=ebsd(grains(grains.grainSize>100 & grains.phase==1)); %discard all small grains and non-forsterite grains before labeling
[grains, ebsd.grainId, ebsd.mis2mean]=calcGrains(ebsd,'unitcell');

% plot grains and find an interesting one
om=ipfHSVKey(ebsd('f').CS,ebsd('f').CS);
om.maxAngle=10*degree;

kilir

function [ebsd, grains]=loadPhaseMap(varargin)
% Load a phase map and create "ebsd" which can be used with some 
% of the avaiable tools for grain/grainboundary analysis
%
% Three cases are be distinguished.
%
% 1) Single phase,tightly packed no matrix ('single')
%    input:  boundary map - binary image ("white" boundaries, value should be 255)!
%    output: ebsd with grains of distinct, nonsense orientation and notIndexed 
%            at the boundaries

kilir

function SF = BinghamSphericalFunction(r,Z,varargin)
% define a Bingham Distribution on a sphere
%
% Input
%   r  - @ rotation
%   Z  - 3-by-1 smoothing parameter with Z(1)>=Z(2)>=Z(3), Z3<0
%      or diagonal matrix with Z1, Z2 ,Z3
%      Z1=Z2  rotationally symmetric unimodal distribution
%      Z1<<Z2 (partial girdle distribution
%

kilir

% crystal shape demo
% needs @crystalShape avaiable in mtex 4.5.3
% script plots a map and the user can select points where a little crystal shape
% will be dispalyed -crystal will be cc according to the map

mtexdata titanium
[grains,ebsd.grainId]=calcGrains(ebsd,'angle',5*degree); 
% plot something
cs=ebsd('t').CS;
f=newMtexFigure;