kilir

function saveFigure(fname,varargin)
% save figure as graphics file
%
% Description
% This function is supposed to produce cropped, publication ready image
% files from your plots. The format of the file is determined by the
% extension of the filename. 
%
% Syntax
%   saveFigure(fname)

kilir

%% select profile
lineX = ginput(2) % select a line
[ebsd_lineX, dist ]= spatialProfile(ebsd,lineX); %extract orientations

%%  average orientations perpendicular to profile and plot things along line
clear meanO
% average along line (put 0 if you want no averaging)
%//////////////////////////////////////////////////////
av_width = 8 %number of pixels to average perp to line (towards both sides
% use 0 to use only ebsd_lineX

kilir

function [gkam, gid, kam] = gKAM(ebsd,varargin)
% calculate grain average misorientation angle from KAM
% input:
%      ebsd (with grainID)
% 
%   options:
%      threshold:    angles to ignore (upper limit) in radian 
%      lowlim:       angles to ignore: (lower limit) in radian
%      order:        1st,2nd etc. neighbourhood around each point
% 

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;

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

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

% 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 [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

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 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;