sort orientations into clusters
Syntax
[c,center] = calcCluster(ori,'halfwidth',2.5*degree)
[c,center] = calcCluster(ori,'numCluster',n,'method','hierarchical')
[c,center] = calcCluster(ori,'maxAngle',omega,'method','hierarchical')Input
| ori | orientation |
| n | number of clusters |
| omega | maximum angle |
Output
| c | list of clusters |
| center | center of the clusters |
Example
% generate orientation clustered around 5 centers
cs = crystalSymmetry('432');
center = orientation.rand(5,cs);
odf = unimodalODF(center,'halfwidth',5*degree)
ori = odf.discreteSample(1500);odf = SO3FunRBF (432 → xyz)
<strong>multimodal components</strong>
kernel: de la Vallee Poussin, halfwidth 5°
center: 5 orientations
Bunge Euler angles in degree
phi1 Phi phi2 weight
103.4 169.894 63.4096 0.2
90.4449 133.852 179.823 0.2
101.873 124.175 125.358 0.2
271.64 62.1178 172.783 0.2
3.75952 131.241 144.325 0.2% find the clusters and its centers
[cId,centerRec] = calcCluster(ori);..................% visualize result
for i = 1:length(centerRec)
plot(ori(cId==i),'axisAngle')
hold on
plot(centerRec(i),'MarkerFaceColor','k','MarkerSize',15)
end
hold off