Coloring The Dots in biPlot Chart
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I have created biplot as below and I'm looking for a way to distinguish the dots by different colors according to their group name. There are 12 groups and here are mydata and codes.
categories = ['F1';'F2';'F3';'F4';'F5';'F6';'F7';'F8'];
load('MAT_ALL.mat')
figure(1)
[coefforth,score,~,~,explainedVar] = pca(MaT_All(:,9:16));
load('DataGroup.mat')
clusters = DataGroup(:,20);
[coefforth,score,~,~,explainedVar] = pca(MaT_All(:,9:16));
figure(3)
biplot([coefforth(:,1) coefforth(:,2)],'Scores',[score(:,1) score(:,2)],'Varlabels',categories);
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Adam Danz
2019년 4월 25일
편집: Adam Danz
2019년 4월 25일
The biplot() function has an output that lists handles to all objects in the plot. All you need to do is isolate the handles to the scatter points by referencing the handle tags and then assign color based on the category.
If you have any questions, feel free to leave a comment.
% Your code
categories = ['F1';'F2';'F3';'F4';'F5';'F6';'F7';'F8'];
load('MAT_ALL.mat')
% figure(1) (No need for this)
[coefforth,score,~,~,explainedVar] = pca(MaT_All(:,9:16));
load('DataGroup.mat')
clusters = DataGroup(:,20);
[coefforth,score,~,~,explainedVar] = pca(MaT_All(:,9:16));
figure()
% Store handle to biplot
h = biplot([coefforth(:,1) coefforth(:,2)],'Scores',[score(:,1) score(:,2)],'Varlabels',categories);
% Identify each handle
hID = get(h, 'tag');
% Isolate handles to scatter points
hPt = h(strcmp(hID,'obsmarker'));
% Identify cluster groups
grp = findgroups(clusters); %r2015b or later - leave comment if you need an alternative
grp(isnan(grp)) = max(grp(~isnan(grp)))+1;
grpID = 1:max(grp);
% assign colors and legend display name
clrMap = lines(length(unique(grp))); % using 'lines' colormap
for i = 1:max(grp)
set(hPt(grp==i), 'Color', clrMap(i,:), 'DisplayName', sprintf('Cluster %d', grpID(i)))
end
% add legend to identify cluster
[~, unqIdx] = unique(grp);
legend(hPt(unqIdx))
You can select a different color map (I'm using 'lines'). : https://www.mathworks.com/help/matlab/ref/colormap.html#buc3wsn-1-map
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Adam Danz
2020년 11월 29일
You need to keep track of your random permutation indices and apply the same permutation to the species vector.
randIdx = randperm(size(iris, 1));
irisRandom = iris(randIdx, :);
species = species(randIdx);
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