3D Histogram from raw data
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I am trying to create the a rainflow matrix out of time history of a load data. I can do it easily with the rainflow command but I am trying to learn how I can produce it myself. It is basically a 3D Histogram of three variables ( Mean, Range and Cycle count , random X,Y and Z let's say )
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/1386564/image.png)
This is what a rainflow matrix looks like for reference.
For any dataset with X,Y and Z data, I undertand that the first step is to discretize X and Y . What I do not understand is how I can allot the Z value to each bins and ultimately plot something like this.
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Mathieu NOE
2023-5-17
hello
see example below - this is equivalent to hist3
% dummy data (col vectors)
x = rand(100,1);
y = rand(100,1);
z = rand(100,1);
%% bin the data (Hist3 clone)
nBins = 10; %number of bins (there will be nBins + 1 edges)
XEdge = linspace(min(x),max(x),nBins+1);
YEdge = linspace(min(y),max(y),nBins+1);
[~, xBin] = histc(x, XEdge);
[~, yBin] = histc(y, YEdge);
% count number of elements per (x,y) pair
[xIdx, yIdx] = meshgrid(1:nBins, 1:nBins);
xyPairs = [xIdx(:), yIdx(:)];
Z = zeros(size(xyPairs,1),1);
for i = 1:size(xyPairs,1)
Z(i) = sum(ismember([xBin, yBin], xyPairs(i,:), 'rows'));
end
% Reshape nPerBin to grid size
Z = reshape(Z, [nBins, nBins]);
% plot data
figure(1)
b = bar3(Z);
% change bar color to match Z value
for k = 1:length(b)
zdata = b(k).ZData;
b(k).CData = zdata;
b(k).FaceColor = 'interp';
end
colorbar('vert');
% Change colormap
colormap jet
% Label the axes
xlabel('x')
ylabel('y')
title('hist3 simulation');
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