Fancy Correlation Plots in MATLAB

조회 수: 33 (최근 30일)
emami.m
emami.m 2020년 12월 21일
댓글: Mathieu NOE 2025년 9월 19일
I'm trying to find a way to generate these pretty correlation plots in MATLAB. These are generated in R using 'corrplot' function, but couldn't find any similar code in MATLAB. Any help would be appreciated.
As a quick description, this function will create a color scale of the correlation values, and create circles in each cell of the correlation matrix/plot with the associated color. The size of the circles is also an indicator of the magnitude of the correlation, with larger circles representing a stronger relationship (positive or negative). More details could be found here.

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Ive J
Ive J 2020년 12월 22일
Maybe something like this can work for you (after more polishing)
% sample correlation matrix
r = normalize(randn(10, 10), 'range', [-1, 1]);
for i = 1:size(r, 1)
r(i, i) = 1;
end
% labels
labels = "variable" + (1:size(r, 1));
% scatter plot
n = size(r, 1);
y = triu(repmat(n+1, n, n) - (1:n)') + 0.5;
x = triu(repmat(1:n, n, 1)) + 0.5;
x(x == 0.5) = NaN;
scatter(x(:), y(:), 400.*abs(r(:)), r(:), 'filled', 'MarkerFaceAlpha', 0.6)
% enclose markers in a grid
xl = [1:n+1;repmat(n+1, 1, n+1)];
xl = [xl(:, 1), xl(:, 1:end-1)];
yl = repmat(n+1:-1:1, 2, 1);
line(xl, yl, 'color', 'k') % horizontal lines
line(yl, xl, 'color', 'k') % vertical lines
% show labels
text(1:n, (n:-1:1) + 0.5, labels, 'HorizontalAlignment', 'right')
text((1:n) + 0.5, repmat(n + 1, n, 1), labels, ...
'HorizontalAlignment', 'right', 'Rotation', 270)
h = gca;
colorbar(h);
h.Visible = 'off';
h.Position(4) = h.Position(4)*0.9;
axis(h, 'equal')
colormap('jet')
  댓글 수: 3
Ive J
Ive J 2020년 12월 23일
편집: Ive J 2020년 12월 23일
That's because of MarkerFaceAlpha. If you remove that argument, everything works fine.
emami.m
emami.m 2020년 12월 23일
Thank you !

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추가 답변 (2개)

emami.m
emami.m 2020년 12월 23일
편집: emami.m 2020년 12월 23일
Thanks to Mathieu NOE I have edited the code provided in this post:
to produce more similar graph to the one I was looking for (The one generated with R).
Also an issue with circle size for correlations in [-1,1] has been solved.
This code can produce triangular display as well.
Custom colormap and a sample graph that I generated is attached.
For using custom colormap, uncomment line 7,21,34.
% Produce the input lower triangular matrix data
C = -1 + 2.*rand(12,12);
C = tril(C,-1);
C(logical(eye(size(C)))) = 1;
% Set [min,max] value of C to scale colors
clrLim = [-1,1];
% load('CorrColormap.mat') % Uncomment for custom CorrColormap
% Set the [min,max] of diameter where 1 consumes entire grid square
diamLim = [0.1, 1];
myLabel = {'ICA','Elev','Pr','Rmax','Rmin','Srad','Wspd','Tmin','Tmax','VPD','ET_o','AW'};
% Compute center of each circle
% This assumes the x and y values were not entered in imagesc()
x = 1 : 1 : size(C,2); % x edges
y = 1 : 1 : size(C,1); % y edges
[xAll, yAll] = meshgrid(x,y);
xAll(C==0)=nan; % eliminate cordinates for zero correlations
% Set color of each rectangle
% Set color scale
cmap = jet(256);
% cmap = CorrColormap; % Uncomment for CorrColormap
Cscaled = (C - clrLim(1))/range(clrLim); % always [0:1]
colIdx = discretize(Cscaled,linspace(0,1,size(cmap,1)));
% Set size of each circle
% Scale the size between [0 1]
Cscaled = (abs(C) - 0)/1;
diamSize = Cscaled * range(diamLim) + diamLim(1);
% Create figure
fh = figure();
ax = axes(fh);
hold(ax,'on')
colormap(ax,'jet');
% colormap(CorrColormap) %Uncomment for CorrColormap
tickvalues = 1:length(C);
x = zeros(size(tickvalues));
text(x, tickvalues, myLabel, 'HorizontalAlignment', 'right');
x(:) = length(C)+1;
text(tickvalues, x, myLabel, 'HorizontalAlignment', 'right','Rotation',90);
% Create circles
theta = linspace(0,2*pi,50); % the smaller, the less memory req'd.
h = arrayfun(@(i)fill(diamSize(i)/2 * cos(theta) + xAll(i), ...
diamSize(i)/2 * sin(theta) + yAll(i), cmap(colIdx(i),:),'LineStyle','none'),1:numel(xAll));
axis(ax,'equal')
axis(ax,'tight')
set(ax,'YDir','Reverse')
colorbar()
caxis(clrLim);
axis off
  댓글 수: 8
Ziwei Liu
Ziwei Liu 2023년 7월 25일
Thanks for sharing this and it helps me a lot. Just one tiny thing I found out during my time playing with this script is that the following lines:
Cscaled = (C - clrLim(1))/range(clrLim); % always [0:1]
colIdx = discretize(Cscaled,linspace(0,1,size(cmap,1)));
may cause a problem if (1) clrlim is switched to [0 1] and (2) the max of C is larger than 1. In this case the current Cscaled line actually does not scaled C at all, resulting in NaN values in colIdx at positions i where C(i) > 1. I modified the Cscaled line to overcome this problem:
Cscaled = (C - min(C(:)))/(max(C(:))-min(C(:)));
Hope this helps!
emami.m
emami.m 2023년 7월 25일
Thank you for sharing it!

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jon erickson
jon erickson 2025년 9월 18일
Thanks for sharing this. For producing a single, standalone figure this works well. However, in the case of wishing to compare two correlation matrices (say a before and after intervention), the color indexing can vary wildly depending on the nature of the data. So the use case is limited in this sense.
  댓글 수: 1
Mathieu NOE
Mathieu NOE 2025년 9월 19일
hello
why woudn't it possible to compare two correlation plots ? I don't see what speaks against that

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