Making a contour plot from x and y data
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Markus Similä
el 21 de Jul. de 2020
Comentada: Markus Similä
el 23 de Jul. de 2020
I have a two column vector containing x and y values. The y values have a high accuracy (many decimal points).
x ranges from 0 to 50000 and y from 0 to 14.
I need to use contourf to make a 2d representation of this data.
How can this be done?
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Adam Danz
el 22 de Jul. de 2020
Editada: Adam Danz
el 22 de Jul. de 2020
The bivariate density can be computed using histcounts2. You'll need to specify either the number of bins or the bin edges for the x and y variables using one of the syntaxes below.
Here's what the solution will look like. xy is your nx2 matrix of [x,y] values.
[N,Xedges,Yedges] = histcounts2(xy(:,1), xy(:,2), 5);
% or use [N,Xedges,Yedges] = histcounts2(X,Y,Xedges,Yedges);
% Compute bin centers
Xcnt = Xedges(2:end) - abs(diff(Xedges(1:2))/2);
Ycnt = Yedges(2:end) - abs(diff(Yedges(1:2))/2);
figure()
contour(Xcnt,Ycnt, N)
% show bins
xlim = [min(Xedges),max(Xedges)];
ylim = [min(Yedges),max(Yedges)];
arrayfun(@(x)xline(x,'Color',[.8 .8 .8]),Xedges)
arrayfun(@(y)yline(y,'Color',[.8 .8 .8]),Yedges)
% colorbar
cb = colorbar();
ylabel(cb,'density')
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KSSV
el 22 de Jul. de 2020
I would follow like below:
- You need to generate z values which are density values.
- I would fix a distance r and calculate the number of points within r for each point using rangesearch.
- Now you can use scatter to plot the density values.
- If your data is structured arrange the data and use contourf.
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