Surf plot line by line

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TheStranger on 22 Aug 2017
Commented: KSSV on 23 Aug 2017
Hello there!
I want to make a 3D surface plot with, but I have the following problem.
Imagine that I have X and Y vectors and plot some function of them as Z using the colormap. The trick is that my Y-values might depend upon values of the X-vector, meaning that for a fixed xj = X(1, j) I might have different Yj vectors. So, the obvious solution is to plot it line-by-line fixing a particular X-value and plotting the Y dependency of the function. The problem is that surf does not support Z as vectors.
I kind of found the way to do that, but its not exactly what I wanted.
Here comes some code: Conventional 3D SurfPlot of some function:
yvec = linspace(0.0, 2*pi, 100);
xvec = linspace(0.0, 2*pi, 200);
[xm, ym] = meshgrid(xvec, yvec);
zmat = cos(xm).*sin(ym);
surf(xvec, yvec, zmat, 'edgealpha', 0.0); hold on;
xlim([min(xvec), max(xvec)]);
and then I just make slices of the X vector, but not containing the last possible slice, which would be a single point, making Z not a matrix, but a vector and, therefore, throwing an error.
for ind = length(xvec)-1:-1:1
yvec = linspace(0.0, 2*pi, 100);
yvec = yvec + 0.1*rand(1, 100);
[xm, ym] = meshgrid(xvec(ind:end), yvec);
zmat = cos(xm).*sin(ym);
surf(xvec(1, ind:end), yvec, zmat, 'edgealpha', 0.0); hold on;
xlim([min(xvec), max(xvec)]);
As an example I just added some random noise to the y-values, so that it varies for each xvec(1, ind) value.
Is there any other way to do it efficiently? Actually, this looping takes more time to plot and this method also obviously loses one line of data related to xvec(1, end).

Answers (1)

KSSV on 22 Aug 2017
Doc waterfall
TheStranger on 23 Aug 2017
Edited: TheStranger on 23 Aug 2017
Yeah, it does not have such a restriction that z mast be a matrix, but it looks a bit awful, if you want to see some colormap, since it does not connect the X/Y lines, so ~half is just an empty space. Compare
I don't see anything about the linewidth for 'waterfall' func.
Anyway, thx
KSSV on 23 Aug 2017
What you expect?

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