Plotting a surface from a two-dimensional matrix
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Answered: Deepak Meena on 21 Jan 2021
Good day, I have the following problem:
I've run a simulation that produces some signals depending on two variables. As my advisor told me, I made a python pipeline that saves the simulated signals on a file in a two-dimensional matrix, with the first two columns being the sweeps of the two variables in all the possible permutations. For example. assuming that the two variables have values [1 2 3] and [4 5 6], the first two columns would be:
Now i have to plot these signals on surfaces on a 3d plot. From what I know, to plot a surface one needs the "surf" command, that takes two vectos with dimensions N and M, plus a two-dimensional matrix with dimensions N x M. The only way that i can think of to obtain this in my case would be to build a new data matrix from scratch using a for cycle, to assign the values of the error signals to two-dimensional matrix, but it seems unefficient and lenghty. Am i missing something?
Deepak Meena on 21 Jan 2021
Hi Mattia ,
Since we want to have permutation for the create the Surface plot , mex grid will of great use. It returns 2-D grid coordinates based on the coordinates contained in vectors x and y. X is a matrix where each row is a copy of x, and Y is a matrix where each column is a copy of y. The grid represented by the coordinates X and Y has length(y) rows and length(x) columns.
so for your example x = [1 2 3 ] & y = [4 5 6]
1 2 3
1 2 3
1 2 3
4 4 4
5 5 5
6 6 6
so we run
F = X.*exp(-X.^2-Y.^2);
It plots for all the possible pairs of x and y. Since you have already a Z value associated value with them , you can plot the surface plot
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