I'll compare two methods here:

interp2 is the one I defaulted to originally. I noticed it was typically the bottleneck though so I looked for alternatives almost immediately. griddedInterpolant was significantly faster and is fast enough that it's no longer a bottleneck, so I stopped looking at that point. To show the performance difference, I put together a really short example that's listed below.

For a quick background, the example generates a 1000x1000 grid and assigns random values to each point. It then tries to find the interpolated values at 200 random x/y locations completely contained in the grid. E.g., it might try to find the value at x = 1.56, y = 98.14 while the values are actually known when x and y are integers.

I do this interpolation four different ways, output the time each method takes, and output a check that they returned the same values.

For a quick background, the example generates a 1000x1000 grid and assigns random values to each point. It then tries to find the interpolated values at 200 random x/y locations completely contained in the grid. E.g., it might try to find the value at x = 1.56, y = 98.14 while the values are actually known when x and y are integers.

I do this interpolation four different ways, output the time each method takes, and output a check that they returned the same values.

clear all close all %Setup 1000 x 1000 grid and create random numbers for the V(x,y) you'll %interpolate x = -1000:1:1000; y = -1000:1:1000; [X, Y] = meshgrid(x, y); [A, B] = ndgrid(x, y); V = rand(length(x)); %setup smaller set of random x/y locations where you want the interpolated %value xi = zeros(200, 1); yi = zeros(200, 1); for i = 1:length(xi); xi(i) = 2000*rand() - 1000; yi(i) = 2000*rand() - 1000; end %avoid unnecessary operations in the interpolations W = V'; Vi = zeros(1, length(xi)); Vj = zeros(length(xi), 1); Vk = zeros(length(xi), 1); Vl = zeros(length(xi), 1); %super-slow interp2 method t = cputime; for i = 1:length(xi) Vi(i) = interp2(X, Y, W, xi(i), yi(i)); end cputime - t %faster interp2 method testTime = zeros(100, 1); for i = 1:length(testTime) t = cputime; Vj = interp2(X, Y, W, xi, yi); testTime(i) = cputime - t; end mean(testTime) %slower griddedInterpolant method for i = 1:length(testTime) t = cputime; F = griddedInterpolant(A, B, V); for j = 1:length(xi) Vk(j) = F([xi(j) yi(j)]); end testTime(i) = cputime - t; end mean(testTime) %faster griddedInterpolant method for i = 1:length(testTime) t = cputime; F = griddedInterpolant(A, B, V); Vl = F(xi, yi); testTime(i) = cputime - t; end mean(testTime) %make sure the results agree sum(Vl - Vk) sum(Vk - Vj) sum(Vj - Vi')

On my laptop, running this yields the following times:

- slow interp2: 17,594 ms
- fast interp2: 114 ms
- slow griddedInterpolant: 17 ms
- fast griddedInterpolant: 11 ms

There are probably even faster ways to do this, but this was more than enough for my use case so I figured I'd share it.

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