2d interpolation of n-dimensional data
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I have this set of data (simplified)
x = [1 2 3]
y = [3 7 2]
temp = [22 25 23; 33 25 17; 19 25 26];
each X Y coordinate pair corresponds to a column in temp. So (X,Y) = (1,3) -> [22; 33; 19]. I'm trying to setup a 2D interpolation which gives me interpolated values of temp from input XY. My solution which works, but is slow, is to create a scatteredinterpolant for every row of temp ie
int1 = scatteredinterpolant([1 2 3]', [3 7 2]', [22 25 23]')
int2 = scatteredinterpolant([1 2 3]', [3 7 2]', [33 25 17]')
int3 = scatteredinterpolant([1 2 3]', [3 7 2]', [19 25 26]')
and then using the scatteredinterpolants 3 times. My actual dataset of temp has 30000 elements per coordinate pair, so this goes pretty slow. Any suggestions?
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Sean de Wolski
2021-8-24
You can just change the Values of one scatteredInterpolant object. It won't have to redo the expensive underlying triangulation of x/y then. Example using zeros and ones for your temp.
s = scatteredInterpolant(rand(3,1),rand(3,1),zeros(3,1))
s(0.3,0.2)
s.Values = ones(3,1) % swap for your second set of values
s(0.3,0.2)
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