Interpolation of 3D arrays against a 1D vector

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Hello all.
I have a video data represented as 3D matrix in the form of Data(x,y,t). Here, x,y represent the pixel number and t is the time. I have the time vector stored in a separate variable. I need to interpolate the variable Data at a new time vector represented by variable t_new to get the new variable Data_new(x,y,t_new). I am using the following code:
n = 20;
m = 60;
t = linspace(0,1,n)';
t_new = linspace(0,1,m)';
Data = rand(50,50,n);
Data_new = permute(interpn(t,permute(Data,[3 2 1]),t_new),[3 2 1]);
% Verification by plotting the time history of selected pixel:
x = 25;
y = 25;
plot(t,reshape(Data(x,y,:),n,1),t_new,reshape(Data_new(x,y,:),m,1))
It looks fine to me. but the main concerns I am asking about:
  1. I had to use permute twice. I am not able to do it without permute. Can I avoid this?
  2. Is there a faster method to perform this interpolation?
Thanks and best,
Ahmad

Accepted Answer

Matt J
Matt J on 25 Aug 2022
Edited: Matt J on 25 Aug 2022
[Nx,Ny,~]=size(Data);
F=griddedInterpolant({1:Nx,1:Ny,t},Data);
Data_new=F({1:Nx,1:Ny,t_new});
  2 Comments
Ahmad Gad
Ahmad Gad on 25 Aug 2022
Thank you very much for the prompt response. That is very helpful.
Ahmad Gad
Ahmad Gad on 25 Aug 2022
Can you tell me why griddedInterpolant is nearly 5-6 times faster than interpn? Thanks!

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