Interpolation of 3D arrays against a 1D vector

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

Answer 1

[Matt J]

[Nx,Ny,~]=size(Data);

F=griddedInterpolant({1:Nx,1:Ny,t},Data);

Data_new=F({1:Nx,1:Ny,t_new});

[Ahmad Gad]

Thank you very much for the prompt response. That is very helpful.

[Ahmad Gad]

Can you tell me why griddedInterpolant is nearly 5-6 times faster than interpn? Thanks!