Asked by Justin
on 9 Aug 2012

I am currently working with large data cubes in the form of an MxNxP matrix. The P-dimension represents the signal at each (m,n) pixel. I must obtain a Z-order polynomial fit(where Z varies depending on the situation) for each signal in the data cube. Currently, I utilize a "for" loop to obtain the signal at each pixel, obtain the polynomial coefficients, then calculate the fitted curve. The code I use is fundamentally similar to the following:

dataCube = rand(1000,1000,300);

x = rand(300,1);

sizeCube = size(dataCube);

polyCube = zeros(sizeCube);

for ii = 1:sizeCube(1);

for iii = 1:sizeCube(2);

signal = squeeze(dataCube(ii,iii,:));

a = polyfit(x,signal,z)

y = polyval(a,x);

polyCube(ii,iii,:) = y;

end

end

Because of the quantity of iterations in the for loop, this operation takes a considerable amount of time for each data cube. Is there a faster way to obtain the polynomial fitting, without having to resort to the iterative process I use here. Perhaps, something similar to the filter function where you can apply the filter to a specific dimension of a matrix, rather than extracting each signal?

filteredCube = filter(b,a,dataCube,[],3)

Thanks, Justin

Teja Muppirala
님의 답변 10 Aug 2012

채택된 답변

This can be accomplished in a fraction of the time with some matrix operations.

dataCube = rand(100,100,300);

sizeCube = size(dataCube);

x = rand(300,1);

z = 3;

V = bsxfun(@power,x,0:z);

M = V*pinv(V);

polyCube = M*reshape(permute(dataCube,[3 1 2]),sizeCube(3),[]);

polyCube = reshape(polyCube,[sizeCube(3) sizeCube(1) sizeCube(2)]);

polyCube = permute(polyCube,[2 3 1]);

Justin
on 14 Aug 2012

Teja,

Thank you! This is a slick solution that drastically reduces the processing time. It went from ~50 minutes to process a 1920x1040x301 image_cube (@ 0.0015 seconds per loop), to about 15 seconds!

Thank you for the help! Justin

Jan
on 18 Dec 2017

+1, Teja, what a powerful solution!

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Answer by Martin Offterdinger
on 9 Apr 2019

Dear Teja,

I am having a similar problem- actually a simpler one even. I have the same array, but I always need to fit a first-order polynom (linear, z=1 in your code). Is it possible to get the coefficients of the linear fit (p1,p2) from your solution as well?

Thanks,

Martin

Jan
on 9 Apr 2019

@Martin: Please do not attach a new question in the section for answer. Open a new thread instead and remove this pseudo-answer. Including a link to this thread is a good idea. Thanks.

What's wrong with setting z=1? Which array is "the same" and why do you need to determine the fit multiple times for the same array? (Please explain this in your new question...)

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## 2 Comments

## Walter Roberson (view profile)

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https://www.mathworks.com/matlabcentral/answers/45680-faster-method-for-polyfit-along-3rd-dimension-of-a-large-3d-matrix#comment_93812

## Justin (view profile)

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