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Fill NaN cell with mean of eight surrounding cells in grid data in matlab

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Shakir Hussain
Shakir Hussain on 21 Apr 2018
Edited: Jan on 25 Apr 2018
I am trying to fill the NaN values of grid data with 8 surrounding values but could not understand, what is going wrong here in my matlab code. The data is 752*891*11 %%% (11 years precipitation of 752*891 cells).
for i = 2 : 752
for j = 2 : 891
for k = 1 : 11
if isnan(data(i,j,k)) == 1
data(i,j,k) = nanmean(nanmean(data(i-2:i+2,j-2:j+2,k-2:k+2)));
end
end
end
end
Thanks in advance for help

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Accepted Answer

Jan
Jan on 21 Apr 2018
Edited: Jan on 25 Apr 2018

If you want to replace a scalar based on a 3D array, you either need 3 nanmean calls:

nanmean(nanmean(nanmean(data(i-1:i+1, j-1:j+1, k-1:k+1))))

with i-1:i+1, instead of i-2:i+2. This would be easier:

if isnan(data(i,j,k))   % "== 1" is not needed
  tmp         = data(i-1:i+1, j-1:j+1, k-1:k+1);  % 3D block
  data(i,j,k) = nanmean(tmp(:));                  % Make it a vector
end

But this is a 3x3x3 neighborhood with 27 elements, not 8. I assume you mean:

if isnan(data(i,j,k))   % "== 1" is not needed
  tmp1        = data(i-1:i+1, j, k);
  tmp2        = data(i:i, j-1:j+1, k);
  tmp3        = data(i, j, k-1:k+1);
  tmp         = [tmp1(:); tmp2(:); tmp3(:)];  % Create a vector
  data(i,j,k) = nanmean(tmp);
end

Because the center point data(i,j,k) is included 3 times, but ignored by nanmean, you have 6 neighbors now, not 8.

So please explain again, what you exactly want.

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Shakir Hussain
Shakir Hussain on 24 Apr 2018
The above four preference is for single year and wants to repeat the same way for 11 years. We have both positive and negative values of temperature and your above given code is pop up with (Subscript indices must either be real positive integers or logicals.) error.
Jan
Jan on 24 Apr 2018

When you access the index i-2:i+2, the loop for i must start at 3, not at 2, because 0 is not a valid index. And the loop must stop at size(data, 1) - 2. Equivalently for j.

Please post a copy of the complete message, if you mention an error in the forum.

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More Answers (1)

Walter Roberson
Walter Roberson on 22 Apr 2018
means = conv2(YourMatrix, [1 1 1;1 0 1;1 1 1]/8,'same') ;
mask = isnan(YourMatrix);
YourMatrix(mask) = means(mask);

No loops needed.

Note: you would need a little adjustment to handle a nan on the edge of the matrix, to calculate the means properly.

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Walter Roberson
Walter Roberson on 22 Apr 2018
Ah, good point, the 0 * nan at the point itself makes the conv2() result into nan.
Jan
Jan on 22 Apr 2018

A solution to use conv2 with NaNs:

nanX    = isnan(X);
X(nanX) = 0;
mask    = [1 1 1; 1 0 1; 1 1 1];
means   = conv2(X,     mask, 'same') ./ ...
          conv2(~nanX, mask, 'same');
X(nanX) = means(nanX);

But I'm not sure, how this can be applied to the OP's problem. A neighborhood of 6 or 10(?) elements is wanted.

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