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Daily 10*10 grid precipitation data of 6 days (10*10*6) includes NaN, zeros and negative values. We are trying to replace the NaN values with surrounding cell values.The below script is giving two errors and could not fix it, ("Subscript indices must either be real positive integers or logical") ("Index exceeds matrix dimensions") And the script is as

for i = 2:10;

for j = 2:10;

for k = 2:6;

if isnan(tstsample(i,j,k))

tmp = tstsample(i-1:i+1,j-1:j+1,k);

tstsample(i,j,k) = nanmean(tmp);

end

end

end

end

Need help to solve these issues. I found few materials but not exact one https://ch.mathworks.com/matlabcentral/answers/120517-index-exceeds-matrix-dimensions-error

Thank you in advance

Walter Roberson
on 1 May 2018

Suppose it finds a nan when i=10. Then you would try to access from i-1:i+1 = 9:11. But the maximum for your first dimension is 10.

You could run the code for i=2:9 but you have the general problem that you cannot fix nan that are on the boundary.

Walter Roberson
on 3 May 2018

Walter Roberson
on 3 May 2018

You are mistaken.

In the below, I used Jan's conv2 version, but put on some data creation and some display code to emphasize nans. If you run this code you will see nans on the left highlighted in red. You will not see any nans on the right, but if you look at the code you can see that the display logic is the same so there would be red if the nans existed.

If you examine the values such as comparing x(end-1:end,end-1:end) to X(end-1:end,end-1:end) then you will see that X (the version without nans) has properly calculated X(end,end) based upon the average of the surrounding areas.

if ~exist('x', 'var')

x = randi([0 255], [64 40]);

x(randperm(numel(x),15)) = nan;

x(1,5) = nan; x(end,end) = nan;

end

subplot(1,2,1);

image(uint8(x), 'AlphaData', 0+~isnan(x));

colormap(gray(256));

set(gca,'color', 'r');

[ny, nx] = find(isnan(x));

hold on

%scatter(nx, ny, 'go')

hold off

X = x;

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);

subplot(1,2,2);

image(uint8(X), 'AlphaData', 0+~isnan(X));

colormap(gray(256));

set(gca,'color', 'r');

[nY, nX] = find(isnan(X));

hold on

%scatter(nX, nY, 'go')

hold off

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