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# How to take 2D mean ignoring nan values using cellfun?

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Niky Taylor on 1 Mar 2021
Edited: Niky Taylor on 1 Mar 2021
Hi,
I am trying to write a code that takes a large square image, breaks it up into small square segments, and then calculates the mean and standard deviation of each segment ignoring nan values.
Right now I'm trying to use cellfun to do this. I have the following code:
% splitting large matrix into segments
a = mat2cell(A,dimSpec1,dimSpec1);
% calculating standard deviation in segments
sigma = cellfun(@std2,a,'UniformOutput',true);
% calculating standard deviation in segments
xbar = cellfun(@mean2,a,'UniformOutput',true);
The problem is that most of the small segments have nan values, so when I calculate sigma or xbar I end up with a matrix full of nan values. But when I use something like nanmean or mean with ignore nan, I can't do the calculation in 2d. So how can I calculate the 2D mean and std, ignoring nans, in cellfun?
I don't use cellfun before so apologies if this is a overly basic question. It's also very likely that I'm approaching the whole problem badly, so if anyone has any suggestions I'm more than happy to hear them. Thanks!
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### Answers (2)

Allen on 1 Mar 2021
Try the following:
a = mat2cell(A,dimSpec1,dimSpec1);
% calculating standard deviation in segments
sigma = cellfun(@(x) std(x,'all','omitnan'),a,'UniformOutput',true);
% calculating standard deviation in segments
xbar = cellfun(@(x) mean(x,'all','omitnan'),a,'UniformOutput',true);
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Niky Taylor on 1 Mar 2021
Aha, it seems like what you suggested works for mean. For std I changed it to:
sigma = cellfun(@(x) std(x,0,[1 2],'omitnan'),a,'UniformOutput',true);
after taking a look at the documentation. Thanks!

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Allen on 1 Mar 2021
Niky,
My previous suggestion did not fully look at the input requirements for 2D usage of std. The following revision should accomplish what you needing.
a = mat2cell(A,dimSpec1,dimSpec1); % Your inputs
% calculating standard deviation in segments
sigma = cellfun(@(x) std(x,0,'all','omitnan'),a,'UniformOutput',true);
% or
% cellfun defaults to uniform output, so no need to include for these uses
sigma = cellfun(@(x) std(x(:),'omitnan'),a);
% calculating standard deviation in segments
xbar = cellfun(@(x) mean(x,'all','omitnan'),a);
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