ignore NaN values in loop
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Hi everyone,
So I have a numeric matrix "walknov" with several columns of different lengths and I interpolated them all to be 100 points and created a new matrix "CC" with the following loop:
for i = 2:16
A = walknov(:,i);
A(any(isnan(A),2),:) = [];
A = interpft(A, 100);
CC = [CC A];
end
NaNs fill the differences of length between columns, so I have eliminated each row containing NaN everytime I interpolate each column. The problem is that some columns have no values at all (i.e. only NaNs) and this makes the loop stop as the interpolation function won't accept such values.
I do not want to drop the column as I need the matrix to match other matrices, but instead I would like to just leave NaN values in those missing columns. Is there a way to solve this?
Thanks a lot!
PS: I have attached a sample dataset
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Plus de réponses (2)
David Hill
le 12 Jan 2021
CC=[];
for i = 2:16
A = walknov(:,i);
A = interpft(A(~isnan(A)), 100);
if isempty(A)
CC=[CC;nan(1,100)];
else
CC = [CC;A];
end
end
1 commentaire
Cristina Elmeua
le 16 Jan 2021
Adam Danz
le 12 Jan 2021
The image below shows the location of your missing values. The good news is that the missing values either consume entire columns or the end of columns instead of being dispersed.
To work around this,
for i = 2:16
A = walknov(:,i);
A(any(isnan(A),2),:) = [];
if isempty(A)
A = NaN(size(CC,1)); % 1 column?
else
A = interpft(A, 100);
end
CC = [CC A];
end
This assumes CC is defined before the loop. Otherwise if the empty 'A' appears on the first loop, there will be an error indicating that CC is not defined.
Show NaN pattern.
imagesc(isnan(w2_2)) % or heatmap(double(isnan(w2_2))

1 commentaire
Cristina Elmeua
le 16 Jan 2021
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