ignore NaN values in loop

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Cristina Elmeua
Cristina Elmeua el 12 de En. de 2021
Comentada: Cristina Elmeua el 16 de En. de 2021
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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Walter Roberson
Walter Roberson el 12 de En. de 2021
Editada: Walter Roberson el 12 de En. de 2021
if isempty(A)
CC(:,i) = nan;
else
A = interpft(A, 100);
CC(:,i) = A;
end
Can interpft operate with only one non-nan value?
  1 comentario
Cristina Elmeua
Cristina Elmeua el 16 de En. de 2021
This has worked great Walter. A very simple and effective approach, thanks.

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Más respuestas (2)

David Hill
David Hill el 12 de En. de 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

Adam Danz
Adam Danz el 12 de En. de 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))

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