Apply logical mask to every matrix in array

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Marcel345614
Marcel345614 el 24 de Feb. de 2022
Respondida: Loïc Reymond el 29 de Mayo de 2023
I have a 3D array of size 640x640x20 i.e. 20 matrices of size 640x640. In addition I have a logical mask of size 640x640. How can I apply this mask to every matrix in the array? Is this only possible with a for loop?
for jj=1:20
mat_temp=B(:,:,jj);
mat_temp(mask==1)=NaN
B(:,:,jj)=mat_temp;
end
%% I tried the following but it didn't worked (mask was only applied to first matrix)
B(mask==1)=NaN;

Respuestas (3)

Jan
Jan el 24 de Feb. de 2022
Editada: Jan el 25 de Feb. de 2022
B = reshape(1:24, 2,3,4);
mask = logical([1,0,1; 0,1,0]);
sB = size(B);
B = reshape(B, [], sB(3)); % Join the first two dimensions
B(mask, :) = NaN;
B = reshape(B, sB)
D =
D(:,:,1) = NaN 3 NaN 2 NaN 6 D(:,:,2) = NaN 9 NaN 8 NaN 12 D(:,:,3) = NaN 15 NaN 14 NaN 18 D(:,:,4) = NaN 21 NaN 20 NaN 24
% Alternatively:
M = ones(size(mask));
M(mask) = NaN;
B = B .* M;
Note: No need to compare mask with 1: mask==1. Use mask directly, if it is a logical array.
  2 comentarios
Jan
Jan el 25 de Feb. de 2022
A speed coparison with R2018b:
X = rand(640, 640, 20);
mask = rand(640, 640) > 0.6;
rep = 1e2;
B = X;
tic;
for k = 1:rep
for jj=1:20
mat_temp = B(:,:,jj);
mat_temp(mask==1) = NaN;
B(:,:,jj) = mat_temp;
end
end
toc % Elapsed time is 8.416893 seconds.
B = X;
tic;
for k = 1:rep
sB = size(B);
B = reshape(B, [], sB(3));
B(mask, :) = NaN;
B = reshape(B, sB);
end
toc % Elapsed time is 0.966218 seconds.
B = X;
tic;
for k = 1:rep
M = ones(size(mask));
M(mask) = NaN;
B = B .* M;
end
toc % Elapsed time is 1.173872 seconds.
B = X;
tic;
for k = 1:rep
s = size(B);
f = find(mask==1) + (0:s(3)-1) .* (s(1)*s(2));
B(f) = nan;
end
toc % Elapsed time is 2.992846 seconds.
Marcel345614
Marcel345614 el 25 de Feb. de 2022
Thank you! This was helpful!

Iniciar sesión para comentar.


David Hill
David Hill el 24 de Feb. de 2022
s=size(B);
f=find(mask==1)+(0:s(3)-1).*(s(1)*s(2));
B(f)=nan;

Loïc Reymond
Loïc Reymond el 29 de Mayo de 2023
The most compact way would probably be:
bsxfun(@(x,y) x.*y,mat,mask)
Or alternatively (probably slower):
mat.*repmat(mask,1,1,size(mat,3))
Where mat is your 640x640x20 matrix and mask your masking array.

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