mask a matrix based on values in two arrays
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I am looking for a more effective means of masking a matrix based on values held in two arrays. Ultimately I'm looking to mask off chunks of a surface to alter their values. I have been able to achieve this based on the logic in the following loop, but for my actual model runs, which typically have meshgrid sizes in the millions of elements, and array lengths in the 1000's I feel like there could be a less memory intensive (and read/write intensive) solution.
[x y]=meshgrid(0:1:100,0:1:100);
u=floor(rand(10,1)*100);
v=floor(rand(10,1)*100);
padu=5; padv=5;
for i=1:size(u,1)
if i==1
mask=1*(x>u(i)-padu & x<u(i)+padu & y>v(i)-padv & y<v(i)+padv);
else
maskh=(x>u(i)-padu & x<u(i)+padu & y>v(i)-padv & y<v(i)+padv);
mask(maskh==1)=1;
end
end
surf(x,y,mask)
is there a more effective solution? I've searched but perhaps using the wrong terms, as I don't have an answer.
Thank you.
2 个评论
Jan
2022-11-19
It would be useful if you write down in words, how the mask should be created. Of course Matlab can parse this easily from the code, but even experiences programmers can use some help by reading the idea of the author.
采纳的回答
Jan
2022-11-19
编辑:Jan
2022-11-19
n = 1e4;
u = floor(rand(10,1)*100);
v = floor(rand(10,1)*100);
tic % Original version:
[x y] = meshgrid(linspace(0, 100, n), linspace(0, 100, n));
padu = 5;
padv = 5;
for i=1:size(u,1)
if i==1
mask=1*(x>u(i)-padu & x<u(i)+padu & y>v(i)-padv & y<v(i)+padv);
else
maskh=(x>u(i)-padu & x<u(i)+padu & y>v(i)-padv & y<v(i)+padv);
mask(maskh==1)=1;
end
end
toc
tic; % Version 1:
x = linspace(0, 100, n); % Avoid MESHGRID, because if creates huge
y = linspace(0, 100, n).'; % redundant matrices
padu = 5;
padv = 5;
% Use a logical array as mask instead of a double array:
mask2 = (x>u(1)-padu & x<u(1)+padu) & (y>v(1)-padv & y<v(1)+padv);
on = true; % Slightly faster to use a constant instead of a function
for i = 2:size(u,1)
% Avoid check of i==1 in each iteration my moving this exception
% out of the loop.
maskh = (x>u(i)-padu & x<u(i)+padu) & (y>v(i)-padv & y<v(i)+padv);
mask2(maskh) = on;
end
toc
assert(isequal(mask, mask2), 'Different results!')
It is faster to call
mask = or(mask, newmask)
then
newmask = xy;
mask(newmask) = true;
See:
tic; % Version 2
x = linspace(0, 100, n).';
y = linspace(0, 100, n).';
padu = 5;
padv = 5;
xm = (x > u.'-padu & x < u.' + padu); % Or: abs(x - u.') < padu;
ym = (y > v.'-padv & y < v.' + padv); % Or: abs(y - v.') < padv;
on = true;
mask3 = false(n, n);
for i = 1:size(u, 1)
mask3 = mask3 | (xm(:, i).' & ym(:, i));
end
toc
assert(isequal(mask, mask3), 'Different results!')
In my measurements this has almost the same speed:
tic; % Version 3
x = linspace(0, 100, n); % Avoid MESHGRID, because if creates huge
y = linspace(0, 100, n).'; % redundant matrices
padu = 5;
padv = 5;
mask4 = false;
for i = 1:size(u,1)
mask4 = mask4 | (abs(x-u(i)) < padu) & (abs(y-v(i)) < padv);
% Or:
% mask4 = mask4 | (x>u(i)-padu & x<u(i)+padu) & (y>v(i)-padv & y<v(i)+padv);
end
toc
assert(isequal(mask, mask4), 'Different results!')
Check the speed with the original data on your local machine. The timings from the forum seem to be strange sometimes.
更多回答(1 个)
Catalytic
2022-11-20
A=accumarray([u,v],1,[100,100]);
k=ones(2*padu,2*padv);
mask=conv2(A,k,'same');
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