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How to "smear" a logical mask without looping

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I would like to "smear" a logical mask - fast. There may be a proper term and even standard operation for this but I haven't been able to find them. The following code and image help describe the requirement:
r=20;
c=25;
a=false(r,c);
a(10,3)=true;
a(4,15)=true;
a(18,18)=true;
a2=a;
n=5; %length to "smear"
for j=1:c
i=1;
while i<=r
if a2(i,j);
a2(i:(i+n),j)=true;
i=i+n;
end
i=i+1;
end
end
a2=a2(1:r,:);
figure(1)
colormap(flipud(gray))
subplot(1,2,1)
imagesc(a)
title('Input')
subplot(1,2,2)
imagesc(a2)
title('Desired Output')
This is easy in a loop but very slow for large arrays. I've managed a few approaches without loops, some are faster but still messy and I'm sure there is a better way! Hence posting it here for the Gurus :)

Risposta accettata

Greg Dionne
Greg Dionne il 22 Mar 2017
Modificato: Greg Dionne il 22 Mar 2017
If you have a recent copy (R2016a) try:
a2 = movmax(a, [n 0]);
  3 Commenti
Sonomatic Australia
Sonomatic Australia il 22 Mar 2017
Wow how good is that!? Time to update my Matlab then!
Greg Dionne
Greg Dionne il 22 Mar 2017
Thanks Guillaume,
I've updated the answer accordingly.
-G

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Più risposte (3)

Stephen23
Stephen23 il 21 Mar 2017
Modificato: Stephen23 il 21 Mar 2017
I have no idea how fast this is, but it is relatively compact:
>> idx = cumsum(cumsum(a,1),1);
>> out = 0<idx & idx<=n
out =
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0
Note that this method will not work if there are more than one non-zero value in a column. It could be adapted for that situation though.
  1 Commento
Sonomatic Australia
Sonomatic Australia il 21 Mar 2017
Thank you Stephen, that's pretty neat! I do need to handle columns with more than one non-zero value. Will keep trying!

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Guillaume
Guillaume il 21 Mar 2017
This would work regardless of the numbers of non-zero values in each column. The loop is only over the length of the smear, so should be fairly fast:
a2 = a;
smearlength = 5;
for s = 1 : smearlength
a2 = a2 | [zeros(s, size(a, 2)); a(1:end-s, :)];
end
  1 Commento
Sonomatic Australia
Sonomatic Australia il 22 Mar 2017
Nice one Guillaume, thank you for that! I'll have to run some comparisons with larger arrays and post results.

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Guillaume
Guillaume il 22 Mar 2017
Modificato: Guillaume il 22 Mar 2017
And here is a one liner that also works regardless of the numbers of ones in each column:
%a: logical matrix
%n: number of 1s to add to each smear
a2 = any(a(permute(toeplitz(1:size(a, 1), ones(1, n+1)), [1 3 2]) + (0:size(a, 1):numel(a)-1)), 3);
Requires R2016b or later (otherwise use bsxfun for the +) and is probably not faster than my loop answer.
edit: actually, it is faster than the loop on my machine. But not as fast as Stephen's answer.
  1 Commento
Sonomatic Australia
Sonomatic Australia il 22 Mar 2017
Thank you Guillaume, I need some time to understand that one! For interest, I setup the following and did a quick test:
r=50000;
c=10000;
a=false(r,c);
ntrue=round(r*c*0.3);
b=round(rand(20,1)*numel(a));
a(b)=true;
n=30; %length to "smear"
Your method which loops for "n" took 183.267894 s. The method in the original question took 6.552720 s which surprised me.

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