how to find common values in two matrix for particular column?

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if true
% code
A=[0 1 1 0; 1 0 0 1; 1 1 0 0; 0 0 1 1]
B=[0 1 0 1; 1 0 1 0; 0 0 1 1; 1 1 0 0]
end
for 1st column of A and ALL columns of b
if we check
the expected answer is
1 0 2 1
these are the total number of instances they are matching
  3 Comments
Bruno Luong
Bruno Luong on 24 Oct 2018
Please put care on
  • code formatting
  • explanation
  • formulation of synthetic question (Why give the whole A and ask just result that depends only on first column)
Shubham Mohan Tatpalliwar
Shubham Mohan Tatpalliwar on 24 Oct 2018
in the first column of A, there are two ones at 2nd row and 3 rd row
so considering this it will check all columns of B
in the first column of B, there is 1 in 2nd row that match and it did not match with the 3rd row
so for 1st column of B answer is 1
for 2nd column of B and 1st column of A nothing match so the answer is zero
Further for the 3rd column of B and 1st column A the second and 3rd row of both are 1 so the answer is 2
and so on...

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Accepted Answer

Bruno Luong
Bruno Luong on 24 Oct 2018
>> sum(A(:,1)+B==2)
ans =
1 0 2 1
>>
  9 Comments
Bruno Luong
Bruno Luong on 25 Oct 2018
Edited: Bruno Luong on 25 Oct 2018
The reshape() just moves the 2nd dimension (column) of A to the 3rd dimension
So each origin column A(:,j) now can be addressed as A(:,:j).
The explanation for SUM(... & B) you already know, but now use in the context of auto-expansion. Excepted that the result now is of the size (1 x size(B,2) x size(A,2)): each number of common 1-values of B and A(:,j) is in a slide XX(1,:,j) before SQUEEZE is invoked.
The squeeze command removes the 1st singleton dimension, so XX(:,j) is common 1-values of B and A(:,j).
NOTE: You might transpose the result so each row corresponds to result of a column of A with you prefer.

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More Answers (1)

Stephen23
Stephen23 on 24 Oct 2018
You don't need to use a loop:
>> sum(permute(A,[3,2,1])&permute(B,[2,3,1]),3)
ans =
1 0 1 2
0 1 2 1
2 1 0 1
1 2 1 0

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