Random number with no repeats in set matrix
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Rainaire Hansford
on 14 Apr 2019
Commented: Walter Roberson
on 28 Jun 2019
Hello again.
I want to make a matrix with random numbers that do not repeat in each row in a k X p matrix
and can be modified depending on inputs.
So far i have a code:
clc
k=input('# rows ');
p=input('# columns')
S=randperm(p);
S=S(1:(k*p));
S=reshape(S,k,p)
This works some times but not all the times.
Please help?
4 Comments
Walter Roberson
on 20 Apr 2019
Edited: Walter Roberson
on 20 Apr 2019
hasdup = any( sum(bsxfun(@eq, s, permute(unique(s), [2 3 1])),2) > 1, 3);
Now hasdup is true for the rows of s which contain duplicate values within the row (and so you will need to regenerate the row.)
It is not clear to me why you do not use the sort-based code that I posted: it is guaranteed that the rows of S will contain unique integers in the range 1 to p with no need to regenerate.
Accepted Answer
Walter Roberson
on 14 Apr 2019
Old trick that randperm() used to implement:
[~, S] = sort(rand(k, p), 2);
14 Comments
More Answers (2)
Steven Lord
on 21 Jun 2019
You have a requirement that no row may contain the same number twice. Can different rows in the same matrix contain the same number? So in the example below, A would not be acceptable (the second row has two 3's) but B would be acceptable (the first and second rows each have 2)?
A = [1 2; 3 3];
B = [1 2; 2 3];
If so, call randperm once for each row, telling it to generate size(B, 2) numbers from 1 to your upper limit.
nrows = 10;
ncols = 7;
maxvalue = 100;
A = zeros(nrows, ncols);
for whichrow = 1:nrows
A(whichrow, :) = randperm(maxvalue, ncols);
end
If you call rng default immediately before calling that code the resulting matrix should have three rows that contain the number 4 and three rows that contain 89, but that neither 4 nor 89 repeat in the same row.
0 Comments
Rainaire Hansford
on 21 Jun 2019
7 Comments
Walter Roberson
on 28 Jun 2019
You can use reshape and bsxfun to compare each member of one array to each member of another, resulting in a k by s by w by p array. You then any() along one of the dimensions and sum along a different dimension and squeeze to get a 2d array of results.
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