# Checking repetition of random data

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Student for ever on 4 Jan 2018
Edited: Student for ever on 9 Jan 2018
I heed your help please. I made a random data for example T1 = randn (1000,1); T2= randn (1000,1); .... T100=randn (1000,1); and I want check whether there is any repetition for T's if so then remove it. How can I do that ?? Thanks in advance :)
Regards, Ahmed
Student for ever on 7 Jan 2018
Edited: Jan on 7 Jan 2018
Dear Jan,
I am new in matlab :), May my question is not clear, but your answer it is so close of what I want to do I think. I have 200 timeseries, which were come from parallel computation and I just want make sure that 200 are not repeated (what I mean, if I make plot for them they should give me different graphs). So, I put all the 200 timeseries as a matrix, it will be 200 column , then I just want check these columns not the same.

Jan on 4 Jan 2018
Edited: Jan on 8 Jan 2018
Do not create a list of variables called T1, T2, ... See https://www.mathworks.com/matlabcentral/answers/57445-faq-how-can-i-create-variables-a1-a2-a10-in-a-loop. Use a cell or multidimensional array instead.
I assume your problem is to have no repeated values inside each vector and between all vectors. Then you need 1000*100 different random numbers at first:
Pool = rand(1, 100000);
end
T = reshape(Pool, 1000, 100);
Maybe this is faster:
[EDITED] If all you want is to create a unique set of vectors, and randn was just an example to create test data for the forum:
[T, Idx] = unique(T, 'rows')
[EDITED] And for unique columns:
T = unique(T.', 'rows').'
Student for ever on 8 Jan 2018
Thank you so much

Birdman on 4 Jan 2018
Firstly, generate random data as follows:
T=randn(1000,100);
Secondly, as Adam said, use unique function to check repetitions.
Tun=unique(T,'stable');
stable command helps to protect the initial order of values.
Birdman on 4 Jan 2018
It is needed for result, exactly.

John BG on 5 Jan 2018
Hi Ahmed
so far, the supplied answers increase the probability to generate all-different, random Ts.
Each of the answers improves generation randomness, yet if you really want to make sure that all T sequences are different, once generated, let's say you don't really have control on the randomness of the data and the the suggested randn(1000,1) is you model, then there's no other way than comparing them by pairs.
1.
Let be N the amount of T sequences
N=5
2.
then all possible pairs of T sequences are
L=combinator(N,2,'c')
=
1 2
1 3
1 4
1 5
2 3
2 4
2 5
3 4
3 5
4 5
3.
As Jan Simon mentions, sometimes it's more practical to put all data in a structure that can be indexed, instead of working with N different sequence names.
Let be T all your input Ti sequences compiled into a single matrix
T=randi([1 10],N)
T =
8 2 3 9 3
3 5 8 10 9
7 10 3 6 3
7 4 6 2 9
2 6 7 2 3
4.
Checking there are no 2 equal sequences
D=[0 0];
for k=1:1:size(L,1)
if isequal(T(L(k,1),:),T(L(k,2),:))
D=[D;L(k,:)];
end
end
5.
Removing repeated sequences
if size(D,1)>1
D(1,:)=[];
T(D(:,1),:)=[]; % removing one of the repeated identical pairs
end
T
.
Ahmed, I have overwritten some sequences on purpose, so the counter D shows spotted repeated sequences and these simple lines remove all repetition without losing data (when more than one repetition of same given sequence) and it works.
thanks in advance for time and attention
John BG
Student for ever on 9 Jan 2018
Edited: Student for ever on 9 Jan 2018

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