I have a series of numbers:
test = [1 1 1 2 2 2 3 3 3 4 4 4 5 5 5]
which I want to randomely fill into a 3x5 matrix without having the same number in the same row.
How can I do this in matlab? Potentially I could randomize the test vector and fill it into the 5x3 matrix but I don't know how to do this without getting the same number in the same row.
If you want to fill a 3-by-5 matrix with all of the values in test, making sure each row has no repeated values, you can do this very succinctly by using toeplitz to first generate an index matrix, then randomly permute the dimensions with randperm:
index = toeplitz(1:3, [3 5:-1:2]);
index = index(randperm(3), randperm(5));
And a sample index:
index =
1 5 4 2 3
4 3 2 5 1
5 4 3 1 2
If your values in test are the numbers 1 through 5, this should be all you need to do. If test could be any vector with with 5 different numbers, three of each, then you can get the unique values of your test vector and index them with index. This solution will generalize to any test vector:
test = [3 3 3 7 7 7 5 5 5 9 9 9 4 4 4]; % Sample data
uniqueValues = unique(test); % Get the unique values [3 4 5 7 9]
M = uniqueValues(index); % Use index as generated above
And the result will be guaranteed to be a reordered version of what's in test:
M =
3 9 7 4 5
7 5 4 9 3
9 7 5 3 4
You can take the unique matrix of test and pick any three elements out of it and fill in the required 5X3 matrix.
test = [1 1 1 2 2 2 3 3 3 4 4 4 5 5 5] ;
test_unique = unique(test) ;
A = zeros(5,3) ;
for i = 1:size(A,1)
A(i,:) = randsample(test_unique,3) ;
end
randsample needs a statistics toolbox, if you doesn't have it, you may use randperm as shown below.
test = [1 1 1 2 2 2 3 3 3 4 4 4 5 5 5] ;
test_unique = unique(test) ;
A = zeros(5,3) ;
for i = 1:size(A,1)
A(i,:) = test_unique(randperm(length(test_unique),3)) ;
end
If you want 3X5 matrix:
test = [1 1 1 2 2 2 3 3 3 4 4 4 5 5 5] ;
test_unique = unique(test) ;
A = zeros(3,5) ;
for i = 1:size(A,1)
A(i,:) = randsample(test_unique,5) ;
end
Here is a brute-force way of doing it
% data
test = [1 1 1 2 2 2 3 3 3 4 4 4 5 5 5];
% randomly permute the indices
indices = randperm(numel(test));
% create a random matrix
matrix = reshape(test(indices), 5, 3);
% while number of unique elements in any of the rows is other than 3
while any(arrayfun(#(x) numel(unique(matrix(x,:))), (1:size(matrix,1)).')~=3)
% keep generating random matrices
indices = randperm(numel(test));
matrix = reshape(test(indices), 5, 3);
end;
% here is the result
result=matrix;
EDIT : If you want 3x5 like you mentioned in your comment, it is a lot easier. Just one line below.
[~, result] = sort(rand(3,5),2);
Related
I have some data in 10 matrices. Each matrix has a different number of rows, but the same number of columns.
I want to combine all 10 matrices to one matrix row-wise, interleaved, meaning the rows in that matrix will look like:
row 1 from matrix 0
...
row 1 from matrix 9
row 2 from matrix 0
...
row 2 from matrix 9
...
Example (with 3 matrices):
Matrix 1: [1 2 3 ; 4 5 6; 7 8 9]
Matrix 2: [3 2 1 ; 6 5 4]
Matrix 3: [1 1 1 ; 2 2 2 ; 3 3 3]
Combined matrix will be: [1 2 3 ; 3 2 1 ; 1 1 1 ; 4 5 6 ; 6 5 4 ; 2 2 2 ; 7 8 9 ; 3 3 3]
You can download the function interleave2 here https://au.mathworks.com/matlabcentral/fileexchange/45757-interleave-vectors-or-matrices
z = interleave2(a,b,c,'row')
you can see the way the function works in the source code of course
Here's a general solution that allows you to place however many matrices you want (with matching number of columns) into the starting cell array Result:
Result = {Matrix1, Matrix2, Matrix3};
index = cellfun(#(m) {1:size(m, 1)}, Result);
[~, index] = sort([index{:}]);
Result = vertcat(Result{:});
Result = Result(index, :);
This will generate an index vector 1:m for each matrix, where m is its number of rows. By concatenating these indices and sorting them, we can get a new index that can be used to sort the rows of the vertically-concatenated set of matrices so that they are interleaved.
I have the following vector
a = 3 3 5 5 20 20 20 4 4 4 2 2 2 10 10 10 6 6 1 1 1
does anyone know how to shuffle this vector with the same elementsnever be seperate?
something like bellow
a = 10 10 10 5 5 4 4 4 20 20 20 1 1 1 3 3 2 2 2 6 6
thank you, best regard...
You can use unique combined with accumarray to create a cell array where each group of values is placed into a separate cell element. You can then shuffle these elements and recombine them into an array.
% Put each group into a separate cell of a cell array
[~, ~, ind] = unique(a);
C = accumarray(ind(:), a(:), [], #(x){x});
% Shuffle it
shuffled = C(randperm(numel(C)));
% Now make it back into a vector
out = cat(1, shuffled{:}).';
% 20 20 20 1 1 1 3 3 10 10 10 5 5 4 4 4 6 6 2 2 2
Another option is to get the values using unique and then compute the number that each occurs. You can then shuffle the values and use repelem to expand out the result
u = unique(a);
counts = histc(a, u);
% Shuffle the values
inds = randperm(numel(u));
% Now expand out the array
out = repelem(u(inds), counts(inds));
A very similar answer to #Suever, using a loop and logical matrix rather than cells
a = [3 3 5 5 20 20 20 4 4 4 2 2 2 10 10 10 6 6 1 1 1];
vals = unique(a); %find unique values
vals = vals(randperm(length(vals))); %shuffle vals matrix
aout = []; %initialize output matrix
for ii = 1:length(vals)
aout = [aout a(a==(vals(ii)))]; %add correct number of each value
end
Here's another approach:
a = [3 3 5 5 20 20 20 4 4 4 2 2 2 10 10 10 6 6 1 1 1];
[~, ~, lab] = unique(a);
r = randperm(max(lab));
[~, ind] = sort(r(lab));
result = a(ind);
Example result:
result =
2 2 2 3 3 5 5 20 20 20 4 4 4 10 10 10 1 1 1 6 6
It works as follows:
Assign unique labels to each element of a depending on their values (this is vector lab);
Apply a random bijection from the values of lab to themselves (the random bijection is represented by r; the result of applying it is r(lab));
Sort r(lab) and get the indices of the sorting (this is ind);
Apply those indices to a.
As the title says, I want to find all rows in a Matlab matrix that in certain columns the values in the row are equal with the values in the previous row, or in general, equal in some row in the matrix. For example I have a matrix
1 2 3 4
1 2 8 10
4 5 7 9
2 3 6 4
1 2 4 7
and I want to find the following rows:
1 2 3 4
1 2 3 10
1 2 4 7
How do I do something like that and how do I do it generally for all the possible pairs in columns 1 and 2, and have equal values in previous rows, that exist in the matrix?
Here's a start to see if we're headed in the right direction:
>> M = [1 2 3 4;
1 2 8 10;
4 5 7 9;
2 3 6 4;
1 2 4 7];
>> N = M; %// copy M into a new matrix so we can modify it
>> idx = ismember(N(:,1:2), N(1,1:2), 'rows')
idx =
1
1
0
0
1
>> N(idx, :)
ans =
1 2 3 4
1 2 8 10
1 2 4 7
Then you can remove those rows from the original matrix and repeat.
>> N = N(~idx,:)
N =
4 5 7 9
2 3 6 4
this will give you the results
data1 =[1 2 3 4
1 2 8 10
4 5 7 9
2 3 6 4
1 2 4 7];
data2 = [1 2 3 4
1 2 3 10
1 2 4 7];
[exists,position] = ismember(data1,data2, 'rows')
where the exists vector tells you wheter the row is on the other matrix and position gives you the position...
a less elegant and simpler version would be
array_data1 = reshape (data1',[],1);
array_data2 = reshape (data2',[],1);
matchmatrix = zeros(size(data2,1),size(data1,1));
for irow1 = 1: size(data2,1)
for irow2 = 1: size(data1,1)
matchmatrix(irow1,irow2) = min(data2(irow1,:) == data1(irow2,:))~= 0;
end
end
the matchmatrix is to read as a connectivity matrix where value of 1 indicates which row of data1 matches with which row of data2
I have a matrix, L, with two columns. I want to find its sub-matrices have equal values on their 2nd column. I want to do that using MATLAB without any for loop.
example:
L=[1 2;3 2;4 6;5 3;7 3;1 3;2 7;9 7]
then the sub-matrices are:
[1 2;3 2] , [4 6] , [5 3;7 3;1 3] and [2 7;9 7]
You can use a combination of arrayfun + unique to get that -
[~,~,labels] = unique(L(:,2),'stable')
idx = arrayfun(#(x) L(labels==x,:),1:max(labels),'Uniform',0)
Display output -
>> celldisp(idx)
idx{1} =
1 2
3 2
idx{2} =
4 6
idx{3} =
5 3
7 3
1 3
idx{4} =
2 7
9 7
You can use accumarray directly or with a sorted array, depending on you want the order of the rows to be stable, or the order of the submatricxes to be stable.
Say you want the rows to be stable:
>> [L2s,inds] = sort(L(:,2));
>> M = accumarray(L2s,inds,[],#(v){L(v,:)});
>> M(cellfun(#isempty,M)) = []; % remove empty cells
>> celldisp(M)
M{1} =
1 2
3 2
M{2} =
5 3
7 3
1 3
M{3} =
4 6
M{4} =
2 7
9 7
This question already has answers here:
Got confused with a vector indexed by a matrix, in Matlab
(2 answers)
Closed 8 years ago.
Suppose:
a =
1 2 3
4 5 6
2 3 4
and
b =
1 3 2
6 4 8
In MATLABa(b) gives:
>> a(b)
ans =
1 2 4
3 2 6
What is the reason for this output?
when you have a matrix a:
a =
1 2 3
4 5 6
7 8 9
and b:
b =
1 3 4
3 2 6
then a(b) is a way of adressing items in a and gives you:
>> a(b)
ans =
1 7 2
7 4 8
to understand this you have to think of a als a single column vector
>> a(:)
ans =
1
4
7
2
5
8
3
6
9
now the first row of b (1 3 4) addresses elements in this vector so the first, the 3rd and the forth element of that single column vector which are 1 7 and 2 are adressed. Next the secound row of b is used as adresses for a secound line in the output so the 3rd, the 2nd and the 6th elements are taken from a, those are 7 4 and 8.
It's just a kind of matrix indexing.
Matrix indexes numeration in 'a' matrix is:
1 4 7
2 5 8
3 6 9
This is a possible duplicate to this post where I gave an answer: Got confused with a vector indexed by a matrix, in Matlab
However, I would like to duplicate my answer here as I think it is informative.
That's a very standard MATLAB operation that you're doing. When you have a vector or a matrix, you can provide another vector or matrix in order to access specific values. Accessing values in MATLAB is not just limited to single indices (i.e. A(1), A(2) and so on).
For example, let's say we had a vector a = [1 2 3 4]. Let's also say we had b as a matrix such that it was b = [1 2 3; 1 2 3; 1 2 3]. By doing a(b) to access the vector, what you are essentially doing is a lookup. The output is basically the same size as b, and you are creating a matrix where there are 3 rows, and each element accesses the first, second and third element. Not only can you do this for a vector, but you can do this for a matrix as well.
Bear in mind that when you're doing this for a matrix, you access the elements in column major format. For example, supposing we had this matrix:
A = [1 2
3 4
5 6
7 8]
A(1) would be 1, A(2) would be 3, A(3) would be 5 and so on. You would start with the first column, and increasing indices will traverse down the first column. Once you hit the 5th index, it skips over to the next column. So A(5) would be 2, A(6) would be 4 and so on.
Here are some examples to further your understanding. Let's define a matrix A such that:
A = [5 1 3
7 8 0
4 6 2]
Here is some MATLAB code to strengthen your understanding for this kind of indexing:
A = [5 1 3; 7 8 0; 4 6 2]; % 3 x 3 matrix
B = [1 2 3 4];
C = A(B); % C should give [5 7 4 1]
D = [5 6 7; 1 2 3; 4 5 6];
E = A(D); % E should give [8 6 3; 5 7 4; 1 8 6]
F = [9 8; 7 6; 1 2];
G = A(F); % G should give [2 0; 3 6; 5 7]
As such, the output when you access elements this way is whatever the size of the vector or matrix that you specify as the argument.
In order to be complete, let's do this for a vector:
V = [-1 9 7 3 0 5]; % A 6 x 1 vector
B = [1 2 3 4];
C = V(B); % C should give [-1 9 7 3]
D = [1 3 5 2];
E = V(D); % E should give [-1 7 0 9]
F = [1 2; 4 5; 6 3];
G = V(F); % G should give [-1 9; 3 0; 5 7]
NB: You have to make sure that you are not providing indexes that would make the accessing out of bounds. For example if you tried to specify the index of 5 in your example, it would give you an error. Also, if you tried anything bigger than 9 in my example, it would also give you an error. There are 9 elements in that 3 x 3 matrix, so specifying a column major index of anything bigger than 9 will give you an out of bounds error.