Suppose
A = [1 2 3 5 7 9
6 5 0 3 2 3]
I want to randomize the position of the matrix column position; to give B like so:
B = [3 9 1 7 2 5
0 3 6 2 5 3]
How can I do this Matlab?
Try
B = A(randperm(length(A)))
Consult the documentation for explanations.
Now that code is formatted properly, it's clear the OP wants column preservation, although randperm is still the easiest option as given by HPM's answer.
idx = randperm(size(A,2)); % Create list of integers 1:n, in random order,
% where n = num of columns
B = A(:, idx); % Shuffles columns about, on all rows, to indixes in idx
You'll want to use the randperm function to generate a random permutation of column indices (from 1 to the number of columns in A), which you can then index A with:
B = A(:, randperm(size(A, 2)));
Related
I want to find all possible variations (combinations) of a vector, choosing various numbers of elements from that vector.
For example, suppose I have the vector:
x = [1 2 3 4 5];
I can determine the number of combinations for each number of chosen elements:
x = [1 2 3 4 5]';
n = numel(x);
for k = 1:n
combs(k) = nchoosek(n,k);
end
sum(combs)
This results in:
combs = 5 10 10 5 1
sum(combs) = 31
I want a way to store all 31 of these combinations in an array, for example a cell array, with n cells, within each is an array in which each row is a vector combination of the elements.
e.g. at k = 4:
combs{4} =
1 2 3 4
1 2 3 5
1 2 4 5
1 3 4 5
2 3 4 5
Is there an existing function that does this, or what would be the most simple approach to this?
Call nchoosek with a vector as first input, using arrayfun (or equivalently for) to loop over the number of picked elements:
n = 5;
combs = arrayfun(#(k) nchoosek(1:n,k), 1:n, 'UniformOutput', false);
Here is an approach using dec2bin , find and accumarray:
x = [1 2 3 4 5];
[a b] = find(dec2bin(1:2^numel(x)-1)=='1');
combs = accumarray(a,x(b),[],#(c){c});
I have an array [2; 3] and a matrix [ 1 3 4 5; 2 4 9 2].
Now I would like to extract the second element from the first row and the third element from the second row and thus obtain [3 ; 9]. I managed it to do it with a loop, but since I'm working with much larger arrays, I would like to avoid these.
You can use sub2ind to convert each of the column subscripts (along with their row subscripts) into a linear index and then use that to index into your matrix.
A = [1 3 4 5; 2 4 9 2];
cols = [2; 3];
% Compute the linear index using sub2ind
inds = sub2ind(size(A), (1:numel(cols)).', cols);
B = A(inds)
% 3
% 9
Alternately, you could compute the linear indices yourself which is going to be more performant than sub2ind
B = A((cols - 1) * size(A, 1) + (1:numel(cols)).');
% 3
% 9
By exploiting the diag function, you can obtain an elegant one-line solution:
A = [1 3 4 5; 2 4 9 2];
cols = [2; 3];
B = diag(A(:,cols))
% 3
% 9
Here is what diag(A(:,cols)) does:
A(:,cols) selects the columns cols of A, with column k of A(:,cols) corresponding to the column cols(k) of A, giving [3 4; 4 9];
diag returns the diagonal entries of this matrix, thus returning at position k the k-th diagonal element of A(:,cols), which is A(k,cols(k)).
I'm looking to find the median of just a specific row of an m x n array. I couldn't find anything useful in the Matlab help section. E.g. if I had a small array
[1 2 4; 2 3 4; 6 2 8]
how would I find the median of row 2? Many thanks.
Search for median in google or matlab (doc median) and you will find the median function.
If you want to find the median of row 2, just use row,column indexing syntax, where : means all entries:
A = [1 2 4; 2 3 4; 6 2 8];
median(A(2,:))
You could try to use:
A = [1 2 4; 2 3 4; 6 2 8];
medianRows = median(A, 2); % to find every rows' median
medianRows(2)
Or:
medianRow2 = median(A(2, :)); % every column of 2nd row
just lets make it simple, assume that I have a 10x3 matrix in matlab. The numbers in the first two columns in each row represent the x and y (position) and the number in 3rd columns show the corresponding value. For instance, [1 4 12] shows that the value of function in x=1 and y=4 is equal to 12. I also have same x, and y in different rows, and I want to average the values with same x,y. and replace all of them with averaged one.
For example :
A = [1 4 12
1 4 14
1 4 10
1 5 5
1 5 7];
I want to have
B = [1 4 12
1 5 6]
I really appreciate your help
Thanks
Ali
Like this?
A = [1 4 12;1 4 14;1 4 10; 1 5 5;1 5 7];
[x,y] = consolidator(A(:,1:2),A(:,3),#mean);
B = [x,y]
B =
1 4 12
1 5 6
Consolidator is on the File Exchange.
Using built-in functions:
sparsemean = accumarray(A(:,1:2), A(:,3).', [], #mean, 0, true);
[i,j,v] = find(sparsemean);
B = [i.' j.' v.'];
A = [1 4 12;1 4 14;1 4 10; 1 5 5;1 5 7]; %your example data
B = unique(A(:, 1:2), 'rows'); %find the unique xy pairs
C = nan(length(B), 1);
% calculate means
for ii = 1:length(B)
C(ii) = mean(A(A(:, 1) == B(ii, 1) & A(:, 2) == B(ii, 2), 3));
end
C =
12
6
The step inside the for loop uses logical indexing to find the mean of rows that match the current xy pair in the loop.
Use unique to get the unique rows and use the returned indexing array to find the ones that should be averaged and ask accumarray to do the averaging part:
[C,~,J]=unique(A(:,1:2), 'rows');
B=[C, accumarray(J,A(:,3),[],#mean)];
For your example
>> [C,~,J]=unique(A(:,1:2), 'rows')
C =
1 4
1 5
J =
1
1
1
2
2
C contains the unique rows and J shows which rows in the original matrix correspond to the rows in C then
>> accumarray(J,A(:,3),[],#mean)
ans =
12
6
returns the desired averages and
>> B=[C, accumarray(J,A(:,3),[],#mean)]
B =
1 4 12
1 5 6
is the answer.
I am trying to sort the columns of a matrix based on the another vector values in a
fast way in matlab.
Let assume I have a reference vector:
a = [1 8 3];
And the matrix I wanna sort by rows
b =[2 3 4
5 6 4
1 2 1];
And I want the result based on the vector a if the sorted a is
a = [8 3 1]
the sorted matrix will be now
b = [3 4 2
6 4 5
2 1 1];
So the index of the first vector is the same with the index of the columns
So we sort columns based on the values of the vector.
In Matlab the sort function returns two variables, the first is the sorted vector/matrix and the second is a set of indices that can be combined with the original data to produce the sorted values.
A = [ 5 4 1 2 3 ];
[A_sorted1, idx] = sort(A);
A_sorted2 = A(idx);
A_sorted1 and A_sorted2 are equivalent.
If the number of rows in b is equal to the number of elements in a then you can simply use:
[~, idx] = sort(a);
b_sorted = b(idx,:);
And if you want to sort by columns use:
b_sorted = b(:,idx);