How to create a mxn matrix with a specific rank in matlab? - matlab
I want to create a m by n matrix with rank k.
Like A is 8 × 8 with rank 5 or B is 4 × 6 with rank 4.
So I try to write a function in MATLAB like below.
My thought is:
generate an m by n zeros matrix
generate m by n matrix and convert it into reduced row echelon form
assign rank of 2.'s matrix to num
if num = k, then assign current matrix to the output
break the iteration
function output = check_rank(m,n,k)
while 1
output = zeros(m,n);
matrix = randi(20,m,n);
tmp = rref(matrix);
num = rank(tmp);
if (num == k)
output = matrix;
break;
end
disp(output);
end
A = check_rank(8,8,4)
The outcome is an infinite loop and all the answers are 6x6 zeros matrix:
Command Window Output
I have also tried method in the how to create a rank k matrix using matlab?
A = zeros(8,8);
for i = 1:4, A = A + randn(8,1) * randn(1,8); end
A
rank(A)
It can reach my goal, but I have no idea how it work successfully?
Thanks, #anonymous!
If you want to generate a random matrix with specified rank, you can try to build a user function like below
function [Y,rk] = fn(m,n,k)
P = orth(randn(m,k));
Q = orth(randn(n,k))';
Y = P*Q;
rk = rank(Y);
end
where P and Q are unitary matrices. Y is the generated matrix with random values, and rk helps you check the rank.
Example
>> [Y,rk] = fn(8,6,5)
Y =
3.8613e-02 7.5837e-03 -7.1011e-02 -7.0392e-02 -3.8519e-02 1.6612e-01
-3.1381e-02 -3.6287e-02 1.4888e-01 -7.6202e-02 -3.7867e-02 3.2707e-01
-1.9689e-01 2.2684e-01 1.2606e-01 -1.2657e-03 1.9724e-01 7.2793e-02
-1.2652e-01 7.7531e-02 1.3906e-01 3.1568e-02 1.8327e-01 -1.3804e-01
-2.6604e-01 -1.4345e-01 1.6961e-03 -9.7833e-02 5.9299e-01 -1.5765e-01
1.7787e-01 -3.5007e-01 3.8482e-01 -6.0741e-02 -2.1415e-02 -2.4317e-01
8.9910e-02 -2.5538e-01 -1.8029e-01 -7.0032e-02 -1.0739e-01 2.2188e-01
-3.4824e-01 3.7603e-01 2.8561e-02 2.6553e-02 2.4871e-02 6.8021e-01
rk = 5
You can easily use eye function:
I = eye(k);
M = zeros(m,n);
M(1:k, 1:k) = I;
The rank(M) is equal to k.
Related
Performance of using a matrix as vector index
In my code I have a slow part of which the idea can be summarized in the following short example: A = randi(10,5); %Random 5×5 matrix containing integers ranging from 0 to 10 B = rand(10,1); %Random 10×1 vector containing values ranging from 0 to 1 C = B(A); %New 5×5 matrix consisting of elements from B, indexed using A In my case, the matrix A is sized 1000×1000, B is a 500×1 vector and C is also 1000×1000. Given that this 3rd line is in a for loop, where A is constant and B is updated every iteration, how can I further improve speed performance? According to the profile viewer 75% of code execution is at this single line. As expected, using a for loop for this operation is much slower (10x for a 1000×1000 matrix): AA = A(:); %Convert matrix to vector for k=1:length(AA) %Loop through this vector and use it as index D(k) = B(AA(k)); end E = reshape(D,5,5); %Reshape vector to matrix of 5x5 Any ideas to optimize this? Edit: Script used to measure performance: N = 1500; A = randi(500,N); AA = A(:); D = zeros(N,N); B = rand(500,1); f1 = #() VectorIndex(A,B); timeit(f1,1) f2 = #() LoopIndex(AA,B,N); timeit(f2,1) function C = VectorIndex(A,B) C = B(A); end function D = LoopIndex(AA,B,N) D = zeros(N,N); for k=1:length(AA) D(k) = B(AA(k)); end D = reshape(D,N,N); end
How can we use nchoosek() to get all the combinations of the rows of a matrix?
If we have a vector v of 1- 5 numbers we can use nchoosek(v,2) to get all the combinations having two elements. But this function does now allow us to get all the combinations of a matrix. I want to use it to get all the combinations of rows of a matrix.
Here's one way to do it:
function p = q47204269(inMat)
% Input handling:
if nargin == 0 || isempty(inMat)
inMat = magic(5);
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
rowsCell = num2cell(inMat,2);
nRows = size(inMat,1);
p = cell(nRows,1);
for indR = 1:nRows
r = nchoosek(1:nRows,indR);
p{indR} = cell2mat(reshape(rowsCell(r.',:).',indR,1,[]));
end
See also:
The perms function, as it might come in handy in what you're doing.
This question.
with square matrix A v = 1:size(A,1); a = nchoosek(v,2); B = zeros(2,size(A,1),length(a)); for i = 1:length(a) B(:,:,i) = A(a(i,:)',:); end Each layer of array B is a 2 row matrix with the row combos from A
Not the most readable answer, but just for the sake of a one-liner :-) A = randn(5,3); % example matrix N = 2; % number of rows to pick each time result = permute(reshape(A(nchoosek(1:size(A,1), N).', :), N, [], size(A,2)), [1 3 2]); The result is a 3D array, such that each third-dim slice gives one of the a submatrices of A.
Iterating over all integer vectors summing up to a certain value in MATLAB?
I would like to find a clean way so that I can iterate over all the vectors of positive integers of length, say n (called x), such that sum(x) == 100 in MATLAB. I know it is an exponentially complex task. If the length is sufficiently small, say 2-3 I can do it by a for loop (I know it is very inefficient) but how about longer vectors? Thanks in advance,
Here is a quick and dirty method that uses recursion. The idea is that to generate all vectors of length k that sum to n, you first generate vectors of length k-1 that sum to n-i for each i=1..n, and then add an extra i to the end of each of these. You could speed this up by pre-allocating x in each loop. Note that the size of the output is (n + k - 1 choose n) rows and k columns. function x = genperms(n, k) if k == 1 x = n; elseif n == 0 x = zeros(1,k); else x = zeros(0, k); for i = 0:n y = genperms(n-i,k-1); y(:,end+1) = i; x = [x; y]; end end Edit As alluded to in the comments, this will run into memory issues for large n and k. A streaming solution is preferable, which generates the outputs one at a time. In a non-strict language like Haskell this is very simple - genperms n k | k == 1 = return [n] | n == 0 = return (replicate k 0) | otherwise = [i:y | i <- [0..n], y <- genperms (n-i) (k-1)] viz. >> mapM_ print $ take 10 $ genperms 100 30 [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,100] [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,99] [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,98] [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,97] [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,96] [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,95] [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,94] [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7,93] [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,92] [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,91] which runs virtually instantaneously - no memory issues to worry about. In Python you could achieve something nearly as simple using generators and the yield keyword. In Matlab it is certainly possible, but I leave the translation up to you!
This is one possible method to generate all vectors at once (will give memory problems for moderately large n):
s = 10; %// desired sum
n = 3; %// number of digits
vectors = cell(1,n);
[vectors{:}] = ndgrid(0:s); %// I assume by "integer" you mean non-negative int
vectors = cell2mat(cellfun(#(c) reshape(c,1,[]), vectors, 'uni', 0).');
vectors = vectors(:,sum(vectors)==s); %// each column is a vector
Now you can iterate over those vectors:
for vector = vectors %// take one column at each iteration
%// do stuff with the vector
end
To avoid memory problems it is better to generate each vector as needed, instead of generating all of them initially. The following approach iterates over all possible n-vectors in one for loop (regardless of n), rejecting those vectors whose sum is not the desired value:
s = 10; %// desired sum
n = 3;; %// number of digits
for number = 0: s^n-1
vector = dec2base(number,s).'-'0'; %// column vector of n rows
if sum(vector) ~= s
continue %// reject that vector
end
%// do stuff with the vector
end
Looping with two variables from a vector
I have a 30-vector, x where each element of x follows a standardised normal distribution. So in Matlab, I have: for i=1:30; x(i)=randn; end; Now I want to create 30*30=900 elements from vector, x to make a 900-vector, C defined as follows: I am unable to do the loop for two variables (k and l) properly. I have: for k=1:30,l=1:30; C(k,l)=(1/30)*symsum((x(i))*(x(i-abs(k-l))),1,30+abs(k-l)); end It says '??? Undefined function or method 'symsum' for input arguments of type 'double'.' I hope to gain from this a 900-vector, C which I will then rewrite as a matrix. The reason I have using two indices k and l instead of one is because I eventually want these indices to denote the (k,l)-entry of such a matrix so it is important that that my 900-vector will be in the form of C = [ row 1 row 2 row 3 ... row 30 ] so I can use the reshape tool i.e. C'=reshape(C,30,30) Could anyone help me with the code for the summation and getting such a 900 vector.
Let's try to make this a bit efficient. n = 30; x = randn(n,1); %# preassign C for speed C = zeros(n); %# fill only one half of C, since it's symmetric for k = 2:n for l = 1:k-1 %# shift the x-vector by |k-l| and sum it up delta = k-l; %# k is always larger than l C(k,l) = sum( x(1:end-delta).*x(1+delta:end) ); end end %# fill in the other half of C C = C + C'; %# add the diagonal (where delta is 0, and thus each %# element of x is multiplied with itself C(1:n+1:end) = sum(x.^2);
It seems to me that you want a matrix C of 30x30 elements. Given the formula that you provided I would do x = randn(1,30) C = zeros(30,30) for k=1:30 for l=1:30 v = abs(k-l); for i =1:30-v C(k,l) = C(k,l) + x(i)*x(i+v); end end end if you actually need the vector you can obtain it from the matrix.
Matlab Generating a Matrix
I am trying to generate a matrix in matlab which I will use to solve a polynomial regression formula.
Here is how I am trying to generate the matrix:
I have an input vector X containing N elements and an integer d. d is the integer to know how many times we will add a new column to the matrix we are trying to generate int he following way.
N = [X^d X^{d-1} ... X^2 X O]
O is a vector of same length as X with all 1's.
Everytime d > 2 it does not work.
Can you see any errors in my code (i am new to matlab):
function [ PR ] = PolyRegress( X, Y, d )
O = ones(length(X), 1)
N = [X O]
for j = 2:d
tmp = power(X, j)
N = [tmp N]
end
%TO DO: compute PR
end
It looks like the matlab function vander already does what you want to do.
The VANDER function will only generate powers of the vector upto d = length(X)-1. For a more general solution, you can use the BSXFUN function (works with any value of d): N = bsxfun(#power, X(:), d:-1:0) Example: >> X = (1:.5:2); >> d = 5; >> N = bsxfun(#power, X(:), d:-1:0) N = 1 1 1 1 1 1 7.5938 5.0625 3.375 2.25 1.5 1 32 16 8 4 2 1 I'm not sure if this is the order you want, but it can be easily reversed: use 0:d instead of d:-1:0...