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initialize a MxN matrix with the same number

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Salvatore Mazzarino
Salvatore Mazzarino on 20 Oct 2012
Answered: Matt J on 11 Nov 2018
I would initialize a M x N matrix with the same number. Which could be the best way in terms of speed?
Es.
[2 2;
2 2
2 2]

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Answers (8)

Matt Fig
Matt Fig on 20 Oct 2012
Another:
% Make a 3-by-8 matrix of 9s:
A(1:3,1:8) = 9

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Jan
Jan on 20 Oct 2012
This method can cause problems, if A has been defined before, e.g. by A = rand(9) or A = 'string'.
John BG
John BG on 28 Sep 2016
if it has been defined before ..
if it coincides with the name of a function ..
if you start looking backward there is not way to move forward.
Matt gave the right answer, get on with it, or prove it wrong.
Walter Roberson
Walter Roberson on 29 Sep 2016
? You are arguing with a 4 year old posting ?
Jan did give a counter example:
A = rand(9);
A(1:3, 1:8) = 9;
A
A =
9.0000 9.0000 9.0000 9.0000 9.0000 9.0000 9.0000 9.0000 0.9651
9.0000 9.0000 9.0000 9.0000 9.0000 9.0000 9.0000 9.0000 0.6406
9.0000 9.0000 9.0000 9.0000 9.0000 9.0000 9.0000 9.0000 0.7577
0.5009 0.5300 0.3514 0.0230 0.6206 0.5925 0.8718 0.5488 0.7359
0.8410 0.9315 0.2206 0.2301 0.4299 0.1449 0.7987 0.3064 0.6590
0.9057 0.9739 0.3609 0.8522 0.6744 0.5350 0.7201 0.2121 0.9933
0.2481 0.8476 0.1054 0.9497 0.9710 0.2542 0.0973 0.6881 0.8679
0.1017 0.7075 0.1900 0.1831 0.3252 0.8435 0.3257 0.7090 0.4237
0.5273 0.9981 0.1697 0.2163 0.9954 0.9812 0.1355 0.4648 0.6465
Part of the array was set as required but the rest was left alone, which does not meet the specifications.

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Azzi Abdelmalek
Azzi Abdelmalek on 20 Oct 2012
Edited: Azzi Abdelmalek on 20 Oct 2012
A=zeros(M,N)

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Jan
Jan on 20 Oct 2012
To avoid troubles with earlier definitions, I prefer:
A = repmat(12, M, N);
The overhead for calling the M-file repmat can be omitted:
a = 12;
A = a(ones(M, N));

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Friedrich
Friedrich on 14 Aug 2018
Edited: Friedrich on 15 Aug 2018
I know this is old but I could not let it go. I found
A=zeros(M,N)+10;
to be the fastest. At least on my computer. Heres my code for testing and the results in Matlab 2017b
% produces 6.4GB of data
M = 80e6;
N = 10;
clear A
tic;
A=ones(M,N)*10;
disp(['A=ones(M,N)*10; = ' num2str(toc) 's']);
clear A
tic;
A=uninit(M,N);
A(:) = 10;
disp(['A=uninit(M,N); A(:)=10; = ' num2str(toc) 's']);
clear A
tic;
A=repmat(10,[M,N]);
disp(['A=repmat(10,[M,N]); = ' num2str(toc) 's']);
clear A
tic;
A = mxFastZeros(0,M,N)+10;
disp(['A=mxFastZeros(0,M,N)+10; = ' num2str(toc) 's']);
clear A
tic;
A=zeros(M,N)+10;
disp(['A=zeros(M,N)+10; = ' num2str(toc) 's']);
clear A
tic;
a = 12;
A = a(ones(M, N));
disp(['a=10;A=a(ones(M, N)); = ' num2str(toc) 's']);
clear A
Results
A=ones(M,N)*10; = 3.312s
A=uninit(M,N); A(:)=10; = 2.508s
A=repmat(10,[M,N]); = 2.1169s
A=mxFastZeros(0,M,N)+10; = 1.8326s
A=zeros(M,N)+10; = 1.8487s
a=10;A=a(ones(M, N)); = 25.0576s
Edit: Thank you James for the hint on mxFastZeros. I included that in the benchmark.

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James Tursa
James Tursa on 14 Aug 2018
Here's another one you can try using the undocumented API function mxFastZeros:
A = mxFastZeros(0,M,N)+10;
The behavior of this seems highly version dependent. In some versions it seems to run fast at first and then maybe exhaust the supply of pre-0'ed data and the timings jump up significantly. But just guessing here.
The mex code:
/* mxFastZeros.c generates a zero 2D double matrix
Syntax: z = mxFastZeros( ComplexFlag, M, N )
Where:
ComplexFlag = 0 (real) or 1 (complex)
M = row size
N = column size
Programmer: James Tursa
*/
#include "mex.h"
#undef mxFastZeros
#undef mxCreateSharedDataCopy
mxArray *mxFastZeros(mxComplexity ComplexFlag, mwSize m, mwSize n);
mxArray *mxCreateSharedDataCopy(mxArray *mx);
void mexFunction(int nlhs, mxArray *plhs[], int nrhs, const mxArray *prhs[])
{
mxArray *mx;
mxComplexity ComplexFlag;
mwSize m, n;
if( nrhs != 3 ) {
mexErrMsgTxt("Syntax: mxFastZeros(ComplexFlag,M,N)");
}
if( nlhs > 1 ) {
mexErrMsgTxt("Too many outputs.");
}
ComplexFlag = mxGetScalar(prhs[0]);
m = mxGetScalar(prhs[1]);
n = mxGetScalar(prhs[2]);
mx = mxFastZeros(ComplexFlag,m,n);
plhs[0] = mxCreateSharedDataCopy(mx);
mxDestroyArray(mx);
}

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Matt J
Matt J on 20 Oct 2012
A=zeros(M,N);
A(:)=some_number;

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James Tursa
James Tursa on 20 Oct 2012
Edited: James Tursa on 20 Oct 2012
Another method if matrix A is not already allocated:
A = uninit(M,N);
A(:) = some_number;
UNINIT can be found here:
If the matrix A is pre-existing, then of course skip the allocation step and just fill the values ala the 2nd line above.
SIDE NOTE: On later version of MATLAB it seems the parser is smart enough to recognize the value*ones(m,n) formulation and not actually do the multiply. At least that is my conclusion based on speed tests.

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MathWorks Support Team
MathWorks Support Team on 9 Nov 2018
In general, the easiest ways to initialize a matrix with the same number are the following, which produce a 3-by-2 matrix whose elements are all 2:
A = 2*ones(3,2)
A = zeros(3,2) + 2
A = repmat(2,3,2)
The speed of these methods relative to each other can depend on your computing environment.

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Matt J
Matt J on 11 Nov 2018
Here's a safe one-liner, but I don't know how fast it is.
A=randi([n,n], M,N);

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