# initialize a MxN matrix with the same number

조회 수: 1,026 (최근 30일)
Salvatore Mazzarino 2012년 10월 20일
댓글: Walter Roberson 2023년 12월 11일
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]

댓글을 달려면 로그인하십시오.

### 답변 (10개)

Matt Fig 2012년 10월 20일
Another:
% Make a 3-by-8 matrix of 9s:
A(1:3,1:8) = 9
##### 댓글 수: 3이전 댓글 1개 표시이전 댓글 1개 숨기기
John BG 2016년 9월 28일
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 2016년 9월 29일
? 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.

댓글을 달려면 로그인하십시오.

Friedrich 2018년 8월 14일
편집: Friedrich 2018년 8월 15일
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.
##### 댓글 수: 5이전 댓글 3개 표시이전 댓글 3개 숨기기
Matt J 2020년 6월 18일
You should probably add repelem to this comparison.
Rik 2020년 6월 18일
I also added your suggestion with randi and reposted it as an answer to avoid this being burried.

댓글을 달려면 로그인하십시오.

Rik 2020년 6월 18일
편집: Rik 2020년 6월 19일
Inspired by the comparative speed test in the answer by Friedrich, I extended his code to have more robust testing that could be performed on multiple different releases. Timings below are normalized to 10*ones(M,N), and Octave and ML6.5 have fewer elements to prevent max array size errors. See the attached file for all details.
(failed options are removed from this post, but are displayed by the function) (you could make the function more fancy, but I didn't feel like spending time on that. I might update this function at some point)
Matlab 6.5:
A=ones(M,N)*10; = 0.0410s (normalized time = 0.99)
A=zeros(M,N)+10; = 0.0400s (normalized time = 1.01)
A=repmat(10,[M,N]) = 0.0460s (normalized time = 1.14)
a=10;A=a(ones(M, N)); = 0.2770s (normalized time = 6.84)
R2011a:
A=repmat(10,[M,N]) = 1.8918s (normalized time = 0.98)
A=ones(M,N)*10; = 1.8975s (normalized time = 0.99)
A=uninit(M,N); A(:)=10; = 1.9129s (normalized time = 1.00)
A=zeros(M,N)+10; = 2.0259s (normalized time = 1.05)
A=mxFastZeros(0,M,N)+10; = 3.7976s (normalized time = 1.94)
a=10;A=a(ones(M, N)); = 8.4049s (normalized time = 4.36)
A=randi([10,10], M,N); = 12.0829s (normalized time = 6.20)
R2015a:
A=repmat(10,[M,N]) = 0.6856s (normalized time = 0.39)
A=repelem(10, M, N); = 0.7803s (normalized time = 0.44)
A=mxFastZeros(0,M,N)+10; = 1.7123s (normalized time = 0.97)
A=uninit(M,N); A(:)=10; = 1.7477s (normalized time = 0.99)
A=ones(M,N)*10; = 1.7598s (normalized time = 0.99)
A=zeros(M,N)+10; = 1.8429s (normalized time = 1.04)
a=10;A=a(ones(M, N)); = 7.6893s (normalized time = 4.35)
A=randi([10,10], M,N); = 7.7680s (normalized time = 4.40)
R2020a:
A=mxFastZeros(0,M,N)+10; = 0.6672s (normalized time = 0.31)
A=zeros(M,N)+10; = 0.6879s (normalized time = 0.31)
A=repmat(10,[M,N]) = 0.7013s (normalized time = 0.32)
A=repelem(10, M, N); = 0.7761s (normalized time = 0.36)
A=uninit(M,N); A(:)=10; = 1.7886s (normalized time = 0.83)
A=ones(M,N)*10; = 2.1304s (normalized time = 0.98)
A=randi([10,10], M,N); = 6.9900s (normalized time = 3.21)
a=10;A=a(ones(M, N)); = 7.2315s (normalized time = 3.32)
Octave 5.2.0
A=repmat(10,[M,N]) = 0.0264s (normalized time = 0.43)
A=repelem(10, M, N); = 0.0366s (normalized time = 0.59)
A=zeros(M,N)+10; = 0.0583s (normalized time = 0.94)
A=uninit(M,N); A(:)=10; = 0.0628s (normalized time = 1.00)
A=ones(M,N)*10; = 0.0637s (normalized time = 1.03)
a=10;A=a(ones(M, N)); = 0.0945s (normalized time = 1.53)
A=randi([10,10], M,N); = 0.4947s (normalized time = 8.00)
##### 댓글 수: 3이전 댓글 1개 표시이전 댓글 1개 숨기기
Rik 2020년 6월 18일
This is the output. I replaced the current directory and the install path with placeholders. In case it is relevant: the pwd doesn't have spaces, but the install path does.
Building with 'MinGW64 Compiler (C)'.
Error using mex
{{pwd}}\mxFastZeros.c:14:10: error: conflicting types for 'mxFastZeros'
mxArray *mxFastZeros(mxComplexity ComplexFlag, mwSize m, mwSize n);
^~~~~~~~~~~
In file included from {{mlroot}}/extern/include/mex.h:43:0,
from {{pwd}}\mxFastZeros.c:10:
{{mlroot}}/extern/include/matrix.h:1171:46: note: previous declaration of 'mxFastZeros' was here
LIBMMWMATRIX_PUBLISHED_API_EXTERN_C mxArray *mxFastZeros(int cmplx_flag, int m, int n);
^~~~~~~~~~~
{{pwd}}\mxFastZeros.c:15:10: error: conflicting types for 'mxCreateSharedDataCopy'
mxArray *mxCreateSharedDataCopy(mxArray *mx);
^~~~~~~~~~~~~~~~~~~~~~
In file included from {{mlroot}}/extern/include/mex.h:43:0,
from {{pwd}}\mxFastZeros.c:10:
{{mlroot}}/extern/include/matrix.h:1169:46: note: previous declaration of 'mxCreateSharedDataCopy' was here
LIBMMWMATRIX_PUBLISHED_API_EXTERN_C mxArray *mxCreateSharedDataCopy(const mxArray *pa);
^~~~~~~~~~~~~~~~~~~~~~
James Tursa 2020년 6월 18일
Looks like they have exposed the true interfaces to these unofficial functions. Just use them. E.g.,
mxArray *mxFastZeros(int cmplx_flag, int m, int n);
mxArray *mxCreateSharedDataCopy(const mxArray *mx);

댓글을 달려면 로그인하십시오.

Azzi Abdelmalek 2012년 10월 20일
편집: Azzi Abdelmalek 2012년 10월 20일
A=zeros(M,N)
##### 댓글 수: 4이전 댓글 2개 표시이전 댓글 2개 숨기기
Azzi Abdelmalek 2012년 10월 20일
or
A=repmat(12,M,N);
Azzi Abdelmalek 2012년 10월 20일
Matt's init is the fastest

댓글을 달려면 로그인하십시오.

Jan 2012년 10월 20일
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));
##### 댓글 수: 0이전 댓글 -2개 표시이전 댓글 -2개 숨기기

댓글을 달려면 로그인하십시오.

Matt J 2012년 10월 20일
A=zeros(M,N);
A(:)=some_number;
##### 댓글 수: 0이전 댓글 -2개 표시이전 댓글 -2개 숨기기

댓글을 달려면 로그인하십시오.

James Tursa 2012년 10월 20일
편집: James Tursa 2012년 10월 20일
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.
##### 댓글 수: 0이전 댓글 -2개 표시이전 댓글 -2개 숨기기

댓글을 달려면 로그인하십시오.

Rozh Al-Mashhdi 2023년 12월 10일
편집: Stephen23 2023년 12월 10일
At least on my system (macbook pro 2021, Matlab 2023), the following is faster than V * ones (M,N) for very large M and N. For small M and N there is no measurable difference
A=zeros(M,1)+V;
B=zeros(1,N)+1;
C=A*B;
The above is inspired by:
##### 댓글 수: 5이전 댓글 3개 표시이전 댓글 3개 숨기기
Walter Roberson 2023년 12월 11일
For those sizes, here on MATLAB Answers, nothing is reliable about the timing, and the third version I came up with might be a hair faster.
Relative performance on your own system might be substantially different.
format long g
testtimes();
ans = 3×3
0.393793 0.451649 0.390828 0.335784 0.370165 0.399899 0.330778 0.365417 0.367776
function testtimes()
M = 12000; N = 18000;
V = 123;
start = tic;
A1 = zeros(M,1)+V;
B1 = zeros(1,N)+1;
C1 = A1*B1;
t1a = toc(start);
start = tic;
A2 = zeros(M,1)+V;
B2 = ones(1,N);
C2 = A2*B2;
t2a = toc(start);
start = tic;
A3 = ones(M,1)*V;
B3 = ones(1,N);
C3 = A3*B3;
t3a = toc(start);
start = tic;
A1 = zeros(M,1)+V;
B1 = zeros(1,N)+1;
C1 = A1*B1;
t1b = toc(start);
start = tic;
A2 = zeros(M,1)+V;
B2 = ones(1,N);
C2 = A2*B2;
t2b = toc(start);
start = tic;
A3 = ones(M,1)*V;
B3 = ones(1,N);
C3 = A3*B3;
t3b = toc(start);
start = tic;
A1 = zeros(M,1)+V;
B1 = zeros(1,N)+1;
C1 = A1*B1;
t1c = toc(start);
start = tic;
A2 = zeros(M,1)+V;
B2 = ones(1,N);
C2 = A2*B2;
t2c = toc(start);
start = tic;
A3 = ones(M,1)*V;
B3 = ones(1,N);
C3 = A3*B3;
t3c = toc(start);
[t1a, t1b, t1c; t2a, t2b, t2c; t3a, t3b, t3c]
end
Walter Roberson 2023년 12월 11일
On my system, with those array sizes:
>> another_way
ans =
0.110873719 0.192779666 0.17914935
0.105916544 0.167061579 0.178607924
0.108013696 0.177013045 0.169540193
>> another_way
ans =
0.101248998 0.176637954 0.200039796
0.10419013 0.155409292 0.162791305
0.098662435 0.154152901 0.173319562
Nothing there is reliable either.

댓글을 달려면 로그인하십시오.

MathWorks Support Team 2018년 11월 9일
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.
##### 댓글 수: 0이전 댓글 -2개 표시이전 댓글 -2개 숨기기

댓글을 달려면 로그인하십시오.

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

댓글을 달려면 로그인하십시오.

### 카테고리

Help CenterFile Exchange에서 Programming Utilities에 대해 자세히 알아보기

### Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by