Octave / Matlab: Extend a vector making it repeat itself?
MatlabVectorOctaveMatlab Problem Overview
Is there a way to extend a vector by making it repeat itself?
>v = [1 2];
>v10 = v x 5; %x represents some function. Something like "1 2" x 5 in perl
Then v10 would be:
>v10
1 2 1 2 1 2 1 2 1 2
This should work for the general case, not just for [1 2]
Matlab Solutions
Solution 1 - Matlab
The function you're looking for is repmat()
.
v10 = repmat(v, 1, 5)
Solution 2 - Matlab
Obviously repmat is the way to go if you know in which direction you want to expand the vector.
However, if you want a general solution that always repeats the vector in the longest direction, this combination of repmat and indexing should do the trick:
v10=v(repmat(1:length(v),1,5))
Solution 3 - Matlab
here.
Although late, I am posting this because this turned out to be the most popular answer to a similar questionThis is a Faster Method Than repmat
or reshape
by an Order of Magnitude
One of the best methods for doing such things is Using Tony's Trick. I came across this trick in one of the Electrical Engineering course lectures notes of Columbia University. Repmat and Reshape are usually found to be slower than Tony's trick as it directly uses Matlabs inherent indexing. To answer you question,
Lets say, you want to tile the row vector r=[1 2 3]
N
times like r=[1 2 3 1 2 3 1 2 3...]
, then,
c=r'
cc=c(:,ones(N,1));
r_tiled = cc(:)';
This method has significant time savings against reshape
or repmat
for large N
's.
I conducted a small Matlab test to check the speed differential between repmat
and tony's trick
. Using the code mentioned below, I calculated the times for constructing the same tiled vector from a base vector A=[1:N]
. The results show that YES, Tony's-Trick is FASTER BY AN ORDER of MAGNITUDE, especially for larger N. People are welcome to try it themselves. This much time differential can be critical if such an operation has to be performed in loops. Here is the small script I used;
N= 10 ;% ASLO Try for values N= 10, 100, 1000, 10000
% time for tony_trick
tic;
A=(1:N)';
B=A(:,ones(N,1));
C=B(:)';
t_tony=toc;
clearvars -except t_tony N
% time for repmat
tic;
A=(1:N);
B=repmat(A,1,N);
t_repmat=toc;
clearvars -except t_tony t_repmat N
The Times (in seconds) for both methods are given below;
- N=10, time_repmat = 8e-5 , time_tony = 3e-5
- N=100, time_repmat = 2.9e-4 , time_tony = 6e-5
- N=1000, time_repmat = 0.0302 , time_tony = 0.0058
- N=10000, time_repmat = 2.9199 , time_tony = 0.5292
My RAM didn't permit me to go beyond N=10000. I am sure, the time difference between the two methods will be even more significant for N=100000. I know, these times might be different for different machines, but the relative difference in order-of-magnitude of times will stand. Also, I know, the avg of times could have been a better metric, but I just wanted to show the order of magnitude difference in time consumption between the two approaches. My machine/os details are given below :
Relevant Machine/OS/Matlab Details : Athlon i686 Arch, Ubuntu 11.04 32 bit, 3gb ram, Matlab 2011b