What is the fastest way of taking an array A
and outputing both unique(A)
[i.e. the set of unique array elements of A
] as well as the multiplicity array which takes in its i-th place the i-th multiplicity of the i-th entry of unique(A)
in A
.
That's a mouthful, so here's an example. Given A=[1 1 3 1 4 5 3]
, I want:
unique(A)=[1 3 4 5]
mult = [3 2 1 1]
This can be done with a tedious for loop, but would like to know if there is a way to exploit the array nature of MATLAB.
uA = unique(A);
mult = histc(A,uA);
Alternatively:
uA = unique(A);
mult = sum(bsxfun(@eq, uA(:).', A(:)));
Benchmarking
N = 100;
A = randi(N,1,2*N); %// size 1 x 2*N
%// Luis Mendo, first approach
tic
for iter = 1:1e3;
uA = unique(A);
mult = histc(A,uA);
end
toc
%// Luis Mendo, second approach
tic
for iter = 1:1e3;
uA = unique(A);
mult = sum(bsxfun(@eq, uA(:).', A(:)));
end
toc
%'// chappjc
tic
for iter = 1:1e3;
[uA,~,ic] = unique(A); % uA(ic) == A
mult= accumarray(ic.',1);
end
toc
Results with N = 100
:
Elapsed time is 0.096206 seconds.
Elapsed time is 0.235686 seconds.
Elapsed time is 0.154150 seconds.
Results with N = 1000
:
Elapsed time is 0.481456 seconds.
Elapsed time is 4.534572 seconds.
Elapsed time is 0.550606 seconds.
[uA,~,ic] = unique(A); % uA(ic) == A
mult = accumarray(ic.',1);
accumarray
is very fast. Unfortunately, unique
gets slow with 3 outputs.
Late addition:
uA = unique(A);
mult = nonzeros(accumarray(A(:),1,[],@sum,0,true))
S = sparse(A,1,1);
[uA,~,mult] = find(S);
I've found this elegant solution in an old Newsgroup thread.
Testing with the benchmark of Luis Mendo for N = 1000
:
Elapsed time is 0.228704 seconds. % histc
Elapsed time is 1.838388 seconds. % bsxfun
Elapsed time is 0.128791 seconds. % sparse
(On my machine, accumarray
results in Error: Maximum variable size allowed by the program is exceeded.
)
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