bsxfun based approach -
A = [0.1 0.2 0.3 0.4 0.5]
r = [5 2 3 2 1]
repeats = bsxfun(@le,[1:max(r)]',r) %//' logical 2D array with ones in each column
%// same as the repeats for each entry
A1 = A(ones(1,max(r)),:) %// 2D matrix of all entries repeated maximum r times
%// and this resembles your repmat
out = A1(repeats) %// desired output with repeated entries
It could essentially become a two-liner -
A1 = A(ones(1,max(r)),:);
out = A1(bsxfun(@le,[1:max(r)]',r));
Output -
out =
0.1000
0.1000
0.1000
0.1000
0.1000
0.2000
0.2000
0.3000
0.3000
0.3000
0.4000
0.4000
0.5000
Benchmarking
Some benchmark results could be produced for the solutions presented here thus far.
Benchmarking Code - Case I
%// Parameters and input data
N = 4000;
max_repeat = 4000;
A = rand(1,N);
r = randi(max_repeat,1,N);
num_runs = 10; %// no. of times each solution is repeated for better benchmarking
disp('------------------- With arrayfun')
tic
for k1 = 1:num_runs
Anew = arrayfun(@(x) repmat(A(x), r(x), 1), 1:numel(A), 'uni', 0);
Anew = vertcat(Anew{:});
end
toc, clear Anew
disp('------------------- With cumsum')
tic
for k1 = 1:num_runs
B(cumsum(r) + 1) = 1;
idx = cumsum(B) + 1;
idx(end) = [];
out1 = A(idx);
end
toc,clear B idx out1
disp('------------------- With bsxfun')
tic
for k1 = 1:num_runs
A1 = A(ones(1,max(r)),:);
out2 = A1(bsxfun(@le,[1:max(r)]',r));
end
toc
Results
------------------- With arrayfun
Elapsed time is 2.198521 seconds.
------------------- With cumsum
Elapsed time is 5.360725 seconds.
------------------- With bsxfun
Elapsed time is 2.896414 seconds.
Benchmarking Code - Case II [Bigger datasize but lesser max of r]
%// Parameters and input data
N = 10000;
max_repeat = 1000;
Results
------------------- With arrayfun
Elapsed time is 2.641980 seconds.
------------------- With cumsum
Elapsed time is 3.426921 seconds.
------------------- With bsxfun
Elapsed time is 1.858007 seconds.
Conclusions from benchmarks
For case I, arrayfun seems like the way to go, while for Case II, bsxfun might be the weapon of choice. So, it seems that the type of data you are dealing with, would really dictate which approach to go with.
