cumsum
based approach for a generic case (negative numbers or overlaps) -
%// Positions in intended output array at which group shifts
intv = cumsum([1 B-A+1])
%// Values to be put at those places with intention of doing cumsum at the end
put_vals = [A(1) A(2:end) - B(1:end-1)]
%// Get vector of ones and put_vals
id_arr = ones(1,intv(end)-1)
id_arr(intv(1:end-1)) = put_vals
%// Final output with cumsum of id_arr
out = cumsum(id_arr)
Sample run -
>> A,B
A =
-2 -3 1
B =
5 -1 3
>> out
out =
-2 -1 0 1 2 3 4 5 -3 -2 -1 1 2 3
Benchmarking
Here's a runtime test after warming-up tic-toc
to compare the various approaches listed to solve the problem for large sized A
and B
-
%// Create inputs
A = round(linspace(1,400000000,200000));
B = round((A(1:end-1) + A(2:end))/2);
B = [B A(end)+B(1)];
disp('------------------ Divakar Method')
.... Proposed approach in this solution
disp('------------------ Dan Method')
tic
idx = zeros(1,max(B)+1);
idx(A) = 1;
idx(B+1) = -1;
C = find(cumsum(idx));
toc, clear C idx
disp('------------------ Santhan Method')
tic
In = [A;B];
difIn = diff(In);
out1 = bsxfun(@plus, (0:max(difIn)).',A); %//'
mask = bsxfun(@le, (1:max(difIn)+1).',difIn+1); %//'
out1 = out1(mask).'; %//'
toc, clear out1 mask difIn In
disp('------------------ Itamar Method')
tic
C = cell2mat(cellfun(@(a,b){a:b},num2cell(A),num2cell(B)));
toc, clear C
disp('------------------ dlavila Method')
tic
C = cell2mat(arrayfun(@(a,b)a:b, A, B, 'UniformOutput', false));
toc
Runtimes
------------------ Divakar Method
Elapsed time is 0.793758 seconds.
------------------ Dan Method
Elapsed time is 2.640529 seconds.
------------------ Santhan Method
Elapsed time is 1.662889 seconds.
------------------ Itamar Method
Elapsed time is 2.524527 seconds.
------------------ dlavila Method
Elapsed time is 2.096454 seconds.