algorithm efficiency (memory allocation issue?)

[Aaron Brick]

hello all,

i wrote a simple routine to reproduce a vector many times (i couldn't find
any built-in method of copying and aggregating whole vectors - let me know,
please, if i missed it). i included a progress meter and was surprised to
note that the algorithm ran hugely slower as time went on, perhaps in O(n^2)
time. i can only suspect that it had to do with memory allocation and having
to copy the whole data set into a new space at each iteration, but it seems
like allocating logarithmically bigger spaces as need grows would make more
sense. anywya, without knowing implementation details, i'd like to know what
i can do to avoid this slowdown. here is the code. f is a vector (of rows)
and n is the number of times to reproduce it. try running the command
"multiply ( (1:200)', 100 )" for a dramatic demonstration of the slowdown.

function wave = multiply ( f, n )

        current = 0;
        for i = ( 1 : n ) 
                for j = ( 1 : rows (f) )
                        wave ( ++current ) = f ( j );
                endfor
                fprintf ( stderr, "%d ", i );
        endfor
        fprintf ( stderr, "\n\n" );

endfunction

thanks!

aaron.
                           - | | | | | | | | | | -
                           -                     -
                           -                     -
                           -     aaron brick     -
                           -    address@hidden    -
                           -                     -
                           -                     -
                           - | | | | | | | | | | -



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