Here are two functions that I am using to sort = through a database prior to analysis. I call these function many times = through a particular run. My issue is the consumption of memory through the run. If you recall my previous message, a long run will consume = >750MB of memory while I can account for only about 10MB. John Eaton = suggested that looping in some functions might lead to virtual memory leaks. = I would appreciate any comment on my programming in two example = functions.

Thanks for the help.

Example1.m:

function [ out, = weight, nmax, idx ] =3D S_out(code, mat1, mat2, S1, S2 )

# = Input:

# code - the three-column vector of three-letter reference = codes

# mat1 - matrix of values: if mat1 is a matrix of

# a n-length time series of values for m observations, the m = values

# are averaged over time.

# mat2 - matrix of identifying codes

# = Output:

# out - m-vector of weighted values

# weight - weights

# n - largest number of observations for any identifying = code

# idx - index of codes found in mat2

m =3D = size(idx,1);

n =3D = size(cap_mat,1);

if n > = 1

= mat1_mean =3D mean(mat1);

= else

= mat1_mean =3D mat1;

= endif

for i =3D = 1:m

= ix =3D [];

= ix =3D find( idx(i,:) !=3D 0 );

= n(i) =3D size(ix,2);

= out(i) =3D sum( mat1_mean( idx(i, ix) ) );

= endfor;

nmax =3D = max(n);

weight =3D zeros(m,nmax);

imx =3D = find(mat !=3D 0);

for i =3D = imx'

= ix =3D [];

= ix =3D find( idx(i,:) !=3D 0 );

weight(i,ix) =3D (mat1_mean( idx(i, ix) ))/out(i);

= endfor;

endfunction;

Example 2:

function [ = Rtn_val, idx ] =3D S_Index(mat, code)

# Return the = ID-sorted indicies of elements in the input code

# = Input:

# mat =3D database values (including several character strings - positions = known)

# code =3D the three-letter from the database

# S1, S2 =3D reference indicies

# = Output:

# Rtn_val =3D Vector of identification numbers

# idx =3D the set of indicies from the ID-sorted list

ID =3D = mat(:,1:5);

matrix =3D = toascii(mat(:,S1:S2));

c_code =3D toascii(code);

m =3D = size(code,1);

n =3D = size(sec_mat,2);

idx =3D = zeros(m,n);

Rtn_val =3D = zeros(m,1);

for i =3D = 1:m

= iz =3D [];

= iz1 =3D [];

= iz2 =3D [];

= iz3 =3D [];

= iz1 =3D find( matrix(:,1) =3D=3D c_code(i,1) );

= iz2 =3D find( matrix(:,2) =3D=3D c_code(i,2) );

= iz3 =3D find( matrix(:,3) =3D=3D c_code(i,3) );

= iz =3D intersection(iz1,iz2);

= iz =3D intersection(iz,iz3);

= n =3D size(iz,2);

idx(i,1:n) =3D iz;

= for j =3D 1:n

Rtn_val =3D str2num(ID(j,1:5));

= endfor;

endfunction;

David Pruitt, PhD

Ashdon Investment Analysis and Reseach, = LLC

Phone: 931.695.3220

Mobile: = 931.639.2477

Fax: 931.695.5545

e-mail: david dot pruitt@ashdonanalys= is.com