function [lat,lon,d,an,mn,sd,se,oa,ma,ng,nn] = read_csv_write_mat(input_dir,filename,output_dir);
% Read CSV files where the input arguments are strings:
% variable - field to use, ex: 
%      't' for temperature,
%      's' for salinity,
%      'o' for oxygen
% time - 01 to 12 for monthly
%        00 for annual
%        13 to 16 for seasonal
%             13 for winter (Jan-Mar), 
%             14 for spring (Apr-Jun),
%             15 for summer (Jul-Sep),
%             16 for autumn (Oct-Dec)
% depth - '01' to '33' standard levels
% res - '1d' for 1 degree, '5d' for 5 degrees

% input_dir = '/home/eleanor/data/woa05/csv/';
% filename = [variable,'_',time,'_',depth,'_',res];

% read the file, skipping 14 lines of header 
% (starting at row 14, col 0) where the first data entry is at row 0, col 0
mydata = csvread([input_dir,filename,'.csv'],14,0);

[N C] = size(mydata);
lat = sort(unique(mydata(:,1)));  % latitude grid
lon = sort(unique(mydata(:,2)));  % longitude grid
d = mydata(1,3);                  % depth

LT = length(lat);   
LN = length(lon);

an = zeros(LN,LT);   % objectively analyzed mean
mn = an;             % statitistically analyzed mean
sd = an;             % standard deviation of stat mean
se = an;             % standard error of stat mean
oa = an;             % an - mn
ma = an;             % an - <an>annual average
ng = an;             % number of grids with statistical means within radius of influence,
nn = an;             % number of data used to calculate statistical mean

for n=1:N
    % Find lat/lon indices
    ilat = find(lat==mydata(n,1));
    ilon = find(lon==mydata(n,2));

    an(ilon,ilat) = mydata(n,4);
    mn(ilon,ilat) = mydata(n,5);
    sd(ilon,ilat) = mydata(n,6);
    se(ilon,ilat) = mydata(n,7);
    oa(ilon,ilat) = mydata(n,8);
    ma(ilon,ilat) = mydata(n,9);
    ng(ilon,ilat) = mydata(n,10);
    nn(ilon,ilat) = mydata(n,11);
end

eval(['save ',output_dir,filename,'.mat lat lon d an mn sd se oa ma ng nn']);