Matlab code to analyze data on a grid -

i have point set (x,y) coordinates , corresponding weights in matrix 1st, 2nd , 3rd columns x, y, , weight respectively. want divide point set grid cells, , count number of points in each grid , total weight of each grid.

i tried small example below, did not work. here tried divide data set 2x2 small grid , tried count number of points , sum of weights. further, have big data set, can not extend approach further when need different step sizes grid.

can please me develop easier approach?

function datatree count=zeros(9,1); avg=zeros(9,1); data=[1 3 100; 2 1 120; 3 5 110; 4 2 100; 5 3 150; 6 2 100];  i=1:6     if data(i,1)<=2         j=1:6             if data(j,2)<=2                 count(1) = count(1) + 1;                 avg(1) = avg(1) + data(j,3);             elseif data(j,2)<=4                     count(2) = count(2) + 1;                     avg(2) = avg(2) + data(j,3);              elseif data(j,2)<=6                     count(3) = count(3) + 1;                     avg(3) = avg(3) + data(j,3);             end         end     elseif data(i,1)<=4         j=1:6             if data(j,2)<=2                 count(4) = count(4) + 1;                 avg(4) = avg(4) + data(j,3);             elseif data(j,2)<=4                     count(5) = count(5) + 1;                     avg(5) = avg(5) + data(j,3);              elseif data(j,2)<=6                     count(6) = count(6) + 1;                     avg(6) = avg(6) + data(j,3);             end         end     elseif data(i,1)<=6         j=1:6             if data(j,2)<=2                 count(7) = count(7) + 1;                 avg(7) = avg(7) + data(j,3);             elseif data(j,2)<=4                     count(8) = count(8) + 1;                     avg(8) = avg(8) + data(j,3);              elseif data(j,2)<=6                     count(9) = count(9) + 1;                     avg(9) = avg(9) + data(j,3);             end         end      end end count' avg' 

if x , y not yet rounded arbitrary units, first:

x = round((x - min(x))/edgelength+1); 

this makes sure obtain grid edgelength sized squares, indicated non-zero integers. same y.

then can use either sparse or accumarray total weight. sparse faster, less wide applicable:

gridweight = sparse(x,y,weight); 

if want average weights, add 1 each entry , divide matrix:

numentries = sparse(x,y,1); meanweights = gridweight./numentries; 

accumarray can both of these operations in 1 go:

gridweight = accumarray([x y],weight); meanweights = accumarray([x y], weight,[],@mean); %//add ,[], 'issparse' sparse matrix 

note sparse sub-functionality of accumarary setting accumarray=([i,j],val,[],@sum,[],'issparse'). function sparse can handle @sum , it's sole fill-value 0, whilst accumarray other functions , values can used.