timour_matlab/mscripts/radialwmean.m

% create circular sampling rings
t=w;

Nn=Nx/2;

rad=[1:1:(Nn-1)];
ring=ones(Nx,Ny,Nz);
weight=zeros(1,Nn-1);
radialmean=zeros(1,Nn-1);
XCenter = (Nx+1)/2 ;
YCenter = (Ny+1)/2 ;


for k=1:Nn-1
  for i=1:Nx
    for j=1:Ny
      radius(i,j) = sqrt((i-XCenter)^2+(j-YCenter)^2);
    end
  end
  radius(find( round(radius) > (k+1) ))=radius(find (round(radius) > (k+1) ))*0;
  radius(find( round(radius) < (k)   ))=radius(find (round(radius) < (k)   ))*0;
  radius(find(radius>0))=1.0;
  ring(:,:,k)=radius;
  weight(:,k)=length(find(ring(:,:,k) > 0));
end


for i=1:Nn-1
tring=t(:,:,15).*ring(:,:,i);
meandoubleu(i)=sum(sum(tring))/weight(:,i);
end

figure
plot([1:Nn-1],meandoubleu,'o-')
1	edhill	1.1	% create circular sampling rings
2			t=w;
3
4			Nn=Nx/2;
5
6			rad=[1:1:(Nn-1)];
7			ring=ones(Nx,Ny,Nz);
8			weight=zeros(1,Nn-1);
9			radialmean=zeros(1,Nn-1);
10			XCenter = (Nx+1)/2 ;
11			YCenter = (Ny+1)/2 ;
12
13
14			for k=1:Nn-1
15			for i=1:Nx
16			for j=1:Ny
17			radius(i,j) = sqrt((i-XCenter)^2+(j-YCenter)^2);
18			end
19			end
20			radius(find( round(radius) > (k+1) ))=radius(find (round(radius) > (k+1) ))*0;
21			radius(find( round(radius) < (k) ))=radius(find (round(radius) < (k) ))*0;
22			radius(find(radius>0))=1.0;
23			ring(:,:,k)=radius;
24			weight(:,k)=length(find(ring(:,:,k) > 0));
25			end
26
27
28			for i=1:Nn-1
29			tring=t(:,:,15).*ring(:,:,i);
30			meandoubleu(i)=sum(sum(tring))/weight(:,i);
31			end
32
33			figure
34			plot([1:Nn-1],meandoubleu,'o-')