nt_wmean

y=nt_wmean(x,w,dim) - weighted average

 y: vector of weighed means

 x: column vector or matrix of values to average columnwise
 w: column vector or matrix of weights (default: all ones)
 dim: dimension over which to average (default: 1)
 
 if x contains nans the corresponding weights are set to zero

0001 function y=nt_wmean(x,w,dim) 
0002 %y=nt_wmean(x,w,dim) - weighted average
0003 %
0004 % y: vector of weighed means
0005 %
0006 % x: column vector or matrix of values to average columnwise
0007 % w: column vector or matrix of weights (default: all ones)
0008 % dim: dimension over which to average (default: 1)
0009 %
0010 % if x contains nans the corresponding weights are set to zero
0011 
0012 if nargin<3; dim=[]; end
0013 if nargin<2; w=[]; end
0014 
0015 % treat nans as zero-weighted 0s
0016 if numel(find(isnan(x)))>0
0017     x(find(isnan(x)))=0;
0018     if isempty(w)
0019         w=ones(size(x));
0020     end
0021     w(find(isnan(x)))=0;
0022 end
0023 
0024 if isempty(dim); dim=1; end
0025 if isempty(w)
0026     y=mean(x,dim);
0027 else
0028     if size(x,1) ~= size(w,1); error('data and weight must have same nrows'); end
0029     if size(w,2)==1; w=repmat(w,1,size(x,2)); end
0030     if size(w,2) ~= size(x,2); error('weight must have same ncols as data, or 1'); end
0031     y=sum(x.*w,dim)./sum(w,dim);
0032     y(find(isnan(y)))=0;
0033 end
0034