samer@57: function [NN,map1,map2]=hist2d(X,m1spec,m2spec,varargin)
samer@57: % hist2d - 2D histogram
samer@57: %
samer@57: % hist2d :: 
samer@57: %    [[N,2]]	~'N rows of 2D data',
samer@57: %    (K1:natural | dmap(K1)) ~'num bins for dim 1, or bins',
samer@57: %    (K2:natural | dmap(K2)) ~'num bins for dim 1, or bins'
samer@57: % -> [[K1,K2]->natural] ~'bin counts',
samer@57: %    dmap(K1),
samer@57: %    dmap(K2).
samer@57: %
samer@57: % if second map spec is empty, it means use the same map
samer@57: % for both dimensions.
samer@57: 
samer@57: mins=min(X); mm=max(X); maxs=mm+eps(mm);
samer@57: map1=mkdmap(mins(1),maxs(1),m1spec,[]);
samer@57: map2=mkdmap(mins(2),maxs(2),m2spec,m1spec);
samer@57: 
samer@57: N=accumhist([map1(X(:,1)) map2(X(:,2))],1,[cardr(map1) cardr(map2)]);
samer@57: if nargout==0,
samer@57: 	opts=prefs('cmap',@(t)log(1+t),varargin{:});
samer@57: 	imagexy(centres(map2),centres(map1),opts.cmap(N));
samer@57: else
samer@57: 	NN=N;
samer@57: end
samer@57: 
samer@57: 
samer@57: function M=mkdmap(min,max,spec,def)
samer@57: 	if isempty(spec), spec=def; end
samer@57: 	if isa(spec,'dmap') % is alread a dmap
samer@57: 		M=spec;
samer@57: 	elseif length(spec)==1, % spec=number of bins
samer@57: 		M=linmap(min,max,spec);
samer@57: 	else
samer@57: 		error('invalid discretisation map');
samer@57: 	end
samer@57: