% function qHistogram = ndHistc (mData, vEdge1, vEdge2, ... )
%
% * Input Arguments:
%
% + mData: nRecord by nDim 2-dimensional array of doubles
% + vEdge1, vEdge2, ... : nDim vectors of histogram edges
%
% * Return value:
%
% + qHistogram: nDim-dimensional data cube
% containing number of points in each cell
% defined by histogram edges. For instance,
% qHistogram(1,1,1,...) means number of data points
% satisfying
% vEdge1(1) <= mData(:,1) < vEdge1(2) & ...
% vEdge2(1) <= mData(:,2) < vEdge2(1) & ...
% vEdge3(1) <= mData(:,3) < vEdge3(1) & ...
% ...
% * Example
% mRand = rand(1e6,5);
% ve1 = linspace(0,1,5);
% ve2 = linspace(0,1,6);
% ve3 = linspace(0,1,7);
% ve4 = linspace(0,1,8);
% ve5 = linspace(0,1,9);
% qHist = ndhistc(mRand, ve1, ve2, ve3, ve4, ve5);
%
% * Comparison with ndhist.m (compiled using mcc -x ndhist)
% + 1e6 by 2 data -> 5 by 6
% ndhist.m 79.49 sec
% ndhistc.c 0.4610 sec
%
% + 1e6 by 5 data -> 5 by 6 by 7 by 8 by 9
% ndhist.m 199.32 sec
% ndhistc.c 2.4430 sec
%
% ==> More efficient if More data points & Less dimensions
%
% CopyLEFT (c) 2003 by Kangwon "Wayne" Lee. ;)
% $Revision: 1.0 $
% Implemented in a MATLAB mex file.
%#mex
