Density.m

classdef Density <handle
    %The purpose of this class is to empirically estimate
    %one dimensional probability densities using linear interpolation
    %
    %Dependent files:
    %
    %   XDomainFunction.m , http://pastebin.com/qY5DRj3i
    %   XDomainStatistics.m , http://pastebin.com/h42ZWauh
    %

   properties (GetAccess = 'private', SetAccess = 'private')
      Function;
      Statistics;
   end
   methods
       function D = Density(D,dx)
           if nargin == 1
               dx = 1;
           end

           %add function properties
           D.Statistics = XDomainStatistics();
           D.Function = XDomainFunction(-dx/2,dx/2);
       end
       function [n_float, supportPointsAdded] = addPoint(D,x,weight)
           if nargin == 2
               weight = 1;
           end

           %update density
           D.Function.addPoint(x,weight);

           %add linear interpolated weight to function
           D.Statistics.addPoint(x,weight);

           n_float = D.Function.getNFloat(x);
           supportPointsAdded = D.Function.supportPointsAdded;
       end
       function p = prob(D,x)
          %x is scalar
          p = D.Function.linearInterpolatedValue(x)/D.Statistics.cumWeight;
       end

       %Extra Statistics member functions
       function n_MaxP = nMaxP(D)
           n_MaxP = D.Function.nMaxValue;
       end
       function n_MinP = nMinP(D)
           n_MinP = D.Function.nMinValue;
       end
       function minP = minP(D)
           minP = D.Function.minValue()/D.Statistics.cumWeight;
       end
       function maxP = maxP(D)
           maxP = D.Function.maxValue()/D.Statistics.cumWeight;
       end

       %Overloaded Statistics
       function ExpectedValue = Ex(D)
           ExpectedValue = D.Statistics.Ex;
       end
       function ExpectedValueSquared = Exx(D)
           ExpectedValueSquared = D.Statistics.Exx;
       end
       function Variance = Var(D)
           Variance = D.Statistics.Var;
       end
       function functionX = fX(D,nn)
           if nargin == 2
               functionX = D.Function.fX(nn)/D.Statistics.cumWeight;
           else
               functionX = D.Function.fX/D.Statistics.cumWeight;
           end
       end
       function domainX = X(D,nn)
           if nargin == 2
               domainX = D.Function.X(nn);
           else
               domainX = D.Function.X;
           end
       end
       function differentialX = dX(D)
           differentialX = D.Function.dX;
       end
       function cumulativeSum = cumWeight(D)
           cumulativeSum = D.Statistics.cumWeight;
       end
   end
end