function c = conf(D,x)
%        c = conf(D,x)
% Calculates the confidence that x belongs to the data distribution D,
% assuming D is a normal distribution.
% Input: D - 2xn or nx2 dimensional data array
%        x - a single 2D measurement that is to be tested against D.
%            x is an array of size 2x1 or 1x2
% Output: c - confidence, as a percentage.
% This function calls on functions:
%                   [C,a] =  prin_comp(D)
%                    
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
[C,a] = prin_comp(D); % Get the mean, a,  and covariance, C,  of the data.
R = chol(C); % Cholesky factorization: C = R'*R
[m,n] = size(x);
if (m==2)&(n==1)
    x = x;
elseif (m==1)&(n==2)
    x = x';
else
    error('x is not a suitable data point');
end
xm = x-a;
ym = inv(R')*xm;
radius = norm(ym);

% Integrate  numerically
% P = gaussian(radius);
%c = round((1-P)*100);

% Integrate analytically
c = (exp(-0.5*radius*radius)*100);
c = round(c);