function [mu,S,C,SX,W] = ckf_transform(m,P,g,param,varargin)
% CKF_TRANSFORM - Cubature Kalman filter transform of random variables
%
% Syntax:
% [mu,S,C,SX,W] = CKF_TRANSFORM(M,P,g,param)
%
% In:
% M - Random variable mean (Nx1 column vector)
% P - Random variable covariance (NxN pos.def. matrix)
% g - Transformation function of the form g(x,param) as
% matrix, inline function, function name or function reference
% g_param - Parameters of g (optional, default empty)
%
% Out:
% mu - Estimated mean of y
% S - Estimated covariance of y
% C - Estimated cross-covariance of x and y
% SX - Sigma points of x
% W - Weights as cell array
% Copyright (c), 2010 Arno Solin
%
% This software is distributed under the GNU General Public
% Licence (version 2 or later); please refer to the file
% Licence.txt, included with the software, for details.
%%
% Estimate the mean of g
if nargin < 4
[mu,SX,W,F] = sphericalradial(g,m,P);
else
[mu,SX,W,F] = sphericalradial(g,m,P,param);
end
% Estimate the P and C
if nargin < 4
[pc,SX,W,FPC] = sphericalradial(@ckf_packed_pc,m,P,{g,m,mu});
else
[pc,SX,W,FPC] = sphericalradial(@ckf_packed_pc,m,P,{g,m,mu,param});
end
d = size(m,1);
s = size(mu,1);
S = reshape(pc(1:s^2),s,s);
C = reshape(pc(s^2+(1:s*d)),d,s);