/** @note Because of the virtual public inheritance, we create the Pdf
baseclass ourselves
*/
CondGausAddNoise::CondGausAddNoise(const Gaussian& additiveNoise,
int num_conditional_arguments)
: AnalyticConditionalGaussian(additiveNoise.DimensionGet(),
num_conditional_arguments)
, _additiveNoise_Mu (additiveNoise.ExpectedValueGet())
, _additiveNoise_Sigma(additiveNoise.CovarianceGet())
{}
// constructor
NonLinearAnalyticConditionalGaussian_Ginac::NonLinearAnalyticConditionalGaussian_Ginac
(const GiNaC::matrix& func,
const vector<GiNaC::symbol>& u,
const vector<GiNaC::symbol>& x,
const Gaussian& additiveNoise,
const vector<GiNaC::symbol>& cond )
:AnalyticConditionalGaussianAdditiveNoise(additiveNoise,3),
func_sym (func),
cond_sym (cond),
u_sym (u),
x_sym (x),
cond_size (cond_sym.size()),
u_size (u_sym.size()),
x_size (x_sym.size()),
func_size (func_sym.rows()),
dfunc_dcond (cond_size),
dfunc_dx (x_size)
{
// test for consistent input
assert (func_sym.cols() == 1);
assert (additiveNoise.DimensionGet() == cond_size);
// derive func to cond
for (unsigned int i=0; i < cond_size; i++)
dfunc_dcond[i] = func_sym.diff(cond_sym[i]);
// derive func to x
for (unsigned int i=0; i < x_size; i++)
dfunc_dx[i] = func_sym.diff(x_sym[i]);
}