virtual void gradient(real& grad, const real& x) const {
real eps = finiteDifferenceEpsilon(), fp, fm;
real xx = x;
xx += eps;
fp = this->operator()(xx);
xx -= 2.0*eps;
fm = this->operator()(xx);
grad = 0.5 * (fp - fm) / eps;
}
//! method to overload to compute grad_f, the first derivative of
// the cost function with respect to x
virtual void gradient(Array& grad, const Array& x) const {
Real eps = finiteDifferenceEpsilon(), fp, fm;
Array xx(x);
for (Size i=0; i<x.size(); i++) {
xx[i] += eps;
fp = value(xx);
xx[i] -= 2.0*eps;
fm = value(xx);
grad[i] = 0.5*(fp - fm)/eps;
xx[i] = x[i];
}
}
//! method to overload to compute J_f, the jacobian of
// the cost function with respect to x
virtual void jacobian(Matrix &jac, const Array &x) const {
Real eps = finiteDifferenceEpsilon();
Array xx(x), fp, fm;
for(Size i=0; i<x.size(); ++i) {
xx[i] += eps;
fp = values(xx);
xx[i] -= 2.0*eps;
fm = values(xx);
for(Size j=0; j<fp.size(); ++j) {
jac[j][i] = 0.5*(fp[j]-fm[j])/eps;
}
xx[i] = x[i];
}
}
