1 #ifndef STAN__COMMON__INIT_ADAPT_HPP
2 #define STAN__COMMON__INIT_ADAPT_HPP
12 template<
class Sampler>
18 const Eigen::VectorXd& cont_params) {
19 const double epsilon = sampler->get_nominal_stepsize();
21 sampler->get_stepsize_adaptation().set_mu(
log(10 * epsilon));
22 sampler->get_stepsize_adaptation().set_delta(delta);
23 sampler->get_stepsize_adaptation().set_gamma(gamma);
24 sampler->get_stepsize_adaptation().set_kappa(kappa);
25 sampler->get_stepsize_adaptation().set_t0(t0);
27 sampler->engage_adaptation();
30 sampler->z().q = cont_params;
31 sampler->init_stepsize();
32 }
catch (
const std::exception&
e) {
33 std::cout <<
"Exception initializing step size." << std::endl
34 << e.what() << std::endl;
41 template<
class Sampler>
44 const Eigen::VectorXd& cont_params) {
51 Sampler* s =
dynamic_cast<Sampler*
>(sampler);
53 return init_adapt<Sampler>(s, delta, gamma, kappa, t0, cont_params);
argument * arg(const std::string name)
bool init_adapt(Sampler *sampler, const double delta, const double gamma, const double kappa, const double t0, const Eigen::VectorXd &cont_params)
double e()
Return the base of the natural logarithm.
fvar< T > log(const fvar< T > &x)