void print_sample_params(RNG& rng,
stan::mcmc::sample& sample,
stan::mcmc::base_mcmc& sampler,
M& model) {
if(!_sample_stream) return;
std::vector<double> values;
sample.get_sample_params(values);
sampler.get_sampler_params(values);
std::vector<double> model_values;
model.write_array(rng,
const_cast<std::vector<double>&>(sample.cont_params()),
const_cast<std::vector<int>&>(sample.disc_params()),
model_values,
true, true); // FIXME: add ostream for msgs!
values.insert(values.end(), model_values.begin(), model_values.end());
(*_sample_stream) << values.at(0);
for (size_t i = 1; i < values.size(); ++i) {
(*_sample_stream) << "," << values.at(i);
}
(*_sample_stream) << std::endl;
}
/**
* Print diagnostic params to the diagnostic stream.
*
* @param sample unconstrained sample
* @param sampler sampler
*
* @pre sample and sampler are consistent
* @post none.
* @sideeffects diagnostic_stream_ is appended with csv values of the
* sample's get_sample_params(), the sampler's get_sampler_params(),
* and get_sampler_diagnostics()
*/
void write_diagnostic_params(stan::mcmc::sample& sample,
stan::mcmc::base_mcmc* sampler) {
std::vector<double> values;
sample.get_sample_params(values);
sampler->get_sampler_params(values);
sampler->get_sampler_diagnostics(values);
diagnostic_writer_(values);
}
void output_sample_params(RNG& rng,
stan::mcmc::sample& s,
stan::mcmc::base_mcmc* sampler_ptr,
M& model,
std::vector<Rcpp::NumericVector>& chains,
bool is_warmup,
std::vector<Rcpp::NumericVector>& sampler_params,
std::vector<Rcpp::NumericVector>& iter_params,
std::vector<double>& sum_pars,
double& sum_lp,
const std::vector<size_t>& qoi_idx,
int iter_save_i,
std::ostream* pstream) {
std::vector<double> values;
s.get_sample_params(values);
std::vector<double> sampler_values;
sampler_ptr -> get_sampler_params(sampler_values);
std::vector<double> param_values;
model.write_array(rng,
const_cast<std::vector<double>&>(s.cont_params()),
const_cast<std::vector<int>&>(s.disc_params()),
param_values, true, true, pstream);
// values in param_values are column-major.
size_t z = 0;
if (!is_warmup) {
for (z = 0; z < param_values.size(); z++)
sum_pars[z] += param_values[z];
sum_lp += values.at(index_for_lp_);
}
for (z = 0; z < sample_names_.size(); z++) {
iter_params[z][iter_save_i] = values[z];
}
for (z = 0; z < qoi_idx.size() - 1; ++z) {
chains[z][iter_save_i] = param_values[qoi_idx[z]];
}
chains[z][iter_save_i] = values.at(index_for_lp_);
for (z = 0; z < sampler_values.size(); z++)
sampler_params[z][iter_save_i] = sampler_values[z];
if (!psample_stream_) return;
(*psample_stream_) << values.at(0);
for (size_t i = 1; i < values.size(); ++i) {
(*psample_stream_) << "," << values[i];
}
for (size_t i = 0; i < sampler_values.size(); ++i)
(*psample_stream_) << "," << sampler_values[i];
for (size_t i = 0; i < param_values.size(); ++i)
(*psample_stream_) << "," << param_values[i];
(*psample_stream_) << std::endl;
}
void output_diagnostic_params(stan::mcmc::sample& s,
stan::mcmc::base_mcmc* sampler_ptr) {
if (!pdiagnostic_stream_) return;
std::vector<double> values;
s.get_sample_params(values);
sampler_ptr -> get_sampler_params(values);
sampler_ptr -> get_sampler_diagnostics(values); // FIXME,col/row-major order??
(*pdiagnostic_stream_) << values.at(0);
for (size_t i = 1; i < values.size(); ++i) {
(*pdiagnostic_stream_) << "," << values.at(i);
}
(*pdiagnostic_stream_) << std::endl;
}
void print_diagnostic_params(stan::mcmc::sample& sample,
stan::mcmc::base_mcmc* sampler) {
if(!_diagnostic_stream) return;
std::vector<double> values;
sample.get_sample_params(values);
sampler->get_sampler_params(values);
sampler->get_sampler_diagnostics(values);
(*_diagnostic_stream) << values.at(0);
for (size_t i = 1; i < values.size(); ++i) {
(*_diagnostic_stream) << "," << values.at(i);
}
(*_diagnostic_stream) << std::endl;
}
void write_sample_params(RNG& rng,
stan::mcmc::sample& sample,
stan::mcmc::base_mcmc& sampler,
M& model) {
std::vector<double> values;
sample.get_sample_params(values);
sampler.get_sampler_params(values);
Eigen::VectorXd model_values;
model.write_array(rng,
const_cast<Eigen::VectorXd&>(sample.cont_params()),
model_values,
true, true,
msg_stream_);
for (int i = 0; i < model_values.size(); ++i)
values.push_back(model_values(i));
sample_writer_(values);
}