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#ifndef _CCRP_NT_H_
#define _CCRP_NT_H_
#include <numeric>
#include <cassert>
#include <cmath>
#include <list>
#include <iostream>
#include <vector>
#include <tr1/unordered_map>
#include <boost/functional/hash.hpp>
#include "sampler.h"
#include "slice_sampler.h"
// Chinese restaurant process (1 parameter)
template <typename Dish, typename DishHash = boost::hash<Dish> >
class CCRP_NoTable {
public:
explicit CCRP_NoTable(double conc) :
num_customers_(),
concentration_(conc),
concentration_prior_shape_(std::numeric_limits<double>::quiet_NaN()),
concentration_prior_rate_(std::numeric_limits<double>::quiet_NaN()) {}
CCRP_NoTable(double c_shape, double c_rate, double c = 10.0) :
num_customers_(),
concentration_(c),
concentration_prior_shape_(c_shape),
concentration_prior_rate_(c_rate) {}
double concentration() const { return concentration_; }
bool has_concentration_prior() const {
return !std::isnan(concentration_prior_shape_);
}
void clear() {
num_customers_ = 0;
custs_.clear();
}
unsigned num_customers() const {
return num_customers_;
}
unsigned num_customers(const Dish& dish) const {
const typename std::tr1::unordered_map<Dish, unsigned, DishHash>::const_iterator it = custs_.find(dish);
if (it == custs_.end()) return 0;
return it->second;
}
int increment(const Dish& dish) {
int table_diff = 0;
if (++custs_[dish] == 1)
table_diff = 1;
++num_customers_;
return table_diff;
}
int decrement(const Dish& dish) {
int table_diff = 0;
int nc = --custs_[dish];
if (nc == 0) {
custs_.erase(dish);
table_diff = -1;
} else if (nc < 0) {
std::cerr << "Dish counts dropped below zero for: " << dish << std::endl;
abort();
}
--num_customers_;
return table_diff;
}
double prob(const Dish& dish, const double& p0) const {
const unsigned at_table = num_customers(dish);
return (at_table + p0 * concentration_) / (num_customers_ + concentration_);
}
double logprob(const Dish& dish, const double& logp0) const {
const unsigned at_table = num_customers(dish);
return log(at_table + exp(logp0 + log(concentration_))) - log(num_customers_ + concentration_);
}
double log_crp_prob() const {
return log_crp_prob(concentration_);
}
static double log_gamma_density(const double& x, const double& shape, const double& rate) {
assert(x >= 0.0);
assert(shape > 0.0);
assert(rate > 0.0);
const double lp = (shape-1)*log(x) - shape*log(rate) - x/rate - lgamma(shape);
return lp;
}
// taken from http://en.wikipedia.org/wiki/Chinese_restaurant_process
// does not include P_0's
double log_crp_prob(const double& concentration) const {
double lp = 0.0;
if (has_concentration_prior())
lp += log_gamma_density(concentration, concentration_prior_shape_, concentration_prior_rate_);
assert(lp <= 0.0);
if (num_customers_) {
lp += lgamma(concentration) - lgamma(concentration + num_customers_) +
custs_.size() * log(concentration);
assert(std::isfinite(lp));
for (typename std::tr1::unordered_map<Dish, unsigned, DishHash>::const_iterator it = custs_.begin();
it != custs_.end(); ++it) {
lp += lgamma(it->second);
}
}
assert(std::isfinite(lp));
return lp;
}
void resample_hyperparameters(MT19937* rng, const unsigned nloop = 5, const unsigned niterations = 10) {
assert(has_concentration_prior());
ConcentrationResampler cr(*this);
for (int iter = 0; iter < nloop; ++iter) {
concentration_ = slice_sampler1d(cr, concentration_, *rng, 0.0,
std::numeric_limits<double>::infinity(), 0.0, niterations, 100*niterations);
}
}
struct ConcentrationResampler {
ConcentrationResampler(const CCRP_NoTable& crp) : crp_(crp) {}
const CCRP_NoTable& crp_;
double operator()(const double& proposed_concentration) const {
return crp_.log_crp_prob(proposed_concentration);
}
};
void Print(std::ostream* out) const {
(*out) << "DP(alpha=" << concentration_ << ") customers=" << num_customers_ << std::endl;
int cc = 0;
for (typename std::tr1::unordered_map<Dish, unsigned, DishHash>::const_iterator it = custs_.begin();
it != custs_.end(); ++it) {
(*out) << " " << it->first << "(" << it->second << " eating)";
++cc;
if (cc > 10) { (*out) << " ..."; break; }
}
(*out) << std::endl;
}
unsigned num_customers_;
std::tr1::unordered_map<Dish, unsigned, DishHash> custs_;
typedef typename std::tr1::unordered_map<Dish, unsigned, DishHash>::const_iterator const_iterator;
const_iterator begin() const {
return custs_.begin();
}
const_iterator end() const {
return custs_.end();
}
double concentration_;
// optional gamma prior on concentration_ (NaN if no prior)
double concentration_prior_shape_;
double concentration_prior_rate_;
};
template <typename T,typename H>
std::ostream& operator<<(std::ostream& o, const CCRP_NoTable<T,H>& c) {
c.Print(&o);
return o;
}
#endif
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