diff options
author | Chris Dyer <cdyer@cs.cmu.edu> | 2012-05-27 15:34:44 -0400 |
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committer | Chris Dyer <cdyer@cs.cmu.edu> | 2012-05-27 15:34:44 -0400 |
commit | bfa5c4866101161c5fb20220d335c80ed075ae0a (patch) | |
tree | e6ce21957a114d8eebcffcfe538f5af273fd9bcd /phrasinator/ccrp_nt.h | |
parent | 425a6300f2ec00a44d3f23cb43c239bec58cf765 (diff) |
clean up
Diffstat (limited to 'phrasinator/ccrp_nt.h')
-rw-r--r-- | phrasinator/ccrp_nt.h | 170 |
1 files changed, 0 insertions, 170 deletions
diff --git a/phrasinator/ccrp_nt.h b/phrasinator/ccrp_nt.h deleted file mode 100644 index 811bce73..00000000 --- a/phrasinator/ccrp_nt.h +++ /dev/null @@ -1,170 +0,0 @@ -#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 (Pitman-Yor parameters) with table tracking. - -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 |