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authorKenneth Heafield <github@kheafield.com>2012-10-22 12:07:20 +0100
committerKenneth Heafield <github@kheafield.com>2012-10-22 12:07:20 +0100
commit5f98fe5c4f2a2090eeb9d30c030305a70a8347d1 (patch)
tree9b6002f850e6dea1e3400c6b19bb31a9cdf3067f /utils/ccrp_nt.h
parentcf9994131993b40be62e90e213b1e11e6b550143 (diff)
parent21825a09d97c2e0afd20512f306fb25fed55e529 (diff)
Merge remote branch 'upstream/master'
Conflicts: Jamroot bjam decoder/Jamfile decoder/cdec.cc dpmert/Jamfile jam-files/sanity.jam klm/lm/Jamfile klm/util/Jamfile mira/Jamfile
Diffstat (limited to 'utils/ccrp_nt.h')
-rw-r--r--utils/ccrp_nt.h164
1 files changed, 0 insertions, 164 deletions
diff --git a/utils/ccrp_nt.h b/utils/ccrp_nt.h
deleted file mode 100644
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--- a/utils/ccrp_nt.h
+++ /dev/null
@@ -1,164 +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"
-#include "m.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_(),
- alpha_(conc),
- alpha_prior_shape_(std::numeric_limits<double>::quiet_NaN()),
- alpha_prior_rate_(std::numeric_limits<double>::quiet_NaN()) {}
-
- CCRP_NoTable(double c_shape, double c_rate, double c = 10.0) :
- num_customers_(),
- alpha_(c),
- alpha_prior_shape_(c_shape),
- alpha_prior_rate_(c_rate) {}
-
- double alpha() const { return alpha_; }
- void set_alpha(const double& alpha) { alpha_ = alpha; assert(alpha_ > 0.0); }
-
- bool has_alpha_prior() const {
- return !std::isnan(alpha_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;
- }
-
- template <typename F>
- F prob(const Dish& dish, const F& p0) const {
- const unsigned at_table = num_customers(dish);
- return (F(at_table) + p0 * F(alpha_)) / F(num_customers_ + alpha_);
- }
-
- double logprob(const Dish& dish, const double& logp0) const {
- const unsigned at_table = num_customers(dish);
- return log(at_table + exp(logp0 + log(alpha_))) - log(num_customers_ + alpha_);
- }
-
- double log_crp_prob() const {
- return log_crp_prob(alpha_);
- }
-
- // taken from http://en.wikipedia.org/wiki/Chinese_restaurant_process
- // does not include P_0's
- double log_crp_prob(const double& alpha) const {
- double lp = 0.0;
- if (has_alpha_prior())
- lp += Md::log_gamma_density(alpha, alpha_prior_shape_, alpha_prior_rate_);
- assert(lp <= 0.0);
- if (num_customers_) {
- lp += lgamma(alpha) - lgamma(alpha + num_customers_) +
- custs_.size() * log(alpha);
- 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_alpha_prior());
- ConcentrationResampler cr(*this);
- for (unsigned iter = 0; iter < nloop; ++iter) {
- alpha_ = slice_sampler1d(cr, alpha_, *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_alpha) const {
- return crp_.log_crp_prob(proposed_alpha);
- }
- };
-
- void Print(std::ostream* out) const {
- (*out) << "DP(alpha=" << alpha_ << ") 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 alpha_;
-
- // optional gamma prior on alpha_ (NaN if no prior)
- double alpha_prior_shape_;
- double alpha_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