From 0acc92a0eecf04a2c429f6f7685bfcaa68c7ec3a Mon Sep 17 00:00:00 2001
From: Chris Dyer <cdyer@cs.cmu.edu>
Date: Tue, 11 Oct 2011 12:06:32 +0100
Subject: check in some experimental particle filtering code, some gitignore
fixes
---
utils/ccrp_nt.h | 169 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++
1 file changed, 169 insertions(+)
create mode 100644 utils/ccrp_nt.h
(limited to 'utils/ccrp_nt.h')
diff --git a/utils/ccrp_nt.h b/utils/ccrp_nt.h
new file mode 100644
index 00000000..63b6f4c2
--- /dev/null
+++ b/utils/ccrp_nt.h
@@ -0,0 +1,169 @@
+#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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