1 files changed, 241 insertions, 0 deletions
diff --git a/utils/ccrp_onetable.h b/utils/ccrp_onetable.h
new file mode 100644
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--- /dev/null
+++ b/utils/ccrp_onetable.h
@@ -0,0 +1,241 @@
+#ifndef _CCRP_ONETABLE_H_
+#define _CCRP_ONETABLE_H_
+
+#include <numeric>
+#include <cassert>
+#include <cmath>
+#include <list>
+#include <iostream>
+#include <tr1/unordered_map>
+#include <boost/functional/hash.hpp>
+#include "sampler.h"
+#include "slice_sampler.h"
+
+// Chinese restaurant process (Pitman-Yor parameters) with one table approximation
+
+template <typename Dish, typename DishHash = boost::hash<Dish> >
+class CCRP_OneTable {
+  typedef std::tr1::unordered_map<Dish, unsigned, DishHash> DishMapType;
+ public:
+  CCRP_OneTable(double disc, double conc) :
+    num_tables_(),
+    num_customers_(),
+    discount_(disc),
+    concentration_(conc),
+    discount_prior_alpha_(std::numeric_limits<double>::quiet_NaN()),
+    discount_prior_beta_(std::numeric_limits<double>::quiet_NaN()),
+    concentration_prior_shape_(std::numeric_limits<double>::quiet_NaN()),
+    concentration_prior_rate_(std::numeric_limits<double>::quiet_NaN()) {}
+
+  CCRP_OneTable(double d_alpha, double d_beta, double c_shape, double c_rate, double d = 0.9, double c = 1.0) :
+    num_tables_(),
+    num_customers_(),
+    discount_(d),
+    concentration_(c),
+    discount_prior_alpha_(d_alpha),
+    discount_prior_beta_(d_beta),
+    concentration_prior_shape_(c_shape),
+    concentration_prior_rate_(c_rate) {}
+
+  double discount() const { return discount_; }
+  double concentration() const { return concentration_; }
+  void set_concentration(double c) { concentration_ = c; }
+  void set_discount(double d) { discount_ = d; }
+
+  bool has_discount_prior() const {
+    return !std::isnan(discount_prior_alpha_);
+  }
+
+  bool has_concentration_prior() const {
+    return !std::isnan(concentration_prior_shape_);
+  }
+
+  void clear() {
+    num_tables_ = 0;
+    num_customers_ = 0;
+    dish_counts_.clear();
+  }
+
+  unsigned num_tables() const {
+    return num_tables_;
+  }
+
+  unsigned num_tables(const Dish& dish) const {
+    const typename DishMapType::const_iterator it = dish_counts_.find(dish);
+    if (it == dish_counts_.end()) return 0;
+    return 1;
+  }
+
+  unsigned num_customers() const {
+    return num_customers_;
+  }
+
+  unsigned num_customers(const Dish& dish) const {
+    const typename DishMapType::const_iterator it = dish_counts_.find(dish);
+    if (it == dish_counts_.end()) return 0;
+    return it->second;
+  }
+
+  // returns +1 or 0 indicating whether a new table was opened
+  int increment(const Dish& dish) {
+    unsigned& dc = dish_counts_[dish];
+    ++dc;
+    ++num_customers_;
+    if (dc == 1) {
+      ++num_tables_;
+      return 1;
+    } else {
+      return 0;
+    }
+  }
+
+  // returns -1 or 0, indicating whether a table was closed
+  int decrement(const Dish& dish) {
+    unsigned& dc = dish_counts_[dish];
+    assert(dc > 0);
+    if (dc == 1) {
+      dish_counts_.erase(dish);
+      --num_tables_;
+      --num_customers_;
+      return -1;
+    } else {
+      assert(dc > 1);
+      --dc;
+      --num_customers_;
+      return 0;
+    }
+  }
+
+  double prob(const Dish& dish, const double& p0) const {
+    const typename DishMapType::const_iterator it = dish_counts_.find(dish);
+    const double r = num_tables_ * discount_ + concentration_;
+    if (it == dish_counts_.end()) {
+      return r * p0 / (num_customers_ + concentration_);
+    } else {
+      return (it->second - discount_ + r * p0) /
+               (num_customers_ + concentration_);
+    }
+  }
+
+  double log_crp_prob() const {
+    return log_crp_prob(discount_, concentration_);
+  }
+
+  static double log_beta_density(const double& x, const double& alpha, const double& beta) {
+    assert(x > 0.0);
+    assert(x < 1.0);
+    assert(alpha > 0.0);
+    assert(beta > 0.0);
+    const double lp = (alpha-1)*log(x)+(beta-1)*log(1-x)+lgamma(alpha+beta)-lgamma(alpha)-lgamma(beta);
+    return lp;
+  }
+
+  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& discount, const double& concentration) const {
+    double lp = 0.0;
+    if (has_discount_prior())
+      lp = log_beta_density(discount, discount_prior_alpha_, discount_prior_beta_);
+    if (has_concentration_prior())
+      lp += log_gamma_density(concentration, concentration_prior_shape_, concentration_prior_rate_);
+    assert(lp <= 0.0);
+    if (num_customers_) {
+      if (discount > 0.0) {
+        const double r = lgamma(1.0 - discount);
+        lp += lgamma(concentration) - lgamma(concentration + num_customers_)
+             + num_tables_ * log(discount) + lgamma(concentration / discount + num_tables_)
+             - lgamma(concentration / discount);
+        assert(std::isfinite(lp));
+        for (typename DishMapType::const_iterator it = dish_counts_.begin();
+             it != dish_counts_.end(); ++it) {
+          const unsigned& cur = it->second;
+          lp += lgamma(cur - discount) - r;
+        }
+      } else {
+        assert(!"not implemented yet");
+      }
+    }
+    assert(std::isfinite(lp));
+    return lp;
+  }
+
+  void resample_hyperparameters(MT19937* rng, const unsigned nloop = 5, const unsigned niterations = 10) {
+    assert(has_discount_prior() || has_concentration_prior());
+    DiscountResampler dr(*this);
+    ConcentrationResampler cr(*this);
+    for (int iter = 0; iter < nloop; ++iter) {
+      if (has_concentration_prior()) {
+        concentration_ = slice_sampler1d(cr, concentration_, *rng, 0.0,
+                               std::numeric_limits<double>::infinity(), 0.0, niterations, 100*niterations);
+      }
+      if (has_discount_prior()) {
+        discount_ = slice_sampler1d(dr, discount_, *rng, std::numeric_limits<double>::min(),
+                               1.0, 0.0, niterations, 100*niterations);
+      }
+    }
+    concentration_ = slice_sampler1d(cr, concentration_, *rng, 0.0,
+                             std::numeric_limits<double>::infinity(), 0.0, niterations, 100*niterations);
+  }
+
+  struct DiscountResampler {
+    DiscountResampler(const CCRP_OneTable& crp) : crp_(crp) {}
+    const CCRP_OneTable& crp_;
+    double operator()(const double& proposed_discount) const {
+      return crp_.log_crp_prob(proposed_discount, crp_.concentration_);
+    }
+  };
+
+  struct ConcentrationResampler {
+    ConcentrationResampler(const CCRP_OneTable& crp) : crp_(crp) {}
+    const CCRP_OneTable& crp_;
+    double operator()(const double& proposed_concentration) const {
+      return crp_.log_crp_prob(crp_.discount_, proposed_concentration);
+    }
+  };
+
+  void Print(std::ostream* out) const {
+    (*out) << "PYP(d=" << discount_ << ",c=" << concentration_ << ") customers=" << num_customers_ << std::endl;
+    for (typename DishMapType::const_iterator it = dish_counts_.begin(); it != dish_counts_.end(); ++it) {
+      (*out) << "  " << it->first << " = " << it->second << std::endl;
+    }
+  }
+
+  typedef typename DishMapType::const_iterator const_iterator;
+  const_iterator begin() const {
+    return dish_counts_.begin();
+  }
+  const_iterator end() const {
+    return dish_counts_.end();
+  }
+
+  unsigned num_tables_;
+  unsigned num_customers_;
+  DishMapType dish_counts_;
+
+  double discount_;
+  double concentration_;
+
+  // optional beta prior on discount_ (NaN if no prior)
+  double discount_prior_alpha_;
+  double discount_prior_beta_;
+
+  // 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_OneTable<T,H>& c) {
+  c.Print(&o);
+  return o;
+}
+
+#endif