cdec cleanup, remove bayesian stuff, parsing stuff

1 files changed, 0 insertions, 370 deletions

diff --git a/utils/mfcr.h b/utils/mfcr.h
deleted file mode 100644
index 4aacb567..00000000
--- a/utils/mfcr.h
+++ /dev/null
@@ -1,370 +0,0 @@
-#ifndef _MFCR_H_
-#define _MFCR_H_
-
-#include <algorithm>
-#include <numeric>
-#include <cassert>
-#include <cmath>
-#include <list>
-#include <iostream>
-#include <vector>
-#include <iterator>
-#include <tr1/unordered_map>
-#include <boost/functional/hash.hpp>
-#include "sampler.h"
-#include "slice_sampler.h"
-#include "m.h"
-
-struct TableCount {
-  TableCount() : count(), floor() {}
-  TableCount(int c, int f) : count(c), floor(f) {
-    assert(f >= 0);
-  }
-  int count;               // count or delta (may be 0, <0, or >0)
-  unsigned char floor;     // from which floor?
-};
- 
-std::ostream& operator<<(std::ostream& o, const TableCount& tc) {
-  return o << "[c=" << tc.count << " floor=" << static_cast<unsigned int>(tc.floor) << ']';
-}
-
-// Multi-Floor Chinese Restaurant as proposed by Wood & Teh (AISTATS, 2009) to simulate
-// graphical Pitman-Yor processes.
-// http://jmlr.csail.mit.edu/proceedings/papers/v5/wood09a/wood09a.pdf
-//
-// Implementation is based on Blunsom, Cohn, Goldwater, & Johnson (ACL 2009) and code
-// referenced therein.
-// http://www.aclweb.org/anthology/P/P09/P09-2085.pdf
-//
-template <unsigned Floors, typename Dish, typename DishHash = boost::hash<Dish> >
-class MFCR {
- public:
-
-  MFCR(double d, double strength) :
-    num_tables_(),
-    num_customers_(),
-    discount_(d),
-    strength_(strength),
-    discount_prior_strength_(std::numeric_limits<double>::quiet_NaN()),
-    discount_prior_beta_(std::numeric_limits<double>::quiet_NaN()),
-    strength_prior_shape_(std::numeric_limits<double>::quiet_NaN()),
-    strength_prior_rate_(std::numeric_limits<double>::quiet_NaN()) { check_hyperparameters(); }
-
-  MFCR(double discount_strength, double discount_beta, double strength_shape, double strength_rate, double d = 0.9, double strength = 10.0) :
-    num_tables_(),
-    num_customers_(),
-    discount_(d),
-    strength_(strength),
-    discount_prior_strength_(discount_strength),
-    discount_prior_beta_(discount_beta),
-    strength_prior_shape_(strength_shape),
-    strength_prior_rate_(strength_rate) { check_hyperparameters(); }
-
-  void check_hyperparameters() {
-    if (discount_ < 0.0 || discount_ >= 1.0) {
-      std::cerr << "Bad discount: " << discount_ << std::endl;
-      abort();
-    }
-    if (strength_ <= -discount_) {
-      std::cerr << "Bad strength: " << strength_ << " (discount=" << discount_ << ")" << std::endl;
-      abort();
-    }
-  }
-
-  double discount() const { return discount_; }
-  double strength() const { return strength_; }
-  void set_hyperparameters(double d, double s) {
-    discount_ = d; strength_ = s;
-    check_hyperparameters();
-  }
-  void set_discount(double d) { discount_ = d; check_hyperparameters(); }
-  void set_strength(double a) { strength_ = a; check_hyperparameters(); }
-
-  bool has_discount_prior() const {
-    return !std::isnan(discount_prior_strength_);
-  }
-
-  bool has_strength_prior() const {
-    return !std::isnan(strength_prior_shape_);
-  }
-
-  void clear() {
-    num_tables_ = 0;
-    num_customers_ = 0;
-    dish_locs_.clear();
-  }
-
-  unsigned num_tables() const {
-    return num_tables_;
-  }
-
-  unsigned num_tables(const Dish& dish) const {
-    const typename std::tr1::unordered_map<Dish, DishLocations, DishHash>::const_iterator it = dish_locs_.find(dish);
-    if (it == dish_locs_.end()) return 0;
-    return it->second.table_counts_.size();
-  }
-
-  // this is not terribly efficient but it should not typically be necessary to execute this query
-  unsigned num_tables(const Dish& dish, const unsigned floor) const {
-    const typename std::tr1::unordered_map<Dish, DishLocations, DishHash>::const_iterator it = dish_locs_.find(dish);
-    if (it == dish_locs_.end()) return 0;
-    unsigned c = 0;
-    for (typename std::list<TableCount>::const_iterator i = it->second.table_counts_.begin();
-         i != it->second.table_counts_.end(); ++i) {
-      if (i->floor == floor) ++c;
-    }
-    return c;
-  }
-
-  unsigned num_customers() const {
-    return num_customers_;
-  }
-
-  unsigned num_customers(const Dish& dish) const {
-    const typename std::tr1::unordered_map<Dish, DishLocations, DishHash>::const_iterator it = dish_locs_.find(dish);
-    if (it == dish_locs_.end()) return 0;
-    return it->total_dish_count_;
-  }
-
-  // returns (delta, floor) indicating whether a new table (delta) was opened and on which floor
-  template <class InputIterator, class InputIterator2>
-  TableCount increment(const Dish& dish, InputIterator p0s, InputIterator2 lambdas, MT19937* rng) {
-    DishLocations& loc = dish_locs_[dish];
-    // marg_p0 = marginal probability of opening a new table on any floor with label dish
-    typedef typename std::iterator_traits<InputIterator>::value_type F;
-    const F marg_p0 = std::inner_product(p0s, p0s + Floors, lambdas, F(0.0));
-    assert(marg_p0 <= F(1.0001));
-    int floor = -1;
-    bool share_table = false;
-    if (loc.total_dish_count_) {
-      const F p_empty = F(strength_ + num_tables_ * discount_) * marg_p0;
-      const F p_share = F(loc.total_dish_count_ - loc.table_counts_.size() * discount_);
-      share_table = rng->SelectSample(p_empty, p_share);
-    }
-    if (share_table) {
-      // this can be done with doubles since P0 (which may be tiny) is not involved
-      double r = rng->next() * (loc.total_dish_count_ - loc.table_counts_.size() * discount_);
-      for (typename std::list<TableCount>::iterator ti = loc.table_counts_.begin();
-           ti != loc.table_counts_.end(); ++ti) {
-        r -= ti->count - discount_;
-        if (r <= 0.0) {
-          ++ti->count;
-          floor = ti->floor;
-          break;
-        }
-      }
-      if (r > 0.0) {
-        std::cerr << "Serious error: r=" << r << std::endl;
-        Print(&std::cerr);
-        assert(r <= 0.0);
-      }
-    } else { // sit at currently empty table -- must sample what floor
-      if (Floors == 1) {
-        floor = 0;
-      } else {
-        F r = F(rng->next()) * marg_p0;
-        for (unsigned i = 0; i < Floors; ++i) {
-          r -= (*p0s) * (*lambdas);
-          ++p0s;
-          ++lambdas;
-          if (r <= F(0.0)) {
-            floor = i;
-            break;
-          }
-        }
-      }
-      assert(floor >= 0);
-      loc.table_counts_.push_back(TableCount(1, floor));
-      ++num_tables_;
-    }
-    ++loc.total_dish_count_;
-    ++num_customers_;
-    return (share_table ? TableCount(0, floor) : TableCount(1, floor));
-  }
-
-  // returns first = -1 or 0, indicating whether a table was closed, and on what floor (second)
-  TableCount decrement(const Dish& dish, MT19937* rng) {
-    DishLocations& loc = dish_locs_[dish];
-    assert(loc.total_dish_count_);
-    int floor = -1;
-    int delta = 0;
-    if (loc.total_dish_count_ == 1) {
-      floor = loc.table_counts_.front().floor;
-      dish_locs_.erase(dish);
-      --num_tables_;
-      --num_customers_;
-      delta = -1;
-    } else {
-      // sample customer to remove UNIFORMLY. that is, do NOT use the d
-      // here. if you do, it will introduce (unwanted) bias!
-      double r = rng->next() * loc.total_dish_count_;
-      --loc.total_dish_count_;
-      --num_customers_;
-      for (typename std::list<TableCount>::iterator ti = loc.table_counts_.begin();
-           ti != loc.table_counts_.end(); ++ti) {
-        r -= ti->count;
-        if (r <= 0.0) {
-          floor = ti->floor;
-          if ((--ti->count) == 0) {
-            --num_tables_;
-            delta = -1;
-            loc.table_counts_.erase(ti);
-          }
-          break;
-        }
-      }
-      if (r > 0.0) {
-        std::cerr << "Serious error: r=" << r << std::endl;
-        Print(&std::cerr);
-        assert(r <= 0.0);
-      }
-    }
-    return TableCount(delta, floor);
-  }
-
-  template <class InputIterator, class InputIterator2>
-  typename std::iterator_traits<InputIterator>::value_type prob(const Dish& dish, InputIterator p0s, InputIterator2 lambdas) const {
-    typedef typename std::iterator_traits<InputIterator>::value_type F;
-    const F marg_p0 = std::inner_product(p0s, p0s + Floors, lambdas, F(0.0));
-    assert(marg_p0 <= F(1.0001));
-    const typename std::tr1::unordered_map<Dish, DishLocations, DishHash>::const_iterator it = dish_locs_.find(dish);
-    const F r = F(num_tables_ * discount_ + strength_);
-    if (it == dish_locs_.end()) {
-      return r * marg_p0 / F(num_customers_ + strength_);
-    } else {
-      return (F(it->second.total_dish_count_ - discount_ * it->second.table_counts_.size()) + F(r * marg_p0)) /
-               F(num_customers_ + strength_);
-    }
-  }
-
-  double log_crp_prob() const {
-    return log_crp_prob(discount_, strength_);
-  }
-
-  // taken from http://en.wikipedia.org/wiki/Chinese_restaurant_process
-  // does not include draws from G_w's
-  double log_crp_prob(const double& discount, const double& strength) const {
-    double lp = 0.0;
-    if (has_discount_prior())
-      lp = Md::log_beta_density(discount, discount_prior_strength_, discount_prior_beta_);
-    if (has_strength_prior())
-      lp += Md::log_gamma_density(strength + discount, strength_prior_shape_, strength_prior_rate_);
-    assert(lp <= 0.0);
-    if (num_customers_) {
-      if (discount > 0.0) {
-        const double r = lgamma(1.0 - discount);
-        if (strength)
-          lp += lgamma(strength) - lgamma(strength / discount);
-        lp += - lgamma(strength + num_customers_)
-             + num_tables_ * log(discount) + lgamma(strength / discount + num_tables_);
-        assert(std::isfinite(lp));
-        for (typename std::tr1::unordered_map<Dish, DishLocations, DishHash>::const_iterator it = dish_locs_.begin();
-             it != dish_locs_.end(); ++it) {
-          const DishLocations& cur = it->second;
-          for (std::list<TableCount>::const_iterator ti = cur.table_counts_.begin(); ti != cur.table_counts_.end(); ++ti) {
-            lp += lgamma(ti->count - discount) - r;
-          }
-        }
-      } else if (!discount) { // discount == 0.0
-        lp += lgamma(strength) + num_tables_ * log(strength) - lgamma(strength + num_tables_);
-        assert(std::isfinite(lp));
-        for (typename std::tr1::unordered_map<Dish, DishLocations, DishHash>::const_iterator it = dish_locs_.begin();
-             it != dish_locs_.end(); ++it) {
-          const DishLocations& cur = it->second;
-          lp += lgamma(cur.table_counts_.size());
-        }
-      } else {
-        assert(!"discount less than 0 detected!");
-      }
-    }
-    assert(std::isfinite(lp));
-    return lp;
-  }
-
-  void resample_hyperparameters(MT19937* rng, const unsigned nloop = 5, const unsigned niterations = 10) {
-    assert(has_discount_prior() || has_strength_prior());
-    DiscountResampler dr(*this);
-    StrengthResampler sr(*this);
-    for (int iter = 0; iter < nloop; ++iter) {
-      if (has_strength_prior()) {
-        strength_ = slice_sampler1d(sr, strength_, *rng, -discount_,
-                               std::numeric_limits<double>::infinity(), 0.0, niterations, 100*niterations);
-      }
-      if (has_discount_prior()) {
-        double min_discount = std::numeric_limits<double>::min();
-        if (strength_ < 0.0) min_discount -= strength_;
-        discount_ = slice_sampler1d(dr, discount_, *rng, min_discount,
-                               1.0, 0.0, niterations, 100*niterations);
-      }
-    }
-    strength_ = slice_sampler1d(sr, strength_, *rng, -discount_,
-                             std::numeric_limits<double>::infinity(), 0.0, niterations, 100*niterations);
-  }
-
-  struct DiscountResampler {
-    DiscountResampler(const MFCR& crp) : crp_(crp) {}
-    const MFCR& crp_;
-    double operator()(const double& proposed_d) const {
-      return crp_.log_crp_prob(proposed_d, crp_.strength_);
-    }
-  };
-
-  struct StrengthResampler {
-    StrengthResampler(const MFCR& crp) : crp_(crp) {}
-    const MFCR& crp_;
-    double operator()(const double& proposediscount_strength) const {
-      return crp_.log_crp_prob(crp_.discount_, proposediscount_strength);
-    }
-  };
-
-  struct DishLocations {
-    DishLocations() : total_dish_count_() {}
-    unsigned total_dish_count_;          // customers at all tables with this dish
-    std::list<TableCount> table_counts_; // list<> gives O(1) deletion and insertion, which we want
-                                         // .size() is the number of tables for this dish
-  };
-
-  void Print(std::ostream* out) const {
-    (*out) << "MFCR<" << Floors << ">(d=" << discount_ << ",strength=" << strength_ << ") customers=" << num_customers_ << std::endl;
-    for (typename std::tr1::unordered_map<Dish, DishLocations, DishHash>::const_iterator it = dish_locs_.begin();
-         it != dish_locs_.end(); ++it) {
-      (*out) << it->first << " (" << it->second.total_dish_count_ << " on " << it->second.table_counts_.size() << " tables): ";
-      for (typename std::list<TableCount>::const_iterator i = it->second.table_counts_.begin();
-           i != it->second.table_counts_.end(); ++i) {
-        (*out) << " " << *i;
-      }
-      (*out) << std::endl;
-    }
-  }
-
-  typedef typename std::tr1::unordered_map<Dish, DishLocations, DishHash>::const_iterator const_iterator;
-  const_iterator begin() const {
-    return dish_locs_.begin();
-  }
-  const_iterator end() const {
-    return dish_locs_.end();
-  }
-
-  unsigned num_tables_;
-  unsigned num_customers_;
-  std::tr1::unordered_map<Dish, DishLocations, DishHash> dish_locs_;
-
-  double discount_;
-  double strength_;
-
-  // optional beta prior on discount_ (NaN if no prior)
-  double discount_prior_strength_;
-  double discount_prior_beta_;
-
-  // optional gamma prior on strength_ (NaN if no prior)
-  double strength_prior_shape_;
-  double strength_prior_rate_;
-};
-
-template <unsigned N,typename T,typename H>
-std::ostream& operator<<(std::ostream& o, const MFCR<N,T,H>& c) {
-  c.Print(&o);
-  return o;
-}
-
-#endif