From e26434979adc33bd949566ba7bf02dff64e80a3e Mon Sep 17 00:00:00 2001
From: Chris Dyer <cdyer@cab.ark.cs.cmu.edu>
Date: Tue, 2 Oct 2012 00:19:43 -0400
Subject: cdec cleanup, remove bayesian stuff, parsing stuff

---
 utils/ccrp_nt.h | 164 --------------------------------------------------------
 1 file changed, 164 deletions(-)
 delete mode 100644 utils/ccrp_nt.h

(limited to 'utils/ccrp_nt.h')

diff --git a/utils/ccrp_nt.h b/utils/ccrp_nt.h
deleted file mode 100644
index 724b11bd..00000000
--- 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
-- 
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