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1 files changed, 155 insertions, 0 deletions

diff --git a/gi/pf/conditional_pseg.h b/gi/pf/conditional_pseg.h
new file mode 100644
index 00000000..edcdc813
--- /dev/null
+++ b/gi/pf/conditional_pseg.h
@@ -0,0 +1,155 @@
+#ifndef _CONDITIONAL_PSEG_H_
+#define _CONDITIONAL_PSEG_H_
+
+#include <vector>
+#include <tr1/unordered_map>
+#include <boost/functional/hash.hpp>
+#include <iostream>
+
+#include "prob.h"
+#include "ccrp_nt.h"
+#include "trule.h"
+#include "base_measures.h"
+#include "tdict.h"
+
+template <typename ConditionalBaseMeasure>
+struct ConditionalTranslationModel {
+  explicit ConditionalTranslationModel(ConditionalBaseMeasure& rcp0) :
+    rp0(rcp0) {}
+
+  void Summary() const {
+    std::cerr << "Number of conditioning contexts: " << r.size() << std::endl;
+    for (RuleModelHash::const_iterator it = r.begin(); it != r.end(); ++it) {
+      std::cerr << TD::GetString(it->first) << "   \t(\\alpha = " << it->second.concentration() << ") --------------------------" << std::endl;
+      for (CCRP_NoTable<TRule>::const_iterator i2 = it->second.begin(); i2 != it->second.end(); ++i2)
+        std::cerr << "   " << i2->second << '\t' << i2->first << std::endl;
+    }
+  }
+
+  void ResampleHyperparameters(MT19937* rng) {
+    for (RuleModelHash::iterator it = r.begin(); it != r.end(); ++it)
+      it->second.resample_hyperparameters(rng);
+  } 
+
+  int DecrementRule(const TRule& rule) {
+    RuleModelHash::iterator it = r.find(rule.f_);
+    assert(it != r.end());    
+    int count = it->second.decrement(rule);
+    if (count) {
+      if (it->second.num_customers() == 0) r.erase(it);
+    }
+    return count;
+  }
+
+  int IncrementRule(const TRule& rule) {
+    RuleModelHash::iterator it = r.find(rule.f_);
+    if (it == r.end()) {
+      it = r.insert(make_pair(rule.f_, CCRP_NoTable<TRule>(1.0, 1.0, 8.0))).first;
+    } 
+    int count = it->second.increment(rule);
+    return count;
+  }
+
+  void IncrementRules(const std::vector<TRulePtr>& rules) {
+    for (int i = 0; i < rules.size(); ++i)
+      IncrementRule(*rules[i]);
+  }
+
+  void DecrementRules(const std::vector<TRulePtr>& rules) {
+    for (int i = 0; i < rules.size(); ++i)
+      DecrementRule(*rules[i]);
+  }
+
+  prob_t RuleProbability(const TRule& rule) const {
+    prob_t p;
+    RuleModelHash::const_iterator it = r.find(rule.f_);
+    if (it == r.end()) {
+      p.logeq(log(rp0(rule)));
+    } else {
+      p.logeq(it->second.logprob(rule, log(rp0(rule))));
+    }
+    return p;
+  }
+
+  prob_t Likelihood() const {
+    prob_t p = prob_t::One();
+    for (RuleModelHash::const_iterator it = r.begin(); it != r.end(); ++it) {
+      prob_t q; q.logeq(it->second.log_crp_prob());
+      p *= q;
+      for (CCRP_NoTable<TRule>::const_iterator i2 = it->second.begin(); i2 != it->second.end(); ++i2)
+        p *= rp0(i2->first);
+    }
+    return p;
+  }
+
+  const ConditionalBaseMeasure& rp0;
+  typedef std::tr1::unordered_map<std::vector<WordID>,
+                                  CCRP_NoTable<TRule>,
+                                  boost::hash<std::vector<WordID> > > RuleModelHash;
+  RuleModelHash r;
+};
+
+template <typename ConditionalBaseMeasure>
+struct ConditionalParallelSegementationModel {
+  explicit ConditionalParallelSegementationModel(ConditionalBaseMeasure& rcp0) :
+    tmodel(rcp0), base(prob_t::One()), aligns(1,1) {}
+
+  ConditionalTranslationModel<ConditionalBaseMeasure> tmodel;
+
+  void DecrementRule(const TRule& rule) {
+    tmodel.DecrementRule(rule);
+  }
+
+  void IncrementRule(const TRule& rule) {
+    tmodel.IncrementRule(rule);
+  }
+
+  void IncrementRulesAndAlignments(const std::vector<TRulePtr>& rules) {
+    tmodel.IncrementRules(rules);
+    for (int i = 0; i < rules.size(); ++i) {
+      IncrementAlign(rules[i]->f_.size());
+    }
+  }
+
+  void DecrementRulesAndAlignments(const std::vector<TRulePtr>& rules) {
+    tmodel.DecrementRules(rules);
+    for (int i = 0; i < rules.size(); ++i) {
+      DecrementAlign(rules[i]->f_.size());
+    }
+  }
+
+  prob_t RuleProbability(const TRule& rule) const {
+    return tmodel.RuleProbability(rule);
+  }
+
+  void IncrementAlign(unsigned span) {
+    if (aligns.increment(span)) {
+      // TODO
+    }
+  }
+
+  void DecrementAlign(unsigned span) {
+    if (aligns.decrement(span)) {
+      // TODO
+    }
+  }
+
+  prob_t AlignProbability(unsigned span) const {
+    prob_t p;
+    p.logeq(aligns.logprob(span, log_poisson(span, 1.0)));
+    return p;
+  }
+
+  prob_t Likelihood() const {
+    prob_t p; p.logeq(aligns.log_crp_prob());
+    p *= base;
+    p *= tmodel.Likelihood();
+    return p;
+  }
+
+  prob_t base;
+  CCRP_NoTable<unsigned> aligns;
+};
+
+#endif
+