summaryrefslogtreecommitdiff
path: root/gi/pyp-topics/src/contexts_corpus.cc
blob: 26d5718abb1d6147df1bbbb440f3eea22b2f4c3f (plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
#include <sstream>
#include <iostream>
#include <set>

#include "contexts_corpus.hh"
#include "gzstream.hh"
#include "contexts_lexer.h"

#include <boost/tuple/tuple.hpp>


using namespace std;

//////////////////////////////////////////////////
// ContextsCorpus
//////////////////////////////////////////////////

void read_callback(const ContextsLexer::PhraseContextsType& new_contexts, void* extra) {
  assert(new_contexts.contexts.size() == new_contexts.counts.size());

  boost::tuple<ContextsCorpus*, BackoffGenerator*, map<string,int>* >* extra_pair
    = static_cast< boost::tuple<ContextsCorpus*, BackoffGenerator*, map<string,int>* >* >(extra);

  ContextsCorpus* corpus_ptr = extra_pair->get<0>();
  BackoffGenerator* backoff_gen = extra_pair->get<1>();
  //map<string,int>* counts = extra_pair->get<2>();

  Document* doc(new Document());

  //cout << "READ: " << new_contexts.phrase << "\t";
  for (int i=0; i < new_contexts.counts.size(); ++i) {
    int cache_word_count = corpus_ptr->m_dict.max();

    //string context_str = corpus_ptr->m_dict.toString(new_contexts.contexts[i]);
    int context_index = new_contexts.counts.at(i).first;
    string context_str = corpus_ptr->m_dict.toString(new_contexts.contexts[context_index]);

    // filter out singleton contexts
    //if (!counts->empty()) {
    //  map<string,int>::const_iterator find_it = counts->find(context_str);
    //  if (find_it == counts->end() || find_it->second < 2)
    //    continue;
    //}

    WordID id = corpus_ptr->m_dict.Convert(context_str);
    if (cache_word_count != corpus_ptr->m_dict.max()) {
      corpus_ptr->m_backoff->terms_at_level(0)++;
      corpus_ptr->m_num_types++;
    }

    //int count = new_contexts.counts[i];
    int count = new_contexts.counts.at(i).second;
    for (int j=0; j<count; ++j)
      doc->push_back(id);
    corpus_ptr->m_num_terms += count;

    // generate the backoff map
    if (backoff_gen) {
      int order = 1;
      WordID backoff_id = id;
      //ContextsLexer::Context backedoff_context = new_contexts.contexts[i];
      ContextsLexer::Context backedoff_context = new_contexts.contexts[context_index];
      while (true) {
        if (!corpus_ptr->m_backoff->has_backoff(backoff_id)) {
          //cerr << "Backing off from " << corpus_ptr->m_dict.Convert(backoff_id) << " to ";
          backedoff_context = (*backoff_gen)(backedoff_context);

          if (backedoff_context.empty()) {
            //cerr << "Nothing." << endl;
            (*corpus_ptr->m_backoff)[backoff_id] = -1;
            break;
          }

          if (++order > corpus_ptr->m_backoff->order())
            corpus_ptr->m_backoff->order(order);

          int cache_word_count = corpus_ptr->m_dict.max();
          int new_backoff_id = corpus_ptr->m_dict.Convert(backedoff_context);
          if (cache_word_count != corpus_ptr->m_dict.max())
            corpus_ptr->m_backoff->terms_at_level(order-1)++;

          //cerr << corpus_ptr->m_dict.Convert(new_backoff_id) << " ." << endl;

          backoff_id = ((*corpus_ptr->m_backoff)[backoff_id] = new_backoff_id);
        }
        else break;
      }
    }
    //cout << context_str << " (" << id << ") ||| C=" << count << " ||| ";
  }
  //cout << endl;

  //if (!doc->empty()) {
    corpus_ptr->m_documents.push_back(doc);
    corpus_ptr->m_keys.push_back(new_contexts.phrase);
  //}
}

void filter_callback(const ContextsLexer::PhraseContextsType& new_contexts, void* extra) {
  assert(new_contexts.contexts.size() == new_contexts.counts.size());

  map<string,int>* context_counts = (static_cast<map<string,int>*>(extra));

  for (int i=0; i < new_contexts.counts.size(); ++i) {
    int context_index = new_contexts.counts.at(i).first;
    int count = new_contexts.counts.at(i).second;
    //int count = new_contexts.counts[i];
    pair<map<string,int>::iterator,bool> result 
      = context_counts->insert(make_pair(Dict::toString(new_contexts.contexts[context_index]),count));
      //= context_counts->insert(make_pair(Dict::toString(new_contexts.contexts[i]),count));
    if (!result.second)
      result.first->second += count;
  }
}


unsigned ContextsCorpus::read_contexts(const string &filename, 
                                       BackoffGenerator* backoff_gen_ptr,
                                       bool /*filter_singeltons*/) {
  map<string,int> counts;
  //if (filter_singeltons) 
  {
  //  cerr << "--- Filtering singleton contexts ---" << endl;

    igzstream in(filename.c_str());
    ContextsLexer::ReadContexts(&in, filter_callback, &counts);
  }

  m_num_terms = 0;
  m_num_types = 0;

  igzstream in(filename.c_str());
  boost::tuple<ContextsCorpus*, BackoffGenerator*, map<string,int>* > extra_pair(this,backoff_gen_ptr,&counts);
  ContextsLexer::ReadContexts(&in, read_callback, &extra_pair);

  //m_num_types = m_dict.max();

  cerr << "Read backoff with order " << m_backoff->order() << "\n";
  for (int o=0; o<m_backoff->order(); o++)
    cerr << "  Terms at " << o << " = " << m_backoff->terms_at_level(o) << endl;
  //cerr << endl;

  int i=0; double av_freq=0;
  for (map<string,int>::const_iterator it=counts.begin(); it != counts.end(); ++it, ++i) {
    WordID id = m_dict.Convert(it->first);
    m_context_counts[id] = it->second;
    av_freq += it->second;
  }
  cerr << "  Average term frequency = " << av_freq / (double) i << endl;

  return m_documents.size();
}