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#include "precomputation.h"
#include <iostream>
#include <queue>
#include "data_array.h"
#include "suffix_array.h"
#include "time_util.h"
#include "vocabulary.h"
using namespace std;
namespace extractor {
Precomputation::Precomputation(
shared_ptr<Vocabulary> vocabulary, shared_ptr<SuffixArray> suffix_array,
int num_frequent_patterns, int num_super_frequent_patterns,
int max_rule_span, int max_rule_symbols, int min_gap_size,
int max_frequent_phrase_len, int min_frequency) {
Clock::time_point start_time = Clock::now();
shared_ptr<DataArray> data_array = suffix_array->GetData();
vector<int> data = data_array->GetData();
vector<vector<int>> frequent_patterns = FindMostFrequentPatterns(
suffix_array, data, num_frequent_patterns, max_frequent_phrase_len,
min_frequency);
Clock::time_point end_time = Clock::now();
cerr << "Finding most frequent patterns took "
<< GetDuration(start_time, end_time) << " seconds..." << endl;
vector<vector<int>> pattern_annotations(frequent_patterns.size());
unordered_map<vector<int>, int, VectorHash> frequent_patterns_index;
for (size_t i = 0; i < frequent_patterns.size(); ++i) {
frequent_patterns_index[frequent_patterns[i]] = i;
pattern_annotations[i] = AnnotatePattern(vocabulary, data_array,
frequent_patterns[i]);
}
start_time = Clock::now();
vector<tuple<int, int, int>> matchings;
vector<vector<int>> annotations;
for (size_t i = 0; i < data.size(); ++i) {
// If the sentence is over, add all the discontiguous frequent patterns to
// the index.
if (data[i] == DataArray::END_OF_LINE) {
UpdateIndex(matchings, annotations, max_rule_span, min_gap_size,
max_rule_symbols);
matchings.clear();
annotations.clear();
continue;
}
// Find all the contiguous frequent patterns starting at position i.
vector<int> pattern;
for (int j = 1; j <= max_frequent_phrase_len && i + j <= data.size(); ++j) {
pattern.push_back(data[i + j - 1]);
auto it = frequent_patterns_index.find(pattern);
if (it == frequent_patterns_index.end()) {
// If the current pattern is not frequent, any longer pattern having the
// current pattern as prefix will not be frequent.
break;
}
int is_super_frequent = it->second < num_super_frequent_patterns;
matchings.push_back(make_tuple(i, j, is_super_frequent));
annotations.push_back(pattern_annotations[it->second]);
}
}
end_time = Clock::now();
cerr << "Constructing collocations index took "
<< GetDuration(start_time, end_time) << " seconds..." << endl;
}
Precomputation::Precomputation() {}
Precomputation::~Precomputation() {}
vector<vector<int>> Precomputation::FindMostFrequentPatterns(
shared_ptr<SuffixArray> suffix_array, const vector<int>& data,
int num_frequent_patterns, int max_frequent_phrase_len, int min_frequency) {
vector<int> lcp = suffix_array->BuildLCPArray();
vector<int> run_start(max_frequent_phrase_len);
// Find all the patterns occurring at least min_frequency times.
priority_queue<pair<int, pair<int, int>>> heap;
for (size_t i = 1; i < lcp.size(); ++i) {
for (int len = lcp[i]; len < max_frequent_phrase_len; ++len) {
int frequency = i - run_start[len];
int start = suffix_array->GetSuffix(run_start[len]);
if (frequency >= min_frequency && start + len <= data.size()) {
heap.push(make_pair(frequency, make_pair(start, len + 1)));
}
run_start[len] = i;
}
}
// Extract the most frequent patterns.
vector<vector<int>> frequent_patterns;
while (frequent_patterns.size() < num_frequent_patterns && !heap.empty()) {
int start = heap.top().second.first;
int len = heap.top().second.second;
heap.pop();
vector<int> pattern(data.begin() + start, data.begin() + start + len);
if (find(pattern.begin(), pattern.end(), DataArray::END_OF_LINE) ==
pattern.end()) {
frequent_patterns.push_back(pattern);
}
}
return frequent_patterns;
}
vector<int> Precomputation::AnnotatePattern(
shared_ptr<Vocabulary> vocabulary, shared_ptr<DataArray> data_array,
const vector<int>& pattern) const {
vector<int> annotation;
for (int word_id: pattern) {
annotation.push_back(vocabulary->GetTerminalIndex(
data_array->GetWord(word_id)));
}
return annotation;
}
void Precomputation::UpdateIndex(
const vector<tuple<int, int, int>>& matchings,
const vector<vector<int>>& annotations,
int max_rule_span, int min_gap_size, int max_rule_symbols) {
// Select the leftmost subpattern.
for (size_t i = 0; i < matchings.size(); ++i) {
int start1, size1, is_super1;
tie(start1, size1, is_super1) = matchings[i];
// Select the second (middle) subpattern
for (size_t j = i + 1; j < matchings.size(); ++j) {
int start2, size2, is_super2;
tie(start2, size2, is_super2) = matchings[j];
if (start2 - start1 >= max_rule_span) {
break;
}
if (start2 - start1 - size1 >= min_gap_size
&& start2 + size2 - start1 <= max_rule_span
&& size1 + size2 + 1 <= max_rule_symbols) {
vector<int> pattern = annotations[i];
pattern.push_back(-1);
AppendSubpattern(pattern, annotations[j]);
AppendCollocation(index[pattern], start1, start2);
// Try extending the binary collocation to a ternary collocation.
if (is_super2) {
pattern.push_back(-2);
// Select the rightmost subpattern.
for (size_t k = j + 1; k < matchings.size(); ++k) {
int start3, size3, is_super3;
tie(start3, size3, is_super3) = matchings[k];
if (start3 - start1 >= max_rule_span) {
break;
}
if (start3 - start2 - size2 >= min_gap_size
&& start3 + size3 - start1 <= max_rule_span
&& size1 + size2 + size3 + 2 <= max_rule_symbols
&& (is_super1 || is_super3)) {
AppendSubpattern(pattern, annotations[k]);
AppendCollocation(index[pattern], start1, start2, start3);
pattern.erase(pattern.end() - size3);
}
}
}
}
}
}
}
void Precomputation::AppendSubpattern(
vector<int>& pattern,
const vector<int>& subpattern) {
copy(subpattern.begin(), subpattern.end(), back_inserter(pattern));
}
void Precomputation::AppendCollocation(
vector<int>& collocations, int pos1, int pos2) {
collocations.push_back(pos1);
collocations.push_back(pos2);
}
void Precomputation::AppendCollocation(
vector<int>& collocations, int pos1, int pos2, int pos3) {
collocations.push_back(pos1);
collocations.push_back(pos2);
collocations.push_back(pos3);
}
bool Precomputation::Contains(const vector<int>& pattern) const {
return index.count(pattern);
}
vector<int> Precomputation::GetCollocations(const vector<int>& pattern) const {
return index.at(pattern);
}
bool Precomputation::operator==(const Precomputation& other) const {
return index == other.index;
}
} // namespace extractor
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