void Data::loadNBest(const string &file)
{
TRACE_ERR("loading nbest from " << file << endl);
inputfilestream inp(file); // matches a stream with a file. Opens the file
if (!inp.good())
throw runtime_error("Unable to open: " + file);
ScoreStats scoreentry;
string line, sentence_index, sentence, feature_str;
while (getline(inp, line, '\n')) {
if (line.empty()) continue;
// adding statistics for error measures
scoreentry.clear();
getNextPound(line, sentence_index, "|||"); // first field
getNextPound(line, sentence, "|||"); // second field
getNextPound(line, feature_str, "|||"); // third field
m_scorer->prepareStats(sentence_index, sentence, scoreentry);
m_score_data->add(scoreentry, sentence_index);
// examine first line for name of features
if (!existsFeatureNames()) {
InitFeatureMap(feature_str);
}
AddFeatures(feature_str, sentence_index);
}
inp.close();
}
void Data::loadNBest(const string &file, bool oneBest)
{
TRACE_ERR("loading nbest from " << file << endl);
util::FilePiece in(file.c_str());
ScoreStats scoreentry;
string sentence, feature_str, alignment;
int sentence_index;
while (true) {
try {
StringPiece line = in.ReadLine();
if (line.empty()) continue;
// adding statistics for error measures
scoreentry.clear();
util::TokenIter<util::MultiCharacter> it(line, util::MultiCharacter("|||"));
sentence_index = ParseInt(*it);
if (oneBest && m_score_data->exists(sentence_index)) continue;
++it;
sentence = it->as_string();
++it;
feature_str = it->as_string();
++it;
if (it) {
++it; // skip model score.
if (it) {
alignment = it->as_string(); //fifth field (if present) is either phrase or word alignment
++it;
if (it) {
alignment = it->as_string(); //sixth field (if present) is word alignment
}
}
}
//TODO check alignment exists if scorers need it
if (m_scorer->useAlignment()) {
sentence += "|||";
sentence += alignment;
}
m_scorer->prepareStats(sentence_index, sentence, scoreentry);
m_score_data->add(scoreentry, sentence_index);
// examine first line for name of features
if (!existsFeatureNames()) {
InitFeatureMap(feature_str);
}
AddFeatures(feature_str, sentence_index);
} catch (util::EndOfFileException &e) {
PrintUserTime("Loaded N-best lists");
break;
}
}
}
void DataAsiya::loadNBest(const string &file)
{
TRACE_ERR("loading nbest from DataAsiya " << file << endl);
inputfilestream inp(file); // matches a stream with a file. Opens the file
if (!inp.good())
throw runtime_error("Unable to open: " + file);
ScoreStats scoreentry;
string line, sentence_index, sentence, feature_str, alignment;
AsiyaScorer* a_scorer = dynamic_cast<AsiyaScorer*>(m_scorer);
/*todo. change this loop. instead of obtaining the score for each sentence, obtain all the scores at once!*/
while (getline(inp, line, '\n')) {
if (line.empty()) continue;
// adding statistics for error measures
scoreentry.clear();
getNextPound(line, sentence_index, "|||"); // first field
getNextPound(line, sentence, "|||"); // second field
getNextPound(line, feature_str, "|||"); // third field
if (line.length() > 0) {
string temp;
getNextPound(line, temp, "|||"); //fourth field sentence score
if (line.length() > 0) {
getNextPound(line, alignment, "|||"); //fourth field only there if alignment scorer
}
}
//TODO check alignment exists if scorers need it
if (a_scorer->useAlignment()) {
sentence += "|||";
sentence += alignment;
}
// prepare stats gets all the scores for sentence_i of sentence_index
// a_scorer->addCandidateSentence(sentence_index, sentence);
a_scorer->prepareStats(atoi(sentence_index.c_str()), sentence, scoreentry);
// examine first line for name of features
if (!existsFeatureNames()) {
InitFeatureMap(feature_str);
}
AddFeatures(feature_str, atoi(sentence_index.c_str()));
}
a_scorer->doScoring();
// TRACE_ERR("before getAllScoreStats" << endl);
std::vector<std::vector <ScoreStats> > allScoreStats = a_scorer->getAllScoreStats();
for (int i = 0; i < allScoreStats.size(); ++i)
for(int j = 0; j < allScoreStats[i].size(); ++j)
{
stringstream ss;
ss << i;
m_score_data->add(allScoreStats[i][j], atoi(ss.str().c_str()));
// TRACE_ERR("allScoreStats[" << i << "].size() " << allScoreStats[i].size() << " " << allScoreStats[i][j] << endl);
}
inp.close();
// a_scorer->doScoring( m_score_data );
//score each sentence
//a_scorer->prepareStats(sentence_index, sentence, scoreentry);
// save the score for previous sentence. Do it aling with previous function
//m_score_data->add(scoreentry, sentence_index);
}