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/*
* FeatureData.cpp
* mert - Minimum Error Rate Training
*
* Created by Nicola Bertoldi on 13/05/08.
*
*/
#include "FeatureData.h"
#include <limits>
#include "FileStream.h"
#include "Util.h"
using namespace std;
namespace MosesTuning
{
FeatureData::FeatureData()
: m_num_features(0) {}
void FeatureData::save(ostream* os, bool bin)
{
for (featdata_t::iterator i = m_array.begin(); i != m_array.end(); i++)
i->save(os, bin);
}
void FeatureData::save(const string &file, bool bin)
{
if (file.empty()) return;
TRACE_ERR("saving the array into " << file << endl);
ofstream ofs(file.c_str(), ios::out); // matches a stream with a file. Opens the file
ostream* os = &ofs;
save(os, bin);
ofs.close();
}
void FeatureData::save(bool bin)
{
save(&cout, bin);
}
void FeatureData::load(istream* is, const SparseVector& sparseWeights)
{
FeatureArray entry;
while (!is->eof()) {
if (!is->good()) {
cerr << "ERROR FeatureData::load inFile.good()" << endl;
}
entry.clear();
entry.load(is, sparseWeights);
if (entry.size() == 0)
break;
if (size() == 0)
setFeatureMap(entry.Features());
add(entry);
}
}
void FeatureData::load(const string &file, const SparseVector& sparseWeights)
{
TRACE_ERR("loading feature data from " << file << endl);
inputfilestream input_stream(file); // matches a stream with a file. Opens the file
if (!input_stream) {
throw runtime_error("Unable to open feature file: " + file);
}
istream* is = &input_stream;
load(is, sparseWeights);
input_stream.close();
}
void FeatureData::add(FeatureArray& e)
{
if (exists(e.getIndex())) { // array at position e.getIndex() already exists
//enlarge array at position e.getIndex()
size_t pos = getIndex(e.getIndex());
m_array.at(pos).merge(e);
} else {
m_array.push_back(e);
setIndex();
}
}
void FeatureData::add(FeatureStats& e, int sent_idx)
{
if (exists(sent_idx)) { // array at position e.getIndex() already exists
//enlarge array at position e.getIndex()
size_t pos = getIndex(sent_idx);
// TRACE_ERR("Inserting " << e << " in array " << sent_idx << std::endl);
m_array.at(pos).add(e);
} else {
// TRACE_ERR("Creating a new entry in the array and inserting " << e << std::endl);
FeatureArray a;
a.NumberOfFeatures(m_num_features);
a.Features(m_features);
a.setIndex(sent_idx);
a.add(e);
add(a);
}
}
bool FeatureData::check_consistency() const
{
if (m_array.size() == 0)
return true;
for (featdata_t::const_iterator i = m_array.begin(); i != m_array.end(); i++)
if (!i->check_consistency()) return false;
return true;
}
void FeatureData::setIndex()
{
size_t j=0;
for (featdata_t::iterator i = m_array.begin(); i !=m_array.end(); i++) {
m_index_to_array_name[j]=(*i).getIndex();
m_array_name_to_index[(*i).getIndex()] = j;
j++;
}
}
void FeatureData::setFeatureMap(const string& feat)
{
m_num_features = 0;
m_features = feat;
vector<string> buf;
Tokenize(feat.c_str(), ' ', &buf);
for (vector<string>::const_iterator it = buf.begin();
it != buf.end(); ++it) {
const size_t size = m_index_to_feature_name.size();
m_feature_name_to_index[*it] = size;
m_index_to_feature_name[size] = *it;
++m_num_features;
}
}
string FeatureData::ToString() const
{
string res;
{
stringstream ss;
ss << "number of features: " << m_num_features
<< ", features: " << m_features;
res.append(ss.str());
}
res.append("feature_id_map = { ");
for (map<string, size_t>::const_iterator it = m_feature_name_to_index.begin();
it != m_feature_name_to_index.end(); ++it) {
stringstream ss;
ss << it->first << " => " << it->second << ", ";
res.append(ss.str());
}
res.append("}");
return res;
}
}
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