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/*
* FeatureData.h
* mert - Minimum Error Rate Training
*
* Created by Nicola Bertoldi on 13/05/08.
*
*/
#ifndef MERT_FEATURE_DATA_H_
#define MERT_FEATURE_DATA_H_
#include <vector>
#include <iostream>
#include <stdexcept>
#include <boost/lexical_cast.hpp>
#include "FeatureArray.h"
namespace MosesTuning
{
class FeatureData
{
private:
std::size_t m_num_features;
std::string m_features;
std::map<std::string, std::size_t> m_feature_name_to_index; // map from name to index of features
std::map<std::size_t, std::string> m_index_to_feature_name; // map from index to name of features
featdata_t m_array;
idx2name m_index_to_array_name; // map from index to name of array
name2idx m_array_name_to_index; // map from name to index of array
public:
FeatureData();
~FeatureData() {}
void clear() {
m_array.clear();
}
FeatureArray& get(size_t idx) {
return m_array.at(idx);
}
const FeatureArray& get(size_t idx) const {
return m_array.at(idx);
}
inline bool exists(int sent_idx) const {
return existsInternal(getIndex(sent_idx));
}
inline bool existsInternal(int sent_idx) const {
return (sent_idx > -1 && sent_idx < static_cast<int>(m_array.size())) ? true : false;
}
inline FeatureStats& get(std::size_t i, std::size_t j) {
return m_array.at(i).get(j);
}
inline const FeatureStats& get(std::size_t i, std::size_t j) const {
return m_array.at(i).get(j);
}
void add(FeatureArray& e);
void add(FeatureStats& e, int sent_idx);
std::size_t size() const {
return m_array.size();
}
std::size_t NumberOfFeatures() const {
return m_num_features;
}
void NumberOfFeatures(std::size_t v) {
m_num_features = v;
}
std::string Features() const {
return m_features;
}
void Features(const std::string& f) {
m_features = f;
}
void save(const std::string &file, bool bin=false);
void save(std::ostream* os, bool bin=false);
void save(bool bin=false);
void load(std::istream* is, const SparseVector& sparseWeights);
void load(const std::string &file, const SparseVector& sparseWeights);
bool check_consistency() const;
void setIndex();
inline int getIndex(int idx) const {
name2idx::const_iterator i = m_array_name_to_index.find(idx);
if (i != m_array_name_to_index.end())
return i->second;
else
return -1;
}
inline int getName(std::size_t idx) const {
idx2name::const_iterator i = m_index_to_array_name.find(idx);
if (i != m_index_to_array_name.end())
throw std::runtime_error("there is no entry at index " + boost::lexical_cast<std::string>(idx));
return i->second;
}
bool existsFeatureNames() const {
return (m_index_to_feature_name.size() > 0) ? true : false;
}
std::string getFeatureName(std::size_t idx) const {
if (idx >= m_index_to_feature_name.size())
throw std::runtime_error("Error: you required an too big index");
std::map<std::size_t, std::string>::const_iterator it = m_index_to_feature_name.find(idx);
if (it == m_index_to_feature_name.end()) {
throw std::runtime_error("Error: specified id is unknown: " + boost::lexical_cast<std::string>(idx));
} else {
return it->second;
}
}
std::size_t getFeatureIndex(const std::string& name) const {
std::map<std::string, std::size_t>::const_iterator it = m_feature_name_to_index.find(name);
if (it == m_feature_name_to_index.end()) {
std::string msg = "Error: feature " + name + " is unknown. Known features: ";
for (std::map<std::string, std::size_t>::const_iterator cit = m_feature_name_to_index.begin();
cit != m_feature_name_to_index.end(); cit++) {
msg += cit->first;
msg += ", ";
}
throw std::runtime_error(msg);
}
return it->second;
}
void setFeatureMap(const std::string& feat);
/* For debugging */
std::string ToString() const;
};
}
#endif // MERT_FEATURE_DATA_H_
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