mirror of
https://github.com/moses-smt/mosesdecoder.git
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137 lines
3.4 KiB
C++
137 lines
3.4 KiB
C++
/*
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* FeatureData.h
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* met - Minimum Error Training
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*
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* Created by Nicola Bertoldi on 13/05/08.
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*
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*/
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#ifndef FEATURE_DATA_H
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#define FEATURE_DATA_H
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using namespace std;
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#include <vector>
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#include <iostream>
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#include <stdexcept>
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#include "FeatureArray.h"
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class FeatureData
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{
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private:
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size_t number_of_features;
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std::string features;
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map<std::string, size_t> featname2idx_; // map from name to index of features
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map<size_t, std::string> idx2featname_; // map from index to name of features
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protected:
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featdata_t array_;
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idx2name idx2arrayname_; // map from index to name of array
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name2idx arrayname2idx_; // map from name to index of array
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public:
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FeatureData();
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~FeatureData() {}
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inline void clear() {
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array_.clear();
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}
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inline FeatureArray get(const std::string& idx) {
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return array_.at(getIndex(idx));
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}
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inline FeatureArray& get(size_t idx) {
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return array_.at(idx);
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}
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inline const FeatureArray& get(size_t idx) const {
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return array_.at(idx);
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}
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inline bool exists(const std::string& sent_idx) {
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return exists(getIndex(sent_idx));
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}
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inline bool exists(int sent_idx) {
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return (sent_idx>-1 && sent_idx<(int) array_.size())?true:false;
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}
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inline FeatureStats& get(size_t i, size_t j) {
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return array_.at(i).get(j);
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}
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inline const FeatureStats& get(size_t i, size_t j) const {
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return array_.at(i).get(j);
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}
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void add(FeatureArray& e);
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void add(FeatureStats& e, const std::string& sent_idx);
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inline size_t size() const {
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return array_.size();
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}
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inline size_t NumberOfFeatures() const {
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return number_of_features;
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}
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inline void NumberOfFeatures(size_t v) {
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number_of_features = v;
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}
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inline std::string Features() const {
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return features;
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}
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inline void Features(const std::string& f) {
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features = f;
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}
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void save(const std::string &file, bool bin=false);
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void save(ofstream& outFile, bool bin=false);
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inline void save(bool bin=false) {
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save("/dev/stdout", bin);
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}
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void load(ifstream& inFile, const SparseVector& sparseWeights);
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void load(const std::string &file, const SparseVector& sparseWeights);
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bool check_consistency() const;
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void setIndex();
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inline int getIndex(const std::string& idx) const {
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name2idx::const_iterator i = arrayname2idx_.find(idx);
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if (i != arrayname2idx_.end())
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return i->second;
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else
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return -1;
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}
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inline std::string getIndex(size_t idx) const {
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idx2name::const_iterator i = idx2arrayname_.find(idx);
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if (i != idx2arrayname_.end())
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throw runtime_error("there is no entry at index " + idx);
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return i->second;
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}
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bool existsFeatureNames() const {
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return (idx2featname_.size() > 0) ? true : false;
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}
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std::string getFeatureName(size_t idx) const {
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if (idx >= idx2featname_.size())
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throw runtime_error("Error: you required an too big index");
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map<size_t, std::string>::const_iterator it = idx2featname_.find(idx);
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if (it == idx2featname_.end()) {
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throw runtime_error("Error: specified id is unknown: " + idx);
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} else {
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return it->second;
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}
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}
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size_t getFeatureIndex(const std::string& name) const {
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map<std::string, size_t>::const_iterator it = featname2idx_.find(name);
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if (it == featname2idx_.end())
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throw runtime_error("Error: feature " + name + " is unknown");
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return it->second;
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}
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void setFeatureMap(const std::string& feat);
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};
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#endif // FEATURE_DATA_H
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