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#ifndef _FF_SPANS_H_
#define _FF_SPANS_H_
#include <vector>
#include <map>
#include "ff.h"
#include "array2d.h"
#include "wordid.h"
class SpanFeatures : public FeatureFunction {
public:
SpanFeatures(const std::string& param);
protected:
virtual void TraversalFeaturesImpl(const SentenceMetadata& smeta,
const Hypergraph::Edge& edge,
const std::vector<const void*>& ant_contexts,
SparseVector<double>* features,
SparseVector<double>* estimated_features,
void* context) const;
virtual void PrepareForInput(const SentenceMetadata& smeta);
private:
WordID MapIfNecessary(const WordID& w) const;
const int kS;
const int kX;
Array2D<std::pair<int,int> > span_feats_; // first for X, second for S
Array2D<std::pair<int,int> > len_span_feats_; // first for X, second for S, including length
std::vector<int> end_span_ids_;
std::vector<int> end_bigram_ids_;
std::vector<int> beg_span_ids_;
std::vector<int> beg_bigram_ids_;
std::map<WordID, WordID> word2class_; // optional projection to coarser class
// collapsed feature values
bool use_collapsed_features_;
int fid_beg_;
int fid_end_;
int fid_span_s_;
int fid_span_;
std::map<std::string, double> feat2val_;
std::vector<double> end_span_vals_;
std::vector<double> beg_span_vals_;
Array2D<std::pair<double,double> > span_vals_;
WordID oov_;
};
class RuleNgramFeatures : public FeatureFunction {
public:
RuleNgramFeatures(const std::string& param);
protected:
virtual void TraversalFeaturesImpl(const SentenceMetadata& smeta,
const Hypergraph::Edge& edge,
const std::vector<const void*>& ant_contexts,
SparseVector<double>* features,
SparseVector<double>* estimated_features,
void* context) const;
virtual void PrepareForInput(const SentenceMetadata& smeta);
private:
mutable std::map<const TRule*, SparseVector<double> > rule2_feats_;
};
class CMR2008ReorderingFeatures : public FeatureFunction {
public:
CMR2008ReorderingFeatures(const std::string& param);
protected:
virtual void TraversalFeaturesImpl(const SentenceMetadata& smeta,
const Hypergraph::Edge& edge,
const std::vector<const void*>& ant_contexts,
SparseVector<double>* features,
SparseVector<double>* estimated_features,
void* context) const;
private:
const int kS;
std::pair<int, int> unconditioned_fids_; // first = monotone
// second = inverse
std::vector<std::pair<int, int> > fids_; // index=(j-i)
// collapsed feature values
bool use_collapsed_features_;
int fid_reorder_;
std::pair<double, double> uncoditioned_vals_;
std::vector<std::pair<double, double> > fvals_;
};
#endif
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