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#pragma once
#include "search/model.hpp"
#include "search/pre_ranking_info.hpp"
#include "search/ranking_utils.hpp"
#include <cstddef>
#include <cstdint>
#include <ostream>
#include <string>
#include <utility>
class FeatureType;
namespace search
{
struct RankingInfo
{
static double const kMaxDistMeters;
static void PrintCSVHeader(std::ostream & os);
void ToCSV(std::ostream & os) const;
// Returns rank calculated by a linear model. Large values
// correspond to important features.
double GetLinearModelRank() const;
size_t GetErrorsMade() const;
// Distance from the feature to the pivot point.
double m_distanceToPivot = kMaxDistMeters;
// Rank of the feature.
uint8_t m_rank = 0;
// Popularity rank of the feature.
uint8_t m_popularity = 0;
// Confidence and UGC rating.
std::pair<uint8_t, float> m_rating = {0, 0.0f};
// Score for the feature's name.
NameScore m_nameScore = NAME_SCORE_ZERO;
// Number of typos.
ErrorsMade m_errorsMade;
// True iff all tokens that are not stop-words
// were used when retrieving the feature.
bool m_allTokensUsed = true;
// Search type for the feature.
Model::Type m_type = Model::TYPE_COUNT;
// True if all of the tokens that the feature was matched by
// correspond to this feature's categories.
bool m_pureCats = false;
// True if none of the tokens that the feature was matched by
// corresponds to this feature's categories although all of the
// tokens are categorial ones.
bool m_falseCats = false;
// True iff the request is categorial.
bool m_categorialRequest = false;
// True iff the feature has a name.
bool m_hasName = false;
};
std::string DebugPrint(RankingInfo const & info);
} // namespace search
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