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/* SPDX-License-Identifier: MIT */
/* Copyright © 2022 Max Bachmann */
#pragma once
#include <cmath>
#include <rapidfuzz/details/Range.hpp>
#include <rapidfuzz/details/common.hpp>
#include <rapidfuzz/details/simd.hpp>
#include <type_traits>
namespace rapidfuzz {
namespace detail {
template <typename T, typename... Args>
struct NormalizedMetricBase {
template <typename InputIt1, typename InputIt2,
typename = rapidfuzz::rf_enable_if_t<!std::is_same<InputIt2, double>::value>>
static double normalized_distance(InputIt1 first1, InputIt1 last1, InputIt2 first2, InputIt2 last2,
Args... args, double score_cutoff, double score_hint)
{
return _normalized_distance(make_range(first1, last1), make_range(first2, last2),
std::forward<Args>(args)..., score_cutoff, score_hint);
}
template <typename Sentence1, typename Sentence2>
static double normalized_distance(const Sentence1& s1, const Sentence2& s2, Args... args,
double score_cutoff, double score_hint)
{
return _normalized_distance(make_range(s1), make_range(s2), std::forward<Args>(args)..., score_cutoff,
score_hint);
}
template <typename InputIt1, typename InputIt2,
typename = rapidfuzz::rf_enable_if_t<!std::is_same<InputIt2, double>::value>>
static double normalized_similarity(InputIt1 first1, InputIt1 last1, InputIt2 first2, InputIt2 last2,
Args... args, double score_cutoff, double score_hint)
{
return _normalized_similarity(make_range(first1, last1), make_range(first2, last2),
std::forward<Args>(args)..., score_cutoff, score_hint);
}
template <typename Sentence1, typename Sentence2>
static double normalized_similarity(const Sentence1& s1, const Sentence2& s2, Args... args,
double score_cutoff, double score_hint)
{
return _normalized_similarity(make_range(s1), make_range(s2), std::forward<Args>(args)...,
score_cutoff, score_hint);
}
protected:
template <typename InputIt1, typename InputIt2>
static double _normalized_distance(const Range<InputIt1>& s1, const Range<InputIt2>& s2, Args... args,
double score_cutoff, double score_hint)
{
auto maximum = T::maximum(s1, s2, args...);
auto cutoff_distance =
static_cast<decltype(maximum)>(std::ceil(static_cast<double>(maximum) * score_cutoff));
auto hint_distance =
static_cast<decltype(maximum)>(std::ceil(static_cast<double>(maximum) * score_hint));
auto dist = T::_distance(s1, s2, std::forward<Args>(args)..., cutoff_distance, hint_distance);
double norm_dist = (maximum != 0) ? static_cast<double>(dist) / static_cast<double>(maximum) : 0.0;
return (norm_dist <= score_cutoff) ? norm_dist : 1.0;
}
template <typename InputIt1, typename InputIt2>
static double _normalized_similarity(const Range<InputIt1>& s1, const Range<InputIt2>& s2, Args... args,
double score_cutoff, double score_hint)
{
double cutoff_score = NormSim_to_NormDist(score_cutoff);
double hint_score = NormSim_to_NormDist(score_hint);
double norm_dist =
_normalized_distance(s1, s2, std::forward<Args>(args)..., cutoff_score, hint_score);
double norm_sim = 1.0 - norm_dist;
return (norm_sim >= score_cutoff) ? norm_sim : 0.0;
}
NormalizedMetricBase()
{}
friend T;
};
template <typename T, typename ResType, int64_t WorstSimilarity, int64_t WorstDistance, typename... Args>
struct DistanceBase : public NormalizedMetricBase<T, Args...> {
template <typename InputIt1, typename InputIt2,
typename = rapidfuzz::rf_enable_if_t<!std::is_same<InputIt2, double>::value>>
static ResType distance(InputIt1 first1, InputIt1 last1, InputIt2 first2, InputIt2 last2, Args... args,
ResType score_cutoff, ResType score_hint)
{
return T::_distance(make_range(first1, last1), make_range(first2, last2), std::forward<Args>(args)...,
score_cutoff, score_hint);
}
template <typename Sentence1, typename Sentence2>
static ResType distance(const Sentence1& s1, const Sentence2& s2, Args... args, ResType score_cutoff,
ResType score_hint)
{
return T::_distance(make_range(s1), make_range(s2), std::forward<Args>(args)..., score_cutoff,
score_hint);
}
template <typename InputIt1, typename InputIt2,
typename = rapidfuzz::rf_enable_if_t<!std::is_same<InputIt2, double>::value>>
static ResType similarity(InputIt1 first1, InputIt1 last1, InputIt2 first2, InputIt2 last2, Args... args,
ResType score_cutoff, ResType score_hint)
{
return _similarity(make_range(first1, last1), make_range(first2, last2), std::forward<Args>(args)...,
score_cutoff, score_hint);
}
template <typename Sentence1, typename Sentence2>
static ResType similarity(const Sentence1& s1, const Sentence2& s2, Args... args, ResType score_cutoff,
ResType score_hint)
{
return _similarity(make_range(s1), make_range(s2), std::forward<Args>(args)..., score_cutoff,
score_hint);
}
protected:
template <typename InputIt1, typename InputIt2>
static ResType _similarity(Range<InputIt1> s1, Range<InputIt2> s2, Args... args, ResType score_cutoff,
ResType score_hint)
{
auto maximum = T::maximum(s1, s2, args...);
if (score_cutoff > maximum) return 0;
score_hint = std::min(score_cutoff, score_hint);
ResType cutoff_distance = maximum - score_cutoff;
ResType hint_distance = maximum - score_hint;
ResType dist = T::_distance(s1, s2, std::forward<Args>(args)..., cutoff_distance, hint_distance);
ResType sim = maximum - dist;
return (sim >= score_cutoff) ? sim : 0;
}
DistanceBase()
{}
friend T;
};
template <typename T, typename ResType, int64_t WorstSimilarity, int64_t WorstDistance, typename... Args>
struct SimilarityBase : public NormalizedMetricBase<T, Args...> {
template <typename InputIt1, typename InputIt2,
typename = rapidfuzz::rf_enable_if_t<!std::is_same<InputIt2, double>::value>>
static ResType distance(InputIt1 first1, InputIt1 last1, InputIt2 first2, InputIt2 last2, Args... args,
ResType score_cutoff, ResType score_hint)
{
return _distance(make_range(first1, last1), make_range(first2, last2), std::forward<Args>(args)...,
score_cutoff, score_hint);
}
template <typename Sentence1, typename Sentence2>
static ResType distance(const Sentence1& s1, const Sentence2& s2, Args... args, ResType score_cutoff,
ResType score_hint)
{
return _distance(make_range(s1), make_range(s2), std::forward<Args>(args)..., score_cutoff,
score_hint);
}
template <typename InputIt1, typename InputIt2,
typename = rapidfuzz::rf_enable_if_t<!std::is_same<InputIt2, double>::value>>
static ResType similarity(InputIt1 first1, InputIt1 last1, InputIt2 first2, InputIt2 last2, Args... args,
ResType score_cutoff, ResType score_hint)
{
return T::_similarity(make_range(first1, last1), make_range(first2, last2),
std::forward<Args>(args)..., score_cutoff, score_hint);
}
template <typename Sentence1, typename Sentence2>
static ResType similarity(const Sentence1& s1, const Sentence2& s2, Args... args, ResType score_cutoff,
ResType score_hint)
{
return T::_similarity(make_range(s1), make_range(s2), std::forward<Args>(args)..., score_cutoff,
score_hint);
}
protected:
template <typename InputIt1, typename InputIt2>
static ResType _distance(const Range<InputIt1>& s1, const Range<InputIt2>& s2, Args... args,
ResType score_cutoff, ResType score_hint)
{
auto maximum = T::maximum(s1, s2, args...);
ResType cutoff_similarity =
(maximum >= score_cutoff) ? maximum - score_cutoff : static_cast<ResType>(WorstSimilarity);
ResType hint_similarity =
(maximum >= score_hint) ? maximum - score_hint : static_cast<ResType>(WorstSimilarity);
ResType sim = T::_similarity(s1, s2, std::forward<Args>(args)..., cutoff_similarity, hint_similarity);
ResType dist = maximum - sim;
return _apply_distance_score_cutoff(dist, score_cutoff);
}
template <typename U>
static rapidfuzz::rf_enable_if_t<std::is_floating_point<U>::value, U>
_apply_distance_score_cutoff(U score, U score_cutoff)
{
return (score <= score_cutoff) ? score : 1.0;
}
template <typename U>
static rapidfuzz::rf_enable_if_t<!std::is_floating_point<U>::value, U>
_apply_distance_score_cutoff(U score, U score_cutoff)
{
return (score <= score_cutoff) ? score : score_cutoff + 1;
}
SimilarityBase()
{}
friend T;
};
template <typename T>
struct CachedNormalizedMetricBase {
template <typename InputIt2>
double normalized_distance(InputIt2 first2, InputIt2 last2, double score_cutoff = 1.0,
double score_hint = 1.0) const
{
return _normalized_distance(make_range(first2, last2), score_cutoff, score_hint);
}
template <typename Sentence2>
double normalized_distance(const Sentence2& s2, double score_cutoff = 1.0, double score_hint = 1.0) const
{
return _normalized_distance(make_range(s2), score_cutoff, score_hint);
}
template <typename InputIt2>
double normalized_similarity(InputIt2 first2, InputIt2 last2, double score_cutoff = 0.0,
double score_hint = 0.0) const
{
return _normalized_similarity(make_range(first2, last2), score_cutoff, score_hint);
}
template <typename Sentence2>
double normalized_similarity(const Sentence2& s2, double score_cutoff = 0.0,
double score_hint = 0.0) const
{
return _normalized_similarity(make_range(s2), score_cutoff, score_hint);
}
protected:
template <typename InputIt2>
double _normalized_distance(const Range<InputIt2>& s2, double score_cutoff, double score_hint) const
{
const T& derived = static_cast<const T&>(*this);
auto maximum = derived.maximum(s2);
auto cutoff_distance =
static_cast<decltype(maximum)>(std::ceil(static_cast<double>(maximum) * score_cutoff));
auto hint_distance =
static_cast<decltype(maximum)>(std::ceil(static_cast<double>(maximum) * score_hint));
double dist = static_cast<double>(derived._distance(s2, cutoff_distance, hint_distance));
double norm_dist = (maximum != 0) ? dist / static_cast<double>(maximum) : 0.0;
return (norm_dist <= score_cutoff) ? norm_dist : 1.0;
}
template <typename InputIt2>
double _normalized_similarity(const Range<InputIt2>& s2, double score_cutoff, double score_hint) const
{
double cutoff_score = NormSim_to_NormDist(score_cutoff);
double hint_score = NormSim_to_NormDist(score_hint);
double norm_dist = _normalized_distance(s2, cutoff_score, hint_score);
double norm_sim = 1.0 - norm_dist;
return (norm_sim >= score_cutoff) ? norm_sim : 0.0;
}
CachedNormalizedMetricBase()
{}
friend T;
};
template <typename T, typename ResType, int64_t WorstSimilarity, int64_t WorstDistance>
struct CachedDistanceBase : public CachedNormalizedMetricBase<T> {
template <typename InputIt2>
ResType distance(InputIt2 first2, InputIt2 last2,
ResType score_cutoff = static_cast<ResType>(WorstDistance),
ResType score_hint = static_cast<ResType>(WorstDistance)) const
{
const T& derived = static_cast<const T&>(*this);
return derived._distance(make_range(first2, last2), score_cutoff, score_hint);
}
template <typename Sentence2>
ResType distance(const Sentence2& s2, ResType score_cutoff = static_cast<ResType>(WorstDistance),
ResType score_hint = static_cast<ResType>(WorstDistance)) const
{
const T& derived = static_cast<const T&>(*this);
return derived._distance(make_range(s2), score_cutoff, score_hint);
}
template <typename InputIt2>
ResType similarity(InputIt2 first2, InputIt2 last2,
ResType score_cutoff = static_cast<ResType>(WorstSimilarity),
ResType score_hint = static_cast<ResType>(WorstSimilarity)) const
{
return _similarity(make_range(first2, last2), score_cutoff, score_hint);
}
template <typename Sentence2>
ResType similarity(const Sentence2& s2, ResType score_cutoff = static_cast<ResType>(WorstSimilarity),
ResType score_hint = static_cast<ResType>(WorstSimilarity)) const
{
return _similarity(make_range(s2), score_cutoff, score_hint);
}
protected:
template <typename InputIt2>
ResType _similarity(const Range<InputIt2>& s2, ResType score_cutoff, ResType score_hint) const
{
const T& derived = static_cast<const T&>(*this);
ResType maximum = derived.maximum(s2);
if (score_cutoff > maximum) return 0;
score_hint = std::min(score_cutoff, score_hint);
ResType cutoff_distance = maximum - score_cutoff;
ResType hint_distance = maximum - score_hint;
ResType dist = derived._distance(s2, cutoff_distance, hint_distance);
ResType sim = maximum - dist;
return (sim >= score_cutoff) ? sim : 0;
}
CachedDistanceBase()
{}
friend T;
};
template <typename T, typename ResType, int64_t WorstSimilarity, int64_t WorstDistance>
struct CachedSimilarityBase : public CachedNormalizedMetricBase<T> {
template <typename InputIt2>
ResType distance(InputIt2 first2, InputIt2 last2,
ResType score_cutoff = static_cast<ResType>(WorstDistance),
ResType score_hint = static_cast<ResType>(WorstDistance)) const
{
return _distance(make_range(first2, last2), score_cutoff, score_hint);
}
template <typename Sentence2>
ResType distance(const Sentence2& s2, ResType score_cutoff = static_cast<ResType>(WorstDistance),
ResType score_hint = static_cast<ResType>(WorstDistance)) const
{
return _distance(make_range(s2), score_cutoff, score_hint);
}
template <typename InputIt2>
ResType similarity(InputIt2 first2, InputIt2 last2,
ResType score_cutoff = static_cast<ResType>(WorstSimilarity),
ResType score_hint = static_cast<ResType>(WorstSimilarity)) const
{
const T& derived = static_cast<const T&>(*this);
return derived._similarity(make_range(first2, last2), score_cutoff, score_hint);
}
template <typename Sentence2>
ResType similarity(const Sentence2& s2, ResType score_cutoff = static_cast<ResType>(WorstSimilarity),
ResType score_hint = static_cast<ResType>(WorstSimilarity)) const
{
const T& derived = static_cast<const T&>(*this);
return derived._similarity(make_range(s2), score_cutoff, score_hint);
}
protected:
template <typename InputIt2>
ResType _distance(const Range<InputIt2>& s2, ResType score_cutoff, ResType score_hint) const
{
const T& derived = static_cast<const T&>(*this);
ResType maximum = derived.maximum(s2);
ResType cutoff_similarity = (maximum > score_cutoff) ? maximum - score_cutoff : 0;
ResType hint_similarity = (maximum > score_hint) ? maximum - score_hint : 0;
ResType sim = derived._similarity(s2, cutoff_similarity, hint_similarity);
ResType dist = maximum - sim;
return _apply_distance_score_cutoff(dist, score_cutoff);
}
template <typename U>
static rapidfuzz::rf_enable_if_t<std::is_floating_point<U>::value, U>
_apply_distance_score_cutoff(U score, U score_cutoff)
{
return (score <= score_cutoff) ? score : 1.0;
}
template <typename U>
static rapidfuzz::rf_enable_if_t<!std::is_floating_point<U>::value, U>
_apply_distance_score_cutoff(U score, U score_cutoff)
{
return (score <= score_cutoff) ? score : score_cutoff + 1;
}
CachedSimilarityBase()
{}
friend T;
};
template <typename T, typename ResType>
struct MultiNormalizedMetricBase {
template <typename InputIt2>
void normalized_distance(double* scores, size_t score_count, InputIt2 first2, InputIt2 last2,
double score_cutoff = 1.0) const
{
_normalized_distance(scores, score_count, make_range(first2, last2), score_cutoff);
}
template <typename Sentence2>
void normalized_distance(double* scores, size_t score_count, const Sentence2& s2,
double score_cutoff = 1.0) const
{
_normalized_distance(scores, score_count, make_range(s2), score_cutoff);
}
template <typename InputIt2>
void normalized_similarity(double* scores, size_t score_count, InputIt2 first2, InputIt2 last2,
double score_cutoff = 0.0) const
{
_normalized_similarity(scores, score_count, make_range(first2, last2), score_cutoff);
}
template <typename Sentence2>
void normalized_similarity(double* scores, size_t score_count, const Sentence2& s2,
double score_cutoff = 0.0) const
{
_normalized_similarity(scores, score_count, make_range(s2), score_cutoff);
}
protected:
template <typename InputIt2>
void _normalized_distance(double* scores, size_t score_count, const Range<InputIt2>& s2,
double score_cutoff = 1.0) const
{
const T& derived = static_cast<const T&>(*this);
if (score_count < derived.result_count())
throw std::invalid_argument("scores has to have >= result_count() elements");
// reinterpretation only works when the types have the same size
ResType* scores_orig = nullptr;
RAPIDFUZZ_IF_CONSTEXPR (sizeof(double) == sizeof(ResType))
scores_orig = reinterpret_cast<ResType*>(scores);
else
scores_orig = new ResType[derived.result_count()];
derived.distance(scores_orig, derived.result_count(), s2);
for (size_t i = 0; i < derived.get_input_count(); ++i) {
auto maximum = derived.maximum(i, s2);
double norm_dist =
(maximum != 0) ? static_cast<double>(scores_orig[i]) / static_cast<double>(maximum) : 0.0;
scores[i] = (norm_dist <= score_cutoff) ? norm_dist : 1.0;
}
RAPIDFUZZ_IF_CONSTEXPR (sizeof(double) != sizeof(ResType)) delete[] scores_orig;
}
template <typename InputIt2>
void _normalized_similarity(double* scores, size_t score_count, const Range<InputIt2>& s2,
double score_cutoff) const
{
const T& derived = static_cast<const T&>(*this);
_normalized_distance(scores, score_count, s2);
for (size_t i = 0; i < derived.get_input_count(); ++i) {
double norm_sim = 1.0 - scores[i];
scores[i] = (norm_sim >= score_cutoff) ? norm_sim : 0.0;
}
}
MultiNormalizedMetricBase()
{}
friend T;
};
template <typename T, typename ResType, int64_t WorstSimilarity, int64_t WorstDistance>
struct MultiDistanceBase : public MultiNormalizedMetricBase<T, ResType> {
template <typename InputIt2>
void distance(ResType* scores, size_t score_count, InputIt2 first2, InputIt2 last2,
ResType score_cutoff = static_cast<ResType>(WorstDistance)) const
{
const T& derived = static_cast<const T&>(*this);
derived._distance(scores, score_count, make_range(first2, last2), score_cutoff);
}
template <typename Sentence2>
void distance(ResType* scores, size_t score_count, const Sentence2& s2,
ResType score_cutoff = static_cast<ResType>(WorstDistance)) const
{
const T& derived = static_cast<const T&>(*this);
derived._distance(scores, score_count, make_range(s2), score_cutoff);
}
template <typename InputIt2>
void similarity(ResType* scores, size_t score_count, InputIt2 first2, InputIt2 last2,
ResType score_cutoff = static_cast<ResType>(WorstSimilarity)) const
{
_similarity(scores, score_count, make_range(first2, last2), score_cutoff);
}
template <typename Sentence2>
void similarity(ResType* scores, size_t score_count, const Sentence2& s2,
ResType score_cutoff = static_cast<ResType>(WorstSimilarity)) const
{
_similarity(scores, score_count, make_range(s2), score_cutoff);
}
protected:
template <typename InputIt2>
void _similarity(ResType* scores, size_t score_count, const Range<InputIt2>& s2,
ResType score_cutoff) const
{
const T& derived = static_cast<const T&>(*this);
derived._distance(scores, score_count, s2);
for (size_t i = 0; i < derived.get_input_count(); ++i) {
ResType maximum = derived.maximum(i, s2);
ResType sim = maximum - scores[i];
scores[i] = (sim >= score_cutoff) ? sim : 0;
}
}
MultiDistanceBase()
{}
friend T;
};
template <typename T, typename ResType, int64_t WorstSimilarity, int64_t WorstDistance>
struct MultiSimilarityBase : public MultiNormalizedMetricBase<T, ResType> {
template <typename InputIt2>
void distance(ResType* scores, size_t score_count, InputIt2 first2, InputIt2 last2,
ResType score_cutoff = static_cast<ResType>(WorstDistance)) const
{
_distance(scores, score_count, make_range(first2, last2), score_cutoff);
}
template <typename Sentence2>
void distance(ResType* scores, size_t score_count, const Sentence2& s2,
ResType score_cutoff = static_cast<ResType>(WorstDistance)) const
{
_distance(scores, score_count, make_range(s2), score_cutoff);
}
template <typename InputIt2>
void similarity(ResType* scores, size_t score_count, InputIt2 first2, InputIt2 last2,
ResType score_cutoff = static_cast<ResType>(WorstSimilarity)) const
{
const T& derived = static_cast<const T&>(*this);
derived._similarity(scores, score_count, make_range(first2, last2), score_cutoff);
}
template <typename Sentence2>
void similarity(ResType* scores, size_t score_count, const Sentence2& s2,
ResType score_cutoff = static_cast<ResType>(WorstSimilarity)) const
{
const T& derived = static_cast<const T&>(*this);
derived._similarity(scores, score_count, make_range(s2), score_cutoff);
}
protected:
template <typename InputIt2>
void _distance(ResType* scores, size_t score_count, const Range<InputIt2>& s2, ResType score_cutoff) const
{
const T& derived = static_cast<const T&>(*this);
derived._similarity(scores, score_count, s2);
for (size_t i = 0; i < derived.get_input_count(); ++i) {
ResType maximum = derived.maximum(i, s2);
ResType dist = maximum - scores[i];
scores[i] = _apply_distance_score_cutoff(dist, score_cutoff);
}
}
template <typename U>
static rapidfuzz::rf_enable_if_t<std::is_floating_point<U>::value, U>
_apply_distance_score_cutoff(U score, U score_cutoff)
{
return (score <= score_cutoff) ? score : 1.0;
}
template <typename U>
static rapidfuzz::rf_enable_if_t<!std::is_floating_point<U>::value, U>
_apply_distance_score_cutoff(U score, U score_cutoff)
{
return (score <= score_cutoff) ? score : score_cutoff + 1;
}
MultiSimilarityBase()
{}
friend T;
};
} // namespace detail
} // namespace rapidfuzz
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