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/* SPDX-License-Identifier: MIT */
/* Copyright © 2022-present Max Bachmann */
#pragma once
#include <rapidfuzz/details/Range.hpp>
#include <rapidfuzz/distance/Jaro_impl.hpp>
#include <stdlib.h>
namespace rapidfuzz {
template <typename InputIt1, typename InputIt2>
double jaro_distance(InputIt1 first1, InputIt1 last1, InputIt2 first2, InputIt2 last2,
double score_cutoff = 1.0)
{
return detail::Jaro::distance(first1, last1, first2, last2, score_cutoff, score_cutoff);
}
template <typename Sentence1, typename Sentence2>
double jaro_distance(const Sentence1& s1, const Sentence2& s2, double score_cutoff = 1.0)
{
return detail::Jaro::distance(s1, s2, score_cutoff, score_cutoff);
}
template <typename InputIt1, typename InputIt2>
double jaro_similarity(InputIt1 first1, InputIt1 last1, InputIt2 first2, InputIt2 last2,
double score_cutoff = 0.0)
{
return detail::Jaro::similarity(first1, last1, first2, last2, score_cutoff, score_cutoff);
}
template <typename Sentence1, typename Sentence2>
double jaro_similarity(const Sentence1& s1, const Sentence2& s2, double score_cutoff = 0.0)
{
return detail::Jaro::similarity(s1, s2, score_cutoff, score_cutoff);
}
template <typename InputIt1, typename InputIt2>
double jaro_normalized_distance(InputIt1 first1, InputIt1 last1, InputIt2 first2, InputIt2 last2,
double score_cutoff = 1.0)
{
return detail::Jaro::normalized_distance(first1, last1, first2, last2, score_cutoff, score_cutoff);
}
template <typename Sentence1, typename Sentence2>
double jaro_normalized_distance(const Sentence1& s1, const Sentence2& s2, double score_cutoff = 1.0)
{
return detail::Jaro::normalized_distance(s1, s2, score_cutoff, score_cutoff);
}
template <typename InputIt1, typename InputIt2>
double jaro_normalized_similarity(InputIt1 first1, InputIt1 last1, InputIt2 first2, InputIt2 last2,
double score_cutoff = 0.0)
{
return detail::Jaro::normalized_similarity(first1, last1, first2, last2, score_cutoff, score_cutoff);
}
template <typename Sentence1, typename Sentence2>
double jaro_normalized_similarity(const Sentence1& s1, const Sentence2& s2, double score_cutoff = 0.0)
{
return detail::Jaro::normalized_similarity(s1, s2, score_cutoff, score_cutoff);
}
#ifdef RAPIDFUZZ_SIMD
namespace experimental {
template <int MaxLen>
struct MultiJaro : public detail::MultiSimilarityBase<MultiJaro<MaxLen>, double, 0, 1> {
private:
friend detail::MultiSimilarityBase<MultiJaro<MaxLen>, double, 0, 1>;
friend detail::MultiNormalizedMetricBase<MultiJaro<MaxLen>, double>;
static_assert(MaxLen == 8 || MaxLen == 16 || MaxLen == 32 || MaxLen == 64, "incorrect MaxLen used");
using VecType = typename std::conditional<
MaxLen == 8, uint8_t,
typename std::conditional<MaxLen == 16, uint16_t,
typename std::conditional<MaxLen == 32, uint32_t, uint64_t>::type>::type>::
type;
constexpr static size_t get_vec_size()
{
# ifdef RAPIDFUZZ_AVX2
return detail::simd_avx2::native_simd<VecType>::size;
# else
return detail::simd_sse2::native_simd<VecType>::size;
# endif
}
constexpr static size_t get_vec_alignment()
{
# ifdef RAPIDFUZZ_AVX2
return detail::simd_avx2::native_simd<VecType>::alignment;
# else
return detail::simd_sse2::native_simd<VecType>::alignment;
# endif
}
static size_t find_block_count(size_t count)
{
size_t vec_size = get_vec_size();
size_t simd_vec_count = detail::ceil_div(count, vec_size);
return detail::ceil_div(simd_vec_count * vec_size * MaxLen, 64);
}
public:
MultiJaro(size_t count) : input_count(count), PM(find_block_count(count) * 64)
{
/* align for avx2 so we can directly load into avx2 registers */
str_lens_size = result_count();
str_lens = static_cast<VecType*>(
detail::rf_aligned_alloc(get_vec_alignment(), sizeof(VecType) * str_lens_size));
std::fill(str_lens, str_lens + str_lens_size, VecType(0));
}
~MultiJaro()
{
detail::rf_aligned_free(str_lens);
}
/**
* @brief get minimum size required for result vectors passed into
* - distance
* - similarity
* - normalized_distance
* - normalized_similarity
*
* @return minimum vector size
*/
size_t result_count() const
{
size_t vec_size = get_vec_size();
size_t simd_vec_count = detail::ceil_div(input_count, vec_size);
return simd_vec_count * vec_size;
}
template <typename Sentence1>
void insert(const Sentence1& s1_)
{
insert(detail::to_begin(s1_), detail::to_end(s1_));
}
template <typename InputIt1>
void insert(InputIt1 first1, InputIt1 last1)
{
auto len = std::distance(first1, last1);
int block_pos = static_cast<int>((pos * MaxLen) % 64);
auto block = (pos * MaxLen) / 64;
assert(len <= MaxLen);
if (pos >= input_count) throw std::invalid_argument("out of bounds insert");
str_lens[pos] = static_cast<VecType>(len);
for (; first1 != last1; ++first1) {
PM.insert(block, *first1, block_pos);
block_pos++;
}
pos++;
}
private:
template <typename InputIt2>
void _similarity(double* scores, size_t score_count, const detail::Range<InputIt2>& s2,
double score_cutoff = 0.0) const
{
if (score_count < result_count())
throw std::invalid_argument("scores has to have >= result_count() elements");
auto scores_ = detail::make_range(scores, scores + score_count);
detail::jaro_similarity_simd<VecType>(scores_, PM, str_lens, str_lens_size, s2, score_cutoff);
}
template <typename InputIt2>
double maximum(size_t, const detail::Range<InputIt2>&) const
{
return 1.0;
}
size_t get_input_count() const noexcept
{
return input_count;
}
size_t input_count;
size_t pos = 0;
detail::BlockPatternMatchVector PM;
VecType* str_lens;
size_t str_lens_size;
};
} /* namespace experimental */
#endif /* RAPIDFUZZ_SIMD */
template <typename CharT1>
struct CachedJaro : public detail::CachedSimilarityBase<CachedJaro<CharT1>, double, 0, 1> {
template <typename Sentence1>
explicit CachedJaro(const Sentence1& s1_) : CachedJaro(detail::to_begin(s1_), detail::to_end(s1_))
{}
template <typename InputIt1>
CachedJaro(InputIt1 first1, InputIt1 last1) : s1(first1, last1), PM(detail::make_range(first1, last1))
{}
private:
friend detail::CachedSimilarityBase<CachedJaro<CharT1>, double, 0, 1>;
friend detail::CachedNormalizedMetricBase<CachedJaro<CharT1>>;
template <typename InputIt2>
double maximum(const detail::Range<InputIt2>&) const
{
return 1.0;
}
template <typename InputIt2>
double _similarity(const detail::Range<InputIt2>& s2, double score_cutoff, double) const
{
return detail::jaro_similarity(PM, detail::make_range(s1), s2, score_cutoff);
}
std::vector<CharT1> s1;
detail::BlockPatternMatchVector PM;
};
#ifdef RAPIDFUZZ_DEDUCTION_GUIDES
template <typename Sentence1>
explicit CachedJaro(const Sentence1& s1_) -> CachedJaro<char_type<Sentence1>>;
template <typename InputIt1>
CachedJaro(InputIt1 first1, InputIt1 last1) -> CachedJaro<iter_value_t<InputIt1>>;
#endif
} // namespace rapidfuzz
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