OSA.hpp

/* SPDX-License-Identifier: MIT */
/* Copyright © 2021 Max Bachmann */
 
#pragma once
 
#include <limits>
#include <rapidfuzz/details/common.hpp>
#include <rapidfuzz/distance/OSA_impl.hpp>
 
namespace rapidfuzz {
 
template <typename InputIt1, typename InputIt2>
size_t osa_distance(InputIt1 first1, InputIt1 last1, InputIt2 first2, InputIt2 last2,
                    size_t score_cutoff = std::numeric_limits<size_t>::max())
{
    return detail::OSA::distance(first1, last1, first2, last2, score_cutoff, score_cutoff);
}
 
template <typename Sentence1, typename Sentence2>
size_t osa_distance(const Sentence1& s1, const Sentence2& s2,
                    size_t score_cutoff = std::numeric_limits<size_t>::max())
{
    return detail::OSA::distance(s1, s2, score_cutoff, score_cutoff);
}
 
template <typename InputIt1, typename InputIt2>
size_t osa_similarity(InputIt1 first1, InputIt1 last1, InputIt2 first2, InputIt2 last2,
                      size_t score_cutoff = 0)
{
    return detail::OSA::similarity(first1, last1, first2, last2, score_cutoff, score_cutoff);
}
 
template <typename Sentence1, typename Sentence2>
size_t osa_similarity(const Sentence1& s1, const Sentence2& s2, size_t score_cutoff = 0)
{
    return detail::OSA::similarity(s1, s2, score_cutoff, score_cutoff);
}
 
template <typename InputIt1, typename InputIt2>
double osa_normalized_distance(InputIt1 first1, InputIt1 last1, InputIt2 first2, InputIt2 last2,
                               double score_cutoff = 1.0)
{
    return detail::OSA::normalized_distance(first1, last1, first2, last2, score_cutoff, score_cutoff);
}
 
template <typename Sentence1, typename Sentence2>
double osa_normalized_distance(const Sentence1& s1, const Sentence2& s2, double score_cutoff = 1.0)
{
    return detail::OSA::normalized_distance(s1, s2, score_cutoff, score_cutoff);
}
 
template <typename InputIt1, typename InputIt2>
double osa_normalized_similarity(InputIt1 first1, InputIt1 last1, InputIt2 first2, InputIt2 last2,
                                 double score_cutoff = 0.0)
{
    return detail::OSA::normalized_similarity(first1, last1, first2, last2, score_cutoff, score_cutoff);
}
 
template <typename Sentence1, typename Sentence2>
double osa_normalized_similarity(const Sentence1& s1, const Sentence2& s2, double score_cutoff = 0.0)
{
    return detail::OSA::normalized_similarity(s1, s2, score_cutoff, score_cutoff);
}
 
#ifdef RAPIDFUZZ_SIMD
namespace experimental {
template <int MaxLen>
struct MultiOSA
    : public detail::MultiDistanceBase<MultiOSA<MaxLen>, size_t, 0, std::numeric_limits<int64_t>::max()> {
private:
    friend detail::MultiDistanceBase<MultiOSA<MaxLen>, size_t, 0, std::numeric_limits<int64_t>::max()>;
    friend detail::MultiNormalizedMetricBase<MultiOSA<MaxLen>, size_t>;
 
    RAPIDFUZZ_CONSTEXPR_CXX14 static size_t get_vec_size()
    {
#    ifdef RAPIDFUZZ_AVX2
        using namespace detail::simd_avx2;
#    else
        using namespace detail::simd_sse2;
#    endif
        RAPIDFUZZ_IF_CONSTEXPR (MaxLen <= 8)
            return native_simd<uint8_t>::size;
        else RAPIDFUZZ_IF_CONSTEXPR (MaxLen <= 16)
            return native_simd<uint16_t>::size;
        else RAPIDFUZZ_IF_CONSTEXPR (MaxLen <= 32)
            return native_simd<uint32_t>::size;
        else RAPIDFUZZ_IF_CONSTEXPR (MaxLen <= 64)
            return native_simd<uint64_t>::size;
 
        static_assert(MaxLen <= 64, "expected MaxLen <= 64");
    }
 
    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:
    MultiOSA(size_t count) : input_count(count), PM(find_block_count(count) * 64)
    {
        str_lens.resize(result_count());
    }
 
    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<size_t>(len);
        for (; first1 != last1; ++first1) {
            PM.insert(block, *first1, block_pos);
            block_pos++;
        }
        pos++;
    }
 
private:
    template <typename InputIt2>
    void _distance(size_t* scores, size_t score_count, const detail::Range<InputIt2>& s2,
                   size_t score_cutoff = std::numeric_limits<size_t>::max()) 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);
        RAPIDFUZZ_IF_CONSTEXPR (MaxLen == 8)
            detail::osa_hyrroe2003_simd<uint8_t>(scores_, PM, str_lens, s2, score_cutoff);
        else RAPIDFUZZ_IF_CONSTEXPR (MaxLen == 16)
            detail::osa_hyrroe2003_simd<uint16_t>(scores_, PM, str_lens, s2, score_cutoff);
        else RAPIDFUZZ_IF_CONSTEXPR (MaxLen == 32)
            detail::osa_hyrroe2003_simd<uint32_t>(scores_, PM, str_lens, s2, score_cutoff);
        else RAPIDFUZZ_IF_CONSTEXPR (MaxLen == 64)
            detail::osa_hyrroe2003_simd<uint64_t>(scores_, PM, str_lens, s2, score_cutoff);
    }
 
    template <typename InputIt2>
    size_t maximum(size_t s1_idx, const detail::Range<InputIt2>& s2) const
    {
        return std::max(str_lens[s1_idx], s2.size());
    }
 
    size_t get_input_count() const noexcept
    {
        return input_count;
    }
 
    size_t input_count;
    size_t pos = 0;
    detail::BlockPatternMatchVector PM;
    std::vector<size_t> str_lens;
};
} /* namespace experimental */
#endif
 
template <typename CharT1>
struct CachedOSA
    : public detail::CachedDistanceBase<CachedOSA<CharT1>, size_t, 0, std::numeric_limits<int64_t>::max()> {
    template <typename Sentence1>
    explicit CachedOSA(const Sentence1& s1_) : CachedOSA(detail::to_begin(s1_), detail::to_end(s1_))
    {}
 
    template <typename InputIt1>
    CachedOSA(InputIt1 first1, InputIt1 last1) : s1(first1, last1), PM(detail::make_range(first1, last1))
    {}
 
private:
    friend detail::CachedDistanceBase<CachedOSA<CharT1>, size_t, 0, std::numeric_limits<int64_t>::max()>;
    friend detail::CachedNormalizedMetricBase<CachedOSA<CharT1>>;
 
    template <typename InputIt2>
    size_t maximum(const detail::Range<InputIt2>& s2) const
    {
        return std::max(s1.size(), s2.size());
    }
 
    template <typename InputIt2>
    size_t _distance(const detail::Range<InputIt2>& s2, size_t score_cutoff, size_t) const
    {
        size_t res;
        if (s1.empty())
            res = s2.size();
        else if (s2.empty())
            res = s1.size();
        else if (s1.size() < 64)
            res = detail::osa_hyrroe2003(PM, detail::make_range(s1), s2, score_cutoff);
        else
            res = detail::osa_hyrroe2003_block(PM, detail::make_range(s1), s2, score_cutoff);
 
        return (res <= score_cutoff) ? res : score_cutoff + 1;
    }
 
    std::vector<CharT1> s1;
    detail::BlockPatternMatchVector PM;
};
 
#ifdef RAPIDFUZZ_DEDUCTION_GUIDES
template <typename Sentence1>
CachedOSA(const Sentence1& s1_) -> CachedOSA<char_type<Sentence1>>;
 
template <typename InputIt1>
CachedOSA(InputIt1 first1, InputIt1 last1) -> CachedOSA<iter_value_t<InputIt1>>;
#endif
 
} // namespace rapidfuzz