reformat

Author: maxbachmann

rapidfuzz/distance/JaroWinkler.hpp

@@ -200,11 +200,11 @@ struct CachedJaroWinkler : public detail::CachedSimilarityBase<CachedJaroWinkler
 };
 
 template <typename Sentence1>
-explicit CachedJaroWinkler(const Sentence1& s1_, double _prefix_weight = 0.1)
-    -> CachedJaroWinkler<char_type<Sentence1>>;
+explicit CachedJaroWinkler(const Sentence1& s1_,
+                           double _prefix_weight = 0.1) -> CachedJaroWinkler<char_type<Sentence1>>;
 
 template <typename InputIt1>
-CachedJaroWinkler(InputIt1 first1, InputIt1 last1, double _prefix_weight = 0.1)
-    -> CachedJaroWinkler<iter_value_t<InputIt1>>;
+CachedJaroWinkler(InputIt1 first1, InputIt1 last1,
+                  double _prefix_weight = 0.1) -> CachedJaroWinkler<iter_value_t<InputIt1>>;
 
 } // namespace rapidfuzz

rapidfuzz/distance/Jaro_impl.hpp

@@ -296,7 +296,8 @@ static inline size_t count_transpositions_block(const BlockPatternMatchVector& P
 
             uint64_t PatternFlagMask = blsi(P_flag);
 
-            Transpositions += !(PM.get(PatternWord, T_first[static_cast<ptrdiff_t>(countr_zero(T_flag))]) & PatternFlagMask);
+            Transpositions += !(PM.get(PatternWord, T_first[static_cast<ptrdiff_t>(countr_zero(T_flag))]) &
+                                PatternFlagMask);
 
             T_flag = blsr(T_flag);
             P_flag ^= PatternFlagMask;
@@ -649,7 +650,9 @@ jaro_similarity_simd_long_s2(Range<double*> scores, const detail::BlockPatternMa
 
         for (size_t i = 0; i < vec_width; ++i) {
             size_t CommonChars = static_cast<size_t>(counts[i]);
-            if (!jaro_common_char_filter(static_cast<size_t>(s1_lengths[result_index]), s2.size(), CommonChars, score_cutoff)) {
+            if (!jaro_common_char_filter(static_cast<size_t>(s1_lengths[result_index]), s2.size(),
+                                         CommonChars, score_cutoff))
+            {
                 scores[result_index] = 0.0;
                 result_index++;
                 continue;
@@ -683,8 +686,8 @@ jaro_similarity_simd_long_s2(Range<double*> scores, const detail::BlockPatternMa
                 }
             }
 
-            double Sim =
-                jaro_calculate_similarity(static_cast<size_t>(s1_lengths[result_index]), s2.size(), CommonChars, Transpositions);
+            double Sim = jaro_calculate_similarity(static_cast<size_t>(s1_lengths[result_index]), s2.size(),
+                                                   CommonChars, Transpositions);
 
             scores[result_index] = (Sim >= score_cutoff) ? Sim : 0;
             result_index++;
@@ -760,7 +763,9 @@ jaro_similarity_simd_short_s2(Range<double*> scores, const detail::BlockPatternM
         T_flag.store(T_flags.data());
         for (size_t i = 0; i < vec_width; ++i) {
             size_t CommonChars = static_cast<size_t>(counts[i]);
-            if (!jaro_common_char_filter(static_cast<size_t>(s1_lengths[result_index]), s2.size(), CommonChars, score_cutoff)) {
+            if (!jaro_common_char_filter(static_cast<size_t>(s1_lengths[result_index]), s2.size(),
+                                         CommonChars, score_cutoff))
+            {
                 scores[result_index] = 0.0;
                 result_index++;
                 continue;
@@ -783,8 +788,8 @@ jaro_similarity_simd_short_s2(Range<double*> scores, const detail::BlockPatternM
                 P_flag_cur ^= PatternFlagMask;
             }
 
-            double Sim =
-                jaro_calculate_similarity(static_cast<size_t>(s1_lengths[result_index]), s2.size(), CommonChars, Transpositions);
+            double Sim = jaro_calculate_similarity(static_cast<size_t>(s1_lengths[result_index]), s2.size(),
+                                                   CommonChars, Transpositions);
 
             scores[result_index] = (Sim >= score_cutoff) ? Sim : 0;
             result_index++;

rapidfuzz/distance/LCSseq_impl.hpp

@@ -188,8 +188,8 @@ void lcs_simd(Range<size_t*> scores, const BlockPatternMatchVector& block, const
 #endif
 
 template <size_t N, bool RecordMatrix, typename PMV, typename InputIt1, typename InputIt2>
-auto lcs_unroll(const PMV& block, const Range<InputIt1>&, const Range<InputIt2>& s2, size_t score_cutoff = 0)
-    -> LCSseqResult<RecordMatrix>
+auto lcs_unroll(const PMV& block, const Range<InputIt1>&, const Range<InputIt2>& s2,
+                size_t score_cutoff = 0) -> LCSseqResult<RecordMatrix>
 {
     uint64_t S[N];
     unroll<size_t, N>([&](size_t i) { S[i] = ~UINT64_C(0); });

rapidfuzz/distance/Levenshtein.hpp

@@ -482,11 +482,11 @@ struct CachedLevenshtein : public detail::CachedDistanceBase<CachedLevenshtein<C
 };
 
 template <typename Sentence1>
-explicit CachedLevenshtein(const Sentence1& s1_, LevenshteinWeightTable aWeights = {1, 1, 1})
-    -> CachedLevenshtein<char_type<Sentence1>>;
+explicit CachedLevenshtein(const Sentence1& s1_, LevenshteinWeightTable aWeights = {
+                                                     1, 1, 1}) -> CachedLevenshtein<char_type<Sentence1>>;
 
 template <typename InputIt1>
-CachedLevenshtein(InputIt1 first1, InputIt1 last1, LevenshteinWeightTable aWeights = {1, 1, 1})
-    -> CachedLevenshtein<iter_value_t<InputIt1>>;
+CachedLevenshtein(InputIt1 first1, InputIt1 last1,
+                  LevenshteinWeightTable aWeights = {1, 1, 1}) -> CachedLevenshtein<iter_value_t<InputIt1>>;
 
 } // namespace rapidfuzz