o °#¨e°ã@sŽddlmZddlmZmZmZddlmZddlm Z dd d „Z d d d œddd„Z d d d œddd„Z d d d œddd„Z d d d œddd„Zd S)é)Ú annotations)ÚCallableÚHashableÚSequence)Úconv_sequences)Úis_noneÚs1úSequence[Hashable]Ús2ÚreturnÚintcCs°tt|ƒt|ƒƒd}i}|j}t|ƒd}|g|}|g|}tt|ƒƒ}||d<tdt|ƒdƒD]ž} ||}}d} |d} | |d<|} tdt|ƒdƒD]y} || d|| d|| dk}|| dd}|| d}t|||ƒ}|| d|| dkr| } || d|| <| } n0||| ddƒ}| }| |dkr¯|| | |}t||ƒ}n| |dkrÀ| | |}t||ƒ}|| } ||| <qO| ||| d<q3|t|ƒS)Néééÿÿÿÿr)ÚmaxÚlenÚgetÚlistÚrangeÚmin)rr ÚmaxValÚ last_row_idÚlast_row_id_getÚsizeÚFRÚR1ÚRÚiÚ last_col_idÚ last_i2l1ÚTÚjÚdiagÚleftÚupÚtempÚkÚlÚ transpose©r)úW/var/www/myenv/lib/python3.10/site-packages/rapidfuzz/distance/DamerauLevenshtein_py.pyÚ"_damerau_levenshtein_distance_zhao sF     $         r+N)Ú processorÚ score_cutoffr,ú(Callable[..., Sequence[Hashable]] | Noner-ú int | NonecCsL|dur ||ƒ}||ƒ}t||ƒ\}}t||ƒ}|dus ||kr"|S|dS)a« Calculates the Damerau-Levenshtein distance. Parameters ---------- s1 : Sequence[Hashable] First string to compare. s2 : Sequence[Hashable] Second string to compare. processor: callable, optional Optional callable that is used to preprocess the strings before comparing them. Default is None, which deactivates this behaviour. score_cutoff : int, optional Maximum distance between s1 and s2, that is considered as a result. If the distance is bigger than score_cutoff, score_cutoff + 1 is returned instead. Default is None, which deactivates this behaviour. Returns ------- distance : int distance between s1 and s2 Examples -------- Find the Damerau-Levenshtein distance between two strings: >>> from rapidfuzz.distance import DamerauLevenshtein >>> DamerauLevenshtein.distance("CA", "ABC") 2 Nr )rr+)rr r,r-Údistr)r)r*Údistance:s & r1cCsb|dur ||ƒ}||ƒ}t||ƒ\}}tt|ƒt|ƒƒ}t||ƒ}||}|dus-||kr/|SdS)a* Calculates the Damerau-Levenshtein similarity in the range [max, 0]. This is calculated as ``max(len1, len2) - distance``. Parameters ---------- s1 : Sequence[Hashable] First string to compare. s2 : Sequence[Hashable] Second string to compare. processor: callable, optional Optional callable that is used to preprocess the strings before comparing them. Default is None, which deactivates this behaviour. score_cutoff : int, optional Maximum distance between s1 and s2, that is considered as a result. If the similarity is smaller than score_cutoff, 0 is returned instead. Default is None, which deactivates this behaviour. Returns ------- similarity : int similarity between s1 and s2 Nr)rrrr1)rr r,r-Úmaximumr0Úsimr)r)r*Ú similarityis  r4ú float | NoneÚfloatcCs~t|ƒst|ƒr dS|dur||ƒ}||ƒ}t||ƒ\}}tt|ƒt|ƒƒ}t||ƒ}|r1||nd}|dus;||kr=|SdS)a@ Calculates a normalized Damerau-Levenshtein distance in the range [1, 0]. This is calculated as ``distance / max(len1, len2)``. Parameters ---------- s1 : Sequence[Hashable] First string to compare. s2 : Sequence[Hashable] Second string to compare. processor: callable, optional Optional callable that is used to preprocess the strings before comparing them. Default is None, which deactivates this behaviour. score_cutoff : float, optional Optional argument for a score threshold as a float between 0 and 1.0. For norm_dist > score_cutoff 1.0 is returned instead. Default is 1.0, which deactivates this behaviour. Returns ------- norm_dist : float normalized distance between s1 and s2 as a float between 0 and 1.0 çð?Nrr )rrrrr1)rr r,r-r2r0Ú norm_distr)r)r*Únormalized_distance”s r9cCsdt|ƒst|ƒr dS|dur||ƒ}||ƒ}t||ƒ\}}t||ƒ}d|}|dus.||kr0|SdS)a: Calculates a normalized Damerau-Levenshtein similarity in the range [0, 1]. This is calculated as ``1 - normalized_distance`` Parameters ---------- s1 : Sequence[Hashable] First string to compare. s2 : Sequence[Hashable] Second string to compare. processor: callable, optional Optional callable that is used to preprocess the strings before comparing them. Default is None, which deactivates this behaviour. score_cutoff : float, optional Optional argument for a score threshold as a float between 0 and 1.0. For norm_sim < score_cutoff 0 is returned instead. Default is 0, which deactivates this behaviour. Returns ------- norm_sim : float normalized similarity between s1 and s2 as a float between 0 and 1.0 gNr7r)rrr9)rr r,r-r8Únorm_simr)r)r*Únormalized_similarityÁs r;)rr r r r r ) rr r r r,r.r-r/r r ) rr r r r,r.r-r5r r6)Ú __future__rÚtypingrrrÚrapidfuzz._common_pyrÚrapidfuzz._utilsrr+r1r4r9r;r)r)r)r*Ús"    2û3û/û1û