U e?S @sddlZddlmZddlmZddlmZddlm Z ddZGdd d Z d d Z d.ddZ e dZd/ddZddZd0ddZddZe dejZe dZddZd d!d"d#d$d%d&d'd(g d fd)d*Zd+d,Zed-kredS)1N)accuracy)map_tag) str2tuple)TreecCsBg}g}|D]*}||}|t|7}|t|7}q t||S)a| Score the accuracy of the chunker against the gold standard. Strip the chunk information from the gold standard and rechunk it using the chunker, then compute the accuracy score. :type chunker: ChunkParserI :param chunker: The chunker being evaluated. :type gold: tree :param gold: The chunk structures to score the chunker on. :rtype: float )parseflattentree2conlltags _accuracy)ZchunkerZgoldZ gold_tagsZ test_tagsZ gold_treeZ test_treer P/var/www/html/assets/scripts/venv/lib/python3.8/site-packages/nltk/chunk/util.pyrs  rc@seZdZdZddZddZddZdd Zd d Zd d Z d ddZ ddZ ddZ ddZ ddZddZddZddZdS)! ChunkScorea; A utility class for scoring chunk parsers. ``ChunkScore`` can evaluate a chunk parser's output, based on a number of statistics (precision, recall, f-measure, misssed chunks, incorrect chunks). It can also combine the scores from the parsing of multiple texts; this makes it significantly easier to evaluate a chunk parser that operates one sentence at a time. Texts are evaluated with the ``score`` method. The results of evaluation can be accessed via a number of accessor methods, such as ``precision`` and ``f_measure``. A typical use of the ``ChunkScore`` class is:: >>> chunkscore = ChunkScore() # doctest: +SKIP >>> for correct in correct_sentences: # doctest: +SKIP ... guess = chunkparser.parse(correct.leaves()) # doctest: +SKIP ... chunkscore.score(correct, guess) # doctest: +SKIP >>> print('F Measure:', chunkscore.f_measure()) # doctest: +SKIP F Measure: 0.823 :ivar kwargs: Keyword arguments: - max_tp_examples: The maximum number actual examples of true positives to record. This affects the ``correct`` member function: ``correct`` will not return more than this number of true positive examples. This does *not* affect any of the numerical metrics (precision, recall, or f-measure) - max_fp_examples: The maximum number actual examples of false positives to record. This affects the ``incorrect`` member function and the ``guessed`` member function: ``incorrect`` will not return more than this number of examples, and ``guessed`` will not return more than this number of true positive examples. This does *not* affect any of the numerical metrics (precision, recall, or f-measure) - max_fn_examples: The maximum number actual examples of false negatives to record. This affects the ``missed`` member function and the ``correct`` member function: ``missed`` will not return more than this number of examples, and ``correct`` will not return more than this number of true negative examples. This does *not* affect any of the numerical metrics (precision, recall, or f-measure) - chunk_label: A regular expression indicating which chunks should be compared. Defaults to ``'.*'`` (i.e., all chunks). :type _tp: list(Token) :ivar _tp: List of true positives :type _fp: list(Token) :ivar _fp: List of false positives :type _fn: list(Token) :ivar _fn: List of false negatives :type _tp_num: int :ivar _tp_num: Number of true positives :type _fp_num: int :ivar _fp_num: Number of false positives :type _fn_num: int :ivar _fn_num: Number of false negatives. cKst|_t|_t|_t|_t|_|dd|_|dd|_|dd|_ |dd|_ d|_ d|_ d|_ d|_d|_d|_d |_dS) NZmax_tp_examplesdZmax_fp_examplesZmax_fn_examples chunk_labelz.*rgF)set_correct_guessed_tp_fp_fngetZ_max_tpZ_max_fpZ_max_fn _chunk_label_tp_num_fp_num_fn_num_count _tags_correct _tags_total_measuresNeedUpdate)selfkwargsr r r __init__rs zChunkScore.__init__cCs^|jrZ|j|j@|_|j|j|_|j|j|_t|j|_t|j|_t|j|_ d|_dS)NF) rrrrrrlenrrrrr r r _updateMeasuress   zChunkScore._updateMeasurescCs|jt||j|jO_|jt||j|jO_|jd7_d|_zt|}t|}Wntk rxd}}YnX|jt |7_|j t ddt ||D7_ dS)aU Given a correctly chunked sentence, score another chunked version of the same sentence. :type correct: chunk structure :param correct: The known-correct ("gold standard") chunked sentence. :type guessed: chunk structure :param guessed: The chunked sentence to be scored. Tr css|]\}}||krdVqdS)r$Nr ).0tgr r r sz#ChunkScore.score..N) r _chunksetsrrrrr ValueErrorrr!rsumzip)rcorrectguessedZ correct_tagsZ guessed_tagsr r r scores  zChunkScore.scorecCs|jdkrdS|j|jS)z Return the overall tag-based accuracy for all text that have been scored by this ``ChunkScore``, using the IOB (conll2000) tag encoding. :rtype: float rr$)rrr"r r r rs zChunkScore.accuracycCs.||j|j}|dkr dS|j|SdS)z Return the overall precision for all texts that have been scored by this ``ChunkScore``. :rtype: float rN)r#rrrdivr r r precisions  zChunkScore.precisioncCs.||j|j}|dkr dS|j|SdS)z Return the overall recall for all texts that have been scored by this ``ChunkScore``. :rtype: float rNr#rrr0r r r recalls  zChunkScore.recall?cCsD||}|}|dks(|dkr,dSd||d||S)a Return the overall F measure for all texts that have been scored by this ``ChunkScore``. :param alpha: the relative weighting of precision and recall. Larger alpha biases the score towards the precision value, while smaller alpha biases the score towards the recall value. ``alpha`` should have a value in the range [0,1]. :type alpha: float :rtype: float rr$)r#r2r4)ralphaprr r r f_measures zChunkScore.f_measurecCs |t|j}dd|DS)z Return the chunks which were included in the correct chunk structures, but not in the guessed chunk structures, listed in input order. :rtype: list of chunks cSsg|] }|dqSr$r r%cr r r sz%ChunkScore.missed..)r#listrrchunksr r r misseds zChunkScore.missedcCs |t|j}dd|DS)z Return the chunks which were included in the guessed chunk structures, but not in the correct chunk structures, listed in input order. :rtype: list of chunks cSsg|] }|dqSr:r r;r r r r=sz(ChunkScore.incorrect..)r#r>rr?r r r incorrects zChunkScore.incorrectcCst|j}dd|DS)z Return the chunks which were included in the correct chunk structures, listed in input order. :rtype: list of chunks cSsg|] }|dqSr:r r;r r r r=sz&ChunkScore.correct..)r>rr?r r r r-s zChunkScore.correctcCst|j}dd|DS)z Return the chunks which were included in the guessed chunk structures, listed in input order. :rtype: list of chunks cSsg|] }|dqSr:r r;r r r r=sz&ChunkScore.guessed..)r>rr?r r r r.s zChunkScore.guessedcCs||j|jS)Nr3r"r r r __len__szChunkScore.__len__cCsdtt|dS)z` Return a concise representation of this ``ChunkScoring``. :rtype: str z)reprr!r"r r r __repr__szChunkScore.__repr__cCs\dd|dddd|dddd|dddd|ddd S) a- Return a verbose representation of this ``ChunkScoring``. This representation includes the precision, recall, and f-measure scores. For other information about the score, use the accessor methods (e.g., ``missed()`` and ``incorrect()``). :rtype: str zChunkParse score: z IOB Accuracy: r z5.1fz%% z Precision: z Recall: z F-Measure: z%%)rr2r4r9r"r r r __str__s zChunkScore.__str__N)r5)__name__ __module__ __qualname____doc__r r#r/rr2r4r9rArBr-r.rCrErFr r r r r 3s>       r cCsdd}g}|D]N}t|trRt||r@|||f|f|t|7}q |d7}q t |S)Nrr$) isinstancerrematchlabelappendfreezer!leavesr)r&countrposr@childr r r r)2s  r)NPS/c Cs*td}t|gg}||D]}|} | ddkr|t|dkrXtd|dt|g} |d| || q | ddkrt|d krtd |d| q |d kr|d| q t | |\} } |r|rt ||| } |d| | fq t|dkr"td t|d|dS) aB Divide a string of bracketted tagged text into chunks and unchunked tokens, and produce a Tree. Chunks are marked by square brackets (``[...]``). Words are delimited by whitespace, and each word should have the form ``text/tag``. Words that do not contain a slash are assigned a ``tag`` of None. :param s: The string to be converted :type s: str :param chunk_label: The label to use for chunk nodes :type chunk_label: str :param root_label: The label to use for the root of the tree :type root_label: str :rtype: Tree z\[|\]|[^\[\]\s]+r[r$zUnexpected [ at char d]zUnexpected ] at char NzExpected ] at char ) rLcompilerfinditergroupr!r*startrOpoprr) sr root_labelsepZ source_tagsetZ target_tagsetZWORD_OR_BRACKETstackrMtextchunkwordtagr r r tagstr2tree?s.          rjz(\S+)\s+(\S+)\s+([IOB])-?(\S+)?rUPPZVPc Cst|gg}t|dD]\}}|s,qt|}|dkrNtd|d|\}}} } |dk rr| |krrd} | dko| |dk} | dks| rt |d kr| | d ks| rt| g} |d | | | |d ||fq|d S) a* Return a chunk structure for a single sentence encoded in the given CONLL 2000 style string. This function converts a CoNLL IOB string into a tree. It uses the specified chunk types (defaults to NP, PP and VP), and creates a tree rooted at a node labeled S (by default). :param s: The CoNLL string to be converted. :type s: str :param chunk_types: The chunk types to be converted. :type chunk_types: tuple :param root_label: The node label to use for the root. :type root_label: str :rtype: Tree  NzError on line rYOIrZZBOr\Br) r enumeratesplitstrip_LINE_RErMr*groupsrNr!rarO) rb chunk_typesrcrelinenolinerMrhristateZ chunk_typeZ mismatch_Irgr r r conllstr2treeus(       rzc Csg}|D]~}zL|}d}|D]6}t|tr4td||d|d||fd}qWqtk r||d|ddfYqXq|S)z Return a list of 3-tuples containing ``(word, tag, IOB-tag)``. Convert a tree to the CoNLL IOB tag format. :param t: The tree to be converted. :type t: Tree :rtype: list(tuple) B-z7Tree is too deeply nested to be printed in CoNLL formatrr$I-rn)rNrKrr*rOAttributeError)r&tagsrTcategoryprefixcontentsr r r rs    rFcCst|g}|D]\}}}|dkr>|r.tdn|||fq|drh|t|dd||fgq|drt|dkst|dtr|d|ddkr|rtdq|t|dd||fgn|d||fq|dkr|||fqtd |q|S) z1 Convert the CoNLL IOB format to a tree. NzBad conll tag sequencer{r\r|rrZrnzBad conll tag )rr*rO startswithr!rKrN)ZsentencervrcstricttreerhZpostagZchunktagr r r conlltags2trees.         rcCsddt|D}d|S)z Return a multiline string where each line contains a word, tag and IOB tag. Convert a tree to the CoNLL IOB string format :param t: The tree to be converted. :type t: Tree :rtype: str cSsg|]}d|qS) )join)r%tokenr r r r=sz!tree2conllstr..rm)rr)r&linesr r r tree2conllstrs ra\s*(\s*(?P.+?)\s*\s*)?(\s*(?P.+?)\s*\s*)?(\s*(?P.+?)\s*\s*)?\s*(\s*(?P.+?)\s*\s*)?(?P.*?)\s*\s*\s*z#]*?type="(?P\w+)"c Cst|gg}|dkrgStd|D]}|}zv|drt|}|dkrXtd|t|dg}|d|||n"|dr| n|d|Wq$t t fk r}zt d| dd |W5d}~XYq$Xq$t |d krt d |d S) Nz<[^>]+>|[^\s<]+z sX     3  5 $ #  +0