Ng$4ddlmZmZGddeZdS))ABCMetaabstractmethodceZdZdZdZdZddZdZedZ dZ edd Z d Z d Z d Zd ZdZdZdZdZeedZdS)Featurea An abstract base class for Features. A Feature is a combination of a specific property-computing method and a list of relative positions to apply that method to. The property-computing method, M{extract_property(tokens, index)}, must be implemented by every subclass. It extracts or computes a specific property for the token at the current index. Typical extract_property() methods return features such as the token text or tag; but more involved methods may consider the entire sequence M{tokens} and for instance compute the length of the sentence the token belongs to. In addition, the subclass may have a PROPERTY_NAME, which is how it will be printed (in Rules and Templates, etc). If not given, defaults to the classname. znltk.tbl.FeatureNc~d|_|,ttd|D|_nj ||krttt ||dz|_n6#t$r)}t d|||d}~wwxYw|jjp |jj |_dS)al Construct a Feature which may apply at C{positions}. >>> # For instance, importing some concrete subclasses (Feature is abstract) >>> from nltk.tag.brill import Word, Pos >>> # Feature Word, applying at one of [-2, -1] >>> Word([-2,-1]) Word([-2, -1]) >>> # Positions need not be contiguous >>> Word([-2,-1, 1]) Word([-2, -1, 1]) >>> # Contiguous ranges can alternatively be specified giving the >>> # two endpoints (inclusive) >>> Pos(-3, -1) Pos([-3, -2, -1]) >>> # In two-arg form, start <= end is enforced >>> Pos(2, 1) Traceback (most recent call last): File "", line 1, in File "nltk/tbl/template.py", line 306, in __init__ raise TypeError ValueError: illegal interval specification: (start=2, end=1) :type positions: list of int :param positions: the positions at which this features should apply :raises ValueError: illegal position specifications An alternative calling convention, for contiguous positions only, is Feature(start, end): :type start: int :param start: start of range where this feature should apply :type end: int :param end: end of range (NOTE: inclusive!) where this feature should apply Nc,h|]}t|S)int).0is L/var/www/html/ai-engine/env/lib/python3.11/site-packages/nltk/tbl/feature.py z#Feature.__init__..Ms*E*E*Ea3q66*E*E*Ez2illegal interval specification: (start={}, end={})) positionstuplesorted TypeErrorrange ValueErrorformat __class__ PROPERTY_NAME__name__)selfrendes r __init__zFeature.__init__#sP ;"6*E*E9*E*E*E#F#FGGDNN s??#O!&uYa'@'@!A!A    HOO!3  "^9TT^=Ts2A** B4$BBc|jSN)rrs r encode_json_objzFeature.encode_json_obj^s ~rc|}||Sr r )clsobjrs r decode_json_objzFeature.decode_json_objas s9~~rcJ|jjdt|jdS)N())rrlistrr!s r __repr__zFeature.__repr__fs(.)EED,@,@EEEErFctd|Dstd|fd|D}fd|DS)a Return a list of features, one for each start point in starts and for each window length in winlen. If excludezero is True, no Features containing 0 in its positions will be generated (many tbl trainers have a special representation for the target feature at [0]) For instance, importing a concrete subclass (Feature is abstract) >>> from nltk.tag.brill import Word First argument gives the possible start positions, second the possible window lengths >>> Word.expand([-3,-2,-1], [1]) [Word([-3]), Word([-2]), Word([-1])] >>> Word.expand([-2,-1], [1]) [Word([-2]), Word([-1])] >>> Word.expand([-3,-2,-1], [1,2]) [Word([-3]), Word([-2]), Word([-1]), Word([-3, -2]), Word([-2, -1])] >>> Word.expand([-2,-1], [1]) [Word([-2]), Word([-1])] A third optional argument excludes all Features whose positions contain zero >>> Word.expand([-2,-1,0], [1,2], excludezero=False) [Word([-2]), Word([-1]), Word([0]), Word([-2, -1]), Word([-1, 0])] >>> Word.expand([-2,-1,0], [1,2], excludezero=True) [Word([-2]), Word([-1]), Word([-2, -1])] All window lengths must be positive >>> Word.expand([-2,-1], [0]) Traceback (most recent call last): File "", line 1, in File "nltk/tag/tbl/template.py", line 371, in expand :param starts: where to start looking for Feature ValueError: non-positive window length in [0] :param starts: where to start looking for Feature :type starts: list of ints :param winlens: window lengths where to look for Feature :type starts: list of ints :param excludezero: do not output any Feature with 0 in any of its positions. :type excludezero: bool :returns: list of Features :raises ValueError: for non-positive window lengths c3"K|] }|dkV dS)rNr )r xs r z!Feature.expand..s&**Q1q5******rznon-positive window length in c3|K|]6}tt|z dzD]}|||zV7dS)rN)rlen)r wr startss r r/z!Feature.expand..sU U UA%F aRS@S:T:T U UQfQQY U U U U U U Urc2g|]}rd|v|S)rr )r r.r$ excludezeros r z"Feature.expand..s+CCC1;C166A666r)allr)r$r3winlensr5xss`` ` r expandzFeature.expandisul**'***** IGgGGHH H U U U U U U UCCCCCCCCCrcr|j|juo)t|jt|jkS)aQ Return True if this Feature always returns True when other does More precisely, return True if this feature refers to the same property as other; and this Feature looks at all positions that other does (and possibly other positions in addition). #For instance, importing a concrete subclass (Feature is abstract) >>> from nltk.tag.brill import Word, Pos >>> Word([-3,-2,-1]).issuperset(Word([-3,-2])) True >>> Word([-3,-2,-1]).issuperset(Word([-3,-2, 0])) False #Feature subclasses must agree >>> Word([-3,-2,-1]).issuperset(Pos([-3,-2])) False :param other: feature with which to compare :type other: (subclass of) Feature :return: True if this feature is superset, otherwise False :rtype: bool )rsetrrothers r issupersetzFeature.issupersets>8~0 S5H5HC OM M 6  rct|j|juo(t|jt|jzS)a Return True if the positions of this Feature intersects with those of other More precisely, return True if this feature refers to the same property as other; and there is some overlap in the positions they look at. #For instance, importing a concrete subclass (Feature is abstract) >>> from nltk.tag.brill import Word, Pos >>> Word([-3,-2,-1]).intersects(Word([-3,-2])) True >>> Word([-3,-2,-1]).intersects(Word([-3,-2, 0])) True >>> Word([-3,-2,-1]).intersects(Word([0])) False #Feature subclasses must agree >>> Word([-3,-2,-1]).intersects(Pos([-3,-2])) False :param other: feature with which to compare :type other: (subclass of) Feature :return: True if feature classes agree and there is some overlap in the positions they look at :rtype: bool )boolrr<rr=s r intersectszFeature.intersectssC: Neo - ;DN##c%/&:&::   rc>|j|juo|j|jkSr )rrr=s r __eq__zFeature.__eq__s~0VT^u5VVrcV|jj|jjkp|j|jkSr )rrrr=s r __lt__zFeature.__lt__s, N #eo&> > - NU_ ,  rc||k Sr r r=s r __ne__zFeature.__ne__sEM""rc||kSr r r=s r __gt__zFeature.__gt__s t|rc||k Sr r r=s r __ge__zFeature.__ge__s%<rc||kp||kSr r r=s r __le__zFeature.__le__se|,tu},rcdS)a@ Any subclass of Feature must define static method extract_property(tokens, index) :param tokens: the sequence of tokens :type tokens: list of tokens :param index: the current index :type index: int :return: feature value :rtype: any (but usually scalar) Nr )tokensindexs r extract_propertyzFeature.extract_propertysrr )F)r __module__ __qualname____doc__json_tagrrr" classmethodr&r+r:r?rBrDrFrHrJrLrN staticmethodrrRr rr rr sF$"HM9U9U9U9Uv[FFF8D8D8D[8Dt   @    HWWW   ###   ---   ^\    rr) metaclassN)abcrrrr rr r[sc('''''''~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ r