Of$&SSKJrJr "SS\S9rg))ABCMetaabstractmethodc\rSrSrSrSrSrSSjrSr\ S5r Sr \ SS j5r S r S rS rS rSrSrSrSr\\S55rSrg)Feature a 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 SUlUc4[[UVs1sHn[U5iM sn55UlO(X:a[e[[ XS-55UlURR=(d URRUl gs snf![a n[ SRX55UeSnAff=f)a| 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 Nz2illegal interval specification: (start={}, end={})) positionstuplesortedint TypeErrorrange ValueErrorformat __class__ PROPERTY_NAME__name__)selfr endies 2/usr/lib/python3/dist-packages/nltk/tbl/feature.py__init__Feature.__init__#sP ;"69*E9a3q69*E#FGDN ?#O!&uYa'@!A"^^99TT^^=T=T+F   HOO!  sB 'B%% C/C  CcUR$N)r rs rencode_json_objFeature.encode_json_obj^s ~~cUnU"U5$r)clsobjr s rdecode_json_objFeature.decode_json_objas 9~r!cbURRS[UR5<S3$)N())rrlistr rs r__repr__Feature.__repr__fs*..))*!D,@+C1EEr!c^[SU55(d[SU35eU4SjU5nUVs/sHoS(aSU;aMU"U5PM sn$s snf)a Return a list of features, one for each start point in starts and for each window length in winlen. If excludezero is True, no Features containing 0 in its positions will be generated (many tbl trainers have a special representation for the target feature at [0]) For instance, importing a concrete subclass (Feature is abstract) >>> from nltk.tag.brill import Word First argument gives the possible start positions, second the possible window lengths >>> Word.expand([-3,-2,-1], [1]) [Word([-3]), Word([-2]), Word([-1])] >>> Word.expand([-2,-1], [1]) [Word([-2]), Word([-1])] >>> Word.expand([-3,-2,-1], [1,2]) [Word([-3]), Word([-2]), Word([-1]), Word([-3, -2]), Word([-2, -1])] >>> Word.expand([-2,-1], [1]) [Word([-2]), Word([-1])] A third optional argument excludes all Features whose positions contain zero >>> Word.expand([-2,-1,0], [1,2], excludezero=False) [Word([-2]), Word([-1]), Word([0]), Word([-2, -1]), Word([-1, 0])] >>> Word.expand([-2,-1,0], [1,2], excludezero=True) [Word([-2]), Word([-1]), Word([-2, -1])] All window lengths must be positive >>> Word.expand([-2,-1], [0]) Traceback (most recent call last): File "", line 1, in File "nltk/tag/tbl/template.py", line 371, in expand :param starts: where to start looking for Feature ValueError: non-positive window length in [0] :param starts: where to start looking for Feature :type starts: list of ints :param winlens: window lengths where to look for Feature :type starts: list of ints :param excludezero: do not output any Feature with 0 in any of its positions. :type excludezero: bool :returns: list of Features :raises ValueError: for non-positive window lengths c3*# UH oS:v M g7f)rNr#).0xs r !Feature.expand..s*'Qq5'sznon-positive window length in c3v># UH.n[[T5U- S-5H nTX"U-v M M0 g7f)r N)rlen)r0wrstartss rr2r3s7 UA%F aRS@S:TQfQQ:Ts69r)allr)r$r7winlens excludezeroxsr1s ` rexpandFeature.expandisZl*'***=gYGH H U U "C1;16ACCCs A AcURURL=(a+ [UR5[UR5:$)a Return True if this Feature always returns True when other does More precisely, return True if this feature refers to the same property as other; and this Feature looks at all positions that other does (and possibly other positions in addition). #For instance, importing a concrete subclass (Feature is abstract) >>> from nltk.tag.brill import Word, Pos >>> Word([-3,-2,-1]).issuperset(Word([-3,-2])) True >>> Word([-3,-2,-1]).issuperset(Word([-3,-2, 0])) False #Feature subclasses must agree >>> Word([-3,-2,-1]).issuperset(Pos([-3,-2])) False :param other: feature with which to compare :type other: (subclass of) Feature :return: True if this feature is superset, otherwise False :rtype: bool )rsetr rothers r issupersetFeature.issupersets=8~~0 S5HC OOM 6  r!c[URURL=(a+ [UR5[UR5-5$)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?r r@s r intersectsFeature.intersectss@: NNeoo - ;DNN#c%//&::  r!crURURL=(a URUR:H$r)rr r@s r__eq__Feature.__eq__s'~~0VT^^u5VVr!cURRURR:=(d URUR:$r)rrr r@s r__lt__Feature.__lt__s: NN # #eoo&>&> > - NNU__ ,  r!c X:X+$rr#r@s r__ne__Feature.__ne__s ""r!c X:$rr#r@s r__gt__Feature.__gt__s |r!c X:+$rr#r@s r__ge__Feature.__ge__s r!c X:=(d X:H$rr#r@s r__le__Feature.__le__s|,t},r!cg)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 rextract_propertyFeature.extract_propertysr!)rr r)F)r __module__ __qualname____firstlineno____doc__json_tagrrr classmethodr&r,r<rBrFrIrLrOrRrUrX staticmethodrr]__static_attributes__r#r!rrr s$"HM9UvF8D8Dt @  HW # -    r!r) metaclassN)abcrrrr#r!rris(~ ~ r!