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# coding: utf-8
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from __future__ import unicode_literals
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from . . util import get_doc
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from . . . tokens import Doc
from . . . vocab import Vocab
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import pytest
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import numpy
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@pytest.mark.parametrize ( ' text ' , [ [ " one " , " two " , " three " ] ] )
def test_doc_api_compare_by_string_position ( en_vocab , text ) :
doc = get_doc ( en_vocab , text )
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# Get the tokens in this order, so their ID ordering doesn't match the idx
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token3 = doc [ - 1 ]
token2 = doc [ - 2 ]
token1 = doc [ - 1 ]
token1 , token2 , token3 = doc
assert token1 < token2 < token3
assert not token1 > token2
assert token2 > token1
assert token2 < = token3
assert token3 > = token1
def test_doc_api_getitem ( en_tokenizer ) :
text = " Give it back! He pleaded. "
tokens = en_tokenizer ( text )
assert tokens [ 0 ] . text == ' Give '
assert tokens [ - 1 ] . text == ' . '
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with pytest . raises ( IndexError ) :
tokens [ len ( tokens ) ]
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def to_str ( span ) :
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return ' / ' . join ( token . text for token in span )
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span = tokens [ 1 : 1 ]
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assert not to_str ( span )
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span = tokens [ 1 : 4 ]
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assert to_str ( span ) == ' it/back/! '
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span = tokens [ 1 : 4 : 1 ]
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assert to_str ( span ) == ' it/back/! '
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with pytest . raises ( ValueError ) :
tokens [ 1 : 4 : 2 ]
with pytest . raises ( ValueError ) :
tokens [ 1 : 4 : - 1 ]
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span = tokens [ - 3 : 6 ]
assert to_str ( span ) == ' He/pleaded '
span = tokens [ 4 : - 1 ]
assert to_str ( span ) == ' He/pleaded '
span = tokens [ - 5 : - 3 ]
assert to_str ( span ) == ' back/! '
span = tokens [ 5 : 4 ]
assert span . start == span . end == 5 and not to_str ( span )
span = tokens [ 4 : - 3 ]
assert span . start == span . end == 4 and not to_str ( span )
span = tokens [ : ]
assert to_str ( span ) == ' Give/it/back/!/He/pleaded/. '
span = tokens [ 4 : ]
assert to_str ( span ) == ' He/pleaded/. '
span = tokens [ : 4 ]
assert to_str ( span ) == ' Give/it/back/! '
span = tokens [ : - 3 ]
assert to_str ( span ) == ' Give/it/back/! '
span = tokens [ - 3 : ]
assert to_str ( span ) == ' He/pleaded/. '
span = tokens [ 4 : 50 ]
assert to_str ( span ) == ' He/pleaded/. '
span = tokens [ - 50 : 4 ]
assert to_str ( span ) == ' Give/it/back/! '
span = tokens [ - 50 : - 40 ]
assert span . start == span . end == 0 and not to_str ( span )
span = tokens [ 40 : 50 ]
assert span . start == span . end == 7 and not to_str ( span )
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span = tokens [ 1 : 4 ]
assert span [ 0 ] . orth_ == ' it '
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subspan = span [ : ]
assert to_str ( subspan ) == ' it/back/! '
subspan = span [ : 2 ]
assert to_str ( subspan ) == ' it/back '
subspan = span [ 1 : ]
assert to_str ( subspan ) == ' back/! '
subspan = span [ : - 1 ]
assert to_str ( subspan ) == ' it/back '
subspan = span [ - 2 : ]
assert to_str ( subspan ) == ' back/! '
subspan = span [ 1 : 2 ]
assert to_str ( subspan ) == ' back '
subspan = span [ - 2 : - 1 ]
assert to_str ( subspan ) == ' back '
subspan = span [ - 50 : 50 ]
assert to_str ( subspan ) == ' it/back/! '
subspan = span [ 50 : - 50 ]
assert subspan . start == subspan . end == 4 and not to_str ( subspan )
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@pytest.mark.parametrize ( ' text ' , [ " Give it back! He pleaded. " ,
" Give it back! He pleaded. " ] )
def test_doc_api_serialize ( en_tokenizer , text ) :
tokens = en_tokenizer ( text )
new_tokens = get_doc ( tokens . vocab ) . from_bytes ( tokens . to_bytes ( ) )
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assert tokens . text == new_tokens . text
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assert [ t . text for t in tokens ] == [ t . text for t in new_tokens ]
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assert [ t . orth for t in tokens ] == [ t . orth for t in new_tokens ]
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def test_doc_api_set_ents ( en_tokenizer ) :
text = " I use goggle chrone to surf the web "
tokens = en_tokenizer ( text )
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assert len ( tokens . ents ) == 0
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tokens . ents = [ ( tokens . vocab . strings [ ' PRODUCT ' ] , 2 , 4 ) ]
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assert len ( list ( tokens . ents ) ) == 1
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assert [ t . ent_iob for t in tokens ] == [ 0 , 0 , 3 , 1 , 0 , 0 , 0 , 0 ]
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assert tokens . ents [ 0 ] . label_ == ' PRODUCT '
assert tokens . ents [ 0 ] . start == 2
assert tokens . ents [ 0 ] . end == 4
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def test_doc_api_merge ( en_tokenizer ) :
text = " WKRO played songs by the beach boys all night "
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# merge 'The Beach Boys'
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doc = en_tokenizer ( text )
assert len ( doc ) == 9
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doc . merge ( doc [ 4 ] . idx , doc [ 6 ] . idx + len ( doc [ 6 ] ) , ' NAMED ' , ' LEMMA ' , ' TYPE ' )
assert len ( doc ) == 7
assert doc [ 4 ] . text == ' the beach boys '
assert doc [ 4 ] . text_with_ws == ' the beach boys '
assert doc [ 4 ] . tag_ == ' NAMED '
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# merge 'all night'
doc = en_tokenizer ( text )
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assert len ( doc ) == 9
doc . merge ( doc [ 7 ] . idx , doc [ 8 ] . idx + len ( doc [ 8 ] ) , ' NAMED ' , ' LEMMA ' , ' TYPE ' )
assert len ( doc ) == 8
assert doc [ 7 ] . text == ' all night '
assert doc [ 7 ] . text_with_ws == ' all night '
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def test_doc_api_merge_children ( en_tokenizer ) :
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""" Test that attachments work correctly after merging. """
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text = " WKRO played songs by the beach boys all night "
doc = en_tokenizer ( text )
assert len ( doc ) == 9
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doc . merge ( doc [ 4 ] . idx , doc [ 6 ] . idx + len ( doc [ 6 ] ) , ' NAMED ' , ' LEMMA ' , ' TYPE ' )
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for word in doc :
if word . i < word . head . i :
assert word in list ( word . head . lefts )
elif word . i > word . head . i :
assert word in list ( word . head . rights )
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def test_doc_api_merge_hang ( en_tokenizer ) :
text = " through North and South Carolina "
doc = en_tokenizer ( text )
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doc . merge ( 18 , 32 , ' ' , ' ' , ' ORG ' )
doc . merge ( 8 , 32 , ' ' , ' ' , ' ORG ' )
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def test_doc_api_sents_empty_string ( en_tokenizer ) :
doc = en_tokenizer ( " " )
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doc . is_parsed = True
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sents = list ( doc . sents )
assert len ( sents ) == 0
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def test_doc_api_runtime_error ( en_tokenizer ) :
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# Example that caused run-time error while parsing Reddit
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text = " 67 % o f black households are single parent \n \n 72 % o f all black babies born out of wedlock \n \n 50 % o f all black kids don \u2019 t finish high school "
deps = [ ' nsubj ' , ' prep ' , ' amod ' , ' pobj ' , ' ROOT ' , ' amod ' , ' attr ' , ' ' ,
' nummod ' , ' prep ' , ' det ' , ' amod ' , ' pobj ' , ' acl ' , ' prep ' , ' prep ' ,
' pobj ' , ' ' , ' nummod ' , ' prep ' , ' det ' , ' amod ' , ' pobj ' , ' aux ' , ' neg ' ,
' ROOT ' , ' amod ' , ' dobj ' ]
tokens = en_tokenizer ( text )
doc = get_doc ( tokens . vocab , [ t . text for t in tokens ] , deps = deps )
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nps = [ ]
for np in doc . noun_chunks :
while len ( np ) > 1 and np [ 0 ] . dep_ not in ( ' advmod ' , ' amod ' , ' compound ' ) :
np = np [ 1 : ]
if len ( np ) > 1 :
nps . append ( ( np . start_char , np . end_char , np . root . tag_ , np . text , np . root . ent_type_ ) )
for np in nps :
doc . merge ( * np )
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def test_doc_api_right_edge ( en_tokenizer ) :
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""" Test for bug occurring from Unshift action, causing incorrect right edge """
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text = " I have proposed to myself, for the sake of such as live under the government of the Romans, to translate those books into the Greek tongue. "
heads = [ 2 , 1 , 0 , - 1 , - 1 , - 3 , 15 , 1 , - 2 , - 1 , 1 , - 3 , - 1 , - 1 , 1 , - 2 , - 1 , 1 ,
- 2 , - 7 , 1 , - 19 , 1 , - 2 , - 3 , 2 , 1 , - 3 , - 26 ]
tokens = en_tokenizer ( text )
doc = get_doc ( tokens . vocab , [ t . text for t in tokens ] , heads = heads )
assert doc [ 6 ] . text == ' for '
subtree = [ w . text for w in doc [ 6 ] . subtree ]
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assert subtree == [ ' for ' , ' the ' , ' sake ' , ' of ' , ' such ' , ' as ' ,
' live ' , ' under ' , ' the ' , ' government ' , ' of ' , ' the ' , ' Romans ' , ' , ' ]
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assert doc [ 6 ] . right_edge . text == ' , '
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def test_doc_api_has_vector ( ) :
vocab = Vocab ( )
vocab . clear_vectors ( 2 )
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vocab . vectors . add ( ' kitten ' , vector = numpy . asarray ( [ 0. , 2. ] , dtype = ' f ' ) )
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doc = Doc ( vocab , words = [ ' kitten ' ] )
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assert doc . has_vector
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def test_lowest_common_ancestor ( en_tokenizer ) :
tokens = en_tokenizer ( ' the lazy dog slept ' )
doc = get_doc ( tokens . vocab , [ t . text for t in tokens ] , heads = [ 2 , 1 , 1 , 0 ] )
lca = doc . get_lca_matrix ( )
assert ( lca [ 1 , 1 ] == 1 )
assert ( lca [ 0 , 1 ] == 2 )
assert ( lca [ 1 , 2 ] == 2 )
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def test_parse_tree ( en_tokenizer ) :
""" Tests doc.print_tree() method. """
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text = ' I like New York in Autumn. '
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heads = [ 1 , 0 , 1 , - 2 , - 3 , - 1 , - 5 ]
tags = [ ' PRP ' , ' IN ' , ' NNP ' , ' NNP ' , ' IN ' , ' NNP ' , ' . ' ]
tokens = en_tokenizer ( text )
doc = get_doc ( tokens . vocab , [ t . text for t in tokens ] , heads = heads , tags = tags )
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# full method parse_tree(text) is a trivial composition
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trees = doc . print_tree ( )
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assert len ( trees ) > 0
tree = trees [ 0 ]
assert all ( k in list ( tree . keys ( ) ) for k in [ ' word ' , ' lemma ' , ' NE ' , ' POS_fine ' , ' POS_coarse ' , ' arc ' , ' modifiers ' ] )
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assert tree [ ' word ' ] == ' like ' # check root is correct