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bugfix in span similarity (#5155) (#5358)

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* bugfix in span similarity

* also rewrite doc.pyx for clarity

* formatting

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
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adrianeboyd 2020-04-27 16:51:27 +02:00 committed by GitHub
parent 9203d821ae
commit f8ac5b9f56
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3 changed files with 30 additions and 9 deletions
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18
spacy/tests/regression/test_issue5152.py Normal file
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@ -0,0 +1,18 @@
from spacy.lang.en import English
def test_issue5152():
# Test that the comparison between a Span and a Token, goes well
# There was a bug when the number of tokens in the span equaled the number of characters in the token (!)
nlp = English()
text = nlp("Talk about being boring!")
text_var = nlp("Talk of being boring!")
y = nlp("Let")
span = text[0:3] # Talk about being
span_2 = text[0:3] # Talk about being
span_3 = text_var[0:3] # Talk of being
token = y[0] # Let
assert span.similarity(token) == 0.0
assert span.similarity(span_2) == 1.0
assert span_2.similarity(span_3) < 1.0

15
spacy/tokens/doc.pyx
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@ -387,13 +387,14 @@ cdef class Doc:
if isinstance(other, (Lexeme, Token)) and self.length == 1:
if self.c[0].lex.orth == other.orth:
return 1.0
elif isinstance(other, (Span, Doc)):
if len(self) == len(other):
for i in range(self.length):
if self[i].orth != other[i].orth:
break
else:
return 1.0
elif isinstance(other, (Span, Doc)) and len(self) == len(other):
similar = True
for i in range(self.length):
if self[i].orth != other[i].orth:
similar = False
break
if similar:
return 1.0
if self.vocab.vectors.n_keys == 0:
models_warning(Warnings.W007.format(obj="Doc"))
if self.vector_norm == 0 or other.vector_norm == 0:

6
spacy/tokens/span.pyx
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@ -324,11 +324,13 @@ cdef class Span:
if len(self) == 1 and hasattr(other, "orth"):
if self[0].orth == other.orth:
return 1.0
elif hasattr(other, "__len__") and len(self) == len(other):
elif isinstance(other, (Doc, Span)) and len(self) == len(other):
similar = True
for i in range(len(self)):
if self[i].orth != getattr(other[i], "orth", None):
similar = False
break
else:
if similar:
return 1.0
if self.vocab.vectors.n_keys == 0:
models_warning(Warnings.W007.format(obj="Span"))