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Update docstrings and API docs for Span

This commit is contained in:
ines 2017-05-19 18:47:46 +02:00
parent 23f9a3ccc8
commit 62ceec4fc6
2 changed files with 93 additions and 52 deletions
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31
spacy/tokens/span.pyx
View File

@ -121,7 +121,7 @@ cdef class Span:
return self.doc.merge(self.start_char, self.end_char, *args, **attributes)
def similarity(self, other):
""" Make a semantic similarity estimate. The default estimate is cosine
"""Make a semantic similarity estimate. The default estimate is cosine
similarity using an average of word vectors.
other (object): The object to compare with. By default, accepts `Doc`,
@ -168,14 +168,23 @@ cdef class Span:
return self.doc[root.l_edge : root.r_edge + 1]
property has_vector:
# TODO: docstring
"""A boolean value indicating whether a word vector is associated with
the object.
RETURNS (bool): Whether a word vector is associated with the object.
"""
def __get__(self):
if 'has_vector' in self.doc.user_span_hooks:
return self.doc.user_span_hooks['has_vector'](self)
return any(token.has_vector for token in self)
property vector:
# TODO: docstring
"""A real-valued meaning representation. Defaults to an average of the
token vectors.
RETURNS (numpy.ndarray[ndim=1, dtype='float32']): A 1D numpy array
representing the span's semantics.
"""
def __get__(self):
if 'vector' in self.doc.user_span_hooks:
return self.doc.user_span_hooks['vector'](self)
@ -184,7 +193,10 @@ cdef class Span:
return self._vector
property vector_norm:
# TODO: docstring
"""The L2 norm of the document's vector representation.
RETURNS (float): The L2 norm of the vector representation.
"""
def __get__(self):
if 'vector_norm' in self.doc.user_span_hooks:
return self.doc.user_span_hooks['vector'](self)
@ -206,7 +218,10 @@ cdef class Span:
return sum([token.sentiment for token in self]) / len(self)
property text:
# TODO: docstring
"""A unicode representation of the span text.
RETURNS (unicode): The original verbatim text of the span.
"""
def __get__(self):
text = self.text_with_ws
if self[-1].whitespace_:
@ -214,7 +229,11 @@ cdef class Span:
return text
property text_with_ws:
# TODO: docstring
"""The text content of the span with a trailing whitespace character if
the last token has one.
RETURNS (unicode): The text content of the span (with trailing whitespace).
"""
def __get__(self):
return u''.join([t.text_with_ws for t in self])

114
website/docs/api/span.jade
View File

@ -127,9 +127,7 @@ p
| similarity using an average of word vectors.
+aside-code("Example").
doc = nlp(u'apples and oranges')
apples = doc[0]
oranges = doc[1]
apples, and, oranges = nlp(u'apples and oranges')
apples_oranges = apples.similarity(oranges)
oranges_apples = oranges.similarity(apples)
assert apples_oranges == oranges_apples
@ -165,49 +163,6 @@ p Retokenize the document, such that the span is merged into a single token.
+cell #[code Token]
+cell The newly merged token.
+h(2, "text") Span.text
+tag property
+aside-code("Example").
doc = nlp('Give it back! He pleaded.')
assert doc[1:4].text == 'it back!'
p A unicode representation of the span text.
+table(["Name", "Type", "Description"])
+footrow
+cell returns
+cell unicode
+cell The original verbatim text of the span.
+h(2, "text_with_ws") Span.text_with_ws
+tag property
+aside-code("Example").
doc = nlp('Give it back! He pleaded.')
assert doc[1:4].text_with_ws == 'it back! '
p
| The text content of the span with a trailing whitespace character if the
| last token has one.
+table(["Name", "Type", "Description"])
+footrow
+cell returns
+cell unicode
+cell The text content of the span (with trailing whitespace).
+h(2, "sent") Span.sent
+tag property
p The sentence span that this span is a part of.
+table(["Name", "Type", "Description"])
+footrow
+cell returns
+cell #[code Span]
+cell The sentence this is part of.
+h(2, "root") Span.root
+tag property
@ -262,6 +217,56 @@ p Tokens that descend from tokens in the span, but fall outside it.
+cell #[code Token]
+cell A descendant of a token within the span.
+h(2, "has_vector") Span.has_vector
+tag property
+tag requires model
p
| A boolean value indicating whether a word vector is associated with the
| object.
+aside-code("Example").
apple = nlp(u'apple')
assert apple.has_vector
+table(["Name", "Type", "Description"])
+footrow
+cell returns
+cell bool
+cell Whether the span has a vector data attached.
+h(2, "vector") Span.vector
+tag property
+tag requires model
p
| A real-valued meaning representation. Defaults to an average of the
| token vectors.
+aside-code("Example").
apple = nlp(u'apple')
(apple.vector.dtype, apple.vector.shape)
# (dtype('float32'), (300,))
+table(["Name", "Type", "Description"])
+footrow
+cell returns
+cell #[code numpy.ndarray[ndim=1, dtype='float32']]
+cell A 1D numpy array representing the span's semantics.
+h(2, "vector_norm") Span.vector_norm
+tag property
+tag requires model
p
| The L2 norm of the span's vector representation.
+table(["Name", "Type", "Description"])
+footrow
+cell returns
+cell float
+cell The L2 norm of the vector representation.
+h(2, "attributes") Attributes
+table(["Name", "Type", "Description"])
@ -270,6 +275,11 @@ p Tokens that descend from tokens in the span, but fall outside it.
+cell #[code Doc]
+cell The parent document.
+row
+cell #[code sent]
+cell #[code Span]
+cell The sentence span that this span is a part of.
+row
+cell #[code start]
+cell int
@ -290,6 +300,18 @@ p Tokens that descend from tokens in the span, but fall outside it.
+cell int
+cell The character offset for the end of the span.
+row
+cell #[code text]
+cell unicode
+cell A unicode representation of the span text.
+row
+cell #[code text_with_ws]
+cell unicode
+cell
| The text content of the span with a trailing whitespace character
| if the last token has one.
+row
+cell #[code label]
+cell int