def to_semantic_network(self,
nodes='words',
normalize='lemma',
edge_weighting='default',
window_width=10):
"""
Transform ``Doc`` into a semantic network, where nodes are either 'words'
or 'sents' and edges between nodes may be weighted in different ways.
Args:
nodes ({'words', 'sents'}): type of doc component to use as nodes
in the semantic network
normalize (str or callable): if 'lemma', lemmatize terms; if 'lower',
lowercase terms; if false-y, use the form of terms as they appear
in doc; if a callable, must accept a ``spacy.Token`` or ``spacy.Span``
(if ``nodes`` = 'words' or 'sents', respectively) and return a
str, e.g. :func:`textacy.spacy_utils.normalized_str()`
edge_weighting (str): type of weighting to apply to edges
between nodes; if ``nodes == 'words'``, options are {'cooc_freq', 'binary'},
if ``nodes == 'sents'``, options are {'cosine', 'jaccard'}; if
'default', 'cooc_freq' or 'cosine' will be automatically used
window_width (int): size of sliding window over terms that
determines which are said to co-occur; only applicable if 'words'
Returns:
:class:`networkx.Graph <networkx.Graph>`: where nodes represent either
terms or sentences in doc; edges, the relationships between them
Raises:
ValueError: if ``nodes`` is neither 'words' nor 'sents'
See Also:
:func:`terms_to_semantic_network() <textacy.network.terms_to_semantic_network>`
:func:`sents_to_semantic_network() <textacy.network.sents_to_semantic_network>`
"""
if nodes == 'words':
if edge_weighting == 'default':
edge_weighting = 'cooc_freq'
return network.terms_to_semantic_network(
list(textacy.extract.words(self)),
normalize=normalize,
window_width=window_width,
edge_weighting=edge_weighting)
elif nodes == 'sents':
if edge_weighting == 'default':
edge_weighting = 'cosine'
return network.sents_to_semantic_network(
list(self.sents),
normalize=normalize,
edge_weighting=edge_weighting)
else:
msg = 'nodes "{}" not valid; must be in {}'.format(
nodes, {'words', 'sents'})
raise ValueError(msg)
def to_semantic_network(self, nodes='words',
edge_weighting='default', window_width=10):
"""
Transform ``Doc`` into a semantic network, where nodes are either 'words'
or 'sents' and edges between nodes may be weighted in different ways.
Args:
nodes ({'words', 'sents'}): type of doc component to use as nodes
in the semantic network
edge_weighting (str): type of weighting to apply to edges
between nodes; if ``nodes == 'words'``, options are {'cooc_freq', 'binary'},
if ``nodes == 'sents'``, options are {'cosine', 'jaccard'}; if
'default', 'cooc_freq' or 'cosine' will be automatically used
window_width (int): size of sliding window over terms that
determines which are said to co-occur; only applicable if 'words'
Returns:
:class:`networkx.Graph <networkx.Graph>`: where nodes represent either
terms or sentences in doc; edges, the relationships between them
Raises:
ValueError: if ``nodes`` is neither 'words' nor 'sents'
See Also:
:func:`terms_to_semantic_network() <textacy.network.terms_to_semantic_network>`
:func:`sents_to_semantic_network() <textacy.network.sents_to_semantic_network>`
"""
if nodes == 'words':
if edge_weighting == 'default':
edge_weighting = 'cooc_freq'
return network.terms_to_semantic_network(
list(textacy.extract.words(self)),
window_width=window_width,
edge_weighting=edge_weighting)
elif nodes == 'sents':
if edge_weighting == 'default':
edge_weighting = 'cosine'
return network.sents_to_semantic_network(
list(self.sents), edge_weighting=edge_weighting)
else:
msg = 'nodes "{}" not valid; must be in {}'.format(
nodes, {'words', 'sents'})
raise ValueError(msg)
