本文整理汇总了Python中networkx.adamic_adar_index方法的典型用法代码示例。如果您正苦于以下问题：Python networkx.adamic_adar_index方法的具体用法？Python networkx.adamic_adar_index怎么用？Python networkx.adamic_adar_index使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类networkx的用法示例。
在下文中一共展示了networkx.adamic_adar_index方法的5个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: get_edge_weight
# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import adamic_adar_index [as 别名]
def get_edge_weight(self, i, j):
aa_index = nx.adamic_adar_index(self._G, [(i, j)])
return six.next(aa_index)[2] 示例2: adamic_adar
# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import adamic_adar_index [as 别名]
def adamic_adar(self):
"""Computes adamic adar scores."""
graph = nx.from_scipy_sparse_matrix(self.adj_matrix)
scores = nx.adamic_adar_index(graph)
return scores 示例3: setUp
# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import adamic_adar_index [as 别名]
def setUp(self):
self.func = nx.adamic_adar_index
self.test = partial(_test_func, predict_func=self.func) 示例4: adamic_adar_index
# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import adamic_adar_index [as 别名]
def adamic_adar_index(G, ebunch=None):
r"""Compute the Adamic-Adar index of all node pairs in ebunch.
Adamic-Adar index of `u` and `v` is defined as
.. math::
\sum_{w \in \Gamma(u) \cap \Gamma(v)} \frac{1}{\log |\Gamma(w)|}
where :math:`\Gamma(u)` denotes the set of neighbors of `u`.
Parameters
----------
G : graph
NetworkX undirected graph.
ebunch : iterable of node pairs, optional (default = None)
Adamic-Adar index will be computed for each pair of nodes given
in the iterable. The pairs must be given as 2-tuples (u, v)
where u and v are nodes in the graph. If ebunch is None then all
non-existent edges in the graph will be used.
Default value: None.
Returns
-------
piter : iterator
An iterator of 3-tuples in the form (u, v, p) where (u, v) is a
pair of nodes and p is their Adamic-Adar index.
Examples
--------
>>> import networkx as nx
>>> G = nx.complete_graph(5)
>>> preds = nx.adamic_adar_index(G, [(0, 1), (2, 3)])
>>> for u, v, p in preds:
... '(%d, %d) -> %.8f' % (u, v, p)
...
'(0, 1) -> 2.16404256'
'(2, 3) -> 2.16404256'
References
----------
.. [1] D. Liben-Nowell, J. Kleinberg.
The Link Prediction Problem for Social Networks (2004).
http://www.cs.cornell.edu/home/kleinber/link-pred.pdf
"""
if ebunch is None:
ebunch = nx.non_edges(G)
def predict(u, v):
return sum(1 / math.log(G.degree(w))
for w in nx.common_neighbors(G, u, v))
return ((u, v, predict(u, v)) for u, v in ebunch) 示例5: adamic_adar_index
# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import adamic_adar_index [as 别名]
def adamic_adar_index(G, ebunch=None):
r"""Compute the Adamic-Adar index of all node pairs in ebunch.
Adamic-Adar index of `u` and `v` is defined as
.. math::
\sum_{w \in \Gamma(u) \cap \Gamma(v)} \frac{1}{\log |\Gamma(w)|}
where $\Gamma(u)$ denotes the set of neighbors of $u$.
Parameters
----------
G : graph
NetworkX undirected graph.
ebunch : iterable of node pairs, optional (default = None)
Adamic-Adar index will be computed for each pair of nodes given
in the iterable. The pairs must be given as 2-tuples (u, v)
where u and v are nodes in the graph. If ebunch is None then all
non-existent edges in the graph will be used.
Default value: None.
Returns
-------
piter : iterator
An iterator of 3-tuples in the form (u, v, p) where (u, v) is a
pair of nodes and p is their Adamic-Adar index.
Examples
--------
>>> import networkx as nx
>>> G = nx.complete_graph(5)
>>> preds = nx.adamic_adar_index(G, [(0, 1), (2, 3)])
>>> for u, v, p in preds:
... '(%d, %d) -> %.8f' % (u, v, p)
...
'(0, 1) -> 2.16404256'
'(2, 3) -> 2.16404256'
References
----------
.. [1] D. Liben-Nowell, J. Kleinberg.
The Link Prediction Problem for Social Networks (2004).
http://www.cs.cornell.edu/home/kleinber/link-pred.pdf
"""
def predict(u, v):
return sum(1 / log(G.degree(w)) for w in nx.common_neighbors(G, u, v))
return _apply_prediction(G, predict, ebunch)