本文整理汇总了Python中networkx.square_clustering方法的典型用法代码示例。如果您正苦于以下问题：Python networkx.square_clustering方法的具体用法？Python networkx.square_clustering怎么用？Python networkx.square_clustering使用的例子？那么恭喜您, 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.square_clustering方法的11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: clustering
# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import square_clustering [as 别名]
def clustering(graph, name="cluster"):
"""
Calculates the squares clustering coefficient for nodes.
Wrapper around ``networkx.square_clustering``.
Parameters
----------
graph : networkx.Graph
Graph representing street network.
Ideally generated from GeoDataFrame using :func:`momepy.gdf_to_nx`
name : str, optional
calculated attribute name
Returns
-------
Graph
networkx.Graph
Examples
--------
>>> network_graph = mm.clustering(network_graph)
"""
netx = graph.copy()
vals = nx.square_clustering(netx)
nx.set_node_attributes(netx, vals, name)
return netx 示例2: test_clustering
# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import square_clustering [as 别名]
def test_clustering(self):
G = nx.Graph()
assert_equal(list(nx.square_clustering(G).values()),[])
assert_equal(nx.square_clustering(G),{}) 示例3: test_path
# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import square_clustering [as 别名]
def test_path(self):
G = nx.path_graph(10)
assert_equal(list(nx.square_clustering(G).values()),
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0])
assert_equal(nx.square_clustering(G),
{0: 0.0, 1: 0.0, 2: 0.0, 3: 0.0, 4: 0.0,
5: 0.0, 6: 0.0, 7: 0.0, 8: 0.0, 9: 0.0}) 示例4: test_cubical
# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import square_clustering [as 别名]
def test_cubical(self):
G = nx.cubical_graph()
assert_equal(list(nx.square_clustering(G).values()),
[0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5])
assert_equal(list(nx.square_clustering(G,[1,2]).values()),[0.5, 0.5])
assert_equal(nx.square_clustering(G,[1])[1],0.5)
assert_equal(nx.square_clustering(G,[1,2]),{1: 0.5, 2: 0.5}) 示例5: test_k5
# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import square_clustering [as 别名]
def test_k5(self):
G = nx.complete_graph(5)
assert_equal(list(nx.square_clustering(G).values()),[1, 1, 1, 1, 1]) 示例6: test_bipartite_k5
# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import square_clustering [as 别名]
def test_bipartite_k5(self):
G = nx.complete_bipartite_graph(5,5)
assert_equal(list(nx.square_clustering(G).values()),
[1, 1, 1, 1, 1, 1, 1, 1, 1, 1]) 示例7: test_clustering
# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import square_clustering [as 别名]
def test_clustering(self):
G = nx.Graph()
assert_equal(list(nx.square_clustering(G).values()), [])
assert_equal(nx.square_clustering(G), {}) 示例8: test_path
# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import square_clustering [as 别名]
def test_path(self):
G = nx.path_graph(10)
assert_equal(list(nx.square_clustering(G).values()),
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0])
assert_equal(nx.square_clustering(G),
{0: 0.0, 1: 0.0, 2: 0.0, 3: 0.0, 4: 0.0,
5: 0.0, 6: 0.0, 7: 0.0, 8: 0.0, 9: 0.0}) 示例9: test_cubical
# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import square_clustering [as 别名]
def test_cubical(self):
G = nx.cubical_graph()
assert_equal(list(nx.square_clustering(G).values()),
[0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5])
assert_equal(list(nx.square_clustering(G, [1, 2]).values()), [0.5, 0.5])
assert_equal(nx.square_clustering(G, [1])[1], 0.5)
assert_equal(nx.square_clustering(G, [1, 2]), {1: 0.5, 2: 0.5}) 示例10: test_k5
# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import square_clustering [as 别名]
def test_k5(self):
G = nx.complete_graph(5)
assert_equal(list(nx.square_clustering(G).values()), [1, 1, 1, 1, 1]) 示例11: test_bipartite_k5
# 需要导入模块: import networkx [as 别名]
# 或者: from networkx import square_clustering [as 别名]
def test_bipartite_k5(self):
G = nx.complete_bipartite_graph(5, 5)
assert_equal(list(nx.square_clustering(G).values()),
[1, 1, 1, 1, 1, 1, 1, 1, 1, 1])