NetworkX包

官方教程

NetworkX是一个创建，操作，研究复杂网络的结构，动态，功能的python包。

#创建一个network
import networkx as nx
G = nx.Graph()

#nodes
import networkx as nx
G = nx.Graph()
'''
在networkx中，nodes可以是任何能够hash的对象，
例如a text string，an image，an XML object，another Graph，a customized node object等等'''

G.add_node(11)
G.add_nodes_from([12, 13])
print(G.nodes())

H = nx.path_graph(10)
G.add_nodes_from(H)
G.add_node(H)
print(G.nodes())

'''
输出：
[11, 12, 13]
[11, 12, 13, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, <networkx.classes.graph.Graph object at 0x00000000021C8828>]

G可以将H中的node作为自己的node，也可以将H单独作为一个node'''

添加edges

import networkx as nx
G = nx.Graph()

'''G.add_edge(1, 2)
e = (2, 3)
G.add_edge(*e)
G.add_edges_from([(4, 5), (6, 7)])'''

'''
adding any ebunch of edges. An ebunch is any iterable container of edge-tuples.
An edge-tuple can be a 2-tuple of nodes or a 3-tuple with
2 nodes followed by an edge attribute dictionary, e.g., (2, 3, {'weight': 3.1415})'''
H = nx.path_graph(10)
G.add_edges_from(H.edges())

print(G.nodes())
print(G.edges())
print(G.number_of_edges())
print(G.number_of_nodes())
'''
输出：
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
[(0, 1), (1, 2), (2, 3), (3, 4), (4, 5), (5, 6), (6, 7), (7, 8), (8, 9)]
9
10
'''
print('..............')
print(list(G.adj[1]))
print(G.neighbors(1))
print(G.degree(1))
'''
输出：
[0, 2]
[0, 2]
2
'''

print(G.edges([2, 5]))
print(G.degree([2, 3]))
'''
输出：
[(2, 1), (2, 3), (5, 4), (5, 6)]
{2: 2, 3: 2}
'''

G.remove_node(2)
G.remove_edge(6, 7)

print(G.nodes())
print(G.edges())
'''
输出：
[0, 1, 3, 4, 5, 6, 7, 8, 9]
[(0, 1), (3, 4), (4, 5), (5, 6), (7, 8), (8, 9)]
'''

G.add_edge(6, 7)
H = nx.DiGraph(G)
print(H.edges())
'''
[(0, 1), (1, 0), (3, 4), (4, 3), (4, 5), (5, 4), (5, 6), (6, 5), (6, 7), (7, 8), (7, 6), (8, 7), (8, 9), (9, 8)]
'''

edgelist = [(0, 1), (2, 3), (4, 5)]
H = nx.Graph(edgelist)
print(H.edges())
'''
[(0, 1), (2, 3), (4, 5)]
'''

访问edges或neighbors：

#访问edges或neighbors
import networkx as nx
G = nx.Graph()

H = nx.path_graph(7)
G.add_edges_from(H.edges())

print('G.nodes()为:', G.nodes())
print('G.edges()为:', G.edges())
'''
G.nodes()为: [0, 1, 2, 3, 4, 5, 6]
G.edges()为: [(0, 1), (1, 2), (2, 3), (3, 4), (4, 5), (5, 6)]
'''

print('...............')
print('G[1]为:', G[1])
print('G[1][2]为：', G[1][2])
'''
G[1]为: {0: {}, 2: {}}
G[1][2]为： {}
'''

G.add_edge(1, 3)
G[1][3]['color'] = 'blue'
G[1][3]['size'] = 22

print('...............')
print('G[1]为:', G[1])
print('G[1][3]为:', G[1][3])
'''
G[1]为: {0: {}, 2: {}, 3: {'color': 'blue', 'size': 22}}
G[1][3]为: {'color': 'blue', 'size': 22}'''

print('...................')
print('G.adj.items()为:   ', G.adj.items())
print('G.adjacency_list()为:   ',G.adjacency_list())
print('G.adjlist_dict_factory为:   ', G.adjlist_dict_factory)
'''
G.adj.items()为:    dict_items([(0, {1: {}}), (1, {0: {}, 2: {}, 3: {'color': 'blue', 'size': 22}}), (2, {1: {}, 3: {}}), (3, {2: {}, 4: {}, 1: {'color': 'blue', 'size': 22}}), (4, {3: {}, 5: {}}), (5, {4: {}, 6: {}}), (6, {5: {}})])
G.adjacency_list()为:    [[1], [0, 2, 3], [1, 3], [2, 4, 1], [3, 5], [4, 6], [5]]
G.adjlist_dict_factory为:    <class 'dict'>
'''

print('..........................')
FG = nx.Graph()
FG.add_weighted_edges_from([(1, 2, 0.125), (1, 3, 0.75), (2, 4, 1.2), (3, 4, 0.375)])
for n,nbrs in FG.adj.items():
    for nbr, edgeAttr in nbrs.items():
        wt = edgeAttr['weight']
        if wt < 0.5:
            print('(%d, %d, %.3f)' % (n, nbr, wt))
'''
(1, 2, 0.125)
(2, 1, 0.125)
(3, 4, 0.375)
(4, 3, 0.375)
'''

为graphs，nodes，edges添加属性

#Adding attributes to graphs, nodes, and edges
#任何python object比如weights，labels，colors都可以作为graphs，nodes，edges的属性

'''Graph attributes'''
import networkx as nx
G = nx.Graph(day='Friday')
print(G.graph)
#{'day': 'Friday'}

#modify attributes
G.graph['day'] = "monday"
print(G.graph)
#{'day': 'monday'}

'''Node attributes'''
#用add_node(),add_nodes_from()或G.nodes为node添加属性
G.add_node(1, time='11am')
G.add_nodes_from([3],time='2pm')

print(G.node[1])
#{'time': '11am'}
G.node[1]['room'] = 714
print(G.node)
#{1: {'time': '11am', 'room': 714}, 3: {'time': '2pm'}}

'''Edge Attributes'''
#用add_edge(), add_edges_from(),或下标来为edge添加或修改属性
G.add_edge(1, 2, weight=4.5)
G.add_edges_from([(3, 4),(4, 5)], color='red')
G.add_edges_from([(1, 2,{'color':'blue'}),(2, 3,{'weight':8})])

G[1][2]['weight'] = 7878
G.edge[1][2]['color'] = 'wetuweywiu'
print(G.edge)
'''
{1: {2: {'weight': 7878, 'color': 'wetuweywiu'}}, 3: {4: {'color': 'red'}, 2: {'weight': 8}}, 2: {1: {'weight': 7878, 'color': 'wetuweywiu'}, 3: {'weight': 8}},
4: {3: {'color': 'red'}, 5: {'color': 'red'}}, 5: {4: {'color': 'red'}}}
'''
print(G.edges())
#[(1, 2), (3, 4), (3, 2), (4, 5)]

print(G[1])#1的邻接node以及edge的属性
# {2: {'weight': 7878, 'color': 'wetuweywiu'}}
print(G[1][2])
#{'weight': 7878, 'color': 'wetuweywiu'}
print(G.edge[1][2])
#{'weight': 7878, 'color': 'wetuweywiu'}

'''
总结：
访问node的具体属性，必须是G.node[u][attr]， 而访问edge的具体属性可以是G.edge[u][v][attr]或G[u][v][attr]
G.node[u]:node u的所有属性，  G.edge[u][v]或G[u][v]：边(u, v)的所有属性
G.node：所有点以及属性，  G.edge:所有edge以及属性
'''

有向图：

import networkx as nx
DG = nx.DiGraph()
DG.add_weighted_edges_from([(1, 2, 0.5), (3, 1, 0.75)])
print(DG.out_degree(1, weight='weight'))
#0.5
print(DG.in_degree(1, weight='weight'))
#0.75
print(DG.degree(1, weight='weight'))
#1.25
print(DG.successors(1))
#[2]
print(DG.neighbors(1))
#[2]
print(DG.out_edges(3))
#[(3, 1)]
print(DG.in_edges(2))
#[(1, 2)]
print(DG.predecessors(1))
[3]
'''
总结：
DiGraph.out_edges(), DiGraph.in_edges()
DiGraph.in_degree(), DiGraph.out_degree(),DiGraph.degree()
DiGraph.predecessors(),
DiGraph.successors()相当于DiGraph.neighbours()
'''

H = nx.Graph(DG)#将有向图转化为无向图
print(H.edge)
# {1: {2: {'weight': 0.5}, 3: {'weight': 0.75}}, 2: {1: {'weight': 0.5}}, 3: {1: {'weight': 0.75}}}

H1 = DG.to_undirected()
print(H1.edge)
#{1: {2: {'weight': 0.5}, 3: {'weight': 0.75}}, 2: {1: {'weight': 0.5}}, 3: {1: {'weight': 0.75}}}

MultiGraph：

任意一对nodes之间可以有多条边。边的属性不同

#任意一对nodes之间可以有多条边。边的属性不同
import networkx as nx
MG = nx.MultiGraph()
MG.add_weighted_edges_from([(1, 2, 0.5), (1, 2, 0.75), (2, 3, 0.5)])

print(MG.degree(weight='weight'))
#{1: 1.25, 2: 1.75, 3: 0.5}

GG = nx.Graph()
for n, nbrs in MG.adj.items():
    for nbr, edgeDict in nbrs.items():
        minvalue = min([d['weight'] for d in edgeDict.values()])
        GG.add_edge(n, nbr, weight=minvalue)

print(nx.shortest_path(GG, 1, 3))
#[1, 2, 3]

print(MG.adj.items())
#dict_items([(1, {2: {0: {'weight': 0.5}, 1: {'weight': 0.75}}}),
# (2, {1: {0: {'weight': 0.5}, 1: {'weight': 0.75}}, 3: {0: {'weight': 0.5}}}),
# (3, {2: {0: {'weight': 0.5}}})])