【发布时间】:2021-10-25 11:07:10
【问题描述】:
我有这个图结构
graph = thisdict['data']['graph']
dict_edges = graph['edges']
edges = []
for edge in dict_edges:
edges.append((edge['source']['node_id'], edge['target']['node_id']))
print('Source:\t\t\t Target:\n')
for edge in edges:
print(str(edge))
print('\n')
dict_nodes = graph['nodes']
nodes = {}
for node in dict_nodes:
nodes[node['id']] = node['name']
print('Node ID:\t\t Node Name:\n')
for key, value in nodes.items():
print("'%s':'%s'" %(key, value))
输出:
Source: Target:
('61697b94f74c92a808641ba3', '61697b95f74c92a808641ba4')
('61697b94f74c92a808641ba3', '61697b96f74c92a808641ba5')
('61697b95f74c92a808641ba4', '61697b96f74c92a808641ba6')
('61697b96f74c92a808641ba6', '61697b97f74c92a808641ba7')
('61697b96f74c92a808641ba5', '61697b97f74c92a808641ba7')
('61697b97f74c92a808641ba7', '61697b98f74c92a808641ba8')
('61697b98f74c92a808641ba8', '61697b98f74c92a808641ba9')
Node ID: Node Name:
'61697b94f74c92a808641ba3':'S3 connector'
'61697b95f74c92a808641ba4':'loader 1'
'61697b96f74c92a808641ba5':'loader 2'
'61697b96f74c92a808641ba6':'sampler 1'
'61697b97f74c92a808641ba7':'concator'
'61697b98f74c92a808641ba8':'sampler 2'
'61697b98f74c92a808641ba9':'splitter'
我写了这段代码来绘制图形:
nx_graph = nx.Graph()
plt.figure(figsize=(3,3))
for key, value in nodes.items():
nx_graph.add_node(key, layer = nodes.values())
#I need to put every node name in a single layer, So I should have 6 layers
for edge in edges:
nx_graph.add_edge(*edge)
pos = nx.multipartite_layout(nx_graph, subset_key="layer")
nx.draw(nx_graph, pos, labels=nodes, with_labels=True)
plt.show()
显示错误:TypeError: unsupported operand type(s) for -: 'dict_values' and 'float'
我需要将每个节点名称放在一个层中,所以我应该有 6 层。 图层排序应如下所示:
S3 connector --> loader 1 & loader 2
loader 1 will give sampler 1
loader 2 & sampler 1 will meet in concator
concator will give sampler 2
sampler 2 will give splitter
【问题讨论】:
标签: python matplotlib machine-learning data-science networkx