如何使用 networkx 和 matplotlib 绘制重量标签?
How to draw weight labels with networkx and matplotlib?
我正在研究图表,所以我尝试使用 networkx 和 matplotlib 在 python 中给定字典绘制图表,这是我的代码:
import networkx as nx
import matplotlib.pyplot as plt
G = nx.Graph()
graph = {
"A":["B","C"],
"B":["D","E"],
"C":["E","F"],
"D":["B","G"],
"E":["B","C"],
"F":["C","G"],
"G":["D","F"]
}
x=10
for vertex, edges in graph.items():
G.add_node("%s" % vertex)
x+=2
for edge in edges:
G.add_node("%s" % edge)
G.add_edge("%s" % vertex, "%s" % edge, weight = x)
print("'%s' it connects with '%s'" % (vertex,edge))
nx.draw(G,with_labels=True)
plt.show()
我已经尝试过 draw_networkx_edge_labels 函数,但似乎我需要一个位置,因为我动态添加节点后我没有这个位置,所以我需要一种方法绘制适合我当前实现的边缘标签。
添加所有节点后绘制图形,以便计算位置并根据它们使用nx.draw_networkx_edge_labels(...)
:
import networkx as nx
import matplotlib.pyplot as plt
G = nx.Graph()
graph = {
"A":["B","C"],
"B":["D","E"],
"C":["E","F"],
"D":["B","G"],
"E":["B","C"],
"F":["C","G"],
"G":["D","F"]
}
x=10
for vertex, edges in graph.items():
G.add_node("%s" % vertex)
x+=2
for edge in edges:
G.add_node("%s" % edge)
G.add_edge("%s" % vertex, "%s" % edge, weight = x)
print("'%s' it connects with '%s'" % (vertex,edge))
# ---- END OF UNCHANGED CODE ----
# Create positions of all nodes and save them
pos = nx.spring_layout(G)
# Draw the graph according to node positions
nx.draw(G, pos, with_labels=True)
# Create edge labels
labels = {e: str(e) for e in G.edges}
# Draw edge labels according to node positions
nx.draw_networkx_edge_labels(G, pos, edge_labels=labels)
plt.show()
我正在研究图表,所以我尝试使用 networkx 和 matplotlib 在 python 中给定字典绘制图表,这是我的代码:
import networkx as nx
import matplotlib.pyplot as plt
G = nx.Graph()
graph = {
"A":["B","C"],
"B":["D","E"],
"C":["E","F"],
"D":["B","G"],
"E":["B","C"],
"F":["C","G"],
"G":["D","F"]
}
x=10
for vertex, edges in graph.items():
G.add_node("%s" % vertex)
x+=2
for edge in edges:
G.add_node("%s" % edge)
G.add_edge("%s" % vertex, "%s" % edge, weight = x)
print("'%s' it connects with '%s'" % (vertex,edge))
nx.draw(G,with_labels=True)
plt.show()
我已经尝试过 draw_networkx_edge_labels 函数,但似乎我需要一个位置,因为我动态添加节点后我没有这个位置,所以我需要一种方法绘制适合我当前实现的边缘标签。
添加所有节点后绘制图形,以便计算位置并根据它们使用nx.draw_networkx_edge_labels(...)
:
import networkx as nx
import matplotlib.pyplot as plt
G = nx.Graph()
graph = {
"A":["B","C"],
"B":["D","E"],
"C":["E","F"],
"D":["B","G"],
"E":["B","C"],
"F":["C","G"],
"G":["D","F"]
}
x=10
for vertex, edges in graph.items():
G.add_node("%s" % vertex)
x+=2
for edge in edges:
G.add_node("%s" % edge)
G.add_edge("%s" % vertex, "%s" % edge, weight = x)
print("'%s' it connects with '%s'" % (vertex,edge))
# ---- END OF UNCHANGED CODE ----
# Create positions of all nodes and save them
pos = nx.spring_layout(G)
# Draw the graph according to node positions
nx.draw(G, pos, with_labels=True)
# Create edge labels
labels = {e: str(e) for e in G.edges}
# Draw edge labels according to node positions
nx.draw_networkx_edge_labels(G, pos, edge_labels=labels)
plt.show()