我有一个问题,我有向图的加权邻接矩阵C,所以C(j,i)= 0,只要从j到i都没有边且C(j,i)> 0,那么C(j,i)是边缘的权重;
现在,我想绘制有向图。当您手动添加边线时,有很多解决方案,例如在这里:
Add edge-weights to plot output in networkx
但是我想基于矩阵C绘制边缘和边缘权重;我以下列方式开始:
def DrawGraph(C):
import networkx as nx
import matplotlib.pyplot as plt
G = nx.DiGraph(C)
plt.figure(figsize=(8,8))
nx.draw(G, with_labels=True)
这会绘制一个图形,并且在顶点上有标签,但是没有边权重-同样,我也无法通过上链接调整技术以使其起作用-那我该怎么办?
我将如何更改节点大小和颜色?
答案 0 :(得分:1)
使用networkx可以有多种方法-这是一种适合您要求的解决方案:
代码:
# Set up weighted adjacency matrix
A = np.array([[0, 0, 0],
[2, 0, 3],
[5, 0, 0]])
# Create DiGraph from A
G = nx.from_numpy_matrix(A, create_using=nx.DiGraph)
# Use spring_layout to handle positioning of graph
layout = nx.spring_layout(G)
# Use a list for node_sizes
sizes = [1000,400,200]
# Use a list for node colours
color_map = ['g', 'b', 'r']
# Draw the graph using the layout - with_labels=True if you want node labels.
nx.draw(G, layout, with_labels=True, node_size=sizes, node_color=color_map)
# Get weights of each edge and assign to labels
labels = nx.get_edge_attributes(G, "weight")
# Draw edge labels using layout and list of labels
nx.draw_networkx_edge_labels(G, pos=layout, edge_labels=labels)
# Show plot
plt.show()
结果: