我有一个networkx图的图,其中边缘颜色取决于使用以下代码分配给相应边的权重(使用a_netw nx.Graph)：
a_netw_edges = a_netw.edges()
a_netw_weights = [a_netw[source][dest]['weight'] for source, dest in a_netw_edges]
a_netw_colors = [plt.cm.Blues(weight*15) for weight in a_netw_weights]
nx.draw_networkx(a_netw, edges=a_netw_edges, width=1, edge_color=a_netw_colors)
在这张图中,我想添加一个图例,使权重和颜色之间的连接显式;就像在使用pcolor的热图中一样.
虽然我对如何开始有一个粗略的想法：
fig, axes = plt.subplots(nrows=2)
nx.draw_networkx(a_netw, edges=a_netw_edges, width=1, edge_color=a_netw_colors, ax=axes[0])
axes[0].get_xaxis().set_visible(False)
axes[0].get_yaxis().set_visible(False)
gradient = np.linspace(0, 1, 256)
gradient = np.vstack((gradient, gradient))
axes[1].imshow(gradient, aspect=3, cmap=plt.cm.Blues)
axes[1].get_yaxis().set_visible(False)
plt.tight_layout()
我不知道如何执行以下步骤：
>在相关轴上添加正确的刻度以获得与权重的连接.
>垂直绘制而不是水平绘制.
解决方法:
我建议你使用colorbar()命令,如下所示.我提供了一个示例Graph,看看它是否有意义？
import networkx as nx
import matplotlib.pyplot as plt
#generate a graph with weights
a_netw=nx.Graph()
a_netw.add_edge('a','b',weight=6)
a_netw.add_edge('a','c',weight=2)
a_netw.add_edge('c','d',weight=1)
a_netw.add_edge('c','e',weight=7)
a_netw.add_edge('c','f',weight=9)
a_netw.add_edge('a','d',weight=3)
#creating a color list for each edge based on weight
a_netw_edges = a_netw.edges()
a_netw_weights = [a_netw[source][dest]['weight'] for source, dest in a_netw_edges]
#scale weights in range 0-1 before assigning color
maxWeight=float(max(a_netw_weights))
a_netw_colors = [plt.cm.Blues(weight/maxWeight) for weight in a_netw_weights]
#suppress plotting for the following dummy heatmap
plt.ioff()
#multiply all tuples in color list by scale factor
colors_unscaled=[tuple(map(lambda x: maxWeight*x, y)) for y in a_netw_colors]
#generate a 'dummy' heatmap using the edgeColors as substrate for colormap
heatmap = plt.pcolor(colors_unscaled,cmap=plt.cm.Blues)
#re-enable plotting
plt.ion()
fig,axes = plt.subplots()
nx.draw_networkx(a_netw, edges=a_netw_edges, width=10, edge_color=a_netw_colors, ax=axes)
axes.get_xaxis().set_visible(False)
axes.get_yaxis().set_visible(False)
#add colorbar
cbar = plt.colorbar(heatmap)
cbar.ax.set_ylabel('edge weight',labelpad=15,rotation=270)
标签：python,matplotlib,networkx
来源： https://codeday.me/bug/20190628/1310605.html