python networkx中的图例

Question

我有以下代码来绘制带节点的图形，但我未能添加正确的图例： （对不起，我无法发布图片，似乎我没有足够的声誉）

我想要一个有 4 种颜色的图例，例如“浅蓝色 = 过时，红色 = 草稿，黄色 = 重新发布，深蓝色 = 初始化”。

我见过一些“分散”的解决方案，但我认为它太复杂了。有没有办法用plt.legend(G.nodes) 做到这一点？

代码如下：

import networkx as nx
import matplotlib.pyplot as plt
import numpy as np
G=nx.Graph()
G.add_node("kind1")
G.add_node("kind2")
G.add_node("Obsolete")
G.add_node("Draft")
G.add_node("Release")
G.add_node("Initialisation")
val_map = {'kind1': 2,'kind2': 2,'Obsolete': 2,'Initialisation': 1,'Draft': 4,'Release': 3}
values = [val_map.get(node, 0) for node in G.nodes()]
nodes = nx.draw(G, cmap = plt.get_cmap('jet'), node_color = values)

plt.legend(G.nodes())
plt.show() 

Answer 1

您在使用nx.draw 时似乎出现了某种错误。尝试改用nx.draw_networkx。 然后在绘制图形时使用来自matplotlib 的轴来传递它。该轴应包含节点的标签和颜色，同时在 (0,0) 中绘制一个点 --> 这是棘手的部分。

希望对您有所帮助！这是我运行的代码：

import networkx as nx
import matplotlib.pyplot as plt
import numpy as np
# For color mapping
import matplotlib.colors as colors
import matplotlib.cm as cmx

G=nx.Graph()
G.add_node("kind1")
G.add_node("kind2")
G.add_node("Obsolete")
G.add_node("Draft")
G.add_node("Release")
G.add_node("Initialisation")

# You were missing the position.
pos=nx.spring_layout(G)
val_map = {'kind1': 2, 
           'kind2': 2, 
           'Obsolete': 2, 
           'Initialisation': 1, 
           'Draft': 4, 
           'Release': 3}
values = [val_map.get(node, 0) for node in G.nodes()]
# Color mapping
jet = cm = plt.get_cmap('jet')
cNorm  = colors.Normalize(vmin=0, vmax=max(values))
scalarMap = cmx.ScalarMappable(norm=cNorm, cmap=jet)

# Using a figure to use it as a parameter when calling nx.draw_networkx
f = plt.figure(1)
ax = f.add_subplot(1,1,1)
for label in val_map:
    ax.plot([0],[0],
            color=scalarMap.to_rgba(val_map[label]),
            label=label)

# Just fixed the color map
nx.draw_networkx(G,pos, cmap=jet, vmin=0, vmax=max(values),
                 node_color=values,
                 with_labels=False, ax=ax)

# Here is were I get an error with your code                                                                                                                         
#nodes = nx.draw(G, cmap=plt.get_cmap('jet'), node_color=values)                                                                             

# Setting it to how it was looking before.                                                                                                              
plt.axis('off')
f.set_facecolor('w')

plt.legend(loc='center')

f.tight_layout()
plt.show()

一些有用的资源：

1. http://pydoc.net/Python/networkx/1.0.1/networkx.drawing.nx_pylab/
2. http://matplotlib.org/api/legend_api.html
3. Using Colormaps to set color of line in matplotlib
4. http://matplotlib.org/1.3.1/users/artists.html

Answer 2

非常感谢您的帮助，但这并不是我想要的。我做了一些更改，所以我可以让颜色图例的名称与节点的名称不同。

这是最终代码：

import networkx as nx
import matplotlib.pyplot as plt
import numpy as np
# For color mapping
import matplotlib.colors as colors
import matplotlib.cm as cmx

G=nx.Graph()
G.add_node("kind1")
G.add_node("kind2")
G.add_node("kind3")
G.add_node("kind4")
G.add_node("kind5")
G.add_node("kind6")

# You were missing the position.
pos=nx.spring_layout(G)
val_map = {'kind1': 2,'kind2': 2,'kind3': 2,'kind4': 1,'kind5':4,'kind6': 3}
#I had this list for the name corresponding t the color but different from the node name
ColorLegend = {'Obsolete': 2,'Initialisation': 1,'Draft': 4,'Release': 3}
values = [val_map.get(node, 0) for node in G.nodes()]
# Color mapping
jet = cm = plt.get_cmap('jet')
cNorm  = colors.Normalize(vmin=0, vmax=max(values))
scalarMap = cmx.ScalarMappable(norm=cNorm, cmap=jet)

# Using a figure to use it as a parameter when calling nx.draw_networkx
f = plt.figure(1)
ax = f.add_subplot(1,1,1)
for label in ColorLegend:
    ax.plot([0],[0],color=scalarMap.to_rgba(ColorLegend[label]),label=label)

# Just fixed the color map
nx.draw_networkx(G,pos, cmap = jet, vmin=0, vmax= max(values),node_color=values,with_labels=True,ax=ax)

# Setting it to how it was looking before.                                                                                                              
plt.axis('off')
f.set_facecolor('w')

plt.legend()

f.tight_layout()
plt.show()