networkx绘制超500节点图出现Invalid RGBA argument: nan错误如何解决

绘制含1000个节点的网络图时触发报错，经排查是颜色映射mapper中存在nan值，该代码在节点数小于500时可正常运行，节点数超过500时就会触发报错。

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
~/opt/anaconda3/lib/python3.8/site-packages/matplotlib/axes/_axes.py in _parse_scatter_color_args(c, edgecolors, kwargs, xsize, get_next_color_func)
   4290             try:  # Is 'c' acceptable as PathCollection facecolors?
-> 4291                 colors = mcolors.to_rgba_array(c)
   4292             except (TypeError, ValueError) as err:

~/opt/anaconda3/lib/python3.8/site-packages/matplotlib/colors.py in to_rgba_array(c, alpha)
    340     else:
--> 341         return np.array([to_rgba(cc, alpha) for cc in c])
    342 

~/opt/anaconda3/lib/python3.8/site-packages/matplotlib/colors.py in <listcomp>(.0)
    340     else:
--> 341         return np.array([to_rgba(cc, alpha) for cc in c])
    342 

~/opt/anaconda3/lib/python3.8/site-packages/matplotlib/colors.py in to_rgba(c, alpha)
    188     if rgba is None:  # Suppress exception chaining of cache lookup failure.
--> 189         rgba = _to_rgba_no_colorcycle(c, alpha)
    190     try:

~/opt/anaconda3/lib/python3.8/site-packages/matplotlib/colors.py in _to_rgba_no_colorcycle(c, alpha)
    262     if not np.iterable(c):
--> 263         raise ValueError(f"Invalid RGBA argument: {orig_c!r}")
    264     if len(c) not in [3, 4]:

ValueError: Invalid RGBA argument: nan

ValueError: 'c' argument must be a color, a sequence of colors, or a sequence of numbers, not dict_values(['#0010ff', '#40ffb7', '#00a4ff', '#40ffb7', '#00a4ff', '#40ffb7', '#ffb900', '#0010ff', nan, '#000080', '#000080', '#000080', '#000080', nan, '#0010ff', '#0010ff', '#800000', '#0010ff', '#0010ff', '#ff3000', '#0010ff', nan, '#00a4ff', '#0010ff', '#0010ff', '#ff3000', nan, nan, '#000080', '#0010ff', '#0010ff', '#0010ff', nan, nan, '#0010ff', nan, nan, '#0010ff', '#0010ff', nan, '#40ffb7', '#00a4ff', '#00a4ff', '#00a4ff', '#0010ff', '#0010ff', '#0010ff', nan, '#800000', nan])

import networkx as nx
import numpy as np
import pandas as pd
from matplotlib import pyplot as plt, colors as mcolor

# Sample DataFrames
df1 = pd.DataFrame({
    'Node': ['A', 'A', 'B', 'B', 'B', 'Z'],
    'Edge': ['B', 'D', 'N', 'A', 'X', 'C']
})
df2 = pd.DataFrame({
    'Nodes': ['A', 'B', 'C', 'D', 'N', 'S', 'X'],
    'Attribute': [-1, 0, -1.5, 1, 1, 9, 0]
})

# Simplified construction of `colour_map`
uni_val = df2['Attribute'].unique()
colors = plt.cm.jet(np.linspace(0, 1, len(uni_val)))
# Map colours to_hex then zip with
mapper = dict(zip(uni_val, map(mcolor.to_hex, colors)))

G = nx.from_pandas_edgelist(df1, source='Node', target='Edge')
# Create Colour map. Ensure all nodes have a value via reindex
color_map = (
    df2.set_index('Nodes')['Attribute'].map(mapper)
        .reindex(G.nodes(), fill_value='black')
)
# Add Attribute to each node
nx.set_node_attributes(G, color_map, name="colour")

# Then draw with colours based on attribute values:
nx.draw(G,
        node_color=nx.get_node_attributes(G, 'colour').values(),
        with_labels=True)

plt.show()

报错的核心是颜色映射过程中产生了nan值，matplotlib无法将nan识别为合法的颜色值。当节点数较少时，Attribute列刚好没有空值、映射全部命中，不会触发报错；节点数增多后，df2的Attribute列出现空值，或者部分属性值无法匹配到mapper中的键，就会生成nan流入后续绘图步骤。
注意原代码中reindex的fill_value='black'仅能补全G中存在但df2中不存在的节点的颜色，无法处理df2中已经存在的节点映射后产生的nan。

在映射之后新增一步fillna，提前将所有映射产生的nan替换为默认颜色即可，修改后的核心代码段如下：

color_map = (
    df2.set_index('Nodes')['Attribute'].map(mapper)
        .fillna('black') # 新增：将映射生成的nan替换为黑色
        .reindex(G.nodes(), fill_value='black')
)

如果需要为属性为空的节点指定其他颜色，替换fillna的参数即可。也可以在构建mapper时显式为nan指定映射颜色：

mapper = dict(zip(uni_val, map(mcolor.to_hex, colors)))
mapper[np.nan] = 'black' # 显式为nan指定对应颜色

内容的提问来源于stack exchange，提问作者LdM