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python - ValueError：无效的 RGBA 参数：nan

问题描述

当我尝试绘制具有 1000 个节点的图形时出现错误。原因似乎是由于

事实上，我可以在映射器中看到一些 nan 值：

---------------------------------------------------------------------------
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

然后

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])

代码（来自ValueError 由于颜色图中缺少元素）。请注意，以下代码有效，但是当我扩展节点数>500 时，会出现上述错误：

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()

我不知道如何在 nan 值的情况下使用 if 条件来避免 ValueError 消息并将节点与其颜色正确关联。我希望你能提供一些帮助。

标签： pythonnetworkx

解决方案

即使有 1000 个节点，您的代码也适用于我，请尝试运行：

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

    G = nx.fast_gnp_random_graph(1000,0.05)
    df2 = pd.DataFrame({
        'Nodes': [i for i in G.nodes()],
        'Attribute': [np.random.rand()*9 for i in G.nodes()]
    })
    # 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)))

    # 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

    print(color_map)
    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()

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