如何从networkx中的图形中删除float('nan')节点? [英] How to remove float('nan') node from a graph in networkx?

问题描述

我有一个包含 float('nan') 的数据集(pickle 格式)，我需要删除它.

可以将 float('nan') 作为 networkx 中的节点添加到图中.但是，我不知道如何删除它.

将 networkx 导入为 nxG = nx.Graph()G.add_node(float('nan'))print(G.nodes) # [nan]，所以图中有float('nan')G.remove_node(float('nan')) # 这个语句引发了一个 NetworkxError，显示 nan 不在图中

CoReRank-WSDM-2019 和 中的代码和数据="https://bhooi.github.io/code/birdnest.zip" rel="nofollow noreferrer">鸟巢.

有人能帮我解决这个问题吗?提前致谢.

解决方案

我们可以在一个简单的字典上进行测试，它是 NetworkX 图的底层数据结构.假设您有:

d = {'a':3, float('nan'):4}

如果我们像您一样尝试访问 NaN 键:

d[float('nan')]>关键错误:nan

造成这种情况的核心原因是 NaN 不等于自身:

<预><代码>>>>浮动(南")==浮动(南")错误的

这导致查找失败的原因，在这里有很好的解释.

一种解决方法，可能是遍历图形键，并识别 NaN 节点，然后然后使用对象的相同引用删除该键:

导入数学G = nx.Graph()G.add_node(float('nan'))G.add_node(3)打印(G.nodes)# [南, 3]nan_nodes = []对于 G.nodes() 中的节点:如果 math.isnan(节点):nan_nodes.append(节点)G.remove_nodes_from(nan_nodes)G.nodes()# NodeView((3,))

I have a dataset(pickle format) containing float('nan'), and I need to remove it.

It is possible to add float('nan') to a graph as a node in networkx. However, I don't know how to remove it.

import networkx as nx
G = nx.Graph()
G.add_node(float('nan'))
print(G.nodes) # [nan], so there is float('nan') in the graph
G.remove_node(float('nan')) # this statement raise a NetworkxError showing nan not in the graph

Code and data in CoReRank-WSDM-2019 and BirdNest.

Could anyone help me with this problem? Thank you in advance.

解决方案

We can test this on a simple dictionary, which is the underlying data structure of a NetworkX graph. Say you have:

d = {'a':3, float('nan'):4}

If we try accessing the NaN key, as you're trying to do:

d[float('nan')]
> KeyError: nan

The core cause of this, is explained by the fact that a NaN does not equal to itself:

>>> float("nan") == float("nan")
False

The reason behind why this causes the lookup to fail, is nicely explained here.

A workaround, could be to loop over the graph keys, and identify the NaN node and then remove that key using the same reference of the object:

import math

G = nx.Graph()
G.add_node(float('nan'))
G.add_node(3)
print(G.nodes) 
# [nan, 3]

nan_nodes = []
for node in G.nodes():
    if math.isnan(node):
        nan_nodes.append(node)
G.remove_nodes_from(nan_nodes)

G.nodes()
# NodeView((3,))

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