无法通过 NetworkX 中的属性检索节点

我正在使用 NetworkX 开发一个代码，其中我有一个类似于以下的多部分图：

每个节点具有以下属性：

• 层：指的是图中可以找到节点的那一列
• 标签：对于每一列，我为每个节点分配一个标签
• 轨迹：它是节点之间的关系。如果一个节点与另一个节点相关，则这些到节点的标记可能不同，但将共享相同的轨迹。

在上面的照片中，每个节点标签都被描述为“label.layer”（在这种情况下，我们可以看到更大图的一个子集，因此层编号从 451 开始，而不是从 0 开始）。

What I would like to get are separate dictionaries from this graph, and these dictionaries should only contain the nodes which belong to the same trajectory, that is, all the nodes which are neighbours between each other. So far I followed these posts and my solution is:

Select network nodes with a given attribute value

Select nodes and edges form networkx graph with attributes

for i in range(trajectory):
        sel_nodes = dict((node, attribute['trajectory']) for node, attribute in G.nodes().items() if attribute['trajectory'] == i)
        print(sel_nodes)

This should return a dictionary for each 'row' of nodes, however the output are the following dicts:

{'0.451': 0, '0.452': 0, '0.453': 0, '0.454': 0, '0.455': 0, '0.456': 0, '0.457': 0, '0.458': 0, '0.459': 0, '0.460': 0}
{'1.451': 1, '1.452': 1, '1.453': 1, '1.454': 1, '1.455': 1, '1.456': 1, '1.457': 1, '1.458': 1, '1.459': 1, '1.460': 1}
{'2.451': 2, '3.452': 2, '3.453': 2, '3.454': 2, '3.455': 2, '3.456': 2, '3.457': 2, '3.458': 2, '3.459': 2, '4.460': 2}
{'3.451': 3, '2.452': 3, '2.453': 3, '2.454': 3, '2.455': 3, '2.456': 3, '2.457': 3, '2.458': 3, '2.459': 3, '3.460': 3}
{'4.451': 4, '4.452': 4, '4.453': 4, '4.454': 4, '4.455': 4, '4.456': 4, '4.457': 4, '4.458': 4, '4.459': 4, '5.460': 4}
{'5.451': 5, '5.452': 5, '5.453': 5, '5.454': 5, '5.455': 5, '5.456': 5, '5.457': 5, '5.458': 5, '5.459': 5, '6.460': 5}
{'6.451': 6, '6.452': 6, '6.453': 6, '6.454': 6, '6.455': 6, '6.456': 6, '6.457': 6, '6.458': 6, '6.459': 6, '7.460': 6}
{'7.451': 7, '7.452': 7, '7.453': 7, '7.454': 7, '7.455': 7, '7.456': 7, '7.457': 7, '7.458': 7, '7.459': 7, '8.460': 7}
{'8.451': 8, '8.452': 8, '8.453': 8, '8.454': 8, '8.455': 8, '8.456': 8, '8.457': 8, '8.458': 8, '8.459': 8, '9.460': 8}
{}
{}

The last two empty dicts should be containing the lower line of nodes, and the lonely node at the last column of the graph, respectively, however it is not the case and I am only able to retrieve the nodes which are somehow connected to the first column.

Is there some way to fix this behaviour?

EDIT: To narrow down the problem a little bit, I believe the problem lies in the dictionary comprehension I used, since I have checked if the attribute trajectory has a value assigned to it by doing:

print(G.nodes['9.455']['trajectory']) 

And the output gives me trajectory 9, which is coherent with which I expect the trajectory to be.