Renaming or Setting labels on Nodes about causal-learn

[kunwuz]

I see, that requires some refactorization of the graph classes in causal-learn. For now, it seems that creating a mapping/look-up table is the easiest way. We have put it on the list. Please also feel free to let me know if you have any suggestions or would like to improve it together.

[kunwuz]

Hi, the recommended way to assign labels to the nodes is 'cg.draw_pydot_graph(labels=[“A”, “B”, “C”])' or 'GraphUtils.to_pydot(cg.G, labels=[“A”, “B”, “C”])', as mentioned in the documentation. Here are some usage examples.

This visualizes the graph with assigned labels. But I'm not sure if you are looking for something else.

[priamai]

That is only for saving in pydot, I need to rewrite the actual node names for my downstream tasks and avoid confusion when referring to the original dataframe e.g. variable names.

[priamai]

@kunwuz for example when I add the Background Knowledge I want to do it by referring to the real node names defined in my ground truth NetworkX graph, instead now I have to go back and forward converting between the X{0} notation and the real variable names. Hope it makes better sense.