Yujia Zheng

Thanks so much! Would you like to incorporate it into a PR, so that these functions can be merged into causal-learn after tests? Of course, these functions are already super...

Hi, these rules were not included in the implementation. The pull request by @kenneth-lee-ch has just been merged. It would be great if you are interested in incorporating rules 5,6,7...

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](https://github.com/cmu-phil/causal-learn/blob/main/tests/TestGraphVisualization.py). This...

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...

Hi all @fengxie009 @tofuwen, just would like to quickly check whether there are any updates on this PR. Please feel free to let others know if there are any questions...

Hi, this [improved version](https://github.com/verae98/Causal-discovery/blob/master/FastBackgroundKnowledge.py) of BackGroundKnowledge might be helpful, which is proposed and implemented by @verae98. Also a related issue: #90 Not sure if the solution is 100% free of...

Hi @fengxie009 and @tofuwen, are there any updates on this PR? I believe some quick tests to make sure that the modification is correct is enough to merge this. It...

Hi, maybe something as follows could be helpful: ``` reshaped_coeff = np.zeros((T, N, N)) for t in range(T): block = coeff[:, N*t:N*(t+1)] reshaped_coeff[t] = block ```

Hey, if the weight is just for some type of coefficient but not really something 'causal', perhaps regression-based methods can do it (e.g., DirectLiNGAM). I'm not sure what methods could...

Yea, these (DAG structure learning methods) could produce a weighted DAG, but the weight does not necessarily correspond to the 'causal strength'. I'm not aware of any formal definition of...