py-why / py-why/causal-learn

Background knowledge not working

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Description

Hi! I have come across an issue where even when I forbid certain nodes when using PC, they still appear in my causal graph result:

from causallearn.utils.PCUtils.BackgroundKnowledge import BackgroundKnowledge
from causallearn.search.ConstraintBased.PC import pc

cg_without_background_knowledge = pc(X)  # Run PC and obtain the estimated graph (CausalGraph object)
nodes = cg_without_background_knowledge.G.get_nodes()

bk = BackgroundKnowledge() \
    .add_forbidden_by_node(nodes[0], nodes[1]) \
    .add_forbidden_by_node(nodes[1], nodes[2]) \
    .add_forbidden_by_node(nodes[0], nodes[2]) \
    .add_forbidden_by_node(nodes[0], nodes[3]) \
    .add_forbidden_by_node(nodes[1], nodes[3]) \
    .add_forbidden_by_node(nodes[2], nodes[3])

cg_with_background_knowledge = pc(X, background_knowledge=bk)

assert cg_with_background_knowledge.G.get_edge(nodes[2], nodes[3]) is None
assert cg_with_background_knowledge.G.get_edge(nodes[0], nodes[1]) is None

I get this error, as well as an error for some other node combinations in my background knowledge:

AssertionError Traceback (most recent call last)
Cell In[9], line 18
15 cg_with_background_knowledge = pc(X, background_knowledge=bk)
17 assert cg_with_background_knowledge.G.get_edge(nodes[2], nodes[3]) is None
---> 18 assert cg_with_background_knowledge.G.get_edge(nodes[0], nodes[1]) is None
20 g, edges = fci(X, background_knowledge=bk)
22 sns.heatmap(g.graph, cmap='coolwarm', annot=True, xticklabels=node_names, yticklabels=node_names)

AssertionError:

It seems like if the background knowledge is being used, it's being overriden somewhere. Please help! This also happens with FCI. I looked at the code and I can't figure out why this could be happening.

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Research direction

Reproduce the assertions with the BackgroundKnowledge example, then trace how background_knowledge is passed through causallearn/search/ConstraintBased/PC.py and the FCI entry point. Check where forbidden node pairs are applied during graph construction and orienting; done means the reported forbidden edges are absent for both PC and FCI, with regression coverage for the example.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
machine-learning
Issue type
Bug
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Mostly clear
Newbie friendliness
35/100

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