adding minimal test

Signed-off-by: Nicholas Parente <parentenickj@gmail.com>
py-why · Dec 30, 2024 · ed55a3e · ed55a3e
1 parent 5f3bc5b
commit ed55a3e
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Showing 2 changed files with 24 additions and 6 deletions.
diff --git a/dowhy/causal_identifier/auto_identifier.py b/dowhy/causal_identifier/auto_identifier.py
@@ -91,14 +91,13 @@ def __init__(
         backdoor_adjustment: BackdoorAdjustment = BackdoorAdjustment.BACKDOOR_DEFAULT,
         optimize_backdoor: bool = False,
         costs: Optional[List] = None,
+        # By default, we will just compute a minimal adjustment set
         covariate_adjustment: CovariateAdjustment = CovariateAdjustment.COVARIATE_ADJUSTMENT_DEFAULT,
     ):
         self.estimand_type = estimand_type
         self.backdoor_adjustment = backdoor_adjustment
         self.optimize_backdoor = optimize_backdoor
         self.costs = costs
-        # By default, we will just compute a minimal adjustment set (since it can be
-        # quite lengthy to compute an exhaustive set)
         self.covariate_adjustment = covariate_adjustment
         self.logger = logging.getLogger(__name__)
 
@@ -895,10 +894,10 @@ def identify_complete_adjustment_set(
         # In default case, we don't find all exhaustive adjustment sets
         adjustment_set = nx.algorithms.find_minimal_d_separator(
             graph_pbd,
-            action_nodes,
-            outcome_nodes,
+            set(action_nodes),
+            set(outcome_nodes),
             # Require the adjustment set to consist only of observed nodes
-            restricted=((set(graph.nodes) - set(pcp_nodes)) & set(observed_nodes))
+            restricted=((set(graph_pbd.nodes) - set(pcp_nodes)) & set(observed_nodes))
         )
         if adjustment_set is None:
             logger.info("No adjustment sets found.")

diff --git a/tests/causal_identifiers/test_complete_adjustment_identifier.py b/tests/causal_identifiers/test_complete_adjustment_identifier.py
@@ -9,7 +9,7 @@
 
 
 class TestGeneralAdjustmentIdentification(object):
-    def test_identify_general_adjustment(self, example_complete_adjustment_graph_solution: IdentificationTestGeneralCovariateAdjustmentGraphSolution):
+    def test_identify_exhaustive_adjustment(self, example_complete_adjustment_graph_solution: IdentificationTestGeneralCovariateAdjustmentGraphSolution):
         graph = example_complete_adjustment_graph_solution.graph
         expected_sets = example_complete_adjustment_graph_solution.exhaustive_adjustment_sets
         adjustment_set_results = identify_complete_adjustment_set(
@@ -30,4 +30,23 @@ def test_identify_general_adjustment(self, example_complete_adjustment_graph_sol
             for s in expected_sets
         )
 
+    def test_identify_minimal_adjustment(self, example_complete_adjustment_graph_solution: IdentificationTestGeneralCovariateAdjustmentGraphSolution):
+        graph = example_complete_adjustment_graph_solution.graph
+        expected_set = example_complete_adjustment_graph_solution.minimal_adjustment_sets[0]
+        adjustment_set_results = identify_complete_adjustment_set(
+            graph,
+            action_nodes=["X"],
+            outcome_nodes=["Y"],
+            observed_nodes=example_complete_adjustment_graph_solution.observed_nodes,
+            covariate_adjustment=CovariateAdjustment.COVARIATE_ADJUSTMENT_DEFAULT,
+        )
+        adjustment_sets = [
+            set(adjustment_set.get_variables())
+            for adjustment_set in adjustment_set_results
+            if len(adjustment_set.get_variables()) > 0
+        ]
+
+        assert (len(expected_set) == 0 and len(adjustment_sets) == 0) or set(expected_set) in adjustment_sets
+
+