Add tests for BP edge cases and UAI errors

Author: Morningliumengkun

tests/test_uai_parser.py

@@ -58,6 +58,46 @@ def test_read_evidence_file(self):
         evidence = read_evidence_file("examples/simple_model.evid")
         self.assertEqual(evidence, {1: 1})
 
+    def test_invalid_network_type(self):
+        content = "\n".join(
+            [
+                "INVALID",
+                "1",
+                "2",
+                "0",
+            ]
+        )
+        with self.assertRaises(ValueError):
+            read_model_from_string(content)
+
+    def test_scope_size_mismatch(self):
+        content = "\n".join(
+            [
+                "MARKOV",
+                "2",
+                "2 2",
+                "1",
+                "2 0",
+                "2",
+                "0.5 0.5",
+            ]
+        )
+        with self.assertRaises(ValueError):
+            read_model_from_string(content)
+
+    def test_missing_table_entries(self):
+        content = "\n".join(
+            [
+                "MARKOV",
+                "1",
+                "2",
+                "1",
+                "1 0",
+            ]
+        )
+        with self.assertRaises(ValueError):
+            read_model_from_string(content)
+
 
 if __name__ == "__main__":
     unittest.main()

tests/testcase.py

@@ -16,6 +16,7 @@
     initial_state,
     collect_message,
     process_message,
+    apply_evidence,
 )
 
 
@@ -91,6 +92,45 @@ def test_message_normalization(self):
             for msg in var_msgs:
                 self.assertAlmostEqual(float(msg.sum()), 1.0, places=6)
 
+    def test_zero_message_handling(self):
+        content = "\n".join(
+            [
+                "MARKOV",
+                "1",
+                "2",
+                "2",
+                "1 0",
+                "1 0",
+                "2",
+                "0.0 0.0",
+                "2",
+                "0.7 0.3",
+            ]
+        )
+        model = read_model_from_string(content)
+        bp = BeliefPropagation(model)
+        state = initial_state(bp)
+        collect_message(bp, state, normalize=True)
+        process_message(bp, state, normalize=True, damping=0.0)
+        self.assertAlmostEqual(float(state.message_in[0][0].sum()), 0.0, places=6)
+        self.assertAlmostEqual(float(state.message_out[0][1].sum()), 0.0, places=6)
+
+    def test_evidence_out_of_range_zeros_factor(self):
+        content = "\n".join(
+            [
+                "MARKOV",
+                "1",
+                "2",
+                "1",
+                "1 0",
+                "2",
+                "0.4 0.6",
+            ]
+        )
+        model = read_model_from_string(content)
+        bp = apply_evidence(BeliefPropagation(model), {1: 5})
+        self.assertAlmostEqual(float(bp.factors[0].values.sum()), 0.0, places=6)
+
 
 if __name__ == "__main__":
     unittest.main()