89 add tests to cover missing scorer behavior

src/konnektor/tests/network_planners/generators/test_heuristic_maximal_network_planner.py

@@ -6,12 +6,16 @@
 from konnektor.network_analysis import get_is_connected
 from konnektor.network_planners import HeuristicMaximalNetworkGenerator
 from konnektor.utils.toy_data import build_random_dataset
-
+from konnektor.tests.network_planners.conf import (
+    genScorer,
+    GenAtomMapper,
+    BadMapper,
+    SuperBadMapper
+)
 
 @pytest.mark.parametrize("n_process", [1, 2])
 @pytest.mark.parametrize("with_progress", [True, False])
-@pytest.mark.parametrize("with_scorer", [True, False])
-def test_generate_maximal_network(with_progress, with_scorer, n_process):
+def test_generate_maximal_network(with_progress, n_process):
     n_compounds = 20
     components, genMapper, genScorer = build_random_dataset(n_compounds=n_compounds)
 
@@ -30,3 +34,31 @@ def test_generate_maximal_network(with_progress, with_scorer, n_process):
     assert len(network.edges) <= edge_count
     assert len(network.edges) > n_compounds
     assert get_is_connected(network)
+
+@pytest.mark.parametrize("n_process", [1, 2])
+@pytest.mark.parametrize("with_progress", [True, False])
+def test_generate_maximal_network_missing_scorer(with_progress, n_process):
+    """If no scorer is provided, the first mapping of the last mapper should be used.
+       Note: this test isn't great because BadMapper only returns one mapping
+    """
+    n_compounds = 4
+    components, _, _ = build_random_dataset(n_compounds=n_compounds)
+
+    planner = HeuristicMaximalNetworkGenerator(
+        mappers= [SuperBadMapper(), GenAtomMapper(), BadMapper()],
+        scorer=None,
+        n_samples=3,
+        progress=with_progress,
+        n_processes=n_process,
+    )
+    network = planner.generate_ligand_network(components)
+
+    assert len(network.nodes) == n_compounds
+
+    edge_count = n_compounds * 3
+    assert len(network.edges) <= edge_count
+    assert len(network.edges) > n_compounds
+    assert get_is_connected(network)
+
+    assert [e.componentA_to_componentB for e in network.edges] == len(network.edges)*[{0:0}]
+

src/konnektor/tests/network_planners/generators/test_maximal_network_planner.py

@@ -9,8 +9,11 @@
     toluene_vs_others,
     genScorer,
     GenAtomMapper,
+    BadMapper,
+    SuperBadMapper
 )
-
+from gufe import LigandAtomMapping, AtomMapper, AtomMapping
+from konnektor.utils.toy_data import build_random_dataset
 
 @pytest.mark.parametrize("n_process", [1, 2])
 @pytest.mark.parametrize("with_progress", [True, False])
@@ -41,3 +44,24 @@ def test_generate_maximal_network(
     else:
         for edge in network.edges:
             assert "score" not in edge.annotations
+
+@pytest.mark.parametrize("n_process", [1, 2])
+@pytest.mark.parametrize("with_progress", [True, False])
+def test_generate_maximal_network_missing_scorer(toluene_vs_others, n_process, with_progress):
+    """If no scorer is provided, the first mapping of the last mapper should be used.
+       Note: this test isn't great because BadMapper only returns one mapping
+    """
+
+    toluene, others = toluene_vs_others
+    components = others+[toluene]
+
+    planner = MaximalNetworkGenerator(
+        mappers= [SuperBadMapper(), GenAtomMapper(), BadMapper()],
+        scorer=None,
+        progress=with_progress,
+        n_processes=n_process,
+    )
+
+    network = planner.generate_ligand_network(components)
+
+    assert [e.componentA_to_componentB for e in network.edges] == len(network.edges)*[{0:0}]