Csse tdmb 537h

.github/workflows/CI.yml

@@ -180,7 +180,7 @@ jobs:
       #if: false
       run: |
         conda remove qcelemental --force
-        python -m pip install 'git+https://github.com/MolSSI/QCElemental.git@next2025' --no-deps
+        python -m pip install 'git+https://github.com/loriab/QCElemental.git@csse_layout_536g' --no-deps
 
       # note: conda remove --force, not mamba remove --force b/c https://github.com/mamba-org/mamba/issues/412
       #       alt. is micromamba but not yet ready for setup-miniconda https://github.com/conda-incubator/setup-miniconda/issues/75
@@ -200,7 +200,7 @@ jobs:
       run: |
         conda install pydantic=2 -c conda-forge
         conda remove qcelemental --force
-        python -m pip install 'git+https://github.com/MolSSI/QCElemental.git@next2025' --no-deps
+        python -m pip install 'git+https://github.com/loriab/QCElemental.git@csse_layout_536g' --no-deps
 
     - name: Special Config - Forced Interface Upgrade
       if: matrix.cfg.label == 'Psi4-1.6'

qcengine/procedures/torsiondrive.py

@@ -8,6 +8,7 @@
     FailedOperation,
     Molecule,
     OptimizationInput,
+    OptimizationProperties,
     OptimizationResult,
     TorsionDriveInput,
     TorsionDriveResult,
@@ -119,16 +120,20 @@ def _compute(self, input_model: "TorsionDriveInput", config: "TaskConfig"):
         }
 
         # even if we hit an error during the torsiondrive, we output what we can
-        output_data["final_energies"], output_data["final_molecules"] = {}, {}
+        output_data["scan_properties"], output_data["final_molecules"] = {}, {}
 
         for grid_point, results in optimization_results.items():
 
-            final_energy, final_molecule = self._find_final_results(results)
+            final_energy, final_properties, final_molecule = self._find_final_results(results)
 
-            output_data["final_energies"][grid_point] = final_energy
+            # v1: output_data["final_energies"][grid_point] = final_energy
+            output_data["scan_properties"][grid_point] = final_properties
             output_data["final_molecules"][grid_point] = final_molecule
 
         output_data["scan_results"] = optimization_results
+        output_data["properties"] = {
+            "calcinfo_ngrid": len(optimization_results),
+        }
 
         if error is not None:
             output_data["error"] = error
@@ -211,14 +216,18 @@ def _spawn_optimization(
     @staticmethod
     def _find_final_results(
         optimization_results: List[OptimizationResult],
-    ) -> Tuple[float, Molecule]:
+    ) -> Tuple[float, OptimizationProperties, Molecule]:
         """Returns the energy and final molecule of the lowest energy optimization
         in a set."""
 
         final_energies = np.array([result.properties.return_energy for result in optimization_results])
         lowest_energy_idx = final_energies.argmin()
 
-        return float(final_energies[lowest_energy_idx]), optimization_results[lowest_energy_idx].final_molecule
+        return (
+            float(final_energies[lowest_energy_idx]),
+            optimization_results[lowest_energy_idx].properties,
+            optimization_results[lowest_energy_idx].final_molecule,
+        )
 
     def _spawn_optimizations(
         self, next_jobs: Dict[str, List[float]], input_model: "TorsionDriveInput", config: "TaskConfig"

qcengine/tests/test_procedures.py

@@ -687,7 +687,10 @@ def test_torsiondrive_generic(schema_versions, request, scan_ptcl):
     if not (from_v2(request.node.name) and scan_ptcl == "none"):
         assert {*opthist_tgt} == expected_grid_ids
 
-    assert {*ret.final_energies} == expected_grid_ids
+    if "v2" in request.node.name:
+        assert {*ret.scan_properties} == expected_grid_ids
+    else:
+        assert {*ret.final_energies} == expected_grid_ids
     assert {*ret.final_molecules} == expected_grid_ids
 
     assert (
@@ -741,9 +744,9 @@ def test_torsiondrive_extra_constraints(schema_versions, request):
 
     if from_v2(request.node.name):
         input_data = models.TorsionDriveInput(
-            initial_molecules=[models.Molecule(**qcng.get_molecule("propane", return_dict=True))],
+            initial_molecule=[models.Molecule(**qcng.get_molecule("propane", return_dict=True))],
             specification=models.TorsionDriveSpecification(
-                keywords=models.TDKeywords(dihedrals=[(3, 0, 1, 2)], grid_spacing=[180]),
+                keywords=models.TorsionDriveKeywords(dihedrals=[(3, 0, 1, 2)], grid_spacing=[180]),
                 specification=models.OptimizationSpecification(
                     program="geomeTRIC",
                     keywords=keywords,
@@ -753,7 +756,9 @@ def test_torsiondrive_extra_constraints(schema_versions, request):
                         driver=models.DriverEnum.gradient,
                         model=models.Model(method="small", basis=None),
                     ),
+                    protocols=models.OptimizationProtocols(trajectory_results="all"),
                 ),
+                protocols=models.TorsionDriveProtocols(scan_results="all"),
             ),
         )
     else:
@@ -782,11 +787,16 @@ def test_torsiondrive_extra_constraints(schema_versions, request):
     assert ret.success
 
     expected_grid_ids = {"180", "0"}
+    opthist_tgt = ret.scan_results if "v2" in request.node.name else ret.optimization_history
 
-    assert {*ret.optimization_history} == expected_grid_ids
-
-    assert {*ret.final_energies} == expected_grid_ids
+    assert {*opthist_tgt} == expected_grid_ids
+    if "v2" in request.node.name:
+        assert {*ret.scan_properties} == expected_grid_ids
+    else:
+        assert {*ret.final_energies} == expected_grid_ids
     assert {*ret.final_molecules} == expected_grid_ids
+    if "v2" in request.node.name:
+        assert ret.properties.calcinfo_ngrid == 2
 
     assert (
         pytest.approx(ret.final_molecules["180"].measure([3, 0, 1, 2]), abs=1.0e-2) == 180.0
@@ -796,11 +806,11 @@ def test_torsiondrive_extra_constraints(schema_versions, request):
     assert pytest.approx(ret.final_molecules["0"].measure([3, 0, 1, 2]), abs=1.0e-2) == 0.0
 
     assert ret.provenance.creator.lower() == "torsiondrive"
-    assert ret.optimization_history["180"][0].provenance.creator.lower() == "geometric"
+    assert opthist_tgt["180"][0].provenance.creator.lower() == "geometric"
     if "v2" in request.node.name:
-        assert ret.optimization_history["180"][0].trajectory_results[0].provenance.creator.lower() == "mace"
+        assert opthist_tgt["180"][0].trajectory_results[0].provenance.creator.lower() == "mace"
     else:
-        assert ret.optimization_history["180"][0].trajectory[0].provenance.creator.lower() == "mace"
+        assert opthist_tgt["180"][0].trajectory[0].provenance.creator.lower() == "mace"
 
     assert "Using MACE-OFF23 MODEL for MACECalculator" in ret.stdout
     assert "All optimizations converged at lowest energy. Job Finished!\n" in ret.stdout