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openforcefield · Nov 14, 2022 · f0ad914 · f0ad914
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commit f0ad914
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Showing 9 changed files with 157 additions and 97 deletions.
diff --git a/openff/qcsubmit/datasets/datasets.py b/openff/qcsubmit/datasets/datasets.py
@@ -25,15 +25,11 @@
 from qcportal.datasets.optimization import OptimizationDatasetNewEntry
 from qcportal.datasets.singlepoint import SinglepointDatasetNewEntry
 from qcportal.datasets.torsiondrive import TorsiondriveDatasetNewEntry
-from qcportal.records.singlepoint import SinglepointDriver, QCSpecification
 from qcportal.records.optimization import OptimizationSpecification
+from qcportal.records.singlepoint import QCSpecification, SinglepointDriver
 from typing_extensions import Literal
 
-from openff.qcsubmit.common_structures import (
-    CommonBase,
-    Metadata,
-    MoleculeAttributes,
-)
+from openff.qcsubmit.common_structures import CommonBase, Metadata, MoleculeAttributes
 from openff.qcsubmit.constraints import Constraints
 from openff.qcsubmit.datasets.entries import (
     DatasetEntry,
@@ -150,7 +146,6 @@ def _get_specifications(self) -> "OptimizationSpecification":
         """
         raise NotImplementedError()
 
-
     @abc.abstractmethod
     def _get_entries(self) -> List[Any]:
         """Add entries to the Dataset's corresponding Collection.
@@ -167,7 +162,6 @@ def _get_entries(self) -> List[Any]:
         """
         pass
 
-
     @abc.abstractmethod
     def to_tasks(self) -> Dict[str, List[Union[AtomicInput, OptimizationInput]]]:
         """
@@ -199,7 +193,6 @@ def submit(
 
         """
 
-
         # pre submission checks
         # make sure we have some QCSpec to submit
         self._check_qc_specs()
@@ -738,7 +731,6 @@ def _molecules_to_inchikey(self) -> List[str]:
         return inchikey
 
 
-
 # TODO: SinglepointDataset
 class BasicDataset(_BaseDataset):
     """
@@ -799,7 +791,9 @@ def __add__(self, other: "BasicDataset") -> "BasicDataset":
 
         return new_dataset
 
-    def _generate_collection(self, client: "PortalClient") -> ptl.datasets.SinglepointDataset:
+    def _generate_collection(
+        self, client: "PortalClient"
+    ) -> ptl.datasets.SinglepointDataset:
 
         return client.add_dataset(
             dataset_type="singlepoint",
@@ -817,7 +811,7 @@ def _get_specifications(self) -> Dict[str, QCSpecification]:
         """Needed for `submit` usage."""
 
         ret = {}
-        for spec_name,spec in self.qc_specifications.items():
+        for spec_name, spec in self.qc_specifications.items():
             ret[spec_name] = QCSpecification(
                 driver=self.driver,
                 method=spec.method,
@@ -829,7 +823,6 @@ def _get_specifications(self) -> Dict[str, QCSpecification]:
 
         return ret
 
-
     def _get_entries(self) -> List[SinglepointDatasetNewEntry]:
 
         entries: List[SinglepointDatasetNewEntry] = []
@@ -844,13 +837,16 @@ def _get_entries(self) -> List[SinglepointDatasetNewEntry]:
 
                 for j, molecule in enumerate(entry.initial_molecules):
                     name = index + f"-{tag + j}"
-                    entries.append(SinglepointDatasetNewEntry(name=name, molecule=molecule))
+                    entries.append(
+                        SinglepointDatasetNewEntry(name=name, molecule=molecule)
+                    )
             else:
                 entries.append(
                     SinglepointDatasetNewEntry(
                         name=entry_name,
                         molecule=entry.initial_molecules[0],
-                    ))
+                    )
+                )
 
         return entries
 
@@ -1008,7 +1004,7 @@ def _get_specifications(self) -> Dict[str, OptimizationSpecification]:
 
         ret = {}
 
-        for spec_name,spec in self.qc_specifications.items():
+        for spec_name, spec in self.qc_specifications.items():
             qc_spec = QCSpecification(
                 driver=self.driver,
                 method=spec.method,
@@ -1021,7 +1017,7 @@ def _get_specifications(self) -> Dict[str, OptimizationSpecification]:
             ret[spec_name] = OptimizationSpecification(
                 program=self.optimization_procedure.program,
                 qc_specification=qc_spec,
-                keywords=opt_kw
+                keywords=opt_kw,
             )
 
         return ret
@@ -1040,17 +1036,21 @@ def _get_entries(self) -> List[OptimizationDatasetNewEntry]:
 
                 for j, molecule in enumerate(entry.initial_molecules):
                     name = index + f"-{tag + j}"
-                    entries.append(OptimizationDatasetNewEntry(name=name, initial_molecule=molecule))
+                    entries.append(
+                        OptimizationDatasetNewEntry(
+                            name=name, initial_molecule=molecule
+                        )
+                    )
             else:
                 entries.append(
                     OptimizationDatasetNewEntry(
                         name=entry_name,
                         initial_molecule=entry.initial_molecules[0],
-                    ))
+                    )
+                )
 
         return entries
 
-
     def to_tasks(self) -> Dict[str, List[OptimizationInput]]:
         """
         Build a list of QCEngine optimisation inputs organised by the optimisation engine which should be used to run the task.
@@ -1222,15 +1222,16 @@ def _get_entries(self) -> List[TorsiondriveDatasetNewEntry]:
 
             td_keywords.update(entry.keywords.dict(exclude_defaults=True))
 
-            entries.append(TorsiondriveDatasetNewEntry(
-                name=entry_name,
-                initial_molecules=entry.initial_molecules,
-                torsiondrive_keywords=td_keywords
-            ))
+            entries.append(
+                TorsiondriveDatasetNewEntry(
+                    name=entry_name,
+                    initial_molecules=entry.initial_molecules,
+                    torsiondrive_keywords=td_keywords,
+                )
+            )
 
         return entries
 
-
     def to_tasks(self) -> Dict[str, List[OptimizationInput]]:
         """Build a list of QCEngine procedure tasks which correspond to this dataset."""
 

diff --git a/openff/qcsubmit/procedures.py b/openff/qcsubmit/procedures.py
@@ -2,7 +2,7 @@
 The procedure settings controllers
 """
 
-from typing import Dict, Any
+from typing import Any, Dict
 
 from pydantic import BaseModel, Field, validator
 from qcportal.records.optimization import OptimizationSpecification

diff --git a/openff/qcsubmit/results/caching.py b/openff/qcsubmit/results/caching.py
@@ -9,8 +9,12 @@
 from openff.toolkit.topology import Molecule
 from qcportal import PortalClient
 from qcportal.molecules import Molecule as QCMolecule
-from qcportal.records import TorsiondriveRecord
-from qcportal.records import OptimizationRecord, BaseRecord, SinglepointRecord
+from qcportal.records import (
+    BaseRecord,
+    OptimizationRecord,
+    SinglepointRecord,
+    TorsiondriveRecord,
+)
 
 try:
     from openmm import unit
@@ -159,7 +163,7 @@ def cached_query_procedures(client_address: str, record_ids: List[str]) -> List[
     client_address = client_address.rstrip("/")
     client = cached_fractal_client(client_address)
 
-    query_limit = client.api_limits['get_records']
+    query_limit = client.api_limits["get_records"]
 
     return _cached_client_query(
         client_address,
@@ -186,7 +190,7 @@ def cached_query_molecules(
     client_address = client_address.rstrip("/")
     client = cached_fractal_client(client_address)
 
-    query_limit = client.api_limits['get_molecules']
+    query_limit = client.api_limits["get_molecules"]
 
     return _cached_client_query(
         client_address,
@@ -330,10 +334,14 @@ def cached_query_torsion_drive_results(
 
         qc_record = qc_records[result.record_id]
 
-        qc_grid_molecules = [(grid_point, opt.final_molecule)
-                             for grid_point, opt in qc_record.minimum_optimizations.items()]
+        qc_grid_molecules = [
+            (grid_point, opt.final_molecule)
+            for grid_point, opt in qc_record.minimum_optimizations.items()
+        ]
         # order the ids so the conformers follow the torsiondrive scan range
-        qc_grid_molecules.sort(key=lambda s: tuple(float(x) for x in s.strip("[]").split(", ")))
+        qc_grid_molecules.sort(
+            key=lambda s: tuple(float(x) for x in s.strip("[]").split(", "))
+        )
 
         molecule: Molecule = Molecule.from_mapped_smiles(
             result.cmiles, allow_undefined_stereo=True

diff --git a/openff/qcsubmit/results/filters.py b/openff/qcsubmit/results/filters.py
@@ -16,8 +16,8 @@
 from pydantic import BaseModel, Field, PrivateAttr, root_validator, validator
 from qcelemental.molutil import guess_connectivity
 from qcportal.records import (
-    OptimizationRecord,
     BaseRecord,
+    OptimizationRecord,
     RecordStatusEnum,
     SinglepointRecord,
 )
@@ -26,6 +26,7 @@
     from openmm import unit
 except ImportError:
     from simtk import unit
+
 from typing_extensions import Literal
 
 from openff.qcsubmit.results.results import (
@@ -234,7 +235,12 @@ class LowestEnergyFilter(SinglepointRecordGroupFilter):
     def _filter_function(
         self,
         entries: List[
-            Tuple["_BaseResult", Union[SinglepointRecord, OptimizationRecord], Molecule, str]
+            Tuple[
+                "_BaseResult",
+                Union[SinglepointRecord, OptimizationRecord],
+                Molecule,
+                str,
+            ]
         ],
     ) -> List[Tuple["_BaseResult", str]]:
         """Only return the lowest energy entry or final molecule."""
@@ -366,7 +372,12 @@ def _compute_rmsd_matrix(self, molecule: Molecule) -> numpy.ndarray:
     def _filter_function(
         self,
         entries: List[
-            Tuple["_BaseResult", Union[SinglepointRecord, OptimizationRecord], Molecule, str]
+            Tuple[
+                "_BaseResult",
+                Union[SinglepointRecord, OptimizationRecord],
+                Molecule,
+                str,
+            ]
         ],
     ) -> List[Tuple["_BaseResult", str]]:
 
@@ -440,7 +451,12 @@ class MinimumConformersFilter(SinglepointRecordGroupFilter):
     def _filter_function(
         self,
         entries: List[
-            Tuple["_BaseResult", Union[SinglepointRecord, OptimizationRecord], Molecule, str]
+            Tuple[
+                "_BaseResult",
+                Union[SinglepointRecord, OptimizationRecord],
+                Molecule,
+                str,
+            ]
         ],
     ) -> List[Tuple["_BaseResult", str]]: