def _batch_by_same_component(self, submission, force_field_id): """Batches a set of requested properties based on which substance they were measured for. Properties which were measured for substances containing the exact same components (but not necessarily in the same amounts) will be placed into the same batch. Parameters ---------- submission: EvaluatorClient._Submission The full request submission. force_field_id: str The unique id of the force field to use. Returns ------- list of Batch The property batches. """ reserved_batch_ids = { *self._queued_batches.keys(), *self._finished_batches.keys(), } batches = [] for substance in submission.dataset.substances: batch = Batch() batch.force_field_id = force_field_id batch.enable_data_caching = self._enable_data_caching # Make sure we don't somehow generate the same uuid # twice (although this is very unlikely to ever happen). while batch.id in reserved_batch_ids: batch.id = str(uuid.uuid4()).replace("-", "") batch.queued_properties = [ x for x in submission.dataset.properties_by_substance(substance) ] batch.options = RequestOptions.parse_json( submission.options.json()) batch.parameter_gradient_keys = copy.deepcopy( submission.parameter_gradient_keys) reserved_batch_ids.add(batch.id) batches.append(batch) return batches
def _batch_by_shared_component(self, submission, force_field_id): """Batches a set of requested properties based on which substance they were measured for. Properties which were measured for substances sharing at least one common component (defined only by its smiles pattern and not necessarily in the same amount) will be placed into the same batch. Parameters ---------- submission: EvaluatorClient._Submission The full request submission. force_field_id: str The unique id of the force field to use. Returns ------- list of Batch The property batches. """ reserved_batch_ids = { *self._queued_batches.keys(), *self._finished_batches.keys(), } all_smiles = set(x.smiles for y in submission.dataset.substances for x in y) # Build a graph containing all of the different component # smiles patterns as nodes. substance_graph = networkx.Graph() substance_graph.add_nodes_from(all_smiles) # Add edges to the graph based on which substances contain # the different component nodes. for substance in submission.dataset.substances: if len(substance) < 2: continue smiles = [x.smiles for x in substance] for smiles_a, smiles_b in zip(smiles, smiles[1:]): substance_graph.add_edge(smiles_a, smiles_b) # Find clustered islands of those smiles which exist in # overlapping substances. islands = [ substance_graph.subgraph(c) for c in networkx.connected_components(substance_graph) ] # Create one batch per island batches = [] for _ in range(len(islands)): batch = Batch() batch.force_field_id = force_field_id # Make sure we don't somehow generate the same uuid # twice (although this is very unlikely to ever happen). while batch.id in reserved_batch_ids: batch.id = str(uuid.uuid4()).replace("-", "") batch.options = RequestOptions.parse_json( submission.options.json()) batch.parameter_gradient_keys = copy.deepcopy( submission.parameter_gradient_keys) reserved_batch_ids.add(batch.id) batches.append(batch) for physical_property in submission.dataset: smiles = [x.smiles for x in physical_property.substance] island_id = 0 for island_id, island in enumerate(islands): if not any(x in island for x in smiles): continue break batches[island_id].queued_properties.append(physical_property) return batches