EvaluatorServer object is responsible for coordinating the estimation of physical property data sets as requested
by evaluator clients. Its primary responsibilities are to:
recieve incoming requests from an evaluator clients to either estimate a dataset of properties, or to query the status of a previous request.
request that each specified calculation layers attempt to estimate the data set of properties, cascading unestimated properties through the different layers.
EvaluatorServer must be created with an accompanying calculation backend
which will be responsible for distributing any calculations launched by the different calculation layers:
with DaskLocalCluster() as calculation_backend: evaluator_server = EvaluatorServer(calculation_backend) evaluator_server.start()
It may also be optionally created using a specific storage backend if the default
LocalFileStorage is not sufficient:
with DaskLocalCluster() as calculation_backend: storage_backend = LocalFileStorage() evaluator_server = EvaluatorServer(calculation_backend, storage_backend) evaluator_server.start()
By default the server will run synchronously until it is killed, however it may also be run asynchronously such that it can be interacted with directly by a client in the same script:
with DaskLocalCluster() as calculation_backend: with EvaluatorServer(calculation_backend) as evaluator_server: # Specify the data set. data_set = PhysicalPropertyDataSet() data_set.add_properties(...) # Specify the force field source. force_field = SmirnoffForceFieldSource.from_path("openff-1.0.0.offxml") # Request the estimation of the data set. request, errors = evaluator_client.request_estimate(data_set,force_field) # Wait for the results. results = request.results(synchronous=True)
When a server recieves a request from a client, it will attempt to split the requested set of properties into
smaller batches, represented by the
Batch object. The server is currently only able to mark entire batches of
estimated properties as being completed, as opposed to individual properties.
Currently the server supports two ways of batching properties:
SameComponents: All properties measured for the substance containing the same components will be batched together. As an example, the density of a 80:20 and a 20:80 mix of ethanol and water would be batched together, but the density of pure ethanol and the density of pure water would be placed into separate batches.
SharedComponents: All properties measured for substances containing at least one common component will be batched together. As an example, the densities of 80:20 and 20:80 mixtures of ethanol and water, and the pure densities of ethanol and water would be batched together.
The mode of batching is set by the client using the
batch_mode attribute of the request options.