def __init__(self):
self.connection_options = ConnectionOptions()
self.estimation_options = RequestOptions()
self.data_set_path = ""
self.weights = {}
self.denominators = {}
self.polling_interval = 600
def _run_calculations(
data_set: "PhysicalPropertyDataSet",
force_field: "ForceField",
polling_interval: int,
request_options: "RequestOptions",
server_config: EvaluatorServerConfig,
) -> "RequestResult":
"""Attempt to estimate the data set using the specified force field.
Parameters
----------
data_set
The data set to estimate.
force_field
The force field to estimate the data set with.
polling_interval
The interval with which to attempt to retrieve the results.
request_options
The options to use when estimating the data set.
server_config
The configuration to use for the evaluator server.
"""
from openff.evaluator.client import ConnectionOptions, EvaluatorClient
calculation_backend = server_config.to_backend()
with calculation_backend:
evaluator_server = server_config.to_server(calculation_backend)
with evaluator_server:
# Request the estimates.
client = EvaluatorClient(
ConnectionOptions(server_port=server_config.port))
request, error = client.request_estimate(
property_set=data_set,
force_field_source=force_field,
options=request_options,
)
if error is not None:
raise error
# Wait for the results.
results, error = request.results(True,
polling_interval=polling_interval)
if error is not None:
raise error
return results
def main():
setup_timestamp_logging()
# Load in the force field
force_field_path = "smirnoff99Frosst-1.1.0.offxml"
force_field_source = SmirnoffForceFieldSource.from_path(force_field_path)
# Load in the data set containing the pure and binary properties.
data_set = PhysicalPropertyDataSet.from_json("pure_data_set.json")
data_set.merge(PhysicalPropertyDataSet.from_json("binary_data_set.json"))
# Set up a server object to run the calculations using.
server = setup_server(backend_type=BackendType.LocalGPU,
max_number_of_workers=1,
port=8001)
with server:
# Request the estimates.
property_estimator = EvaluatorClient(
ConnectionOptions(server_port=8001))
for calculation_layer in ["SimulationLayer", "ReweightingLayer"]:
options = RequestOptions()
options.calculation_layers = [calculation_layer]
parameter_gradient_keys = [
ParameterGradientKey(tag="vdW",
smirks="[#6X4:1]",
attribute="epsilon"),
ParameterGradientKey(tag="vdW",
smirks="[#6X4:1]",
attribute="rmin_half"),
]
request, _ = property_estimator.request_estimate(
property_set=data_set,
force_field_source=force_field_source,
options=options,
parameter_gradient_keys=parameter_gradient_keys,
)
# Wait for the results.
results, _ = request.results(True, 5)
layer_name = re.sub(r"(?<!^)(?=[A-Z])", "_",
calculation_layer).lower()
results.json(f"pure_binary_{layer_name}.json", True)
def from_json(cls, json_source):
"""Creates this class from a JSON string.
Parameters
-------
json_source: str or file-like object
The JSON representation of this class.
"""
if isinstance(json_source, str):
with open(json_source, "r") as file:
dictionary = json.load(file, cls=TypedJSONDecoder)
else:
dictionary = json.load(json_source, cls=TypedJSONDecoder)
if "polling_interval" not in dictionary:
dictionary["polling_interval"] = 600
assert (
"connection_options" in dictionary
and "estimation_options" in dictionary
and "data_set_path" in dictionary
and "weights" in dictionary
and "denominators" in dictionary
and "polling_interval" in dictionary
)
value = cls()
value.connection_options = ConnectionOptions()
value.connection_options.__setstate__(dictionary["connection_options"])
value.estimation_options = RequestOptions()
value.estimation_options.__setstate__(dictionary["estimation_options"])
value.data_set_path = dictionary["data_set_path"]
value.weights = {
property_name: dictionary["weights"][property_name]
for property_name in dictionary["weights"]
}
value.denominators = {
property_name: dictionary["denominators"][property_name]
for property_name in dictionary["denominators"]
}
value.polling_interval = dictionary["polling_interval"]
return value
def main():
setup_timestamp_logging()
# Load in the force field
force_field_path = "smirnoff99Frosst-1.1.0.offxml"
force_field_source = SmirnoffForceFieldSource.from_path(force_field_path)
# Create a data set containing three solvation free energies.
data_set = PhysicalPropertyDataSet.from_json("hydration_data_set.json")
data_set.json("hydration_data_set.json", format=True)
# Set up a server object to run the calculations using.
server = setup_server(backend_type=BackendType.LocalGPU,
max_number_of_workers=1,
port=8002)
with server:
# Request the estimates.
property_estimator = EvaluatorClient(
ConnectionOptions(server_port=8002))
options = RequestOptions()
options.calculation_layers = ["SimulationLayer"]
options.add_schema("SimulationLayer", "SolvationFreeEnergy",
_get_fixed_lambda_schema())
request, _ = property_estimator.request_estimate(
property_set=data_set,
force_field_source=force_field_source,
options=options,
)
# Wait for the results.
results, _ = request.results(True, 60)
# Save the result to file.
results.json("results.json", True)
class OptionsFile:
"""Represents the set of options that a `Evaluator_SMIRNOFF`
target will be run with.
Attributes
----------
connection_options: openff.evaluator.client.ConnectionOptions
The options for how the `evaluator` client should
connect to a running server instance.
estimation_options: openff.evaluator.client.RequestOptions
The options for how properties should be estimated by the
`evaluator` (e.g. the uncertainties to which properties
should be estimated).
data_set_path: str
The path to a JSON serialized PhysicalPropertyDataSet which
contains those physical properties which will be optimised
against.
weights: dict of float
The weighting of each property which will be optimised against.
denominators: dict of str and unit.Quantity
The denominators will be used to remove units from the properties
and scale their values.
polling_interval: float
The time interval with which to check whether the evaluator has
finished fulfilling the request (in seconds).
"""
def __init__(self):
self.connection_options = ConnectionOptions()
self.estimation_options = RequestOptions()
self.data_set_path = ""
self.weights = {}
self.denominators = {}
self.polling_interval = 600
def to_json(self):
"""Converts this class into a JSON string.
Returns
-------
str
The JSON representation of this class.
"""
value = {
"connection_options": self.connection_options.__getstate__(),
"estimation_options": self.estimation_options.__getstate__(),
"data_set_path": self.data_set_path,
"weights": {
property_name: self.weights[property_name]
for property_name in self.weights
},
"denominators": {
property_name: self.denominators[property_name]
for property_name in self.denominators
},
"polling_interval": self.polling_interval
}
return json.dumps(
value,
sort_keys=True,
indent=4,
separators=(",", ": "),
cls=TypedJSONEncoder,
)
@classmethod
def from_json(cls, json_source):
"""Creates this class from a JSON string.
Parameters
-------
json_source: str or file-like object
The JSON representation of this class.
"""
if isinstance(json_source, str):
with open(json_source, "r") as file:
dictionary = json.load(file, cls=TypedJSONDecoder)
else:
dictionary = json.load(json_source, cls=TypedJSONDecoder)
if "polling_interval" not in dictionary:
dictionary["polling_interval"] = 600
assert (
"connection_options" in dictionary
and "estimation_options" in dictionary
and "data_set_path" in dictionary
and "weights" in dictionary
and "denominators" in dictionary
and "polling_interval" in dictionary
)
value = cls()
value.connection_options = ConnectionOptions()
value.connection_options.__setstate__(dictionary["connection_options"])
value.estimation_options = RequestOptions()
value.estimation_options.__setstate__(dictionary["estimation_options"])
value.data_set_path = dictionary["data_set_path"]
value.weights = {
property_name: dictionary["weights"][property_name]
for property_name in dictionary["weights"]
}
value.denominators = {
property_name: dictionary["denominators"][property_name]
for property_name in dictionary["denominators"]
}
value.polling_interval = dictionary["polling_interval"]
return value