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# MIT License
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# Copyright (c) 2022 GT4SD team
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from typing import Any, Dict, List
from .core import PropertyPredictor
from .crystals import CRYSTALS_PROPERTY_PREDICTOR_FACTORY
from .molecules import MOLECULE_PROPERTY_PREDICTOR_FACTORY
from .proteins import PROTEIN_PROPERTY_PREDICTOR_FACTORY
from .scorer import (
MoleculePropertyPredictorScorer,
PropertyPredictorScorer,
ProteinPropertyPredictorScorer,
)
PROPERTY_PREDICTOR_FACTORY: Dict[str, Any] = {
**CRYSTALS_PROPERTY_PREDICTOR_FACTORY,
**MOLECULE_PROPERTY_PREDICTOR_FACTORY,
**PROTEIN_PROPERTY_PREDICTOR_FACTORY,
}
AVAILABLE_PROPERTY_PREDICTORS = sorted(PROPERTY_PREDICTOR_FACTORY.keys())
SCORING_FACTORY_WITH_PROPERTY_PREDICTORS = {
"property_predictor_scorer": PropertyPredictorScorer,
"molecule_property_predictor_scorer": MoleculePropertyPredictorScorer,
"protein_property_predictor_scorer": ProteinPropertyPredictorScorer,
}
AVAILABLE_SCORING_WITH_PROPERTY_PREDICTORS = sorted(
SCORING_FACTORY_WITH_PROPERTY_PREDICTORS.keys()
)
[docs]class PropertyPredictorRegistry:
"""A registry for property predictors."""
[docs] @staticmethod
def get_property_predictor_parameters_schema(name: str) -> Dict[str, Any]:
try:
_, parameters_class = PROPERTY_PREDICTOR_FACTORY[name]
return parameters_class.schema_json()
except KeyError:
raise ValueError(
f"Property predictor name={name} not supported. Pick one from {AVAILABLE_PROPERTY_PREDICTORS}"
)
[docs] @staticmethod
def get_property_predictor(
name: str, parameters: Dict[str, Any] = {}
) -> PropertyPredictor:
try:
property_class, parameters_class = PROPERTY_PREDICTOR_FACTORY[name]
return property_class(parameters_class(**parameters))
except KeyError:
raise ValueError(
f"Property predictor name={name} not supported. Pick one from {AVAILABLE_PROPERTY_PREDICTORS}"
)
[docs] @staticmethod
def get_property_predictor_scorer(
property_name: str,
scorer_name: str,
target: float,
parameters: Dict[str, Any] = {},
) -> PropertyPredictorScorer:
"""Get a property predictor scorer.
Args:
property_name: name of the property to score.
scorer_name: name of the scorer to use.
target: target score that will be used to get the distance to the score of a molecule or protein (not be confused with parameters["target"]).
parameters: parameters for the scoring function.
Returns:
A property predictor scorer.
"""
scoring_function = PropertyPredictorRegistry.get_property_predictor(
name=property_name, parameters=parameters
)
if scorer_name not in SCORING_FACTORY_WITH_PROPERTY_PREDICTORS:
raise ValueError(
f"Scorer name={scorer_name} not supported. Pick one from {AVAILABLE_SCORING_WITH_PROPERTY_PREDICTORS}"
)
property_predictor_scorer = SCORING_FACTORY_WITH_PROPERTY_PREDICTORS[
scorer_name
]
return property_predictor_scorer(property_name, scoring_function, target)
[docs] @staticmethod
def list_available() -> List[str]:
return AVAILABLE_PROPERTY_PREDICTORS
[docs] @staticmethod
def list_available_scorers() -> List[str]:
return AVAILABLE_SCORING_WITH_PROPERTY_PREDICTORS