schrodinger.application.steps.scorers module¶

class schrodinger.application.steps.scorers.PropertyScorer(*args, **kwargs)¶

Bases: schrodinger.application.steps.dataclasses.ScorerMixin, schrodinger.application.steps.basesteps.MolReduceStep

Yield scored molecules where the score is the property value.

The property in the settings is the descriptor name of the property, e.g., ‘MVCorrMW’ or ‘r_rdkit_MolWt’.

class Settings(*args, _param_type=<object object>, **kwargs)¶

Bases: schrodinger.models.parameters.CompoundParam

property: str¶

Base class for all Param classes. A Param is a descriptor for storing data, which means that a single Param instance will manage the data values for multiple instances of the class that owns it. Example:

class Coord(CompoundParam):
    x: int
    y: int

An instance of the Coord class can be created normally, and Params can be accessed as normal attributes:

coord = Coord()
coord.x = 4

When a Param value is set, the valueChanged signal is emitted. Params can be serialized and deserialized to and from JSON. Params can also be nested:

class Atom(CompoundParam):
    coord: Coord
    element: str

propertyChanged¶

pyqtSignal(*types, name: str = …, revision: int = …, arguments: Sequence = …) -> PYQT_SIGNAL

types is normally a sequence of individual types. Each type is either a type object or a string that is the name of a C++ type. Alternatively each type could itself be a sequence of types each describing a different overloaded signal. name is the optional C++ name of the signal. If it is not specified then the name of the class attribute that is bound to the signal is used. revision is the optional revision of the signal that is exported to QML. If it is not specified then 0 is used. arguments is the optional sequence of the names of the signal’s arguments.

propertyReplaced¶

pyqtSignal(*types, name: str = …, revision: int = …, arguments: Sequence = …) -> PYQT_SIGNAL

types is normally a sequence of individual types. Each type is either a type object or a string that is the name of a C++ type. Alternatively each type could itself be a sequence of types each describing a different overloaded signal. name is the optional C++ name of the signal. If it is not specified then the name of the class attribute that is bound to the signal is used. revision is the optional revision of the signal that is exported to QML. If it is not specified then 0 is used. arguments is the optional sequence of the names of the signal’s arguments.

validateSettings()¶

Check whether the step settings are valid and return a list of SettingsError and SettingsWarning to report any invalid settings. Default implementation checks that all stepper files are set to valid file paths.

Return type: list[TaskError or TaskWarning]

reduceFunction(inputs)¶

The main computation for this step. This function should take in a iterable of inputs and return an iterable of outputs.

Example:

def reduceFunction(self, words):
    # Find all unique words
    seen_words = set()
    for word in words:
        if word not in seen_words:
            seen_words.add(word)
            yield word

class schrodinger.application.steps.scorers.LigandMLScorer(*args, **kwargs)¶

Bases: schrodinger.application.steps.dataclasses.ScorerMixin, schrodinger.application.steps.basesteps.MolReduceStep

Yield scored molecules where the score is the value predicted by the model.

The only setting is the required ml_file: the path to the ML qzip file.

class Settings(*args, _param_type=<object object>, **kwargs)¶

Bases: schrodinger.models.parameters.CompoundParam

ml_file: schrodinger.stepper.stepper.StepperFile¶

Base class for all Param classes. A Param is a descriptor for storing data, which means that a single Param instance will manage the data values for multiple instances of the class that owns it. Example:

class Coord(CompoundParam):
    x: int
    y: int

An instance of the Coord class can be created normally, and Params can be accessed as normal attributes:

coord = Coord()
coord.x = 4

When a Param value is set, the valueChanged signal is emitted. Params can be serialized and deserialized to and from JSON. Params can also be nested:

class Atom(CompoundParam):
    coord: Coord
    element: str

validate_model: bool¶

Base class for all Param classes. A Param is a descriptor for storing data, which means that a single Param instance will manage the data values for multiple instances of the class that owns it. Example:

class Coord(CompoundParam):
    x: int
    y: int

An instance of the Coord class can be created normally, and Params can be accessed as normal attributes:

coord = Coord()
coord.x = 4

When a Param value is set, the valueChanged signal is emitted. Params can be serialized and deserialized to and from JSON. Params can also be nested:

class Atom(CompoundParam):
    coord: Coord
    element: str

ml_fileChanged¶

pyqtSignal(*types, name: str = …, revision: int = …, arguments: Sequence = …) -> PYQT_SIGNAL

types is normally a sequence of individual types. Each type is either a type object or a string that is the name of a C++ type. Alternatively each type could itself be a sequence of types each describing a different overloaded signal. name is the optional C++ name of the signal. If it is not specified then the name of the class attribute that is bound to the signal is used. revision is the optional revision of the signal that is exported to QML. If it is not specified then 0 is used. arguments is the optional sequence of the names of the signal’s arguments.

ml_fileReplaced¶

pyqtSignal(*types, name: str = …, revision: int = …, arguments: Sequence = …) -> PYQT_SIGNAL

types is normally a sequence of individual types. Each type is either a type object or a string that is the name of a C++ type. Alternatively each type could itself be a sequence of types each describing a different overloaded signal. name is the optional C++ name of the signal. If it is not specified then the name of the class attribute that is bound to the signal is used. revision is the optional revision of the signal that is exported to QML. If it is not specified then 0 is used. arguments is the optional sequence of the names of the signal’s arguments.

validate_modelChanged¶

pyqtSignal(*types, name: str = …, revision: int = …, arguments: Sequence = …) -> PYQT_SIGNAL

types is normally a sequence of individual types. Each type is either a type object or a string that is the name of a C++ type. Alternatively each type could itself be a sequence of types each describing a different overloaded signal. name is the optional C++ name of the signal. If it is not specified then the name of the class attribute that is bound to the signal is used. revision is the optional revision of the signal that is exported to QML. If it is not specified then 0 is used. arguments is the optional sequence of the names of the signal’s arguments.

validate_modelReplaced¶

pyqtSignal(*types, name: str = …, revision: int = …, arguments: Sequence = …) -> PYQT_SIGNAL

types is normally a sequence of individual types. Each type is either a type object or a string that is the name of a C++ type. Alternatively each type could itself be a sequence of types each describing a different overloaded signal. name is the optional C++ name of the signal. If it is not specified then the name of the class attribute that is bound to the signal is used. revision is the optional revision of the signal that is exported to QML. If it is not specified then 0 is used. arguments is the optional sequence of the names of the signal’s arguments.

validateSettings(what='ml_file')¶

Check whether the step settings are valid and return a list of SettingsError and SettingsWarning to report any invalid settings. Default implementation checks that all stepper files are set to valid file paths.

Return type: list[TaskError or TaskWarning]

reduceFunction(inputs)¶

The main computation for this step. This function should take in a iterable of inputs and return an iterable of outputs.

Example:

def reduceFunction(self, words):
    # Find all unique words
    seen_words = set()
    for word in words:
        if word not in seen_words:
            seen_words.add(word)
            yield word