ReweightingSchema

class openff.evaluator.layers.reweighting.ReweightingSchema[source]

A schema which encodes the options and the workflow schema that the SimulationLayer should use when estimating a given class of physical properties using the built-in workflow framework.

__init__()

Methods

`__init__`()
`from_json`(file_path)	Create this object from a JSON file.
`get_attributes`([attribute_type])	Returns all attributes of a specific attribute_type.
`json`([file_path, format])	Creates a JSON representation of this class.
`parse_json`(string_contents)
`validate`([attribute_type])	Validate the values of the attributes.

Attributes

`absolute_tolerance`	The absolute uncertainty that the property should be estimated to within.
`maximum_data_points`	The maximum number of data points to include as part of the multi-state reweighting calculations.
`relative_tolerance`	The relative uncertainty that the property should be estimated to within, i.e relative_tolerance * measured_property.uncertainty.
`storage_queries`	The queries to perform when retrieving data for each of the components in the system from the storage backend.
`temperature_cutoff`	The maximum difference between the target temperature and the temperature at which cached data was collected to.
`workflow_schema`	The workflow schema to use when estimating properties.

storage_queries

The queries to perform when retrieving data for each of the components in the system from the storage backend. The keys of this dictionary will correspond to the metadata keys made available to the workflow system.

Type: dict

maximum_data_points

The maximum number of data points to include as part of the multi-state reweighting calculations. If zero, no cap will be applied. The default value of this attribute is 4.

Type: int

temperature_cutoff

The maximum difference between the target temperature and the temperature at which cached data was collected to. Data collected for temperatures outside of this cutoff will be ignored. The default value of this attribute is 5.0 K.

Type: Quantity

validate(attribute_type=None)[source]

Validate the values of the attributes. If attribute_type is set, only attributes of that type will be validated.

Parameters: attribute_type (type of Attribute, optional) – The type of attribute to validate.
Raises: ValueError or AssertionError –

absolute_tolerance

The absolute uncertainty that the property should be estimated to within. This attribute is mutually exclusive with the relative_tolerance attribute. The default value of this attribute is not set. This attribute is optional.

Type: Quantity

classmethod from_json(file_path)

Create this object from a JSON file.

Parameters: file_path (str) – The path to load the JSON from.
Returns: The parsed class.
Return type: cls

classmethod get_attributes(attribute_type=None)

Returns all attributes of a specific attribute_type.

Parameters: attribute_type (type of Attribute, optional) – The type of attribute to search for.
Returns: The names of the attributes of the specified type.
Return type: list of str

json(file_path=None, format=False)

Creates a JSON representation of this class.

Parameters

file_path (str, optional) – The (optional) file path to save the JSON file to.
format (bool) – Whether to format the JSON or not.

Returns

The JSON representation of this class.

Return type

str

relative_tolerance

The relative uncertainty that the property should be estimated to within, i.e relative_tolerance * measured_property.uncertainty. This attribute is mutually exclusive with the absolute_tolerance attribute. The default value of this attribute is not set. This attribute is optional.

Type: float

workflow_schema

The workflow schema to use when estimating properties. The default value of this attribute is not set and must be set by the user..

Type: WorkflowSchema