ScanFilter

class openff.qcsubmit.workflow_components.ScanFilter(*, type='ScanFilter', scans_to_include=None, scans_to_exclude=None)[source]

A filter to remove/include molecules from the workflow who have scans targeting the specified SMARTS.

Important

Currently only checks against 1D scans.

Parameters:

type (Literal['ScanFilter']) –
scans_to_include (List[str] | None) –
scans_to_exclude (List[str] | None) –

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises ValidationError if the input data cannot be parsed to form a valid model.

Parameters:: data (Any) –
Return type:: None

Methods

`__init__`(**data)	Create a new model by parsing and validating input data from keyword arguments.
`apply`(molecules, toolkit_registry[, ...])	This is the main feature of the workflow component which should accept a molecule, perform the component action and then return any resulting molecules.
`construct`([_fields_set])	Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
`copy`(*[, include, exclude, update, deep])	Duplicate a model, optionally choose which fields to include, exclude and change.
`description`()	Returns a friendly description of the workflow component.
`dict`(*[, include, exclude, by_alias, ...])	Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
`fail_reason`()	Returns a friendly description of why a molecule would fail to pass the component.
`from_orm`(obj)
`info`()	Returns a dictionary of the friendly descriptions of the class.
`is_available`()	Check if any of the requested backend toolkits can be used.
`json`(*[, include, exclude, by_alias, ...])	Generate a JSON representation of the model, include and exclude arguments as per dict().
`parse_file`(path, *[, content_type, ...])
`parse_obj`(obj)
`parse_raw`(b, *[, content_type, encoding, ...])
`properties`()	Returns the runtime properties of the component such as parallel safe.
`provenance`(toolkit_registry)	This component calls the OFFTK to perform the task and logs information on the backend toolkit used.
`schema`([by_alias, ref_template])
`schema_json`(*[, by_alias, ref_template])
`update_forward_refs`(**localns)	Try to update ForwardRefs on fields based on this Model, globalns and localns.
`validate`(value)

Attributes

`type`
`scans_to_include`
`scans_to_exclude`

classmethod description()[source]

Returns a friendly description of the workflow component.

Return type:: str

classmethod fail_reason()[source]

Returns a friendly description of why a molecule would fail to pass the component.

Return type:: str

classmethod properties()[source]

Returns the runtime properties of the component such as parallel safe.

Return type:: ComponentProperties

apply(molecules, toolkit_registry, processors=None, verbose=True)

This is the main feature of the workflow component which should accept a molecule, perform the component action and then return any resulting molecules.

Parameters:

molecules (List[Molecule]) – The list of molecules to be processed by this component.
toolkit_registry (ToolkitRegistry) – The openff.toolkit.utils.ToolkitRegistry which declares the available backend toolkits to be used.
processors (int | None) – The number of processor the component can use to run the job in parallel across molecules, None will default to all cores.
verbose (bool) – If true a progress bar should be shown on screen.

Returns:

A component result class which handles collecting together molecules that pass and fail the component

Return type:

ComponentResult

classmethod info()

Returns a dictionary of the friendly descriptions of the class.

Return type:: Dict[str, str]

classmethod is_available()

Check if any of the requested backend toolkits can be used.

Return type:: bool

provenance(toolkit_registry)

This component calls the OFFTK to perform the task and logs information on the backend toolkit used.

Parameters:: toolkit_registry (ToolkitRegistry) – The openff.toolkit.utils.ToolkitRegistry which declares the available toolkits for the component.
Returns:: A dictionary containing the version information about the backend toolkit called to perform the task.
Return type:: Dict