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