EnumerateStereoisomers

class openff.qcsubmit.workflow_components.EnumerateStereoisomers(*, type='EnumerateStereoisomers', undefined_only=False, max_isomers=20, rationalise=True)[source]

Enumerate the stereo centers and bonds of a molecule using the backend toolkits through the OFFTK, only well defined molecules are returned by this component, this is check via a OFFTK round trip.

Parameters
  • type (Literal['EnumerateStereoisomers']) –

  • undefined_only (bool) –

  • max_isomers (int) –

  • rationalise (bool) –

Return type

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

undefined_only

max_isomers

rationalise

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

openff.qcsubmit.common_structures.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
Returns

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

Return type

openff.qcsubmit.workflow_components.utils.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 (openff.toolkit.utils.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