ScanEnumerator
- class openff.qcsubmit.workflow_components.ScanEnumerator(*, type='ScanEnumerator', torsion_scans=[], double_torsion_scans=[], improper_scans=[])[source]
This module will tag any matching substructures for scanning, useful for torsiondrive datasets.
- Parameters:
- __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.
add_double_torsion(smarts1, smarts2[, ...])Add a targeted 2D torsion scan to the scan enumerator.
add_improper_torsion(smarts, central_smarts)Add a targeted Improper torsion to the scan enumerator.
add_torsion_scan(smarts[, scan_rage, ...])Add a targeted 1D torsion scan to the scan enumerator.
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.
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.
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.
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, ...])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
typetorsion_scansdouble_torsion_scansimproper_scans- classmethod description()[source]
Returns a friendly description of the workflow component.
- Return type:
- classmethod fail_reason()[source]
Returns a friendly description of why a molecule would fail to pass the component.
- Return type:
- classmethod properties()[source]
Returns the runtime properties of the component such as parallel safe.
- Return type:
- add_torsion_scan(smarts, scan_rage=None, scan_increment=15)[source]
Add a targeted 1D torsion scan to the scan enumerator.
- Parameters:
- Return type:
None
- add_double_torsion(smarts1, smarts2, scan_range1=None, scan_range2=None, scan_increments=(15, 15))[source]
Add a targeted 2D torsion scan to the scan enumerator.
- Parameters:
smarts1 (str) – The numerically tagged SMARTs pattern that should be used to identify the first torsion atoms.
smarts2 (str) – The numerically tagged SMARTs pattern that should be used to identify the second torsion atoms.
scan_range1 (Tuple[int, int] | None) – The angle in degrees the first torsion should be scanned between, from low to high
scan_range2 (Tuple[int, int] | None) – The angle in degrees the second torsion should be scanned between, from low to high
scan_increments (List[int]) – A list of the values in degrees between each grid point in the scans.
- Return type:
None
- add_improper_torsion(smarts, central_smarts, scan_range=None, scan_increment=15)[source]
Add a targeted Improper torsion to the scan enumerator.
- Parameters:
smarts (str) – The numerically tagged SMARTs pattern which describes the entire improper.
central_smarts (str) – The numerically tagged SMARTs pattern which identifies the central atom in the improper.
scan_range (Tuple[int, int] | None) – The angles in degrees the improper should be scanned between, from low to high.
scan_increment (int) – The value in degrees between each grid point in the scan.
- Return type:
None
- 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:
- 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: