flow360.Slice

pydantic model Slice

NamedSlice class

Parameters:

slice_normal (Vector) – slice_origin : _VectorType output_fields : Optional[List[Literal[‘Cp’, ‘gradW’, ‘kOmega’, ‘Mach’, ‘mut’, ‘mutRatio’, ‘nuHat’, ‘primitiveVars’, ‘qcriterion’, ‘residualNavierStokes’, ‘residualTransition’, ‘residualTurbulence’, ‘s’, ‘solutionNavierStokes’, ‘solutionTransition’, ‘solutionTurbulence’, ‘T’, ‘vorticity’, ‘wallDistance’, ‘numericalDissipationFactor’, ‘residualHeatSolver’, ‘VelocityRelative’, ‘lowMachPreconditionerSensor’, ‘betMetrics’, ‘betMetricsPerDisk’, ‘Coefficient of pressure’, ‘Gradient of primitive solution’, ‘k and omega’, ‘Mach number’, ‘Turbulent viscosity’, ‘Turbulent viscosity and freestream dynamic viscosity ratio’, ‘Spalart-Almaras variable’, ‘rho, u, v, w, p (density, 3 velocities and pressure)’, ‘Q criterion’, ‘N-S residual’, ‘Transition residual’, ‘Turbulence residual’, ‘Entropy’, ‘N-S solution’, ‘Transition solution’, ‘Turbulence solution’, ‘Temperature’, ‘Vorticity’, ‘Wall distance’, ‘NumericalDissipationFactor sensor’, ‘Heat equation residual’, ‘Velocity with respect to non-inertial frame’, ‘Low-Mach preconditioner factor’, ‘BET Metrics’, ‘BET Metrics per Disk’]]] = []

Fields:

• output_fields (types.ConstrainedListValue[Literal['Cp', 'gradW', 'kOmega', 'Mach', 'mut', 'mutRatio', 'nuHat', 'primitiveVars', 'qcriterion', 'residualNavierStokes', 'residualTransition', 'residualTurbulence', 's', 'solutionNavierStokes', 'solutionTransition', 'solutionTurbulence', 'T', 'vorticity', 'wallDistance', 'numericalDissipationFactor', 'residualHeatSolver', 'VelocityRelative', 'lowMachPreconditionerSensor', 'betMetrics', 'betMetricsPerDisk', 'Coefficient of pressure', 'Gradient of primitive solution', 'k and omega', 'Mach number', 'Turbulent viscosity', 'Turbulent viscosity and freestream dynamic viscosity ratio', 'Spalart-Almaras variable', 'rho, u, v, w, p (density, 3 velocities and pressure)', 'Q criterion', 'N-S residual', 'Transition residual', 'Turbulence residual', 'Entropy', 'N-S solution', 'Transition solution', 'Turbulence solution', 'Temperature', 'Vorticity', 'Wall distance', 'NumericalDissipationFactor sensor', 'Heat equation residual', 'Velocity with respect to non-inertial frame', 'Low-Mach preconditioner factor', 'BET Metrics', 'BET Metrics per Disk']] | None)

• slice_normal (flow360.component.types.Vector)

• slice_origin (flow360.component.flow360_params.unit_system._VectorType)

field slice_normal [Required] (alias 'sliceNormal')

Constraints:

• type = array

• minItems = 3

• maxItems = 3

• items = [{‘type’: ‘number’}, {‘type’: ‘number’}, {‘type’: ‘number’}]

field slice_origin [Required] (alias 'sliceOrigin')

Constraints:

• properties = {‘value’: {‘type’: ‘array’, ‘items’: {‘type’: ‘number’}, ‘minItems’: 3, ‘maxItems’: 3, ‘strictType’: {‘type’: ‘vector3’}}, ‘units’: {‘type’: ‘string’, ‘dimension’: ‘length’, ‘enum’: [‘m’, ‘cm’, ‘ft’, ‘flow360_length_unit’, ‘mm’, ‘inch’]}}

field output_fields = [] (alias 'outputFields')

Constraints:

• uniqueItems = True

to_solver(params, **kwargs)

Loops through all fields, for Flow360BaseModel runs .to_solver() recusrively. For dimensioned value performs

unit conversion to flow360_base system.

Parameters:

• params (Flow360Params) – Full config definition as Flow360Params.

• exclude (List[str] (optional)) – List of fields to ignore on returned model.

• required_by (List[str] (optional)) – Path to property which requires conversion.

Returns:

returns caller class with units all in flow360 base unit system

Return type:

caller class

classmethod add_type_field()

Automatically place “type” field with model name in the model field dictionary.

append(params, overwrite=False)

append parametrs to the model

Parameters:

• params (Flow360BaseModel) – Flow360BaseModel parameters to be appended

• overwrite (bool, optional) – Whether to overwrite if key exists, by default False

classmethod construct(_fields_set=None, **values)

Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values

copy(update=None, **kwargs)

Copy a Flow360BaseModel. With deep=True as default.

dict(*args, exclude=None, **kwargs)

Returns dict representation of the model.

Parameters:

• *args – Arguments passed to pydantic’s dict method.

• **kwargs – Keyword arguments passed to pydantic’s dict method.

Returns:

A formatted dict.

Return type:

dict

Example

>>> params.dict() 

classmethod dict_from_file(filename)

Loads a dictionary containing the model from a .json or .yaml file.

Parameters:

filename (str) – Full path to the .yaml or .json file to load the Flow360BaseModel from.

Returns:

A dictionary containing the model.

Return type:

dict

Example

>>> params = Flow360Params.from_file(filename='folder/flow360.json') 

classmethod flow360_schema()

Generate a schema json string for the flow360 model

classmethod flow360_ui_schema()

Generate a UI schema json string for the flow360 model

classmethod from_file(filename)

Loads a Flow360BaseModel from .json, or .yaml file.

Parameters:

filename (str) – Full path to the .yaml or .json file to load the Flow360BaseModel from.

Returns:

An instance of the component class calling load.

Return type:

Flow360BaseModel

Example

>>> simulation = Simulation.from_file(filename='folder/sim.json') 

classmethod from_json(filename, **parse_obj_kwargs)

Load a Flow360BaseModel from .json file.

Parameters:

filename (str) – Full path to the .json file to load the Flow360BaseModel from.

Returns:

• Flow360BaseModel – An instance of the component class calling load.

• **parse_obj_kwargs – Keyword arguments passed to pydantic’s parse_obj method.

Example

>>> params = Flow360Params.from_json(filename='folder/flow360.json') 

classmethod from_orm(obj)

classmethod from_yaml(filename, **parse_obj_kwargs)

Loads Flow360BaseModel from .yaml file.

Parameters:

• filename (str) – Full path to the .yaml file to load the Flow360BaseModel from.

• **parse_obj_kwargs – Keyword arguments passed to pydantic’s parse_obj method.

Returns:

An instance of the component class calling from_yaml.

Return type:

Flow360BaseModel

Example

>>> params = Flow360Params.from_yaml(filename='folder/flow360.yaml') 

classmethod generate_docstring()

Generates a docstring for a Flow360 model and saves it to the __doc__ of the class.

help(methods=False)

Prints message describing the fields and methods of a Flow360BaseModel.

Parameters:

methods (bool = False) – Whether to also print out information about object’s methods.

Example

>>> solver_params.help(methods=True) 

json(*args, exclude=None, **kwargs)

Returns json representation of the model.

Parameters:

• *args – Arguments passed to pydantic’s json method.

• **kwargs – Keyword arguments passed to pydantic’s json method.

Returns:

A formatted json. Sets default vaules by_alias=True, exclude_none=True

Return type:

json

Example

>>> params.json() 

classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

classmethod parse_obj(obj)

classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)

classmethod schema(by_alias=True, ref_template='#/definitions/{model}')

classmethod schema_json(*, by_alias=True, ref_template='#/definitions/{model}', **dumps_kwargs)

set_will_export_to_flow360(flag)

Recursivly sets flag will_export_to_flow360

Parameters:

flag (bool) – set to true before exporting to flow360 json

to_file(filename)

Exports Flow360BaseModel instance to .json or .yaml file

Parameters:

filename (str) – Full path to the .json or .yaml or file to save the Flow360BaseModel to.

Example

>>> params.to_file(filename='folder/flow360.json') 

to_json(filename)

Exports Flow360BaseModel instance to .json file

Parameters:

filename (str) – Full path to the .json file to save the Flow360BaseModel to.

Example

>>> params.to_json(filename='folder/flow360.json') 

to_yaml(filename)

Exports Flow360BaseModel instance to .yaml file.

Parameters:

filename (str) – Full path to the .yaml file to save the Flow360BaseModel to.

Example

>>> params.to_yaml(filename='folder/flow360.yaml') 

classmethod update_forward_refs(**localns)

Try to update ForwardRefs on fields based on this Model, globalns and localns.

classmethod validate(value)