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flow360.VolumeMeshingParams

flow360.VolumeMeshingParams#

pydantic model VolumeMeshingParams[source]#

Flow360 Volume Meshing parameters

Parameters:

volume (Volume) – refinement_factor : Optional[PositiveFloat] = None farfield : Optional[Farfield] = None refinement : Optional[List[Union[BoxRefinement, CylinderRefinement]]] = None rotor_disks : Optional[List[RotorDisk]] = None sliding_interfaces : Optional[List[SlidingInterface]] = None

Fields:

  • farfield (flow360.component.meshing.params.Farfield | None)

  • refinement (List[flow360.component.meshing.params.BoxRefinement | flow360.component.meshing.params.CylinderRefinement] | None)

  • refinement_factor (pydantic.types.PositiveFloat | None)

  • rotor_disks (List[flow360.component.meshing.params.RotorDisk] | None)

  • sliding_interfaces (List[flow360.component.meshing.params.SlidingInterface] | None)

  • volume (flow360.component.meshing.params.Volume)

field volume [Required]#
Constraints:

  • title = Volume

  • description = Core volume meshing parameters Parameters ———- first_layer_thickness : PositiveFloat growth_rate : Optional[PositiveFloat] = 1.2 gap_treatment_strength : Optional[ConstrainedFloatValue] = None

  • type = object

  • properties = {‘firstLayerThickness’: {‘title’: ‘Firstlayerthickness’, ‘exclusiveMinimum’: 0, ‘type’: ‘number’}, ‘growthRate’: {‘title’: ‘Growthrate’, ‘default’: 1.2, ‘exclusiveMinimum’: 0, ‘type’: ‘number’}, ‘gapTreatmentStrength’: {‘title’: ‘Gaptreatmentstrength’, ‘minimum’: 0, ‘maximum’: 1, ‘type’: ‘number’}, ‘_type’: {‘title’: ‘ Type’, ‘default’: ‘Volume’, ‘enum’: [‘Volume’], ‘type’: ‘string’}}

  • required = [‘firstLayerThickness’]

  • additionalProperties = False

field refinement_factor = None (alias 'refinementFactor')#
Constraints:

  • exclusiveMinimum = 0

field farfield = None#
Constraints:

  • title = Farfield

  • description = Farfield type for meshing Parameters ———- type : Literal[‘auto’, ‘quasi-3d’]

  • type = object

  • properties = {‘type’: {‘title’: ‘Type’, ‘enum’: [‘auto’, ‘quasi-3d’], ‘type’: ‘string’}, ‘_type’: {‘title’: ‘ Type’, ‘default’: ‘Farfield’, ‘enum’: [‘Farfield’], ‘type’: ‘string’}}

  • required = [‘type’]

  • additionalProperties = False

field refinement = None#
field rotor_disks = None (alias 'rotorDisks')#
field sliding_interfaces = None (alias 'slidingInterfaces')#
flow360_json()[source]#

Generate a JSON representation of the model, as required by Flow360

Returns:

Returns JSON representation of the model.

Return type:

json

Example

>>> params.flow360_json()
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_solver(params, exclude=None, required_by=None)#

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

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)#
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