Ctrl+K

flow360.AirPressureTemperature

flow360.AirPressureTemperature#

pydantic model AirPressureTemperature[source]#

Model representing air properties based on pressure and temperature.

Parameters:

  • model_type (Literal['AirPressure'] = AirPressure) – pressure : _Constrained temperature : TemperatureType

  • pressure (PressureType) – Pressure of the air.

  • temperature (TemperatureType) – Temperature of the air.

Fields:

  • model_type (Literal['AirPressure'])

  • pressure (flow360.component.flow360_params.unit_system._Constrained)

  • temperature (flow360.component.flow360_params.unit_system.TemperatureType)

field model_type = 'AirPressure' (alias 'modelType')#
Constraints:

  • const = AirPressure

field pressure [Required]#
Constraints:

  • properties = {‘value’: {‘type’: ‘number’, ‘exclusiveMinimum’: 0}, ‘units’: {‘type’: ‘string’, ‘dimension’: ‘pressure’, ‘enum’: [‘Pa’, ‘dyn/cm**2’, ‘lbf/ft**2’, ‘flow360_pressure_unit’]}}

field temperature [Required]#
Constraints:

  • properties = {‘value’: {‘type’: ‘number’}, ‘units’: {‘type’: ‘string’, ‘dimension’: ‘temperature’, ‘enum’: [‘K’, ‘R’, ‘flow360_temperature_unit’]}}

to_fluid_properties()[source]#

Converts the instance to _FluidProperties, incorporating temperature, pressure, density, and viscosity.

speed_of_sound()[source]#

Calculates the speed of sound in the air based on the temperature.

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)#
Contents