flow360.PressureCorrectionSolver#
- pydantic model PressureCorrectionSolver[source]#
PressureCorrectionSolver
class- Parameters:
linear_solver (LinearSolver = LinearSolver(max_iterations=50, absolute_tolerance=1e-08, relative_tolerance=None, _type='LinearSolver')) –
- Fields:
linear_solver (flow360.component.flow360_params.solvers.LinearSolver)
- field linear_solver = LinearSolver(max_iterations=50, absolute_tolerance=1e-08, relative_tolerance=None, _type='LinearSolver') (alias 'linearSolver')#
- Constraints:
title = LinearSolver
description =
LinearSolver
class for setting up linear solver for heat equation Parameters ———- max_iterations : Optional[PositiveInt] = 50 absolute_tolerance : Optional[PositiveFloat] = None relative_tolerance : Optional[PositiveFloat] = None Parameters ———- max_iterations : PositiveInt, optional Maximum number of linear solver iterations, by default 50 absolute_tolerance : PositiveFloat, optional The linear solver converges when the final residual of the pseudo steps below this value. Either absolute tolerance or relative tolerance can be used to determine convergence, by default 1e-10 relative_tolerance : The linear solver converges when the ratio of the final residual and the initial residual of the pseudo step is below this value. Returns ——-LinearSolver
An instance of the component class LinearSolver. Example ——- >>> ls = LinearSolver( max_iterations=50, absoluteTolerance=1e-10 )type = object
properties = {‘maxIterations’: {‘title’: ‘Maxiterations’, ‘default’: 50, ‘exclusiveMinimum’: 0, ‘type’: ‘integer’}, ‘absoluteTolerance’: {‘title’: ‘Absolutetolerance’, ‘exclusiveMinimum’: 0, ‘type’: ‘number’}, ‘relativeTolerance’: {‘title’: ‘Relativetolerance’, ‘exclusiveMinimum’: 0, ‘type’: ‘number’}, ‘_type’: {‘title’: ‘ Type’, ‘default’: ‘LinearSolver’, ‘enum’: [‘LinearSolver’], ‘type’: ‘string’}}
additionalProperties = False
- 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:
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:
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)#