Bases: BaseModel
Input/output utilities for the models with support for the following features:
- Hashing of the model
- Conversion to and from dictionaries, json, toml, and yaml files
- Compatibility with pydantic v1 and v2
property
Fields to exclude from the model, typically used to exclude arbitrary types when it is allowed in the pydantic model to avoid hashing issues.
__hash__() -> int
Return the hash of the model.
classmethod
Load the model from a binary string or file if a path is provided.
classmethod
Decrypt the model using the key.
classmethod
fromDict(*, data: dict, **kwargs) -> Self
Load the model from a dictionary.
classmethod
Load the model from a json string or file if a path is provided.
classmethod
Load the model from a toml string or file if a path is provided.
classmethod
Load the model from a yaml string or file if a path is provided.
Convert the model to a binary string or save it to a file if a path is provided.
Encrypt the model using the key.
toDict(**kwargs) -> dict
Convert the model to a dictionary.
Convert the model to a json string or save it to a file if a path is provided.
Convert the model to a toml string or save it to a file if a path is provided.
Convert the model to a yaml string or save it to a file if a path is provided.
update(data: dict = None, **kwargs) -> Self
Update the options of the optimizer
Bases: ScipyOptimizer
Bases: ScipyOptions
Bases: ScipyOptimizer
Bases: ScipyOptions
Base class for optimizers
__init__(objective_function: Callable, x0: ndarray, *, args: tuple = (), bounds: ndarray | None = None, callback: Callable[[Iterable], Any] | None = None, maxiter: int = 1000, maxfun: int = 10000, **options)
Initialize the optimizer
| PARAMETER | DESCRIPTION |
|---|---|
objective_function |
Objective function
TYPE:
|
x0 |
Initial parameters
TYPE:
|
args |
Additional arguments for the objective function
TYPE:
|
bounds |
Bounds of the parameter
TYPE:
|
maxiter |
Maximal number of iterations
TYPE:
|
maxfun |
Maximal number of function evaluations
TYPE:
|
callback |
Callback function that will be evaluated after each iteration
TYPE:
|
options |
Optimizer-specific options |
Callback function that will be evaluated after each iteration
classmethod
fmin(*args, **kwargs) -> OptimizerResult
Static method to do the optimization
| PARAMETER | DESCRIPTION |
|---|---|
args |
Positional and keyword arguments for the optimizer
DEFAULT:
|
kwargs |
Positional and keyword arguments for the optimizer
DEFAULT:
|
| RETURNS | DESCRIPTION |
|---|---|
res
|
Optimize result
TYPE:
|
optimize() -> OptimizerResult
Optimize the objective function
Bases: ScipyOptimizer
Bases: ScipyOptions
Bases: OptimizerBase, ABC
Bases: HashableBaseModelIO
Bases: OptimizerResult
Represents the optimization result for scipy optimize algorithms
Notes
OptimizeResult may have additional attributes not listed here depending
on the specific solver being used. Since this class is essentially a
subclass of dict with attribute accessors, one can see which
attributes are available using the OptimizeResult.keys method.
Bases: ScipyOptimizer
Bases: ScipyOptions
register(cls_or_name: Type[OptimizerBase] | str | None = None, name: str | None = None, *, jitclass: bool = False, spec: List[Tuple[str, type]] | Mapping[str, Type] | None = None, saveto: Registry | None = None, **methods) -> Type | Callable
Register a new model
Examples:
The following calls are equivalent:
1) cls_or_name = "Foo", name = None
@register("Foo") ... class Foo: ... ...
2) cls_or_name = None, name = "Foo"
@register(name="Foo") ... class Foo: ... ...
3) cls_or_name = Foo, name = "Foo"
class Foo: ... ... register(Foo, "Foo") # noqa
| PARAMETER | DESCRIPTION |
|---|---|
cls_or_name |
The class to register or the name of the class, by default None. |
name |
The name of the class, by default None
TYPE:
|
jitclass |
Whether to compile the class with numba jitclass, by default False
TYPE:
|
spec |
The numba jitclass spec, by default None
TYPE:
|
saveto |
The registry to save the class, by default None which will use the default registry
TYPE:
|
methods |
The additional methods to add to the class before the jitclass compilation, functions with the first argument
being the class instance
DEFAULT:
|
| RETURNS | DESCRIPTION |
|---|---|
Type | Callable
|
The class that was registered or a callable that registers the class |