LambdaFun

class negmas.preferences.LambdaFun(f: Callable[[Any], float], bias: float = 0, min_value: float | None = None, max_value: float | None = None)

Bases: BaseFun

Attributes Summary

bias
dim
f
max_value
min_value

Methods Summary

__call__(x)	Call self as a function.
from_dict(d[, python_class_identifier])
max(input)
min(input)
minmax(input)
scale_by(scale)
shift_by(offset[, change_bias])
to_dict([python_class_identifier])
xml(indx, issue[, bias])

Attributes Documentation

bias: float

dim

f: Callable[[Any], float]

max_value: float | None

min_value: float | None

Methods Documentation

__call__(x: Any) → float

Call self as a function.

classmethod from_dict(d: dict, python_class_identifier='__python_class__')

max(input: Issue) → float

min(input: Issue) → float

minmax(input) → tuple[float, float]

scale_by(scale: float) → LambdaFun

shift_by(offset: float, change_bias: bool = False) → LambdaFun

to_dict(python_class_identifier='__python_class__') → dict[str, Any]

xml(indx: int, issue: Issue, bias=0.0) → str