LambdaFun

class negmas.preferences.LambdaFun(f, bias=0, min_value=None, max_value=None)[source]

Bases: BaseFun

Attributes Summary

`bias`
`dim`
`f`
`max_value`
`min_value`

Methods Summary

`__call__`(x)	Call self as a function.
`from_dict`(d)
`max`(input)	rtype: `float`
`min`(input)	rtype: `float`
`minmax`(input)	rtype: `tuple`[`float`, `float`]
`scale_by`(scale)	rtype: `LambdaFun`
`shift_by`(offset[, change_bias])	rtype: `LambdaFun`
`to_dict`()	rtype: `dict`[`str`, `Any`]
`xml`(indx, issue[, bias])	rtype: `str`

Attributes Documentation

bias: float

dim

f: Callable[[Any], float]

max_value: float | None

min_value: float | None

Methods Documentation

__call__(x)[source]

Call self as a function.

Return type:: float

classmethod from_dict(d)

max(input)

Return type:: float

min(input)

Return type:: float

minmax(input)[source]

Return type:: tuple[float, float]

scale_by(scale)[source]

Return type:: LambdaFun

shift_by(offset, change_bias=False)[source]

Return type:: LambdaFun

to_dict()

Return type:: dict[str, Any]

xml(indx, issue, bias=0.0)[source]

Return type:: str