FloatAggregator#
- class tpcp.validate.FloatAggregator(func: Callable[[Sequence[float]], float | dict[str, float]], *, return_raw_scores: bool = True)[source]#
Methods
__call__
(value)Set the value of the aggregator.
aggregate
(values, datapoints)Aggregate a sequence of floats by taking the mean.
clone
()Create a new instance of the class with all parameters copied over.
get_params
([deep])Get parameters for this algorithm.
Return the value wrapped by aggregator.
set_params
(**params)Set the parameters of this Algorithm.
- __init__(func: Callable[[Sequence[float]], float | dict[str, float]], *, return_raw_scores: bool = True) None [source]#
- _assert_is_all_valid(values: Sequence[Any], _key_name: str)[source]#
Check if all scoring values are consistently of the same type.
This methods is called on the first aggregator instance acountered of a scoring value.
It’s role is to check, if all other values are of the same type (aka the same class and same config) as the first one.
- _get_emtpy_instance() Self [source]#
Return an empty instance of the aggregator with the same config, but no value.
- aggregate(values: Sequence[float], datapoints: Sequence[Dataset]) float | dict[str, float] [source]#
Aggregate a sequence of floats by taking the mean.
- clone() Self [source]#
Create a new instance of the class with all parameters copied over.
This will create a new instance of the class itself and all nested objects
- get_params(deep: bool = True) dict[str, Any] [source]#
Get parameters for this algorithm.
- Parameters:
- deep
Only relevant if object contains nested algorithm objects. If this is the case and deep is True, the params of these nested objects are included in the output using a prefix like
nested_object_name__
(Note the two “_” at the end)
- Returns:
- params
Parameter names mapped to their values.