KuiperTest

class frouros.detectors.data_drift.batch.statistical_test.KuiperTest(callbacks: BaseCallbackBatch | list[BaseCallbackBatch] | None = None)

Kuiper’s test [kuiper1960tests] detector.

Parameters:

callbacks (Optional[Union[BaseCallbackBatch, list[BaseCallbackBatch]]]) – callbacks, defaults to None

References:

[kuiper1960tests]

Kuiper, Nicolaas H. “Tests concerning random points on a circle.” Nederl. Akad. Wetensch. Proc. Ser. A. Vol. 63. No. 1. 1960.

Example:

>>> from frouros.detectors.data_drift import KuiperTest
>>> import numpy as np
>>> np.random.seed(seed=31)
>>> X = np.random.normal(loc=0, scale=1, size=100)
>>> Y = np.random.normal(loc=1, scale=1, size=100)
>>> detector = KuiperTest()
>>> _ = detector.fit(X=X)
>>> detector.compare(X=Y)[0]
StatisticalResult(statistic=0.55, p_value=5.065664859580971e-13)

property X_ref: ndarray | None

Reference data property.

Returns:

reference data

Return type:

Optional[numpy.ndarray]

property callbacks: list[BaseCallback] | None

Callbacks property.

Returns:

callbacks

Return type:

Optional[list[BaseCallback]]

compare(X: ndarray, **kwargs: Any) → Tuple[ndarray, dict[str, Any]]

Compare values.

Parameters:

X (numpy.ndarray) – test data

Returns:

compare result and callbacks logs

Return type:

Tuple[numpy.ndarray, dict[str, Any]]

property data_type: BaseDataType

Data type property.

Returns:

data type

Return type:

BaseDataType

fit(X: ndarray, **kwargs: Any) → dict[str, Any]

Fit detector.

Parameters:

• X (numpy.ndarray) – feature data

• kwargs (Any) – additional fit parameters

Returns:

callbacks logs

Return type:

dict[str, Any]

reset() → None

Reset method.

property statistical_type: BaseStatisticalType

Statistical type property.

Returns:

statistical type

Return type:

BaseStatisticalType