ConstantValueDetector

ConstantValueDetector(window_size=3, threshold=1e-07)

Detect contiguous periods of constant values within a configurable time window.

Commonly caused by sensor failures, which get stuck at a constant level.

Parameters

Name	Type	Description	Default
window_size	int	Number of consecutive points to evaluate.	3
threshold	float	Maximum variation (max - min) within window to consider constant.	1e-7

Methods

Name	Description
detect	Detect anomalies
fit	Set detector parameters based on data.
save	Save a detector for later use.
validate	Check that input data is in correct format and possibly adjust.

detect

ConstantValueDetector.detect(data)

Detect anomalies

Parameters

Name	Type	Description	Default
data	Union[pd.Series, pd.DataFrame]	Time series data with possible anomalies	required

Returns

Name	Type	Description
	pd.Series or pd.DataFrame	Time series with bools, True == anomaly.

fit

ConstantValueDetector.fit(data)

Set detector parameters based on data.

Parameters

Name	Type	Description	Default
data	Union[pd.Series, pd.DataFrame]	Normal (non-anomalous) time series data for training. If DataFrame, must contain exactly one column	required

Returns

Name	Type	Description
	Self

save

ConstantValueDetector.save(path)

Save a detector for later use.

Parameters

Name	Type	Description	Default
path	str or Path	File path to save the detector to.	required

validate

ConstantValueDetector.validate(data)

Check that input data is in correct format and possibly adjust.

Parameters

Name	Type	Description	Default
data	pd.Series or pd.DataFrame	Input data to validate.	required

Returns

Name	Type	Description
	pd.DataFrame	Validated data.

Raises

Name	Type	Description
	WrongInputDataTypeError	If data is not a pd.Series or pd.DataFrame.