RangeDetector

RangeDetector(min_value=-np.inf, max_value=np.inf, quantiles=None)

Detect values outside range.

Parameters

Name	Type	Description	Default
min_value	float	Minimum value threshold.	-np.inf
max_value	float	Maximum value threshold.	np.inf
quantiles	list of float	Quantiles to use for determining min and max during fit. Default is [0.0, 1.0], which corresponds to absolute min and max values. Use values like [0.001, 0.999] to exclude extreme outliers.	None

Examples

>>> normal_data = pd.Series(np.random.normal(size=100))
>>> abnormal_data = pd.Series(np.random.normal(size=100))
>>> abnormal_data[[2, 6, 15, 57, 60, 73]] = 5
>>> normal_data_with_some_outliers = pd.Series(np.random.normal(size=100))
>>> normal_data_with_some_outliers[[12, 13, 20, 90]] = 7

>>> detector = RangeDetector(min_value=0.0, max_value=2.0)
>>> anomalies = detector.detect(abnormal_data)

>>> detector = RangeDetector()
>>> detector.fit(normal_data) # min, max inferred from normal data
>>> anomalies = detector.detect(abnormal_data)

>>> detector = RangeDetector(quantiles=[0.001,0.999])
>>> detector.fit(normal_data_with_some_outliers)
>>> anomalies = detector.detect(abnormal_data)

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

RangeDetector.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

RangeDetector.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

RangeDetector.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

RangeDetector.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.