utils.validation.check_interval

utils.validation.check_interval(
    interval=None,
    ensure_symmetric_intervals=False,
    quantiles=None,
    alpha=None,
    alpha_literal='alpha',
)

Validate that a confidence interval specification is valid.

This function checks that interval values are properly formatted and within valid ranges for confidence interval prediction.

Parameters

Name	Type	Description	Default
interval	Union[List[float], Tuple[float], None]	Confidence interval percentiles (0-100 inclusive). Should be [lower_bound, upper_bound]. Example: [2.5, 97.5] for 95% interval.	None
ensure_symmetric_intervals	bool	If True, ensure intervals are symmetric (lower + upper = 100).	False
quantiles	Union[List[float], Tuple[float], None]	Sequence of quantiles (0-1 inclusive). Currently not validated, reserved for future use.	None
alpha	Optional[float]	Confidence level (1-alpha). Currently not validated, reserved for future use.	None
alpha_literal	Optional[str]	Name used in error messages for alpha parameter.	'alpha'

Raises

Name	Type	Description
	TypeError	If interval is not a list or tuple.
	ValueError	If interval doesn’t have exactly 2 values, values out of range (0-100), lower >= upper, or intervals not symmetric when required.

Examples

>>> from spotforecast2_safe.utils.validation import check_interval
>>>
>>> # Valid 95% confidence interval
>>> check_interval(interval=[2.5, 97.5])  # No error
>>>
>>> # Valid symmetric interval
>>> check_interval(interval=[2.5, 97.5], ensure_symmetric_intervals=True)  # No error
>>>
>>> # Invalid: not symmetric
>>> try:
...     check_interval(interval=[5, 90], ensure_symmetric_intervals=True)
... except ValueError as e:
...     print("Error: Interval not symmetric")
Error: Interval not symmetric
>>>
>>> # Invalid: wrong number of values
>>> try:
...     check_interval(interval=[2.5, 50, 97.5])
... except ValueError as e:
...     print("Error: Must have exactly 2 values")
Error: Must have exactly 2 values
>>>
>>> # Invalid: out of range
>>> try:
...     check_interval(interval=[-5, 105])
... except ValueError as e:
...     print("Error: Values out of range")
Error: Values out of range