import numpy as np
from dascore.utils.intervals import normalize_value
normalize_value(np.bool_(True)) is TrueTruenormalize_value
normalize_value(
value ,
error: type[<class ’Exception] = <class ‘dascore.exceptions.ParameterError’>,
)
Normalize an interval’s value so its Python type survives validation.
Numpy scalars are unwrapped: pydantic’s smart union resolves every numpy scalar to float, which would turn a mask element into a numeric group.
Parameters
| Parameter | Description |
|---|---|
| value | The value to normalize. |
| error | The exception raised when the value is a non-finite number. |