colour.models.log_decoding_Panalog

colour.models.log_decoding_Panalog(y: Annotated[_Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str], 1], black_offset: ArrayLike = 10**64 - 681 / 444) → Annotated[ndarray[tuple[Any, ...], dtype[float16 | float32 | float64]], 1]

Apply the Panalog log decoding inverse opto-electronic transfer function (OETF).

Parameters:

• y (Annotated[_Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str], 1]) – Panalog non-linear encoded data \(y\).

• black_offset (ArrayLike) – Black offset.

Returns:

Linear data \(x\).

Return type:

numpy.ndarray

Warning

These are estimations known to be close enough, the actual log encoding curves are not published.

Notes

Domain	Scale - Reference	Scale - 1
y	1	1

Range	Scale - Reference	Scale - 1
x	1	1

References

[SonyImageworks12]

Examples

>>> log_decoding_Panalog(0.374576791382298)
0.1...