colour.models.log_decoding_PivotedLog#

Apply the Josh Pines style Pivoted Log 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]) – Logarithmically encoded data \(y\).
log_reference (float) – Log reference that defines the pivot point in code values where the logarithmic encoding is centred. Typical value is 445.
linear_reference (float) – Linear reference that establishes the relationship between linear scene-referred values and the logarithmic code values. Typical value is 0.18, representing 18% grey.
negative_gamma (float) – Negative gamma that controls the slope and curvature of the logarithmic portion of the encoding curve. Lower values produce steeper curves with more contrast in the shadows.
density_per_code_value (float) – Density per code value that determines the logarithmic step size and affects the overall contrast and dynamic range of the encoded values.

Returns:

Linear data \(x\).

Return type:

numpy.ndarray

Notes

Domain	Scale - Reference	Scale - 1
`y`	1	1

Range	Scale - Reference	Scale - 1
`x`	1	1

References

Examples

>>> log_decoding_PivotedLog(0.434995112414467)
0.1...