colour.models.logarithmic_function_camera#

colour.models.logarithmic_function_camera(x: ArrayLike, style: Literal['cameraLinToLog', 'cameraLogToLin'] | str = 'cameraLinToLog', base: int = 2, log_side_slope: float = 1, lin_side_slope: float = 1, log_side_offset: float = 0, lin_side_offset: float = 0, lin_side_break: float = 0.005, linear_slope: float | None = None) → NDArrayFloat[source]#

Apply a camera logarithmic function to the specified array.

Apply a piece-wise function with logarithmic and linear segments for encoding or decoding camera data.

Parameters:

  • x (ArrayLike) – Logarithmically encoded data \(x\).

  • style (Literal['cameraLinToLog', 'cameraLogToLin'] | str) –

    Specifies the behaviour for the logarithmic function to operate:

    • cameraLinToLog: Applies a piece-wise function with logarithmic and linear segments on linear values, converting them to non-linear values.

    • cameraLogToLin: Applies a piece-wise function with logarithmic and linear segments on non-linear values, converting them to linear values.

  • base (int) – Logarithmic base used for the conversion.

  • log_side_slope (float) – Slope (or gain) applied to the log side of the logarithmic function. The default value is 1.

  • lin_side_slope (float) – Slope of the linear side of the logarithmic function. The default value is 1.

  • log_side_offset (float) – Offset applied to the log side of the logarithmic function. The default value is 0.

  • lin_side_offset (float) – Offset applied to the linear side of the logarithmic function. The default value is 0.

  • lin_side_break (float) – Break-point, defined in linear space, at which the piece-wise function transitions between the logarithmic and linear segments.

  • linear_slope (float | None) – Slope of the linear portion of the curve. The default value is None.

Returns:

Encoded/Decoded data.

Return type:

numpy.ndarray

Examples

>>> logarithmic_function_camera(
...     0.18, "cameraLinToLog"
... )
np.float64(-2.4739311...)
>>> logarithmic_function_camera(
...     -2.4739311883324122, "cameraLogToLin"
... )
np.float64(0.1800000...)