Source code for colour.models.rgb.transfer_functions.pivoted_log

"""
Pivoted Log Encoding
====================

Define the *Pivoted Log* encoding:

-   :func:`colour.models.log_encoding_PivotedLog`
-   :func:`colour.models.log_decoding_PivotedLog`

References
----------
-   :cite:`SonyImageworks2012a` : Sony Imageworks. (2012). make.py. Retrieved
    November 27, 2014, from
    https://github.com/imageworks/OpenColorIO-Configs/blob/master/\
nuke-default/make.py
"""

from __future__ import annotations

import numpy as np

from colour.hints import ArrayLike, NDArrayFloat
from colour.utilities import as_float, from_range_1, to_domain_1

__author__ = "Colour Developers"
__copyright__ = "Copyright 2013 Colour Developers"
__license__ = "BSD-3-Clause - https://opensource.org/licenses/BSD-3-Clause"
__maintainer__ = "Colour Developers"
__email__ = "colour-developers@colour-science.org"
__status__ = "Production"

__all__ = [
    "log_encoding_PivotedLog",
    "log_decoding_PivotedLog",
]


[docs] def log_encoding_PivotedLog( x: ArrayLike, log_reference: float = 445, linear_reference: float = 0.18, negative_gamma: float = 0.6, density_per_code_value: float = 0.002, ) -> NDArrayFloat: """ Define the *Josh Pines* style *Pivoted Log* log encoding curve / opto-electronic transfer function. Parameters ---------- x Linear data :math:`x`. log_reference Log reference. linear_reference Linear reference. negative_gamma Negative gamma. density_per_code_value Density per code value. Returns ------- :class:`numpy.ndarray` Non-linear data :math:`y`. Notes ----- +------------+-----------------------+---------------+ | **Domain** | **Scale - Reference** | **Scale - 1** | +============+=======================+===============+ | ``x`` | [0, 1] | [0, 1] | +------------+-----------------------+---------------+ +------------+-----------------------+---------------+ | **Range** | **Scale - Reference** | **Scale - 1** | +============+=======================+===============+ | ``y`` | [0, 1] | [0, 1] | +------------+-----------------------+---------------+ References ---------- :cite:`SonyImageworks2012a` Examples -------- >>> log_encoding_PivotedLog(0.18) # doctest: +ELLIPSIS 0.4349951... """ x = to_domain_1(x) y = ( log_reference + np.log10(x / linear_reference) / (density_per_code_value / negative_gamma) ) / 1023 return as_float(from_range_1(y))
[docs] def log_decoding_PivotedLog( y: ArrayLike, log_reference: float = 445, linear_reference: float = 0.18, negative_gamma: float = 0.6, density_per_code_value: float = 0.002, ) -> NDArrayFloat: """ Define the *Josh Pines* style *Pivoted Log* log decoding curve / electro-optical transfer function. Parameters ---------- y Non-linear data :math:`y`. log_reference Log reference. linear_reference Linear reference. negative_gamma Negative gamma. density_per_code_value Density per code value. Returns ------- :class:`numpy.ndarray` Linear data :math:`x`. Notes ----- +------------+-----------------------+---------------+ | **Domain** | **Scale - Reference** | **Scale - 1** | +============+=======================+===============+ | ``y`` | [0, 1] | [0, 1] | +------------+-----------------------+---------------+ +------------+-----------------------+---------------+ | **Range** | **Scale - Reference** | **Scale - 1** | +============+=======================+===============+ | ``x`` | [0, 1] | [0, 1] | +------------+-----------------------+---------------+ References ---------- :cite:`SonyImageworks2012a` Examples -------- >>> log_decoding_PivotedLog(0.434995112414467) # doctest: +ELLIPSIS 0.1... """ y = to_domain_1(y) x = ( 10 ** ((y * 1023 - log_reference) * (density_per_code_value / negative_gamma)) * linear_reference ) return as_float(from_range_1(x))