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

"""
Panalog Encoding
================

Define the *Panalog* encoding:

-   :func:`colour.models.log_encoding_Panalog`
-   :func:`colour.models.log_decoding_Panalog`

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,
    as_float_array,
    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_Panalog",
    "log_decoding_Panalog",
]


[docs] def log_encoding_Panalog( x: ArrayLike, black_offset: ArrayLike = 10 ** ((64 - 681) / 444), ) -> NDArrayFloat: """ Define the *Panalog* log encoding curve / opto-electronic transfer function. Parameters ---------- x Linear data :math:`x`. black_offset Black offset. Returns ------- :class:`numpy.ndarray` Non-linear data :math:`y`. Warnings -------- These are estimations known to be close enough, the actual log encoding curves are not published. 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_Panalog(0.18) # doctest: +ELLIPSIS 0.3745767... """ x = to_domain_1(x) black_offset = as_float_array(black_offset) y = (681 + 444 * np.log10(x * (1 - black_offset) + black_offset)) / 1023 return as_float(from_range_1(y))
[docs] def log_decoding_Panalog( y: ArrayLike, black_offset: ArrayLike = 10 ** ((64 - 681) / 444), ) -> NDArrayFloat: """ Define the *Panalog* log decoding curve / electro-optical transfer function. Parameters ---------- y Non-linear data :math:`y`. black_offset Black offset. Returns ------- :class:`numpy.ndarray` Linear data :math:`x`. Warnings -------- These are estimations known to be close enough, the actual log encoding curves are not published. 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_Panalog(0.374576791382298) # doctest: +ELLIPSIS 0.1... """ y = to_domain_1(y) black_offset = as_float_array(black_offset) x = (10 ** ((1023 * y - 681) / 444) - black_offset) / (1 - black_offset) return as_float(from_range_1(x))