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 ( # noqa: TC001
ArrayLike,
Domain1,
Range1,
)
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: Domain1,
black_offset: ArrayLike = 10 ** ((64 - 681) / 444),
) -> Range1:
"""
Apply the *Panalog* log encoding opto-electronic transfer function (OETF).
Parameters
----------
x
Linear data :math:`x`.
black_offset
Black offset.
Returns
-------
:class:`numpy.ndarray`
*Panalog* non-linear encoded 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`` | 1 | 1 |
+------------+-----------------------+---------------+
+------------+-----------------------+---------------+
| **Range** | **Scale - Reference** | **Scale - 1** |
+============+=======================+===============+
| ``y`` | 1 | 1 |
+------------+-----------------------+---------------+
References
----------
:cite:`SonyImageworks2012a`
Examples
--------
>>> log_encoding_Panalog(0.18) # doctest: +ELLIPSIS
np.float64(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: Domain1,
black_offset: ArrayLike = 10 ** ((64 - 681) / 444),
) -> Range1:
"""
Apply the *Panalog* log decoding inverse opto-electronic transfer function (OETF).
Parameters
----------
y
*Panalog* non-linear encoded 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`` | 1 | 1 |
+------------+-----------------------+---------------+
+------------+-----------------------+---------------+
| **Range** | **Scale - Reference** | **Scale - 1** |
+============+=======================+===============+
| ``x`` | 1 | 1 |
+------------+-----------------------+---------------+
References
----------
:cite:`SonyImageworks2012a`
Examples
--------
>>> log_decoding_Panalog(0.374576791382298) # doctest: +ELLIPSIS
np.float64(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))
