#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Panalog Encoding
================
Defines the *Panalog* encoding:
- :func:`log_encoding_Panalog`
- :func:`log_decoding_Panalog`
See Also
--------
`RGB Colourspaces IPython Notebook
<http://nbviewer.jupyter.org/github/colour-science/colour-notebooks/\
blob/master/notebooks/models/rgb.ipynb>`_
References
----------
.. [1] 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 division, unicode_literals
import numpy as np
__author__ = 'Colour Developers'
__copyright__ = 'Copyright (C) 2013-2016 - Colour Developers'
__license__ = 'New BSD License - http://opensource.org/licenses/BSD-3-Clause'
__maintainer__ = 'Colour Developers'
__email__ = 'colour-science@googlegroups.com'
__status__ = 'Production'
__all__ = ['log_encoding_Panalog',
'log_decoding_Panalog']
[docs]def log_encoding_Panalog(x,
black_offset=10 ** ((64 - 681) / 444)):
"""
Defines the *Panalog* log encoding curve / opto-electronic transfer
function.
Parameters
----------
x : numeric or array_like
Linear data :math:`x`.
black_offset : numeric or array_like
Black offset.
Returns
-------
numeric or ndarray
Non-linear data :math:`y`.
Warnings
--------
These are estimations known to be close enough, the actual log encoding
curves are not published.
Examples
--------
>>> log_encoding_Panalog(0.18) # doctest: +ELLIPSIS
0.3745767...
"""
x = np.asarray(x)
return ((681 + 444 *
np.log10(x * (1 - black_offset) + black_offset)) / 1023)
[docs]def log_decoding_Panalog(y,
black_offset=10 ** ((64 - 681) / 444)):
"""
Defines the *Panalog* log decoding curve / electro-optical transfer
function.
Parameters
----------
y : numeric or array_like
Non-linear data :math:`y`.
black_offset : numeric or array_like
Black offset.
Returns
-------
numeric or ndarray
Linear data :math:`x`.
Warnings
--------
These are estimations known to be close enough, the actual log encoding
curves are not published.
Examples
--------
>>> log_decoding_Panalog(0.374576791382298) # doctest: +ELLIPSIS
0.1...
"""
y = np.asarray(y)
return ((10 ** ((1023 * y - 681) / 444) - black_offset) /
(1 - black_offset))