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

# -*- coding: utf-8 -*-
"""
GoPro Encoding
==============

Defines the *GoPro* *Protune* encoding:

-   :func:`colour.models.log_encoding_Protune`
-   :func:`colour.models.log_decoding_Protune`

See Also
--------
`RGB Colourspaces Jupyter Notebook
<http://nbviewer.jupyter.org/github/colour-science/colour-notebooks/\
blob/master/notebooks/models/rgb.ipynb>`_

References
----------
-   :cite:`GoPro2016a` : GoPro, Duiker, H.-P., & Mansencal, T. (2016).
    gopro.py. Retrieved April 12, 2017, from
    https://github.com/hpd/OpenColorIO-Configs/blob/master/aces_1.0.3/python/\
aces_ocio/colorspaces/gopro.py
"""

from __future__ import division, unicode_literals

import numpy as np

from colour.utilities import from_range_1, to_domain_1

__author__ = 'Colour Developers'
__copyright__ = 'Copyright (C) 2013-2020 - Colour Developers'
__license__ = 'New BSD License - https://opensource.org/licenses/BSD-3-Clause'
__maintainer__ = 'Colour Developers'
__email__ = 'colour-developers@colour-science.org'
__status__ = 'Production'

__all__ = ['log_encoding_Protune', 'log_decoding_Protune']


[docs]def log_encoding_Protune(x): """ Defines the *Protune* log encoding curve / opto-electronic transfer function. Parameters ---------- x : numeric or array_like Linear data :math:`x`. Returns ------- numeric or 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:`GoPro2016a` Examples -------- >>> log_encoding_Protune(0.18) # doctest: +ELLIPSIS 0.6456234... """ x = to_domain_1(x) y = np.log(x * 112 + 1) / np.log(113) return from_range_1(y)
[docs]def log_decoding_Protune(y): """ Defines the *Protune* log decoding curve / electro-optical transfer function. Parameters ---------- y : numeric or array_like Non-linear data :math:`y`. Returns ------- numeric or 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:`GoPro2016a` Examples -------- >>> log_decoding_Protune(0.645623486803636) # doctest: +ELLIPSIS 0.1... """ y = to_domain_1(y) x = (113 ** y - 1) / 112 return from_range_1(x)