#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Canon Log Encodings
===================
Defines the *Canon Log* encodings:
- :func:`log_encoding_CanonLog`
- :func:`log_decoding_CanonLog`
- :func:`log_encoding_CanonLog2`
- :func:`log_decoding_CanonLog2`
- :func:`log_encoding_CanonLog3`
- :func:`log_decoding_CanonLog3`
See Also
--------
`RGB Colourspaces Jupyter Notebook
<http://nbviewer.jupyter.org/github/colour-science/colour-notebooks/\
blob/master/notebooks/models/rgb.ipynb>`_
References
----------
.. [1] Thorpe, L. (2012). CANON-LOG TRANSFER CHARACTERISTIC. Retrieved
from http://downloads.canon.com/CDLC/\
Canon-Log_Transfer_Characteristic_6-20-2012.pdf
.. [2] Canon. (n.d.). EOS C300 Mark II - EOS C300 Mark II Input Transform
Version 2.0 (for Cinema Gamut / BT.2020). Retrieved August 23, 2016,
from https://www.usa.canon.com/internet/portal/us/home/support/\
details/cameras/cinema-eos/eos-c300-mark-ii
Notes
-----
- [2]_ is available as a *Drivers & Downloads* *Software* for Windows 10
(x64) *Operating System*, a copy of the archive is hosted at this url:
https://drive.google.com/open?id=0B_IQZQdc4Vy8ZGYyY29pMEVwZU0
"""
from __future__ import division, unicode_literals
import numpy as np
from colour.utilities import as_numeric
__author__ = 'Colour Developers'
__copyright__ = 'Copyright (C) 2013-2017 - 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_CanonLog',
'log_decoding_CanonLog',
'log_encoding_CanonLog2',
'log_decoding_CanonLog2',
'log_encoding_CanonLog3',
'log_decoding_CanonLog3']
[docs]def log_encoding_CanonLog(x):
"""
Defines the *Canon Log* log encoding curve / opto-electronic transfer
function.
Parameters
----------
x : numeric or array_like
Linear data :math:`x`.
Returns
-------
numeric or ndarray
*Canon Log* non-linear *IRE* data.
Notes
-----
- Output *Canon Log* non-linear *IRE* data should be converted to code
value *CV* as follows: `CV = IRE * (940 - 64) + 64`.
Examples
--------
>>> log_encoding_CanonLog(0.20) * 100 # doctest: +ELLIPSIS
32.7953896...
"""
x = np.asarray(x)
clog_ire = np.where(
x < log_decoding_CanonLog(0.0730597),
-(0.529136 * (np.log10(-x * 10.1596 + 1)) - 0.0730597),
0.529136 * np.log10(10.1596 * x + 1) + 0.0730597)
return as_numeric(clog_ire)
[docs]def log_decoding_CanonLog(clog_ire):
"""
Defines the *Canon Log* log decoding curve / electro-optical transfer
function.
Parameters
----------
clog_ire : numeric or array_like
*Canon Log* non-linear *IRE* data.
Returns
-------
numeric or ndarray
Linear data :math:`x`.
Notes
-----
- Input *Canon Log* non-linear *IRE* data should be converted from code
value *CV* to *IRE* as follows: `IRE = (CV - 64) / (940 - 64)`.
Examples
--------
>>> log_decoding_CanonLog(32.795389693580908 / 100) # doctest: +ELLIPSIS
0.19999999...
"""
clog_ire = np.asarray(clog_ire)
x = np.where(
clog_ire < 0.0730597,
-(10 ** ((0.0730597 - clog_ire) / 0.529136) - 1) / 10.1596,
(10 ** ((clog_ire - 0.0730597) / 0.529136) - 1) / 10.1596)
return as_numeric(x)
[docs]def log_encoding_CanonLog2(x):
"""
Defines the *Canon Log 2* log encoding curve / opto-electronic transfer
function.
Parameters
----------
x : numeric or array_like
Linear data :math:`x`.
Returns
-------
numeric or ndarray
*Canon Log 2* non-linear *IRE* data.
Notes
-----
- Output *Canon Log 2* non-linear *IRE* data should be converted to code
value *CV* as follows: `CV = IRE * (940 - 64) + 64`.
Examples
--------
>>> log_encoding_CanonLog2(0.20) * 100 # doctest: +ELLIPSIS
39.2025745...
"""
x = np.asarray(x)
clog2_ire = np.where(
x < log_decoding_CanonLog2(0.035388128),
-(0.281863093 * (np.log10(-x * 87.09937546 + 1)) - 0.035388128),
0.281863093 * np.log10(x * 87.09937546 + 1) + 0.035388128)
return as_numeric(clog2_ire)
[docs]def log_decoding_CanonLog2(clog2_ire):
"""
Defines the *Canon Log 2* log decoding curve / electro-optical transfer
function.
Parameters
----------
clog2_ire : numeric or array_like
*Canon Log 2* non-linear *IRE* data.
Returns
-------
numeric or ndarray
Linear data :math:`x`.
Notes
-----
- Input *Canon Log 2* non-linear *IRE* data should be converted from code
value *CV* to *IRE* as follows: `IRE = (CV - 64) / (940 - 64)`.
Examples
--------
>>> log_decoding_CanonLog2(39.202574539700947 / 100) # doctest: +ELLIPSIS
0.2000000...
"""
clog2_ire = np.asarray(clog2_ire)
x = np.where(
clog2_ire < 0.035388128,
-(10 ** ((0.035388128 - clog2_ire) / 0.281863093) - 1) / 87.09937546,
(10 ** ((clog2_ire - 0.035388128) / 0.281863093) - 1) / 87.09937546)
return as_numeric(x)
[docs]def log_encoding_CanonLog3(x):
"""
Defines the *Canon Log 3* log encoding curve / opto-electronic transfer
function.
Parameters
----------
x : numeric or array_like
Linear data :math:`x`.
Returns
-------
numeric or ndarray
*Canon Log 3* non-linear *IRE* data.
Notes
-----
- Output *Canon Log 3* non-linear *IRE* data should be converted to code
value *CV* as follows: `CV = IRE * (940 - 64) + 64`.
Examples
--------
>>> log_encoding_CanonLog3(0.20) * 100 # doctest: +ELLIPSIS
32.7953567...
"""
x = np.asarray(x)
clog3_ire = np.select(
(x < log_decoding_CanonLog3(0.04076162),
x <= log_decoding_CanonLog3(0.105357102),
x > log_decoding_CanonLog3(0.105357102)),
(-(0.42889912 * (np.log10(-x * 14.98325 + 1)) - 0.069886632),
2.3069815 * x + 0.073059361,
0.42889912 * np.log10(x * 14.98325 + 1) + 0.069886632))
return as_numeric(clog3_ire)
[docs]def log_decoding_CanonLog3(clog3_ire):
"""
Defines the *Canon Log 3* log decoding curve / electro-optical transfer
function.
Parameters
----------
clog3_ire : numeric or array_like
*Canon Log 3* non-linear *IRE* data.
Returns
-------
numeric or ndarray
Linear data :math:`x`.
Notes
-----
- Input *Canon Log 3* non-linear *IRE* data should be converted from code
value *CV* to *IRE* as follows: `IRE = (CV - 64) / (940 - 64)`.
Examples
--------
>>> log_decoding_CanonLog3(32.795356721989336 / 100) # doctest: +ELLIPSIS
0.2000000...
"""
clog3_ire = np.asarray(clog3_ire)
x = np.select(
(clog3_ire < 0.04076162,
clog3_ire <= 0.105357102,
clog3_ire > 0.105357102),
(-(10 ** ((0.069886632 - clog3_ire) / 0.42889912) - 1) / 14.98325,
(clog3_ire - 0.073059361) / 2.3069815,
(10 ** ((clog3_ire - 0.069886632) / 0.42889912) - 1) / 14.98325))
return as_numeric(x)