def test_n_dimensional_log_encoding_Cineon(self):
"""
Tests :func:`colour.models.rgb.transfer_functions.cineon.\
log_encoding_Cineon` definition n-dimensional arrays support.
"""
L = 0.18
V = 0.457319613085418
np.testing.assert_almost_equal(
log_encoding_Cineon(L),
V,
decimal=7)
L = np.tile(L, 6)
V = np.tile(V, 6)
np.testing.assert_almost_equal(
log_encoding_Cineon(L),
V,
decimal=7)
L = np.reshape(L, (2, 3))
V = np.reshape(V, (2, 3))
np.testing.assert_almost_equal(
log_encoding_Cineon(L),
V,
decimal=7)
L = np.reshape(L, (2, 3, 1))
V = np.reshape(V, (2, 3, 1))
np.testing.assert_almost_equal(
log_encoding_Cineon(L),
V,
decimal=7)
def test_n_dimensional_log_encoding_Cineon(self):
"""
Tests :func:`colour.models.rgb.transfer_functions.cineon.\
log_encoding_Cineon` definition n-dimensional arrays support.
"""
L = 0.18
V = 0.457319613085418
np.testing.assert_almost_equal(
log_encoding_Cineon(L),
V,
decimal=7)
L = np.tile(L, 6)
V = np.tile(V, 6)
np.testing.assert_almost_equal(
log_encoding_Cineon(L),
V,
decimal=7)
L = np.reshape(L, (2, 3))
V = np.reshape(V, (2, 3))
np.testing.assert_almost_equal(
log_encoding_Cineon(L),
V,
decimal=7)
L = np.reshape(L, (2, 3, 1))
V = np.reshape(V, (2, 3, 1))
np.testing.assert_almost_equal(
log_encoding_Cineon(L),
V,
decimal=7)
def test_nan_log_encoding_Cineon(self):
"""
Tests :func:`colour.models.rgb.transfer_functions.cineon.\
log_encoding_Cineon` definition nan support.
"""
log_encoding_Cineon(
np.array([-1.0, 0.0, 1.0, -np.inf, np.inf, np.nan]))
def test_nan_log_encoding_Cineon(self):
"""
Tests :func:`colour.models.rgb.transfer_functions.cineon.\
log_encoding_Cineon` definition nan support.
"""
log_encoding_Cineon(np.array([-1.0, 0.0, 1.0, -np.inf, np.inf,
np.nan]))
def test_domain_range_scale_log_encoding_Cineon(self):
"""
Tests :func:`colour.models.rgb.transfer_functions.cineon.\
log_encoding_Cineon` definition domain and range scale support.
"""
x = 0.18
y = log_encoding_Cineon(x)
d_r = (('reference', 1), (1, 1), (100, 100))
for scale, factor in d_r:
with domain_range_scale(scale):
np.testing.assert_almost_equal(
log_encoding_Cineon(x * factor), y * factor, decimal=7)
def test_log_encoding_Cineon(self):
"""
Tests :func:`colour.models.rgb.transfer_functions.cineon.\
log_encoding_Cineon` definition.
"""
self.assertAlmostEqual(
log_encoding_Cineon(0.0), 0.092864125122190, places=7)
self.assertAlmostEqual(
log_encoding_Cineon(0.18), 0.457319613085418, places=7)
self.assertAlmostEqual(
log_encoding_Cineon(1.0), 0.669599217986315, places=7)
def test_log_encoding_Cineon(self):
"""
Tests :func:`colour.models.rgb.transfer_functions.cineon.\
log_encoding_Cineon` definition.
"""
self.assertAlmostEqual(
log_encoding_Cineon(0.0), 0.092864125122190, places=7)
self.assertAlmostEqual(
log_encoding_Cineon(0.18), 0.457319613085418, places=7)
self.assertAlmostEqual(
log_encoding_Cineon(1.0), 0.669599217986315, places=7)
def test_domain_range_scale_log_encoding_Cineon(self):
"""
Tests :func:`colour.models.rgb.transfer_functions.cineon.\
log_encoding_Cineon` definition domain and range scale support.
"""
x = 0.18
y = log_encoding_Cineon(x)
d_r = (('reference', 1), (1, 1), (100, 100))
for scale, factor in d_r:
with domain_range_scale(scale):
np.testing.assert_almost_equal(log_encoding_Cineon(x * factor),
y * factor,
decimal=7)
def log_encoding_REDLogFilm(x, black_offset=10**((95 - 685) / 300)):
"""
Defines the *REDLogFilm* 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`.
References
----------
- :cite:`SonyImageworks2012a`
Examples
--------
>>> log_encoding_REDLogFilm(0.18) # doctest: +ELLIPSIS
0.4573196...
"""
return log_encoding_Cineon(x, black_offset)
def log_encoding_REDLogFilm(x,
black_offset=10 ** ((95 - 685) / 300)):
"""
Defines the *REDLogFilm* 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`.
Examples
--------
>>> log_encoding_REDLogFilm(0.18) # doctest: +ELLIPSIS
0.4573196...
"""
return log_encoding_Cineon(x, black_offset)
def test_n_dimensional_log_encoding_Cineon(self):
"""
Tests :func:`colour.models.rgb.transfer_functions.cineon.\
log_encoding_Cineon` definition n-dimensional arrays support.
"""
x = 0.18
y = log_encoding_Cineon(x)
x = np.tile(x, 6)
y = np.tile(y, 6)
np.testing.assert_almost_equal(log_encoding_Cineon(x), y, decimal=7)
x = np.reshape(x, (2, 3))
y = np.reshape(y, (2, 3))
np.testing.assert_almost_equal(log_encoding_Cineon(x), y, decimal=7)
x = np.reshape(x, (2, 3, 1))
y = np.reshape(y, (2, 3, 1))
np.testing.assert_almost_equal(log_encoding_Cineon(x), y, decimal=7)
def test_n_dimensional_log_encoding_Cineon(self):
"""
Test :func:`colour.models.rgb.transfer_functions.cineon.\
log_encoding_Cineon` definition n-dimensional arrays support.
"""
x = 0.18
y = log_encoding_Cineon(x)
x = np.tile(x, 6)
y = np.tile(y, 6)
np.testing.assert_almost_equal(log_encoding_Cineon(x), y, decimal=7)
x = np.reshape(x, (2, 3))
y = np.reshape(y, (2, 3))
np.testing.assert_almost_equal(log_encoding_Cineon(x), y, decimal=7)
x = np.reshape(x, (2, 3, 1))
y = np.reshape(y, (2, 3, 1))
np.testing.assert_almost_equal(log_encoding_Cineon(x), y, decimal=7)
def log_encoding_REDLogFilm(
x: FloatingOrArrayLike,
black_offset: FloatingOrArrayLike = 10 ** ((95 - 685) / 300),
) -> FloatingOrNDArray:
"""
Define the *REDLogFilm* log encoding curve / opto-electronic transfer
function.
Parameters
----------
x
Linear data :math:`x`.
black_offset
Black offset.
Returns
-------
:class:`numpy.floating` or :class:`numpy.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:`SonyImageworks2012a`
Examples
--------
>>> log_encoding_REDLogFilm(0.18) # doctest: +ELLIPSIS
0.4573196...
"""
return log_encoding_Cineon(x, black_offset)
def log_encoding_REDLogFilm(x, black_offset=10 ** ((95 - 685) / 300)):
"""
Defines the *REDLogFilm* 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`.
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_REDLogFilm(0.18) # doctest: +ELLIPSIS
0.4573196...
"""
return log_encoding_Cineon(x, black_offset)
