def test_nan_log_decoding_Log3G10(self):
"""
Tests :func:`colour.models.rgb.transfer_functions.red_log.\
log_decoding_Log3G10` definition nan support.
"""
log_decoding_Log3G10(
np.array([-1.0, 0.0, 1.0, -np.inf, np.inf, np.nan]),
legacy_curve=True)
log_decoding_Log3G10(
np.array([-1.0, 0.0, 1.0, -np.inf, np.inf, np.nan]),
legacy_curve=False)
def test_nan_log_decoding_Log3G10(self):
"""
Tests :func:`colour.models.rgb.transfer_functions.red_log.\
log_decoding_Log3G10` definition nan support.
"""
log_decoding_Log3G10(
np.array([-1.0, 0.0, 1.0, -np.inf, np.inf, np.nan]),
legacy_curve=True)
log_decoding_Log3G10(
np.array([-1.0, 0.0, 1.0, -np.inf, np.inf, np.nan]),
legacy_curve=False)
def test_domain_range_scale_log_decoding_Log3G10(self):
"""
Tests :func:`colour.models.rgb.transfer_functions.red_log.\
log_decoding_Log3G10` definition domain and range scale support.
"""
y = 0.333333644207707
x = log_decoding_Log3G10(y)
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_decoding_Log3G10(y * factor), x * factor, decimal=7)
def test_n_dimensional_log_decoding_Log3G10(self):
"""
Tests :func:`colour.models.rgb.transfer_functions.red_log.\
log_decoding_Log3G10` definition n-dimensional arrays support.
"""
y1 = 0.333333644207707
y2 = 0.333332912025992
x = 0.18
np.testing.assert_almost_equal(log_decoding_Log3G10(y1,
legacy_curve=True),
x,
decimal=7)
np.testing.assert_almost_equal(log_decoding_Log3G10(
y2, legacy_curve=False),
x,
decimal=7)
y1 = np.tile(y1, 6)
y2 = np.tile(y2, 6)
x = np.tile(x, 6)
np.testing.assert_almost_equal(log_decoding_Log3G10(y1,
legacy_curve=True),
x,
decimal=7)
np.testing.assert_almost_equal(log_decoding_Log3G10(
y2, legacy_curve=False),
x,
decimal=7)
y1 = np.reshape(y1, (2, 3))
y2 = np.reshape(y2, (2, 3))
x = np.reshape(x, (2, 3))
np.testing.assert_almost_equal(log_decoding_Log3G10(y1,
legacy_curve=True),
x,
decimal=7)
np.testing.assert_almost_equal(log_decoding_Log3G10(
y2, legacy_curve=False),
x,
decimal=7)
y1 = np.reshape(y1, (2, 3, 1))
y2 = np.reshape(y2, (2, 3, 1))
x = np.reshape(x, (2, 3, 1))
np.testing.assert_almost_equal(log_decoding_Log3G10(y1,
legacy_curve=True),
x,
decimal=7)
np.testing.assert_almost_equal(log_decoding_Log3G10(
y2, legacy_curve=False),
x,
decimal=7)
def test_log_decoding_Log3G10(self):
"""
Tests :func:`colour.models.rgb.transfer_functions.red_log.\
log_decoding_Log3G10` definition.
"""
self.assertAlmostEqual(
log_decoding_Log3G10(-0.496483569056003, legacy_curve=True),
-1.0,
places=7)
self.assertAlmostEqual(
log_decoding_Log3G10(0.0, legacy_curve=True), 0.0, places=7)
self.assertAlmostEqual(
log_decoding_Log3G10(0.333333644207707, legacy_curve=True),
0.18,
places=7)
self.assertAlmostEqual(
log_decoding_Log3G10(-0.491512777522511, legacy_curve=False),
-1.0,
places=7)
self.assertAlmostEqual(
log_decoding_Log3G10(0.091551487714745, legacy_curve=False),
0.0,
places=7)
self.assertAlmostEqual(
log_decoding_Log3G10(0.333332912025992, legacy_curve=False),
0.18,
places=7)
def test_log_decoding_Log3G10(self):
"""
Tests :func:`colour.models.rgb.transfer_functions.red_log.\
log_decoding_Log3G10` definition.
"""
self.assertAlmostEqual(
log_decoding_Log3G10(-0.496483569056003, legacy_curve=True),
-1.0,
places=7)
self.assertAlmostEqual(
log_decoding_Log3G10(0.0, legacy_curve=True), 0.0, places=7)
self.assertAlmostEqual(
log_decoding_Log3G10(0.333333644207707, legacy_curve=True),
0.18,
places=7)
self.assertAlmostEqual(
log_decoding_Log3G10(-0.491512777522511, legacy_curve=False),
-1.0,
places=7)
self.assertAlmostEqual(
log_decoding_Log3G10(0.091551487714745, legacy_curve=False),
0.0,
places=7)
self.assertAlmostEqual(
log_decoding_Log3G10(0.333332912025992, legacy_curve=False),
0.18,
places=7)
def test_n_dimensional_log_decoding_Log3G10(self):
"""
Tests :func:`colour.models.rgb.transfer_functions.red_log.\
log_decoding_Log3G10` definition n-dimensional arrays support.
"""
y_1 = 0.333333644207707
y_2 = 0.333332912025992
x_1 = log_decoding_Log3G10(y_1, legacy_curve=True)
x_2 = log_decoding_Log3G10(y_2, legacy_curve=False)
y_1 = np.tile(y_1, 6)
y_2 = np.tile(y_2, 6)
x_1 = np.tile(x_1, 6)
x_2 = np.tile(x_2, 6)
np.testing.assert_almost_equal(
log_decoding_Log3G10(y_1, legacy_curve=True), x_1, decimal=7)
np.testing.assert_almost_equal(
log_decoding_Log3G10(y_2, legacy_curve=False), x_2, decimal=7)
y_1 = np.reshape(y_1, (2, 3))
y_2 = np.reshape(y_2, (2, 3))
x_1 = np.reshape(x_1, (2, 3))
x_2 = np.reshape(x_2, (2, 3))
np.testing.assert_almost_equal(
log_decoding_Log3G10(y_1, legacy_curve=True), x_1, decimal=7)
np.testing.assert_almost_equal(
log_decoding_Log3G10(y_2, legacy_curve=False), x_2, decimal=7)
y_1 = np.reshape(y_1, (2, 3, 1))
y_2 = np.reshape(y_2, (2, 3, 1))
x_1 = np.reshape(x_1, (2, 3, 1))
x_2 = np.reshape(x_2, (2, 3, 1))
np.testing.assert_almost_equal(
log_decoding_Log3G10(y_1, legacy_curve=True), x_1, decimal=7)
np.testing.assert_almost_equal(
log_decoding_Log3G10(y_2, legacy_curve=False), x_2, decimal=7)
