def test_n_dimensional_log_decoding_CanonLog2(self):
"""
Test :func:`colour.models.rgb.transfer_functions.canon_log.\
log_decoding_CanonLog2` definition n-dimensional arrays support.
"""
clog2 = 0.398254694983167
x = log_decoding_CanonLog2(clog2)
clog2 = np.tile(clog2, 6)
x = np.tile(x, 6)
np.testing.assert_almost_equal(log_decoding_CanonLog2(clog2),
x,
decimal=7)
clog2 = np.reshape(clog2, (2, 3))
x = np.reshape(x, (2, 3))
np.testing.assert_almost_equal(log_decoding_CanonLog2(clog2),
x,
decimal=7)
clog2 = np.reshape(clog2, (2, 3, 1))
x = np.reshape(x, (2, 3, 1))
np.testing.assert_almost_equal(log_decoding_CanonLog2(clog2),
x,
decimal=7)
def test_nan_log_decoding_CanonLog2(self):
"""
Test :func:`colour.models.rgb.transfer_functions.canon_log.\
log_decoding_CanonLog2` definition nan support.
"""
log_decoding_CanonLog2(
np.array([-1.0, 0.0, 1.0, -np.inf, np.inf, np.nan]))
def test_nan_log_decoding_CanonLog2(self):
"""
Tests :func:`colour.models.rgb.transfer_functions.canon_log.\
log_decoding_CanonLog2` definition nan support.
"""
log_decoding_CanonLog2(
np.array([-1.0, 0.0, 1.0, -np.inf, np.inf, np.nan]))
def test_domain_range_scale_log_decoding_CanonLog2(self):
"""
Tests :func:`colour.models.rgb.transfer_functions.canon_log.\
log_decoding_CanonLog2` definition domain and range scale support.
"""
clog = 0.398254694983167
x = log_decoding_CanonLog2(clog)
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_CanonLog2(clog *
factor),
x * factor,
decimal=7)
def test_domain_range_scale_log_decoding_CanonLog2(self):
"""
Tests :func:`colour.models.rgb.transfer_functions.canon_log.\
log_decoding_CanonLog2` definition domain and range scale support.
"""
clog = 0.398254694983167
x = log_decoding_CanonLog2(clog)
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_CanonLog2(clog * factor),
x * factor,
decimal=7)
def test_log_decoding_CanonLog2(self):
"""
Tests :func:`colour.models.rgb.transfer_functions.canon_log.\
log_decoding_CanonLog2` definition.
"""
self.assertAlmostEqual(log_decoding_CanonLog2(-0.155370131996824),
-0.1,
places=7)
self.assertAlmostEqual(log_decoding_CanonLog2(0.092864125247312),
0.0,
places=7)
self.assertAlmostEqual(log_decoding_CanonLog2(0.398254694983167),
0.18,
places=7)
self.assertAlmostEqual(log_decoding_CanonLog2(0.397962933301861, 12),
0.18,
places=7)
self.assertAlmostEqual(log_decoding_CanonLog2(0.392025745397009, 10,
False),
0.18,
places=7)
self.assertAlmostEqual(log_decoding_CanonLog2(0.379864582222983, 10,
False, False),
0.18,
places=7)
self.assertAlmostEqual(log_decoding_CanonLog2(0.573229282897641),
1.0,
places=7)
def test_log_decoding_CanonLog2(self):
"""
Tests :func:`colour.models.rgb.transfer_functions.canon_log.\
log_decoding_CanonLog2` definition.
"""
self.assertAlmostEqual(
log_decoding_CanonLog2(-0.155370131996824), -0.1, places=7)
self.assertAlmostEqual(
log_decoding_CanonLog2(0.092864125247312), 0.0, places=7)
self.assertAlmostEqual(
log_decoding_CanonLog2(0.398254694983167), 0.18, places=7)
self.assertAlmostEqual(
log_decoding_CanonLog2(0.397962933301861, 12), 0.18, places=7)
self.assertAlmostEqual(
log_decoding_CanonLog2(0.392025745397009, 10, False),
0.18,
places=7)
self.assertAlmostEqual(
log_decoding_CanonLog2(0.379864582222983, 10, False, False),
0.18,
places=7)
self.assertAlmostEqual(
log_decoding_CanonLog2(0.573229282897641), 1.0, places=7)
def test_n_dimensional_log_decoding_CanonLog2(self):
"""
Tests :func:`colour.models.rgb.transfer_functions.canon_log.\
log_decoding_CanonLog2` definition n-dimensional arrays support.
"""
V = 0.379864582222983
L = 0.18
np.testing.assert_almost_equal(log_decoding_CanonLog2(V), L, decimal=7)
V = np.tile(V, 6)
L = np.tile(L, 6)
np.testing.assert_almost_equal(log_decoding_CanonLog2(V), L, decimal=7)
V = np.reshape(V, (2, 3))
L = np.reshape(L, (2, 3))
np.testing.assert_almost_equal(log_decoding_CanonLog2(V), L, decimal=7)
V = np.reshape(V, (2, 3, 1))
L = np.reshape(L, (2, 3, 1))
np.testing.assert_almost_equal(log_decoding_CanonLog2(V), L, decimal=7)
def test_log_decoding_CanonLog2(self):
"""
Tests :func:`colour.models.rgb.transfer_functions.canon_log.\
log_decoding_CanonLog2` definition.
"""
self.assertAlmostEqual(log_decoding_CanonLog2(-0.242871750266172),
-0.1,
places=7)
self.assertAlmostEqual(log_decoding_CanonLog2(0.035388127999999),
0.0,
places=7)
self.assertAlmostEqual(log_decoding_CanonLog2(0.379864582222983),
0.18,
places=7)
self.assertAlmostEqual(log_decoding_CanonLog2(0.583604185577946),
1.0,
places=7)
def test_n_dimensional_log_decoding_CanonLog2(self):
"""
Tests :func:`colour.models.rgb.transfer_functions.canon_log.\
log_decoding_CanonLog2` definition n-dimensional arrays support.
"""
clog2 = 0.398254694983167
x = log_decoding_CanonLog2(clog2)
clog2 = np.tile(clog2, 6)
x = np.tile(x, 6)
np.testing.assert_almost_equal(
log_decoding_CanonLog2(clog2), x, decimal=7)
clog2 = np.reshape(clog2, (2, 3))
x = np.reshape(x, (2, 3))
np.testing.assert_almost_equal(
log_decoding_CanonLog2(clog2), x, decimal=7)
clog2 = np.reshape(clog2, (2, 3, 1))
x = np.reshape(x, (2, 3, 1))
np.testing.assert_almost_equal(
log_decoding_CanonLog2(clog2), x, decimal=7)
