def test_n_dimensional_log_decoding_CanonLog(self):
"""
Tests :func:`colour.models.rgb.transfer_functions.canon_log.\
log_decoding_CanonLog` definition n-dimensional arrays support.
"""
V = 0.312012855550395
L = 0.18
np.testing.assert_almost_equal(
log_decoding_CanonLog(V),
L,
decimal=7)
V = np.tile(V, 6)
L = np.tile(L, 6)
np.testing.assert_almost_equal(
log_decoding_CanonLog(V),
L,
decimal=7)
V = np.reshape(V, (2, 3))
L = np.reshape(L, (2, 3))
np.testing.assert_almost_equal(
log_decoding_CanonLog(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_CanonLog(V),
L,
decimal=7)
def test_nan_log_decoding_CanonLog(self):
"""
Tests :func:`colour.models.rgb.transfer_functions.canon_log.\
log_decoding_CanonLog` definition nan support.
"""
log_decoding_CanonLog(
np.array([-1.0, 0.0, 1.0, -np.inf, np.inf, np.nan]))
def test_nan_log_decoding_CanonLog(self):
"""
Tests :func:`colour.models.rgb.transfer_functions.canon_log.\
log_decoding_CanonLog` definition nan support.
"""
log_decoding_CanonLog(
np.array([-1.0, 0.0, 1.0, -np.inf, np.inf, np.nan]))
def test_domain_range_scale_log_decoding_CanonLog(self):
"""
Test :func:`colour.models.rgb.transfer_functions.canon_log.\
log_decoding_CanonLog` definition domain and range scale support.
"""
clog = 0.343389651726069
x = log_decoding_CanonLog(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_CanonLog(clog *
factor),
x * factor,
decimal=7)
def test_domain_range_scale_log_decoding_CanonLog(self):
"""
Tests :func:`colour.models.rgb.transfer_functions.canon_log.\
log_decoding_CanonLog` definition domain and range scale support.
"""
clog = 0.343389651726069
x = log_decoding_CanonLog(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_CanonLog(clog * factor),
x * factor,
decimal=7)
def test_log_decoding_CanonLog(self):
"""
Tests :func:`colour.models.rgb.transfer_functions.canon_log.\
log_decoding_CanonLog` definition.
"""
self.assertAlmostEqual(log_decoding_CanonLog(0.073059700000000),
0.0,
places=7)
self.assertAlmostEqual(log_decoding_CanonLog(0.312012855550395),
0.18,
places=7)
self.assertAlmostEqual(log_decoding_CanonLog(0.627408304537653),
1.0,
places=7)
def test_log_decoding_CanonLog(self):
"""
Tests :func:`colour.models.rgb.transfer_functions.canon_log.\
log_decoding_CanonLog` definition.
"""
self.assertAlmostEqual(log_decoding_CanonLog(-0.023560122781997),
-0.1,
places=7)
self.assertAlmostEqual(log_decoding_CanonLog(0.125122480156403),
0.0,
places=7)
self.assertAlmostEqual(log_decoding_CanonLog(0.343389651726069),
0.18,
places=7)
self.assertAlmostEqual(log_decoding_CanonLog(0.343138084215647, 12),
0.18,
places=7)
self.assertAlmostEqual(log_decoding_CanonLog(0.327953896935809, 10,
False),
0.18,
places=7)
self.assertAlmostEqual(log_decoding_CanonLog(0.312012855550395, 10,
False, False),
0.18,
places=7)
self.assertAlmostEqual(log_decoding_CanonLog(0.618775485598649),
1.0,
places=7)
def test_log_decoding_CanonLog(self):
"""
Tests :func:`colour.models.rgb.transfer_functions.canon_log.\
log_decoding_CanonLog` definition.
"""
self.assertAlmostEqual(
log_decoding_CanonLog(-0.023560122781997), -0.1, places=7)
self.assertAlmostEqual(
log_decoding_CanonLog(0.125122480156403), 0.0, places=7)
self.assertAlmostEqual(
log_decoding_CanonLog(0.343389651726069), 0.18, places=7)
self.assertAlmostEqual(
log_decoding_CanonLog(0.343138084215647, 12), 0.18, places=7)
self.assertAlmostEqual(
log_decoding_CanonLog(0.327953896935809, 10, False),
0.18,
places=7)
self.assertAlmostEqual(
log_decoding_CanonLog(0.312012855550395, 10, False, False),
0.18,
places=7)
self.assertAlmostEqual(
log_decoding_CanonLog(0.618775485598649), 1.0, places=7)
def test_log_decoding_CanonLog(self):
"""
Tests :func:`colour.models.rgb.transfer_functions.canon_log.\
log_decoding_CanonLog` definition.
"""
self.assertAlmostEqual(
log_decoding_CanonLog(0.073059700000000),
0.0,
places=7)
self.assertAlmostEqual(
log_decoding_CanonLog(0.312012855550395),
0.18,
places=7)
self.assertAlmostEqual(
log_decoding_CanonLog(0.627408304537653),
1.0,
places=7)
def test_n_dimensional_log_decoding_CanonLog(self):
"""
Tests :func:`colour.models.rgb.transfer_functions.canon_log.\
log_decoding_CanonLog` definition n-dimensional arrays support.
"""
V = 0.312012855550395
L = 0.18
np.testing.assert_almost_equal(log_decoding_CanonLog(V), L, decimal=7)
V = np.tile(V, 6)
L = np.tile(L, 6)
np.testing.assert_almost_equal(log_decoding_CanonLog(V), L, decimal=7)
V = np.reshape(V, (2, 3))
L = np.reshape(L, (2, 3))
np.testing.assert_almost_equal(log_decoding_CanonLog(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_CanonLog(V), L, decimal=7)
def test_n_dimensional_log_decoding_CanonLog(self):
"""
Tests :func:`colour.models.rgb.transfer_functions.canon_log.\
log_decoding_CanonLog` definition n-dimensional arrays support.
"""
clog = 0.343389651726069
x = log_decoding_CanonLog(clog)
clog = np.tile(clog, 6)
x = np.tile(x, 6)
np.testing.assert_almost_equal(
log_decoding_CanonLog(clog), x, decimal=7)
clog = np.reshape(clog, (2, 3))
x = np.reshape(x, (2, 3))
np.testing.assert_almost_equal(
log_decoding_CanonLog(clog), x, decimal=7)
clog = np.reshape(clog, (2, 3, 1))
x = np.reshape(x, (2, 3, 1))
np.testing.assert_almost_equal(
log_decoding_CanonLog(clog), x, decimal=7)
