def test_nan_log_encoding_VLog(self):
"""
Tests :func:`colour.models.rgb.transfer_functions.panasonic_vlog.\
log_encoding_VLog` definition nan support.
"""
log_encoding_VLog(np.array([-1.0, 0.0, 1.0, -np.inf, np.inf, np.nan]))
def test_n_dimensional_log_encoding_VLog(self):
"""
Tests :func:`colour.models.rgb.transfer_functions.panasonic_vlog.\
log_encoding_VLog` definition n-dimensional arrays support.
"""
L_in = 0.18
V_out = 0.423311448760136
np.testing.assert_almost_equal(log_encoding_VLog(L_in),
V_out,
decimal=7)
L_in = np.tile(L_in, 6)
V_out = np.tile(V_out, 6)
np.testing.assert_almost_equal(log_encoding_VLog(L_in),
V_out,
decimal=7)
L_in = np.reshape(L_in, (2, 3))
V_out = np.reshape(V_out, (2, 3))
np.testing.assert_almost_equal(log_encoding_VLog(L_in),
V_out,
decimal=7)
L_in = np.reshape(L_in, (2, 3, 1))
V_out = np.reshape(V_out, (2, 3, 1))
np.testing.assert_almost_equal(log_encoding_VLog(L_in),
V_out,
decimal=7)
def test_nan_log_encoding_VLog(self):
"""
Tests :func:`colour.models.rgb.transfer_functions.panasonic_vlog.\
log_encoding_VLog` definition nan support.
"""
log_encoding_VLog(np.array([-1.0, 0.0, 1.0, -np.inf, np.inf, np.nan]))
def test_n_dimensional_log_encoding_VLog(self):
"""
Tests :func:`colour.models.rgb.transfer_functions.panasonic_vlog.\
log_encoding_VLog` definition n-dimensional arrays support.
"""
L = 0.18
V = 0.423311448760136
np.testing.assert_almost_equal(
log_encoding_VLog(L),
V,
decimal=7)
L = np.tile(L, 6)
V = np.tile(V, 6)
np.testing.assert_almost_equal(
log_encoding_VLog(L),
V,
decimal=7)
L = np.reshape(L, (2, 3))
V = np.reshape(V, (2, 3))
np.testing.assert_almost_equal(
log_encoding_VLog(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_VLog(L),
V,
decimal=7)
def test_log_encoding_VLog(self):
"""
Tests :func:`colour.models.rgb.transfer_functions.panasonic_vlog.\
log_encoding_VLog` definition.
"""
self.assertAlmostEqual(log_encoding_VLog(0.0), 0.125, places=7)
self.assertAlmostEqual(log_encoding_VLog(0.18),
0.423311448760136,
places=7)
self.assertAlmostEqual(log_encoding_VLog(1.0),
0.599117700158146,
places=7)
def test_domain_range_scale_log_encoding_VLog(self):
"""
Tests :func:`colour.models.rgb.transfer_functions.panasonic_vlog.\
log_encoding_VLog` definition domain and range scale support.
"""
L_in = 0.18
V_out = log_encoding_VLog(L_in)
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_VLog(L_in *
factor),
V_out * factor,
decimal=7)
def test_domain_range_scale_log_encoding_VLog(self):
"""
Tests :func:`colour.models.rgb.transfer_functions.panasonic_vlog.\
log_encoding_VLog` definition domain and range scale support.
"""
L_in = 0.18
V_out = log_encoding_VLog(L_in)
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_VLog(L_in * factor),
V_out * factor,
decimal=7)
def test_log_encoding_VLog(self):
"""
Tests :func:`colour.models.rgb.transfer_functions.panasonic_vlog.\
log_encoding_VLog` definition.
"""
self.assertAlmostEqual(
log_encoding_VLog(0.0),
0.125,
places=7)
self.assertAlmostEqual(
log_encoding_VLog(0.18),
0.423311448760136,
places=7)
self.assertAlmostEqual(
log_encoding_VLog(1.0),
0.599117700158146,
places=7)
def test_log_encoding_VLog(self):
"""
Test :func:`colour.models.rgb.transfer_functions.panasonic_vlog.\
log_encoding_VLog` definition.
"""
self.assertAlmostEqual(log_encoding_VLog(0.0), 0.125, places=7)
self.assertAlmostEqual(log_encoding_VLog(0.18),
0.423311448760136,
places=7)
self.assertAlmostEqual(log_encoding_VLog(0.18, 12),
0.423311448760136,
places=7)
self.assertAlmostEqual(log_encoding_VLog(0.18, 10, False),
0.421287228403675,
places=7)
self.assertAlmostEqual(
log_encoding_VLog(0.18, 10, False, False),
0.409009628526078,
places=7,
)
self.assertAlmostEqual(log_encoding_VLog(1.0),
0.599117700158146,
places=7)
def test_n_dimensional_log_encoding_VLog(self):
"""
Tests :func:`colour.models.rgb.transfer_functions.panasonic_vlog.\
log_encoding_VLog` definition n-dimensional arrays support.
"""
L_in = 0.18
V_out = log_encoding_VLog(L_in)
L_in = np.tile(L_in, 6)
V_out = np.tile(V_out, 6)
np.testing.assert_almost_equal(
log_encoding_VLog(L_in), V_out, decimal=7)
L_in = np.reshape(L_in, (2, 3))
V_out = np.reshape(V_out, (2, 3))
np.testing.assert_almost_equal(
log_encoding_VLog(L_in), V_out, decimal=7)
L_in = np.reshape(L_in, (2, 3, 1))
V_out = np.reshape(V_out, (2, 3, 1))
np.testing.assert_almost_equal(
log_encoding_VLog(L_in), V_out, decimal=7)