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)