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_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)