def setUp(self):
"""Initialise the common tests attributes."""
self._shape = SPECTRAL_SHAPE_OTSU2018
self._cmfs, self._sd_D65 = handle_spectral_arguments(
shape_default=self._shape
)
self._reflectances = sds_and_msds_to_msds(
SDS_COLOURCHECKERS["ColorChecker N Ohta"].values()
)
self._tree = Tree_Otsu2018(self._reflectances)
self._tree.optimise()
for leaf in self._tree.leaves:
if len(leaf.parent.children) == 2:
self._node_a = leaf.parent
self._node_b, self._node_c = self._node_a.children
break
self._data_a = Data_Otsu2018(
np.transpose(reshape_msds(self._reflectances, self._shape).values),
self._cmfs,
self._sd_D65,
)
self._data_b = self._node_b.data
self._partition_axis = self._node_a.partition_axis
def test_mean(self):
"""Test :attr:`colour.recovery.otsu2018.Data_Otsu2018.mean` property."""
data = Data_Otsu2018(self._reflectances, self._cmfs, self._sd_D65)
self.assertIsNone(data.mean)
data.PCA()
self.assertTupleEqual(data.mean.shape, (36,))
def test_raise_exception_reconstruction_error(self):
"""
Test :meth:`colour.recovery.otsu2018.Data_Otsu2018.\
reconstruction_error` method raised exception.
"""
self.assertRaises(
ValueError,
Data_Otsu2018(None, self._cmfs, self._sd_D65).reconstruction_error,
)
def test_reconstruction_error(self):
"""
Test :meth:`colour.recovery.otsu2018.Data_Otsu2018.\
reconstruction_error` method.
"""
data = Data_Otsu2018(self._reflectances, self._cmfs, self._sd_D65)
self.assertAlmostEqual(
data.reconstruction_error(), 2.753352549148681, places=7
)
def test_raise_exception_partition(self):
"""
Test :meth:`colour.recovery.otsu2018.Data_Otsu2018.partition` method
raised exception.
"""
self.assertRaises(
ValueError,
Data_Otsu2018(None, self._cmfs, self._sd_D65).partition,
PartitionAxis(4, 1),
)
def test_raise_exception_origin(self):
"""
Test :meth:`colour.recovery.otsu2018.Data_Otsu2018.origin` method
raised exception.
"""
self.assertRaises(
ValueError,
Data_Otsu2018(None, self._cmfs, self._sd_D65).origin,
4,
1,
)
def test_basis_functions(self):
"""
Test :attr:`colour.recovery.otsu2018.Data_Otsu2018.basis_functions`
property.
"""
data = Data_Otsu2018(self._reflectances, self._cmfs, self._sd_D65)
self.assertIsNone(data.basis_functions)
data.PCA()
self.assertTupleEqual(data.basis_functions.shape, (3, 36))
def setUp(self):
"""Initialise the common tests attributes."""
self._shape = SPECTRAL_SHAPE_OTSU2018
self._cmfs, self._sd_D65 = handle_spectral_arguments(
shape_default=self._shape
)
self._reflectances = np.transpose(
reshape_msds(
sds_and_msds_to_msds(
SDS_COLOURCHECKERS["ColorChecker N Ohta"].values()
),
self._shape,
).values
)
self._data = Data_Otsu2018(
self._reflectances, self._cmfs, self._sd_D65
)
def test_reconstruct(self):
"""
Test :meth:`colour.recovery.otsu2018.Data_Otsu2018.reconstruct`
method.
"""
data = Data_Otsu2018(self._reflectances, self._cmfs, self._sd_D65)
data.PCA()
np.testing.assert_almost_equal(
data.reconstruct(
np.array(
[
0.20654008,
0.12197225,
0.05136952,
]
)
).values,
np.array(
[
0.06899964,
0.08241919,
0.09768650,
0.08938555,
0.07872582,
0.07140930,
0.06385099,
0.05471747,
0.04281364,
0.03073280,
0.01761134,
0.00772535,
0.00379120,
0.00405617,
0.00595014,
0.01323536,
0.03229711,
0.05661531,
0.07763041,
0.10271461,
0.14276781,
0.20239859,
0.27288559,
0.35044541,
0.42170481,
0.47567859,
0.50910276,
0.53578140,
0.55251101,
0.56530032,
0.58029915,
0.59367723,
0.60830542,
0.62100871,
0.62881635,
0.63971254,
]
),
decimal=7,
)
def test_PCA(self):
"""Test :meth:`colour.recovery.otsu2018.Data_Otsu2018.PCA` method."""
data = Data_Otsu2018(self._reflectances, self._cmfs, self._sd_D65)
data.PCA()
np.testing.assert_almost_equal(
data.basis_functions,
np.array(
[
[
0.04391241,
0.08560996,
0.15556120,
0.20826672,
0.22981218,
0.23117641,
0.22718022,
0.21742869,
0.19854261,
0.16868383,
0.12020268,
0.05958463,
-0.01015508,
-0.08775193,
-0.16957532,
-0.23186776,
-0.26516404,
-0.27409402,
-0.27856619,
-0.27685075,
-0.25597708,
-0.21331000,
-0.15372029,
-0.08746878,
-0.02744494,
0.01725581,
0.04756055,
0.07184639,
0.09090063,
0.10317253,
0.10830387,
0.10872694,
0.10645999,
0.10766424,
0.11170078,
0.11620896,
],
[
0.03137588,
0.06204234,
0.11364884,
0.17579436,
0.20914074,
0.22152351,
0.23120105,
0.24039823,
0.24730359,
0.25195045,
0.25237533,
0.24672212,
0.23538236,
0.22094141,
0.20389065,
0.18356599,
0.15952882,
0.13567812,
0.11401807,
0.09178015,
0.06539517,
0.03173809,
-0.00658524,
-0.04710763,
-0.08379987,
-0.11074555,
-0.12606191,
-0.13630094,
-0.13988107,
-0.14193361,
-0.14671866,
-0.15164795,
-0.15772737,
-0.16328073,
-0.16588768,
-0.16947164,
],
[
-0.01360289,
-0.02375832,
-0.04262545,
-0.07345243,
-0.09081235,
-0.09227928,
-0.08922710,
-0.08626299,
-0.08584571,
-0.08843734,
-0.09475094,
-0.10376740,
-0.11331399,
-0.12109706,
-0.12678070,
-0.13401030,
-0.14417036,
-0.15408359,
-0.16265529,
-0.17079814,
-0.17972656,
-0.19005983,
-0.20053986,
-0.21017531,
-0.21808806,
-0.22347400,
-0.22650876,
-0.22895376,
-0.22982598,
-0.23001787,
-0.23036398,
-0.22917409,
-0.22684271,
-0.22387883,
-0.22065773,
-0.21821049,
],
]
),
decimal=7,
)
np.testing.assert_almost_equal(
data.mean,
np.array(
[
0.08795833,
0.12050000,
0.16787500,
0.20675000,
0.22329167,
0.22837500,
0.23229167,
0.23579167,
0.23658333,
0.23779167,
0.23866667,
0.23975000,
0.24345833,
0.25054167,
0.25791667,
0.26150000,
0.26437500,
0.26566667,
0.26475000,
0.26554167,
0.27137500,
0.28279167,
0.29529167,
0.31070833,
0.32575000,
0.33829167,
0.34675000,
0.35554167,
0.36295833,
0.37004167,
0.37854167,
0.38675000,
0.39587500,
0.40266667,
0.40683333,
0.41287500,
]
),
decimal=7,
)