def test_fit_features(self):
trans = Shell(input_type="filename")
feats = trans.fit_transform(ALL)
a = AtomKernel()
values = list(zip(feats, ALL_NUMS))
a.fit(values)
self.assertEqual(ALL_NUMS, list(a._numbers))
self.assertEqual(list(ALL_FEATURES), list(a._features))
def test_transform_transformer(self):
trans = Shell(input_type="filename")
a = AtomKernel(transformer=trans)
a.fit(ALL)
res = a.transform(ALL)
try:
numpy.testing.assert_array_almost_equal(RBF_KERNEL, res)
except AssertionError as e:
self.fail(e)
def test_laplace_kernel(self):
# Set depth=2 so the comparison is not trivial
trans = Shell(input_type="filename", depth=2)
a = AtomKernel(transformer=trans, kernel="laplace", gamma=1.)
a.fit(ALL)
res = a.transform(ALL)
try:
numpy.testing.assert_array_almost_equal(LAPLACE_KERNEL, res)
except AssertionError as e:
self.fail(e)
def test_transform_features(self):
trans = Shell(input_type="filename")
feats = trans.fit_transform(ALL)
a = AtomKernel()
values = list(zip(feats, ALL_NUMS))
a.fit(values)
res = a.transform(values)
try:
numpy.testing.assert_array_almost_equal(RBF_KERNEL, res)
except AssertionError as e:
self.fail(e)
def test_custom_kernel(self):
# Set depth=2 so the comparison is not trivial
trans = Shell(input_type="filename", depth=2)
# Simple linear kernel
a = AtomKernel(transformer=trans,
kernel=lambda x, y: numpy.dot(x, numpy.transpose(y)))
a.fit(ALL)
res = a.transform(ALL)
try:
numpy.testing.assert_array_almost_equal(LINEAR_KERNEL, res)
except AssertionError as e:
self.fail(e)
def test_fit_transformer(self):
trans = Shell(input_type="filename")
a = AtomKernel(transformer=trans)
a.fit(ALL)
self.assertEqual(ALL_NUMS, [x.tolist() for x in a._numbers])
self.assertEqual(list(ALL_FEATURES), list(a._features))