def test_apply_kernel_invalid(self):
"""Check that an invalid kernel choice raises an exception."""
clf = BaseRVM(kernel='wrong')
x = np.array([[1, 2], [3, 4]])
y = np.array([[5, 6], [7, 8]])
try:
clf._apply_kernel(x, y)
except ValueError as error:
self.assertEqual(str(error), "Kernel selection is invalid.")
else:
self.fail()
def test_apply_kernel_1D(self):
"""Check that _apply_kernel catches a non-2D phi."""
def custom(x, y):
return np.array([1, 2])
clf = BaseRVM(kernel=custom, bias_used=False)
x = np.array([[1, 2], [3, 4]])
y = np.array([[5, 6], [7, 8]])
try:
clf._apply_kernel(x, y)
except ValueError as error:
self.assertEqual(
str(error), "Custom kernel function did not return 2D matrix")
else:
self.fail()
def test_apply_kernel_row_mismatch(self):
"""Check that _apply_kernel catches a mismatch between input/output."""
def custom(x, y):
return np.array([[1, 2]])
clf = BaseRVM(kernel=custom, bias_used=False)
x = np.array([[1, 2], [3, 4]])
y = np.array([[5, 6], [7, 8]])
try:
clf._apply_kernel(x, y)
except ValueError as error:
self.assertEqual(
str(error),
"""Custom kernel function did not return matrix with rows"""
""" equal to number of data points.""")
else:
self.fail()
def test_apply_kernel_linear(self):
"""Check linear kernel is applied correctly."""
clf = BaseRVM(kernel='linear', bias_used=False)
x = np.array([[1, 2], [3, 4]])
y = np.array([[5, 6], [7, 8]])
phi = clf._apply_kernel(x, y)
target = np.array([[17, 23], [39, 53]])
np.testing.assert_array_equal(phi, target)
def test_apply_kernel_bias(self):
"""Check the kernel function correctly applies a bias."""
clf = BaseRVM(kernel='linear', bias_used=True)
x = np.array([[1, 2], [3, 4]])
y = np.array([[5, 6], [7, 8]])
phi = clf._apply_kernel(x, y)
target = np.array([[17, 23, 1], [39, 53, 1]])
np.testing.assert_array_equal(phi, target)
def test_apply_kernel_rbf(self):
"""Check RBF kernel is applied correctly."""
clf = BaseRVM(kernel='rbf', bias_used=False, coef1=0.5)
x = np.array([[1, 2], [3, 4]])
y = np.array([[5, 6], [7, 8]])
phi = clf._apply_kernel(x, y)
target = np.array([[1.12535175e-07, 2.31952283e-16],
[1.83156389e-02, 1.12535175e-07]])
np.testing.assert_allclose(phi, target)
def test_apply_kernel_custom(self):
"""Check custom kernels are applied correctly."""
def custom(x, y):
return 2 * x.dot(y.T)
clf = BaseRVM(kernel=custom, bias_used=False)
x = np.array([[1, 2], [3, 4]])
y = np.array([[5, 6], [7, 8]])
phi = clf._apply_kernel(x, y)
target = np.array([[34, 46], [78, 106]])
np.testing.assert_array_equal(phi, target)
def test_apply_kernel_poly(self):
"""Check polynomial kernel is applied correctly."""
clf = BaseRVM(kernel='poly',
bias_used=False,
degree=2,
coef1=1,
coef0=0.5)
x = np.array([[1, 2], [3, 4]])
y = np.array([[5, 6], [7, 8]])
phi = clf._apply_kernel(x, y)
target = np.array([[306.25, 552.25], [1560.25, 2862.25]])
np.testing.assert_allclose(phi, target)
