def check_simple_operations():
##check multiplication and division with a scalar value
#check if normal division works and it does not change the operands
kl1 = SFK_generator(X_tr).make_a_list(n)
k = kl1[1]
kl2 = kl1 / 10
assert_array_almost_equal(kl2[1], k / 10)
kk = kl1[1]
assert_array_almost_equal(k, kk)
assert_array_almost_equal(kl2[6], kl1[6] / 10)
#check if idiv works correctly
kl1 /= 10
assert_array_almost_equal(kl1[2], kl2[2])
#check if mul work correctly
kl1 = SFK_generator(X_tr).make_a_list(n)
k = kl1[1]
kl2 = kl1 * 10
assert_array_almost_equal(kl2[1], k * 10)
kk = kl1[1]
assert_array_almost_equal(k, kk)
assert_array_almost_equal(kl2[6], kl1[6] * 10)
#check if imul works correctly
kl1 *= 10
assert_array_almost_equal(kl1[2], kl2[2])
return
def check_concatenation():
#check with 2 HPK
kl1 = HPK_generator(X_tr).make_a_list(n)
kl2 = HPK_generator(X_tr).make_a_list(n)
kl3 = kl1 + kl2
assert_array_equal(kl1[1], kl3[1])
assert_array_equal(kl1[7], kl3[7])
assert_array_equal(kl2[1], kl3[n + 1])
assert_array_equal(kl2[4], kl3[n + 4])
#check with HPK and SFK
del kl2, kl3, kl1
kl1 = HPK_generator(X_tr).make_a_list(n)
kl2 = SFK_generator(X_tr).make_a_list(n)
kl3 = kl1 + kl2
assert_array_equal(kl1[1], kl3[1])
assert_array_equal(kl1[7], kl3[7])
assert_array_equal(kl2[1], kl3[n + 1])
assert_array_equal(kl2[4], kl3[n + 4])
#check iadd
del kl2, kl3, kl1
kl1 = SFK_generator(X_tr).make_a_list(n)
kl2 = kernel_list(X_tr)
kl2 += kl1
assert_array_equal(kl1[3], kl2[3])
assert_array_equal(kl1[9], kl2[9])
kl3 = HPK_generator(X_tr).make_a_list(n)
kl2 += kl3
assert_array_equal(kl2[4], kl1[4])
assert_array_equal(kl2[4 + n], kl3[4])
return
def check_generated():
#check if kl can be generated by a generator with tr set
kl = SFK_generator(X_tr).make_a_list(n)
assert_equal(kl.__class__.__name__, 'kernel_list')
kl = HPK_generator(X_tr).make_a_list(n)
assert_equal(kl.__class__.__name__, 'kernel_list')
#check if kl can be generated by a generator with tr and test as inoput
kl = SFK_generator(X_tr, X_te).make_a_list(n)
assert_equal(kl.__class__.__name__, 'kernel_list')
kl = HPK_generator(X_tr, X_te).make_a_list(n)
assert_equal(kl.__class__.__name__, 'kernel_list')
#check if make_a_list(n) perform exactly n kernels in list
assert_equal(len(kl), n)
return
def check_complex_operations():
##check multiplication and division with a scalar value
#check if normal division works and it does not change the operands
v = [i for i in range(1, 11)]
kl1 = HPK_generator(X_tr).make_a_list(n)
k = kl1[3].copy()
kl2 = kl1 / v
assert_array_almost_equal(kl2[9], kl1[9] / v[9])
assert_array_almost_equal(kl2[0], kl1[0] / v[0])
assert_array_almost_equal(kl2[6], kl1[6] / v[6])
assert_array_almost_equal(kl2[3], k / v[3])
#normal div does not affect first operand
assert_array_almost_equal(kl1[3], k)
#check if idiv works correctly
kl1 /= v
assert_array_almost_equal(kl1[2], kl2[2])
#check if mul works correctly
kl1 = SFK_generator(X_tr).make_a_list(n)
k = kl1[1]
kl2 = kl1 * v
assert_array_almost_equal(kl2[1], k * v[1])
kk = kl1[1]
assert_array_almost_equal(k, kk)
assert_array_almost_equal(kl2[6], kl1[6] * v[6])
#check if imul works correctly
kl1 *= v
assert_array_almost_equal(kl1[2], kl2[2])
return
def check_SFKs2():
#check a training list
kl = SFK_generator(X_tr, func='rbf').make_a_list(20)
ka = kl.to_array()
assert_array_almost_equal(kl[0], ka[0])
assert_array_almost_equal(kl[3], ka[3])
#check a test list
#kt = SFK_generator(X_tr,X_te).make_a_list(10)
kt = kernel_list(X_tr, X_te, kl)
kb = kt.to_array()
assert_array_almost_equal(kt[0], kb[0])
assert_array_almost_equal(kt[3], kb[3])
#test with the selected feature list
fl = kl.__getitem__(3, 'feature')
k = rbf_kernel(X_tr[:, fl])
assert_array_almost_equal(k, kl[3])
#test with the function in list
ff = kl.__getitem__(3, 'func')
k = ff(X_tr[:, fl], X_tr[:, fl])
assert_array_equal(k, kl[3])
#check that train and test use the same functions
assert_array_equal(kl.__getitem__(2, 'feature'),
kt.__getitem__(2, 'feature'))
assert_array_equal(kl.__getitem__(7, 'feature'),
kt.__getitem__(7, 'feature'))
kt.T = X_tr #one trick to
assert_array_equal(kt[1], kl[1])
def check_getitem():
#check if getitem return a valid kernel
kl = HPK_generator(X_tr).make_a_list(n)
k = kl[3]
#check if k is an ndarray
assert_equal(type(k), np.ndarray)
#check the shape of the single kernel
assert_equal(k.shape, (X_tr.shape[0], X_tr.shape[0]))
#the same with test and SFK
kl = SFK_generator(X_tr, X_te).make_a_list(n)
k = kl[4]
assert_equal(k.shape, (X_te.shape[0], X_tr.shape[0]))
assert np.min(k) >= 0, 'error: kernel matrix with a negative value'
return
def check_SFKs():
#check if SFK gen works with a default params
kl = SFK_generator(X_tr).make_a_list(n)
#check if the list of feature used has the same length defined as input
kl = SFK_generator(X_tr, n_feature=3).make_a_list(n)
fl = kl.__getitem__(0, 'feature')
assert_equal(len(kl.__getitem__(0, 'feature')), 3)
assert_equal(len(kl.__getitem__(6, 'feature')), 3)
#check if a kernel is consistent with his kernel function and the relative feature vector
kl = SFK_generator(X_tr, n_feature=2, func='rbf').make_a_list(n)
assert_array_almost_equal(
kl[2], rbf_kernel(X_tr[:, kl.__getitem__(2, 'feature')]))
assert_array_almost_equal(
kl[5], rbf_kernel(X_tr[:, kl.__getitem__(5, 'feature')]))
#the same with also a test set
kl = SFK_generator(X_tr, X_te, n_feature=2, func='rbf').make_a_list(n)
assert_array_almost_equal(
kl[3],
rbf_kernel(X_te[:, kl.__getitem__(3, 'feature')],
X_tr[:, kl.__getitem__(3, 'feature')]))
assert_array_almost_equal(
kl[8],
rbf_kernel(X_te[:, kl.__getitem__(8, 'feature')],
X_tr[:, kl.__getitem__(8, 'feature')]))
#check if a kernel function with parameters works well
kl = SFK_generator(X_tr, n_feature=2, func='rbf', params={
'gamma': 1
}).make_a_list(n)
assert_array_almost_equal(
kl[2], rbf_kernel(X_tr[:, kl.__getitem__(2, 'feature')], gamma=1))
assert_array_almost_equal(
kl[5], rbf_kernel(X_tr[:, kl.__getitem__(5, 'feature')], gamma=1))
#check if a callable works well
kl = SFK_generator(X_tr, func=rbf_kernel).make_a_list(n)
assert_array_almost_equal(
kl[2], rbf_kernel(X_tr[:, kl.__getitem__(2, 'feature')]))
#check if a callable with params works well
kl = SFK_generator(X_tr, func=rbf_kernel, params={
'gamma': 2
}).make_a_list(n)
assert_array_almost_equal(
kl[2], rbf_kernel(X_tr[:, kl.__getitem__(2, 'feature')], gamma=2))
return