def test_check_labels_positive_notok():
y = np.array([1, 1, -1])
cl = _BaseClassifier(print_progress=0, random_seed=1)
assert_raises(AttributeError,
'y array must not contain negative labels.\nFound [-1 1]',
cl._check_target_array,
y)
def test_check_labels_interger_notok():
y = np.array([1., 2.], dtype=np.float64)
cl = _BaseClassifier(print_progress=0, random_seed=1)
assert_raises(AttributeError,
'y must be an integer array.\nFound float64',
cl._check_target_array,
y)
def test_check_labels_not_ok_1():
y = np.array([1, 3, 2])
cl = _BaseClassifier(print_progress=0, random_seed=1)
assert_raises(AttributeError,
'Labels not in {(1, 2), (0, 1)}.\nFound (1, 2, 3)',
cl._check_target_array,
y,
{(0, 1), (1, 2)})
def test_check_labels_positive_notok():
y = np.array([1, 1, -1])
cl = _BaseClassifier(print_progress=0, random_seed=1)
assert_raises(AttributeError,
'y array must not contain negative labels.\nFound [-1 1]',
cl._check_target_array, y)
def test_check_labels_interger_notok():
y = np.array([1., 2.], dtype=np.float64)
cl = _BaseClassifier(print_progress=0, random_seed=1)
assert_raises(AttributeError, 'y must be an integer array.\nFound float64',
cl._check_target_array, y)
def test_check_labels_not_ok_1():
y = np.array([1, 3, 2])
cl = _BaseClassifier(print_progress=0, random_seed=1)
assert_raises(AttributeError,
'Labels not in {(1, 2), (0, 1)}.\nFound (1, 2, 3)',
cl._check_target_array, y, {(0, 1), (1, 2)})
def test_check_labels_ok_2():
y = np.array([1, 2, 2])
cl = _BaseClassifier(print_progress=0, random_seed=1)
cl._check_target_array(y=y, allowed={(1, 2), (0, 1)})
def test_init():
cl = _BaseClassifier(print_progress=0, random_seed=1)
assert hasattr(cl, 'print_progress')
assert hasattr(cl, 'random_seed')
def test_check_labels_ok_2():
y = np.array([1, 2, 2])
cl = _BaseClassifier(print_progress=0, random_seed=1)
cl._check_target_array(y=y, allowed={(1, 2), (0, 1)})
def test_init():
cl = _BaseClassifier(print_progress=0, random_seed=1)
assert hasattr(cl, 'print_progress')
assert hasattr(cl, 'random_seed')