def test_imbalance():
X, y = make_multiplexer_dataset(address_bits=2, sample_size=1000,
positive_class_ratio=0.3)
np.bincount(y) == (700, 300), np.bincount(y)
X, y = make_multiplexer_dataset(address_bits=2, sample_size=1000,
positive_class_ratio=0.7)
np.bincount(y) == (300, 700), np.bincount(y)
def test_imbalance():
X, y = make_multiplexer_dataset(address_bits=2,
sample_size=1000,
positive_class_ratio=0.3)
np.bincount(y) == (700, 300), np.bincount(y)
X, y = make_multiplexer_dataset(address_bits=2,
sample_size=1000,
positive_class_ratio=0.7)
np.bincount(y) == (300, 700), np.bincount(y)
def test_defaults():
X, y = make_multiplexer_dataset()
assert X.shape == (100, 6), X.shape
assert X.dtype == np.int
assert y.shape == (100, ), y.shape
assert y.dtype == np.int
def test_defaults():
X, y = make_multiplexer_dataset()
assert X.shape == (100, 6), X.shape
assert X.dtype == np.int
assert y.shape == (100, ), y.shape
assert y.dtype == np.int
def test_class_labels():
X, y = make_multiplexer_dataset(address_bits=2,
sample_size=10,
random_seed=0)
assert np.array_equal(y, np.array([1, 1, 1, 1, 1, 0, 0, 0, 0, 0]))
features = np.array([[0, 1, 0, 1, 1, 0], [0, 1, 1, 1, 1, 0],
[1, 0, 1, 0, 1, 1], [0, 1, 1, 1, 1, 1],
[0, 1, 0, 1, 1, 1], [0, 1, 1, 0, 1, 1],
[1, 1, 1, 1, 1, 0], [0, 1, 0, 0, 0, 0],
[0, 1, 1, 0, 0, 1], [1, 0, 1, 0, 0, 1]])
print(X)
assert np.array_equal(X, features)
def test_class_labels_shuffle():
X, y = make_multiplexer_dataset(address_bits=2, sample_size=10,
random_seed=0, shuffle=True)
print(y)
assert np.array_equal(y, np.array([0, 1, 0, 0, 1, 0, 1, 0, 1, 1]))
features = np.array([[0, 1, 1, 0, 1, 1],
[0, 1, 1, 1, 1, 0],
[1, 0, 1, 0, 0, 1],
[1, 1, 1, 1, 1, 0],
[0, 1, 0, 1, 1, 0],
[0, 1, 1, 0, 0, 1],
[0, 1, 0, 1, 1, 1],
[0, 1, 0, 0, 0, 0],
[1, 0, 1, 0, 1, 1],
[0, 1, 1, 1, 1, 1]])
assert np.array_equal(X, features)
def test_address_bits():
X, y = make_multiplexer_dataset(address_bits=3, sample_size=100)
assert X.shape == (100, 11)
def test_address_bits():
X, y = make_multiplexer_dataset(address_bits=3, sample_size=100)
assert X.shape == (100, 11)
