def test_information_gain():
np.random.seed(22)
for i in xrange(8):
labels0 = (np.random.randn(20) > .2).astype(int)
labels1 = (np.random.randn(33) > .8).astype(int)
fast = information_gain(labels0, labels1)
slow = slow_information_gain(labels0, labels1)
assert np.abs(fast - slow) < 1.e-8
def test_information_gain():
np.random.seed(22)
for i in range(8):
labels0 = (np.random.randn(20) > .2).astype(int)
labels1 = (np.random.randn(33) > .8).astype(int)
fast = information_gain(labels0, labels1)
slow = slow_information_gain(labels0, labels1)
assert np.abs(fast - slow) < 1.e-8
def test_information_gain_small():
labels1 = np.array([0])
labels0 = np.array([0, 1])
assert information_gain(labels0, labels1) < 0.
def test_information_gain_small():
labels1 = np.array([0])
labels0 = np.array([0, 1])
assert information_gain(labels0, labels1) < 0.
