def test_check_increasing_small_number_of_samples():
x = [0, 1, 2]
y = [1, 1.1, 1.05]
with pytest.warns(None) as record:
is_increasing = check_increasing(x, y)
assert len(record) == 0
assert is_increasing
def test_check_increasing(self):
data = np.abs(np.random.randn(100))
data = data.cumsum()
df = pdml.ModelFrame(np.arange(len(data)), target=data)
result = df.isotonic.check_increasing()
expected = isotonic.check_increasing(np.arange(len(data)), data)
self.assertTrue(result)
self.assertTrue(expected)
data = np.abs(np.random.randn(100))
data = data.cumsum()[-1::-1] # reverse
df = pdml.ModelFrame(np.arange(len(data)), target=data)
result = df.isotonic.check_increasing()
expected = isotonic.check_increasing(np.arange(len(data)), data)
self.assertFalse(result)
self.assertFalse(expected)
def test_check_increasing(self):
data = np.abs(np.random.randn(100))
data = data.cumsum()
df = pdml.ModelFrame(np.arange(len(data)), target=data)
result = df.isotonic.check_increasing()
expected = isotonic.check_increasing(np.arange(len(data)), data)
self.assertTrue(result)
self.assertTrue(expected)
data = np.abs(np.random.randn(100))
data = data.cumsum()[-1::-1] # reverse
df = pdml.ModelFrame(np.arange(len(data)), target=data)
result = df.isotonic.check_increasing()
expected = isotonic.check_increasing(np.arange(len(data)), data)
self.assertFalse(result)
self.assertFalse(expected)
def test_check_increasing_small_number_of_samples():
x = [0, 1, 2]
y = [1, 1.1, 1.05]
with warnings.catch_warnings():
warnings.simplefilter("error", UserWarning)
is_increasing = check_increasing(x, y)
assert is_increasing
def test_check_increasing_small_number_of_samples():
x = [0, 1, 2]
y = [1, 1.1, 1.05]
with pytest.warns(None) as record:
is_increasing = check_increasing(x, y)
assert not [w.message for w in record]
assert is_increasing
def test_check_ci_warn():
x = [0, 1, 2, 3, 4, 5]
y = [0, -1, 2, -3, 4, -5]
# Check that we got increasing=False and CI interval warning
msg = "interval"
with pytest.warns(UserWarning, match=msg):
is_increasing = check_increasing(x, y)
assert not is_increasing
def test_check_increasing_down_extreme():
x = [0, 1, 2, 3, 4, 5]
y = [0, -1, -2, -3, -4, -5]
# Check that we got increasing=False and no warnings
with pytest.warns(None) as record:
is_increasing = check_increasing(x, y)
assert len(record) == 0
assert not is_increasing
def test_check_increasing_down():
x = [0, 1, 2, 3, 4, 5]
y = [0, -1.5, -2.77, -8.99, -8.99, -50]
# Check that we got increasing=False and no warnings
with pytest.warns(None) as record:
is_increasing = check_increasing(x, y)
assert len(record) == 0
assert not is_increasing
def test_check_increasing_up_extreme():
x = [0, 1, 2, 3, 4, 5]
y = [0, 1, 2, 3, 4, 5]
# Check that we got increasing=True and no warnings
with pytest.warns(None) as record:
is_increasing = check_increasing(x, y)
assert len(record) == 0
assert is_increasing
def test_check_increasing_down_extreme():
x = [0, 1, 2, 3, 4, 5]
y = [0, -1, -2, -3, -4, -5]
# Check that we got increasing=False and no warnings
with warnings.catch_warnings():
warnings.simplefilter("error", UserWarning)
is_increasing = check_increasing(x, y)
assert not is_increasing
def test_check_increasing_down():
x = [0, 1, 2, 3, 4, 5]
y = [0, -1.5, -2.77, -8.99, -8.99, -50]
# Check that we got increasing=False and no warnings
with warnings.catch_warnings():
warnings.simplefilter("error", UserWarning)
is_increasing = check_increasing(x, y)
assert not is_increasing
def test_check_increasing_up_extreme():
x = [0, 1, 2, 3, 4, 5]
y = [0, 1, 2, 3, 4, 5]
# Check that we got increasing=True and no warnings
with warnings.catch_warnings():
warnings.simplefilter("error", UserWarning)
is_increasing = check_increasing(x, y)
assert is_increasing
def test_check_increasing_up_extreme():
x = [0, 1, 2, 3, 4, 5]
y = [0, 1, 2, 3, 4, 5]
# Check that we got increasing=True and no warnings
with pytest.warns(None) as record:
is_increasing = check_increasing(x, y)
assert not [w.message for w in record]
assert is_increasing
def check_increasing(self, X, y):
"""it sets self.is_increasing
Args:
X: 2d-array. training instances.
y: 1d-array. labels
"""
dim = X.shape[1]
self.is_increasing = [None] * dim
for d in range(dim):
# here, we use spearman's rank correlation
self.is_increasing[d] = check_increasing(X[:, d], y)
