def test_isotonic_regression_oob_bad_after():
# Set y and x
y = np.array([3, 7, 5, 9, 8, 7, 10])
x = np.arange(len(y))
# Create model and fit
ir = IsotonicRegression(increasing='auto', out_of_bounds="raise")
# Make sure that we throw an error for bad out_of_bounds value in transform
ir.fit(x, y)
ir.out_of_bounds = "xyz"
assert_raises(ValueError, ir.transform, x)
def test_isotonic_regression_oob_bad_after():
# Set y and x
y = np.array([3, 7, 5, 9, 8, 7, 10])
x = np.arange(len(y))
# Create model and fit
ir = IsotonicRegression(increasing='auto', out_of_bounds="raise")
# Make sure that we throw an error for bad out_of_bounds value in transform
ir.fit(x, y)
ir.out_of_bounds = "xyz"
assert_raises(ValueError, ir.transform, x)
def test_isotonic_regression_oob_bad_after():
# Set y and x
y = np.array([3, 7, 5, 9, 8, 7, 10])
x = np.arange(len(y))
# Create model and fit
ir = IsotonicRegression(increasing="auto", out_of_bounds="raise")
# Make sure that we throw an error for bad out_of_bounds value in transform
ir.fit(x, y)
ir.out_of_bounds = "xyz"
msg = "The argument ``out_of_bounds`` must be in 'nan', 'clip', 'raise'; got xyz"
with pytest.raises(ValueError, match=msg):
ir.transform(x)
