def test_smooth_spline_scipy_cv(self):
"""Test the univariate spline using spline (with crossvalidation)"""
sm = smoothing.UnivarSplineCV()
sm.initialize(self.data1, self.data2)
r = sm.predict(self.data1)
self.assertEqual(len(r), 8)
# This is slightly better than the NoCV variation
expected = [
4.1626385843797094, 7.3804099239612029, 8.9667396489152544,
10.384851777100122, 11.316311505414465, 13.994282700490476,
7.5367306411050095, 5.8580352186337672
]
for a, b in zip(expected, r):
self.assertTrue(abs(1.0 - a / b) < 0.1)
