def test_interp(): times = [0,4,5.] values = [2.,4,6] for int_func in (interp, linear_interp): s = int_func(times, values, bounds_error=False) tval = np.array([-0.1,0.1,3.9,4.1,5.1]) res = lambdify(t, s)(tval) yield assert_array_equal(np.isnan(res), [True, False, False, False, True]) yield assert_array_almost_equal(res[1:-1], [2.05, 3.95, 4.2]) # specifying kind as linear is OK s = linear_interp(times, values, kind='linear')
def test_linear_inter_kind(): s = linear_interp([0, 1], [1, 2], kind='cubic')