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')
