def test_1waypoints(self):
"The case where there is only one waypoint."
pi = SplineInterpolator([0], [[1, 2, 3]])
assert pi.dof == 3
npt.assert_allclose(pi.get_path_interval(), np.r_[0, 0])
npt.assert_allclose(pi.eval(0), np.r_[1, 2, 3])
npt.assert_allclose(pi.evald(0), np.r_[0, 0, 0])
npt.assert_allclose(pi.eval([0, 0]), [[1, 2, 3], [1, 2, 3]])
npt.assert_allclose(pi.evald([0, 0]), [[0, 0, 0], [0, 0, 0]])
def test_scalar(self, sswp, wp, ss, path_interval):
"A scalar (dof=1) trajectory."
pi = SplineInterpolator(sswp, wp) # 1 + 2s + 3s^2
assert pi.dof == 1
assert pi.eval(ss).shape == (len(ss), )
assert pi.evald(ss).shape == (len(ss), )
assert pi.evaldd(ss).shape == (len(ss), )
assert pi.eval(0).shape == ()
npt.assert_allclose(pi.get_path_interval(), path_interval)
def test_5_dof(self):
pi = SplineInterpolator([0, 1], np.random.rand(2, 5))
# [1 + 2s + 3s^2]
# [-2 + 3s + 4s^2 + 5s^3]
ss = np.linspace(0, 1, 10)
assert pi.dof == 5
assert pi.eval(ss).shape == (10, 5)
assert pi.evald(ss).shape == (10, 5)
assert pi.evaldd(ss).shape == (10, 5)
npt.assert_allclose(pi.get_path_interval(), np.r_[0, 1])
def test_2waypoints(self, xs, ys, yd):
"There is only two waypoints. Linear interpolation is done between them."
pi = SplineInterpolator(xs, ys, bc_type='natural')
npt.assert_allclose(pi.get_path_interval(), xs)
npt.assert_allclose(pi.evald((xs[0] + xs[1]) / 2), yd)
npt.assert_allclose(pi.evaldd(0), np.zeros_like(ys[0]))