def test_compare_sp_with_brute_force(self):
delay = np.random.uniform(0.0, 2.0)
end = spline[-1][0]
start = end - delay
# Very blunt numerical quadrature
N = 100000
factor = (end - start) / N
bf_sp_sq = 0
for t in np.linspace(start, end, N):
anchors = self.spline.get_anchors(t)
bf_sp_sq += (interpolate(t, 0, anchors) *
interpolate(t, 2, anchors) * factor)
bf_sp_sq += (interpolate(t, 1, anchors) *
interpolate(t, 3, anchors) * factor)
sp = self.spline.scalar_product(delay, [0, 1], [2, 3])
self.assertAlmostEqual(sp, bf_sp_sq, 4)
def test_truncation(self):
truncation_time = np.random.uniform(spline[-2][0], spline[-1][0])
truncated_spline = spline.copy()
truncated_spline.truncate(truncation_time)
assert truncated_spline[-1][0] == truncation_time
anchors = (spline[-2], spline[-1])
anchors_trunc = (truncated_spline[-2], truncated_spline[-1])
for t in np.linspace(spline[-2][0], truncation_time, 30):
for j in range(m):
self.assertAlmostEqual(
interpolate(t, j, anchors),
interpolate(t, j, anchors_trunc),
)
self.assertAlmostEqual(
interpolate_diff(t, j, anchors),
interpolate_diff(t, j, anchors_trunc),
)
def test_interpolation(self):
anchors = (spline[0], spline[1])
for t in np.linspace(spline[0][0], spline[1][0], 100):
for j in range(m):
self.assertAlmostEqual(
poly[j](t),
interpolate(t, j, anchors),
)
self.assertAlmostEqual(
diff[j](t),
interpolate_diff(t, j, anchors),
)
def test_anchors(self):
for s in range(len(spline) - 1):
t = spline[s][0]
anchors = (spline[s], spline[s + 1])
for j in range(m):
self.assertAlmostEqual(
spline[s][1][j],
interpolate(t, j, anchors),
)
self.assertAlmostEqual(
spline[s][2][j],
interpolate_diff(t, j, anchors),
)
def test_compare_norm_with_brute_force(self):
delay = np.random.uniform(0.0, 2.0)
end = spline[-1][0]
start = end - delay
# Very blunt numerical integration
N = 100000
factor = (end - start) / N
bf_norm_sq = 0
for t in np.linspace(start, end, N):
anchors = self.spline.get_anchors(t)
for j in range(m):
bf_norm_sq += interpolate(t, j, anchors)**2 * factor
norm = self.spline.norm(delay, np.array(range(m)))
self.assertAlmostEqual(norm, np.sqrt(bf_norm_sq), 4)