def test_systematic(self, weights):
u = torch.rand(weights.shape)
pyfilter_inds = systematic(weights, u=u, normalized=True).numpy()
for i in range(weights.shape[0]):
filterpy_inds = filterpy_systematic_resample(weights[i], u[i])
assert (pyfilter_inds[i] == filterpy_inds).all()
def test_SystematicVector(self):
weights = torch.tensor(np.random.normal(size=300))
u = np.random.uniform()
pyfilter_inds = systematic(weights, u=torch.tensor(u))
filterpy_inds = filterpy_systematic_resample(normalize(weights), u)
assert (pyfilter_inds.numpy() == filterpy_inds).all()
def test_SystematicMatrix(self):
weights = torch.tensor(np.random.normal(size=(10000, 300)))
u = np.random.uniform(size=(weights.shape[0], 1))
pyfilter_inds = systematic(weights, u=torch.tensor(u))
for i in range(weights.shape[0]):
filterpy_inds = filterpy_systematic_resample(normalize(weights[i]), u[i])
assert (pyfilter_inds[i].numpy() == filterpy_inds).all()