def test_sparsity(self):
topo, geom = mesh.rectilinear([6] * self.ndim)
topo = topo.refined_by(
set(
map(
topo.transforms.index,
itertools.chain(topo[1:3].transforms,
topo[-2:].transforms))))
ns = function.Namespace()
ns.x = geom
ns.tbasis = topo.basis('th-spline',
degree=2,
truncation_tolerance=1e-14)
ns.tnotol = topo.basis('th-spline', degree=2, truncation_tolerance=0)
ns.hbasis = topo.basis('h-spline', degree=2)
tA, tA_tol, hA = topo.sample('gauss', 5).integrate_sparse([
ns.eval_ij('tbasis_i,k tbasis_j,k'),
ns.eval_ij('tnotol_i,k tnotol_j,k'),
ns.eval_ij('hbasis_i,k hbasis_j,k')
])
tA_nnz, tA_tol_nnz, hA_nnz = self.vals[self.ndim]
self.assertEqual(len(sparse.prune(sparse.dedup(tA))), tA_nnz)
self.assertEqual(len(sparse.prune(sparse.dedup(tA_tol))), tA_tol_nnz)
self.assertEqual(len(sparse.prune(sparse.dedup(hA))), hA_nnz)
def test_dedup(self):
for inplace in False, True:
with self.subTest(inplace=inplace), chunksize(self.data.itemsize * 3):
dedup = sparse.dedup(self.data, inplace=inplace)
(self.assertIs if inplace else self.assertIsNot)(dedup, self.data)
self.assertEqual(dedup.tolist(),
[((0,),60), ((1,),40), ((2,),80), ((3,),0), ((4,),30)])
