def test_corner_case_parallel_octree_1d_few_cells():
x, y, z = [0.131, 0.359], [1.544, 1.809], [-3.6489999, -2.8559999]
pa = get_particle_array(name='fluid', x=x, y=y, z=z, h=1.0)
nbrs = UIntArray()
bf_nbrs = UIntArray()
nps = nnps.OctreeNNPS(dim=3, particles=[pa], radius_scale=0.7,
test_parallel=True)
for i in range(2):
nps.get_nearest_particles(0, 0, i, nbrs)
nps.brute_force_neighbors(0, 0, i, bf_nbrs)
assert sorted(nbrs) == sorted(bf_nbrs), 'Failed for particle: %d' % i
def test_large_number_of_neighbors_octree():
x = numpy.random.random(1 << 14) * 0.1
y = x.copy()
z = x.copy()
h = numpy.ones_like(x)
pa = get_particle_array(name='fluid', x=x, y=y, z=z, h=h)
nps = nnps.OctreeNNPS(dim=3, particles=[pa], cache=False)
nbrs = UIntArray()
nps.get_nearest_particles(0, 0, 0, nbrs)
# print(nbrs.length)
assert nbrs.length == len(x)
def test_octree_works_for_large_domain(self):
# Given
pa = self._make_particles(20)
# We turn on cache so it computes all the neighbors quickly for us.
nps = nnps.OctreeNNPS(dim=3, particles=[pa], cache=True)
nbrs = UIntArray()
direct = UIntArray()
nps.set_context(0, 0)
for i in range(pa.get_number_of_particles()):
nps.get_nearest_particles(0, 0, i, nbrs)
nps.brute_force_neighbors(0, 0, i, direct)
x = nbrs.get_npy_array()
y = direct.get_npy_array()
x.sort(); y.sort()
assert numpy.all(x == y)
def setUp(self):
NNPSTestCase.setUp(self)
self.nps = nnps.OctreeNNPS(
dim=3, particles=self.particles, radius_scale=2.0
)
