def test_bitmap_no_collisions():
# Test init for slabs of points in x
left_edge = np.array([0.0, 0.0, 0.0])
right_edge = np.array([1.0, 1.0, 1.0])
periodicity = np.array([0, 0, 0], "bool")
npart = 100
nfiles = 2
file_hash = 12345
order1 = 2
order2 = 2
reg = ParticleBitmap(
left_edge, right_edge, periodicity, file_hash, nfiles, order1, order2
)
# Coarse index
posgen = yield_fake_decomp("sliced", npart, nfiles, left_edge, right_edge)
max_npart = 0
for i, (pos, hsml) in enumerate(posgen):
reg._coarse_index_data_file(pos, hsml, i)
max_npart = max(max_npart, pos.shape[0])
reg._set_coarse_index_data_file(i)
assert_equal(reg.count_total(i), np.sum(reg.masks[:, i]))
mask = reg.masks.sum(axis=1).astype("uint8")
ncoll = np.sum(mask > 1)
nc, nm = reg.find_collisions_coarse()
assert_equal(nc, 0, "%d coarse collisions" % nc)
assert_equal(ncoll, nc, "%d in mask, %d in bitmap" % (ncoll, nc))
# Refined index
sub_mi1 = np.zeros(max_npart, "uint64")
sub_mi2 = np.zeros(max_npart, "uint64")
posgen = yield_fake_decomp("sliced", npart, nfiles, left_edge, right_edge)
coll = None
for i, (pos, hsml) in enumerate(posgen):
nsub_mi, coll = reg._refined_index_data_file(
coll,
pos,
hsml,
mask,
sub_mi1,
sub_mi2,
i,
0,
count_threshold=1,
mask_threshold=2,
)
reg.bitmasks.append(i, coll)
assert_equal(reg.count_refined(i), 0)
nr, nm = reg.find_collisions_refined()
assert_equal(nr, 0, "%d collisions" % nr)
def test_bitmap_collisions():
# Test init for slabs of points in x
left_edge = np.array([0.0, 0.0, 0.0])
right_edge = np.array([1.0, 1.0, 1.0])
periodicity = np.array([0, 0, 0], "bool")
nfiles = 2
file_hash = 12345
order1 = 2
order2 = 2
reg = ParticleBitmap(
left_edge, right_edge, periodicity, file_hash, nfiles, order1, order2
)
# Use same points for all files to force collisions
pos = cell_centers(order1 + order2, left_edge, right_edge)
hsml = None
# Coarse index
max_npart = 0
for i in range(nfiles):
reg._coarse_index_data_file(pos, hsml, i)
max_npart = max(max_npart, pos.shape[0])
reg._set_coarse_index_data_file(i)
assert_equal(reg.count_total(i), np.sum(reg.masks[:, i]))
mask = reg.masks.sum(axis=1).astype("uint8")
ncoll = np.sum(mask > 1)
nc, nm = reg.find_collisions_coarse()
assert_equal(ncoll, nc, "%d in mask, %d in bitmap" % (ncoll, nc))
assert_equal(nc, 2 ** (3 * order1), "%d coarse collisions" % nc)
# Refined index
sub_mi1 = np.zeros(max_npart, "uint64")
sub_mi2 = np.zeros(max_npart, "uint64")
for i in range(nfiles):
nsub_mi, coll = reg._refined_index_data_file(
None,
pos,
hsml,
mask,
sub_mi1,
sub_mi2,
i,
0,
count_threshold=1,
mask_threshold=2,
)
reg.bitmasks.append(i, coll)
assert_equal(reg.count_refined(i), ncoll)
nr, nm = reg.find_collisions_refined()
assert_equal(nr, 2 ** (3 * (order1 + order2)), "%d collisions" % nr)
