def test_compressed_morton_code():
cmc = lambda coord: compressed_morton_code(coord, grid_size=(3, 3, 3))
assert cmc((0, 0, 0)) == 0b000000
assert cmc((1, 0, 0)) == 0b000001
assert cmc((2, 0, 0)) == 0b001000
try:
cmc((3, 0, 0))
assert False
except ValueError:
pass
assert cmc((2, 2, 0)) == 0b011000
assert cmc((2, 2, 1)) == 0b011100
cmc = lambda coord: compressed_morton_code(coord, grid_size=(2, 3, 1))
assert cmc((0, 0, 0)) == 0b000000
assert cmc((1, 0, 0)) == 0b000001
try:
cmc((0, 0, 7))
assert False
except ValueError:
pass
assert cmc((1, 2, 0)) == 0b000101
assert np.array_equal(cmc([(0, 0, 0), (1, 2, 0)]), [0b000000, 0b000101])
cmc = lambda coord: compressed_morton_code(coord, grid_size=(4, 4, 1))
assert cmc((3, 3, 0)) == 0b1111
cmc = lambda coord: compressed_morton_code(coord, grid_size=(8, 8, 2))
assert cmc((5, 5, 0)) == 0b1100011
def test_sharded_image_bits(scale):
dataset_size = Vec(*scale["size"])
chunk_size = Vec(*scale["chunk_sizes"][0])
spec = create_sharded_image_info(dataset_size=dataset_size,
chunk_size=chunk_size,
encoding=scale["encoding"],
dtype=np.uint8)
shape = image_shard_shape_from_spec(spec, dataset_size, chunk_size)
shape = lib.min2(shape, dataset_size)
dataset_bbox = Bbox.from_vec(dataset_size)
gpts = list(gridpoints(dataset_bbox, dataset_bbox, chunk_size))
grid_size = np.ceil(dataset_size / chunk_size).astype(np.int64)
spec = ShardingSpecification.from_dict(spec)
reader = ShardReader(None, None, spec)
morton_codes = compressed_morton_code(gpts, grid_size)
min_num_shards = prod(dataset_size / shape)
max_num_shards = prod(np.ceil(dataset_size / shape))
assert 0 < min_num_shards <= 2**spec.shard_bits
assert 0 < max_num_shards <= 2**spec.shard_bits
real_num_shards = len(set(map(reader.get_filename, morton_codes)))
assert min_num_shards <= real_num_shards <= max_num_shards
def test_compressed_morton_code():
cmc = lambda coord: compressed_morton_code(coord, grid_size=(3, 3, 3))
assert cmc((0, 0, 0)) == 0b000000
assert cmc((1, 0, 0)) == 0b000001
assert cmc((2, 0, 0)) == 0b001000
assert cmc((3, 0, 0)) == 0b001001
assert cmc((2, 2, 0)) == 0b011000
assert cmc((2, 2, 1)) == 0b011100
cmc = lambda coord: compressed_morton_code(coord, grid_size=(2, 3, 1))
assert cmc((0, 0, 0)) == 0b000000
assert cmc((1, 0, 0)) == 0b000001
assert cmc((0, 0, 7)) == 0b000100
assert cmc((2, 3, 1)) == 0b011110
def test_compressed_morton_code():
cmc = lambda coord: compressed_morton_code(coord, grid_size=(3, 3, 3))
assert cmc((0, 0, 0)) == 0b000000
assert cmc((1, 0, 0)) == 0b000001
assert cmc((2, 0, 0)) == 0b001000
assert cmc((3, 0, 0)) == 0b001001
assert cmc((2, 2, 0)) == 0b011000
assert cmc((2, 2, 1)) == 0b011100
cmc = lambda coord: compressed_morton_code(coord, grid_size=(2, 3, 1))
assert cmc((0, 0, 0)) == 0b000000
assert cmc((1, 0, 0)) == 0b000001
assert cmc((0, 0, 7)) == 0b000100
assert cmc((2, 3, 1)) == 0b011110
assert np.array_equal(cmc([(0, 0, 0), (1, 0, 1)]), [0b000000, 0b000101])
def test_image_sharding_hash():
spec = ShardingSpecification(
type="neuroglancer_uint64_sharded_v1",
data_encoding="gzip",
hash="identity",
minishard_bits=6,
minishard_index_encoding="gzip",
preshift_bits=9,
shard_bits=16,
)
point = Vec(144689, 52487, 2829)
volume_size = Vec(*[248832, 134144, 7063])
chunk_size = Vec(*[128, 128, 16])
grid_size = np.ceil(volume_size / chunk_size).astype(np.uint32)
gridpt = np.ceil(point / chunk_size).astype(np.int32)
code = compressed_morton_code(gridpt, grid_size)
loc = spec.compute_shard_location(code)
assert loc.shard_number == '458d'