def testStoreTileDB(self):
ctx = tiledb.Ctx()
tempdir = tempfile.mkdtemp()
try:
t = random.rand(50, 30, chunk_size=13)
t2 = t + 1
saved = totiledb(tempdir, t2)
self.assertEqual(saved.shape, (0, 0))
self.assertIsNone(saved.op.tiledb_config)
self.assertEquals(saved.op.tiledb_uri, tempdir)
with self.assertRaises(tiledb.TileDBError):
tiledb.DenseArray(ctx=ctx, uri=tempdir)
# tiledb array is created in the tile
saved.tiles()
# no error
tiledb.DenseArray(ctx=ctx, uri=tempdir)
self.assertEqual(saved.chunks[0].op.axis_offsets, (0, 0))
self.assertEqual(saved.chunks[1].op.axis_offsets, (0, 13))
self.assertEqual(saved.cix[0, 2].op.axis_offsets, (0, 26))
self.assertEqual(saved.cix[1, 2].op.axis_offsets, (13, 26))
self.assertEqual(saved.cix[3, 2].op.axis_offsets, (39, 26))
with self.assertRaises(ValueError):
t3 = random.rand(30, 50)
totiledb(tempdir, t3, ctx=ctx) # shape incompatible
finally:
shutil.rmtree(tempdir)
def testCheckTileDB(self):
ctx = tiledb.Ctx()
tempdir = tempfile.mkdtemp()
try:
np_a = np.random.rand(2, 3)
tiledb_a = tiledb.DenseArray.from_numpy(ctx=ctx,
uri=tempdir,
array=np_a)
with self.assertRaises(ValueError):
# ndim not match
check_tiledb_array_with_tensor(random.rand(2, 3, 4), tiledb_a)
with self.assertRaises(ValueError):
# shape not matchn
check_tiledb_array_with_tensor(random.rand(2, 4), tiledb_a)
with self.assertRaises(ValueError):
# dtype not match
check_tiledb_array_with_tensor(
random.rand(2, 3, dtype=np.float32), tiledb_a)
# legal
check_tiledb_array_with_tensor(random.rand(2, 3), tiledb_a)
finally:
shutil.rmtree(tempdir)
def testShuffle(self):
with self.assertRaises(TypeError):
shuffle('abc')
x = rand(10, 10, chunk_size=2)
shuffle(x)
self.assertIsInstance(x.op, TensorPermutation)
x = rand(10, 10, chunk_size=2)
shuffle(x, axis=1)
self.assertIsInstance(x.op, TensorPermutation)
self.assertEqual(x.op.axis, 1)
def test_shuffle():
with pytest.raises(TypeError):
shuffle('abc')
x = rand(10, 10, chunk_size=2)
shuffle(x)
assert isinstance(x.op, TensorPermutation)
x = rand(10, 10, chunk_size=2)
shuffle(x, axis=1)
assert isinstance(x.op, TensorPermutation)
assert x.op.axis == 1
def testRandom(self):
arr = rand(2, 3)
self.assertIsNotNone(arr.dtype)
arr = beta(1, 2, chunk_size=2).tiles()
self.assertEqual(arr.shape, ())
self.assertEqual(len(arr.chunks), 1)
self.assertEqual(arr.chunks[0].shape, ())
self.assertEqual(arr.chunks[0].op.dtype, np.dtype('f8'))
arr = beta([1, 2], [3, 4], chunk_size=2).tiles()
self.assertEqual(arr.shape, (2, ))
self.assertEqual(len(arr.chunks), 1)
self.assertEqual(arr.chunks[0].shape, (2, ))
self.assertEqual(arr.chunks[0].op.dtype, np.dtype('f8'))
arr = beta([[2, 3]],
from_ndarray([[4, 6], [5, 2]], chunk_size=2),
chunk_size=1,
size=(3, 2, 2)).tiles()
self.assertEqual(arr.shape, (3, 2, 2))
self.assertEqual(len(arr.chunks), 12)
self.assertEqual(arr.chunks[0].op.dtype, np.dtype('f8'))
def test_random():
arr = rand(2, 3)
assert arr.dtype is not None
arr = tile(beta(1, 2, chunk_size=2))
assert arr.shape == ()
assert len(arr.chunks) == 1
assert arr.chunks[0].shape == ()
assert arr.chunks[0].op.dtype == np.dtype('f8')
arr = tile(beta([1, 2], [3, 4], chunk_size=2))
assert arr.shape == (2, )
assert len(arr.chunks) == 1
assert arr.chunks[0].shape == (2, )
assert arr.chunks[0].op.dtype == np.dtype('f8')
arr = tile(
beta([[2, 3]],
from_ndarray([[4, 6], [5, 2]], chunk_size=2),
chunk_size=1,
size=(3, 2, 2)))
assert arr.shape == (3, 2, 2)
assert len(arr.chunks) == 12
assert arr.chunks[0].op.dtype == np.dtype('f8')
def test_get_tile_db_schema():
ctx = tiledb.Ctx()
nsplits = ((1, 2), (3, 1), (2, 2, 1))
a = random.rand(3, 4, 5, dtype=np.float64, chunk_size=nsplits)
schema = get_tiledb_schema_from_tensor(a, ctx, nsplits)
assert schema.ndim == 3
assert schema.shape == (3, 4, 5)
assert [schema.domain.dim(i).tile for i in range(a.ndim)] == [2, 3, 2]
assert schema.attr(0).dtype == a.dtype
def testGetTileDBSchema(self):
ctx = tiledb.Ctx()
nsplits = ((1, 2), (3, 1), (2, 2, 1))
a = random.rand(3, 4, 5, dtype=np.float64, chunk_size=nsplits)
schema = get_tiledb_schema_from_tensor(a, ctx, nsplits)
self.assertEqual(schema.ndim, 3)
self.assertEqual(schema.shape, (3, 4, 5))
self.assertEqual([schema.domain.dim(i).tile for i in range(a.ndim)],
[2, 3, 2])
self.assertEqual(schema.attr(0).dtype, a.dtype)
def test_store_tile_db():
ctx = tiledb.Ctx()
tempdir = tempfile.mkdtemp()
try:
t = random.rand(50, 30, chunk_size=13)
t2 = t + 1
saved = totiledb(tempdir, t2)
assert saved.shape == (0, 0)
assert saved.op.tiledb_config is None
assert saved.op.tiledb_uri == tempdir
with pytest.raises(tiledb.TileDBError):
tiledb.DenseArray(ctx=ctx, uri=tempdir)
# tiledb array is created in the tile
saved = tile(saved)
# no error
tiledb.DenseArray(ctx=ctx, uri=tempdir)
# TileDB consolidation
assert len(saved.chunks) == 1
assert saved.chunks[0].inputs[0].op.axis_offsets == (0, 0)
assert saved.chunks[0].inputs[1].op.axis_offsets == (0, 13)
assert saved.chunks[0].inputs[2].op.axis_offsets == (0, 26
) # input (0, 2)
assert saved.chunks[0].inputs[5].op.axis_offsets == (13, 26
) # input (1, 2)
assert saved.chunks[0].inputs[11].op.axis_offsets == (39, 26
) # input (3, 2)
with pytest.raises(ValueError):
t3 = random.rand(30, 50)
totiledb(tempdir, t3, ctx=ctx) # shape incompatible
finally:
shutil.rmtree(tempdir)
def testPermutation(self):
x = permutation(10)
self.assertEqual(x.shape, (10, ))
self.assertIsInstance(x.op, TensorPermutation)
x = x.tiles()
self.assertEqual(len(x.chunks), 1)
self.assertIsInstance(x.chunks[0].op, TensorPermutation)
arr = from_ndarray([1, 4, 9, 12, 15], chunk_size=2)
x = permutation(arr)
self.assertEqual(x.shape, (5, ))
self.assertIsInstance(x.op, TensorPermutation)
x = x.tiles()
arr = get_tiled(arr)
self.assertEqual(len(x.chunks), 3)
self.assertTrue(np.isnan(x.chunks[0].shape[0]))
self.assertIs(x.chunks[0].inputs[0].inputs[0].inputs[0],
arr.chunks[0].data)
arr = rand(3, 3, chunk_size=2)
x = permutation(arr)
self.assertEqual(x.shape, (3, 3))
self.assertIsInstance(x.op, TensorPermutation)
x = x.tiles()
arr = get_tiled(arr)
self.assertEqual(len(x.chunks), 4)
self.assertTrue(np.isnan(x.chunks[0].shape[0]))
self.assertEqual(x.chunks[0].shape[1], 2)
self.assertIs(x.cix[0, 0].inputs[0].inputs[0].inputs[0],
arr.cix[0, 0].data)
self.assertIs(x.cix[0, 0].inputs[0].inputs[1].inputs[0],
arr.cix[1, 0].data)
self.assertEqual(x.cix[0, 0].op.seed, x.cix[0, 1].op.seed)
self.assertEqual(x.cix[0, 0].inputs[0].inputs[0].inputs[0].op.seed,
x.cix[1, 0].inputs[0].inputs[0].inputs[0].op.seed)
with self.assertRaises(np.AxisError):
self.assertRaises(permutation('abc'))
def test_permutation():
x = permutation(10)
assert x.shape == (10, )
assert isinstance(x.op, TensorPermutation)
x = tile(x)
assert len(x.chunks) == 1
assert isinstance(x.chunks[0].op, TensorPermutation)
arr = from_ndarray([1, 4, 9, 12, 15], chunk_size=2)
x = permutation(arr)
assert x.shape == (5, )
assert isinstance(x.op, TensorPermutation)
x = tile(x)
arr = tile(arr)
assert len(x.chunks) == 3
assert np.isnan(x.chunks[0].shape[0])
assert x.chunks[0].inputs[0].inputs[0].inputs[0].key == arr.chunks[
0].data.key
arr = rand(3, 3, chunk_size=2)
x = permutation(arr)
assert x.shape == (3, 3)
assert isinstance(x.op, TensorPermutation)
x = tile(x)
arr = tile(arr)
assert len(x.chunks) == 4
assert np.isnan(x.chunks[0].shape[0])
assert x.chunks[0].shape[1] == 2
assert x.cix[0, 0].op.seed == x.cix[0, 1].op.seed
assert x.cix[0, 0].inputs[0].inputs[0].inputs[0].op.seed == \
x.cix[1, 0].inputs[0].inputs[0].inputs[0].op.seed
with pytest.raises(np.AxisError):
pytest.raises(permutation('abc'))
def testUnexpectedKey(self):
with self.assertRaises(ValueError):
rand(10, 10, chunks=5)
with self.assertRaises(ValueError):
randn(10, 10, chunks=5)
def test_unexpected_key():
with pytest.raises(ValueError):
rand(10, 10, chunks=5)
with pytest.raises(ValueError):
randn(10, 10, chunks=5)
