hc99's picture
Add files using upload-large-folder tool
2c3c408 verified
import string
import numpy as np
import pytest
from numpy.testing import assert_array_equal
import tiledb
from .common import DiskTestCase, has_pandas, rand_utf8
class QueryConditionTest(DiskTestCase):
def filter_dense(self, data, mask):
if isinstance(mask, np.ndarray):
mask = mask[0]
if isinstance(mask, float):
return data[np.invert(np.isnan(data))]
if isinstance(mask, np.timedelta64):
return data[np.invert(np.isnat(data))]
if isinstance(mask, (str, bytes)):
return data[np.invert(data == mask)]
return data[data != mask]
def create_input_array_UIDSA(self, sparse):
path = self.path("input_array_UIDSA")
dom = tiledb.Domain(
tiledb.Dim(name="d", domain=(1, 10), tile=1, dtype=np.uint32)
)
attrs = [
tiledb.Attr(name="U", dtype=np.uint32),
tiledb.Attr(name="I", dtype=np.int64),
tiledb.Attr(name="D", dtype=np.float64),
tiledb.Attr(name="S", dtype=np.dtype("|S1"), var=False),
tiledb.Attr(name="A", dtype="ascii", var=True),
tiledb.Attr(name="UTF", dtype=np.dtype("U"), var=True),
]
schema = tiledb.ArraySchema(domain=dom, attrs=attrs, sparse=sparse)
tiledb.Array.create(path, schema)
with tiledb.open(path, "w") as arr:
data = {
"U": np.random.randint(1, 10, 10),
"I": np.random.randint(-5, 5, 10),
"D": np.random.rand(10),
"S": np.array(list(string.ascii_lowercase[:10]), dtype="|S1"),
"A": np.array(
list(string.ascii_lowercase[i] * (i + 1) for i in range(10)),
dtype="|S",
),
"UTF": np.array(
["$", "£$", "€ह£$", "한ह£", "£$𐍈"]
+ [rand_utf8(np.random.randint(1, 100)) for _ in range(5)],
dtype="|U0",
),
}
if sparse:
arr[np.arange(1, 11)] = data
else:
arr[:] = data
return path
def setUp(self):
super().setUp()
if not tiledb.libtiledb.version() >= (2, 2, 3):
pytest.skip("Only run QueryCondition test with TileDB>=2.2.3")
@pytest.mark.parametrize("sparse", [True, False])
def test_errors(self, sparse):
uri = self.create_input_array_UIDSA(sparse)
with self.assertRaises(tiledb.TileDBError):
with tiledb.open(uri) as A:
A.query(cond="1.324 < 1")[:]
with self.assertRaises(tiledb.TileDBError):
with tiledb.open(uri) as A:
A.query(cond="foo >= bar")[:]
with self.assertRaises(tiledb.TileDBError):
with tiledb.open(uri) as A:
A.query(cond="'foo' == 'bar'")[:]
with self.assertRaises(tiledb.TileDBError):
with tiledb.open(uri) as A:
A.query(cond="U < 10000000000000000000000.0", attrs=["U"])[:]
with self.assertRaises(tiledb.TileDBError):
with tiledb.open(uri) as A:
A.query(cond="D", attrs=["D"])[:]
with self.assertRaises(tiledb.TileDBError):
with tiledb.open(uri) as A:
A.query(cond="D,", attrs=["D"])[:]
with self.assertRaises(tiledb.TileDBError):
with tiledb.open(uri) as A:
A.query(cond="D > ", attrs=["D"])[:]
def test_qc_dense(self):
path = self.path("test_qc_dense")
dom = tiledb.Domain(
tiledb.Dim(name="d", domain=(1, 10), tile=1, dtype=np.uint8)
)
attrs = [tiledb.Attr(name="a", dtype=np.uint8)]
schema = tiledb.ArraySchema(domain=dom, attrs=attrs, sparse=False)
tiledb.Array.create(path, schema)
with tiledb.open(path) as A:
A.query(cond="a < 5")
def test_unsigned_sparse(self):
with tiledb.open(self.create_input_array_UIDSA(sparse=True)) as A:
A.query(cond="U < 5", attrs=["U"])[:]
result = A.query(cond="U < 5", attrs=["U"])[:]
assert all(result["U"] < 5)
def test_unsigned_dense(self):
with tiledb.open(self.create_input_array_UIDSA(sparse=False)) as A:
mask = A.attr("U").fill
A.query(cond="U < 5", attrs=["U"])[:]
result = A.query(cond="U < 5", attrs=["U"])[:]
assert all(self.filter_dense(result["U"], mask) < 5)
def test_signed_sparse(self):
uri = self.create_input_array_UIDSA(sparse=True)
with tiledb.open(uri) as A:
result = A.query(cond="I < 1", attrs=["I"])[:]
assert all(result["I"] < 1)
result = A.query(cond="I < +1", attrs=["I"])[:]
assert all(result["I"] < +1)
result = A.query(cond="I < ---1", attrs=["I"])[:]
assert all(result["I"] < ---1)
result = A.query(cond="-5 < I < 5", attrs=["I"])[:]
assert all(-5 < result["I"])
assert all(result["I"] < 5)
def test_signed_dense(self):
uri = self.create_input_array_UIDSA(sparse=False)
with tiledb.open(uri) as A:
mask = A.attr("I").fill
result = A.query(cond="I < 1", attrs=["I"])[:]
assert all(self.filter_dense(result["I"], mask) < 1)
result = A.query(cond="I < +1", attrs=["I"])[:]
assert all(self.filter_dense(result["I"], mask) < +1)
result = A.query(cond="I < ---1", attrs=["I"])[:]
assert all(self.filter_dense(result["I"], mask) < ---1)
result = A.query(cond="-5 < I < 5", attrs=["I"])[:]
assert all(-5 < self.filter_dense(result["I"], mask))
assert all(self.filter_dense(result["I"], mask) < 5)
def test_floats_sparse(self):
with tiledb.open(self.create_input_array_UIDSA(sparse=True)) as A:
result = A.query(cond="D > 5.0", attrs=["D"])[:]
assert all(result["D"] > 5.0)
result = A.query(cond="(D > 0.7) & (D < 3.5)", attrs=["D"])[:]
assert all((result["D"] > 0.7) & (result["D"] < 3.5))
result = A.query(cond="0.2 < D < 0.75", attrs=["D", "D"])[:]
assert all(0.2 < result["D"])
assert all(result["D"] < 0.75)
def test_floats_dense(self):
with tiledb.open(self.create_input_array_UIDSA(sparse=False)) as A:
mask = A.attr("D").fill
result = A.query(cond="D > 5.0", attrs=["D"])[:]
assert all(self.filter_dense(result["D"], mask) > 5.0)
result = A.query(cond="(D > 0.7) & (D < 3.5)", attrs=["D"])[:]
assert all(self.filter_dense(result["D"], mask) > 0.7)
assert all(self.filter_dense(result["D"], mask) < 3.5)
result = A.query(cond="0.2 < D < 0.75", attrs=["D", "D"])[:]
assert all(0.2 < self.filter_dense(result["D"], mask))
assert all(self.filter_dense(result["D"], mask) < 0.75)
def test_string_sparse(self):
with tiledb.open(self.create_input_array_UIDSA(sparse=True)) as A:
with self.assertRaises(tiledb.TileDBError) as exc_info:
A.query(cond="S == c", attrs=["S"])[:]
assert (
"right-hand sides must be constant expressions, not variables -- did you mean to quote the right-hand side as a string?"
in str(exc_info.value)
)
result = A.query(cond="S == 'c'", attrs=["S"])[:]
assert len(result["S"]) == 1
assert result["S"][0] == b"c"
result = A.query(cond="A == 'a'", attrs=["A"])[:]
assert len(result["A"]) == 1
assert result["A"][0] == b"a"
if tiledb.libtiledb.version() > (2, 14):
for t in A.query(attrs=["UTF"])[:]["UTF"]:
cond = f"""UTF == '{t}'"""
result = A.query(cond=cond, attrs=["UTF"])[:]
assert result["UTF"] == t
def test_string_dense(self):
with tiledb.open(self.create_input_array_UIDSA(sparse=False)) as A:
with self.assertRaises(tiledb.TileDBError) as exc_info:
A.query(cond="S == ccc", attrs=["S"])[:]
assert (
"right-hand sides must be constant expressions, not variables -- did you mean to quote the right-hand side as a string?"
in str(exc_info.value)
)
result = A.query(cond="S == 'ccc'", attrs=["S"])[:]
assert all(self.filter_dense(result["S"], A.attr("S").fill) == b"c")
result = A.query(cond="A == 'ccc'", attrs=["A"])[:]
assert all(self.filter_dense(result["A"], A.attr("A").fill) == b"ccc")
if tiledb.libtiledb.version() > (2, 14):
for t in A.query(attrs=["UTF"])[:]["UTF"]:
cond = f"""UTF == '{t}'"""
result = A.query(cond=cond, attrs=["UTF"])[:]
assert all(
self.filter_dense(result["UTF"], A.attr("UTF").fill) == t
)
def test_combined_types_sparse(self):
with tiledb.open(self.create_input_array_UIDSA(sparse=True)) as A:
qc = "(I > 0) & ((-3 < D) & (D < 3.0))"
result = A.query(cond=qc, attrs=["I", "D"])[:]
assert all((result["I"] > 0) & ((-3 < result["D"]) & (result["D"] < 3.0)))
qc = "U >= 3 and 0.7 < D"
result = A.query(cond=qc, attrs=["U", "D"])[:]
assert all(result["U"] >= 3) & all(0.7 < result["D"])
qc = "(0.2 < D and D < 0.75) and (-5 < I < 5)"
result = A.query(cond=qc, attrs=["D", "I"])[:]
assert all((0.2 < result["D"]) & (result["D"] < 0.75))
assert all((-5 < result["I"]) & (result["I"] < 5))
qc = "(-5 < I <= -1) and (0.2 < D < 0.75)"
result = A.query(cond=qc, attrs=["D", "I"])[:]
assert all((0.2 < result["D"]) & (result["D"] < 0.75))
assert all((-5 < result["I"]) & (result["I"] <= -1))
qc = "(0.2 < D < 0.75) and (-5 < I < 5)"
result = A.query(cond=qc, attrs=["D", "I"])[:]
assert all((0.2 < result["D"]) & (result["D"] < 0.75))
assert all((-5 < result["I"]) & (result["I"] < 5))
def test_combined_types_dense(self):
with tiledb.open(self.create_input_array_UIDSA(sparse=False)) as A:
mask_U = A.attr("U").fill
mask_I = A.attr("I").fill
mask_D = A.attr("D").fill
qc = "(I > 0) & ((-3 < D) & (D < 3.0))"
result = A.query(cond=qc, attrs=["I", "D"])[:]
res_I = self.filter_dense(result["I"], mask_I)
res_D = self.filter_dense(result["D"], mask_D)
assert all(res_I > 0) & all(-3 < res_D) & all(res_D < 3.0)
qc = "U >= 3 and 0.7 < D"
result = A.query(cond=qc, attrs=["U", "D"])[:]
res_U = self.filter_dense(result["U"], mask_U)
res_D = self.filter_dense(result["D"], mask_D)
assert all(res_U >= 3) & all(0.7 < res_D)
qc = "(0.2 < D and D < 0.75) and (-5 < I < 5)"
result = A.query(cond=qc, attrs=["D", "I"])[:]
res_D = self.filter_dense(result["D"], mask_D)
res_I = self.filter_dense(result["I"], mask_I)
assert all((0.2 < res_D) & (res_D < 0.75))
assert all((-5 < res_I) & (res_I < 5))
qc = "(-5 < I <= -1) and (0.2 < D < 0.75)"
result = A.query(cond=qc, attrs=["D", "I"])[:]
res_D = self.filter_dense(result["D"], mask_D)
res_I = self.filter_dense(result["I"], mask_I)
assert all((0.2 < res_D) & (res_D < 0.75))
assert all((-5 < res_I) & (res_I <= -1))
qc = "(0.2 < D < 0.75) and (-5 < I < 5)"
result = A.query(cond=qc, attrs=["D", "I"])[:]
res_D = self.filter_dense(result["D"], mask_D)
res_I = self.filter_dense(result["I"], mask_I)
assert all((0.2 < res_D) & (res_D < 0.75))
assert all((-5 < res_I) & (res_I < 5))
def test_check_attrs_sparse(self):
with tiledb.open(self.create_input_array_UIDSA(sparse=True)) as A:
result = A.query(cond="U < 0.1", attrs=["U"])[:]
assert all(result["U"] < 0.1)
result = A.query(cond="U < 1.0", attrs=["U"])[:]
assert all(result["U"] < 1.0)
with self.assertRaises(tiledb.TileDBError):
A.query(cond="U < '1'", attrs=["U"])[:]
with self.assertRaises(tiledb.TileDBError):
A.query(cond="U < 'one'", attrs=["U"])[:]
def test_check_attrs_dense(self):
with tiledb.open(self.create_input_array_UIDSA(sparse=False)) as A:
mask = A.attr("U").fill
result = A.query(cond="U < 0.1", attrs=["U"])[:]
assert all(self.filter_dense(result["U"], mask) < 0.1)
result = A.query(cond="U < 1.0", attrs=["U"])[:]
assert all(self.filter_dense(result["U"], mask) < 1.0)
with self.assertRaises(tiledb.TileDBError):
A.query(cond="U < '1'", attrs=["U"])[:]
with self.assertRaises(tiledb.TileDBError):
A.query(cond="U < 'one'", attrs=["U"])[:]
def test_attr_and_val_casting_num(self):
path = self.path("test_attr_and_val_casting_num")
dom = tiledb.Domain(
tiledb.Dim(name="dim", domain=(1, 10), tile=1, dtype=np.uint32)
)
attrs = [
tiledb.Attr(name="64-bit integer", dtype=np.int64),
tiledb.Attr(name="double", dtype=np.float64),
]
schema = tiledb.ArraySchema(domain=dom, attrs=attrs, sparse=True)
tiledb.Array.create(path, schema)
with tiledb.open(path, "w") as arr:
arr[np.arange(1, 11)] = {
"64-bit integer": np.random.randint(-5, 5, 10),
"double": np.random.rand(10),
}
with tiledb.open(path) as arr:
result = arr.query(cond="attr('64-bit integer') <= val(0)")[:]
assert all(result["64-bit integer"] <= 0)
result = arr.query(cond="attr('64-bit integer') <= 0")[:]
assert all(result["64-bit integer"] <= 0)
result = arr.query(cond="double <= 0.5")[:]
assert all(result["double"] <= 0.5)
result = arr.query(cond="attr('double') <= 0.5")[:]
assert all(result["double"] <= 0.5)
result = arr.query(cond="double <= val(0.5)")[:]
assert all(result["double"] <= 0.5)
result = arr.query(cond="attr('double') <= val(0.5)")[:]
assert all(result["double"] <= 0.5)
def test_casting_str(self):
path = self.path("test_attr_and_val_casting_str")
dom = tiledb.Domain(tiledb.Dim(name="dim with spaces", dtype="ascii"))
attrs = [tiledb.Attr(name="attr with spaces", dtype="ascii", var=True)]
schema = tiledb.ArraySchema(domain=dom, attrs=attrs, sparse=True)
tiledb.Array.create(path, schema)
A = np.array(
[
"value with spaces",
"nospaces",
"value with spaces",
"another value",
"",
]
)
with tiledb.open(path, "w") as arr:
arr[["a", "b", "c", "d", "e"]] = {"attr with spaces": A}
with tiledb.open(path) as arr:
qc = "attr('attr with spaces') == 'value with spaces'"
result = arr.query(cond=qc)[:]
assert list(result["dim with spaces"]) == [b"a", b"c"]
with pytest.raises(tiledb.TileDBError) as exc_info:
result = arr.query(cond="dim('attr with spaces') == 'd'")[:]
assert "is not a dimension" in str(exc_info.value)
qc = "attr('attr with spaces') == val('value with spaces')"
result = arr.query(cond=qc)[:]
assert list(result["dim with spaces"]) == [b"a", b"c"]
with pytest.raises(tiledb.TileDBError) as exc_info:
result = arr.query(cond="attr('dim with spaces') == 'd'")[:]
assert "is not an attribute" in str(exc_info.value)
result = arr.query(cond="dim('dim with spaces') == 'd'")[:]
assert list(result["dim with spaces"]) == [b"d"]
@pytest.mark.skipif(
tiledb.libtiledb.version() < (2, 7, 0),
reason="var-length np.bytes_ query condition support introduced in 2.7.0",
)
def test_var_length_str(self):
path = self.path("test_var_length_str")
dom = tiledb.Domain(tiledb.Dim(name="d", domain=(0, 4)))
attrs = [
tiledb.Attr(name="ascii", dtype="ascii", var=True),
tiledb.Attr(name="bytes", dtype=np.bytes_, var=True),
]
schema = tiledb.ArraySchema(domain=dom, attrs=attrs, sparse=True)
tiledb.Array.create(path, schema)
def create_array(func):
return np.array([func[i - 1] * i for i in range(1, 6)], dtype=np.bytes_)
ascii_data = create_array(string.ascii_lowercase)
bytes_data = create_array(string.ascii_uppercase)
with tiledb.open(path, "w") as arr:
arr[np.arange(5)] = {"ascii": ascii_data, "bytes": bytes_data}
with tiledb.open(path, "r") as arr:
for s in ascii_data:
result = arr.query(cond=f"ascii == '{s.decode()}'")[:]
assert result["ascii"][0] == s
for s in bytes_data:
result = arr.query(cond=f"bytes == '{s.decode()}'")[:]
assert result["bytes"][0] == s
@pytest.mark.skipif(
tiledb.libtiledb.version() < (2, 10, 0),
reason="OR query condition operator introduced in libtiledb 2.10",
)
def test_or_sparse(self):
with tiledb.open(self.create_input_array_UIDSA(sparse=True)) as A:
result = A.query(cond="(D < 0.25) | (D > 0.75)", attrs=["D"])[:]
assert all((result["D"] < 0.25) | (result["D"] > 0.75))
result = A.query(cond="(D < 0.25) or (D > 0.75)", attrs=["D"])[:]
assert all((result["D"] < 0.25) | (result["D"] > 0.75))
@pytest.mark.skipif(
tiledb.libtiledb.version() < (2, 10, 0),
reason="OR query condition operator introduced in libtiledb 2.10",
)
def test_or_dense(self):
with tiledb.open(self.create_input_array_UIDSA(sparse=False)) as A:
mask = A.attr("D").fill
result = A.query(cond="(D < 0.25) | (D > 0.75)", attrs=["D"])[:]
res = self.filter_dense(result["D"], mask)
assert all((res < 0.25) | (res > 0.75))
result = A.query(cond="(D < 0.25) or (D > 0.75)", attrs=["D"])[:]
res = self.filter_dense(result["D"], mask)
assert all((res < 0.25) | (res > 0.75))
@pytest.mark.skipif(
tiledb.libtiledb.version() < (2, 10, 0),
reason="OR query condition operator and bool type introduced in libtiledb 2.10",
)
def test_01(self):
path = self.path("test_01")
dom = tiledb.Domain(tiledb.Dim(domain=(1, 10), tile=1, dtype=np.uint32))
attrs = [
tiledb.Attr(name="a", dtype=np.uint8),
tiledb.Attr(name="b", dtype=np.uint8),
tiledb.Attr(name="c", dtype=np.uint8),
]
schema = tiledb.ArraySchema(domain=dom, attrs=attrs, sparse=True)
tiledb.Array.create(path, schema)
with tiledb.open(path, "w") as arr:
arr[np.arange(1, 11)] = {
"a": np.random.randint(0, high=2, size=10),
"b": np.random.randint(0, high=2, size=10),
"c": np.random.randint(0, high=2, size=10),
}
with tiledb.open(path) as A:
result = A.query(cond="a == 1 and b == 1 and c == 1")[:]
assert all(result["a"] & result["b"] & result["c"])
result = A.query(cond="a == 1 and b == 1 or c == 1")[:]
assert all(result["a"] & result["b"] | result["c"])
result = A.query(cond="a == 1 or b == 1 and c == 1")[:]
assert all(result["a"] | result["b"] & result["c"])
result = A.query(cond="a == 1 or b == 1 or c == 1")[:]
assert all(result["a"] | result["b"] | result["c"])
result = A.query(cond="(a == 1 and b == 1) or c == 1")[:]
assert all(result["a"] & result["b"] | result["c"])
result = A.query(cond="a == 1 and (b == 1 or c == 1)")[:]
assert all(result["a"] & (result["b"] | result["c"]))
result = A.query(cond="(a == 1 or b == 1) and c == 1")[:]
assert all((result["a"] | result["b"]) & result["c"])
result = A.query(cond="a == 1 or (b == 1 and c == 1)")[:]
assert all(result["a"] | result["b"] & result["c"])
def test_in_operator_sparse(self):
with tiledb.open(self.create_input_array_UIDSA(sparse=True)) as A:
result = A.query(cond="U in [1, 2, 3]", attrs=["U"])[:]
for val in result["U"]:
assert val in [1, 2, 3]
result = A.query(cond="S in ['a', 'e', 'i', 'o', 'u']", attrs=["S"])[:]
for val in result["S"]:
assert val in [b"a", b"e", b"i", b"o", b"u"]
qc = "S in ['a', 'e', 'i', 'o', 'u'] and U in [5, 6, 7]"
result = A.query(cond=qc)[:]
for val in result["U"]:
assert val in [5, 6, 7]
for val in result["S"]:
assert val in [b"a", b"e", b"i", b"o", b"u"]
result = A.query(cond="U in [8]")[:]
for val in result["U"]:
assert val == 8
result = A.query(cond="S in ['8']")[:]
assert len(result["S"]) == 0
result = A.query(cond="U not in [5, 6, 7]")[:]
for val in result["U"]:
assert val not in [5, 6, 7]
with pytest.raises(tiledb.TileDBError) as exc_info:
A.query(cond="U not in []")[:]
assert "At least one value must be provided to the set membership" in str(
exc_info.value
)
def test_in_operator_dense(self):
with tiledb.open(self.create_input_array_UIDSA(sparse=False)) as A:
U_mask = A.attr("U").fill
S_mask = A.attr("S").fill
result = A.query(cond="U in [1, 2, 3]", attrs=["U"])[:]
for val in self.filter_dense(result["U"], U_mask):
assert val in [1, 2, 3]
result = A.query(cond="S in ['a', 'e', 'i', 'o', 'u']", attrs=["S"])[:]
for val in self.filter_dense(result["S"], S_mask):
assert val in [b"a", b"e", b"i", b"o", b"u"]
qc = "S in ['a', 'e', 'i', 'o', 'u'] and U in [5, 6, 7]"
result = A.query(cond=qc)[:]
for val in self.filter_dense(result["U"], U_mask):
assert val in [5, 6, 7]
for val in self.filter_dense(result["S"], S_mask):
assert val in [b"a", b"e", b"i", b"o", b"u"]
result = A.query(cond="U in [8]")[:]
for val in self.filter_dense(result["U"], U_mask):
assert val == 8
result = A.query(cond="S in ['8']")[:]
assert len(self.filter_dense(result["S"], S_mask)) == 0
result = A.query(cond="U not in [5, 6, 7]")[:]
for val in self.filter_dense(result["U"], U_mask):
assert val not in [5, 6, 7]
with pytest.raises(tiledb.TileDBError) as exc_info:
A.query(cond="U not in []")[:]
assert "At least one value must be provided to the set membership" in str(
exc_info.value
)
@pytest.mark.parametrize(
"expression_and_message",
[
["foo is True", "the `is` operator is not supported"],
["foo is not True", "the `is not` operator is not supported"],
[
"foo &&& bar",
"Could not parse the given QueryCondition statement: foo &&& bar",
],
],
)
@pytest.mark.parametrize("sparse", [True, False])
def test_not_supported_operators(self, expression_and_message, sparse):
with tiledb.open(self.create_input_array_UIDSA(sparse=sparse)) as A:
expression, message = expression_and_message
with self.assertRaisesRegex(tiledb.TileDBError, message):
A.query(cond=expression)[:]
@pytest.mark.skipif(not has_pandas(), reason="pandas>=1.0,<3.0 not installed")
def test_dense_datetime(self):
import pandas as pd
uri = self.path("query-filter-dense-datetime.tdb")
data = pd.DataFrame(
np.random.randint(438923600, 243892360000, 20, dtype=np.int64),
columns=["dates"],
)
tiledb.from_pandas(
uri,
data,
column_types={"dates": "datetime64[ns]"},
)
with tiledb.open(uri) as A:
idx = 5
dt_mask = A.attr("dates").fill
search_date = data["dates"][idx]
result = A.query(cond=f"dates == {search_date}").df[:]
assert all(self.filter_dense(result["dates"], dt_mask) == A[idx]["dates"])
def test_array_with_bool_but_unused(self):
path = self.path("test_array_with_bool_but_unused")
dom = tiledb.Domain(
tiledb.Dim(name="d", domain=(1, 3), tile=1, dtype=np.uint32)
)
attrs = [
tiledb.Attr(name="myint", dtype=int),
tiledb.Attr(name="mystr", dtype=str),
tiledb.Attr(name="mybool", dtype=bool),
]
schema = tiledb.ArraySchema(domain=dom, attrs=attrs, sparse=True)
tiledb.Array.create(path, schema)
data = {
"myint": np.asarray([10, 20, 30]),
"mystr": np.asarray(["apple", "ball", "cat"]),
"mybool": np.asarray([True, False, True]),
}
with tiledb.open(path, "w") as A:
A[np.arange(1, 4)] = data
with tiledb.open(path) as A:
result = A.query(cond="myint > 10", attrs=["myint"])[:]
assert all(result["myint"] > 10)
def test_do_not_return_queried_attr(self):
with tiledb.open(self.create_input_array_UIDSA(sparse=True)) as A:
qc = "U < 3"
i_result = A.query(cond=qc, attrs=["I", "U"])[:]
assert "I" in i_result.keys()
assert "U" in i_result.keys()
assert all(i_result["U"] < 5)
u_result = A.query(cond=qc, attrs=["I"])[:]
assert "I" in u_result.keys()
assert "U" not in u_result.keys()
assert_array_equal(i_result["I"], u_result["I"])
def test_deprecate_attr_cond(self):
with tiledb.open(self.create_input_array_UIDSA(sparse=True)) as A:
qc = "U < 3"
A.query(cond=qc)
A.query(cond=qc).cond
A.subarray(1, cond=qc)
def test_on_dense_dimensions(self):
with tiledb.open(self.create_input_array_UIDSA(sparse=False)) as A:
with pytest.raises(tiledb.TileDBError) as excinfo:
A.query(cond="2 <= d < 6")[:]
assert (
"Cannot apply query condition to dimensions on dense arrays"
) in str(excinfo.value)
def test_on_sparse_dimensions(self):
with tiledb.open(self.create_input_array_UIDSA(sparse=True)) as A:
result = A.query(cond="2 <= d < 6")[:]
assert_array_equal(result["d"], A[2:6]["d"])
def test_overlapping(self):
path = self.path("test_overlapping")
dom = tiledb.Domain(tiledb.Dim(name="dim", domain=(0, 10), dtype=np.uint32))
attrs = [tiledb.Attr(name="data", dtype=np.uint32)]
schema = tiledb.ArraySchema(domain=dom, attrs=attrs, sparse=True)
tiledb.Array.create(path, schema)
with tiledb.open(path, "w") as A:
A[np.arange(11)] = np.arange(11)
with tiledb.open(path, "r") as A:
result = A.query(cond="2 <= dim < 7 and 5 <= dim < 9")[:]
assert_array_equal(result["dim"], A[5:7]["dim"])
result = A.query(cond="2 <= dim < 6 or 5 <= dim < 9")[:]
assert_array_equal(result["dim"], A[2:9]["dim"])
result = A.query(cond="2 <= data < 7 and 5 <= data < 9")[:]
assert_array_equal(result["data"], A[5:7]["data"])
result = A.query(cond="2 <= data < 6 or 5 <= data < 9")[:]
assert_array_equal(result["data"], A[2:9]["data"])
def test_with_whitespace(self):
with tiledb.open(self.create_input_array_UIDSA(sparse=True)) as A:
result = A.query(cond=" d < 6")[:]
assert_array_equal(result["d"], A[:6]["d"])
result = A.query(cond=" ( d < 6) ")[:]
assert_array_equal(result["d"], A[:6]["d"])
result = A.query(cond=" ( \n d \n\t< 6) ")[:]
assert_array_equal(result["d"], A[:6]["d"])
qc = """
U < 5
or
I >= 5
"""
result = A.query(cond=qc)[:]
assert all((result["U"] < 5) | (result["U"] > 5))
qc = """
A == ' a'
"""
result = A.query(cond=qc)[:]
# ensures that ' a' does not match 'a'
assert len(result["A"]) == 0
def test_attribute_with_dot(self):
path = self.path("test_with_dot")
dom = tiledb.Domain(tiledb.Dim(name="dim", domain=(0, 10), dtype=np.uint32))
attrs = [
tiledb.Attr(name="attr.one", dtype=np.uint32),
tiledb.Attr(name="attr.two", dtype=np.uint32),
]
schema = tiledb.ArraySchema(domain=dom, attrs=attrs, sparse=True)
tiledb.Array.create(path, schema)
with tiledb.open(path, "w") as A:
A[np.arange(11)] = {"attr.one": np.arange(11), "attr.two": np.arange(11)}
with tiledb.open(path, "r") as A:
with pytest.raises(tiledb.TileDBError) as exc_info:
A.query(cond="attr.one < 6")[:]
assert (
"TileDBError: Unhandled dot operator in Attribute(value=Name(id='attr', ctx=Load()), attr='one', ctx=Load()) -- if your attribute name has a dot in it, e.g. `orig.ident`, please wrap it with `attr(\"...\")`, e.g. `attr(\"orig.ident\")`"
in str(exc_info.value)
)
with pytest.raises(tiledb.TileDBError) as exc_info:
A.query(cond="attr.two >= 6")[:]
assert (
"TileDBError: Unhandled dot operator in Attribute(value=Name(id='attr', ctx=Load()), attr='two', ctx=Load()) -- if your attribute name has a dot in it, e.g. `orig.ident`, please wrap it with `attr(\"...\")`, e.g. `attr(\"orig.ident\")`"
in str(exc_info.value)
)
# now test with the correct syntax
result = A.query(cond='attr("attr.one") < 6')[:]
assert_array_equal(result["attr.one"], A[:6]["attr.one"])
result = A.query(cond='attr("attr.two") >= 6')[:]
assert_array_equal(result["attr.two"], A[6:]["attr.two"])
@pytest.mark.skipif(not has_pandas(), reason="pandas>=1.0,<3.0 not installed")
def test_do_not_return_attrs(self):
with tiledb.open(self.create_input_array_UIDSA(sparse=True)) as A:
cond = None
assert "D" in A.query(cond=cond, attrs=None)[:]
assert "D" not in A.query(cond=cond, attrs=[])[:]
assert "D" in A.query(cond=cond, attrs=None).df[:]
assert "D" not in A.query(cond=cond, attrs=[]).df[:]
assert "D" in A.query(cond=cond, attrs=None).multi_index[:]
assert "D" not in A.query(cond=cond, attrs=[]).multi_index[:]
cond = "D > 100"
assert "D" in A.query(cond=cond, attrs=None)[:]
assert "D" not in A.query(cond=cond, attrs=[])[:]
assert "D" in A.query(cond=cond, attrs=None).df[:]
assert "D" not in A.query(cond=cond, attrs=[]).df[:]
assert "D" in A.query(cond=cond, attrs=None).multi_index[:]
assert "D" not in A.query(cond=cond, attrs=[]).multi_index[:]
def test_boolean_sparse(self):
path = self.path("test_boolean_sparse")
dom = tiledb.Domain(tiledb.Dim(domain=(1, 10), tile=1, dtype=np.uint32))
attrs = [
tiledb.Attr(name="a", dtype=np.bool_),
tiledb.Attr(name="b", dtype=np.bool_),
tiledb.Attr(name="c", dtype=np.bool_),
]
schema = tiledb.ArraySchema(domain=dom, attrs=attrs, sparse=True)
tiledb.Array.create(path, schema)
with tiledb.open(path, "w") as arr:
arr[np.arange(1, 11)] = {
"a": np.random.randint(0, high=2, size=10),
"b": np.random.randint(0, high=2, size=10),
"c": np.random.randint(0, high=2, size=10),
}
with tiledb.open(path) as A:
result = A.query(cond="a == True")[:]
assert all(result["a"])
result = A.query(cond="a == False")[:]
assert all(~result["a"])
result = A.query(cond="a == True and b == True")[:]
assert all(result["a"])
assert all(result["b"])
result = A.query(cond="a == False and c == True")[:]
assert all(~result["a"])
assert all(result["c"])
def test_boolean_dense(self):
path = self.path("test_boolean_dense")
dom = tiledb.Domain(tiledb.Dim(domain=(1, 10), tile=1, dtype=np.uint32))
attrs = [
tiledb.Attr(name="a", dtype=np.bool_),
tiledb.Attr(name="b", dtype=np.bool_),
tiledb.Attr(name="c", dtype=np.bool_),
]
schema = tiledb.ArraySchema(domain=dom, attrs=attrs, sparse=False)
tiledb.Array.create(path, schema)
with tiledb.open(path, "w") as arr:
arr[:] = {
"a": np.random.randint(0, high=2, size=10),
"b": np.random.randint(0, high=2, size=10),
"c": np.random.randint(0, high=2, size=10),
}
with tiledb.open(path) as A:
mask = A.attr("a").fill
result = A.query(cond="a == True")[:]
assert all(self.filter_dense(result["a"], mask))
result = A.query(cond="a == True and b == True")[:]
assert all(self.filter_dense(result["a"], mask))
assert all(self.filter_dense(result["b"], mask))
def test_qc_enumeration(self):
uri = self.path("test_qc_enumeration")
dom = tiledb.Domain(tiledb.Dim(domain=(1, 8), tile=1))
enum1 = tiledb.Enumeration("enmr1", True, [0, 1, 2])
enum2 = tiledb.Enumeration("enmr2", True, ["a", "bb", "ccc"])
attr1 = tiledb.Attr("attr1", dtype=np.int32, enum_label="enmr1")
attr2 = tiledb.Attr("attr2", dtype=np.int32, enum_label="enmr2")
schema = tiledb.ArraySchema(
domain=dom, attrs=(attr1, attr2), enums=(enum1, enum2)
)
tiledb.Array.create(uri, schema)
data1 = np.random.randint(0, 3, 8)
data2 = np.random.randint(0, 3, 8)
with tiledb.open(uri, "w") as A:
A[:] = {"attr1": data1, "attr2": data2}
with tiledb.open(uri, "r") as A:
mask = A.attr("attr1").fill
result = A.query(cond="attr1 < 2", attrs=["attr1"])[:]
assert all(self.filter_dense(result["attr1"], mask) < 2)
result = A.query(cond="attr1 <= 2", attrs=["attr1"])[:]
assert all(self.filter_dense(result["attr1"], mask) <= 2)
result = A.query(cond="attr1 > 0", attrs=["attr1"])[:]
assert all(self.filter_dense(result["attr1"], mask) > 0)
result = A.query(cond="attr1 != 1", attrs=["attr1"])[:]
assert all(self.filter_dense(result["attr1"], mask) != 1)
mask = A.attr("attr2").fill
result = A.query(cond="attr2 == 'bb'", attrs=["attr2"])[:]
assert all(
self.filter_dense(result["attr2"], mask)
== list(enum2.values()).index("bb")
)
mask = A.attr("attr2").fill
result = A.query(cond="attr2 < 'ccc'", attrs=["attr2"])[:]
assert list(enum2.values()).index("ccc") not in self.filter_dense(
result["attr2"], mask
)
result = A.query(cond="attr2 == 'b'", attrs=["attr2"])[:]
assert all(self.filter_dense(result["attr2"], mask) == [])
result = A.query(cond="attr2 in ['b']", attrs=["attr2"])[:]
assert all(self.filter_dense(result["attr2"], mask) == [])
result = A.query(cond="attr2 not in ['b']", attrs=["attr2"])[:]
assert len(result["attr2"]) == len(data2)
result = A.query(cond="attr2 not in ['b', 'ccc']", attrs=["attr2"])[:]
assert list(enum2.values()).index("ccc") not in self.filter_dense(
result["attr2"], mask
)
result = A.query(
cond="attr1 < 2 and attr2 == 'bb'", attrs=["attr1", "attr2"]
)[:]
assert all(self.filter_dense(result["attr1"], mask) < 2) and all(
self.filter_dense(result["attr2"], mask)
== list(enum2.values()).index("bb")
)
result = A.query(cond="attr1 == 2", attrs=["attr1"])[:]
assert all(self.filter_dense(result["attr1"], mask) == 2)
result = A.query(
cond="attr1 == 0 or attr2 == 'ccc'", attrs=["attr1", "attr2"]
)[:]
assert any(self.filter_dense(result["attr1"], mask) == 0) or any(
self.filter_dense(result["attr2"], mask)
== list(enum2.values()).index("ccc")
)
def test_boolean_insert(self):
path = self.path("test_boolean_insert")
attr = tiledb.Attr("a", dtype=np.bool_, var=False)
dom = tiledb.Domain(tiledb.Dim(domain=(1, 10), tile=1, dtype=np.uint32))
schema = tiledb.ArraySchema(domain=dom, sparse=True, attrs=[attr])
tiledb.Array.create(path, schema)
a = np.array(
list(
[
np.array([True], dtype=np.bool_),
np.array([True], dtype=np.bool_),
np.array([True], dtype=np.bool_),
np.array([True], dtype=np.bool_),
]
),
dtype=object,
)
with tiledb.open(path, "w") as A:
A[range(1, len(a) + 1)] = {"a": a}
with tiledb.open(path, "r") as A:
for k in A[:]["a"]:
assert k == True # noqa: E712
def test_qc_dense_empty(self):
path = self.path("test_qc_dense_empty")
dom = tiledb.Domain(tiledb.Dim(name="d", domain=(1, 1), tile=1, dtype=np.uint8))
attrs = [tiledb.Attr(name="a", dtype=np.uint8)]
schema = tiledb.ArraySchema(domain=dom, attrs=attrs, sparse=False)
tiledb.Array.create(path, schema)
with tiledb.open(path, mode="w") as A:
A[:] = np.arange(1)
with tiledb.open(path) as A:
assert_array_equal(A.query(cond="")[:]["a"], [0])
def test_qc_sparse_empty(self):
path = self.path("test_qc_sparse_empty")
dom = tiledb.Domain(
tiledb.Dim(name="d", domain=(1, 10), tile=1, dtype=np.uint8)
)
attrs = [tiledb.Attr(name="a", dtype=np.uint8)]
schema = tiledb.ArraySchema(domain=dom, attrs=attrs, sparse=True)
tiledb.Array.create(path, schema)
with tiledb.open(path, mode="w") as A:
A[1] = {"a": np.arange(1)}
with tiledb.open(path) as A:
assert_array_equal(A.query(cond="")[:]["a"], [0])
class QueryDeleteTest(DiskTestCase):
def test_basic_sparse(self):
path = self.path("test_basic_sparse")
dom = tiledb.Domain(tiledb.Dim(domain=(1, 10), tile=1, dtype=np.uint32))
attrs = [tiledb.Attr("ints", dtype=np.uint32)]
schema = tiledb.ArraySchema(domain=dom, attrs=attrs, sparse=True)
tiledb.Array.create(path, schema)
data = np.random.randint(1, 10, 10)
qc = "ints < 5"
with tiledb.open(path, "w") as A:
A[np.arange(1, 11)] = data
with pytest.raises(
tiledb.TileDBError,
match="SparseArray must be opened in read or delete mode",
):
A.query(cond=qc).submit()
with tiledb.open(path, "r") as A:
assert_array_equal(data, A[:]["ints"])
with tiledb.open(path, "d") as A:
with pytest.raises(
tiledb.TileDBError,
match="Cannot initialize deletes; One condition is needed",
):
A.query().submit()
A.query(cond=qc).submit()
with tiledb.open(path, "r") as A:
assert all(A[:]["ints"] >= 5)
def test_basic_dense(self):
path = self.path("test_basic_dense")
dom = tiledb.Domain(tiledb.Dim(domain=(1, 10), tile=1))
attrs = [tiledb.Attr("ints", dtype=np.uint8)]
schema = tiledb.ArraySchema(domain=dom, attrs=attrs, sparse=False)
tiledb.Array.create(path, schema)
with tiledb.open(path, "d") as A:
with pytest.raises(
tiledb.TileDBError,
match="DenseArray must be opened in read mode",
):
A.query()
@pytest.mark.parametrize("use_timestamps", [True, False])
def test_with_fragments(self, use_timestamps):
path = self.path("test_with_fragments")
dom = tiledb.Domain(tiledb.Dim(domain=(1, 3), tile=1))
attrs = [tiledb.Attr("ints", dtype=np.uint8)]
schema = tiledb.ArraySchema(domain=dom, attrs=attrs, sparse=True)
tiledb.Array.create(path, schema)
if use_timestamps:
with tiledb.open(path, "w", timestamp=1) as A:
A[1] = 1
with tiledb.open(path, "w", timestamp=2) as A:
A[2] = 2
with tiledb.open(path, "w", timestamp=3) as A:
A[3] = 3
else:
with tiledb.open(path, "w") as A:
A[1] = 1
A[2] = 2
A[3] = 3
with tiledb.open(path, "r") as A:
assert_array_equal([1, 2, 3], A[:]["ints"])
timestamps = [t[0] for t in tiledb.array_fragments(path).timestamp_range]
with tiledb.open(path, "d", timestamp=timestamps[2]) as A:
A.query(cond="ints == 1").submit()
with tiledb.open(path, "r", timestamp=timestamps[0]) as A:
assert_array_equal([1], A[:]["ints"])
with tiledb.open(path, "r", timestamp=timestamps[1]) as A:
assert_array_equal([1, 2], A[:]["ints"])
with tiledb.open(path, "r", timestamp=timestamps[2]) as A:
assert_array_equal([2, 3], A[:]["ints"])
assert len(tiledb.array_fragments(path)) == 3
tiledb.consolidate(path)
tiledb.vacuum(path)
assert len(tiledb.array_fragments(path)) == 1
with tiledb.open(path, "r") as A:
assert A.nonempty_domain() == ((1, 3),)
assert_array_equal([2, 3], A[:]["ints"])
@pytest.mark.parametrize("use_timestamps", [True, False])
def test_purge_deleted_cells(self, use_timestamps):
path = self.path("test_with_fragments")
dom = tiledb.Domain(tiledb.Dim(domain=(1, 3), tile=1))
attrs = [tiledb.Attr("ints", dtype=np.uint8)]
schema = tiledb.ArraySchema(domain=dom, attrs=attrs, sparse=True)
tiledb.Array.create(path, schema)
if use_timestamps:
with tiledb.open(path, "w", timestamp=1) as A:
A[1] = 1
with tiledb.open(path, "w", timestamp=2) as A:
A[2] = 2
with tiledb.open(path, "w", timestamp=3) as A:
A[3] = 3
else:
with tiledb.open(path, "w") as A:
A[1] = 1
A[2] = 2
A[3] = 3
with tiledb.open(path, "r") as A:
assert_array_equal([1, 2, 3], A[:]["ints"])
timestamps = [t[0] for t in tiledb.array_fragments(path).timestamp_range]
with tiledb.open(path, "d", timestamp=timestamps[2]) as A:
A.query(cond="ints == 1").submit()
with tiledb.open(path, "r", timestamp=timestamps[0]) as A:
assert_array_equal([1], A[:]["ints"])
with tiledb.open(path, "r", timestamp=timestamps[1]) as A:
assert_array_equal([1, 2], A[:]["ints"])
with tiledb.open(path, "r", timestamp=timestamps[2]) as A:
assert_array_equal([2, 3], A[:]["ints"])
cfg = tiledb.Config({"sm.consolidation.purge_deleted_cells": "true"})
with tiledb.scope_ctx(cfg):
tiledb.consolidate(path)
tiledb.vacuum(path)
with tiledb.open(path, "r") as A:
assert A.nonempty_domain() == ((2, 3),)
assert_array_equal([2, 3], A[:]["ints"])
def test_delete_with_string_dimension(self):
path = self.path("test_delete_with_string_dimension")
schema = tiledb.ArraySchema(
domain=tiledb.Domain(tiledb.Dim(name="d", dtype="|S0", var=True)),
attrs=[tiledb.Attr(name="a", dtype="uint32")],
sparse=True,
)
tiledb.Array.create(path, schema)
with tiledb.open(path, "w") as A:
A[["a", "b", "c"]] = [10, 20, 30]
with tiledb.open(path, "d") as A:
A.query(cond="a == 20").submit()
with tiledb.open(path, "r") as A:
assert_array_equal(A[:]["d"], [b"a", b"c"])
assert_array_equal(A[:]["a"], [10, 30])
with tiledb.open(path, "d") as A:
A.query(cond="d == 'a'").submit()
with tiledb.open(path, "r") as A:
assert_array_equal(A[:]["d"], [b"c"])
assert_array_equal(A[:]["a"], [30])