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import numpy as np
import pytest
from numpy.testing import assert_array_equal
import tiledb
from tiledb.tests.common import DiskTestCase, assert_captured
class ArraySchemaTest(DiskTestCase):
def test_schema_basic(self):
dom = tiledb.Domain(
tiledb.Dim("d1", (1, 4), 2, dtype="u8"),
tiledb.Dim("d2", (1, 4), 2, dtype="u8"),
)
attr1 = tiledb.Attr("foo", dtype=float)
attr2 = tiledb.Attr("foo", dtype=int)
# test unique attributes
with self.assertRaises(tiledb.TileDBError):
tiledb.ArraySchema(domain=dom, attrs=(attr1, attr2))
# test schema.check
schema = tiledb.ArraySchema(domain=dom, attrs=(attr1,))
# valid schema does not raise
schema.check()
try:
assert xml.etree.ElementTree.fromstring(schema._repr_html_()) is not None
except:
pytest.fail(
f"Could not parse schema._repr_html_(). Saw {schema._repr_html_()}"
)
def test_dense_array_schema(self):
domain = tiledb.Domain(
tiledb.Dim(domain=(1, 8), tile=2), tiledb.Dim(domain=(1, 8), tile=2)
)
a1 = tiledb.Attr("val", dtype="f8")
schema = tiledb.ArraySchema(domain=domain, attrs=(a1,))
assert schema.sparse is False
assert schema.cell_order == "row-major"
assert schema.tile_order == "row-major"
assert schema.domain == domain
assert schema.ndim == 2
assert schema.shape == (8, 8)
assert schema.nattr == 1
assert schema.domain.homogeneous is True
assert hasattr(schema, "version") # don't pin to a specific version
assert schema.attr(0) == a1
assert schema.has_attr("val") is True
assert schema.has_attr("nononoattr") is False
assert schema == tiledb.ArraySchema(domain=domain, attrs=(a1,))
assert schema != tiledb.ArraySchema(domain=domain, attrs=(a1,), sparse=True)
with self.assertRaises(tiledb.TileDBError):
schema.allows_duplicates
# test iteration over attributes
assert list(schema) == [a1]
with self.assertRaisesRegex(
tiledb.TileDBError,
"Cannot set cell order; Hilbert order is only applicable to sparse arrays",
):
tiledb.ArraySchema(
domain=domain, attrs=(a1,), sparse=False, cell_order="hilbert"
)
def test_dense_array_schema_fp_domain_error(self):
dom = tiledb.Domain(tiledb.Dim(domain=(1, 8), tile=2, dtype=np.float64))
att = tiledb.Attr("val", dtype=np.float64)
with self.assertRaises(tiledb.TileDBError):
tiledb.ArraySchema(domain=dom, attrs=(att,))
def test_dense_array_schema_invalid_cell_and_tile_order(self):
dom = tiledb.Domain(tiledb.Dim(domain=(1, 8), tile=2, dtype=np.float64))
att = tiledb.Attr("val", dtype=np.float64)
with self.assertRaises(ValueError):
tiledb.ArraySchema(domain=dom, attrs=(att,), cell_order="invalid")
with self.assertRaises(ValueError):
tiledb.ArraySchema(domain=dom, attrs=(att,), tile_order="invalid")
def test_sparse_schema(self):
# create dimensions
d1 = tiledb.Dim("d1", domain=(1, 1000), tile=10, dtype="uint64")
d2 = tiledb.Dim("d2", domain=(101, 10000), tile=100, dtype="uint64")
# create domain
domain = tiledb.Domain(d1, d2)
# create attributes
a1 = tiledb.Attr("a1", dtype="int32,int32,int32")
a2 = tiledb.Attr(
"a2", filters=tiledb.FilterList([tiledb.GzipFilter(-1)]), dtype="int32"
)
# create sparse array with schema
coords_filters = tiledb.FilterList([tiledb.ZstdFilter(4)])
offsets_filters = tiledb.FilterList([tiledb.LZ4Filter(5)])
validity_filters = tiledb.FilterList([tiledb.GzipFilter(9)])
with pytest.warns(
DeprecationWarning,
match="coords_filters is deprecated; set the FilterList for each dimension",
):
schema = tiledb.ArraySchema(
domain=domain,
attrs=(a1, a2),
capacity=10,
cell_order="col-major",
tile_order="row-major",
allows_duplicates=True,
sparse=True,
coords_filters=coords_filters,
offsets_filters=offsets_filters,
validity_filters=validity_filters,
)
# schema.dump()
# assert_captured(capfd, "Array type: sparse")
assert schema.sparse is True
assert schema.capacity == 10
assert schema.cell_order, "co == major"
assert schema.tile_order, "ro == major"
# <todo>
# assert schema.coords_compressor, ('zstd' == 4)
# assert schema.offsets_compressor, ('lz4' == 5)
assert len(schema.coords_filters) == 0
assert len(schema.offsets_filters) == 1
assert len(schema.validity_filters) == 1
assert schema.domain == domain
assert schema.ndim == 2
assert schema.shape, 1000 == 9900
assert schema.nattr == 2
assert schema.attr(0) == a1
assert schema.attr("a2") == a2
assert schema.allows_duplicates is True
assert schema.domain.dim("d1").filters == coords_filters
assert schema.domain.dim("d2").filters == coords_filters
with pytest.warns(
DeprecationWarning,
match="coords_filters is deprecated; set the FilterList for each dimension",
):
schema2 = tiledb.ArraySchema(
domain=domain,
attrs=(a1, a2),
capacity=10,
cell_order="col-major",
tile_order="row-major",
allows_duplicates=True,
sparse=True,
coords_filters=coords_filters,
offsets_filters=offsets_filters,
validity_filters=validity_filters,
)
assert schema == schema2
# test iteration over attributes
assert list(schema) == [a1, a2]
with self.assertRaisesRegex(
tiledb.TileDBError,
"Cannot set tile order; Hilbert order is not applicable to tiles",
):
tiledb.ArraySchema(
domain=domain, attrs=(a1,), sparse=True, tile_order="hilbert"
)
def test_sparse_schema_filter_list(self, capfd):
# create dimensions
d1 = tiledb.Dim("d1", domain=(1, 1000), tile=10, dtype="uint64")
d2 = tiledb.Dim("d2", domain=(101, 10000), tile=100, dtype="uint64")
# create domain
domain = tiledb.Domain(d1, d2)
# create attributes
a1 = tiledb.Attr("a1", dtype="int32,int32,int32")
filter_list = tiledb.FilterList([tiledb.GzipFilter()])
a2 = tiledb.Attr("a2", filters=filter_list, dtype="float32")
off_filters_pylist = [tiledb.ZstdFilter(level=10)]
off_filters = tiledb.FilterList(filters=off_filters_pylist, chunksize=2048)
coords_filters_pylist = [tiledb.Bzip2Filter(level=5)]
coords_filters = tiledb.FilterList(
filters=coords_filters_pylist, chunksize=4096
)
validity_filters_pylist = [tiledb.GzipFilter(level=9)]
validity_filters = tiledb.FilterList(
filters=validity_filters_pylist, chunksize=1024
)
# create sparse array with schema
with pytest.warns(
DeprecationWarning,
match="coords_filters is deprecated; set the FilterList for each dimension",
):
schema = tiledb.ArraySchema(
domain=domain,
attrs=(a1, a2),
capacity=10,
cell_order="col-major",
tile_order="row-major",
coords_filters=coords_filters,
offsets_filters=off_filters,
validity_filters=validity_filters,
sparse=True,
)
self.assertTrue(schema.sparse)
assert len(schema.coords_filters) == 0
assert len(schema.domain.dim("d1").filters) == 1
assert schema.domain.dim("d1").filters[0] == tiledb.Bzip2Filter(level=5)
assert schema.domain.dim("d2").filters[0] == tiledb.Bzip2Filter(level=5)
assert len(schema.offsets_filters) == 1
assert schema.offsets_filters[0] == tiledb.ZstdFilter(level=10)
assert len(schema.validity_filters) == 1
assert schema.validity_filters[0] == tiledb.GzipFilter(level=9)
schema.dump()
assert_captured(capfd, "Array type: sparse")
# make sure we can construct ArraySchema with python lists of filters
with pytest.warns(
DeprecationWarning,
match="coords_filters is deprecated; set the FilterList for each dimension",
):
schema2 = tiledb.ArraySchema(
domain=domain,
attrs=(a1, a2),
capacity=10,
cell_order="col-major",
tile_order="row-major",
coords_filters=coords_filters_pylist,
offsets_filters=off_filters,
validity_filters=validity_filters,
sparse=True,
)
assert len(schema2.coords_filters) == 0
assert schema.domain.dim("d1").filters == coords_filters_pylist
assert schema.domain.dim("d2").filters == coords_filters_pylist
assert len(schema2.domain.dim("d1").filters) == 1
assert schema2.domain.dim("d1").filters[0] == tiledb.Bzip2Filter(level=5)
assert schema2.domain.dim("d2").filters[0] == tiledb.Bzip2Filter(level=5)
assert len(schema2.offsets_filters) == 1
assert schema2.offsets_filters[0] == tiledb.ZstdFilter(level=10)
assert len(schema2.validity_filters) == 1
assert schema2.validity_filters[0] == tiledb.GzipFilter(level=9)
def test_none_filter_list(self):
with self.assertRaises(ValueError):
tiledb.FilterList([None])
with self.assertRaises(ValueError):
fl = tiledb.FilterList()
fl.append(None)
def test_mixed_string_schema(self):
path = self.path("test_mixed_string_schema")
dims = [
tiledb.Dim(name="dpos", domain=(-100.0, 100.0), tile=10, dtype=np.float64),
tiledb.Dim(name="str_index", tile=None, dtype=np.bytes_),
]
dom = tiledb.Domain(*dims)
attrs = [tiledb.Attr(name="val", dtype=np.float64)]
schema = tiledb.ArraySchema(domain=dom, attrs=attrs, sparse=True)
self.assertTrue(schema.domain.has_dim("str_index"))
self.assertFalse(schema.domain.has_dim("nonono_str_index"))
self.assertTrue(schema.domain.dim("str_index").isvar)
self.assertFalse(schema.domain.dim("dpos").isvar)
self.assertEqual(schema.domain.dim("dpos").dtype, np.double)
self.assertEqual(schema.domain.dim("str_index").dtype, np.bytes_)
self.assertFalse(schema.domain.homogeneous)
tiledb.Array.create(path, schema)
with tiledb.open(path, "r") as arr:
assert_array_equal(arr[:]["str_index"], np.array([], dtype="|S1"))
def test_schema_dump(self, capfd):
dom = tiledb.Domain(
tiledb.Dim(name="x", domain=(0, 99), tile=100, dtype=np.int64)
)
schema = tiledb.ArraySchema(
domain=dom, sparse=True, attrs=[tiledb.Attr(name="a", dtype=str)]
)
schema.dump()
assert_captured(capfd, "Array type: sparse")
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