code: def test_read_tile_db_execution(setup):
      ctx = tiledb.Ctx()
  
      tempdir = tempfile.mkdtemp()
      try:
          # create TileDB dense array
          dom = tiledb.Domain(
              tiledb.Dim(
                  ctx=ctx, domain=(1, 100), tile=30, dtype=np.int32
              ),
              tiledb.Dim(
                  ctx=ctx, domain=(0, 90), tile=22, dtype=np.int32
              ),
              tiledb.Dim(
                  ctx=ctx, domain=(0, 9), tile=8, dtype=np.int32
              ),
              ctx=ctx,
          )
          schema = tiledb.ArraySchema(
              ctx=ctx,
              domain=dom,
              sparse=False,
              attrs=[tiledb.Attr(ctx=ctx, dtype=np.float64)],
          )
          tiledb.DenseArray.create(tempdir, schema)
  
          expected = np.random.rand(100, 91, 10)
          with tiledb.DenseArray(uri=tempdir, ctx=ctx, mode="w") as arr:
              arr.write_direct(expected)
  
          a = fromtiledb(tempdir, ctx=ctx)
          result = a.execute().fetch()
  
          np.testing.assert_allclose(expected, result)
      finally:
          shutil.rmtree(tempdir)
  
      tempdir = tempfile.mkdtemp()
      try:
          # create 2-d TileDB sparse array
          dom = tiledb.Domain(
              tiledb.Dim(
                  ctx=ctx, domain=(0, 99), tile=30, dtype=np.int32
              ),
              tiledb.Dim(
                  ctx=ctx, domain=(2, 11), tile=8, dtype=np.int32
              ),
              ctx=ctx,
          )
          schema = tiledb.ArraySchema(
              ctx=ctx,
              domain=dom,
              sparse=True,
              attrs=[tiledb.Attr(ctx=ctx, dtype=np.float64)],
          )
          tiledb.SparseArray.create(tempdir, schema)
  
          expected = sps.rand(100, 10, density=0.01)
          with tiledb.SparseArray(
              uri=tempdir, ctx=ctx, mode="w"
          ) as arr:
              I, J = expected.row, expected.col + 2
              arr[I, J] = {arr.attr(0).name: expected.data}
  
          a = fromtiledb(tempdir, ctx=ctx)
          result = a.execute().fetch()
  
          np.testing.assert_allclose(
              expected.toarray(), result.toarray()
          )
      finally:
          shutil.rmtree(tempdir)
  
      tempdir = tempfile.mkdtemp()
      try:
          # create 1-d TileDB sparse array
          dom = tiledb.Domain(
              tiledb.Dim(
                  ctx=ctx, domain=(1, 100), tile=30, dtype=np.int32
              ),
              ctx=ctx,
          )
          schema = tiledb.ArraySchema(
              ctx=ctx,
              domain=dom,
              sparse=True,
              attrs=[tiledb.Attr(ctx=ctx, dtype=np.float64)],
          )
          tiledb.SparseArray.create(tempdir, schema)
  
          expected = sps.rand(1, 100, density=0.05)
          with tiledb.SparseArray(
              uri=tempdir, ctx=ctx, mode="w"
          ) as arr:
              arr[expected.col + 1] = expected.data
  
          a = fromtiledb(tempdir, ctx=ctx)
          result = a.execute().fetch()
  
          np.testing.assert_allclose(
              expected.toarray()[0], result.toarray()
          )
      finally:
          shutil.rmtree(tempdir)
  
      tempdir = tempfile.mkdtemp()
      try:
          # create TileDB dense array with column-major
          dom = tiledb.Domain(
              tiledb.Dim(
                  ctx=ctx, domain=(1, 100), tile=30, dtype=np.int32
              ),
              tiledb.Dim(
                  ctx=ctx, domain=(0, 90), tile=22, dtype=np.int32
              ),
              tiledb.Dim(
                  ctx=ctx, domain=(0, 9), tile=8, dtype=np.int32
              ),
              ctx=ctx,
          )
          schema = tiledb.ArraySchema(
              ctx=ctx,
              domain=dom,
              sparse=False,
              cell_order="F",
              attrs=[tiledb.Attr(ctx=ctx, dtype=np.float64)],
          )
          tiledb.DenseArray.create(tempdir, schema)
  
          expected = np.asfortranarray(np.random.rand(100, 91, 10))
          with tiledb.DenseArray(uri=tempdir, ctx=ctx, mode="w") as arr:
              arr.write_direct(expected)
  
          a = fromtiledb(tempdir, ctx=ctx)
          result = a.execute().fetch()
  
          np.testing.assert_allclose(expected, result)
          assert result.flags["F_CONTIGUOUS"] is True
          assert result.flags["C_CONTIGUOUS"] is False
      finally:
          shutil.rmtree(tempdir)
  
imports: import tempfile
  import shutil
  import os
  import time
  import numpy
  import pandas
  import pytest
  from ....None import tensor
  from ....None import dataframe
  from ....lib.sparse import SparseNDArray
  from ....tests.core import require_cupy
  from ....utils import lazy_import
  from ...lib import nd_grid
  from ..None import tensor, ones_like, zeros, zeros_like, full, full_like, arange, empty, empty_like, diag, diagflat, eye, linspace, meshgrid, indices, triu, tril, from_dataframe, fromtiledb, fromhdf5, fromzarr
label_desc: Use image node_id 16 for calling a global function with example usage: test_read_tile_db_execution(setup) without return types