Consider the Current Domain on indexing (TileDB-Inc#2156)

tiledb/array.py

@@ -127,6 +127,22 @@ def index_domain_subarray(array, dom, idx: tuple):
         )
 
     subarray = list()
+
+    # In the case that current domain is non-empty, we need to consider it
+    if (
+        hasattr(array.schema, "current_domain")
+        and not array.schema.current_domain.is_empty
+    ):
+        for i in range(array.schema.domain.ndim):
+            subarray.append(
+                (
+                    array.schema.current_domain.ndrectangle.range(i)[0],
+                    array.schema.current_domain.ndrectangle.range(i)[1],
+                )
+            )
+
+        return subarray
+
     for r in range(ndim):
         # extract lower and upper bounds for domain dimension extent
         dim = dom.dim(r)

tiledb/multirange_indexing.py

@@ -195,6 +195,22 @@ def label_ranges_from_selection(selection):
 
 def getitem_ranges(array: Array, idx: Any) -> Sequence[Sequence[Range]]:
     ranges: List[Sequence[Range]] = [()] * array.schema.domain.ndim
+
+    # In the case that current domain is non-empty, we need to consider it
+    if (
+        hasattr(array.schema, "current_domain")
+        and not array.schema.current_domain.is_empty
+    ):
+        for i in range(array.schema.domain.ndim):
+            ranges[i] = [
+                (
+                    array.schema.current_domain.ndrectangle.range(i)[0],
+                    array.schema.current_domain.ndrectangle.range(i)[1],
+                )
+            ]
+
+        return tuple(ranges)
+
     ned = array.nonempty_domain()
     if ned is None:
         ned = [None] * array.schema.domain.ndim

tiledb/tests/test_fixes.py

@@ -1,5 +1,6 @@
 import concurrent
 import concurrent.futures
+import itertools
 import json
 import os
 import subprocess
@@ -382,6 +383,62 @@ def test_sc62594_buffer_resize(self, array_data):
         with tiledb.DenseArray(uri) as T:
             assert_array_equal(array_data, T)
 
+    def test_sc61914_take_current_domain_into_account_indexing(self):
+        uri = self.path("test_sc61914")
+        ctx = tiledb.Ctx()
+        dom = tiledb.Domain(
+            tiledb.Dim(name="d1", domain=(0, 99), tile=20, dtype=np.int64),
+            tiledb.Dim(name="d2", domain=(0, 99), tile=20, dtype=np.int64),
+        )
+        att = tiledb.Attr(name="a", dtype=np.int64)
+        schema = tiledb.ArraySchema(sparse=False, ctx=ctx, domain=dom, attrs=(att,))
+
+        tiledb.Array.create(uri, schema)
+
+        data = np.arange(0, 10000).reshape(100, 100)
+
+        with tiledb.open(uri, "w") as A:
+            A[:] = data
+
+        with tiledb.DenseArray(uri, mode="r") as A:
+            ndrect = tiledb.NDRectangle(ctx, dom)
+            range_one = (10, 20)
+            range_two = (30, 35)
+            ndrect.set_range(0, range_one[0], range_one[1])
+            ndrect.set_range(1, range_two[0], range_two[1])
+
+            current_domain = tiledb.CurrentDomain(ctx)
+            current_domain.set_ndrectangle(ndrect)
+            A.schema.set_current_domain(current_domain)
+
+            # Define the expected results
+            d1_values = range(10, 21)
+            d2_values = range(30, 36)
+            data = [
+                (d1, d2, d1 * 100 + d2)
+                for d1, d2 in itertools.product(d1_values, d2_values)
+            ]
+            expected_df = pd.DataFrame(data, columns=["d1", "d2", "a"])
+
+            expected_array = np.array(
+                [
+                    [1030, 1031, 1032, 1033, 1034, 1035],
+                    [1130, 1131, 1132, 1133, 1134, 1135],
+                    [1230, 1231, 1232, 1233, 1234, 1235],
+                    [1330, 1331, 1332, 1333, 1334, 1335],
+                    [1430, 1431, 1432, 1433, 1434, 1435],
+                    [1530, 1531, 1532, 1533, 1534, 1535],
+                    [1630, 1631, 1632, 1633, 1634, 1635],
+                    [1730, 1731, 1732, 1733, 1734, 1735],
+                    [1830, 1831, 1832, 1833, 1834, 1835],
+                    [1930, 1931, 1932, 1933, 1934, 1935],
+                    [2030, 2031, 2032, 2033, 2034, 2035],
+                ]
+            )
+
+            assert_array_equal(A, expected_array)
+            assert_array_equal(A.df[:], expected_df)
+
 
 class SOMA919Test(DiskTestCase):
     """