[python] Fix some dense+2.27 failing test cases

apis/python/src/tiledbsoma/_dense_nd_array.py

@@ -101,9 +101,25 @@
 
         index_column_schema = []
         index_column_data = {}
+
         for dim_idx, dim_shape in enumerate(shape):
             dim_name = f"soma_dim_{dim_idx}"
+
             pa_field = pa.field(dim_name, pa.int64())
+            index_column_schema.append(pa_field)
+
+            # Here is our Arrow data API for communicating schema info between
+            # Python/R and C++ libtiledbsoma:
+            #
+            # [0] core max domain lo
+            # [1] core max domain hi
+            # [2] core extent parameter
+            # If present, these next two signal to use the current-domain feature:
+            # [3] core current domain lo
+            # [4] core current domain hi
+
+            if dim_shape is None:
+                raise ValueError("DenseNDArray shape slots must be numeric")
 
             if NEW_SHAPE_FEATURE_FLAG_ENABLED and DENSE_ARRAYS_CAN_HAVE_CURRENT_DOMAIN:
                 dim_capacity, dim_extent = cls._dim_capacity_and_extent(
@@ -117,11 +133,6 @@
 
                 if dim_shape == 0:
                     raise ValueError("DenseNDArray shape slots must be at least 1")
-                if dim_shape is None:
-                    # Core current-domain semantics are (lo, hi) with both
-                    # inclusive, with lo <= hi. This means smallest is (0, 0)
-                    # which is shape 1, not 0.
-                    dim_shape = 1
 
                 index_column_data[pa_field.name] = [
                     0,
@@ -138,8 +149,7 @@
                     TileDBCreateOptions.from_platform_config(platform_config),
                 )
 
-            index_column_data[pa_field.name] = [0, dim_capacity - 1, dim_extent]
-            index_column_schema.append(pa_field)
+                index_column_data[pa_field.name] = [0, dim_capacity - 1, dim_extent]
 
         index_column_info = pa.RecordBatch.from_pydict(
             index_column_data, schema=pa.schema(index_column_schema)
@@ -349,16 +359,25 @@
         dim_shape: Optional[int],
         create_options: TileDBCreateOptions,
     ) -> Tuple[int, int]:
-        """Given a user-specified shape along a particular dimension, returns a tuple of
-        the TileDB capacity and extent for that dimension, suitable for schema creation.
-        The user-specified shape cannot be ``None`` for :class:`DenseNDArray`.
+        """Given a user-specified shape (maybe ``None``) along a particular dimension,
+        returns a tuple of the TileDB capacity and extent for that dimension, suitable
+        for schema creation. If the user-specified shape is None, the largest possible
+        int64 is returned for the capacity -- which is particularly suitable for
+        maxdomain.
         """
-        if dim_shape is None or dim_shape <= 0:
-            raise ValueError(
-                "SOMADenseNDArray shape must be a non-zero-length tuple of positive ints"
-            )
-
-        dim_capacity = dim_shape
-        dim_extent = min(dim_shape, create_options.dim_tile(dim_name, 2048))
+        if dim_shape is None:
+            dim_capacity = 2**63 - 1
+            dim_extent = min(dim_capacity, create_options.dim_tile(dim_name, 2048))
+            # For core: "domain max expanded to multiple of tile extent exceeds max value
+            # representable by domain type. Reduce domain max by 1 tile extent to allow for
+            # expansion."
+            dim_capacity -= dim_extent
+        else:
+            if dim_shape <= 0:
+                raise ValueError(
+                    "SOMASparseNDArray shape must be a non-zero-length tuple of positive ints or Nones"
+                )
+            dim_capacity = dim_shape
+            dim_extent = min(dim_shape, create_options.dim_tile(dim_name, 2048))
 
         return (dim_capacity, dim_extent)

apis/python/src/tiledbsoma/_sparse_nd_array.py

@@ -150,7 +150,6 @@ def create(
             dim_name = f"soma_dim_{dim_idx}"
 
             pa_field = pa.field(dim_name, pa.int64())
-
             index_column_schema.append(pa_field)
 
             # Here is our Arrow data API for communicating schema info between
@@ -504,7 +503,8 @@ def _dim_capacity_and_extent(
         """Given a user-specified shape (maybe ``None``) along a particular dimension,
         returns a tuple of the TileDB capacity and extent for that dimension, suitable
         for schema creation. If the user-specified shape is None, the largest possible
-        int64 is returned for the capacity.
+        int64 is returned for the capacity -- which is particularly suitable for
+        maxdomain.
         """
         if dim_shape is None:
             dim_capacity = 2**63 - 1

apis/python/src/tiledbsoma/io/ingest.py

@@ -64,7 +64,10 @@
     NotCreateableError,
     SOMAError,
 )
-from .._flags import NEW_SHAPE_FEATURE_FLAG_ENABLED
+from .._flags import (
+    DENSE_ARRAYS_CAN_HAVE_CURRENT_DOMAIN,
+    NEW_SHAPE_FEATURE_FLAG_ENABLED,
+)
 from .._soma_array import SOMAArray
 from .._soma_object import AnySOMAObject, SOMAObject
 from .._tdb_handles import RawHandle
@@ -1322,7 +1325,7 @@
             # in the case when multiple H5ADs/AnnDatas are being
             # ingested to an experiment which doesn't pre-exist.
             shape = (axis_0_mapping.get_shape(), axis_1_mapping.get_shape())
-        elif cls.is_sparse:
+        elif cls.is_sparse or DENSE_ARRAYS_CAN_HAVE_CURRENT_DOMAIN:
             shape = tuple(None for _ in matrix.shape)
         else:
             shape = matrix.shape
@@ -1909,7 +1912,7 @@
         else:
             tensor = pa.Tensor.from_numpy(chunk.toarray())
         if matrix.ndim == 2:
-            soma_ndarray.write((slice(i, i2), slice(None)), tensor)
+            soma_ndarray.write((slice(i, i2), slice(0, ncol)), tensor)
         else:
             soma_ndarray.write((slice(i, i2),), tensor)
 

apis/python/tests/test_io.py

@@ -45,7 +45,7 @@ def src_matrix(request):
     ],
     indirect=True,
 )
-def test_io_create_from_matrix_Dense_nd_array(tmp_path, tdb_create_options, src_matrix):
+def test_io_create_from_matrix_dense_nd_array(tmp_path, tdb_create_options, src_matrix):
     """
     Test soma.io.from_matrix to a DenseNDArray.
 
@@ -94,7 +94,7 @@ def test_io_create_from_matrix_Dense_nd_array(tmp_path, tdb_create_options, src_
     ],
     indirect=True,
 )
-def test_io_create_from_matrix_Sparse_nd_array(
+def test_io_create_from_matrix_sparse_nd_array(
     tmp_path, tdb_create_options, src_matrix
 ):
     """

apis/python/tests/test_shape.py

@@ -205,7 +205,12 @@ def test_dense_nd_array_basics(tmp_path):
 
     with tiledbsoma.DenseNDArray.open(uri) as dnda:
         assert dnda.shape == (100, 200)
-        assert dnda.maxshape == (100, 200)
+        if tiledbsoma._flags.DENSE_ARRAYS_CAN_HAVE_CURRENT_DOMAIN:
+            assert len(dnda.maxshape)
+            assert dnda.maxshape[0] > 2**62
+            assert dnda.maxshape[1] > 2**62
+        else:
+            assert dnda.maxshape == (100, 200)
 
         assert dnda.non_empty_domain() == ((0, 0), (0, 0))
 

apis/r/R/SOMADenseNDArray.R

@@ -35,7 +35,7 @@ SOMADenseNDArray <- R6::R6Class(
     read_arrow_table = function(
       coords = NULL,
       result_order = "auto",
-      log_level = "warn"
+      log_level = "auto"
     ) {
       private$check_open_for_read()