Fix write from array that is not row or column order (#2542)

When writing to a dense array, if the input numpy array is neither row or column order, cast the array to row order.

apis/python/src/tiledbsoma/_dense_nd_array.py

@@ -265,21 +265,25 @@ def write(
 
         clib_dense_array = self._handle._handle
 
+        # Compute the coordinates for the dense array.
         new_coords: List[Union[int, Slice[int], None]] = []
         for c in coords:
             if isinstance(c, slice) and isinstance(c.stop, int):
                 new_coords.append(slice(c.start, c.stop - 1, c.step))
             else:
                 new_coords.append(c)
 
+        # Convert data to a numpy array.
         dtype = self.schema.field("soma_data").type.to_pandas_dtype()
         input = np.array(values, dtype=dtype)
 
-        order = (
-            clib.ResultOrder.colmajor
-            if input.flags.f_contiguous
-            else clib.ResultOrder.rowmajor
-        )
+        # Set the result order. If neither row nor col major, set to be row major.
+        if input.flags.f_contiguous:
+            order = clib.ResultOrder.colmajor
+        else:
+            if not input.flags.contiguous:
+                input = np.ascontiguousarray(input)
+            order = clib.ResultOrder.rowmajor
         clib_dense_array.reset(result_order=order)
 
         self._set_reader_coords(clib_dense_array, new_coords)

apis/python/tests/test_regression.py

@@ -0,0 +1,35 @@
+"""Testing module for regression tests"""
+
+
+import numpy as np
+import pyarrow as pa
+
+import tiledbsoma as soma
+
+
+def test_nd_dense_non_contiguous_write(tmp_path):
+    """Test regression dected in GitHub Issue #2537"""
+    # Create data.
+    data = (
+        np.arange(np.product(24), dtype=np.uint8)
+        .reshape((4, 3, 2))
+        .transpose((2, 0, 1))
+    )
+    coords = tuple(slice(0, dim_len) for dim_len in data.shape)
+    tensor = pa.Tensor.from_numpy(data)
+
+    # Create array and write data to it.
+    with soma.DenseNDArray.create(
+        tmp_path.as_posix(), type=pa.uint8(), shape=data.shape
+    ) as array:
+        array.write(coords, tensor)
+
+    # Check the data is correct when we read it back.
+    with soma.DenseNDArray.open(tmp_path.as_posix()) as array:
+        result = array.read(coords)
+    np.testing.assert_equal(data, result.to_numpy())
+
+    # Check the data is correct when we read it back.
+    with soma.DenseNDArray.open(tmp_path.as_posix()) as array:
+        result = array.read(coords, result_order="column-major")
+    np.testing.assert_equal(data.transpose(), result.to_numpy())