iterating on R dense

apis/python/src/tiledbsoma/_dense_nd_array.py

@@ -263,7 +263,16 @@ def read(
             timestamp=handle.timestamp and (0, handle.timestamp),
         )
 
-        # XXX comment this, and make it conditional on core 2.27 or more, and, new-shape feature-flag enabled
+        # Scenario to avoid:
+        # * Query dense array with coords not provided
+        # * When coords not provided, core uses the core domain
+        # For old shape:
+        # * Core current domain did not exist
+        # * Core max domain may be small; .shape returns this
+        # For new shape (core 2.27 and tiledbsoma 1.15):
+        # * Core current domain exists and will be small; .shape returns this
+        # * Core max domain will be huge
+        # In either case, applying these coords is the right thing to do
         if coords == ():
             coords = tuple(slice(0, e - 1) for e in data_shape)
 

apis/python/tests/test_dense_nd_array.py

@@ -9,6 +9,7 @@
 import pytest
 
 import tiledbsoma as soma
+import tiledbsoma.pytiledbsoma as clib
 from tiledbsoma.options import SOMATileDBContext
 
 from . import NDARRAY_ARROW_TYPES_NOT_SUPPORTED, NDARRAY_ARROW_TYPES_SUPPORTED
@@ -180,8 +181,13 @@ def test_dense_nd_array_requires_shape(tmp_path, shape_is_numeric):
         with soma.DenseNDArray.open(uri) as dnda:
             assert dnda.shape == (2, 3)
     else:
-        with pytest.raises(ValueError):
-            soma.DenseNDArray.create(uri, type=pa.float32(), shape=(None, None)).close()
+        soma.DenseNDArray.create(uri, type=pa.float32(), shape=(None, None)).close()
+        with soma.DenseNDArray.open(uri) as dnda:
+            if (
+                soma._flags.NEW_SHAPE_FEATURE_FLAG_ENABLED
+                and clib.embedded_version_triple() >= (2, 27, 0)
+            ):
+                assert dnda.shape == (1, 1)
 
 
 def test_dense_nd_array_ned_write(tmp_path):

apis/r/R/SOMADataFrame.R

@@ -145,6 +145,7 @@ SOMADataFrame <- R6::R6Class(
         uri = self$uri,
         naap = naap,
         nasp = nasp,
+        coords_list = list(), # only used for SOMADenseNDArray
         ctxxp = private$.soma_context,
         arraytype = "SOMADataFrame",
         config = NULL,

apis/r/R/SOMADenseNDArray.R

@@ -149,9 +149,9 @@ SOMADenseNDArray <- R6::R6Class(
       #arr[] <- values
       writeArrayFromArrow(
         uri = self$uri,
-        coords,
         naap = naap,
         nasp = nasp,
+        coords_list = coords,
         ctxxp = private$.soma_context,
         arraytype = "SOMADenseNDArray",
         config = NULL,

apis/r/R/SOMASparseNDArray.R

@@ -282,6 +282,7 @@ SOMASparseNDArray <- R6::R6Class(
         uri = self$uri,
         naap = naap,
         nasp = nasp,
+        coords_list = list(), # only used for SOMADenseNDArray
         ctxxp = private$.soma_context,
         arraytype = "SOMASparseNDArray",
         config = NULL,

apis/r/src/arrow.cpp

@@ -273,7 +273,20 @@ void writeArrayFromArrow(
             int lo = *std::min_element(slot_values.begin(), slot_values.end());
             int hi = *std::max_element(slot_values.begin(), slot_values.end());
             spdl::debug(
-                "dense array write: dim {} set range lo {} hi {}", dim_name, lo, hi);
+                "dense array write: dim {} set 1-up range lo {} hi {}",
+                dim_name,
+                lo,
+                hi);
+            // These are 1-up indices from R. Convert to 0-up for C++.
+            if (lo < 1) {
+                Rcpp::stop(tfm::format(
+                    "dense array write: expected lower bound %d >= 1 for dim "
+                    "name %s",
+                    lo,
+                    dim_name));
+            }
+            lo--;
+            hi--;
             std::pair<int64_t, int64_t> lo_hi(int64_t{lo}, int64_t{hi});
             std::vector<std::pair<int64_t, int64_t>> range({lo_hi});
             arrup.get()->set_dim_ranges(dim_name, range);