Adding some example

apis/python/src/tiledbsoma/IntIndexer.py

@@ -17,7 +17,7 @@ def map_locations(keys: np.ndarray[np.int64, Any]) -> clib.IntIndexer:
         )
         compute_concurrency = 5
         if context._tiledb_ctx:
-            compute_concurrency = context._tiledb_ctx.config()[
+            compute_concurrency = int(int(context._tiledb_ctx.config()))/2[
                 "sm.compute_concurrency_level"
             ]
         thread_counts = int(compute_concurrency)

apis/python/src/tiledbsoma/_fast_csr.py

@@ -45,9 +45,9 @@ class _CSRAccumulatorFinalResult(NamedTuple):
     Contains a sparse CSR consituent elements
     """
 
-    data: npt.NDArray[np.number]  # type: ignore[type-arg]
-    indptr: npt.NDArray[np.integer]  # type: ignore[type-arg]
-    indices: npt.NDArray[np.integer]  # type: ignore[type-arg]
+    data: npt.NDArray[np.number]  # type: ignore
+    indptr: npt.NDArray[np.integer]  # type: ignore
+    indices: npt.NDArray[np.integer]  # type: ignore
     shape: Tuple[int, int]
 
 
@@ -187,11 +187,11 @@ def _accum_row_length(
 @numba.jit(nopython=True, nogil=True)  # type: ignore[attr-defined]
 def _copy_chunk_range(
     row_ind_chunk: npt.NDArray[np.signedinteger], # ignore-type
-    col_ind_chunk: npt.NDArray[np.signedinteger],
-    data_chunk: npt.NDArray[np.number],
-    data: npt.NDArray[np.number],
-    indices: npt.NDArray[np.signedinteger],
-    indptr: npt.NDArray[np.signedinteger],
+    col_ind_chunk: npt.NDArray[np.signedinteger], # type: ignore
+    data_chunk: npt.NDArray[np.number], # type: ignore
+    data: npt.NDArray[np.number], # type: ignore
+    indices: npt.NDArray[np.signedinteger], # type: ignore
+    indptr: npt.NDArray[np.signedinteger], # type: ignore
     row_rng_mask: int,
     row_rng_val: int,
 ) -> None:
@@ -208,9 +208,9 @@ def _copy_chunk_range(
 @numba.jit(nopython=True, nogil=True)  # type: ignore[attr-defined]
 def _copy_chunklist_range(
     chunk_list: numba.typed.List,
-    data: npt.NDArray[np.number], # type: ignore[attr-defined]
-    indices: npt.NDArray[np.signedinteger], # type: ignore[attr-defined]
-    indptr: npt.NDArray[np.signedinteger], # type: ignore[attr-defined]
+    data: npt.NDArray[np.number], # type: ignore
+    indices: npt.NDArray[np.signedinteger], # type: ignore
+    indptr: npt.NDArray[np.signedinteger], # type: ignore
     row_rng_mask_bits: int,
     job: int,
 ):
@@ -284,7 +284,7 @@ def _read_csr(
         acc = _CSRAccumulator(
             obs_joinids=obs_joinids, var_joinids=var_joinids, pool=pool
         )
-        for tbl in somacore._eager_iter.EagerIterator(
+        for tbl in somacore.query._eager_iter.EagerIterator(
             matrix.read((obs_joinids, var_joinids)).tables(),
             pool=pool,
         ):

libtiledbsoma/src/reindexer/examples/ann_data.py

@@ -0,0 +1,22 @@
+import cellxgene_census
+import tiledbsoma as soma
+from time import perf_counter
+
+soma._query.ExperimentAxisQuery.USE_FAST_INDEXER = False
+
+census_S3_latest = dict(census_version="latest")
+census_local_copy = dict(uri="/Users/brobatmili/projects/census_data/")
+
+def main():
+    t1 = perf_counter()
+    with cellxgene_census.open_soma(**census_S3_latest, context=soma.SOMATileDBContext(use_optimized_reindexing=True)) as census:
+        with census["census_data"]["homo_sapiens"].axis_query(
+                measurement_name="RNA", obs_query=soma.AxisQuery(
+                    value_filter="""tissue_general == 'eye'""")
+
+        ) as query:
+            query.to_anndata(X_name="raw")
+    t2 = perf_counter()
+    print(f"End to end time {t2 - t1}")
+
+main()

libtiledbsoma/src/reindexer/examples/test_indexer.py

@@ -0,0 +1,14 @@
+from tiledbsoma.IntIndexer import IntIndexer
+import numpy as np
+
+# 1d array to list
+keys = np.array([-1, 1, 2, 3, 4, 5])
+look_ups = np.array([-1, 1, 2, 3, 4, 5, -1, 1, 2, 3, 4, 5, -1, 1, 2, 3, 4, 5, -1, 1, 2, 3, 4, 5])
+
+def main():
+    indexer = IntIndexer.map_locations(keys)
+    results = indexer.lookup(look_ups)
+    print(f"Lookup results {results}")
+
+if __name__ == "__main__":
+    main()

libtiledbsoma/src/reindexer/test_indexer.py

@@ -0,0 +1,14 @@
+from tiledbsoma.IntIndexer import IntIndexer
+import numpy as np
+
+# 1d array to list
+keys = np.array([-1, 1, 2, 3, 4, 5])
+look_ups = np.array([-1, 1, 2, 3, 4, 5, -1, 1, 2, 3, 4, 5, -1, 1, 2, 3, 4, 5, -1, 1, 2, 3, 4, 5])
+
+def main():
+    indexer = IntIndexer.map_locations(keys)
+    results = indexer.lookup(look_ups)
+    print(f"Lookup results {results}")
+
+if __name__ == "__main__":
+    main()