Fix slicing when subset args are numpy vectors

CHANGELOG.md

@@ -1,10 +1,12 @@
 # Changelog
 
-## Version 0.5.1 - 0.5.2
+## Version 0.5.1 - 0.5.3
 
 - Add wrapper class methods to combine experiments by rows or columns.
 - Expand function names for readability, still backwards compatible with the older function and method names.
 - Add getters and setters to replace a specific alternative experiment or reduced dimension.
+- Fixed an issue with numpy arrays as slice arguments. Code now uses Biocutils's subset functions to perform these operations.
+
 
 ## Version 0.5.0
 

setup.cfg

@@ -49,7 +49,7 @@ python_requires = >=3.9
 # For more information, check out https://semver.org/.
 install_requires =
     importlib-metadata; python_version<"3.8"
-    summarizedexperiment>=0.5.1
+    summarizedexperiment>=0.5.3
 
 [options.packages.find]
 where = src

src/singlecellexperiment/SingleCellExperiment.py

@@ -980,41 +980,40 @@ def get_slice(
         rows: Optional[Union[str, int, bool, Sequence]],
         columns: Optional[Union[str, int, bool, Sequence]],
     ) -> "SingleCellExperiment":
-        """Alias for :py:attr:`~__getitem__`, for back-compatibility."""
+        """Alias for :py:attr:`~__getitem__`."""
 
         slicer = self._generic_slice(rows=rows, columns=columns)
+        do_slice_rows = not (isinstance(slicer.row_indices, slice) and slicer.row_indices == slice(None))
+        do_slice_cols = not (isinstance(slicer.col_indices, slice) and slicer.col_indices == slice(None))
 
         new_row_ranges = None
-        if slicer.row_indices != slice(None):
+        if do_slice_rows:
             new_row_ranges = self._row_ranges[slicer.row_indices]
 
         new_reduced_dims = {}
         for rdim, rmat in self._reduced_dims.items():
-            if slicer.col_indices != slice(None):
+            if do_slice_cols:
                 rmat = rmat[slicer.col_indices, :]
 
             new_reduced_dims[rdim] = rmat
 
         new_alt_expts = {}
         for altname, altexpt in self._alternative_experiments.items():
-            if slicer.row_indices != slice(None):
-                altexpt = altexpt[slicer.row_indices, :]
-
-            if slicer.col_indices != slice(None):
+            if do_slice_cols:
                 altexpt = altexpt[:, slicer.col_indices]
 
             new_alt_expts[altname] = altexpt
 
         new_row_pairs = {}
         for rname, rpair in self._row_pairs.items():
-            if slicer.row_indices != slice(None):
+            if do_slice_rows:
                 rpair = rpair[slicer.row_indices, :]
 
             new_row_pairs[rname] = rpair
 
         new_col_pairs = {}
         for cname, cpair in self._column_pairs.items():
-            if slicer.col_indices != slice(None):
+            if do_slice_cols:
                 cpair = cpair[:, slicer.col_indices]
 
             new_col_pairs[cname] = cpair

tests/test_sce_slice.py

@@ -66,6 +66,31 @@ def test_SCE_slice():
 
     assert tse_slice.assay("counts").shape == (10, 3)
 
+def test_SCE_slice_with_numpy():
+    tse = SingleCellExperiment(
+        assays={"counts": counts},
+        row_data=row_data,
+        column_data=col_data,
+        reduced_dims={"random_embeds": np.random.rand(ncols, 5)},
+    )
+
+    tse_slice = tse[np.arange(10), 0:3]
+    assert tse_slice is not None
+    assert isinstance(tse_slice, sce)
+
+    assert len(tse_slice.row_data) == 10
+    assert len(tse_slice.col_data) == 3
+
+    assert tse_slice.assay("counts").shape == (10, 3)
+
+    tse_slice = tse[np.arange(10), np.arange(3)]
+    assert tse_slice is not None
+    assert isinstance(tse_slice, sce)
+
+    assert len(tse_slice.row_data) == 10
+    assert len(tse_slice.col_data) == 3
+
+    assert tse_slice.assay("counts").shape == (10, 3)
 
 def test_SCE_creation_with_alts_slice():
     trse = SummarizedExperiment(
@@ -91,4 +116,4 @@ def test_SCE_creation_with_alts_slice():
 
     assert tsce_slice.assay("counts").shape == (10, 3)
     alt_exp = tsce_slice.alternative_experiments["alt"]
-    assert alt_exp.shape == (10, 3)
+    assert alt_exp.shape == (200, 3)