[Debian-med-packaging] Bug#1075928: python-anndata: tests fail with scipy 1.13

[Drew Parsons]

Source: python-anndata
Version: 0.10.6-1
Severity: normal

python-anndata is failing tests with scipy 1.13,
likely due to use of deprecated API

https://ci.debian.net/packages/p/python-anndata/unstable/arm64/48727323/


295s _____________ test_backed_indexing[array_subset-array_subset-h5ad] _____________
295s 
295s ondisk_equivalent_adata = (AnnData object with n_obs × n_vars = 50 × 50, AnnData object with n_obs × n_vars = 50 × 50 backed at '/tmp/pytest-of-...ect with n_obs × n_vars = 50 × 50 backed at '/tmp/pytest-of-debci/pytest-0/test_backed_indexing_array_sub0/dense.h5ad')
295s subset_func = <function array_subset at 0xffffb3096160>
295s subset_func2 = <function array_subset at 0xffffb3096160>
295s 
295s     def test_backed_indexing(
295s         ondisk_equivalent_adata: tuple[AnnData, AnnData, AnnData, AnnData],
295s         subset_func,
295s         subset_func2,
295s     ):
295s         csr_mem, csr_disk, csc_disk, dense_disk = ondisk_equivalent_adata
295s     
295s         obs_idx = subset_func(csr_mem.obs_names)
295s         var_idx = subset_func2(csr_mem.var_names)
295s     
295s >       assert_equal(csr_mem[obs_idx, var_idx].X, csr_disk[obs_idx, var_idx].X)
295s 
295s tests/test_backed_sparse.py:115: 
295s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
295s /usr/lib/python3/dist-packages/anndata/_core/anndata.py:586: in X
295s     X = _subset(X, (self._oidx, self._vidx))
295s /usr/lib/python3.11/functools.py:909: in wrapper
295s     return dispatch(args[0].__class__)(*args, **kw)
295s /usr/lib/python3/dist-packages/anndata/_core/sparse_dataset.py:608: in subset_sparsedataset
295s     return d[subset_idx]
295s /usr/lib/python3/dist-packages/anndata/_core/sparse_dataset.py:427: in __getitem__
295s     sub = mtx[row, col]
295s /usr/lib/python3/dist-packages/scipy/sparse/_index.py:91: in __getitem__
295s     return self._get_columnXarray(row[:,0], col.ravel())
295s /usr/lib/python3/dist-packages/scipy/sparse/_compressed.py:688: in _get_columnXarray
295s     return self._major_index_fancy(major)._minor_index_fancy(minor)
295s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
295s 
295s self = <50x50 sparse matrix of type '<class 'numpy.float64'>'
295s 	with 250 stored elements in Compressed Sparse Row format>
295s idx = array([38, 45, 41, 29, 47,  6, 10, 28, 42,  5,  9, 26, 48, 33])
295s 
295s     def _major_index_fancy(self, idx):
295s         """Index along the major axis where idx is an array of ints.
295s         """
295s         idx_dtype = self._get_index_dtype((self.indptr, self.indices))
295s         indices = np.asarray(idx, dtype=idx_dtype).ravel()
295s     
295s         _, N = self._swap(self.shape)
295s         M = len(indices)
295s         new_shape = self._swap((M, N))
295s         if M == 0:
295s             return self.__class__(new_shape, dtype=self.dtype)
295s     
295s         row_nnz = (self.indptr[indices + 1] - self.indptr[indices]).astype(idx_dtype)
295s     
295s         res_indptr = np.zeros(M+1, dtype=idx_dtype)
295s         np.cumsum(row_nnz, out=res_indptr[1:])
295s     
295s         nnz = res_indptr[-1]
295s         res_indices = np.empty(nnz, dtype=idx_dtype)
295s         res_data = np.empty(nnz, dtype=self.dtype)
295s         csr_row_index(
295s             M,
295s             indices,
295s             self.indptr.astype(idx_dtype, copy=False),
295s >           self.indices.astype(idx_dtype, copy=False),
295s             self.data,
295s             res_indices,
295s             res_data
295s         )
295s E       TypeError: Dataset.astype() got an unexpected keyword argument 'copy'
295s 
295s /usr/lib/python3/dist-packages/scipy/sparse/_compressed.py:714: TypeError



scipy 1.12 was recently uploaded to unstable, but upstream has already
released 1.14, so we'll want to push scipy 1.13 to unstable in the
near future.