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.
