def test_deepcopy_subset(adata, spmat: type):
    adata.obsp["arr"] = np.zeros((adata.n_obs, adata.n_obs))
    adata.obsp["spmat"] = spmat((adata.n_obs, adata.n_obs))

    adata = deepcopy(adata[:10].copy())

    assert isinstance(adata.obsp["arr"], np.ndarray)
    assert not isinstance(adata.obsp["arr"], ArrayView)
    np.testing.assert_array_equal(adata.obsp["arr"].shape, (10, 10))

    assert isinstance(adata.obsp["spmat"], spmat)
    assert not isinstance(
        adata.obsp["spmat"],
        SparseCSRView if spmat is sparse.csr_matrix else SparseCSCView,
    )
    np.testing.assert_array_equal(adata.obsp["spmat"].shape, (10, 10))
def dfs(self, num, target, pos, cur_str, cur_val, mul, ret):
        if pos >= len(num):
            if cur_val == target:
                ret.append(cur_str)
        else:
            for i in xrange(pos, len(num)):
                if i != pos and num[pos] == "0":
                    continue
                nxt_val = int(num[pos:i+1])

                if not cur_str:
                    self.dfs(num, target, i+1, "%d"%nxt_val, nxt_val, nxt_val, ret)
                else:
                    self.dfs(num, target, i+1, cur_str+"+%d"%nxt_val, cur_val+nxt_val, nxt_val, ret)
                    self.dfs(num, target, i+1, cur_str+"-%d"%nxt_val, cur_val-nxt_val, -nxt_val, ret)
                    self.dfs(num, target, i+1, cur_str+"*%d"%nxt_val, cur_val-mul+mul*nxt_val, mul*nxt_val, ret)