def test_set_obsm(adata):
    init_hash = joblib.hash(adata)

    dim0_size = np.random.randint(2, adata.shape[0] - 1)
    dim1_size = np.random.randint(1, 99)
    orig_obsm_val = adata.obsm["o"].copy()
    subset_idx = np.random.choice(adata.obs_names, dim0_size, replace=False)

    subset = adata[subset_idx, :]
    assert subset.is_view
    subset.obsm = dict(o=np.ones((dim0_size, dim1_size)))
    assert not subset.is_view
    assert np.all(orig_obsm_val == adata.obsm["o"])  # Checking for mutation
    assert np.all(subset.obsm["o"] == np.ones((dim0_size, dim1_size)))

    subset = adata[subset_idx, :]
    subset_hash = joblib.hash(subset)
    with pytest.raises(ValueError):
        subset.obsm = dict(o=np.ones((dim0_size + 1, dim1_size)))
    with pytest.raises(ValueError):
        subset.varm = dict(o=np.ones((dim0_size - 1, dim1_size)))
    assert subset_hash == joblib.hash(subset)

    # Only modification have been made to a view
    assert init_hash == joblib.hash(adata)
def noun_chunks(doclike: Union[Doc, Span]) -> Iterator[Span]:
    """
    Detect base noun phrases from a dependency parse. Works on both Doc and Span.
    """
    # fmt: off
    labels = ["nsubj", "nsubj:pass", "obj", "iobj", "ROOT", "appos", "nmod", "nmod:poss"]
    # fmt: on
    doc = doclike.doc  # Ensure works on both Doc and Span.
    if not doc.has_annotation("DEP"):
        raise ValueError(Errors.E029)
    np_deps = [doc.vocab.strings[label] for label in labels]
    conj = doc.vocab.strings.add("conj")
    np_label = doc.vocab.strings.add("NP")
    prev_end = -1
    for i, word in enumerate(doclike):
        if word.pos not in (NOUN, PROPN, PRON):
            continue
        # Prevent nested chunks from being produced
        if word.left_edge.i <= prev_end:
            continue
        if word.dep in np_deps:
            prev_end = word.right_edge.i
            yield word.left_edge.i, word.right_edge.i + 1, np_label
        elif word.dep == conj:
            head = word.head
            while head.dep == conj and head.head.i < head.i:
                head = head.head
            # If the head is an NP, and we're coordinated to it, we're an NP
            if head.dep in np_deps:
                prev_end = word.right_edge.i
                yield word.left_edge.i, word.right_edge.i + 1, np_label