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 loss_density(isa, subreg=[], ax=0):
    """plot loss density of NC/I7/ISA7 model
    Args:
      isa: Isa7/NC object
    """
    if subreg:
        if isinstance(subreg, list):
            sr = subreg
        else:
            sr = [subreg]
        elements = [e for s in sr for sre in isa.get_subregion(s).elements()
                    for e in sre]
    else:
        elements = [e for e in isa.elements]

    lossd = np.array([e.loss_density*1e-3 for e in elements])
    _contour(ax, 'Loss Density kW/m³', elements, lossd)