def test_view_of_view_modification():
    adata = ad.AnnData(np.zeros((10, 10)))
    adata[0, :][:, 5:].X = np.ones(5)
    assert np.all(adata.X[0, 5:] == np.ones(5))
    adata[[1, 2], :][:, [1, 2]].X = np.ones((2, 2))
    assert np.all(adata.X[1:3, 1:3] == np.ones((2, 2)))

    adata.X = sparse.csr_matrix(adata.X)
    adata[0, :][:, 5:].X = np.ones(5) * 2
    assert np.all(asarray(adata.X)[0, 5:] == np.ones(5) * 2)
    adata[[1, 2], :][:, [1, 2]].X = np.ones((2, 2)) * 2
    assert np.all(asarray(adata.X)[1:3, 1:3] == np.ones((2, 2)) * 2)
def _sparse_rmsprop_update_numpy(self, var, gindexs, gvalues, mg, rms, mom,
                                   lr, decay, momentum, centered):
    mg_t = copy.deepcopy(mg)
    rms_t = copy.deepcopy(rms)
    mom_t = copy.deepcopy(mom)
    var_t = copy.deepcopy(var)
    for i in range(len(gindexs)):
      gindex = gindexs[i]
      gvalue = gvalues[i]
      rms_t[gindex] = rms[gindex] * decay + (1 - decay) * gvalue * gvalue
      denom_t = rms_t[gindex]
      if centered:
        mg_t[gindex] = mg_t[gindex] * decay + (1 - decay) * gvalue
        denom_t -= mg_t[gindex] * mg_t[gindex]
      mom_t[gindex] = momentum * mom[gindex] + lr * gvalue / np.sqrt(denom_t)
      var_t[gindex] = var[gindex] - mom_t[gindex]
    return var_t, mg_t, rms_t, mom_t