def METHOD_NAME(
    adata: AnnData, basis: str = "umap", clusters="clusters", color_key_cmap: str = "Spectral", *args, **kwargs
) -> None:
    """Scatter plot for visualizing streamline clusters in selected basis.
    Args:
        adata: an Annodata object.
        basis: the reduced dimension stored in adata.uns. The specific basis key will be constructed as
            `"streamline_clusters_"+basis`. Defaults to "umap".
        clusters: the key of cluster data stored in the basis data. Defaults to "clusters".
        color_key_cmap: name of the pyplot color map used for plotting. Defaults to "Spectral".
        *args: not used. Left here for backward compatibility.
        **kwargs: not used. Left here for backward compatibility.
    """
    if "streamline_clusters_" + basis not in adata.uns_keys():
        from ..vectorfield.clustering import METHOD_NAME
        METHOD_NAME(adata, basis=basis)
    segments = adata.uns["streamline_clusters_" + basis]["segments"]
    clusters = adata.uns["streamline_clusters_" + basis][clusters].astype(int)
    clusters[np.isnan(clusters)] = -1
    num_labels = len(np.unique(clusters))
    color_key = _to_hex(plt.get_cmap(color_key_cmap)(np.linspace(0, 1, num_labels)))
    fig, ax = plt.subplots(1, 1)
    for key, values in segments.items():
        ax.plot(*values.T, color=color_key[int(clusters[key])])
    plt.show()