keep possible deprecated function commented

src/vame/analysis/umap.py

@@ -61,44 +61,44 @@ def umap_embedding(cfg: dict, file: str, model_name: str, n_cluster: int, parame
     return embed
 
 
-def umap_vis_community_labels(cfg: dict, embed: np.ndarray, community_labels_all: np.ndarray, save_path: str | None) -> None:
-    """Create plotly visualizaton of UMAP embedding with community labels.
-
-    Args:
-        cfg (dict): Configuration parameters.
-        embed (np.ndarray): UMAP embedding.
-        community_labels_all (np.ndarray): Community labels.
-        save_path: Path to save the plot. If None it will not save the plot.
-
-    Returns:
-        None
-    """
-    num_points = cfg['num_points']
-    community_labels_all = np.asarray(community_labels_all)
-    if num_points > community_labels_all.shape[0]:
-        num_points = community_labels_all.shape[0]
-    logger.info("Embedding %d data points.." %num_points)
-
-    num = np.unique(community_labels_all)
-
-    fig = plt.figure(1)
-    plt.scatter(
-        embed[:,0],
-        embed[:,1],
-        c=community_labels_all[:num_points],
-        cmap='Spectral',
-        s=2,
-        alpha=1
-    )
-    plt.colorbar(boundaries=np.arange(np.max(num)+2)-0.5).set_ticks(np.arange(np.max(num)+1))
-    plt.gca().set_aspect('equal', 'datalim')
-    plt.grid(False)
-
-    if save_path is not None:
-        plt.savefig(save_path)
-        return fig
-    plt.show()
-    return fig
+# def umap_vis_community_labels(cfg: dict, embed: np.ndarray, community_labels_all: np.ndarray, save_path: str | None) -> None:
+#     """Create plotly visualizaton of UMAP embedding with community labels.
+
+#     Args:
+#         cfg (dict): Configuration parameters.
+#         embed (np.ndarray): UMAP embedding.
+#         community_labels_all (np.ndarray): Community labels.
+#         save_path: Path to save the plot. If None it will not save the plot.
+
+#     Returns:
+#         None
+#     """
+#     num_points = cfg['num_points']
+#     community_labels_all = np.asarray(community_labels_all)
+#     if num_points > community_labels_all.shape[0]:
+#         num_points = community_labels_all.shape[0]
+#     logger.info("Embedding %d data points.." %num_points)
+
+#     num = np.unique(community_labels_all)
+
+#     fig = plt.figure(1)
+#     plt.scatter(
+#         embed[:,0],
+#         embed[:,1],
+#         c=community_labels_all[:num_points],
+#         cmap='Spectral',
+#         s=2,
+#         alpha=1
+#     )
+#     plt.colorbar(boundaries=np.arange(np.max(num)+2)-0.5).set_ticks(np.arange(np.max(num)+1))
+#     plt.gca().set_aspect('equal', 'datalim')
+#     plt.grid(False)
+
+#     if save_path is not None:
+#         plt.savefig(save_path)
+#         return fig
+#     plt.show()
+#     return fig
 
 
 def umap_vis(embed: np.ndarray, num_points: int) -> None: