【Add】 add title

stereo/plots/plot_collection.py

@@ -567,7 +567,8 @@ def violin(
             ax: Optional[Axes] = None,
             order: Optional[Iterable[str]] = None,
             use_raw: Optional[bool] = False,
-            palette: Optional[str] = None
+            palette: Optional[str] = None,
+            title: Optional[str, Sequence[str]] = None,
     ):
         """
         Violin plot to show index distribution of quality control.
@@ -588,6 +589,7 @@ def violin(
         :param ax: a matplotlib axes object. only works if plotting a single component.
         :param order: Order in which to show the categories.
         :param use_raw: Whether to use raw attribute of data. Defaults to True if .raw is present.
+        :param title: the title.
         :param palette: color theme.
             For more color theme selection reference: https://seaborn.pydata.org/tutorial/color_palettes.html
         :param out_path: the path to save the figure.
@@ -610,7 +612,8 @@ def violin(
             ax=ax,
             order=order,
             use_raw=use_raw,
-            palette=palette
+            palette=palette,
+            title=title
         )
 
     @reorganize_coordinate

stereo/plots/violin.py

@@ -203,7 +203,8 @@ def violin_distribution(
         ax: Optional[Axes] = None,
         order: Optional[Iterable[str]] = None,
         use_raw: Optional[bool] = False,
-        palette: Optional[str] = None
+        palette: Optional[str] = None,
+        title: Optional[str] = None
 ):  # Violin Statistics Chart
     """
     violin plot showing quality control index distribution
@@ -226,6 +227,7 @@ def violin_distribution(
     :param order: Order in which to show the categories.
     :param use_raw: Whether to use raw attribute of adata. Defaults to True if .raw is present.
     :param palette: color theme.
+    :param title: the title.
 
     :return: None
     """
@@ -261,6 +263,9 @@ def violin_distribution(
     if not isinstance(obs_df.iloc[0][index_ys], float):
         obs_df[index_ys] = pd.to_numeric(obs_df[index_ys], errors='coerce')
 
+    if title and not isinstance(title, list):
+        title = [title]
+
     if multi_panel and group_by is None and len(ys) == 1:
         y = ys[0]
         g = sns.catplot(
@@ -291,6 +296,9 @@ def violin_distribution(
         if log:
             g.set(yscale='log')
         g.set_titles(col_template='{col_name}').set_xlabels('')
+        if title:
+            for ax in g.axes[0]:
+                ax.set_title(title.pop(0) if title else '')
         if rotation_angle is not None:
             for ax in g.axes[0]:
                 ax.tick_params(axis='x', labelrotation=rotation_angle)
@@ -322,6 +330,8 @@ def violin_distribution(
                 ax.set_yscale('log')
             if rotation_angle is not None:
                 ax.tick_params(axis='x', labelrotation=rotation_angle)
+            if title:
+                ax.set_title(title.pop(0) if title else '')
     pl.show()