src/find_interaction_cluster/clip_figures/clip_compo_analyser.py: the...

src/find_interaction_cluster/clip_figures/clip_compo_analyser.py: the differents violins (enriched, imoverished) are now order in the figure with custom colors

src/find_interaction_cluster/clip_figures/clip_compo_analyser.py

@@ -353,8 +353,12 @@ def make_barplot(df_comp: pd.DataFrame, outfile: Path, cpnt: str,
     :param clip_name: The name of the clip studied
     """
     sns.set(context="talk")
+    dic_col = df_comp[["group", "color"]].drop_duplicates().copy()
+    dic_col.index = dic_col["group"]
+    dic_col.drop("group", axis=1, inplace=True)
+    dic_col = dic_col.to_dict()["color"]
     g = sns.catplot(x="group", y=cpnt, data=df_comp, height=12, aspect=1.7,
-                    kind="violin")
+                    kind="violin", palette=dic_col)
     g.fig.suptitle(f"Mean frequency of {cpnt}({cpnt_type})"
                    f"among different community groups\n"
                    f"created from the peak_density from clip {clip_name}")
@@ -375,6 +379,14 @@ def update_composition_group(df_comp: pd.DataFrame, display_size: bool
     :return: if display_size is False return df_comp else return df_comp \
     with the group column containing the size of the groups.
     """
+    dic = {"ctrl": 1, "enriched": 2, "enriched_nosig": 2, "middle": 3,
+           "impoverished": 4, "impoverished_nosig": 4}
+    dic_color = {"ctrl": "#FFCD00", "enriched": "#D40C00",
+                 "enriched_nosig": "#FF9A00", "middle": "#FF9A00",
+                 "impoverished": "#526EFF", "impoverished_nosig": "#00A5F9"}
+    df_comp["order"] = df_comp["group"].map(dic)
+    df_comp["color"] = df_comp["group"].map(dic_color)
+    df_comp = df_comp.sort_values("order")
     if not display_size:
         return df_comp
     d = {
@@ -531,16 +543,18 @@ def get_ctrl_dic(list_files: List[Path], feature: str) -> Dict:
     }
 
 
-def merge_figures(folder: Path) -> None:
+def merge_figures(folder: Path, list_ft: List[str]) -> None:
     """
     Merge the figures together using imageMagick
 
     :param folder: A folder containing pdf files
+    :param list_ft: The list of feature of interest
     """
     fig_name = folder.parent.name
+    tmp_cmd = " ".join(f"{folder}/*_{ft}_*dft*.pdf" for ft in list_ft)
     cmd = f"montage -geometry +1+1 -tile 1X3  " \
           f"-compress jpeg -density 100 -label %t -pointsize 50 " \
-          f"{folder}/*dft*.pdf {folder}/{fig_name}.pdf"
+          f"{tmp_cmd} {folder}/{fig_name}.pdf"
     sp.check_call(cmd, shell=True)
 
 
@@ -659,7 +673,7 @@ def multi_tads_compo_figures(clip_result_folder: Path, feature: str,
     pool.join()
     list_folder = np.unique([r for r in results if r is not None])
     for folder in list_folder:
-        merge_figures(folder)
+        merge_figures(folder, list_ft)
 
 
 @lp.parse(feature=["gene", "exon"], threshold_feature=range(1, 1001),