Modification de l'affichage graphique des plots et autres modifications

Statistics_methylation.py

@@ -15,6 +15,8 @@ import matplotlib.patches as mpatches
 import argparse
 import re
 from tkinter import *
+import tkinter as tk
+from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
 matplotlib.use('TkAgg')
 # Arguments
 
@@ -58,8 +60,8 @@ def CpG_context():
                 rows.append(row)
     rows_CG_df = pd.DataFrame(rows)
     rows_CG = rows_CG_df.sort_values("chromosome")
-    #output_file = os.path.join(output_dir, filebasename + "_CG.csv")
-    #rows_CG.to_csv(output_file, index=False, sep='\t')
+    output_file = os.path.join(output_dir, filebasename + "_CG.csv")
+    rows_CG.to_csv(output_file, index=False, sep='\t')
     #if not rows_CG.empty:
     #    for chromosome in rows_CG['chromosome'].unique():
     #        positions_par_chromosome[chromosome] = list(rows_CG.loc[rows_CG['chromosome'] == chromosome, ['strand', 'position']])
@@ -184,14 +186,13 @@ def plotting():
     CHG = CHG_context()
     CHH = CHH_context()
 
-    fig, ax = plt.subplots(figsize=(6,3), subplot_kw=dict(aspect="equal"))
+
+    fig, ax = plt.subplots(figsize=(10,6), subplot_kw=dict(aspect="equal"))
     nb_unmethylated = nb_C - CpG - CHG - CHH
     counts = [CpG, CHG, CHH, nb_unmethylated]
 
     labels = ["CpG", "CHG", "CHH", "unmethylated"]
 
-    fig = plt.figure()
-    ax = fig.add_subplot(111)
     wedges, texts, autotexts = ax.pie(counts, autopct='%1.1f%%')
     bbox_props= dict(boxstyle="square, pad=0.3", fc="w", ec="k", lw=0.72)
     kw = dict(arrowprops=dict(arrowstyle="-"), bbox=bbox_props, zorder=0, va="center")
@@ -206,12 +207,22 @@ def plotting():
         ax.annotate(f"{labels[i]}: {counts[i]}", xy=(x, y), xytext=(1.35 * np.sign(x), 1.4 * y),
                     horizontalalignment=horizontalalignment, **kw)
 
-    #ax.pie(counts, autopct='%1.1f%%', startangle=90, center = (-2,0))
-    #legend = ax.legend(labels, loc = 2)
-    #ax.axis('equal')
-
     plt.title(f"Methylation context amoung all cytosines in the sample : {filebasename}")
-    plt.show()
+
+    root = tk.Tk()
+    root.title("Methylation Statistics")
+
+    # Create a canvas to display the figure
+    canvas = FigureCanvasTkAgg(fig, master=root)
+    canvas.draw()
+    canvas.get_tk_widget().pack()
+
+    # Create a button to close the window
+    button = tk.Button(master=root, text="Fermer", command=root.quit)
+    button.pack()
+
+    # Start the tkinter event loop
+    tk.mainloop()
 
 print("####-------- CALCULATION OF METHYLATION STATISTICS FROM TSV FILE GENERATED BY DeepSignal-Plant  --------####")
 
@@ -273,7 +284,7 @@ for filename in glob.glob(files): # to select all files present in that path
     treated_df['k_mer'] = treated_df['k_mer'].str[2:] # filter dataset "treated_df" which contains only from the 3th element from k_mer
 
 
-    CpG_context()
+    #CpG_context()
     #CHG_context()
     #CHH_context()
-    #plotting()
+    plotting()