diff --git a/parties/graph.py b/parties/graph.py
index c3f4253..3eb0c1a 100644
--- a/parties/graph.py
+++ b/parties/graph.py
@@ -498,20 +498,55 @@ def matRecup(i, param):
    
     return matR
 
-#Couleur des Stratégies
-CouleursStrat=['b','r','black','g','purple']
-fig=plt.figure()
-fig.suptitle('Animation des stratégies')
-cmap = mpl.colors.ListedColormap(["b","r" ,"black" ,"g" ,"purple"])
-bounds=[0,1,2,3,4,5]
-norm=mpl.colors.BoundaryNorm(bounds, cmap.N)
-img=plt.imshow(matRecup(0, 'strategie'), interpolation = "nearest", cmap = cmap , norm = norm)
-for i in range(0, 12):
-    print(matRecup(i, 'etat'))
-cb=plt.colorbar(img , cmap=cmap , norm=norm , boundaries = bounds , ticks=bounds)
-labels = np.arange(0, 5, 1)
-cb.set_ticklabels(labels)
 
+def animation_strat():
+    fig=plt.figure()
+    fig.suptitle('Animation des stratégies')
+    cmap = mpl.colors.ListedColormap(["black","green" ,"red" ,"blue" ,"yellow"])
+    bounds=[0,1,2,3,4,5]
+    norm=mpl.colors.BoundaryNorm(bounds, cmap.N)
+    img=plt.imshow(matRecup(0, 'strategie'), interpolation = "nearest", cmap = cmap , norm = norm)
+
+    cb=plt.colorbar(img , cmap=cmap , norm=norm , boundaries = bounds , ticks=bounds)
+    labels = np.arange(1, 6, 1)
+    cb.set_ticklabels(labels)
+
+
+
+
+
+    def update(next_iteration,*args):
+        img.set_array(matRecup(next_iteration , 'strategie'))
+        return [img]
+
+    anim = animation.FuncAnimation(fig, update, frames=range(MaxIterations), interval=1000, repeat = False)
+    plt.show()
+  
+
+
+def animation_etat():
+    fig=plt.figure()
+    fig.suptitle('Animation des états')
+    cmap = mpl.colors.ListedColormap(["black","white"])
+    bounds=[0,1,2]
+    norm=mpl.colors.BoundaryNorm(bounds, cmap.N)
+    img=plt.imshow(matRecup(0, 'etat'), interpolation = "nearest", cmap = cmap , norm = norm)
+
+    cb=plt.colorbar(img , cmap=cmap , norm=norm , boundaries = bounds , ticks=bounds)
+    labels = np.arange(0, 2, 1)
+    cb.set_ticklabels(labels)
+
+
+
+
+
+    def update(next_iteration,*args):
+        img.set_array(matRecup(next_iteration , 'etat'))
+        return [img]
+
+    anim = animation.FuncAnimation(fig, update, frames=range(MaxIterations), interval=1000, repeat = False)
+    plt.show()
+