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Update graph.py

This commit is contained in:
NicolasBSN 2017-03-22 11:20:02 +01:00 committed by GitHub
parent 6307d88a7f
commit d71e7b5a8d
1 changed files with 48 additions and 13 deletions
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61
parties/graph.py
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@ -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()