Enregistrer une figure
fig = plt.figure()
plt.plot(x,y)
fig.set_size_inches(13,10) #largeur,hauteur
fig.savefig('path/nameFig'+'.png',dpi=100)
Enregistrer une fichier texte
f = open('name.txt','w')
f.write('line1'+'\n')
f.close()
Fonction cumulative (CDF)
plt.plot(np.sort(vec),np.linspace(1,len(vec),len(vec))/len(np.linspace(1,len(vec),len(vec))),color='black')
f = open('name.rdb','w')
shutil.move('name.rdb','path')
Échelle Log en scalaire
from matplotlib.ticker import ScalarFormatter
for axis in [ax.xaxis, ax.yaxis]:
axis.set_major_formatter(ScalarFormatter())
ax = plt.subplot(111)
ax.set_xscale("log")
ax.set_xticks([30,50,100])
ax.set_xticklabels([30,50,100])
Liste
eltMultiples = [x for x in list if list.count(x)>1]
Nombre d’occurrences :
compte = {}.fromkeys(set(liste),0) for valeur in liste: compte[valeur] += 1
compte = dict([(k, liste.count(k)) for k in set(liste)])
supprimer les doublons en conservant l’ordre :
sorted(set(aa), key=lambda x: aa.index(x))
Annoter un plot
types = ['apple', 'orange', 'apple', 'pear', 'apple', 'orange', 'apple', 'pear'] x_coords = [10, 10, 5, 4, 3, 20, 19, 21] y_coords = [21, 23, 12, 21, 10, 20, 14, 2] for i,type in enumerate(types): x = x_coords[i] y = y_coords[i] plt.scatter(x, y, marker='x', color='red') plt.text(x+0.3, y+0.3, type, fontsize=9) plt.show()
Histogrammes
bin = plt.hist(nmesSB1,histtype='step')[1] plt.hist(nmesPlanets,bin,histtype='step',color='orange',label='Planets') plt.hist(nmesBD,bin,histtype='step',color='blue',label='BD') plt.hist(nmesSB1,bin,histtype='step',color='green',label='SB1') plt.legend() plt.show()