Advertisement
Not a member of Pastebin yet?
Sign Up,
it unlocks many cool features!
- # Construction de l'approximation de Milstein
- # b ** 2 = b puissance 2
- Xm = X0 * np.ones(shape = (nbValeur, nbSerie))
- for i in range(0, nbValeur - 1, 1):
- Xm[i + 1, : ] = Xm[i, : ] * (1 + a * delta + b * deltaW[i, :] + 0.5 * b * b * (deltaW[i + 1, :]*deltaW[i + 1, : ]-delta))
- plt.plot(t, Xm)
- plt.title('Solution approx')
- plt.xlabel('temps (s)')
- plt.ylabel('solutions')
- plt.grid()
- plt.show()
Advertisement
Add Comment
Please, Sign In to add comment
Advertisement