有谁能给我一些建议,如何用Python解决一个实现了延时的ODE?我好像不知道怎么用scipy.integrate.odeint. 我要找的应该是:
# the constants in the equation
b = 1/50
d = 1/75
a = 0.8
G = 10 ** (-2)
tau = 0.5
u = [b, d, tau, a, G]
# enter initial conditions
N0 = 0.1
No0 = 10
w = [N0, No0]
def logistic(w, t, u):
N, No = w
b, d, tau, a, G = u
dNdt = b * (No(t) - N(t) ) * (N(t) / No(t) ) - d * N(t - tau)
dNodt = G * (a * No(t) - N(t) ) * (N(t) / No(t) )
return [dNdt, dNodt]
# create timescale
# create timescale
stoptime = 1000.0
numpoints = 10000
t = np.linspace(0, stoptime, numpoints)
# in my previous code I would use scipy.integrate.odeint here to integrate my
# equations, but with a time-delay that doesn't work (I think)
soln = ...
其中N(t)、N(t-tau)等表示函数的时间参数。有没有一个好的库来解决这些类型的方程?先谢谢你!在
我是JiTCDDE的作者,这本书可以解延迟微分方程,并且大部分类似于{}。你可以用
pip3 install jitcdde
安装它。据我所知,其他现有的用于Python的DDE库要么已损坏,要么基于不推荐的依赖项。在以下代码将集成您的问题:
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