如何使用scipy odeint求解该微分方程? [英] How to solve this differential equation using scipy odeint?

问题描述

我正在尝试使用scipy odeint求解以下微分方程，但没有取得很大的成功:

I am trying to solve the following differential equation using scipy odeint without much success:

import numpy as np
from scipy.misc import derivative
from scipy.integrate import odeint

Imag = 16000.
w = 2*np.pi*60
tau = .05
theta = 1.52
phi = theta - np.radians(90)
t = np.linspace(0,.1,10000)
def Ip(t):
    return np.sqrt(2)*Imag*(np.sin(w*t+phi-theta)-np.exp(-t/tau)*np.sin(phi-theta))

B = lambda Ip: Ip/(53.05+0.55*abs(Ip))
def L(B):
    return derivative(B,Ip(t))*377.2

def dI(t):
    return derivative(Ip,t)

def f(y,t):
    Rb = 8.
    N = 240.
    Is = y[0]
    f0 = (1/(L(B)+0.002))*((dI(t)*L(B)/N)-Rb*y[0])
    return [f0]

yinit = [0]
sol = odeint(f,yinit,t)
print sol[:,0]

我一直收到以下错误:

odepack.error: Result from function call is not a proper array of floats.
ValueError: object too deep for desired array
odepack.error: Result from function call is not a proper array of floats.

我应该怎么做才能正确运行脚本?

What should I do to run the script without errors?

推荐答案

此功能有问题:

def L(B):
    return derivative(B,Ip(t))*377.2

请注意，t指的是之前定义的全局变量，它是一个numpy数组.我认为您需要重新考虑如何定义函数及其参数-t是否也应作为L的参数?实际上，f返回一个包含数组的列表，即使其第一个参数包含单个元素也是如此:

Note that t refers to the global variable defined earlier, which is a numpy array. I think you need to rethink how you define your functions and their arguments--should t also be an argument to L? As it is, f returns a list containing an array, even when its first argument contains a single element:

In [10]: f([1], 0)
Out[10]: 
[array([ -2.28644086e+10,  -2.28638809e+10,  -2.28633064e+10, ...,
        -1.80290012e+09,  -1.80271510e+09,  -1.80258446e+09])]

这将导致odeint损坏.

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