已成功将复杂的 Matlab 代码转换为 Python，如何将代码转换为运行？

Question

这个问题是我上一个问题的后续问题：

我已经手动转换了Matlab代码。我正在从终端使用 MAC OS 和运行ning Python。但是我如何运行下面的代码，对于 N 的某个值，其中 N 是偶数？我应该得到一个图表（由情节代码指定）。

当我按原样运行时，我什么也得不到。

我的代码如下：

import numpy as np
import matplotlib.pyplot as plt
from scipy.integrate import odeint

def Array(N):
    K00 = np.logspace(0,3,101,10)
    len1 = len(K00)
    y0 = [0]*(3*N/2+3)
    S = [np.zeros((len1,1)) for kkkk in range(N/2+1)]
    KS = [np.zeros((len1,1)) for kkkk in range(N/2)]
    PS = [np.zeros((len1,1)) for kkkk in range(N/2)]
    Splot = [np.zeros((len1,1)) for kkkk in range(N/2+1)]
    KSplot = [np.zeros((len1,1)) for kkkk in range(N/2)]
    PSplot = [np.zeros((len1,1)) for kkkk in range(N/2)]
    Kplot = np.zeros((len1,1))
    Pplot = np.zeros((len1,1))

    for series in range(0,len1):
        K0 = K00[series]
        Q = 10
        r1 = 0.0001
        r2 = 0.001
        d = 0.001
        a = 0.001
        k = 0.999
        P0 = 1
        S10 = 1e5
        tf = 1e10
        time = np.linspace(0,tf,len1)
        y0[0] = S10
        y0[3*N/2+1] = K0
        y0[3*N/2+2] = P0
        for i in range(1,3*N/2+1):
            y0[i] = 0

        [t,y] = odeint(EqnsArray,y0,time, mxstep = 5000)

        for alpha in range(0,(N/2+1)):
            S[alpha] = y[:,alpha]
        for beta in range((N/2)+1,N+1):
            KS[beta-N/2-1] = y[:,beta]
        for gamma in range(N+1,3*N/2+1):
            PS[gamma-N-1] = y[:,gamma]

        for alpha in range(0,(N/2+1)):
            Splot[alpha][series] = y[len1-1,alpha]
        for beta in range((N/2)+1,N+1):
            KSplot[beta-N/2-1][series] = y[len1-1,beta]
        for gamma in range(N+1,3*N/2+1):
            PSplot[gamma-N-1][series] = y[len1-1,gamma]

        for alpha in range(0,(N/2+1)):
            u1 = u1 + Splot[alpha]
        for beta in range((N/2)+1,N+1):
            u2 = u2 + KSplot[beta-N/2-1]
        for gamma in range(N+1,3*N/2+1):
            u3 = u3 + PSplot[gamma-N-1]

        K = soln[:,3*N/2+1]
        P = soln[:,3*N/2+2]
        Kplot[series] = soln[len1-1,3*N/2+1]
        Pplot[series] = soln[len1-1,3*N/2+2]
        utot = u1+u2+u3

    #Plot
    plt.plot(np.log10(K00),utot)
    plt.show()

def EqnsArray(y,t):
    for alpha in range(0,(N/2+1)):
        S[alpha] = y[alpha]
    for beta in range((N/2)+1,N+1):
        KS[beta-N/2-1] = y[beta]
    for gamma in range(N+1,3*N/2+1):
        PS[gamma-N-1] = y[gamma]
    K = y[3*N/2+1]
    P = y[3*N/2+2]

    # The model equations
    ydot = np.zeros((3*N/2+3,1))
    B = range((N/2)+1,N+1)
    G = range(N+1,3*N/2+1)
    runsumPS = 0
    runsum1 = 0
    runsumKS = 0
    runsum2 = 0

    for m in range(0,N/2):
        runsumPS = runsumPS + PS[m]
        runsum1 = runsum1 + S[m+1]
        runsumKS = runsumKS + KS[m]
        runsum2 = runsum2 + S[m]
        ydot[B[m]] = a*K*S[m]-(d+k+r1)*KS[m]

    for i in range(0,N/2-1):
        ydot[G[i]] = a*P*S[i+1]-(d+k+r1)*PS[i]

    for p in range(1,N/2):
        ydot[p] = -S[p]*(r1+a*K+a*P)+k*KS[p-1]+d*(PS[p-1]+KS[p])

    ydot[0] = Q-(r1+a*K)*S[0]+d*KS[0]+k*runsumPS
    ydot[N/2] = k*KS[N/2-1]-(r2+a*P)*S[N/2]+d*PS[N/2-1]
    ydot[G[N/2-1]] = a*P*S[N/2]-(d+k+r2)*PS[N/2-1]
    ydot[3*N/2+1] = (d+k+r1)*runsumKS-a*K*runsum2
    ydot[3*N/2+2] = (d+k+r1)*(runsumPS-PS[N/2-1])- \
                    a*P*runsum1+(d+k+r2)*PS[N/2-1]

    ydot_new = []
    for j in range(0,3*N/2+3):
        ydot_new.extend(ydot[j])
    return ydot_new

Answer 1

您必须调用您的函数，例如：

Array(12)

您必须在代码末尾添加此内容。

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