Python Scipy.optimize curve_fit函数错误与数组可能列表错误输出maxfev

所以我真的不明白我在这里做错了什么，我认为这和变量或循环之类的东西有关。我试着运行这个，除了曲线拟合函数，它只给出了一个maxfev误差，不管我给出了什么maxfev，它都给出了相同的误差

from numpy import *

from matplotlib.pyplot import *

from scipy.optimize import curve_fit

r = array([0.24/2, 0.30/2, 0.40/2, 0.48/2, 0.73/2])


def v(t,*p):
     return p[0]*tanh(9.81*t/p[0]) + p[1]

g = []
terr = array([0.005, 0.005, 0.01, 0.01, 0.015])
xerr = array([0.0005,0.0005,0.0005,0.0005,0.0005])/1000.0
vg = []
vgerr = []

for i in range(5):
gp = []
vgerrp = []
vgp = []
vgerrp = []
for n in range(4):
    gp = gp + [loadtxt(r'%iw-sz=%i.txt' % (n+1,i+1), skiprows=2)]
    gp[n][:,0] = gp[n][:,0]-gp[n][0,0]
    gp[n][:,1] = gp[n][:,1]/1000.0
    vgp = vgp + [zeros(len(gp[n][:,0]))]
    vgerrp = vgerrp + [zeros(len(gp[n][:,0]))]
g = g + [gp]
vg = vg + [vgp]
vgerr = vgerr + [vgerrp]

for i in range(5):
figure('ball size %i' % (i+1))
title('Water Velocity vs Time graph for ball size %i' % (i+1))
for n in range(4):
    subplot('41%i' % (n+1))
    xlabel('Time (s)')
    ylabel('Velocity (m/s)')
    time = zeros(len(vg[i][n]))
    vel = zeros(len(vg[i][n]))
    velerr = zeros(len(vg[i][n]))
    for k in range(len(vg[i][n])-1):
        vg[i][n][k] = (g[i][n][k+1,1]-g[i][n][k,1])/(g[i][n][k+1,0]-g[i][n][k,0])
        vgerr[i][n][k] = vg[i][n][k]*sqrt((sqrt(2)*xerr[i])**2/(g[i][n][k+1,1]-g[i][n][k,1])**2 + (sqrt(2)*terr[i])**2/(g[i][n][k+1,0]-g[i][n][k,0])**2)
        time[k] = float(g[i][n][k,0])
        vel[k] = float(vg[i][n][k])
        velerr[k] = float(vgerr[i][n][k])
        if k == len(vg[i][n])-1:
            vg[i][n][k+1] = vg[i][n][k]
            vgerr[i][n][k+1] = vgerr[i][n][k]
        if n == 0:
            col = 'ob'
        elif n == 1:
            col = 'or'
        elif n == 2:
            col = 'og'
        elif n == 3:
            col = 'oy'
        if vg[i][n][k] != 0:
            plot(g[i][n][k,0],vg[i][n][k], col)
            errorbar(g[i][n][k,0],vg[i][n][k], xerr = terr[i], yerr = vgerr[i][n][k], fmt='+r')
    fparam, fcov = curve_fit(v, time, vel, [0.01,0.0], velerr)
    t = arange(0,max(g[i][n][:,0]),0.01)
    plot(t,v(t, fparam[0]))

show()

我试着用相同的数据运行相同的代码，就像在不同的程序中运行数值一样，结果成功了：

from numpy import *
from matplotlib.pyplot import *
from scipy.optimize import curve_fit


def v(t,*p):
    return p[0]*tanh(9.81*t/p[0]) + p[1]

vel = array([0.06562 ,
0.07654 ,
0.0656 ,
0.06562 ,
0.05468 ,
0.07654 ,
0.0656 ,
0.06562 ,
0.0656 ,
0.07654 ,
0.06562 ,
0.0656 ,
0.06562 ,
0.07654 ,
0.0656 ,
0.06562 ,
0.0656 ,
0.06562 ,
0.07654 ,
0.0656 ,
0.06562 ,
0.07654 ,
0.06562 ,
0.0656 ,
0.0656 ,
0.07656 ,
0.0656 ,
0.06562 ,
0.0656 ,
0.07654 ,
0.06562 ,
0.0656 ,
0.06562 ,
0.07654 ,
0.0656 ,
0.06562 ,
0.0656 ,
0.07654 ,
0.06562 ,
0.0656 ,
0.07656 ,
0.0656 ,
0.0656 ,
0.06562 ,
0.0656 ,
0.06562 ,
0.07654 ,
0.06562 ,
0.0656 ,
0.0656 ,
0.06562 ,
0.07654 ,
0.06562 ,
0.0656 ,
0.06562 ,
0.0656 ,
0.0656 ,
0.07656 ,
0.0656 ,
0.06562 ,
0.0656 ,
0.0656 ,
0.07656 ,
0.0656 ,
0.06562 ,
0.0656 ,
0.06562 ,
0.0656 ,
0.0656 ,
0.06562 ,
0.0656 ,
0.06562])


velerr = array([0.00928008017207 ,
0.0108243998448 ,
0.00927725174823 ,
0.00928008017207 ,
0.00773293269077 ,
0.0108243998448 ,
0.00927725174823 ,
0.00928008017207 ,
0.00927725174823 ,
0.0108243998448 ,
0.00928008017207 ,
0.00927725174823 ,
0.00928008017207 ,
0.0108243998448 ,
0.00927725174823 ,
0.00928008017207 ,
0.00927725174823 ,
0.00928008017207 ,
0.0108243998448 ,
0.00927725174823 ,
0.00928008017207 ,
0.0108243998448 ,
0.00928008017207 ,
0.00927725174823 ,
0.00927725174823 ,
0.0108272282695 ,
0.00927725174823 ,
0.00928008017207 ,
0.00927725174823 ,
0.0108243998448 ,
0.00928008017207 ,
0.00927725174823 ,
0.00928008017207 ,
0.0108243998448 ,
0.00927725174823 ,
0.00928008017207 ,
0.00927725174823 ,
0.0108243998448 ,
0.00928008017207 ,
0.00927725174823 ,
0.0108272282695 ,
0.00927725174823 ,
0.00927725174823 ,
0.00928008017207 ,
0.00927725174823 ,
0.00928008017207 ,
0.0108243998448 ,
0.00928008017207 ,
0.00927725174823 ,
0.00927725174823 ,
0.00928008017207 ,
0.0108243998448 ,
0.00928008017207 ,
0.00927725174823 ,
0.00928008017207 ,
0.00927725174823 ,
0.00927725174823 ,
0.0108272282695 ,
0.00927725174823 ,
0.00928008017207 ,
0.00927725174823 ,
0.00927725174823 ,
0.0108272282695 ,
0.00927725174823 ,
0.00928008017207 ,
0.00927725174823 ,
0.00928008017207 ,
0.00927725174823 ,
0.00927725174823 ,
0.00928008017207 ,
0.00927725174823 ,
0.00928008017207])

time = array([0.0 ,
0.05 ,
0.1 ,
0.15 ,
0.2 ,
0.25 ,
0.3 ,
0.35 ,
0.4 ,
0.45 ,
0.5 ,
0.55 ,
0.6 ,
0.65 ,
0.7 ,
0.75 ,
0.8 ,
0.85 ,
0.9 ,
0.95 ,
1.0 ,
1.05 ,
1.1 ,
1.15 ,
1.2 ,
1.25 ,
1.3 ,
1.35 ,
1.4 ,
1.45 ,
1.5 ,
1.55 ,
1.6 ,
1.65 ,
1.7 ,
1.75 ,
1.8 ,
1.85 ,
1.9 ,
1.95 ,
2.0 ,
2.05 ,
2.1 ,
2.15 ,
2.2 ,
2.25 ,
2.3 ,
2.35 ,
2.4 ,
2.45 ,
2.5 ,
2.55 ,
2.6 ,
2.65 ,
2.7 ,
2.75 ,
2.8 ,
2.85 ,
2.9 ,
2.95 ,
3.0 ,
3.05 ,
3.1 ,
3.15 ,
3.2 ,
3.25 ,
3.3 ,
3.35 ,
3.4 ,
3.45 ,
3.5 ,
3.55])

fparam, fcov = curve_fit(v, time, vel, [0.01,0.0], velerr)

---

这就是为什么我不知道还需要做什么，然后保存数据并在其他程序中运行，有人能帮我吗？

回溯（最近一次调用）：文件“C:\Users\Luke\Desktop\Physics\PHY324\MotionsFluids\WMotions.py”，第61行fparam，fcov=curve\u fit（v，time，vel，[0.01,0.0]，velerr）文件“C:\Python27\lib\site packages\scipy\optimize\minpack.py”，曲线拟合中的第431行raise RUNTIMERROR（msg）RuntimeError:找不到最佳参数：函数调用次数已达到maxfev=600。我个人认为这是在我的代码中某个地方弄乱了外部函数，但我已尝试隔离所有内容。您的代码有缩进错误，因此我们无法运行，而您没有提供数据文件。无论如何，我认为您的数据和模型有问题。随着时间的推移，数据基本上是恒定的，有许多尖峰。