曲线拟合与python错误

我正在尝试将数据拟合为(cos(x))^ n.理论上n的值为2,但我的数据应为1.7.当我定义拟合函数并尝试curve_fit时,出现错误

def f(x,a,b,c):
   return a+b*np.power(np.cos(x),c)

param, extras = curve_fit(f, x, y)

这是我的资料

x   y               error
90  3.3888756187    1.8408898986
60  2.7662844365    1.6632150903
45  2.137309503     1.4619540017
30  1.5256883339    1.2351875703
0   1.4665463518    1.2110104672

错误看起来像这样：

/usr/local/lib/python3.5/dist-packages/ipykernel_launcher.py:4:
RuntimeWarning: invalid value encountered in power after removing
the cwd from sys.path.

/usr/lib/python3/dist-packages/scipy/optimize/minpack.py:690:
OptimizeWarning: Covariance of the parameters could not be estimated
category=OptimizeWarning)

解决方法:

问题在于cos(x)可以变为负数,然后cos(x)^ n可以不确定.插图：

np.cos(90)
-0.44807361612917013

和例如

np.cos(90) ** 1.7
nan

这会导致您收到两条错误消息.

如果您修改模型,例如到a b * np.cos(c * x d).然后该图如下所示：

可以在下面找到一些内联注释的代码：

import numpy as np
import matplotlib.pyplot as plt
from scipy.optimize import curve_fit


def f(x, a, b, c, d):

    return a + b * np.cos(c * x + d)

# your data
xdata = [90, 60, 45, 30, 0]
ydata = [3.3888756187, 2.7662844365, 2.137309503, 1.5256883339, 1.4665463518]

# plot data
plt.plot(xdata, ydata, 'bo', label='data')

# fit the data
popt, pcov = curve_fit(f, xdata, ydata, p0=[3., .5, 0.1, 10.])

# plot the result
xdata_new = np.linspace(0, 100, 200)
plt.plot(xdata_new, f(xdata_new, *popt), 'r-', label='fit')
plt.legend(loc='best')
plt.show()

标签：scipy,curve-fitting,scientific-computing,function-fitting,python
来源： https://codeday.me/bug/20191026/1933871.html