Quartz调度程序与设置cron(Quartz scheduler vs setting up cron)

 问题是cos(x)可能变为负数，然后cos(x) ^ n可能是未定义的。 插图： 
 
np.cos(90)
-0.44807361612917013
 
 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，它可以正常工作，例如a + b * np.cos(c * x + d) 。 然后情节如下： 
 
  
 
 代码可以在下面找到一些内联注释： 
 
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()

The problem is that cos(x) can become negative and then cos(x) ^ n can be undefined. Illustration:
 
np.cos(90)
-0.44807361612917013
 
and e.g.
 
np.cos(90) ** 1.7
nan
 
That causes the two error messages you receive. 
 
It works fine, if you modify your model, e.g. to a + b * np.cos(c * x + d). Then the plot looks as follows:
 
 
The code can be found below with some inline comments:
 
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()