scipy.optimize.fmin 错误:使用序列设置数组元素

Question

我试图通过找到误差值最低的参数来拟合sin函数。

下面是我的代码：

import numpy as np
import scipy.optimize as opt
from scipy.optimize import leastsq
import matplotlib.pyplot as plt
def func_model(x, para):
''' Model: y = a*sin(2*k*pi*x+theta)'''
a, k, theta = para
return a*np.sin(2*k*np.pi*x+theta)
def func_noise(x, para):
a, k, theta = para
return a*np.sin(2*k*np.pi*x+theta) + np.random.randn(100)
def func_error(para_guess):
'''error_func'''
error_sum = 0
x_seq = np.linspace(-2*np.pi, 0, 100)
para_fact = [10, 0.34, np.pi/6]
for x in x_seq:
error_value = (func_noise(x, para_fact)-func_model(x, para_guess))**2
error_sum = error_sum + error_value
return error_sum
para_guess_init = np.array([7, 0.2, 0])
solution = opt.fmin(func_error, para_guess_init) 
print(solution)

但它不起作用，并说了错误：使用序列设置数组

追踪：

File "", line 26, in <module>
solution = opt.fmin(func_error, para_guess_init)
File "C:UserssunAppDataLocalContinuumanaconda3libsite-packagesscipyoptimizeoptimize.py", line 408, in fmin
res = _minimize_neldermead(func, x0, args, callback=callback, **opts)
File "C:UserssunAppDataLocalContinuumanaconda3libsite-packagesscipyoptimizeoptimize.py", line 532, in _minimize_neldermead
fsim[k] = func(sim[k])
ValueError: setting an array element with a sequence.

有人可以帮我吗，提前谢谢

Answer 1

此最小化器期望标量函数评估最小化。

您的函数func_error返回大小为(100,)的向量。

比较您的生产线：

error_value = (func_noise(x, para_fact)-func_model(x, para_guess))**2

例如：

error_value = np.sum(np.square(
func_noise(x, para_fact)-func_model(x, para_guess)))

虽然我更喜欢(客观变化！

error_value = np.linalg.norm(
func_noise(x, para_fact)-func_model(x, para_guess))