scipy.optimize.leastsq：不是一个正确的浮点数组

Question

我试图解决一个小玩具问题

import numpy as np
import scipy.optimize as opt

def f(a):
    return np.array([a+.2,a-.1])

opt.leastsq(f,2)

然而，它给了我一个错误

\site-packages\scipy\optimize\minpack.py in leastsq(func, x0, args, Dfun, full_output, col_deriv, ftol, xtol, gtol, maxfev, epsfcn, factor, diag)
    362             maxfev = 200*(n + 1)
    363         retval = _minpack._lmdif(func, x0, args, full_output, ftol, xtol,
--> 364                 gtol, maxfev, epsfcn, factor, diag)
    365     else:
    366         if col_deriv:

error: Result from function call is not a proper array of floats.

但我的功能f确实给了一个ndarray。

Answer 1

所以它需要一个类似数组的输入。这有效：

import numpy as np
import scipy.optimize as opt

def f(a):
    return np.array([a[0]+.2,a[0]-.1])

print opt.leastsq(f,[2])