TypeError: function() 正好需要 2 个参数(1 个给定)(python)

Question

import numpy as np
import scipy.optimize as spo
def function(x,y):
    return (np.sin(x*y+y)*np.exp(-1*(x**2+y**2)))**-1

xi=[0,0]    
answer=spo.fmin(function,xi)
print 'the answer is', answer

我正在尝试最小化此功能。但是运行它会带来

TypeError: function() takes exactly 2 arguments (1 given)

Answer 1

scipy.optimize.fmin(func, x0, args=(), xtol=0.0001, ftol=0.0001, maxiter=None, maxfun=None, full_output=0, disp=1, retall=0, callback=None)

参数函数是可调用func(x,*args)

在这种情况下，fmin使用一个参数调用function - x(即xi(。第二个参数必须作为args参数传递。

xi = 0
args = (0,)
answer = spo.fmin(function, x0=xi, args=args)

http://docs.scipy.org/doc/scipy-0.16.0/reference/generated/scipy.optimize.fmin.html

Answer 2

您的意图是最小化 2 个以上的变量("x"、"y"(，还是只减少一个变量(将"y"作为额外参数(？

def fn1(x, y):
    # x is minimization variable
    # y is extra argument
    return (np.sin(x*y+y)*np.exp(-1*(x**2+y**2)))**-1
def fn2(xy):
    # xy is minimization variable; assumed to be 2 elements
    x,y = xy                                             
    return (np.sin(x*y+y)*np.exp(-1*(x**2+y**2)))**-1

fmin 个变量;失败

In [35]: optimize.fmin(fn1, x0=0, args=(0,))
Warning: Maximum number of function evaluations has been exceeded.
Out[35]: array([ 0.])

fmin 2 元素数组(x0 和函数(;返回 2 元素数组。

In [38]: optimize.fmin(fn2, x0=np.array([0,0]))
Optimization terminated successfully.
         Current function value: 2.227274
         Iterations: 64
         Function evaluations: 121
Out[38]: array([ 0.29782369,  0.62167083])