为什么我得到不正确的结果从scipy.optimize.fmin

Question

import pandas as pd
from scipy.optimize import fmin
data = pd.DataFrame({'DIV': [1,2,3]*3,
                     'MONTH': ['May','May','May','June','June','Jun','Jul','Jul','Jul'],
                     'C':[8]*9,
                     'U':[3,2,1]*3,
                     'S':[9]*9})
data.to_csv(r'C:UsersmbabskiDocumentsUnit Plan Summer 2016data_test.csv')
def return_array(x):
    return x.values
def mape(c,u,s,r): #returns an array of line level Mean Absolute Percentage Errors
    p = c + u * r
    m = abs(1.0-(p/s))
    return m
def e(c,u,s,r): #calculates average of the MAPEs
    return np.mean(mape(c,u,s,r))
for d in range(1,4):
    div_data = data[data.DIV==d]
    c = return_array(div_data.C)
    u = return_array(div_data.U)
    s = return_array(div_data.S)
    r0 = [[1.0]]
    t = fmin(e,r0,args=(c,u,s))
    print 'r:',t

优化已成功终止。
当前功能值:0.000000
迭代:29日
函数求值:58
r:[-69]。[br>优化成功终止。
当前功能值:0.000000
迭代:29日
函数求值:58
r:[-70]。[br>优化成功终止。
当前功能值:0.000000
迭代:29日
函数求值:58
r: [-71.]

为什么我得到r = -69， -70和-71?根据这些数据，我应该得到r = 0.333, 0.555和0.999

Answer 1

scipy.optimize.fmin将传递它试图最小化的值作为函数的第一个参数。如果将函数重写为

def e(r,c,u,s): #calculates average of the MAPEs
    return np.mean(mape(c,u,s,r))

你得到正确的结果

for d in range(1,4):
    div_data = data[data.DIV==d]
    c = return_array(div_data.C)
    u = return_array(div_data.U)
    s = return_array(div_data.S)
    r0 = [[1.0]]
    t = fmin(e,r0,args=(c,u,s))
    print 'r:',t

Optimization terminated successfully.
         Current function value: 0.000011
         Iterations: 16
         Function evaluations: 32
r: [ 0.33330078]
Optimization terminated successfully.
         Current function value: 0.000000
         Iterations: 15
         Function evaluations: 30
r: [ 0.5]
Optimization terminated successfully.
         Current function value: 0.000000
         Iterations: 10
         Function evaluations: 20
r: [ 1.]