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我正在尝试编写一个程序来计算基于日志实用程序和同时相关事件的最佳投注金额。

为了做到这一点，我正在尝试使用该numpy.optimize.fmin功能。anon我传递给它的函数可以工作并产生（希望）正确的输出，但是当numpy尝试优化函数时，我得到以下错误

s[i].append(f[i][0]*w[i][0] + f[i][1]*w[i][1])
IndexError: invalid index to scalar variable.

因为我不知道fmin，所以我不知道是什么导致了这个错误。

我的代码在下面，希望不是 tl;dr 但我不会怪你。

附录

def main():
     p = [[0.1,0.1,0.2,   0.2,0.1,0,   0.1,0.1,0.1]]
     w = [[5,4]]
     MaxLU(p,w,True)

def MaxLU(p, w, Push = False, maxIter = 10):
    #Maximises LU, using Scipy in built function
    if Push == True:
        anon = lambda f: -PushLogUtility(p, w, f)
    else:
        anon = lambda f: -LogUtility(p, w, f)
    #We use multiple random starts
    f = []
    LU = []
    for i in range(0,maxIter):
        start = np.random.rand(len(p))
        start = start / 5 * np.sum(start)
        f.append(optimize.fmin(anon, start)) #Error occurs in here!
        if Push == True:
            LU.append(PushLogUtility(p, w, f[-1]))
        else:
            LU.append(LogUtility(p, w, f[-1]))

    #Now find the index of the max LU and return that same index of f
    return f[LU.index(np.max(LU))]

def PushLogUtility(p,w,f):
    #Outputs log utility incoroporating pushes and dependent totals, money data
    #p : 9xk length vector of joint probabilities for each of the k games, p = [[p_(W_T W_M), p_(W_T P_M), p_(W_T L_M), p_(P_T W_M) ... ]]
    #w : 2xk matrix of odds where w = [[total odds, money odds] ... ]
    #f : 2xk matrix of bankroll percentages to bet, f = [[f_T, f_M] ... ]
    utility = 0
    k = len(p)
    s = k*[[]]
    for i in range(0,k):
        s[i].append(f[i][0]*w[i][0] + f[i][1]*w[i][1])
        s[i].append(f[i][0]*w[i][0])
        s[i].append(f[i][0]*w[i][0] - f[i][1])
        s[i].append(f[i][1]*w[i][1])
        s[i].append(0)
        s[i].append(-f[i][1])
        s[i].append(-f[i][0] - f[i][1])
        s[i].append(-f[i][0] - f[i][1])
        s[i].append(-f[i][0] - f[i][1])

    for i in range(0,9 ** k):
        l = de2ni(i) #Converts number to base 9
        if i == 0:
            l += int(math.ceil(k - 1 - math.log(i + 1,9))) * [0]
        else:
            l += int(math.ceil(k - 1 - math.log(i,9))) * [0]
        productTerm = np.prod([p[i][l[i]] for i in range(0,k)])
        sumTerm = np.sum([s[i][l[i]] for i in range(0,k)])
        utility = utility + productTerm * np.log(1 + sumTerm)
    return utility
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1 回答 1

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在这里你做：

   s[i].append(f[i][0]*w[i][0] + f[i][1]*w[i][1])

如果您查看类型，您会发现s[i]is a []、f[i]is0.104528和w[i]is [5,4]。然后您尝试f[i]第二次索引 - 这是不可能的并导致错误。

于 2013-07-30T14:06:16.913 回答