0

下面显示的第一个代码块有效；我的问题是试图使该代码块适应我的问题（在其下方定义）。

我正在尝试使用 SCIPY 来最小化下面的功能chisq。整个代码基本上是一个函数链（比如expectperbin，调用一个分布函数来整合过来）；下面的代码有obsperbin、parameterguess、countperbin和 初始参数，所有这些都是预定义的。仅显示函数链的顶部：

from scipy.optimize import minimize
from scipy.stats import chisquare

def chisq( args ):
    ## first subscript [0] gives chi-squared value, [1] gives 0 ≤ p-value ≤ 1
    return chisquare( obsperbin , expectperbin( args ))[0]

def miniz( chisq , parameterguess ):
    ## optimization routine to minimize Chi Square (or negative p-value)
    globmin = minimize( chisq , parameterguess)
    while globmin.success == False:
        ## self-correcting mechanism if 'success test' fails

        try:
            globmin = minimize( chisq , parameterguess)
            print("ERROR:   MINIMIZE LOOPING AGAIN")
            break
        except globmin.success == True:
            print("TA DAA")
            break

    return globmin

res = miniz( chisq, [initial_mu , initial_sigma] ) ## FULL OPTIMIZED RESULT
print(res)

mu上面的代码找到最小化和的优化值sigma（给定每个初始猜测）chisq，并且它按预期工作。所以我现在试图概括定义多个分布的情况下的代码。我使用不可更改的函数输入pickdist来选择要计算的预定义分布expectperbin。我的尝试如下：

def chisq( pickdist , args ):
    obsperbin = countperbin( pickdist = pickdist )
    expperbin = expectperbin( pickdist , args )
    return chisquare( obsperbin , expectperbin( pickdist , args ))[0]

def miniz( pickdist ):
    if pickdist == 1:
        parameterguess = paramguess1
    elif pickdist == 2:
        parameterguess = paramguess2
    elif pickdist == 3:
        parameterguess = paramguess3
    else:
        raise ValueError(errmsg)
    globmin = minimize( chisq , parameterguess, args = (pickdist))
    return globmin

运行该代码会创建错误消息

ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

并在读取的代码行obsperbin = countperbin ...（从上，下chisq）和从下面读取的代码行中找到错误if pickdist == 1:

def countperbin( pickdist ):
## counts multiplicity of observed values per bin via dataset
if pickdist == 1:
    dataset = data
elif pickdist == 2:
    dataset = logdata
elif pickdist == 3:
    dataset = logdata
else:
    raise ValueError(errmsg)
## I can delete the code below if it's too long
bincount = []
    subintervals = binbounder( pickdist )
    for jndex in range(len( subintervals )):
        if jndex != len( subintervals ) - 1:
            summ = 0
            for value in dataset:
                if value > subintervals [ jndex ] and value <= subintervals [ jndex + 1 ]:
                    summ += 1
            bincount.append(summ)
        if jndex == len( subintervals ) - 1:
            pass
    return bincount

obsperbin1 = countperbin( 1 )
    ... ## rest not shown to keep post short but can add if requested

在阅读SO 上的这篇文章后，我尝试调试此代码，但没有成功。如何将错误消息告诉我的内容应用于我的函数？

4

0 回答 0