使用lmfit在python中的卡方最小化

时间:2013-01-16 14:52:50

标签: python chi-squared

我正在尝试使用python和lmfit模块进行多参数拟合。我一直在关注显示here的示例作为我的代码的基础。据我了解代码,我应该能够进行最小二乘拟合,前提是我正确定义了我的目标函数(给出了残差)并为其提供了正确的参数。

这是我目前的目标函数:

# Define objective function: each data point has a different
# objective function which is defined by the model method
# the objective function returns the array to be minimized
def objfunc(params,trans,sum_in,sum_out,data):
    """ model fit using branching ratios and resonance strength
        then subtract data """
    model = fit_model(params,trans,sum_in,sum_out)

    return model - data

其中fit_model(args*)方法由

定义
def fit_model(params,trans,sum_in,sum_out):
    """ model the transition based upon the input string trans
        using parameter convention for the branching """
    model = []

    # The amplitude: technically the resonance strength term
    # here it gives the number of resonant decays
    amp = params['amp'].value

    # For each transition we want to retrieve the parameter values
    # for the branching ratios and evaluate the new value for
    # the fit (of that transition). The easiest way to do this is
    # to store the braching ratios with the same notation used
    # previously, and to explicity call those values using the
    # 'params.['']value' method
    for i in range(len(trans)):

        # Employs the termvalue() method to evalueate the branching
        # and efficiency values
        model.append( str(amp * termValue(trans[i]) + amp * termValue(sum_in[i]) - amp * termValue(sum_out[i])))

    return np.array(model,dtype='float64')

这给了我期望得到的结果:numpy.ndarray我的数据长度。我遇到的问题是,当我尝试用

最小化卡方拟合时
result = minimize(objfunc,params,args=(trans,sum_in,sum_out,data)) 

我收到错误消息:

File "path/chisquare.py", line 94, in <module>
    result = minimize(objfunc,params,args=(trans,sum_in,sum_out,data))
  File "/usr/local/lib/python2.7/dist-packages/lmfit-0.7-py2.7.egg/lmfit/minimizer.py", line 498, in minimize
    fitter.leastsq()
  File "/usr/local/lib/python2.7/dist-packages/lmfit-0.7-py2.7.egg/lmfit/minimizer.py", line 369, in leastsq
    lsout = scipy_leastsq(self.__residual, self.vars, **lskws)
  File "/usr/lib/python2.7/dist-packages/scipy/optimize/minpack.py", line 278, in leastsq
    raise TypeError('Improper input: N=%s must not exceed M=%s' % (n,m))
TypeError: Improper input: N=26 must not exceed M=25

我试图从lmfit源代码中找出这意味着什么,但这有点超出了我的理解范围。有谁知道如何解决这个错误?

由于

1 个答案:

答案 0 :(得分:1)

这个问题似乎是由于参数多于数据点引起的。检查了我的输入并解决了问题!