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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def fitNorm_v2(self, specVals):
 """Fit the normalization given a set of spectral values that define a spectral shape. This version uses `scipy.optimize.fmin`. Parameters specVals : an array of (nebin values that define a spectral shape xlims : fit limits Returns ------- norm : float Best-fit normalization value """

        from scipy.optimize import fmin

        def fToMin(x): return self.__call__(specVals * x)
        result = fmin(fToMin, 0., disp=False, xtol=1e-6)
        return result