def CalculateModelPredictions(self, inCoeffs, inDataCacheDictionary):
        x_in = inDataCacheDictionary['X'] # only need to perform this dictionary look-up once
        
        a = inCoeffs[0]
        b = inCoeffs[1]
        c = inCoeffs[2]
        d = inCoeffs[3]
        f = inCoeffs[4]

        try:
            temp = a * numpy.exp(-0.5 * numpy.power((numpy.log(x_in-f)-b) / c, d))
            return self.extendedVersionHandler.GetAdditionalModelPredictions(temp, inCoeffs, inDataCacheDictionary, self)
        except:
            return numpy.ones(len(inDataCacheDictionary['DependentData'])) / 1.0E300
dataset/ETHPy150Open zunzun/pyeq2/Models_2D/Peak.py/LogNormalA_ModifiedShifted.CalculateModelPredictions/operator `*` -> `/`