def CalculateModelPredictions(self, inCoeffs, inDataCacheDictionary):
        x_in = inDataCacheDictionary['X'] # only need to perform this dictionary look-up once

        Gb = inCoeffs[0]
        mu = inCoeffs[1]
        B = inCoeffs[2]
        Vbmax = inCoeffs[3]
        sigma_b = inCoeffs[4]

        try:
            temp = Gb * numpy.power(x_in / mu, numpy.log(mu/x_in)/(B*B)) + (Vbmax * x_in) / (x_in + sigma_b)
            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/Hamilton.CalculateModelPredictions/original