def CalculateModelPredictions(self, inCoeffs, inDataCacheDictionary):
        x_in = inDataCacheDictionary['X'] # only need to perform this dictionary look-up once
        
        C = inCoeffs[0]
        T = inCoeffs[1]
        K = inCoeffs[2]

        try:
            temp = C * numpy.power(x_in, -1.0 * T) * numpy.exp(-1.0 * x_in / K)
            return self.extendedVersionHandler.GetAdditionalModelPredictions(temp, inCoeffs, inDataCacheDictionary, self)
        except:
            return numpy.ones(len(inDataCacheDictionary['DependentData'])) * 1.0E300
dataset/ETHPy150Open zunzun/pyeq2/Models_2D/Power.py/PowerLawExponentialCutoff.CalculateModelPredictions/original