

def CalculateModelPredictions(self, inCoeffs, inDataCacheDictionary):
    x_in = b['X']
    a = inCoeffs[0]
    b = inCoeffs[1]
    c = inCoeffs[2]
    try:
        temp = (((4.0 * a) * numpy.exp((((- 1.0) * (x_in - b)) / c))) / numpy.square((1.0 + numpy.exp((((- 1.0) * (x_in - b)) / c)))))
        return self.extendedVersionHandler.GetAdditionalModelPredictions(temp, inCoeffs, inDataCacheDictionary, self)
    except:
        return (numpy.ones(len(inDataCacheDictionary['DependentData'])) * 1e+300)

dataset/ETHPy150Open zunzun/pyeq2/Models_2D/Peak.py LogisticPeak.CalculateModelPredictions/VarMisuse@16/27 `inDataCacheDictionary`->`b`