def predict_y(self, model, pos):
        """return the predict y of 'model' when epoch = pos
        
        Parameters
        ----------
        model: string
            name of the curve function model
        pos: int
            the epoch number of the position you want to predict

        Returns
        -------
        int:
            The expected matrix at pos
        """
        if model_para_num[model] == 2:
            y = all_models[model](pos, model_para[model][0], model_para[model][1])
        elif model_para_num[model] == 3:
            y = all_models[model](pos, model_para[model][0], model_para[model][1], model_para[model][2])
        elif model_para_num[model] == 4:
            y = all_models[model](pos, model_para[model][0], model_para[model][1], model_para[model][2], model_para[model][3])
        return y
def predict_y ( self , model , pos ) : if model_para_num [ model ] == 2 : y = all_models [ model ] ( pos , model_para [ model ] [ 0 ] , model_para [ model ] [ 1 ] ) elif model_para_num [ model ] == 3 : y = all_models [ model ] ( pos , model_para [ model ] [ 0 ] , model_para [ model ] [ 1 ] , model_para [ model ] [ 2 ] ) elif model_para_num [ model ] == 4 : y = all_models [ model ] ( pos , model_para [ model ] [ 0 ] , model_para [ model ] [ 1 ] , model_para [ model ] [ 2 ] , model_para [ model ] [ 3 ] ) return y
return the predict y of 'model' when epoch = pos
        
        Parameters
        ----------
        model: string
            name of the curve function model
        pos: int
            the epoch number of the position you want to predict

        Returns
        -------
        int:
            The expected matrix at pos