def _gaussian_function ( self , datalength : int , values : np . ndarray , height : int , index : int ) -> np . ndarray : return height * np . exp ( - ( 1 / ( self . spread_number * datalength ) ) * ( values - ( ( datalength / self . function_number ) * index ) ) ** 2 )
python range step of gaussian distribtuion
i th Regression Model Gaussian
def _gaussian_function(self, datalength: int, values: np.ndarray,
                           height: int, index: int) -> np.ndarray:
        """
        i'th Regression Model Gaussian

        :param: len(x)
        :param: x values
        :param: height of gaussian
        :param: position of gaussian

        :return: gaussian bumps over domain
        """
        return height * np.exp(-(1 / (self.spread_number * datalength)) *
                               (values - ((datalength / self.function_number) * index)) ** 2)