jmimo.py 文件源码

def gen_WR_pilot_only(self, alpha_l1r = 0):
        """
        yT_a and x_a was prepared already. 
        Now, W_a is calculated using alpha and then, 
        decode data. 
        For linear regression, alpha_l1r should not be specified except 0.
        """

        yT_a = self.rx_p["yT_a"]
        x_a = self.rx_p["x_a"]

        # for alpha == 0, model is changed to linear regression.  
        if alpha_l1r == 0:
            model = "LinearRegression"
        else:
            model = self.model

        if model == "LinearRegression":
            lm = linear_model.LinearRegression()
        elif model == "ElasticNet":
            lm = linear_model.ElasticNet( alpha_l1r[0], alpha_l1r[1])
        else: # This is either Ridge or Lasso
            lm = getattr( linear_model, model)(alpha_l1r)

        lm.fit( yT_a, x_a)
        self.W_a = lm.coef_

        # print( "np.dot( W_a, H_a) =", np.dot( self.W_a, self.H_a))

        self.gen_Decoding()