scoring.py 文件源码

def expect_margin(predictions:np.ndarray,answer:np.ndarray):
    predict_sign=np.sign(predictions)
    answer_sign = np.sign(answer)

    margin_array=[]
    for m in range(answer.shape[0]):
        row=[]
        for n in range(answer.shape[1]):
            a=answer[m,n]
            p = predictions[m,n]
            p_s=predict_sign[m,n]
            a_s=answer_sign[m,n]
            if p_s==a_s :
                row.append(min(abs(a),abs(p)))
            # elif p_s!=a_s or p==0:
            #   row.append(-1*(abs(a)+abs(p)))
            else:
                #row.append(-1*abs(a))
                row.append(-1 * (abs(a) + abs(p)))
        margin_array.append(row)
    margin_array=np.array(margin_array)
    return np.sum(margin_array,0)