GaussClasses.py 文件源码

def switchcomp2(self, prev_para, prev_para2, curr_para):
        bet = 0
        ent = 6
        if prev_para.size == 12:
            distrec = np.finfo(np.float64).max
            indrec = [-1, -1]
            for i in xrange(2):
                for j in xrange(2):
                    if i == j:
                        continue
                    tempdist = np.linalg.norm(prev_para[bet:ent] - curr_para[6 * i + bet:6 * i + ent]) + np.linalg.norm(
                        prev_para[6 + bet:6 + ent] - curr_para[6 * j + bet:6 * j + ent]) \
                               + np.linalg.norm(
                        prev_para2[bet:ent] - curr_para[6 * i + bet:6 * i + ent]) + np.linalg.norm(
                        prev_para2[6 + bet:6 + ent] - curr_para[6 * j + bet:6 * j + ent])

                    if tempdist < distrec:
                        distrec = tempdist
                        indrec = [i, j]
            fin_para = np.concatenate(
                (curr_para[6 * indrec[0]:6 * indrec[0] + 6], curr_para[6 * indrec[1]:6 * indrec[1] + 6]))
        return fin_para