12  * The algorithm keeps track of the best, 2nd best & 3rd best min
22  * every new min and overwrites 2nd & 3rd choices. The same property
23  * holds for 2nd & 3rd best.
28 /* As time advances, update the 1st, 2nd, and 3rd choices. */
36 		 * Passed entire window without a new val so make 2nd  in minmax_subwin_update()
37 		 * choice the new val & 3rd choice the new 2nd choice.  in minmax_subwin_update()
38 		 * we may have to iterate this since our 2nd choice  in minmax_subwin_update()
43 		m->s[1] = m->s[2];  in minmax_subwin_update()
44 		m->s[2] = *val;  in minmax_subwin_update()
47 			m->s[1] = m->s[2];  in minmax_subwin_update()
48 			m->s[2] = *val;  in minmax_subwin_update()
53 		 * so take a 2nd choice from the 2nd quarter of the window.  in minmax_subwin_update()
55 		m->s[2] = m->s[1] = *val;  in minmax_subwin_update()
56 	} else if (unlikely(m->s[2].t == m->s[1].t) && dt > win/2) {  in minmax_subwin_update()
61 		m->s[2] = *val;  in minmax_subwin_update()
66 /* Check if new measurement updates the 1st, 2nd or 3rd choice max. */
72 	    unlikely(val.t - m->s[2].t > win))	  /* nothing left in window? */  in minmax_running_max()
76 		m->s[2] = m->s[1] = val;  in minmax_running_max()
77 	else if (unlikely(val.v >= m->s[2].v))  in minmax_running_max()
78 		m->s[2] = val;  in minmax_running_max()
84 /* Check if new measurement updates the 1st, 2nd or 3rd choice min. */
90 	    unlikely(val.t - m->s[2].t > win))	  /* nothing left in window? */  in minmax_running_min()
94 		m->s[2] = m->s[1] = val;  in minmax_running_min()
95 	else if (unlikely(val.v <= m->s[2].v))  in minmax_running_min()
96 		m->s[2] = val;  in minmax_running_min()