class Solution {
public int maxEnvelopes(int[][] envelopes) {
if(envelopes == null || envelopes.length == 0 || envelopes[0].length == 0)return 0;
Arrays.sort(envelopes,new Comparator<int[]>() {
@Override
public int compare(int[] o1, int[] o2) {
if(o1[0] == o2[0])return o2[1] - o1[1];
return o1[0] - o2[0];
}
});
int max;
int res = 0;
for (int i = 1; i < envelopes.length; i++) {
max = 0;
for (int j = res; j >= 0; j--) {
if (envelopes[i][1] > envelopes[j][1]) {
max = j + 1;
res = Math.max(res, max);
break;
}
}
if( max==res || envelopes[i][1]<envelopes[max][1])
envelopes[max][1]=envelopes[i][1];
}
return res+1;
}
}
先按a从小到大进行排序,当a相同时,按b从大到小排序。然后求解b的最长递增子序列。
当前数arr[i]大于ends数组中所有的数(末尾的最大),我们会将arr[i]添加在ends数组中;否则在ends数组中二分查找第一个大于当前数的数且替换它。所以我们的做法会保证在a相等的情况下,b可以有一个最小值,这样可以摞相对多的数。以达更长的序列,同时也避免了a相同b不相同时摞在一起的情况。
private static class Node{
public int a;
public int b;
public Node(int a, int b) {
this.a = a;
this.b = b;
}
}
public static class MyComparator implements Comparator<Node>{
@Override
public int compare(Node o1, Node o2) {
if(o1.a == o2.a){
return o2.b - o1.b;
}else {
return o1.a - o2.a;
}
}
}
/**
* 最长递增子序列的OLogN方法
* @param envelopes
* @return
*/
public static int maxEnvelopes(int[][] envelopes) {
if(envelopes == null || envelopes.length == 0 || envelopes[0].length == 0)return 0;
Node[] nodes = new Node[envelopes.length];
for(int i = 0; i < envelopes.length; i++){
nodes[i] = new Node(envelopes[i][0],envelopes[i][1]);
}
Arrays.sort(nodes,0,nodes.length,new MyComparator());
int[] ends = new int[envelopes.length];
ends[0] = nodes[0].b;
int right = 0;
int l = 0,m = 0,r = 0;
int res = 1;
for(int i = 1; i < nodes.length; i++){
l = 0;
r = right;
while(l <= r){
m = l + (r-l)/2;
if(nodes[i].b > ends[m]){
l = m + 1;
}else {
r = m - 1;
}
}
right = Math.max(l,right);
ends[l] = nodes[i].b;
}
return right + 1;
}