int tree[MAX_L]; void init(int node, int[] a, int start, int end) { if (start == end) { tree[node] = a[start]; return; } int mid = (start + end) / 2; int lnode = 2 * node; int rnode = 2 * node + 1; init(lnode, a
cout <<query(2,6,1,7,1); 输出: query [2,6] (1,7)1 query [2,6] (1,4)2 query [2,6] (1,2)4 query [2,6] (2,2)9//tree[9]=9 Max=9 query [2,6] (3,4)5//tree[5]=6 Max=9 query [2,6] (5,7)3 query [2,6] (5,6)6//tree[6]=99 Max=99 99 分析:查[...
tree[id].sum += (tree[id].right - tree[id].left + 1) * delta; tree[id].delta += delta; return; } if (tree[id].delta) // 下沉操作,向下维护 { tree[id * 2].sum += (tree[id * 2].right - tree[id * 2].left + 1) * tree[id].delta; tree[id * 2].delta += tree...
Thus, we are at a parent level, which means that we need to push down the logged childrenCache of this parent level toward our target step by step*/ if(b <= n[i].m) return query(i * 2, a, b); if(n[i].m < a) return query(i * 2 + 1, a, b); return query(i * 2...
result=seg_tree.query(seg_tree.root,1,4)print(f"更新后的区间和: {result}")# 输出:更新后的区间和:29 总结 线段树是一种高效处理区间查询的数据结构,通过构建树形结构,能够在对数时间内完成查询和更新操作。在Python中,我们可以利用类似上述示例的代码实现线段树,并根据实际问题定制查询和更新的操作。理解线段...
Python中的线段树(Segment Tree):高级数据结构解析 线段树是一种专用于处理区间查询的数据结构,在解决范围内的查询和更新操作时具有高效性能。在本文中,我们将深入讲解Python中的线段树,包括线段树的基本概念、构建、查询和更新操作,并使用代码示例演示线段树的使用。
MAXN = 5e5 + 10; typedef tree<ll, null_type, less_equal<ll>, rb_tree_tag, tree_order_statistics_node_update> TREE; ll a[MAXN], st[MAXN * 4], lazy[MAXN * 4]; ll F(ll a, ll b) { return a + b; } void build(ll n, ll l, ll r) { lazy[n] = 0; if (l ==...
Fenwick Tree BIT (Maybe this is same as above idk_) Order Statistic Tree Square root decomposition Tries etc.. Now I need to work optimally and can't spend time learning more about Fenwick, BIT, and other DS too. I wanted to ask are there kinds of range query questions which can't ...
{ tree[u].right = ++idx; tree[tree[u].right] = new Node(); } } void pushup(int u) { tree[u].val = tree[tree[u].left].val + tree[tree[u].right].val; } public int ping(int t) { update(1, 1, N, t, 1); return query(1, 1, N, Math.max(0, t - 3000), t)...
int height = segmentTree.query(L, R, 1, N, 1) + arr[1]; max = Math.max(max, height); res.add(max); segmentTree.update(L, R, height, 1, N, 1); } return res; } 这里的查询和更新操作将求和变为了取最大值,整体的代码框架没有一点变化。