Table of Contents
Segment TreeResourcesDynamic Range Minimum QueriesRecursive ImplementationIterative ImplementationDynamic Range Sum QueriesRecursive ImplementationIterative ImplementationBinary Indexed TreeResourcesDynamic Range Sum QueriesImplementationFinding the -th ElementOrder Statistic TreeWith a BITWith a Segment TreeInversion CountingImplementationProblemsGeneralUSACOPoint Update Range Sum
Authors: Benjamin Qi, Dong Liu, Nathan Gong
Contributors: Andrew Wang, Pramana Saldin
Segment Tree, Binary Indexed Tree, and Order Statistic Tree (in C++).
Prerequisites
Table of Contents
Segment TreeResourcesDynamic Range Minimum QueriesRecursive ImplementationIterative ImplementationDynamic Range Sum QueriesRecursive ImplementationIterative ImplementationBinary Indexed TreeResourcesDynamic Range Sum QueriesImplementationFinding the -th ElementOrder Statistic TreeWith a BITWith a Segment TreeInversion CountingImplementationProblemsGeneralUSACOMost gold range query problems require you to support following tasks in time each on an array of size :
- Update the element at a single position (point).
- Query the sum of some consecutive subarray.
Both segment trees and binary indexed trees can accomplish this.
Segment Tree
A segment tree allows you to do point update and range query in time each for any associative operation, not just summation.
Resources
You can skip more advanced applications such as lazy propagation for now. They will be covered in platinum.
Resources | ||||
---|---|---|---|---|
CF EDU | basic operations, inversion counting | |||
CSA | Interactive updates. | |||
CPH | Same implementation as AICash below. | |||
CPC | See slides after union-find. Also introduces sqrt bucketing. | |||
cp-algo | "Advanced versions" are covered in Platinum. | |||
CF | simple implementation | |||
KACTL | similar to above |
Dynamic Range Minimum Queries
Focus Problem – try your best to solve this problem before continuing!
Recursive Implementation
Time Complexity:
C++
#include <algorithm>#include <iostream>#include <limits>#include <vector>using std::cout;using std::endl;using std::vector;/** A data structure that can answer point update & range min queries. */
Java
import java.io.*;import java.util.*;/** A data structure that can answer point update & range min queries. */public class MinSegmentTree {public final int len;private final int[] segtree; // index 0 is not in useprivate int combine(int a, int b) { return Math.min(a, b); }
Iterative Implementation
Though less extensible, this implementation is shorter and has a better constant factor. The ranges it operates on are also end-exclusive, unlike the previous one which is end-inclusive.
Time Complexity:
C++
#include <algorithm>#include <iostream>#include <limits>#include <vector>using std::cout;using std::endl;using std::vector;template <class T> class MinSegmentTree {
Java
import java.io.*;import java.util.*;/** A data structure that can answer point update & range minimum queries. */public class MinSegmentTree {private final int[] segtree;private final int len;public MinSegmentTree(int len) {this.len = len;
Python
class MinSegmentTree:"""A data structure that can answer point update & range minimum queries."""def __init__(self, len_: int):self.len = len_self.tree = [0] * (2 * len_)def set(self, ind: int, val: int) -> None:"""Sets the value at ind to val."""ind += self.len
Dynamic Range Sum Queries
Focus Problem – try your best to solve this problem before continuing!
Recursive Implementation
Time Complexity:
C++
Compared to the previous implementation, all we need to change are DEFAULT
and how we combine the elements.
#include <algorithm>#include <iostream>#include <limits>#include <vector>using std::cout;using std::endl;using std::vector;Code Snippet: Segment Tree (Click to expand)
Java
Compared to the previous implementation, all we need to change is
the way we combine the elements, the default value, and the data type
we use for the segment tree (from int
to long
).
import java.io.*;import java.util.*;public class SumSegmentTree {public final int len;private final long[] segtree;private long combine(long a, long b) { return a + b; }private void build(long[] arr, int at, int atLeft, int atRight) {
Iterative Implementation
Time Complexity:
C++
#include <iostream>#include <vector>using std::cout;using std::endl;using std::vector;Code Snippet: Segment Tree (Click to expand)int main() {
Java
import java.io.*;import java.util.*;public class SumSegmentTree {private final long[] segtree;private final int len;public SumSegmentTree(int len) {this.len = len;segtree = new long[len * 2];
Python
Compared to the previous implementation, all we need to change is the way we
aggregate values (from min()
to '+'), and change the initial value to 0.
Code Snippet: Segment Tree (Click to expand)arr_len, query_num = map(int, input().split())arr = list(map(int, input().split()))segtree = SumSegmentTree(arr_len)for i, v in enumerate(arr):segtree.set(i, v)
Binary Indexed Tree
The implementation is shorter than segment tree, but maybe more confusing at first glance.
Resources
Resources | ||||
---|---|---|---|---|
CSA | interactive | |||
CPH | similar to above | |||
cp-algo | also similar to above | |||
TC |
Dynamic Range Sum Queries
Implementation
C++
#include <cassert>#include <iostream>#include <vector>using std::cout;using std::endl;using std::vector;/*** Short for "binary indexed tree",
Java
import java.io.*;import java.util.*;/*** Short for "binary indexed tree",* this data structure supports point update and range sum* queries like a segement tree.*/public class BIT {private final long[] bit;
Python
class BIT:"""Short for "binary indexed tree",this data structure supports point update and range sumqueries like a segment tree."""def __init__(self, len_: int) -> None:self.bit = [0] * (len_ + 1)self.arr = [0] * len_
-th Element
Finding theSuppose that we want a data structure that supports all the operations as a
set
in C++ in addition to the following:
order_of_key(x)
: counts the number of elements in the set that are strictly less thanx
.find_by_order(k)
: similar tofind
, returns the iterator corresponding to thek
-th lowest element in the set (0-indexed).
Order Statistic Tree
Luckily, such a built-in data structure already exists in C++. However, it's only supported on GCC, so Clang users are out of luck.
Resources | ||||
---|---|---|---|---|
CF | ||||
CPH | brief overview with find_by_order and order_of_key | |||
KACTL | code |
With a BIT
However, if all updates are in the range , we can do the same thing with a BIT.
Resources | ||||
---|---|---|---|---|
CF | log N |
With a Segment Tree
Covered in Platinum.
Inversion Counting
Focus Problem – try your best to solve this problem before continuing!
Implementation
C++
Using an indexed set, we can solve this in just a few lines.
#include <bits/stdc++.h>using namespace std;#include <ext/pb_ds/assoc_container.hpp>using namespace __gnu_pbds;template <class T>using Tree =tree<T, null_type, less<T>, rb_tree_tag, tree_order_statistics_node_update>;int main() {
Note that if it were not the case that all elements of the input array were
distinct, then this code would be incorrect since Tree<int>
would remove
duplicates. Instead, we would use an indexed set of pairs
(Tree<pair<int,int>>
), where the first element of each pair would denote the
value while the second would denote the position of the value in the array.
Java
import java.io.*;import java.util.*;public class Main {private static final int MAX_ELEM = (int)1e7;public static void main(String[] args) {Kattio io = new Kattio();int testNum = io.nextInt();for (int t = 0; t < testNum; t++) {
Python
Code Snippet: BIT (Click to expand)MAX_ELEM = 10**7test_num = int(input())for _ in range(test_num):bit = BIT(MAX_ELEM + 1)input()arr_len = int(input())
Problems
Coordinate Compression
If the coordinates are large (say, up to ), then you should apply coordinate compression before using a BIT or segment tree (though sparse segment trees do exist).
General
Status | Source | Problem Name | Difficulty | Tags | |
---|---|---|---|---|---|
CSES | Easy | Show TagsPURS | |||
Kattis | Easy | Show TagsInversions, PURS | |||
CSES | Easy | Show TagsPURS | |||
CSES | Easy | Show TagsCoordinate Compress, PURS | |||
CF | Easy | Show TagsBinary Search, Offline, PURS | |||
CSES | Easy | Show TagsCoordinate Compress, PURS | |||
CSES | Normal | Show TagsOffline, PURS |
USACO
Status | Source | Problem Name | Difficulty | Tags | |
---|---|---|---|---|---|
Gold | Easy | Show TagsInversions, PURS | |||
Gold | Easy | Show TagsInversions, PURS | |||
Gold | Easy | Show TagsInversions, PURS | |||
Gold | Easy | Show TagsPURS | |||
Platinum | Easy | Show TagsInversions, PURS | |||
Old Gold | Hard | Show TagsPURS |
A hint regarding Sleepy Cow Sort: There is only one correct output.
Module Progress:
Join the USACO Forum!
Stuck on a problem, or don't understand a module? Join the USACO Forum and get help from other competitive programmers!