Arithmetic Slices II - Subsequence
Problem
Given an integer array nums, return the number of all the arithmetic subsequences of nums.
A sequence of numbers is called arithmetic if it consists of at least three elements and if the difference between any two consecutive elements is the same.
- For example,
[1, 3, 5, 7, 9],[7, 7, 7, 7], and[3, -1, -5, -9]are arithmetic sequences. - For example,
[1, 1, 2, 5, 7]is not an arithmetic sequence.
A subsequence of an array is a sequence that can be formed by removing some elements (possibly none) of the array.
- For example,
[2,5,10]is a subsequence of[1,2,1,**2**,4,1,**5**,**10**].
The test cases are generated so that the answer fits in 32-bit integer.
Examples
Example 1:
Input:
nums = [2,4,6,8,10]
Output:
7
Explanation: All arithmetic subsequence slices are:
[2,4,6]
[4,6,8]
[6,8,10]
[2,4,6,8]
[4,6,8,10]
[2,4,6,8,10]
[2,6,10]
Example 2:
Input:
nums = [7,7,7,7,7]
Output:
16
Explanation: Any subsequence of this array is arithmetic.
Solution
Method 1 – DP with Hash Maps (Count by Difference)
Intuition
To count all arithmetic subsequences (length ≥ 3), we can use dynamic programming. For each pair of indices (j, i), if nums[i] - nums[j] = d, then any arithmetic subsequence ending at j with difference d can be extended by nums[i].
We use an array of hash maps, where f[i][d] is the number of arithmetic subsequences ending at index i with difference d (including pairs, i.e., length 2). We only count those of length ≥ 3 in the answer.
Approach
- For each index i, loop over all previous indices j < i.
- Compute the difference d = nums[i] - nums[j].
- The number of subsequences ending at j with difference d is f[j][d].
- All those can be extended by nums[i], so add f[j][d] to the answer.
- Also, every pair (nums[j], nums[i]) forms a new sequence of length 2, so increment f[i][d] by f[j][d] + 1.
- At the end, the answer is the total number of arithmetic subsequences of length ≥ 3.
Code
Python
from collections import defaultdict
from typing import List
class Solution:
def numberOfArithmeticSlices(self, nums: List[int]) -> int:
f = [defaultdict(int) for _ in nums]
ans = 0
for i, x in enumerate(nums):
for j, y in enumerate(nums[:i]):
d = x - y
ans += f[j][d]
f[i][d] += f[j][d] + 1
return ans
Java
import java.util.*;
class Solution {
public int numberOfArithmeticSlices(int[] nums) {
int n = nums.length;
Map<Long, Integer>[] f = new Map[n];
Arrays.setAll(f, k -> new HashMap<>());
int ans = 0;
for (int i = 0; i < n; ++i) {
for (int j = 0; j < i; ++j) {
long d = 1L * nums[i] - nums[j];
int cnt = f[j].getOrDefault(d, 0);
ans += cnt;
f[i].put(d, f[i].getOrDefault(d, 0) + cnt + 1);
}
}
return ans;
}
}
C++
#include <vector>
#include <unordered_map>
using namespace std;
class Solution {
public:
int numberOfArithmeticSlices(vector<int>& nums) {
int n = nums.size();
vector<unordered_map<long long, int>> f(n);
int ans = 0;
for (int i = 0; i < n; ++i) {
for (int j = 0; j < i; ++j) {
long long d = 1LL * nums[i] - nums[j];
int cnt = f[j][d];
ans += cnt;
f[i][d] += cnt + 1;
}
}
return ans;
}
};
Go
func numberOfArithmeticSlices(nums []int) int {
n := len(nums)
f := make([]map[int]int, n)
for i := range f {
f[i] = map[int]int{}
}
ans := 0
for i, x := range nums {
for j, y := range nums[:i] {
d := x - y
cnt := f[j][d]
ans += cnt
f[i][d] += cnt + 1
}
}
return ans
}
TypeScript
function numberOfArithmeticSlices(nums: number[]): number {
const n = nums.length;
const f: Map<number, number>[] = Array.from({ length: n }, () => new Map());
let ans = 0;
for (let i = 0; i < n; ++i) {
for (let j = 0; j < i; ++j) {
const d = nums[i] - nums[j];
const cnt = f[j].get(d) || 0;
ans += cnt;
f[i].set(d, (f[i].get(d) || 0) + cnt + 1);
}
}
return ans;
}
Complexity
- ⏰ Time complexity: O(n²). For each index i, we loop over all previous indices j < i.
- 🧺 Space complexity: O(n²). We store a hash map for each index, and in the worst case, each map can have up to O(n) entries.