3154. Find Number of Ways to Reach the K-th Stair
Description
You are given a non-negative integer k
. There exists a staircase with an infinite number of stairs, with the lowest stair numbered 0.
Alice has an integer jump
, with an initial value of 0. She starts on stair 1 and wants to reach stair k
using any number of operations. If she is on stair i
, in one operation she can:
- Go down to stair
i - 1
. This operation cannot be used consecutively or on stair 0. - Go up to stair
i + 2jump
. And then,jump
becomesjump + 1
.
Return the total number of ways Alice can reach stair k
.
Note that it is possible that Alice reaches the stair k
, and performs some operations to reach the stair k
again.
Example 1:
Input: k = 0
Output: 2
Explanation:
The 2 possible ways of reaching stair 0 are:
- Alice starts at stair 1.
- Using an operation of the first type, she goes down 1 stair to reach stair 0.
- Alice starts at stair 1.
- Using an operation of the first type, she goes down 1 stair to reach stair 0.
- Using an operation of the second type, she goes up 20 stairs to reach stair 1.
- Using an operation of the first type, she goes down 1 stair to reach stair 0.
Example 2:
Input: k = 1
Output: 4
Explanation:
The 4 possible ways of reaching stair 1 are:
- Alice starts at stair 1. Alice is at stair 1.
- Alice starts at stair 1.
- Using an operation of the first type, she goes down 1 stair to reach stair 0.
- Using an operation of the second type, she goes up 20 stairs to reach stair 1.
- Alice starts at stair 1.
- Using an operation of the second type, she goes up 20 stairs to reach stair 2.
- Using an operation of the first type, she goes down 1 stair to reach stair 1.
- Alice starts at stair 1.
- Using an operation of the first type, she goes down 1 stair to reach stair 0.
- Using an operation of the second type, she goes up 20 stairs to reach stair 1.
- Using an operation of the first type, she goes down 1 stair to reach stair 0.
- Using an operation of the second type, she goes up 21 stairs to reach stair 2.
- Using an operation of the first type, she goes down 1 stair to reach stair 1.
Constraints:
0 <= k <= 109
Solutions
Solution 1: Memoization Search
We design a function dfs(i, j, jump)
, which represents the number of ways to reach the $k$th step when currently at the $i$th step, having performed $j$ operation 1's and jump
operation 2's. The answer is dfs(1, 0, 0)
.
The calculation process of the function dfs(i, j, jump)
is as follows:
If $i > k + 1$, since we cannot go down twice in a row, we cannot reach the $k$th step again, so return $0$;
If $i = k$, it means that we have reached the $k$th step. The answer is initialized to $1$, and then continue to calculate;
If $i > 0$ and $j = 0$, it means that we can go down, recursively calculate
dfs(i - 1, 1, jump)
;Recursively calculate
dfs(i + 2^{jump}, 0, jump + 1)
, and add it to the answer.
To avoid repeated calculations, we use memoization search to save the calculated states.
The time complexity is $O(\log^2 k)$, and the space complexity is $O(\log^2 k)$.
Python3
class Solution:
def waysToReachStair(self, k: int) -> int:
@cache
def dfs(i: int, j: int, jump: int) -> int:
if i > k + 1:
return 0
ans = int(i == k)
if i > 0 and j == 0:
ans += dfs(i - 1, 1, jump)
ans += dfs(i + (1 << jump), 0, jump + 1)
return ans
return dfs(1, 0, 0)
Java
class Solution {
private Map<Long, Integer> f = new HashMap<>();
private int k;
public int waysToReachStair(int k) {
this.k = k;
return dfs(1, 0, 0);
}
private int dfs(int i, int j, int jump) {
if (i > k + 1) {
return 0;
}
long key = ((long) i << 32) | jump << 1 | j;
if (f.containsKey(key)) {
return f.get(key);
}
int ans = i == k ? 1 : 0;
if (i > 0 && j == 0) {
ans += dfs(i - 1, 1, jump);
}
ans += dfs(i + (1 << jump), 0, jump + 1);
f.put(key, ans);
return ans;
}
}
C++
class Solution {
public:
int waysToReachStair(int k) {
unordered_map<long long, int> f;
auto dfs = [&](this auto&& dfs, int i, int j, int jump) -> int {
if (i > k + 1) {
return 0;
}
long long key = ((long long) i << 32) | jump << 1 | j;
if (f.contains(key)) {
return f[key];
}
int ans = i == k ? 1 : 0;
if (i > 0 && j == 0) {
ans += dfs(i - 1, 1, jump);
}
ans += dfs(i + (1 << jump), 0, jump + 1);
f[key] = ans;
return ans;
};
return dfs(1, 0, 0);
}
};
Go
func waysToReachStair(k int) int {
f := map[int]int{}
var dfs func(i, j, jump int) int
dfs = func(i, j, jump int) int {
if i > k+1 {
return 0
}
key := (i << 32) | jump<<1 | j
if v, has := f[key]; has {
return v
}
ans := 0
if i == k {
ans++
}
if i > 0 && j == 0 {
ans += dfs(i-1, 1, jump)
}
ans += dfs(i+(1<<jump), 0, jump+1)
f[key] = ans
return ans
}
return dfs(1, 0, 0)
}
TypeScript
function waysToReachStair(k: number): number {
const f: Map<bigint, number> = new Map();
const dfs = (i: number, j: number, jump: number): number => {
if (i > k + 1) {
return 0;
}
const key: bigint = (BigInt(i) << BigInt(32)) | BigInt(jump << 1) | BigInt(j);
if (f.has(key)) {
return f.get(key)!;
}
let ans: number = 0;
if (i === k) {
ans++;
}
if (i > 0 && j === 0) {
ans += dfs(i - 1, 1, jump);
}
ans += dfs(i + (1 << jump), 0, jump + 1);
f.set(key, ans);
return ans;
};
return dfs(1, 0, 0);
}