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62. Unique Paths

Description

There is a robot on an m x n grid. The robot is initially located at the top-left corner (i.e., grid[0][0]). The robot tries to move to the bottom-right corner (i.e., grid[m - 1][n - 1]). The robot can only move either down or right at any point in time.

Given the two integers m and n, return the number of possible unique paths that the robot can take to reach the bottom-right corner.

The test cases are generated so that the answer will be less than or equal to 2 * 109.

 

Example 1:

Input: m = 3, n = 7
Output: 28

Example 2:

Input: m = 3, n = 2
Output: 3
Explanation: From the top-left corner, there are a total of 3 ways to reach the bottom-right corner:
1. Right -> Down -> Down
2. Down -> Down -> Right
3. Down -> Right -> Down

 

Constraints:

  • 1 <= m, n <= 100

Solutions

Solution 1: Dynamic Programming

We define $f[i][j]$ to represent the number of paths from the top left corner to $(i, j)$, initially $f[0][0] = 1$, and the answer is $f[m - 1][n - 1]$.

Consider $f[i][j]$:

  • If $i > 0$, then $f[i][j]$ can be reached by taking one step from $f[i - 1][j]$, so $f[i][j] = f[i][j] + f[i - 1][j]$;
  • If $j > 0$, then $f[i][j]$ can be reached by taking one step from $f[i][j - 1]$, so $f[i][j] = f[i][j] + f[i][j - 1]$.

Therefore, we have the following state transition equation:

\[f[i][j] = \begin{cases} 1 & i = 0, j = 0 \\ f[i - 1][j] + f[i][j - 1] & \text{otherwise} \end{cases}\]

The final answer is $f[m - 1][n - 1]$.

The time complexity is $O(m \times n)$, and the space complexity is $O(m \times n)$. Here, $m$ and $n$ are the number of rows and columns of the grid, respectively.

We notice that $f[i][j]$ is only related to $f[i - 1][j]$ and $f[i][j - 1]$, so we can optimize the first dimension space and only keep the second dimension space, resulting in a time complexity of $O(m \times n)$ and a space complexity of $O(n)$.

  • class Solution {
    public int uniquePaths(int m, int n) {
        int[] f = new int[n];
        Arrays.fill(f, 1);
        for (int i = 1; i < m; ++i) {
            for (int j = 1; j < n; ++j) {
                f[j] += f[j - 1];
            }
        }
        return f[n - 1];
    }
}

  • class Solution {
public:
    int uniquePaths(int m, int n) {
        vector<int> f(n, 1);
        for (int i = 1; i < m; ++i) {
            for (int j = 1; j < n; ++j) {
                f[j] += f[j - 1];
            }
        }
        return f[n - 1];
    }
};

  • class Solution:
    def uniquePaths(self, m: int, n: int) -> int:
        # avoid setting dp[][] to 1 for i==0 or j==0 as initialization
        dp = [[1] * n for _ in range(m)]
        for i in range(1, m):
            for j in range(1, n):
                dp[i][j] = dp[i - 1][j] + dp[i][j - 1]
        return dp[-1][-1]

  • func uniquePaths(m int, n int) int {
	f := make([]int, n+1)
	for i := range f {
		f[i] = 1
	}
	for i := 1; i < m; i++ {
		for j := 1; j < n; j++ {
			f[j] += f[j-1]
		}
	}
	return f[n-1]
}

  • function uniquePaths(m: number, n: number): number {
    const f: number[] = Array(n).fill(1);
    for (let i = 1; i < m; ++i) {
        for (let j = 1; j < n; ++j) {
            f[j] += f[j - 1];
        }
    }
    return f[n - 1];
}


  • /**
 * @param {number} m
 * @param {number} n
 * @return {number}
 */
var uniquePaths = function (m, n) {
    const f = Array(n).fill(1);
    for (let i = 1; i < m; ++i) {
        for (let j = 1; j < n; ++j) {
            f[j] += f[j - 1];
        }
    }
    return f[n - 1];
};


  • impl Solution {
    pub fn unique_paths(m: i32, n: i32) -> i32 {
        let (m, n) = (m as usize, n as usize);
        let mut f = vec![1; n];
        for i in 1..m {
            for j in 1..n {
                f[j] += f[j - 1];
            }
        }
        f[n - 1]
    }
}

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