hello-algo/en/codes/swift/chapter_dynamic_programming/min_path_sum.swift

124 lines
3.9 KiB
Swift

/**
* File: min_path_sum.swift
* Created Time: 2023-07-15
* Author: nuomi1 (nuomi1@qq.com)
*/
/* Minimum path sum: Brute force search */
func minPathSumDFS(grid: [[Int]], i: Int, j: Int) -> Int {
// If it's the top-left cell, terminate the search
if i == 0, j == 0 {
return grid[0][0]
}
// If the row or column index is out of bounds, return a + cost
if i < 0 || j < 0 {
return .max
}
// Calculate the minimum path cost from the top-left to (i-1, j) and (i, j-1)
let up = minPathSumDFS(grid: grid, i: i - 1, j: j)
let left = minPathSumDFS(grid: grid, i: i, j: j - 1)
// Return the minimum path cost from the top-left to (i, j)
return min(left, up) + grid[i][j]
}
/* Minimum path sum: Memoized search */
func minPathSumDFSMem(grid: [[Int]], mem: inout [[Int]], i: Int, j: Int) -> Int {
// If it's the top-left cell, terminate the search
if i == 0, j == 0 {
return grid[0][0]
}
// If the row or column index is out of bounds, return a + cost
if i < 0 || j < 0 {
return .max
}
// If there is a record, return it
if mem[i][j] != -1 {
return mem[i][j]
}
// The minimum path cost from the left and top cells
let up = minPathSumDFSMem(grid: grid, mem: &mem, i: i - 1, j: j)
let left = minPathSumDFSMem(grid: grid, mem: &mem, i: i, j: j - 1)
// Record and return the minimum path cost from the top-left to (i, j)
mem[i][j] = min(left, up) + grid[i][j]
return mem[i][j]
}
/* Minimum path sum: Dynamic programming */
func minPathSumDP(grid: [[Int]]) -> Int {
let n = grid.count
let m = grid[0].count
// Initialize dp table
var dp = Array(repeating: Array(repeating: 0, count: m), count: n)
dp[0][0] = grid[0][0]
// State transition: first row
for j in 1 ..< m {
dp[0][j] = dp[0][j - 1] + grid[0][j]
}
// State transition: first column
for i in 1 ..< n {
dp[i][0] = dp[i - 1][0] + grid[i][0]
}
// State transition: the rest of the rows and columns
for i in 1 ..< n {
for j in 1 ..< m {
dp[i][j] = min(dp[i][j - 1], dp[i - 1][j]) + grid[i][j]
}
}
return dp[n - 1][m - 1]
}
/* Minimum path sum: Space-optimized dynamic programming */
func minPathSumDPComp(grid: [[Int]]) -> Int {
let n = grid.count
let m = grid[0].count
// Initialize dp table
var dp = Array(repeating: 0, count: m)
// State transition: first row
dp[0] = grid[0][0]
for j in 1 ..< m {
dp[j] = dp[j - 1] + grid[0][j]
}
// State transition: the rest of the rows
for i in 1 ..< n {
// State transition: first column
dp[0] = dp[0] + grid[i][0]
// State transition: the rest of the columns
for j in 1 ..< m {
dp[j] = min(dp[j - 1], dp[j]) + grid[i][j]
}
}
return dp[m - 1]
}
@main
enum MinPathSum {
/* Driver Code */
static func main() {
let grid = [
[1, 3, 1, 5],
[2, 2, 4, 2],
[5, 3, 2, 1],
[4, 3, 5, 2],
]
let n = grid.count
let m = grid[0].count
// Brute force search
var res = minPathSumDFS(grid: grid, i: n - 1, j: m - 1)
print("Minimum path sum from the top-left corner to the bottom-right corner = \(res)")
// Memoized search
var mem = Array(repeating: Array(repeating: -1, count: m), count: n)
res = minPathSumDFSMem(grid: grid, mem: &mem, i: n - 1, j: m - 1)
print("Minimum path sum from the top-left corner to the bottom-right corner = \(res)")
// Dynamic programming
res = minPathSumDP(grid: grid)
print("Minimum path sum from the top-left corner to the bottom-right corner = \(res)")
// Space-optimized dynamic programming
res = minPathSumDPComp(grid: grid)
print("Minimum path sum from the top-left corner to the bottom-right corner = \(res)")
}
}