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hello-algo/en/codes/python/chapter_dynamic_programming/min_path_sum.py

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"""
File: min_path_sum.py
Created Time: 2023-07-04
Author: krahets (krahets@163.com)
"""
from math import inf
def min_path_sum_dfs(grid: list[list[int]], i: int, j: int) -> int:
"""Minimum path sum: Brute force search"""
# If it's the top-left cell, terminate the search
if i == 0 and j == 0:
return grid[0][0]
# If the row or column index is out of bounds, return a +∞ cost
if i < 0 or j < 0:
return inf
# Calculate the minimum path cost from the top-left to (i-1, j) and (i, j-1)
up = min_path_sum_dfs(grid, i - 1, j)
left = min_path_sum_dfs(grid, i, j - 1)
# Return the minimum path cost from the top-left to (i, j)
return min(left, up) + grid[i][j]
def min_path_sum_dfs_mem(
grid: list[list[int]], mem: list[list[int]], i: int, j: int
) -> int:
"""Minimum path sum: Memoized search"""
# If it's the top-left cell, terminate the search
if i == 0 and j == 0:
return grid[0][0]
# If the row or column index is out of bounds, return a +∞ cost
if i < 0 or j < 0:
return inf
# 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
up = min_path_sum_dfs_mem(grid, mem, i - 1, j)
left = min_path_sum_dfs_mem(grid, mem, i, 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]
def min_path_sum_dp(grid: list[list[int]]) -> int:
"""Minimum path sum: Dynamic programming"""
n, m = len(grid), len(grid[0])
# Initialize dp table
dp = [[0] * m for _ in range(n)]
dp[0][0] = grid[0][0]
# State transition: first row
for j in range(1, m):
dp[0][j] = dp[0][j - 1] + grid[0][j]
# State transition: first column
for i in range(1, n):
dp[i][0] = dp[i - 1][0] + grid[i][0]
# State transition: the rest of the rows and columns
for i in range(1, n):
for j in range(1, m):
dp[i][j] = min(dp[i][j - 1], dp[i - 1][j]) + grid[i][j]
return dp[n - 1][m - 1]
def min_path_sum_dp_comp(grid: list[list[int]]) -> int:
"""Minimum path sum: Space-optimized dynamic programming"""
n, m = len(grid), len(grid[0])
# Initialize dp table
dp = [0] * m
# State transition: first row
dp[0] = grid[0][0]
for j in range(1, m):
dp[j] = dp[j - 1] + grid[0][j]
# State transition: the rest of the rows
for i in range(1, n):
# State transition: first column
dp[0] = dp[0] + grid[i][0]
# State transition: the rest of the columns
for j in range(1, m):
dp[j] = min(dp[j - 1], dp[j]) + grid[i][j]
return dp[m - 1]
"""Driver Code"""
if __name__ == "__main__":
grid = [[1, 3, 1, 5], [2, 2, 4, 2], [5, 3, 2, 1], [4, 3, 5, 2]]
n, m = len(grid), len(grid[0])
# Brute force search
res = min_path_sum_dfs(grid, n - 1, m - 1)
print(f"The minimum path sum from the top-left to the bottom-right corner is {res}")
# Memoized search
mem = [[-1] * m for _ in range(n)]
res = min_path_sum_dfs_mem(grid, mem, n - 1, m - 1)
print(f"The minimum path sum from the top-left to the bottom-right corner is {res}")
# Dynamic programming
res = min_path_sum_dp(grid)
print(f"The minimum path sum from the top-left to the bottom-right corner is {res}")
# Space-optimized dynamic programming
res = min_path_sum_dp_comp(grid)
print(f"The minimum path sum from the top-left to the bottom-right corner is {res}")