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Add Java and C++ code for the chapter of DP.

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krahets
2023-07-11 01:08:26 +08:00
parent 465dafe9ec
commit ad0fd45cfb
9 changed files with 494 additions and 19 deletions
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10
codes/python/chapter_dynamic_programming/knapsack.py
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@ -5,7 +5,7 @@ Author: Krahets (krahets@163.com)
"""
def knapsack_dfs(wgt, val, i, c):
def knapsack_dfs(wgt: list[int], val: list[int], i: int, c: int) -> int:
"""0-1 背包：暴力搜索"""
# 若已选完所有物品或背包无容量，则返回价值 0
if i == 0 or c == 0:
@ -20,7 +20,9 @@ def knapsack_dfs(wgt, val, i, c):
return max(no, yes)
def knapsack_dfs_mem(wgt, val, mem, i, c):
def knapsack_dfs_mem(
wgt: list[int], val: list[int], mem: list[list[int]], i: int, c: int
) -> int:
"""0-1 背包：记忆化搜索"""
# 若已选完所有物品或背包无容量，则返回价值 0
if i == 0 or c == 0:
@ -39,7 +41,7 @@ def knapsack_dfs_mem(wgt, val, mem, i, c):
return mem[i][c]
def knapsack_dp(wgt, val, cap):
def knapsack_dp(wgt: list[int], val: list[int], cap: int) -> int:
"""0-1 背包：动态规划"""
n = len(wgt)
# 初始化 dp 表
@ -56,7 +58,7 @@ def knapsack_dp(wgt, val, cap):
return dp[n][cap]
def knapsack_dp_comp(wgt, val, cap):
def knapsack_dp_comp(wgt: list[int], val: list[int], cap: int) -> int:
"""0-1 背包：状态压缩后的动态规划"""
n = len(wgt)
# 初始化 dp 表

18
codes/python/chapter_dynamic_programming/min_path_sum.py
View File

@ -7,7 +7,7 @@ Author: Krahets (krahets@163.com)
from math import inf
def min_path_sum_dfs(grid, i, j):
def min_path_sum_dfs(grid: list[list[int]], i: int, j: int) -> int:
"""最小路径和：暴力搜索"""
# 若为左上角单元格，则终止搜索
if i == 0 and j == 0:
@ -22,7 +22,9 @@ def min_path_sum_dfs(grid, i, j):
return min(left, up) + grid[i][j]
def min_path_sum_dfs_mem(grid, mem, i, j):
def min_path_sum_dfs_mem(
grid: list[list[int]], mem: list[list[int]], i: int, j: int
) -> int:
"""最小路径和：记忆化搜索"""
# 若为左上角单元格，则终止搜索
if i == 0 and j == 0:
@ -41,7 +43,7 @@ def min_path_sum_dfs_mem(grid, mem, i, j):
return mem[i][j]
def min_path_sum_dp(grid):
def min_path_sum_dp(grid: list[list[int]]) -> int:
"""最小路径和：动态规划"""
n, m = len(grid), len(grid[0])
# 初始化 dp 表
@ -60,7 +62,7 @@ def min_path_sum_dp(grid):
return dp[n - 1][m - 1]
def min_path_sum_dp_comp(grid):
def min_path_sum_dp_comp(grid: list[list[int]]) -> int:
"""最小路径和：状态压缩后的动态规划"""
n, m = len(grid), len(grid[0])
# 初始化 dp 表
@ -86,17 +88,17 @@ if __name__ == "__main__":
# 暴力搜索
res = min_path_sum_dfs(grid, n - 1, m - 1)
print(res)
print(f"从左上角到右下角的做小路径和为 {res}")
# 记忆化搜索
mem = [[-1] * m for _ in range(n)]
res = min_path_sum_dfs_mem(grid, mem, n - 1, m - 1)
print(res)
print(f"从左上角到右下角的做小路径和为 {res}")
# 动态规划
res = min_path_sum_dp(grid)
print(res)
print(f"从左上角到右下角的做小路径和为 {res}")
# 状态压缩后的动态规划
res = min_path_sum_dp_comp(grid)
print(res)
print(f"从左上角到右下角的做小路径和为 {res}")