python - leetcode 2键键盘问题的递归方法

Question

我正在尝试 使用递归解决此问题https://leetcode.com/problems/2-keys-keyboard/ 。我初始化了 2 个变量屏幕和缓冲区。screen 表示屏幕上所有字符的计数，buffer 表示上一步复制的所有字符的计数

所以我们复制的时候函数是这样调用的 - function(screen,screen)

和粘贴意味着 - 功能（屏幕+缓冲区，缓冲区）

但这不起作用这是代码-

def keyboard(screen,buffer, c,n):
    if screen == n:
        return c
    if screen>n:
        return
    if buffer>n:
        return    
  
      
    keyboard(screen+buffer,buffer,c+1,n)
    keyboard(screen,screen,c+1,n)

print(keyboard(1,0,0,8)) 

我得到最大的递归深度这是记忆的方法

    def keyboard(self,screen,buffer,c,n,dp):
        
        large_num = 100000 # larger than possible moves
        
        if dp[screen][buffer] != -1:
            return dp[screen][buffer]
  
        if screen == n:
            return c           

        if screen>n:
            return large_num  

        if buffer>n:
            return large_num  

        if c > n:  
            return large_num
       
        dp[screen][buffer] =  min(self.keyboard(screen,screen,c+1,n,dp), self.keyboard(screen+buffer,buffer,c+1,n,dp))
        return dp[screen][buffer]  

    def minSteps(self, n: int) -> int:
        dp = [[-1 for i in range(n+1)] for j in range(n+1)]

        return(self.keyboard(1,0,0,n,dp))

标签： pythonalgorithmrecursiondynamic-programming

Answer 1

两个问题：

• 需要限制移动次数（即c值）
• 需要通过取最小值来优化动作

代码

def keyboard(screen,buffer,c,n):
  large_num = 100000 # larger than possible moves

  if screen == n:
    return c           # Found solution

  if screen>n:
    return large_num  # Out of bounds (make moves larger than max possible)

  if buffer>n:
    return large_num  # Out of bounds (make moves larger than max possible)

  if c > n:  # limit number of moves
    return large_num
  
  # Optimize choice by taking minimum
  return min(keyboard(screen,screen,c+1,n), keyboard(screen+buffer,buffer,c+1,n))

print(keyboard(1,0,0,8)) 
# Output: 6

添加记忆

def keyboard(screen,buffer,c,n, memcache = None):
  if memcache is None:
    memcache = {}
  large_num = 100000 # larger than possible moves

  # Input state as tuple
  state = (screen, buffer, c, n)

  if state in memcache:
    return memcache[state]

  if screen == n:
    return c           # Found solution

  if screen>n:
    return large_num  # Out of bounds (make moves larger than max possible)

  if buffer>n:
    return large_num  # Out of bounds (make moves larger than max possible)

  if c > n:  # limit number of moves
    return large_num
  
  # Using memoization to cache current value
  # Optimize choice by taking minimum
  memcache[state] = min(keyboard(screen,screen,c+1,n), keyboard(screen+buffer,buffer,c+1,n))

  return memcache[state]

print(keyboard(1,0,0,8)) 

使用装饰器进行记忆

这等效于前一种情况，但使用装饰器允许记忆任何具有可清洗位置参数的函数，

def memoize(f):
    """This automates the previous example where we added a cache.  
       It uses a decorator function to add a cache to any function with
       hashable position arguments
    """
    memo = {}
    def helper(*args):
        if args not in memo:            
            memo[args] = f(*args)
        return memo[args]
    return helper

@memoize
def keyboard(screen,buffer,c,n):

  large_num = 100000 # larger than possible moves

  if screen == n:
    return c           # Found solution

  if screen>n:
    return large_num  # Out of bounds (make moves larger than max possible)

  if buffer>n:
    return large_num  # Out of bounds (make moves larger than max possible)

  if c > n:  # limit number of moves
    return large_num
  
  # Using memoization to cache current value
  # Optimize choice by taking minimum
  return min(keyboard(screen,screen,c+1,n), keyboard(screen+buffer,buffer,c+1,n))

print(keyboard(1,0,0,8))

修复海报记忆代码

问题是记忆没有超过输入的完整状态。

• 发布的代码使用（屏幕，缓冲区）作为状态
• 状态实际上是 (screen, buffer, c) （不需要 n，因为它是固定的）

固定代码

class Solver:
  def keyboard(self,screen,buffer,c,n,dp):
    
    large_num = n + 1 # larger than largest possible moves
    
    if screen>n or buffer>n or c > n:
      return large_num 

    if dp[screen][buffer][c] != -1:
      return dp[screen][buffer][c]

    if screen == n:
      dp[screen][buffer][c] = c          
    
    elif buffer == 0:
      dp[screen][buffer][c] = self.keyboard(screen, screen, c+1, n, dp)
    else:
      # screen can not be zero
      # minimum of copy and paste move
      dp[screen][buffer][c] =  min(self.keyboard(screen,screen,c+1,n,dp), self.keyboard(screen+buffer,buffer,c+1,n,dp))
      
    return dp[screen][buffer][c]  

  def minSteps(self, n: int) -> int:
    dp = [[[-1 for i in range(n+1)] for j in range(n+1)] for k in range(n+1)]

    return self.keyboard(1,0,0,n,dp)

s = Solver()
print(s.minSteps(8))
# Output: 6