Update 0131.分割回文串.md

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jianghongcheng
2023-05-26 21:03:46 -05:00
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@ -349,12 +349,9 @@ class Solution {
```
## Python
**回溯+正反序判断回文串**
回溯 基本版
```python
class Solution:
def __init__(self):
self.paths = []
self.path = []
def partition(self, s: str) -> List[List[str]]:
'''
@ -363,52 +360,14 @@ class Solution:
当切割线迭代至字符串末尾,说明找到一种方法
类似组合问题为了不重复切割同一位置需要start_index来做标记下一轮递归的起始位置(切割线)
'''
self.path.clear()
self.paths.clear()
self.backtracking(s, 0)
return self.paths
result = []
self.backtracking(s, 0, [], result)
return result
def backtracking(self, s: str, start_index: int) -> None:
def backtracking(self, s, start_index, path, result ):
# Base Case
if start_index >= len(s):
self.paths.append(self.path[:])
return
# 单层递归逻辑
for i in range(start_index, len(s)):
# 此次比其他组合题目多了一步判断:
# 判断被截取的这一段子串([start_index, i])是否为回文串
temp = s[start_index:i+1]
if temp == temp[::-1]: # 若反序和正序相同,意味着这是回文串
self.path.append(temp)
self.backtracking(s, i+1) # 递归纵向遍历:从下一处进行切割,判断其余是否仍为回文串
self.path.pop()
else:
continue
```
**回溯+函数判断回文串**
```python
class Solution:
def __init__(self):
self.paths = []
self.path = []
def partition(self, s: str) -> List[List[str]]:
'''
递归用于纵向遍历
for循环用于横向遍历
当切割线迭代至字符串末尾,说明找到一种方法
类似组合问题为了不重复切割同一位置需要start_index来做标记下一轮递归的起始位置(切割线)
'''
self.path.clear()
self.paths.clear()
self.backtracking(s, 0)
return self.paths
def backtracking(self, s: str, start_index: int) -> None:
# Base Case
if start_index >= len(s):
self.paths.append(self.path[:])
if start_index == len(s):
result.append(path[:])
return
# 单层递归逻辑
@ -416,9 +375,9 @@ class Solution:
# 此次比其他组合题目多了一步判断:
# 判断被截取的这一段子串([start_index, i])是否为回文串
if self.is_palindrome(s, start_index, i):
self.path.append(s[start_index:i+1])
self.backtracking(s, i+1) # 递归纵向遍历:从下一处进行切割,判断其余是否仍为回文串
self.path.pop() # 回溯
path.append(s[start_index:i+1])
self.backtracking(s, i+1, path, result) # 递归纵向遍历:从下一处进行切割,判断其余是否仍为回文串
path.pop() # 回溯
else:
continue
@ -432,7 +391,87 @@ class Solution:
j -= 1
return True
```
回溯+优化判定回文函数
```python
class Solution:
def partition(self, s: str) -> List[List[str]]:
result = []
self.backtracking(s, 0, [], result)
return result
def backtracking(self, s, start_index, path, result ):
# Base Case
if start_index == len(s):
result.append(path[:])
return
# 单层递归逻辑
for i in range(start_index, len(s)):
# 若反序和正序相同,意味着这是回文串
if s[start_index: i + 1] == s[start_index: i + 1][::-1]:
path.append(s[start_index:i+1])
self.backtracking(s, i+1, path, result) # 递归纵向遍历:从下一处进行切割,判断其余是否仍为回文串
path.pop() # 回溯
else:
continue
```
回溯+高效判断回文子串
```python
class Solution:
def partition(self, s: str) -> List[List[str]]:
result = []
isPalindrome = [[False] * len(s) for _ in range(len(s))] # 初始化isPalindrome矩阵
self.computePalindrome(s, isPalindrome)
self.backtracking(s, 0, [], result, isPalindrome)
return result
def backtracking(self, s, startIndex, path, result, isPalindrome):
if startIndex >= len(s):
result.append(path[:])
return
for i in range(startIndex, len(s)):
if isPalindrome[startIndex][i]: # 是回文子串
substring = s[startIndex:i + 1]
path.append(substring)
self.backtracking(s, i + 1, path, result, isPalindrome) # 寻找i+1为起始位置的子串
path.pop() # 回溯过程,弹出本次已经填在的子串
def computePalindrome(self, s, isPalindrome):
for i in range(len(s) - 1, -1, -1): # 需要倒序计算保证在i行时i+1行已经计算好了
for j in range(i, len(s)):
if j == i:
isPalindrome[i][j] = True
elif j - i == 1:
isPalindrome[i][j] = (s[i] == s[j])
else:
isPalindrome[i][j] = (s[i] == s[j] and isPalindrome[i+1][j-1])
```
回溯+使用all函数判断回文子串
```python
class Solution:
def partition(self, s: str) -> List[List[str]]:
result = []
self.partition_helper(s, 0, [], result)
return result
def partition_helper(self, s, start_index, path, result):
if start_index == len(s):
result.append(path[:])
return
for i in range(start_index + 1, len(s) + 1):
sub = s[start_index:i]
if self.isPalindrome(sub):
path.append(sub)
self.partition_helper(s, i, path, result)
path.pop()
def isPalindrome(self, s):
return all(s[i] == s[len(s) - 1 - i] for i in range(len(s) // 2))
```
## Go
```go
var (