Merge pull request #213 from xiaoluome/dev

第四周算法作业#36

Author: GeekUniversity

Week_04/id_36/LeetCode_169_36.py

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+#
+# @lc app=leetcode.cn id=169 lang=python3
+#
+# [169] 求众数
+#
+# https://leetcode-cn.com/problems/majority-element/description/
+#
+# algorithms
+# Easy (59.73%)
+# Likes:    259
+# Dislikes: 0
+# Total Accepted:    49.1K
+# Total Submissions: 82.1K
+# Testcase Example:  '[3,2,3]'
+#
+# 给定一个大小为 n 的数组，找到其中的众数。众数是指在数组中出现次数大于 ⌊ n/2 ⌋ 的元素。
+# 
+# 你可以假设数组是非空的，并且给定的数组总是存在众数。
+# 
+# 示例 1:
+# 
+# 输入: [3,2,3]
+# 输出: 3
+# 
+# 示例 2:
+# 
+# 输入: [2,2,1,1,1,2,2]
+# 输出: 2
+# 
+# 
+
+# # 暴力法
+# class Solution:
+#     def majorityElement(self, nums: List[int]) -> int:
+#         majority_num = len(nums)//2
+
+#         for num in nums:
+#             count = 0
+#             for n in nums:
+#                 if n == num:
+#                     count += 1
+
+#             if count > majority_num:
+#                 return num
+        
+#         return -1
+
+# # 哈希表-1
+# class Solution:
+#     def majorityElement(self, nums: List[int]) -> int:
+#         if not nums or len(nums) < 1:
+#             return 0
+
+#         counts = {}
+
+#         for num in nums:
+#             if not counts.get(num):
+#                 counts[num] = 1
+#             else:
+#                 counts[num] += 1
+        
+#         max_value = 0
+#         majority = 0
+        
+#         for key, value in counts.items():
+#             if value > max_value:
+#                 max_value = value
+#                 majority = key
+
+#         return majority
+
+# # 哈希表-2
+# class Solution:
+#     def majorityElement(self, nums: List[int]) -> int:
+#         import collections
+#         counts = collections.Counter(nums)
+#         return max(counts.keys(), key = counts.get)
+
+# # 排序
+# class Solution:
+#     def majorityElement(self, nums: List[int]) -> int:
+#         nums_len = len(nums)
+#         if not nums or nums_len < 1:
+#             return 0
+        
+#         nums.sort()
+#         return nums[nums_len // 2]
+
+# # 分治
+# class Solution:
+#     def majorityElement(self, nums: List[int]) -> int:
+#         def majority_element_rec(low, high):
+#             if low == high:
+#                 return nums[low]
+            
+#             middle = low + (high - low) // 2
+#             left = majority_element_rec(low, middle)
+#             right = majority_element_rec(middle + 1, high)
+
+#             if left == right:
+#                 return left
+            
+#             # left_count = sum(1 for i in range(low, high + 1) if nums[i] == left)
+#             # right_count = sum(1 for i in range(low, high + 1) if nums[i] == right)
+#             left_count = 0
+#             right_count = 0
+#             for i in range(low, high + 1):
+#                 if nums[i] == left:
+#                     left_count += 1
+#                 elif nums[i] == right:
+#                     right_count += 1
+
+#             return left if left_count > right_count else right
+        
+#         return majority_element_rec(0, len(nums) - 1)
+
+# Boyer-Moore 投票算法
+class Solution:
+    def majorityElement(self, nums: List[int]) -> int:
+        count = 0
+        candidate = None
+
+        for num in nums:
+            if count == 0:
+                candidate = num
+            count += (1 if num == candidate else -1)
+        
+        return candidate
+

Week_04/id_36/LeetCode_455_36.py

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+#
+# @lc app=leetcode.cn id=455 lang=python3
+#
+# [455] 分发饼干
+#
+# https://leetcode-cn.com/problems/assign-cookies/description/
+#
+# algorithms
+# Easy (49.91%)
+# Likes:    91
+# Dislikes: 0
+# Total Accepted:    10.7K
+# Total Submissions: 21.4K
+# Testcase Example:  '[1,2,3]\n[1,1]'
+#
+# 假设你是一位很棒的家长，想要给你的孩子们一些小饼干。但是，每个孩子最多只能给一块饼干。对每个孩子 i ，都有一个胃口值 gi
+# ，这是能让孩子们满足胃口的饼干的最小尺寸；并且每块饼干 j ，都有一个尺寸 sj 。如果 sj >= gi ，我们可以将这个饼干 j 分配给孩子 i
+# ，这个孩子会得到满足。你的目标是尽可能满足越多数量的孩子，并输出这个最大数值。
+# 
+# 注意：
+# 
+# 你可以假设胃口值为正。
+# 一个小朋友最多只能拥有一块饼干。
+# 
+# 示例 1:
+# 
+# 
+# 输入: [1,2,3], [1,1]
+# 
+# 输出: 1
+# 
+# 解释: 
+# 你有三个孩子和两块小饼干，3个孩子的胃口值分别是：1,2,3。
+# 虽然你有两块小饼干，由于他们的尺寸都是1，你只能让胃口值是1的孩子满足。
+# 所以你应该输出1。
+# 
+# 
+# 示例 2:
+# 
+# 
+# 输入: [1,2], [1,2,3]
+# 
+# 输出: 2
+# 
+# 解释: 
+# 你有两个孩子和三块小饼干，2个孩子的胃口值分别是1,2。
+# 你拥有的饼干数量和尺寸都足以让所有孩子满足。
+# 所以你应该输出2.
+# 
+# 
+#
+# class Solution:
+#     def findContentChildren(self, g: List[int], s: List[int]) -> int:
+#         g.sort()
+#         s.sort()
+
+#         gi = 0
+#         si = 0
+#         res = 0
+
+#         while gi < len(g) and si < len(s):
+#             if s[si] >= g[gi]:
+#                 si += 1
+#                 gi += 1
+#                 res += 1
+#             else:
+#                 si += 1
+        
+#         return res
+
+class Solution:
+    def findContentChildren(self, g: List[int], s: List[int]) -> int:
+        import heapq
+
+        heapq.heapify(g)
+        heapq.heapify(s)
+
+        res = 0
+
+        while g and s:
+            if s[0] >= g[0]:
+                heapq.heappop(g)
+                heapq.heappop(s)
+                res += 1
+            else:
+                heapq.heappop(s)
+        
+        return res
+

Week_04/id_36/LeetCode_46_36.py

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+#
+# @lc app=leetcode.cn id=46 lang=python3
+#
+# [46] 全排列
+#
+# https://leetcode-cn.com/problems/permutations/description/
+#
+# algorithms
+# Medium (69.78%)
+# Likes:    294
+# Dislikes: 0
+# Total Accepted:    29.2K
+# Total Submissions: 41.9K
+# Testcase Example:  '[1,2,3]'
+#
+# 给定一个没有重复数字的序列，返回其所有可能的全排列。
+# 
+# 示例:
+# 
+# 输入: [1,2,3]
+# 输出:
+# [
+# ⁠ [1,2,3],
+# ⁠ [1,3,2],
+# ⁠ [2,1,3],
+# ⁠ [2,3,1],
+# ⁠ [3,1,2],
+# ⁠ [3,2,1]
+# ]
+# 
+#
+class Solution:
+    def permute(self, nums: List[int]) -> List[List[int]]:
+        def backtrack(first = 0):
+            if first == n:
+                output.append(nums[:])
+            
+            for i in range(first, n):
+                nums[first], nums[i] = nums[i], nums[first]
+                backtrack(first + 1)
+                nums[first], nums[i] = nums[i], nums[first]
+        
+        n = len(nums)
+        output = []
+        backtrack()
+
+        return output
+

Week_04/id_36/LeetCode_53_36.py

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+#
+# @lc app=leetcode.cn id=53 lang=python3
+#
+# [53] 最大子序和
+#
+# https://leetcode-cn.com/problems/maximum-subarray/description/
+#
+# algorithms
+# Easy (45.55%)
+# Likes:    1009
+# Dislikes: 0
+# Total Accepted:    65.3K
+# Total Submissions: 142.9K
+# Testcase Example:  '[-2,1,-3,4,-1,2,1,-5,4]'
+#
+# 给定一个整数数组 nums ，找到一个具有最大和的连续子数组（子数组最少包含一个元素），返回其最大和。
+# 
+# 示例:
+# 
+# 输入: [-2,1,-3,4,-1,2,1,-5,4],
+# 输出: 6
+# 解释: 连续子数组 [4,-1,2,1] 的和最大，为 6。
+# 
+# 
+# 进阶:
+# 
+# 如果你已经实现复杂度为 O(n) 的解法，尝试使用更为精妙的分治法求解。
+# 
+# # 暴力法
+# class Solution:
+#     def maxSubArray(self, nums: List[int]) -> int:
+#         n = len(nums)
+#         if n <= 0:
+#             return 0
+        
+#         tmp = nums[0]
+#         max_value = tmp
+
+#         for i in range(1, n):
+#             tmp = tmp + nums[i] if tmp > 0 else nums[i]
+#             max_value = max(max_value, tmp)
+        
+#         return max_value
+
+# class Solution:
+#     def maxSubArray(self, nums: List[int]) -> int:
+#         n = len(nums)
+#         if n <= 0:
+#             return 0
+#         elif n == 1:
+#             return nums[0]
+        
+#         max_value = nums[0]
+#         tmp = 0
+
+#         for num in nums:
+#             tmp = tmp + num if tmp > 0 else num
+#             max_value = max(max_value, tmp)
+        
+#         return max_value
+
+# 分治法
+class Solution:
+    def maxSubArray(self, nums: List[int]) -> int:
+        n = len(nums)
+        if n <= 0:
+            return 0
+        elif n == 1:
+            return nums[0]
+        
+        middle = n // 2
+        max_left = self.maxSubArray(nums[0 : middle])
+        max_right = self.maxSubArray(nums[middle : n])
+    
+        tmp = 0
+        max_le = nums[middle - 1]
+        for i in range(middle - 1, -1, -1):
+            tmp += nums[i]
+            max_le = max(max_le, tmp)
+        
+        max_ri = nums[middle]
+        tmp = 0
+        for i in range(middle, n):
+            tmp += nums[i]
+            max_ri = max(max_ri, tmp)
+        
+        return max(max_left, max_right, max_le + max_ri)
+