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@@ -339,7 +339,27 @@ comments: true
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=== "Ruby"
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```ruby title="binary_search.rb"
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[class]{}-[func]{binary_search}
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### 二分查找(双闭区间) ###
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def binary_search(nums, target)
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# 初始化双闭区间 [0, n-1] ,即 i, j 分别指向数组首元素、尾元素
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i, j = 0, nums.length - 1
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# 循环,当搜索区间为空时跳出(当 i > j 时为空)
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while i <= j
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# 理论上 Ruby 的数字可以无限大(取决于内存大小),无须考虑大数越界问题
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m = (i + j) / 2 # 计算中点索引 m
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if nums[m] < target
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i = m + 1 # 此情况说明 target 在区间 [m+1, j] 中
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elsif nums[m] > target
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j = m - 1 # 此情况说明 target 在区间 [i, m-1] 中
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else
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return m # 找到目标元素,返回其索引
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end
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end
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-1 # 未找到目标元素,返回 -1
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end
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```
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=== "Zig"
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@@ -667,7 +687,27 @@ comments: true
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=== "Ruby"
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```ruby title="binary_search.rb"
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[class]{}-[func]{binary_search_lcro}
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### 二分查找(左闭右开区间) ###
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def binary_search_lcro(nums, target)
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# 初始化左闭右开区间 [0, n) ,即 i, j 分别指向数组首元素、尾元素+1
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i, j = 0, nums.length
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# 循环,当搜索区间为空时跳出(当 i = j 时为空)
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while i < j
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# 计算中点索引 m
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m = (i + j) / 2
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if nums[m] < target
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i = m + 1 # 此情况说明 target 在区间 [m+1, j) 中
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elsif nums[m] > target
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j = m - 1 # 此情况说明 target 在区间 [i, m) 中
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else
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return m # 找到目标元素,返回其索引
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end
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end
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-1 # 未找到目标元素,返回 -1
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end
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```
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=== "Zig"
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@@ -212,7 +212,16 @@ comments: true
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=== "Ruby"
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```ruby title="binary_search_edge.rb"
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[class]{}-[func]{binary_search_left_edge}
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### 二分查找最左一个 target ###
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def binary_search_left_edge(nums, target)
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# 等价于查找 target 的插入点
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i = binary_search_insertion(nums, target)
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# 未找到 target ,返回 -1
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return -1 if i == nums.length || nums[i] != target
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i # 找到 target ,返回索引 i
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end
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```
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=== "Zig"
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@@ -461,7 +470,19 @@ comments: true
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=== "Ruby"
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```ruby title="binary_search_edge.rb"
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[class]{}-[func]{binary_search_right_edge}
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### 二分查找最右一个 target ###
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def binary_search_right_edge(nums, target)
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# 转化为查找最左一个 target + 1
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i = binary_search_insertion(nums, target + 1)
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# j 指向最右一个 target ,i 指向首个大于 target 的元素
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j = i - 1
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# 未找到 target ,返回 -1
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return -1 if j == -1 || nums[j] != target
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j # 找到 target ,返回索引 j
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end
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```
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=== "Zig"
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@@ -293,7 +293,26 @@ comments: true
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=== "Ruby"
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```ruby title="binary_search_insertion.rb"
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[class]{}-[func]{binary_search_insertion_simple}
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### 二分查找插入点(无重复元素) ###
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def binary_search_insertion_simple(nums, target)
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# 初始化双闭区间 [0, n-1]
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i, j = 0, nums.length - 1
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while i <= j
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# 计算中点索引 m
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m = (i + j) / 2
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if nums[m] < target
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i = m + 1 # target 在区间 [m+1, j] 中
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elsif nums[m] > target
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j = m - 1 # target 在区间 [i, m-1] 中
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else
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return m # 找到 target ,返回插入点 m
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end
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end
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i # 未找到 target ,返回插入点 i
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end
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```
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=== "Zig"
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@@ -625,7 +644,26 @@ comments: true
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=== "Ruby"
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```ruby title="binary_search_insertion.rb"
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[class]{}-[func]{binary_search_insertion}
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### 二分查找插入点(存在重复元素) ###
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def binary_search_insertion(nums, target)
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# 初始化双闭区间 [0, n-1]
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i, j = 0, nums.length - 1
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while i <= j
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# 计算中点索引 m
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m = (i + j) / 2
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if nums[m] < target
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i = m + 1 # target 在区间 [m+1, j] 中
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elsif nums[m] > target
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j = m - 1 # target 在区间 [i, m-1] 中
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else
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j = m - 1 # 首个小于 target 的元素在区间 [i, m-1] 中
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end
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end
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i # 返回插入点 i
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end
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```
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=== "Zig"
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@@ -228,7 +228,17 @@ comments: true
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=== "Ruby"
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```ruby title="two_sum.rb"
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[class]{}-[func]{two_sum_brute_force}
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### 方法一:暴力枚举 ###
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def two_sum_brute_force(nums, target)
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# 两层循环,时间复杂度为 O(n^2)
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for i in 0...(nums.length - 1)
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for j in (i + 1)...nums.length
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return [i, j] if nums[i] + nums[j] == target
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end
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end
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[]
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end
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```
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=== "Zig"
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@@ -531,7 +541,19 @@ comments: true
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=== "Ruby"
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```ruby title="two_sum.rb"
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[class]{}-[func]{two_sum_hash_table}
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### 方法二:辅助哈希表 ###
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def two_sum_hash_table(nums, target)
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# 辅助哈希表,空间复杂度为 O(n)
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dic = {}
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# 单层循环,时间复杂度为 O(n)
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for i in 0...nums.length
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return [dic[target - nums[i]], i] if dic.has_key?(target - nums[i])
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dic[nums[i]] = i
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end
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[]
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end
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```
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=== "Zig"
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