[doh6077] WEEK 10 solutions

invert-binary-tree/doh6077.py

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+"""
+226. Invert Binary Tree
+https://leetcode.com/problems/invert-binary-tree/description/
+
+Solution
+    Recursively swaps the left and right children of the root node.
+
+"""
+# Definition for a binary tree node.
+# class TreeNode:
+#     def __init__(self, val=0, left=None, right=None):
+#         self.val = val
+#         self.left = left
+#         self.right = right
+
+
+# Use DFS
+class Solution:
+    def invertTree(self, root: Optional[TreeNode]) -> Optional[TreeNode]:
+        if root is None:
+            return None
+
+        temp = root.left
+        root.left = root.right
+        root.right = temp
+
+        self.invertTree(root.left)
+        self.invertTree(root.right)
+        return root 

jump-game/doh6077.py

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+# 55. Jump Game
+
+class Solution:
+    def canJump(self, nums: List[int]) -> bool:
+
+        # Recursive 
+        # Time: O(max(nums) ^ n)
+        # goal = len(nums) - 1
+
+        # def jump_recursive(index):
+        #     if index >= goal:
+        #         return True
+        #     max_jump = nums[index]
+        #     if max_jump == 0:
+        #         return False
+
+        #     while max_jump > 0:
+        #         if jump_recursive( index + max_jump):
+        #             return True 
+        #         else:
+        #             max_jump -= 1
+        #     return False
+
+        # return jump_recursive(0)
+
+        # Greedy - start at end 
+        # Time : O(n)
+
+        n = len(nums)
+        target = n - 1
+        # -1 exclusive 
+        for i in range(n-1, -1, -1):
+            max_jump = nums[i]
+            if i + max_jump >= target:
+                target = i 
+        return target == 0
+
+
+# Greedy 
+class Solution:
+    def canJump(self, nums: List[int]) -> bool:
+
+
+        maxValue = 0 
+        reach = len(nums) - 1
+        for i in range(0, len(nums)):
+            maxValue = max(nums[i] +  i, maxValue)
+            if maxValue >= reach: return True
+            if maxValue == i and nums[i] == 0:
+                return False
+
+
+        return False

search-in-rotated-sorted-array/doh6077.py

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+
+
+#33. Search in Rotated Sorted Array
+# First Try: use binary search but consider the rotated part
+
+# Solution: Find the minimum index where the rotation happens, then do binary search in the appropriate half.
+class Solution:
+    def search(self, nums: List[int], target: int) -> int:
+        n = len(nums)
+        l = 0
+        r = n - 1
+        # 1. find the index of the smallest value using binary search.
+        while l < r:
+            m = (l + r) // 2
+
+            if nums[m] > nums[r]:
+                l = m + 1
+            else:
+                r = m
+
+        min_i = l
+        # 2. determine which part to do binary search on.
+        # First edge case: if the smallest index is 0, meaning the array is not rotated.
+        if min_i == 0:
+            l, r = 0, n - 1
+        # Second edge case: if the target is the left part
+        elif target >= nums[0] and target <= nums[min_i - 1]:
+            l, r = 0, min_i - 1
+        # Third edge case: if the target is the right part
+        else:
+            l, r = min_i, n - 1
+        # 3. do binary search on the determined part.
+        while l <= r:
+            m = (l + r) // 2
+            if nums[m] == target:
+                return m
+            elif nums[m] < target:
+                l = m + 1
+            else:
+                r = m - 1
+        return -1
+
+# Time Complexity: O(log(n))
+# Space Complexity: O(1)
+        # if target not in nums:
+        #     return -1
+
+        # # two cases: 
+        # # 1. [left side], [right side]
+        # # if we figure out where is the boundary then we can just use binary search 
+
+        # def bst(target, start, end):
+        #     if ( start > end):
+        #         return -1
+
+        #     mid = math.floor((end + start) / 2)
+        #     print(nums[mid])
+        #     # 1. right side - sorted array 
+
+        #     if nums[mid] == target:
+        #         return mid 
+        #     elif ( nums[mid] < target) and nums[start] < nums[end]:
+        #         return bst(target, mid+1, end)
+        #     elif ( nums[mid] > target) and  nums[start] < nums[end]:
+        #         return bst(target, start, mid -1)
+        #     elif ( nums[mid] < target) and nums[start] > nums[end]:
+        #         return bst(target, start, mid -1)
+        #     elif ( nums[mid] > target) and nums[start] > nums[end]:
+        #         return bst(target, mid+1, end)
+        # return bst(target, 0, len(nums) -1)
+