Trapping Rain Water II | Deep Dive Explanation | What | Why | How | Leetcode 407 | codestorywithMIK
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We will solve a very good problem based 2D Grid and Heap + BFS - Trapping Rain Water II | Deep Dive Explanation | What | Why | How | Leetcode 407 | codestorywithMIK
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Problem Name : Trapping Rain Water II | Deep Dive Explanation | What | Why | How | Leetcode 407 | codestorywithMIK
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Github Solutions Link (C++/Java) : https://github.com/MAZHARMIK/Interview_DS_Algo/blob/master/Heap/Trapping Rain Water II.cpp
Leetcode Link : https://leetcode.com/problems/trapping-rain-water-ii/description/
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Video Summary : Trapping Rain Water (Using Min-Heap + BFS)
The goal is to simulate how water would fill a landscape based on cell heights in a grid. Water flows from the boundary inward, filling lower cells first.
Intuition:
Boundary Cells: Water cannot flow past the boundary, so we start processing from the edges.
Flooding Inward: Water fills lower cells first, and the amount trapped depends on neighboring cell heights.
Why a Min-Heap?
A min-heap is used to always process the lowest height cell first:
Efficient Extraction: The heap allows quick access to the smallest height cell, ensuring correct flooding order.
Simulating Water Flow: After processing a cell, its lower neighbors are added to the heap with updated heights, ensuring proper water flow.
Time Complexity:
Time: O(m * n * log(m * n)), where m and n are grid dimensions.
Space: O(m * n) for the heap and visited array.
The min-heap ensures efficient processing of the grid, simulating water filling the landscape in the correct order.
✨ Timelines✨
00:00 - Introduction
0:50 - Motivation
1:54 - Problem Explanation
6:38 - Thought Process - Imagination
9:13 - A simple example
13:29 - Another Example
21:32 - Good Example - Why Min Heap ?
39:35 - Story To Code
40:46 - Coding in Cpp
51:15 - Coding in Cpp
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