Water - Li #12
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CheezItMan
reviewed
May 1, 2021
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| # Time Complexity: O(nlogn): add O(nlogn) + remove O(nlogn) | ||
| # Space Complexity: O(n) for creating @store to store all the nodes | ||
| def heapsort(list) |
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| # Time Complexity: O(log n): push O(1) + heap_up O(log n) | ||
| # Space Complexity: O(log n) : heap_up O(log n) | ||
| def add(key, value = key) |
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| # Time Complexity: O(log n): pop, swap O(1) + heap_down O(log n) | ||
| # Space Complexity: O(log n) from heap_down call stacks | ||
| def remove() |
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| # Time complexity: O(1) | ||
| # Space complexity: O(1) | ||
| def empty? |
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| # Time complexity: O(log n): swap - O(1), and we will do it up to O(log n) times | ||
| # Space complexity: O(log n) for call stacks | ||
| # min heap, the smallest node goes up to root | ||
| def heap_up(index) |
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| # swap parent with the smaller child | ||
| # Time complexity: O(log n): find_smaller_childs_index - O(1), swap - O(1), and we will do it up to O(log n) times | ||
| # Space complexity: O(log n) for call stacks | ||
| def heap_down(index) |
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Heaps Practice
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Comprehension Questions
heap_up&heap_downmethods useful? Why?