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CheezItMan
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Sep 28, 2020
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Well done Olga, you hit the learning goals here and even got Heapsort to work in-place. Nice work!
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| # Time Complexity: O(n log n) | ||
| # Space Complexity: O(1) | ||
| def heap_sort(list) |
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👍 , Nice work doing this in-place with heapsort. Using the given array as the heap. Well done.
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| # Time Complexity: O(log n) - worst case, when need heap-up, O(1) - best case | ||
| # Space Complexity: O(log n) - worst case, when need heap-up, O(1) - best case | ||
| def add(key, value = key) |
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| # Time Complexity: O(log n) | ||
| # Space Complexity: O(log n) | ||
| 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) | ||
| # Space complexity: O(log n) | ||
| def heap_up(index) |
| while index * 2 + 1 < n | ||
| j = index * 2 + 1 | ||
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| j += 1 if j < n - 1 && @store[j + 1].key < @store[j].key |
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Nice work handling the left and right children here.
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| # This helper method takes an index and | ||
| # moves it up the heap if it's smaller | ||
| # than it's parent node. | ||
| def heap_down(index) |
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Heaps Practice
Congratulations! You're submitting your assignment!
Comprehension Questions
heap_up&heap_downmethods useful? Why?