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kyra-patton
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Jun 1, 2022
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✨💫 Nice work Marjan, you have a solid implementation. I left some comments below on complexity. I'm marking this as yellow since the comprehension questions are not filled out. You can resubmit with them filled out for a green! Let me know what questions you have.
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| Time Complexity: ? | ||
| Space Complexity: ? | ||
| Time Complexity: O(n log n) | ||
| Space Complexity: O(n) |
| @@ -19,18 +19,30 @@ def __init__(self): | |||
| def add(self, key, value = None): | |||
| self.store.append(HeapNode(key,value)) | ||
| self.heap_up(len(self.store)-1) | ||
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| def remove(self): |
| @@ -44,10 +56,11 @@ def __str__(self): | |||
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| def empty(self): | |||
| Time complexity: ? | ||
| Space complexity: ? | ||
| Time complexity: O(log n) | ||
| Space complexity: O(1) |
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✨ The recursive call stack here is going to make the space complexity O(log n) as each recursive call halves the heap
| self.swap(index, parent_node) | ||
| self.heap_up(parent_node) | ||
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| def heap_down(self, index): |
kyra-patton
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Jun 3, 2022
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Thanks for updating. I would note that other big differences between heaps and BSTs are that heaps are semi-ordered and maintain a complete binary tree.
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Heaps Practice
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Comprehension Questions
heap_up&heap_downmethods useful? Why?