Scissors - Araceli#41
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CheezItMan
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Nice work Araceli, you hit the learning goals here. Really nice work with the in-place solution to HeapSort.
I left a few notes on time/space complexity.
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| def heap_sort(arr): | ||
| """ This method uses a heap to sort an array. | ||
| Time Complexity: ? | ||
| Space Complexity: ? | ||
| Time Complexity: O (log n) | ||
| Space Complexity: O(1) | ||
| """ |
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👍 Awesome work an O(1) heapsort solution. Nice work.
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| def add(self, key, value = None): | ||
| """ This method adds a HeapNode instance to the heap | ||
| If value == None the new node's value should be set to key | ||
| Time Complexity: ? | ||
| Space Complexity: ? | ||
| Time Complexity: O(log n) | ||
| Space Complexity: O(1) | ||
| """ |
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👍 However this is O(log n) for space complexity because heap_up is recursive and you have the call stack.
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| def remove(self): | ||
| """ This method removes and returns an element from the heap | ||
| maintaining the heap structure | ||
| Time Complexity: ? | ||
| Space Complexity: ? | ||
| Time Complexity: O(log n) | ||
| Space Complexity: O(1) |
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👍 However space complexity is O(log n) due to the recursive call stack.
| @@ -46,11 +58,12 @@ def __str__(self): | |||
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| def empty(self): | |||
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| return self.store | ||
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| def heap_up(self, index): |
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👍 However time/space complexity are both O(log n) due to recursion.
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| def heap_down(self, index): | ||
| """ This helper method takes an index and | ||
| moves the corresponding element down the heap if it's | ||
| larger than either of its children and continues until | ||
| the heap property is reestablished. | ||
| """ |
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Heaps Practice
Congratulations! You're submitting your assignment!
Comprehension Questions
heap_up&heap_downmethods useful? Why?