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Scissors - Aida R. #49
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| Original file line number | Diff line number | Diff line change |
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| @@ -1,8 +1,19 @@ | ||
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| from heaps.min_heap import MinHeap | ||
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| def heap_sort(list): | ||
| """ This method uses a heap to sort an array. | ||
| Time Complexity: ? | ||
| Space Complexity: ? | ||
| Time Complexity: O(n) | ||
| Space Complexity: O(n) | ||
| """ | ||
| pass | ||
| heaps_dont_lie = MinHeap() | ||
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| for num in list: | ||
| heaps_dont_lie.add(num) | ||
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| i = 0 | ||
| while not heaps_dont_lie.empty(): | ||
| list[i] = heaps_dont_lie.remove() | ||
| i += 1 | ||
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| return list | ||
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@@ -21,18 +21,30 @@ def __init__(self): | |
| 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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There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. 👍 However the space complexity is O(log n) due to |
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| """ | ||
| pass | ||
| if value == None: | ||
| value = key | ||
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| node = HeapNode(key, value) | ||
| self.store.append(node) | ||
| self.heap_up(len(self.store) -1) | ||
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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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There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. 👍 Ditto on space complexity. |
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| pass | ||
| if self.empty(): | ||
| return None | ||
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| self.swap(0, len(self.store) - 1) | ||
| min = self.store.pop() | ||
| self.heap_down(0) | ||
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| return min.value | ||
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@@ -46,10 +58,10 @@ def __str__(self): | |
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| def empty(self): | ||
| """ This method returns true if the heap is empty | ||
| Time complexity: ? | ||
| Space complexity: ? | ||
| Time complexity: O(1) | ||
| Space complexity: O(1) | ||
| """ | ||
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There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. 👍 |
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| pass | ||
| return len(self.store) == 0 | ||
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| def heap_up(self, index): | ||
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There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. 👍 |
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@@ -59,18 +71,25 @@ def heap_up(self, index): | |
| property is reestablished. | ||
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| This could be **very** helpful for the add method. | ||
| Time complexity: ? | ||
| Space complexity: ? | ||
| Time complexity: O(log n) | ||
| Space complexity: O(1) | ||
| """ | ||
| pass | ||
| if index == 0: | ||
| return index | ||
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| parent_node = (index - 1) // 2 | ||
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| if self.store[parent_node].key > self.store[index].key: | ||
| self.swap(parent_node, index) | ||
| self.heap_up(parent_node) | ||
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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. | ||
| """ | ||
| pass | ||
| raise NotImplementedMethodError("Method hasn't been implemented yet!") | ||
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There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. The trick is:
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| def swap(self, index_1, index_2): | ||
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@@ -81,3 +100,6 @@ def swap(self, index_1, index_2): | |
| temp = self.store[index_1] | ||
| self.store[index_1] = self.store[index_2] | ||
| self.store[index_2] = temp | ||
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| class NotImplementedMethodError(Exception): | ||
| pass | ||
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
👍 However the time complexity is O(n log n) because you are adding n elements to the heap and each addition takes O(log n) time.