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authorlshprung <lshprung@yahoo.com>2020-06-03 11:48:22 -0700
committerlshprung <lshprung@yahoo.com>2020-06-03 11:48:22 -0700
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+[\<- 06/01](06-01.md)
+
+---
+
+## Heap Sort
+
+- An improved version of Selection sort
+- How it works?
+ - Build a max-heap (O(nlog(n)))
+ - Select the largest element based on the heap and swap it with the last element in the unsorted list, and reheap (O(nlog(n)))
+ - Partitioned array: left side is an unsorted heap, right side is sorted
+ - total O(nlog(n)) (much faster than O(n^2))
+ - theoretically the fastest algorithm
+
+- Example: 32, 78, 45, 8, 56, 23
+
+|Heap |to be inserted|to be inserted|to be inserted|to be inserted|to be inserted|
+|--------------|--------------|--------------|--------------|--------------|--------------|
+|32 |78 |45 |8 |56 |23 |
+
+- Insert 78
+
+|Heap |Heap |to be inserted|to be inserted|to be inserted|to be inserted|
+|--------------|--------------|--------------|--------------|--------------|--------------|
+|32 |78 |45 |8 |56 |23 |
+
+- To maintain the heap, swap 32 and 78
+
+|Heap |Heap |to be inserted|to be inserted|to be inserted|to be inserted|
+|--------------|--------------|--------------|--------------|--------------|--------------|
+|78 |32 |45 |8 |56 |23 |
+
+- Insert 45
+
+|Heap |Heap |Heap |to be inserted|to be inserted|to be inserted|
+|--------------|--------------|--------------|--------------|--------------|--------------|
+|78 |32 |45 |8 |56 |23 |
+
+- Insert 8
+
+|Heap |Heap |Heap |Heap |to be inserted|to be inserted|
+|--------------|--------------|--------------|--------------|--------------|--------------|
+|78 |32 |45 |8 |56 |23 |
+
+- Insert 56
+
+|Heap |Heap |Heap |Heap |Heap |to be inserted|
+|--------------|--------------|--------------|--------------|--------------|--------------|
+|78 |32 |45 |8 |56 |23 |
+
+- Swap 32 and 56
+
+|Heap |Heap |Heap |Heap |Heap |to be inserted|
+|--------------|--------------|--------------|--------------|--------------|--------------|
+|78 |56 |45 |8 |32 |23 |
+
+- Insert 23
+
+|Heap |Heap |Heap |Heap |Heap |Heap |
+|--------------|--------------|--------------|--------------|--------------|--------------|
+|78 |56 |45 |8 |32 |23 |
+
+- Now the heap has been created, but we still need to sort it
+- Swap 23 and 56
+
+|Heap |Heap |Heap |Heap |Heap |Sorted |
+|--------------|--------------|--------------|--------------|--------------|--------------|
+|23 |56 |45 |8 |32 |78 |
+
+- Reheap down to get
+
+|Heap |Heap |Heap |Heap |Heap |Sorted |
+|--------------|--------------|--------------|--------------|--------------|--------------|
+|56 |32 |45 |8 |23 |78 |
+
+- Swap 56 and 23
+
+|Heap |Heap |Heap |Heap |Sorted |Sorted |
+|--------------|--------------|--------------|--------------|--------------|--------------|
+|23 |32 |45 |8 |56 |78 |
+
+- Reheap Down
+
+|Heap |Heap |Heap |Heap |Sorted |Sorted |
+|--------------|--------------|--------------|--------------|--------------|--------------|
+|45 |32 |23 |8 |56 |78 |
+
+- Swap 45 and 8
+
+|Heap |Heap |Heap |Sorted |Sorted |Sorted |
+|--------------|--------------|--------------|--------------|--------------|--------------|
+|8 |32 |23 |45 |56 |78 |
+
+- Reheap Down
+
+|Heap |Heap |Heap |Sorted |Sorted |Sorted |
+|--------------|--------------|--------------|--------------|--------------|--------------|
+|32 |8 |23 |45 |56 |78 |
+
+- Swap 32 and 23
+
+|Heap |Heap |Sorted |Sorted |Sorted |Sorted |
+|--------------|--------------|--------------|--------------|--------------|--------------|
+|23 |8 |32 |45 |56 |78 |
+
+- Reheap Down (same)
+- Swap 23 and 8
+
+|Heap |Sorted |Sorted |Sorted |Sorted |Sorted |
+|--------------|--------------|--------------|--------------|--------------|--------------|
+|8 |23 |32 |45 |56 |78 |
+
+- Done!
+
+- Is it stable?
+ - No (too much swapping to easily predict where things will be)
+ - This is the only downside of Heap Sort
+ - 78, 56, 32, **32**, 8, 23, 45
+
+- Big O
+ - Worst case: O(nlog(n))
+ - Best case: O(nlog(n))
+ - Average case: O(nlog(n))
+
+- Space overhead? O(1)
+
+## Shell Sort
+
+- An improved version of the insertion sort in which **diminishing partitions** are used to sort the data
+
+- How does it work?
+ - A list of N elements is divided into **K segments**, where K is known as the increment
+ - For each segment, do insertion sort
+ - Reduce the value of K and repeat the process, until K=1
+
+### Demonstration
+
+![demonstration](06-03_img1.png)
+
+- We do insertion sort on each segment
+
+### Example
+
+- 77, 62, 14, 9, 30, 21, 80, 25, 70, 55
+- We set k= 5, 3, 1 progressively
+
+|77|62|14|9 |30|21|80|25|70|55|
+|--|--|--|--|--|--|--|--|--|--|
+
+- Initial Sub-Arrays
+ - 77, 21
+ - 62, 80
+ - 14, 25
+ - 9, 70
+ - 30, 55
+- After sorting the segments, we get
+ - 21, 77
+ - 62, 80
+ - 14, 25
+ - 9, 70
+ - 30, 55
+
+|21|62|14|9 |30|77|80|25|70|55|
+|--|--|--|--|--|--|--|--|--|--|
+
+- Now, k=3, the new sub-arrays are
+ - 21, 9, 80, 55
+ - 62, 30, 25
+ - 14, 77, 70
+- After sorting the segments, we get
+ - 9, 21, 55, 80
+ - 25, 30, 62
+ - 14, 70, 77
+
+|9 |25|14|21|30|70|55|62|77|80|
+|--|--|--|--|--|--|--|--|--|--|
+
+- Now k=1, so the new sub-arrays will be length 1, and we will effectively just be doing an insertion sort
+ - This will actually be pretty fast, since by this point the array is nearly sorted
+
+### Code
+
+```
+void shellSort(int a[], int n){
+ int i, j, temp, k;
+
+ foreach value of k do{
+ for(i=k; i<n; i+=k){
+ temp = a[i];
+ for(j = i-k; j>=0 && temp<a[j]; j-=k){
+ a[j+k] = a[j];
+ }
+ a[j+k] = temp;
+ }
+ }
+}
+```
+
+- Notice that the code inside the for loop is just insertion sort
+
+- How to choose K?
+ - Prime numbers
+ - A power of 2 minus 1 (i.e. k = 2^i - 1)
+ - Fibonacci series
+
+- Is it stable?
+ - No
+ - 5 4 **4** 2 3 6
+
+- Big O
+ - Worst case - depends, O(n^(3/2)) if right k sequence chosen
+ - Average case - depends, O(n^(4/3)) (as above)
+ - Best case - O(nlog(n))
+
+- Space Overhead O(1)
+
+### Additional Notes
+
+- Best-case Big-O analysis:
+ - comparisons =
+ - n, for 1 sort with elements 1-apart (last step)
+ - \+ 3 * n/3, for 3 sorts with elements 3-apart (next-to-last step)
+ - \+ 7 * n/7, for 7 sorts with elements 7-apart
+ - \+ 15 * n/15, for 15 sorts with elements 15-apart
+
+- Each term is n. The question is how many terms are there? The number of terms is the value k such that (2^i - 1)\<n; So i\<log(n+1), meaning that the sorting time in the best case is less than n * log(n+1) = O(n\*log(n))
+
+### Summary
+
+- The method starts by sorting pairs of elements **far apart from each other**, then **progressively reducing the gap** between elements to be compared. Starting with far apart elements can move some out-of-place elements into position faster than a simple nearest neighbor exchange
+
+## Tree Sort
+
+- Two steps:
+ - Insert each value from the array into a binary search tree
+ - Traverse the binary search tree in order and transfer the data back into the array
+
+- Worst case: O(n^2) if BST, O(nlog(n)) if AVL
+- Average case: O(nlog(n))
+- Best case: O(nlog(n))
+
+- Space overhead? O(n) (high!)
+ - You need to build a binary tree for this sort
+
+- It is stable!