task_url
stringlengths 30
116
| task_name
stringlengths 2
86
| task_description
stringlengths 0
14.4k
| language_url
stringlengths 2
53
| language_name
stringlengths 1
52
| code
stringlengths 0
61.9k
|
|---|---|---|---|---|---|
http://rosettacode.org/wiki/Sorting_algorithms/Merge_sort | Sorting algorithms/Merge sort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
The merge sort is a recursive sort of order n*log(n).
It is notable for having a worst case and average complexity of O(n*log(n)), and a best case complexity of O(n) (for pre-sorted input).
The basic idea is to split the collection into smaller groups by halving it until the groups only have one element or no elements (which are both entirely sorted groups).
Then merge the groups back together so that their elements are in order.
This is how the algorithm gets its divide and conquer description.
Task
Write a function to sort a collection of integers using the merge sort.
The merge sort algorithm comes in two parts:
a sort function and
a merge function
The functions in pseudocode look like this:
function mergesort(m)
var list left, right, result
if length(m) ≤ 1
return m
else
var middle = length(m) / 2
for each x in m up to middle - 1
add x to left
for each x in m at and after middle
add x to right
left = mergesort(left)
right = mergesort(right)
if last(left) ≤ first(right)
append right to left
return left
result = merge(left, right)
return result
function merge(left,right)
var list result
while length(left) > 0 and length(right) > 0
if first(left) ≤ first(right)
append first(left) to result
left = rest(left)
else
append first(right) to result
right = rest(right)
if length(left) > 0
append rest(left) to result
if length(right) > 0
append rest(right) to result
return result
See also
the Wikipedia entry: merge sort
Note: better performance can be expected if, rather than recursing until length(m) ≤ 1, an insertion sort is used for length(m) smaller than some threshold larger than 1. However, this complicates the example code, so it is not shown here.
| #Nemerle | Nemerle | using System;
using System.Console;
using Nemerle.Collections;
module Mergesort
{
MergeSort[TEnu, TItem] (sort_me : TEnu) : list[TItem]
where TEnu : Seq[TItem]
where TItem : IComparable
{
def split(xs) {
def loop (zs, xs, ys) {
|(x::y::zs, xs, ys) => loop(zs, x::xs, y::ys)
|(x::[], xs, ys) => (x::xs, ys)
|([], xs, ys) => (xs, ys)
}
loop(xs, [], [])
}
def merge(xs, ys) {
def loop(res, xs, ys) {
|(res, [], []) => res.Reverse()
|(res, x::xs, []) => loop(x::res, xs, [])
|(res, [], y::ys) => loop(y::res, [], ys)
|(res, x::xs, y::ys) => if (x.CompareTo(y) < 0) loop(x::res, xs, y::ys)
else loop(y::res, x::xs, ys)
}
loop ([], xs, ys)
}
def ms(xs) {
|[] => []
|[x] => [x]
|_ => { def (left, right) = split(xs); merge(ms(left), ms(right)) }
}
ms(sort_me.NToList())
}
Main() : void
{
def test1 = MergeSort([1, 5, 9, 2, 7, 8, 4, 6, 3]);
def test2 = MergeSort(array['a', 't', 'w', 'f', 'c', 'y', 'l']);
WriteLine(test1);
WriteLine(test2);
}
} |
http://rosettacode.org/wiki/Stack | Stack |
Data Structure
This illustrates a data structure, a means of storing data within a program.
You may see other such structures in the Data Structures category.
A stack is a container of elements with last in, first out access policy. Sometimes it also called LIFO.
The stack is accessed through its top.
The basic stack operations are:
push stores a new element onto the stack top;
pop returns the last pushed stack element, while removing it from the stack;
empty tests if the stack contains no elements.
Sometimes the last pushed stack element is made accessible for immutable access (for read) or mutable access (for write):
top (sometimes called peek to keep with the p theme) returns the topmost element without modifying the stack.
Stacks allow a very simple hardware implementation.
They are common in almost all processors.
In programming, stacks are also very popular for their way (LIFO) of resource management, usually memory.
Nested scopes of language objects are naturally implemented by a stack (sometimes by multiple stacks).
This is a classical way to implement local variables of a re-entrant or recursive subprogram. Stacks are also used to describe a formal computational framework.
See stack machine.
Many algorithms in pattern matching, compiler construction (e.g. recursive descent parsers), and machine learning (e.g. based on tree traversal) have a natural representation in terms of stacks.
Task
Create a stack supporting the basic operations: push, pop, empty.
See also
Array
Associative array: Creation, Iteration
Collections
Compound data type
Doubly-linked list: Definition, Element definition, Element insertion, List Traversal, Element Removal
Linked list
Queue: Definition, Usage
Set
Singly-linked list: Element definition, Element insertion, List Traversal, Element Removal
Stack
| #XLISP | XLISP | (define-class stack
(instance-variables vals))
(define-method (stack 'initialize)
(setq vals '())
self)
(define-method (stack 'push x)
(setq vals (cons x vals)))
(define-method (stack 'pop)
(define tos (car vals))
(setq vals (cdr vals))
tos)
(define-method (stack 'emptyp)
(null vals)) |
http://rosettacode.org/wiki/Sorting_algorithms/Quicksort | Sorting algorithms/Quicksort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Quicksort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
Task
Sort an array (or list) elements using the quicksort algorithm.
The elements must have a strict weak order and the index of the array can be of any discrete type.
For languages where this is not possible, sort an array of integers.
Quicksort, also known as partition-exchange sort, uses these steps.
Choose any element of the array to be the pivot.
Divide all other elements (except the pivot) into two partitions.
All elements less than the pivot must be in the first partition.
All elements greater than the pivot must be in the second partition.
Use recursion to sort both partitions.
Join the first sorted partition, the pivot, and the second sorted partition.
The best pivot creates partitions of equal length (or lengths differing by 1).
The worst pivot creates an empty partition (for example, if the pivot is the first or last element of a sorted array).
The run-time of Quicksort ranges from O(n log n) with the best pivots, to O(n2) with the worst pivots, where n is the number of elements in the array.
This is a simple quicksort algorithm, adapted from Wikipedia.
function quicksort(array)
less, equal, greater := three empty arrays
if length(array) > 1
pivot := select any element of array
for each x in array
if x < pivot then add x to less
if x = pivot then add x to equal
if x > pivot then add x to greater
quicksort(less)
quicksort(greater)
array := concatenate(less, equal, greater)
A better quicksort algorithm works in place, by swapping elements within the array, to avoid the memory allocation of more arrays.
function quicksort(array)
if length(array) > 1
pivot := select any element of array
left := first index of array
right := last index of array
while left ≤ right
while array[left] < pivot
left := left + 1
while array[right] > pivot
right := right - 1
if left ≤ right
swap array[left] with array[right]
left := left + 1
right := right - 1
quicksort(array from first index to right)
quicksort(array from left to last index)
Quicksort has a reputation as the fastest sort. Optimized variants of quicksort are common features of many languages and libraries. One often contrasts quicksort with merge sort, because both sorts have an average time of O(n log n).
"On average, mergesort does fewer comparisons than quicksort, so it may be better when complicated comparison routines are used. Mergesort also takes advantage of pre-existing order, so it would be favored for using sort() to merge several sorted arrays. On the other hand, quicksort is often faster for small arrays, and on arrays of a few distinct values, repeated many times." — http://perldoc.perl.org/sort.html
Quicksort is at one end of the spectrum of divide-and-conquer algorithms, with merge sort at the opposite end.
Quicksort is a conquer-then-divide algorithm, which does most of the work during the partitioning and the recursive calls. The subsequent reassembly of the sorted partitions involves trivial effort.
Merge sort is a divide-then-conquer algorithm. The partioning happens in a trivial way, by splitting the input array in half. Most of the work happens during the recursive calls and the merge phase.
With quicksort, every element in the first partition is less than or equal to every element in the second partition. Therefore, the merge phase of quicksort is so trivial that it needs no mention!
This task has not specified whether to allocate new arrays, or sort in place. This task also has not specified how to choose the pivot element. (Common ways to are to choose the first element, the middle element, or the median of three elements.) Thus there is a variety among the following implementations.
| #MUMPS | MUMPS |
main
new collection,size
set size=16
set collection=size for i=0:1:size-1 set collection(i)=$random(size)
write "Collection to sort:",!!
zwrite collection ; This will only work on Intersystem's flavor of MUMPS
do quicksort(.collection,0,collection-1)
write:$$isSorted(.collection) !,"Collection is sorted:",!!
zwrite collection ; This will only work on Intersystem's flavor of MUMPS
q
quicksort(array,low,high)
if low<high do
. set pivot=$$partition(.array,low,high)
. do quicksort(.array,low,pivot-1)
. do quicksort(.array,pivot+1,high)
q
partition(A,p,r)
set pivot=A(r)
set i=p-1
for j=p:1:r-1 do
. i A(j)<=pivot do
. . set i=i+1
. . set helper=A(j)
. . set A(j)=A(i)
. . set A(i)=helper
set helper=A(r)
set A(r)=A(i+1)
set A(i+1)=helper
quit i+1
isSorted(array)
set sorted=1
for i=0:1:array-2 do quit:sorted=0
. for j=i+1:1:array-1 do quit:sorted=0
. . set:array(i)>array(j) sorted=0
quit sorted
|
http://rosettacode.org/wiki/Sorting_algorithms/Insertion_sort | Sorting algorithms/Insertion sort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Insertion sort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
An O(n2) sorting algorithm which moves elements one at a time into the correct position.
The algorithm consists of inserting one element at a time into the previously sorted part of the array, moving higher ranked elements up as necessary.
To start off, the first (or smallest, or any arbitrary) element of the unsorted array is considered to be the sorted part.
Although insertion sort is an O(n2) algorithm, its simplicity, low overhead, good locality of reference and efficiency make it a good choice in two cases:
small n,
as the final finishing-off algorithm for O(n logn) algorithms such as mergesort and quicksort.
The algorithm is as follows (from wikipedia):
function insertionSort(array A)
for i from 1 to length[A]-1 do
value := A[i]
j := i-1
while j >= 0 and A[j] > value do
A[j+1] := A[j]
j := j-1
done
A[j+1] = value
done
Writing the algorithm for integers will suffice.
| #ooRexx | ooRexx | /* REXX program sorts a stemmed array (has characters) */
/* using the insertion sort algorithm */
Call gen /* fill the array with test data */
Call show 'before sort' /* display the elements */
Say copies('-',79) /* display a separator line */
Call insertionSort x.0 /* invoke the insertion sort. */
Call show ' after sort' /* display the elements after sort*/
Exit
/*--------------------------------------------------------------------*/
gen: Procedure Expose x.
x.1="---Monday's Child Is Fair of Face (by Mother Goose)---"
x.2="======================================================="
x.3="Monday's child is fair of face;"
x.4="Tuesday's child is full of grace;"
x.5="Wednesday's child is full of woe;"
x.6="Thursday's child has far to go;"
x.7="Friday's child is loving and giving;"
x.8="Saturday's child works hard for a living;"
x.9="But the child that is born on the Sabbath day"
x.10="Is blithe and bonny, good and gay."
x.0=10 /* number of elements */
Return
/*--------------------------------------------------------------------*/
insertionsort: Procedure Expose x.
Parse Arg n
Do i=2 To n
y=x.i
Do j=i-1 By -1 To 1 While x.j>y
z=j+1
x.z=x.j
/* Say 'set x.'z 'to x.'j '('||x.j||')' */
End
z=j+1
x.z=y
/* Say 'set x.'z 'to' y */
End
Return
/*--------------------------------------------------------------------*/
show:
Do j=1 To x.0
Say 'Element' right(j,length(x.0)) arg(1)":" x.j
End
Return |
http://rosettacode.org/wiki/Sorting_algorithms/Heapsort | Sorting algorithms/Heapsort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Heapsort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
Heapsort is an in-place sorting algorithm with worst case and average complexity of O(n logn).
The basic idea is to turn the array into a binary heap structure, which has the property that it allows efficient retrieval and removal of the maximal element.
We repeatedly "remove" the maximal element from the heap, thus building the sorted list from back to front.
A heap sort requires random access, so can only be used on an array-like data structure.
Pseudocode:
function heapSort(a, count) is
input: an unordered array a of length count
(first place a in max-heap order)
heapify(a, count)
end := count - 1
while end > 0 do
(swap the root(maximum value) of the heap with the
last element of the heap)
swap(a[end], a[0])
(decrement the size of the heap so that the previous
max value will stay in its proper place)
end := end - 1
(put the heap back in max-heap order)
siftDown(a, 0, end)
function heapify(a,count) is
(start is assigned the index in a of the last parent node)
start := (count - 2) / 2
while start ≥ 0 do
(sift down the node at index start to the proper place
such that all nodes below the start index are in heap
order)
siftDown(a, start, count-1)
start := start - 1
(after sifting down the root all nodes/elements are in heap order)
function siftDown(a, start, end) is
(end represents the limit of how far down the heap to sift)
root := start
while root * 2 + 1 ≤ end do (While the root has at least one child)
child := root * 2 + 1 (root*2+1 points to the left child)
(If the child has a sibling and the child's value is less than its sibling's...)
if child + 1 ≤ end and a[child] < a[child + 1] then
child := child + 1 (... then point to the right child instead)
if a[root] < a[child] then (out of max-heap order)
swap(a[root], a[child])
root := child (repeat to continue sifting down the child now)
else
return
Write a function to sort a collection of integers using heapsort.
| #Standard_ML | Standard ML | (* Pairing heap - http://en.wikipedia.org/wiki/Pairing_heap *)
functor PairingHeap(type t
val cmp : t * t -> order) =
struct
datatype 'a heap = Empty
| Heap of 'a * 'a heap list;
(* merge, O(1)
* Merges two heaps *)
fun merge (Empty, h) = h
| merge (h, Empty) = h
| merge (h1 as Heap(e1, s1), h2 as Heap(e2, s2)) =
case cmp (e1, e2) of LESS => Heap(e1, h2 :: s1)
| _ => Heap(e2, h1 :: s2)
(* insert, O(1)
* Inserts an element into the heap *)
fun insert (e, h) = merge (Heap (e, []), h)
(* findMin, O(1)
* Returns the smallest element of the heap *)
fun findMin Empty = raise Domain
| findMin (Heap(e, _)) = e
(* deleteMin, O(lg n) amortized
* Deletes the smallest element of the heap *)
local
fun mergePairs [] = Empty
| mergePairs [h] = h
| mergePairs (h1::h2::hs) = merge (merge(h1, h2), mergePairs hs)
in
fun deleteMin Empty = raise Domain
| deleteMin (Heap(_, s)) = mergePairs s
end
(* build, O(n)
* Builds a heap from a list *)
fun build es = foldl insert Empty es;
end
local
structure IntHeap = PairingHeap(type t = int; val cmp = Int.compare);
open IntHeap
fun heapsort' Empty = []
| heapsort' h = findMin h :: (heapsort' o deleteMin) h;
in
fun heapsort ls = (heapsort' o build) ls
val test_0 = heapsort [] = []
val test_1 = heapsort [1,2,3] = [1, 2, 3]
val test_2 = heapsort [1,3,2] = [1, 2, 3]
val test_3 = heapsort [6,2,7,5,8,1,3,4] = [1, 2, 3, 4, 5, 6, 7, 8]
end;
|
http://rosettacode.org/wiki/Sorting_algorithms/Heapsort | Sorting algorithms/Heapsort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Heapsort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
Heapsort is an in-place sorting algorithm with worst case and average complexity of O(n logn).
The basic idea is to turn the array into a binary heap structure, which has the property that it allows efficient retrieval and removal of the maximal element.
We repeatedly "remove" the maximal element from the heap, thus building the sorted list from back to front.
A heap sort requires random access, so can only be used on an array-like data structure.
Pseudocode:
function heapSort(a, count) is
input: an unordered array a of length count
(first place a in max-heap order)
heapify(a, count)
end := count - 1
while end > 0 do
(swap the root(maximum value) of the heap with the
last element of the heap)
swap(a[end], a[0])
(decrement the size of the heap so that the previous
max value will stay in its proper place)
end := end - 1
(put the heap back in max-heap order)
siftDown(a, 0, end)
function heapify(a,count) is
(start is assigned the index in a of the last parent node)
start := (count - 2) / 2
while start ≥ 0 do
(sift down the node at index start to the proper place
such that all nodes below the start index are in heap
order)
siftDown(a, start, count-1)
start := start - 1
(after sifting down the root all nodes/elements are in heap order)
function siftDown(a, start, end) is
(end represents the limit of how far down the heap to sift)
root := start
while root * 2 + 1 ≤ end do (While the root has at least one child)
child := root * 2 + 1 (root*2+1 points to the left child)
(If the child has a sibling and the child's value is less than its sibling's...)
if child + 1 ≤ end and a[child] < a[child + 1] then
child := child + 1 (... then point to the right child instead)
if a[root] < a[child] then (out of max-heap order)
swap(a[root], a[child])
root := child (repeat to continue sifting down the child now)
else
return
Write a function to sort a collection of integers using heapsort.
| #Stata | Stata | function siftup(a, i) {
k = i
while (k > 1) {
p = floor(k/2)
if (a[k] > a[p]) {
s = a[p]
a[p] = a[k]
a[k] = s
k = p
}
else break
}
}
function siftdown(a, i) {
k = 1
while (1) {
l = k+k
if (l > i) break
if (l+1 <= i) {
if (a[l+1] > a[l]) l++
}
if (a[k] < a[l]) {
s = a[k]
a[k] = a[l]
a[l] = s
k = l
}
else break
}
}
function heapsort(a) {
n = length(a)
for (i = 2; i <= n; i++) {
siftup(a, i)
}
for (i = n; i >= 2; i--) {
s = a[i]
a[i] = a[1]
a[1] = s
siftdown(a, i-1)
}
} |
http://rosettacode.org/wiki/Sorting_algorithms/Merge_sort | Sorting algorithms/Merge sort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
The merge sort is a recursive sort of order n*log(n).
It is notable for having a worst case and average complexity of O(n*log(n)), and a best case complexity of O(n) (for pre-sorted input).
The basic idea is to split the collection into smaller groups by halving it until the groups only have one element or no elements (which are both entirely sorted groups).
Then merge the groups back together so that their elements are in order.
This is how the algorithm gets its divide and conquer description.
Task
Write a function to sort a collection of integers using the merge sort.
The merge sort algorithm comes in two parts:
a sort function and
a merge function
The functions in pseudocode look like this:
function mergesort(m)
var list left, right, result
if length(m) ≤ 1
return m
else
var middle = length(m) / 2
for each x in m up to middle - 1
add x to left
for each x in m at and after middle
add x to right
left = mergesort(left)
right = mergesort(right)
if last(left) ≤ first(right)
append right to left
return left
result = merge(left, right)
return result
function merge(left,right)
var list result
while length(left) > 0 and length(right) > 0
if first(left) ≤ first(right)
append first(left) to result
left = rest(left)
else
append first(right) to result
right = rest(right)
if length(left) > 0
append rest(left) to result
if length(right) > 0
append rest(right) to result
return result
See also
the Wikipedia entry: merge sort
Note: better performance can be expected if, rather than recursing until length(m) ≤ 1, an insertion sort is used for length(m) smaller than some threshold larger than 1. However, this complicates the example code, so it is not shown here.
| #NetRexx | NetRexx | /* NetRexx */
options replace format comments java crossref savelog symbols binary
import java.util.List
placesList = [String -
"UK London", "US New York", "US Boston", "US Washington" -
, "UK Washington", "US Birmingham", "UK Birmingham", "UK Boston" -
]
lists = [ -
placesList -
, mergeSort(String[] Arrays.copyOf(placesList, placesList.length)) -
]
loop ln = 0 to lists.length - 1
cl = lists[ln]
loop ct = 0 to cl.length - 1
say cl[ct]
end ct
say
end ln
return
method mergeSort(m = String[]) public constant binary returns String[]
rl = String[m.length]
al = List mergeSort(Arrays.asList(m))
al.toArray(rl)
return rl
method mergeSort(m = List) public constant binary returns ArrayList
result = ArrayList(m.size)
left = ArrayList()
right = ArrayList()
if m.size > 1 then do
middle = m.size % 2
loop x_ = 0 to middle - 1
left.add(m.get(x_))
end x_
loop x_ = middle to m.size - 1
right.add(m.get(x_))
end x_
left = mergeSort(left)
right = mergeSort(right)
if (Comparable left.get(left.size - 1)).compareTo(Comparable right.get(0)) <= 0 then do
left.addAll(right)
result.addAll(m)
end
else do
result = merge(left, right)
end
end
else do
result.addAll(m)
end
return result
method merge(left = List, right = List) public constant binary returns ArrayList
result = ArrayList()
loop label mx while left.size > 0 & right.size > 0
if (Comparable left.get(0)).compareTo(Comparable right.get(0)) <= 0 then do
result.add(left.get(0))
left.remove(0)
end
else do
result.add(right.get(0))
right.remove(0)
end
end mx
if left.size > 0 then do
result.addAll(left)
end
if right.size > 0 then do
result.addAll(right)
end
return result
|
http://rosettacode.org/wiki/Stack | Stack |
Data Structure
This illustrates a data structure, a means of storing data within a program.
You may see other such structures in the Data Structures category.
A stack is a container of elements with last in, first out access policy. Sometimes it also called LIFO.
The stack is accessed through its top.
The basic stack operations are:
push stores a new element onto the stack top;
pop returns the last pushed stack element, while removing it from the stack;
empty tests if the stack contains no elements.
Sometimes the last pushed stack element is made accessible for immutable access (for read) or mutable access (for write):
top (sometimes called peek to keep with the p theme) returns the topmost element without modifying the stack.
Stacks allow a very simple hardware implementation.
They are common in almost all processors.
In programming, stacks are also very popular for their way (LIFO) of resource management, usually memory.
Nested scopes of language objects are naturally implemented by a stack (sometimes by multiple stacks).
This is a classical way to implement local variables of a re-entrant or recursive subprogram. Stacks are also used to describe a formal computational framework.
See stack machine.
Many algorithms in pattern matching, compiler construction (e.g. recursive descent parsers), and machine learning (e.g. based on tree traversal) have a natural representation in terms of stacks.
Task
Create a stack supporting the basic operations: push, pop, empty.
See also
Array
Associative array: Creation, Iteration
Collections
Compound data type
Doubly-linked list: Definition, Element definition, Element insertion, List Traversal, Element Removal
Linked list
Queue: Definition, Usage
Set
Singly-linked list: Element definition, Element insertion, List Traversal, Element Removal
Stack
| #XPL0 | XPL0 | include c:\cxpl\codes; \intrinsic 'code' declarations
int Stack(100), SP;
proc Push(I); \Push an integer onto the Stack
int I;
[SP:= SP+1;
Stack(SP):= I;
]; \Push
func Pop; \Pop an integer from the Stack
int I;
[I:= Stack(SP);
SP:= SP-1;
return I;
]; \Pop
func Empty; \Return 'true' if Stack is empty
return SP<0;
func Top; \Return the integer at top of Stack
return Stack(SP);
int I;
[SP:= -1; \initialize stack pointer
for I:= 0 to 10 do Push(I*I);
IntOut(0, Top); CrLf(0);
while not Empty do [IntOut(0, Pop); ChOut(0, ^ )];
CrLf(0);
] |
http://rosettacode.org/wiki/Sorting_algorithms/Quicksort | Sorting algorithms/Quicksort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Quicksort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
Task
Sort an array (or list) elements using the quicksort algorithm.
The elements must have a strict weak order and the index of the array can be of any discrete type.
For languages where this is not possible, sort an array of integers.
Quicksort, also known as partition-exchange sort, uses these steps.
Choose any element of the array to be the pivot.
Divide all other elements (except the pivot) into two partitions.
All elements less than the pivot must be in the first partition.
All elements greater than the pivot must be in the second partition.
Use recursion to sort both partitions.
Join the first sorted partition, the pivot, and the second sorted partition.
The best pivot creates partitions of equal length (or lengths differing by 1).
The worst pivot creates an empty partition (for example, if the pivot is the first or last element of a sorted array).
The run-time of Quicksort ranges from O(n log n) with the best pivots, to O(n2) with the worst pivots, where n is the number of elements in the array.
This is a simple quicksort algorithm, adapted from Wikipedia.
function quicksort(array)
less, equal, greater := three empty arrays
if length(array) > 1
pivot := select any element of array
for each x in array
if x < pivot then add x to less
if x = pivot then add x to equal
if x > pivot then add x to greater
quicksort(less)
quicksort(greater)
array := concatenate(less, equal, greater)
A better quicksort algorithm works in place, by swapping elements within the array, to avoid the memory allocation of more arrays.
function quicksort(array)
if length(array) > 1
pivot := select any element of array
left := first index of array
right := last index of array
while left ≤ right
while array[left] < pivot
left := left + 1
while array[right] > pivot
right := right - 1
if left ≤ right
swap array[left] with array[right]
left := left + 1
right := right - 1
quicksort(array from first index to right)
quicksort(array from left to last index)
Quicksort has a reputation as the fastest sort. Optimized variants of quicksort are common features of many languages and libraries. One often contrasts quicksort with merge sort, because both sorts have an average time of O(n log n).
"On average, mergesort does fewer comparisons than quicksort, so it may be better when complicated comparison routines are used. Mergesort also takes advantage of pre-existing order, so it would be favored for using sort() to merge several sorted arrays. On the other hand, quicksort is often faster for small arrays, and on arrays of a few distinct values, repeated many times." — http://perldoc.perl.org/sort.html
Quicksort is at one end of the spectrum of divide-and-conquer algorithms, with merge sort at the opposite end.
Quicksort is a conquer-then-divide algorithm, which does most of the work during the partitioning and the recursive calls. The subsequent reassembly of the sorted partitions involves trivial effort.
Merge sort is a divide-then-conquer algorithm. The partioning happens in a trivial way, by splitting the input array in half. Most of the work happens during the recursive calls and the merge phase.
With quicksort, every element in the first partition is less than or equal to every element in the second partition. Therefore, the merge phase of quicksort is so trivial that it needs no mention!
This task has not specified whether to allocate new arrays, or sort in place. This task also has not specified how to choose the pivot element. (Common ways to are to choose the first element, the middle element, or the median of three elements.) Thus there is a variety among the following implementations.
| #Nanoquery | Nanoquery | def quickSort(arr)
less = {}
pivotList = {}
more = {}
if len(arr) <= 1
return arr
else
pivot = arr[0]
for i in arr
if i < pivot
less.append(i)
else if i > pivot
more.append(i)
else
pivotList.append(i)
end
end
less = quickSort(less)
more = quickSort(more)
return less + pivotList + more
end
end |
http://rosettacode.org/wiki/Sorting_algorithms/Insertion_sort | Sorting algorithms/Insertion sort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Insertion sort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
An O(n2) sorting algorithm which moves elements one at a time into the correct position.
The algorithm consists of inserting one element at a time into the previously sorted part of the array, moving higher ranked elements up as necessary.
To start off, the first (or smallest, or any arbitrary) element of the unsorted array is considered to be the sorted part.
Although insertion sort is an O(n2) algorithm, its simplicity, low overhead, good locality of reference and efficiency make it a good choice in two cases:
small n,
as the final finishing-off algorithm for O(n logn) algorithms such as mergesort and quicksort.
The algorithm is as follows (from wikipedia):
function insertionSort(array A)
for i from 1 to length[A]-1 do
value := A[i]
j := i-1
while j >= 0 and A[j] > value do
A[j+1] := A[j]
j := j-1
done
A[j+1] = value
done
Writing the algorithm for integers will suffice.
| #Oz | Oz | declare
proc {InsertionSort A}
Low = {Array.low A}
High = {Array.high A}
in
for I in Low+1..High do
Value = A.I
J = {NewCell I-1}
in
for while:@J >= Low andthen A.@J > Value do
A.(@J+1) := A.@J
J := @J - 1
end
A.(@J+1) := Value
end
end
Arr = {Tuple.toArray unit(3 1 4 1 5 9 2 6 5)}
in
{InsertionSort Arr}
{Show {Array.toRecord unit Arr}} |
http://rosettacode.org/wiki/Sorting_algorithms/Heapsort | Sorting algorithms/Heapsort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Heapsort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
Heapsort is an in-place sorting algorithm with worst case and average complexity of O(n logn).
The basic idea is to turn the array into a binary heap structure, which has the property that it allows efficient retrieval and removal of the maximal element.
We repeatedly "remove" the maximal element from the heap, thus building the sorted list from back to front.
A heap sort requires random access, so can only be used on an array-like data structure.
Pseudocode:
function heapSort(a, count) is
input: an unordered array a of length count
(first place a in max-heap order)
heapify(a, count)
end := count - 1
while end > 0 do
(swap the root(maximum value) of the heap with the
last element of the heap)
swap(a[end], a[0])
(decrement the size of the heap so that the previous
max value will stay in its proper place)
end := end - 1
(put the heap back in max-heap order)
siftDown(a, 0, end)
function heapify(a,count) is
(start is assigned the index in a of the last parent node)
start := (count - 2) / 2
while start ≥ 0 do
(sift down the node at index start to the proper place
such that all nodes below the start index are in heap
order)
siftDown(a, start, count-1)
start := start - 1
(after sifting down the root all nodes/elements are in heap order)
function siftDown(a, start, end) is
(end represents the limit of how far down the heap to sift)
root := start
while root * 2 + 1 ≤ end do (While the root has at least one child)
child := root * 2 + 1 (root*2+1 points to the left child)
(If the child has a sibling and the child's value is less than its sibling's...)
if child + 1 ≤ end and a[child] < a[child + 1] then
child := child + 1 (... then point to the right child instead)
if a[root] < a[child] then (out of max-heap order)
swap(a[root], a[child])
root := child (repeat to continue sifting down the child now)
else
return
Write a function to sort a collection of integers using heapsort.
| #Swift | Swift | func heapsort<T:Comparable>(inout list:[T]) {
var count = list.count
func shiftDown(inout list:[T], start:Int, end:Int) {
var root = start
while root * 2 + 1 <= end {
var child = root * 2 + 1
var swap = root
if list[swap] < list[child] {
swap = child
}
if child + 1 <= end && list[swap] < list[child + 1] {
swap = child + 1
}
if swap == root {
return
} else {
(list[root], list[swap]) = (list[swap], list[root])
root = swap
}
}
}
func heapify(inout list:[T], count:Int) {
var start = (count - 2) / 2
while start >= 0 {
shiftDown(&list, start, count - 1)
start--
}
}
heapify(&list, count)
var end = count - 1
while end > 0 {
(list[end], list[0]) = (list[0], list[end])
end--
shiftDown(&list, 0, end)
}
} |
http://rosettacode.org/wiki/Sorting_algorithms/Heapsort | Sorting algorithms/Heapsort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Heapsort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
Heapsort is an in-place sorting algorithm with worst case and average complexity of O(n logn).
The basic idea is to turn the array into a binary heap structure, which has the property that it allows efficient retrieval and removal of the maximal element.
We repeatedly "remove" the maximal element from the heap, thus building the sorted list from back to front.
A heap sort requires random access, so can only be used on an array-like data structure.
Pseudocode:
function heapSort(a, count) is
input: an unordered array a of length count
(first place a in max-heap order)
heapify(a, count)
end := count - 1
while end > 0 do
(swap the root(maximum value) of the heap with the
last element of the heap)
swap(a[end], a[0])
(decrement the size of the heap so that the previous
max value will stay in its proper place)
end := end - 1
(put the heap back in max-heap order)
siftDown(a, 0, end)
function heapify(a,count) is
(start is assigned the index in a of the last parent node)
start := (count - 2) / 2
while start ≥ 0 do
(sift down the node at index start to the proper place
such that all nodes below the start index are in heap
order)
siftDown(a, start, count-1)
start := start - 1
(after sifting down the root all nodes/elements are in heap order)
function siftDown(a, start, end) is
(end represents the limit of how far down the heap to sift)
root := start
while root * 2 + 1 ≤ end do (While the root has at least one child)
child := root * 2 + 1 (root*2+1 points to the left child)
(If the child has a sibling and the child's value is less than its sibling's...)
if child + 1 ≤ end and a[child] < a[child + 1] then
child := child + 1 (... then point to the right child instead)
if a[root] < a[child] then (out of max-heap order)
swap(a[root], a[child])
root := child (repeat to continue sifting down the child now)
else
return
Write a function to sort a collection of integers using heapsort.
| #Tcl | Tcl | package require Tcl 8.5
proc heapsort {list {count ""}} {
if {$count eq ""} {
set count [llength $list]
}
for {set i [expr {$count/2 - 1}]} {$i >= 0} {incr i -1} {
siftDown list $i [expr {$count - 1}]
}
for {set i [expr {$count - 1}]} {$i > 0} {} {
swap list $i 0
incr i -1
siftDown list 0 $i
}
return $list
}
proc siftDown {varName i j} {
upvar 1 $varName a
while true {
set child [expr {$i*2 + 1}]
if {$child > $j} {
break
}
if {$child+1 <= $j && [lindex $a $child] < [lindex $a $child+1]} {
incr child
}
if {[lindex $a $i] >= [lindex $a $child]} {
break
}
swap a $i $child
set i $child
}
}
proc swap {varName x y} {
upvar 1 $varName a
set tmp [lindex $a $x]
lset a $x [lindex $a $y]
lset a $y $tmp
} |
http://rosettacode.org/wiki/Sorting_algorithms/Merge_sort | Sorting algorithms/Merge sort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
The merge sort is a recursive sort of order n*log(n).
It is notable for having a worst case and average complexity of O(n*log(n)), and a best case complexity of O(n) (for pre-sorted input).
The basic idea is to split the collection into smaller groups by halving it until the groups only have one element or no elements (which are both entirely sorted groups).
Then merge the groups back together so that their elements are in order.
This is how the algorithm gets its divide and conquer description.
Task
Write a function to sort a collection of integers using the merge sort.
The merge sort algorithm comes in two parts:
a sort function and
a merge function
The functions in pseudocode look like this:
function mergesort(m)
var list left, right, result
if length(m) ≤ 1
return m
else
var middle = length(m) / 2
for each x in m up to middle - 1
add x to left
for each x in m at and after middle
add x to right
left = mergesort(left)
right = mergesort(right)
if last(left) ≤ first(right)
append right to left
return left
result = merge(left, right)
return result
function merge(left,right)
var list result
while length(left) > 0 and length(right) > 0
if first(left) ≤ first(right)
append first(left) to result
left = rest(left)
else
append first(right) to result
right = rest(right)
if length(left) > 0
append rest(left) to result
if length(right) > 0
append rest(right) to result
return result
See also
the Wikipedia entry: merge sort
Note: better performance can be expected if, rather than recursing until length(m) ≤ 1, an insertion sort is used for length(m) smaller than some threshold larger than 1. However, this complicates the example code, so it is not shown here.
| #Nim | Nim | proc merge[T](a, b: var openarray[T]; left, middle, right: int) =
let
leftLen = middle - left
rightLen = right - middle
var
l = 0
r = leftLen
for i in left ..< middle:
b[l] = a[i]
inc l
for i in middle ..< right:
b[r] = a[i]
inc r
l = 0
r = leftLen
var i = left
while l < leftLen and r < leftLen + rightLen:
if b[l] < b[r]:
a[i] = b[l]
inc l
else:
a[i] = b[r]
inc r
inc i
while l < leftLen:
a[i] = b[l]
inc l
inc i
while r < leftLen + rightLen:
a[i] = b[r]
inc r
inc i
proc mergeSort[T](a, b: var openarray[T]; left, right: int) =
if right - left <= 1: return
let middle = (left + right) div 2
mergeSort(a, b, left, middle)
mergeSort(a, b, middle, right)
merge(a, b, left, middle, right)
proc mergeSort[T](a: var openarray[T]) =
var b = newSeq[T](a.len)
mergeSort(a, b, 0, a.len)
var a = @[4, 65, 2, -31, 0, 99, 2, 83, 782]
mergeSort a
echo a |
http://rosettacode.org/wiki/Stack | Stack |
Data Structure
This illustrates a data structure, a means of storing data within a program.
You may see other such structures in the Data Structures category.
A stack is a container of elements with last in, first out access policy. Sometimes it also called LIFO.
The stack is accessed through its top.
The basic stack operations are:
push stores a new element onto the stack top;
pop returns the last pushed stack element, while removing it from the stack;
empty tests if the stack contains no elements.
Sometimes the last pushed stack element is made accessible for immutable access (for read) or mutable access (for write):
top (sometimes called peek to keep with the p theme) returns the topmost element without modifying the stack.
Stacks allow a very simple hardware implementation.
They are common in almost all processors.
In programming, stacks are also very popular for their way (LIFO) of resource management, usually memory.
Nested scopes of language objects are naturally implemented by a stack (sometimes by multiple stacks).
This is a classical way to implement local variables of a re-entrant or recursive subprogram. Stacks are also used to describe a formal computational framework.
See stack machine.
Many algorithms in pattern matching, compiler construction (e.g. recursive descent parsers), and machine learning (e.g. based on tree traversal) have a natural representation in terms of stacks.
Task
Create a stack supporting the basic operations: push, pop, empty.
See also
Array
Associative array: Creation, Iteration
Collections
Compound data type
Doubly-linked list: Definition, Element definition, Element insertion, List Traversal, Element Removal
Linked list
Queue: Definition, Usage
Set
Singly-linked list: Element definition, Element insertion, List Traversal, Element Removal
Stack
| #Yabasic | Yabasic | limit = 1000
dim stack(limit)
top = 0
sub push(n)
if top < limit then
top = top + 1 : stack(top) = n
else
print "stack full - ";
end if
end sub
sub pop()
if top then
top = top - 1 : return stack(top + 1)
else
print "stack empty - ";
end if
end sub
sub empty()
return not top
end sub
// ======== test ========
for n = 3 to 5
print "Push ", n : push(n)
next
print "Pop ", pop()
print "Push ", 6 : push(6)
while(not empty())
print "Pop ", pop()
wend
print "Pop ", pop()
|
http://rosettacode.org/wiki/Sorting_algorithms/Quicksort | Sorting algorithms/Quicksort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Quicksort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
Task
Sort an array (or list) elements using the quicksort algorithm.
The elements must have a strict weak order and the index of the array can be of any discrete type.
For languages where this is not possible, sort an array of integers.
Quicksort, also known as partition-exchange sort, uses these steps.
Choose any element of the array to be the pivot.
Divide all other elements (except the pivot) into two partitions.
All elements less than the pivot must be in the first partition.
All elements greater than the pivot must be in the second partition.
Use recursion to sort both partitions.
Join the first sorted partition, the pivot, and the second sorted partition.
The best pivot creates partitions of equal length (or lengths differing by 1).
The worst pivot creates an empty partition (for example, if the pivot is the first or last element of a sorted array).
The run-time of Quicksort ranges from O(n log n) with the best pivots, to O(n2) with the worst pivots, where n is the number of elements in the array.
This is a simple quicksort algorithm, adapted from Wikipedia.
function quicksort(array)
less, equal, greater := three empty arrays
if length(array) > 1
pivot := select any element of array
for each x in array
if x < pivot then add x to less
if x = pivot then add x to equal
if x > pivot then add x to greater
quicksort(less)
quicksort(greater)
array := concatenate(less, equal, greater)
A better quicksort algorithm works in place, by swapping elements within the array, to avoid the memory allocation of more arrays.
function quicksort(array)
if length(array) > 1
pivot := select any element of array
left := first index of array
right := last index of array
while left ≤ right
while array[left] < pivot
left := left + 1
while array[right] > pivot
right := right - 1
if left ≤ right
swap array[left] with array[right]
left := left + 1
right := right - 1
quicksort(array from first index to right)
quicksort(array from left to last index)
Quicksort has a reputation as the fastest sort. Optimized variants of quicksort are common features of many languages and libraries. One often contrasts quicksort with merge sort, because both sorts have an average time of O(n log n).
"On average, mergesort does fewer comparisons than quicksort, so it may be better when complicated comparison routines are used. Mergesort also takes advantage of pre-existing order, so it would be favored for using sort() to merge several sorted arrays. On the other hand, quicksort is often faster for small arrays, and on arrays of a few distinct values, repeated many times." — http://perldoc.perl.org/sort.html
Quicksort is at one end of the spectrum of divide-and-conquer algorithms, with merge sort at the opposite end.
Quicksort is a conquer-then-divide algorithm, which does most of the work during the partitioning and the recursive calls. The subsequent reassembly of the sorted partitions involves trivial effort.
Merge sort is a divide-then-conquer algorithm. The partioning happens in a trivial way, by splitting the input array in half. Most of the work happens during the recursive calls and the merge phase.
With quicksort, every element in the first partition is less than or equal to every element in the second partition. Therefore, the merge phase of quicksort is so trivial that it needs no mention!
This task has not specified whether to allocate new arrays, or sort in place. This task also has not specified how to choose the pivot element. (Common ways to are to choose the first element, the middle element, or the median of three elements.) Thus there is a variety among the following implementations.
| #Nemerle | Nemerle | using System;
using System.Console;
using Nemerle.Collections.NList;
module Quicksort
{
Qsort[T] (x : list[T]) : list[T]
where T : IComparable
{
|[] => []
|x::xs => Qsort($[y|y in xs, (y.CompareTo(x) < 0)]) + [x] + Qsort($[y|y in xs, (y.CompareTo(x) > 0)])
}
Main() : void
{
def empty = [];
def single = [2];
def several = [2, 6, 1, 7, 3, 9, 4];
WriteLine(Qsort(empty));
WriteLine(Qsort(single));
WriteLine(Qsort(several));
}
} |
http://rosettacode.org/wiki/Sorting_algorithms/Insertion_sort | Sorting algorithms/Insertion sort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Insertion sort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
An O(n2) sorting algorithm which moves elements one at a time into the correct position.
The algorithm consists of inserting one element at a time into the previously sorted part of the array, moving higher ranked elements up as necessary.
To start off, the first (or smallest, or any arbitrary) element of the unsorted array is considered to be the sorted part.
Although insertion sort is an O(n2) algorithm, its simplicity, low overhead, good locality of reference and efficiency make it a good choice in two cases:
small n,
as the final finishing-off algorithm for O(n logn) algorithms such as mergesort and quicksort.
The algorithm is as follows (from wikipedia):
function insertionSort(array A)
for i from 1 to length[A]-1 do
value := A[i]
j := i-1
while j >= 0 and A[j] > value do
A[j+1] := A[j]
j := j-1
done
A[j+1] = value
done
Writing the algorithm for integers will suffice.
| #PARI.2FGP | PARI/GP | insertionSort(v)={
for(i=1,#v-1,
my(j=i-1,x=v[i]);
while(j && v[j]>x,
v[j+1]=v[j];
j--
);
v[j+1]=x
);
v
}; |
http://rosettacode.org/wiki/Sorting_algorithms/Heapsort | Sorting algorithms/Heapsort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Heapsort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
Heapsort is an in-place sorting algorithm with worst case and average complexity of O(n logn).
The basic idea is to turn the array into a binary heap structure, which has the property that it allows efficient retrieval and removal of the maximal element.
We repeatedly "remove" the maximal element from the heap, thus building the sorted list from back to front.
A heap sort requires random access, so can only be used on an array-like data structure.
Pseudocode:
function heapSort(a, count) is
input: an unordered array a of length count
(first place a in max-heap order)
heapify(a, count)
end := count - 1
while end > 0 do
(swap the root(maximum value) of the heap with the
last element of the heap)
swap(a[end], a[0])
(decrement the size of the heap so that the previous
max value will stay in its proper place)
end := end - 1
(put the heap back in max-heap order)
siftDown(a, 0, end)
function heapify(a,count) is
(start is assigned the index in a of the last parent node)
start := (count - 2) / 2
while start ≥ 0 do
(sift down the node at index start to the proper place
such that all nodes below the start index are in heap
order)
siftDown(a, start, count-1)
start := start - 1
(after sifting down the root all nodes/elements are in heap order)
function siftDown(a, start, end) is
(end represents the limit of how far down the heap to sift)
root := start
while root * 2 + 1 ≤ end do (While the root has at least one child)
child := root * 2 + 1 (root*2+1 points to the left child)
(If the child has a sibling and the child's value is less than its sibling's...)
if child + 1 ≤ end and a[child] < a[child + 1] then
child := child + 1 (... then point to the right child instead)
if a[root] < a[child] then (out of max-heap order)
swap(a[root], a[child])
root := child (repeat to continue sifting down the child now)
else
return
Write a function to sort a collection of integers using heapsort.
| #TI-83_BASIC | TI-83 BASIC | :If dim(L1)>7
:Then
:Disp "ERR:7"
:Stop
:End
:If dim(L1)<7
:Then
:For(A,1,7)
:If A>dim(L1)
:0→L1(A)
:End
:End
:{0}→L2
:For(B,2,7)
:0→L2(B)
:End
:L1→L3
:For(B,0,6)
:If L3(4)>L3(2)
:Then
:L3(2)→A
:L3(4)→L3(2)
:A→L3(4)
:End
:If L3(5)>L3(2)
:Then
:L3(2)→A
:L3(5)→L3(2)
:A→L3(5)
:End
:If L3(6)>L3(3)
:Then
:L3(3)→A
:L3(6)→L3(3)
:A→L3(6)
:End
:If L3(7)>L3(3)
:Then
:L3(3)→A
:L3(7)→L3(3)
:A→L3(7)
:End
:If L3(2)>L3(1)
:Then
:L3(1)→A
:L3(2)→L3(1)
:A→L3(2)
:End
:If L3(3)>L3(1)
:Then
:L3(1)→A
:L3(3)→L3(1)
:A→L3(3)
:End
:L3(1)→L2(7-B)
:If L3(2)>L3(3)
:Then
:L3(2)→L3(1)
:0→L3(2)
:Else
:L3(3)→L3(1)
:0→L3(3)
:End
:End
:DelVar A
:DelVar B
:DelVar L3
:Return
|
http://rosettacode.org/wiki/Sorting_algorithms/Merge_sort | Sorting algorithms/Merge sort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
The merge sort is a recursive sort of order n*log(n).
It is notable for having a worst case and average complexity of O(n*log(n)), and a best case complexity of O(n) (for pre-sorted input).
The basic idea is to split the collection into smaller groups by halving it until the groups only have one element or no elements (which are both entirely sorted groups).
Then merge the groups back together so that their elements are in order.
This is how the algorithm gets its divide and conquer description.
Task
Write a function to sort a collection of integers using the merge sort.
The merge sort algorithm comes in two parts:
a sort function and
a merge function
The functions in pseudocode look like this:
function mergesort(m)
var list left, right, result
if length(m) ≤ 1
return m
else
var middle = length(m) / 2
for each x in m up to middle - 1
add x to left
for each x in m at and after middle
add x to right
left = mergesort(left)
right = mergesort(right)
if last(left) ≤ first(right)
append right to left
return left
result = merge(left, right)
return result
function merge(left,right)
var list result
while length(left) > 0 and length(right) > 0
if first(left) ≤ first(right)
append first(left) to result
left = rest(left)
else
append first(right) to result
right = rest(right)
if length(left) > 0
append rest(left) to result
if length(right) > 0
append rest(right) to result
return result
See also
the Wikipedia entry: merge sort
Note: better performance can be expected if, rather than recursing until length(m) ≤ 1, an insertion sort is used for length(m) smaller than some threshold larger than 1. However, this complicates the example code, so it is not shown here.
| #OCaml | OCaml | let rec split_at n xs =
match n, xs with
0, xs ->
[], xs
| _, [] ->
failwith "index too large"
| n, x::xs when n > 0 ->
let xs', xs'' = split_at (pred n) xs in
x::xs', xs''
| _, _ ->
invalid_arg "negative argument"
let rec merge_sort cmp = function
[] -> []
| [x] -> [x]
| xs ->
let xs, ys = split_at (List.length xs / 2) xs in
List.merge cmp (merge_sort cmp xs) (merge_sort cmp ys)
let _ =
merge_sort compare [8;6;4;2;1;3;5;7;9] |
http://rosettacode.org/wiki/Stack | Stack |
Data Structure
This illustrates a data structure, a means of storing data within a program.
You may see other such structures in the Data Structures category.
A stack is a container of elements with last in, first out access policy. Sometimes it also called LIFO.
The stack is accessed through its top.
The basic stack operations are:
push stores a new element onto the stack top;
pop returns the last pushed stack element, while removing it from the stack;
empty tests if the stack contains no elements.
Sometimes the last pushed stack element is made accessible for immutable access (for read) or mutable access (for write):
top (sometimes called peek to keep with the p theme) returns the topmost element without modifying the stack.
Stacks allow a very simple hardware implementation.
They are common in almost all processors.
In programming, stacks are also very popular for their way (LIFO) of resource management, usually memory.
Nested scopes of language objects are naturally implemented by a stack (sometimes by multiple stacks).
This is a classical way to implement local variables of a re-entrant or recursive subprogram. Stacks are also used to describe a formal computational framework.
See stack machine.
Many algorithms in pattern matching, compiler construction (e.g. recursive descent parsers), and machine learning (e.g. based on tree traversal) have a natural representation in terms of stacks.
Task
Create a stack supporting the basic operations: push, pop, empty.
See also
Array
Associative array: Creation, Iteration
Collections
Compound data type
Doubly-linked list: Definition, Element definition, Element insertion, List Traversal, Element Removal
Linked list
Queue: Definition, Usage
Set
Singly-linked list: Element definition, Element insertion, List Traversal, Element Removal
Stack
| #Z80_Assembly | Z80 Assembly | LD SP,&FFFF |
http://rosettacode.org/wiki/Sorting_algorithms/Quicksort | Sorting algorithms/Quicksort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Quicksort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
Task
Sort an array (or list) elements using the quicksort algorithm.
The elements must have a strict weak order and the index of the array can be of any discrete type.
For languages where this is not possible, sort an array of integers.
Quicksort, also known as partition-exchange sort, uses these steps.
Choose any element of the array to be the pivot.
Divide all other elements (except the pivot) into two partitions.
All elements less than the pivot must be in the first partition.
All elements greater than the pivot must be in the second partition.
Use recursion to sort both partitions.
Join the first sorted partition, the pivot, and the second sorted partition.
The best pivot creates partitions of equal length (or lengths differing by 1).
The worst pivot creates an empty partition (for example, if the pivot is the first or last element of a sorted array).
The run-time of Quicksort ranges from O(n log n) with the best pivots, to O(n2) with the worst pivots, where n is the number of elements in the array.
This is a simple quicksort algorithm, adapted from Wikipedia.
function quicksort(array)
less, equal, greater := three empty arrays
if length(array) > 1
pivot := select any element of array
for each x in array
if x < pivot then add x to less
if x = pivot then add x to equal
if x > pivot then add x to greater
quicksort(less)
quicksort(greater)
array := concatenate(less, equal, greater)
A better quicksort algorithm works in place, by swapping elements within the array, to avoid the memory allocation of more arrays.
function quicksort(array)
if length(array) > 1
pivot := select any element of array
left := first index of array
right := last index of array
while left ≤ right
while array[left] < pivot
left := left + 1
while array[right] > pivot
right := right - 1
if left ≤ right
swap array[left] with array[right]
left := left + 1
right := right - 1
quicksort(array from first index to right)
quicksort(array from left to last index)
Quicksort has a reputation as the fastest sort. Optimized variants of quicksort are common features of many languages and libraries. One often contrasts quicksort with merge sort, because both sorts have an average time of O(n log n).
"On average, mergesort does fewer comparisons than quicksort, so it may be better when complicated comparison routines are used. Mergesort also takes advantage of pre-existing order, so it would be favored for using sort() to merge several sorted arrays. On the other hand, quicksort is often faster for small arrays, and on arrays of a few distinct values, repeated many times." — http://perldoc.perl.org/sort.html
Quicksort is at one end of the spectrum of divide-and-conquer algorithms, with merge sort at the opposite end.
Quicksort is a conquer-then-divide algorithm, which does most of the work during the partitioning and the recursive calls. The subsequent reassembly of the sorted partitions involves trivial effort.
Merge sort is a divide-then-conquer algorithm. The partioning happens in a trivial way, by splitting the input array in half. Most of the work happens during the recursive calls and the merge phase.
With quicksort, every element in the first partition is less than or equal to every element in the second partition. Therefore, the merge phase of quicksort is so trivial that it needs no mention!
This task has not specified whether to allocate new arrays, or sort in place. This task also has not specified how to choose the pivot element. (Common ways to are to choose the first element, the middle element, or the median of three elements.) Thus there is a variety among the following implementations.
| #NetRexx | NetRexx | /* NetRexx */
options replace format comments java crossref savelog symbols binary
import java.util.List
placesList = [String -
"UK London", "US New York", "US Boston", "US Washington" -
, "UK Washington", "US Birmingham", "UK Birmingham", "UK Boston" -
]
lists = [ -
placesList -
, quickSortSimple(String[] Arrays.copyOf(placesList, placesList.length)) -
, quickSortInplace(String[] Arrays.copyOf(placesList, placesList.length)) -
]
loop ln = 0 to lists.length - 1
cl = lists[ln]
loop ct = 0 to cl.length - 1
say cl[ct]
end ct
say
end ln
return
method quickSortSimple(array = String[]) public constant binary returns String[]
rl = String[array.length]
al = List quickSortSimple(Arrays.asList(array))
al.toArray(rl)
return rl
method quickSortSimple(array = List) public constant binary returns ArrayList
if array.size > 1 then do
less = ArrayList()
equal = ArrayList()
greater = ArrayList()
pivot = array.get(Random().nextInt(array.size - 1))
loop x_ = 0 to array.size - 1
if (Comparable array.get(x_)).compareTo(Comparable pivot) < 0 then less.add(array.get(x_))
if (Comparable array.get(x_)).compareTo(Comparable pivot) = 0 then equal.add(array.get(x_))
if (Comparable array.get(x_)).compareTo(Comparable pivot) > 0 then greater.add(array.get(x_))
end x_
less = quickSortSimple(less)
greater = quickSortSimple(greater)
out = ArrayList(array.size)
out.addAll(less)
out.addAll(equal)
out.addAll(greater)
array = out
end
return ArrayList array
method quickSortInplace(array = String[]) public constant binary returns String[]
rl = String[array.length]
al = List quickSortInplace(Arrays.asList(array))
al.toArray(rl)
return rl
method quickSortInplace(array = List, ixL = int 0, ixR = int array.size - 1) public constant binary returns ArrayList
if ixL < ixR then do
ixP = int ixL + (ixR - ixL) % 2
ixP = quickSortInplacePartition(array, ixL, ixR, ixP)
quickSortInplace(array, ixL, ixP - 1)
quickSortInplace(array, ixP + 1, ixR)
end
array = ArrayList(array)
return ArrayList array
method quickSortInplacePartition(array = List, ixL = int, ixR = int, ixP = int) public constant binary returns int
pivotValue = array.get(ixP)
rValue = array.get(ixR)
array.set(ixP, rValue)
array.set(ixR, pivotValue)
ixStore = ixL
loop i_ = ixL to ixR - 1
iValue = array.get(i_)
if (Comparable iValue).compareTo(Comparable pivotValue) < 0 then do
storeValue = array.get(ixStore)
array.set(i_, storeValue)
array.set(ixStore, iValue)
ixStore = ixStore + 1
end
end i_
storeValue = array.get(ixStore)
rValue = array.get(ixR)
array.set(ixStore, rValue)
array.set(ixR, storeValue)
return ixStore
|
http://rosettacode.org/wiki/Sorting_algorithms/Insertion_sort | Sorting algorithms/Insertion sort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Insertion sort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
An O(n2) sorting algorithm which moves elements one at a time into the correct position.
The algorithm consists of inserting one element at a time into the previously sorted part of the array, moving higher ranked elements up as necessary.
To start off, the first (or smallest, or any arbitrary) element of the unsorted array is considered to be the sorted part.
Although insertion sort is an O(n2) algorithm, its simplicity, low overhead, good locality of reference and efficiency make it a good choice in two cases:
small n,
as the final finishing-off algorithm for O(n logn) algorithms such as mergesort and quicksort.
The algorithm is as follows (from wikipedia):
function insertionSort(array A)
for i from 1 to length[A]-1 do
value := A[i]
j := i-1
while j >= 0 and A[j] > value do
A[j+1] := A[j]
j := j-1
done
A[j+1] = value
done
Writing the algorithm for integers will suffice.
| #Pascal | Pascal |
sub insertion_sort {
my (@list) = @_;
foreach my $i (1 .. $#list) {
my $j = $i;
my $k = $list[$i];
while ( $j > 0 && $k < $list[$j - 1]) {
$list[$j] = $list[$j - 1];
$j--;
}
$list[$j] = $k;
}
return @list;
}
my @a = insertion_sort(4, 65, 2, -31, 0, 99, 83, 782, 1);
print "@a\n";
|
http://rosettacode.org/wiki/Sorting_algorithms/Heapsort | Sorting algorithms/Heapsort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Heapsort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
Heapsort is an in-place sorting algorithm with worst case and average complexity of O(n logn).
The basic idea is to turn the array into a binary heap structure, which has the property that it allows efficient retrieval and removal of the maximal element.
We repeatedly "remove" the maximal element from the heap, thus building the sorted list from back to front.
A heap sort requires random access, so can only be used on an array-like data structure.
Pseudocode:
function heapSort(a, count) is
input: an unordered array a of length count
(first place a in max-heap order)
heapify(a, count)
end := count - 1
while end > 0 do
(swap the root(maximum value) of the heap with the
last element of the heap)
swap(a[end], a[0])
(decrement the size of the heap so that the previous
max value will stay in its proper place)
end := end - 1
(put the heap back in max-heap order)
siftDown(a, 0, end)
function heapify(a,count) is
(start is assigned the index in a of the last parent node)
start := (count - 2) / 2
while start ≥ 0 do
(sift down the node at index start to the proper place
such that all nodes below the start index are in heap
order)
siftDown(a, start, count-1)
start := start - 1
(after sifting down the root all nodes/elements are in heap order)
function siftDown(a, start, end) is
(end represents the limit of how far down the heap to sift)
root := start
while root * 2 + 1 ≤ end do (While the root has at least one child)
child := root * 2 + 1 (root*2+1 points to the left child)
(If the child has a sibling and the child's value is less than its sibling's...)
if child + 1 ≤ end and a[child] < a[child + 1] then
child := child + 1 (... then point to the right child instead)
if a[root] < a[child] then (out of max-heap order)
swap(a[root], a[child])
root := child (repeat to continue sifting down the child now)
else
return
Write a function to sort a collection of integers using heapsort.
| #True_BASIC | True BASIC |
!creamos la matriz y la inicializamos
LET lim = 20
DIM array(20)
FOR i = 1 TO lim
LET array(i) = INT(RND * 100) + 1
NEXT i
SUB printArray (lim)
FOR i = 1 TO lim
!PRINT USING("###", array(i));
PRINT array(i); " ";
NEXT i
PRINT
END SUB
SUB heapify (count)
LET start = INT(count / 2)
DO WHILE start >= 1
CALL siftDown (start, count)
LET start = start - 1
LOOP
END SUB
SUB siftDown (inicio, final)
LET root = inicio
DO WHILE root * 2 <= final
LET child = root * 2
LET SWAP = root
IF array(SWAP) < array(child) THEN
LET SWAP = child
END IF
IF child+1 <= final THEN
IF array(SWAP) < array(child+1) THEN
LET SWAP = child + 1
END IF
END IF
IF SWAP <> root THEN
CALL SWAP (root, SWAP)
LET root = SWAP
ELSE
EXIT SUB
END IF
LOOP
END SUB
SUB SWAP (x,y)
LET tmp = array(x)
LET array(x) = array(y)
LET array(y) = tmp
END SUB
SUB heapSort (count)
CALL heapify (count)
PRINT "el montículo:"
CALL printArray (count)
LET final = count
DO WHILE final > 1
CALL SWAP (final, 1)
CALL siftDown (1, final-1)
LET final = final - 1
LOOP
END SUB
!--------------------------
PRINT "Antes de ordenar:"
CALL printArray (lim)
PRINT
CALL heapSort (lim)
PRINT
PRINT "Despues de ordenar:"
CALL printArray (lim)
END
|
http://rosettacode.org/wiki/Sorting_algorithms/Merge_sort | Sorting algorithms/Merge sort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
The merge sort is a recursive sort of order n*log(n).
It is notable for having a worst case and average complexity of O(n*log(n)), and a best case complexity of O(n) (for pre-sorted input).
The basic idea is to split the collection into smaller groups by halving it until the groups only have one element or no elements (which are both entirely sorted groups).
Then merge the groups back together so that their elements are in order.
This is how the algorithm gets its divide and conquer description.
Task
Write a function to sort a collection of integers using the merge sort.
The merge sort algorithm comes in two parts:
a sort function and
a merge function
The functions in pseudocode look like this:
function mergesort(m)
var list left, right, result
if length(m) ≤ 1
return m
else
var middle = length(m) / 2
for each x in m up to middle - 1
add x to left
for each x in m at and after middle
add x to right
left = mergesort(left)
right = mergesort(right)
if last(left) ≤ first(right)
append right to left
return left
result = merge(left, right)
return result
function merge(left,right)
var list result
while length(left) > 0 and length(right) > 0
if first(left) ≤ first(right)
append first(left) to result
left = rest(left)
else
append first(right) to result
right = rest(right)
if length(left) > 0
append rest(left) to result
if length(right) > 0
append rest(right) to result
return result
See also
the Wikipedia entry: merge sort
Note: better performance can be expected if, rather than recursing until length(m) ≤ 1, an insertion sort is used for length(m) smaller than some threshold larger than 1. However, this complicates the example code, so it is not shown here.
| #Oz | Oz | declare
fun {MergeSort Xs}
case Xs
of nil then nil
[] [X] then [X]
else
Middle = {Length Xs} div 2
Left Right
{List.takeDrop Xs Middle ?Left ?Right}
in
{List.merge {MergeSort Left} {MergeSort Right} Value.'<'}
end
end
in
{Show {MergeSort [3 1 4 1 5 9 2 6 5]}} |
http://rosettacode.org/wiki/Stack | Stack |
Data Structure
This illustrates a data structure, a means of storing data within a program.
You may see other such structures in the Data Structures category.
A stack is a container of elements with last in, first out access policy. Sometimes it also called LIFO.
The stack is accessed through its top.
The basic stack operations are:
push stores a new element onto the stack top;
pop returns the last pushed stack element, while removing it from the stack;
empty tests if the stack contains no elements.
Sometimes the last pushed stack element is made accessible for immutable access (for read) or mutable access (for write):
top (sometimes called peek to keep with the p theme) returns the topmost element without modifying the stack.
Stacks allow a very simple hardware implementation.
They are common in almost all processors.
In programming, stacks are also very popular for their way (LIFO) of resource management, usually memory.
Nested scopes of language objects are naturally implemented by a stack (sometimes by multiple stacks).
This is a classical way to implement local variables of a re-entrant or recursive subprogram. Stacks are also used to describe a formal computational framework.
See stack machine.
Many algorithms in pattern matching, compiler construction (e.g. recursive descent parsers), and machine learning (e.g. based on tree traversal) have a natural representation in terms of stacks.
Task
Create a stack supporting the basic operations: push, pop, empty.
See also
Array
Associative array: Creation, Iteration
Collections
Compound data type
Doubly-linked list: Definition, Element definition, Element insertion, List Traversal, Element Removal
Linked list
Queue: Definition, Usage
Set
Singly-linked list: Element definition, Element insertion, List Traversal, Element Removal
Stack
| #zkl | zkl | class Stack{
var [const] stack=L();
fcn push(x){stack.append(x); self}
fcn pop {stack.pop()}
fcn empty {(not stack.len())}
var [proxy] isEmpty = empty;
} |
http://rosettacode.org/wiki/Sorting_algorithms/Quicksort | Sorting algorithms/Quicksort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Quicksort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
Task
Sort an array (or list) elements using the quicksort algorithm.
The elements must have a strict weak order and the index of the array can be of any discrete type.
For languages where this is not possible, sort an array of integers.
Quicksort, also known as partition-exchange sort, uses these steps.
Choose any element of the array to be the pivot.
Divide all other elements (except the pivot) into two partitions.
All elements less than the pivot must be in the first partition.
All elements greater than the pivot must be in the second partition.
Use recursion to sort both partitions.
Join the first sorted partition, the pivot, and the second sorted partition.
The best pivot creates partitions of equal length (or lengths differing by 1).
The worst pivot creates an empty partition (for example, if the pivot is the first or last element of a sorted array).
The run-time of Quicksort ranges from O(n log n) with the best pivots, to O(n2) with the worst pivots, where n is the number of elements in the array.
This is a simple quicksort algorithm, adapted from Wikipedia.
function quicksort(array)
less, equal, greater := three empty arrays
if length(array) > 1
pivot := select any element of array
for each x in array
if x < pivot then add x to less
if x = pivot then add x to equal
if x > pivot then add x to greater
quicksort(less)
quicksort(greater)
array := concatenate(less, equal, greater)
A better quicksort algorithm works in place, by swapping elements within the array, to avoid the memory allocation of more arrays.
function quicksort(array)
if length(array) > 1
pivot := select any element of array
left := first index of array
right := last index of array
while left ≤ right
while array[left] < pivot
left := left + 1
while array[right] > pivot
right := right - 1
if left ≤ right
swap array[left] with array[right]
left := left + 1
right := right - 1
quicksort(array from first index to right)
quicksort(array from left to last index)
Quicksort has a reputation as the fastest sort. Optimized variants of quicksort are common features of many languages and libraries. One often contrasts quicksort with merge sort, because both sorts have an average time of O(n log n).
"On average, mergesort does fewer comparisons than quicksort, so it may be better when complicated comparison routines are used. Mergesort also takes advantage of pre-existing order, so it would be favored for using sort() to merge several sorted arrays. On the other hand, quicksort is often faster for small arrays, and on arrays of a few distinct values, repeated many times." — http://perldoc.perl.org/sort.html
Quicksort is at one end of the spectrum of divide-and-conquer algorithms, with merge sort at the opposite end.
Quicksort is a conquer-then-divide algorithm, which does most of the work during the partitioning and the recursive calls. The subsequent reassembly of the sorted partitions involves trivial effort.
Merge sort is a divide-then-conquer algorithm. The partioning happens in a trivial way, by splitting the input array in half. Most of the work happens during the recursive calls and the merge phase.
With quicksort, every element in the first partition is less than or equal to every element in the second partition. Therefore, the merge phase of quicksort is so trivial that it needs no mention!
This task has not specified whether to allocate new arrays, or sort in place. This task also has not specified how to choose the pivot element. (Common ways to are to choose the first element, the middle element, or the median of three elements.) Thus there is a variety among the following implementations.
| #Nial | Nial | quicksort is fork [ >= [1 first,tally],
pass,
link [
quicksort sublist [ < [pass, first], pass ],
sublist [ match [pass,first],pass ],
quicksort sublist [ > [pass,first], pass ]
]
] |
http://rosettacode.org/wiki/Sorting_algorithms/Insertion_sort | Sorting algorithms/Insertion sort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Insertion sort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
An O(n2) sorting algorithm which moves elements one at a time into the correct position.
The algorithm consists of inserting one element at a time into the previously sorted part of the array, moving higher ranked elements up as necessary.
To start off, the first (or smallest, or any arbitrary) element of the unsorted array is considered to be the sorted part.
Although insertion sort is an O(n2) algorithm, its simplicity, low overhead, good locality of reference and efficiency make it a good choice in two cases:
small n,
as the final finishing-off algorithm for O(n logn) algorithms such as mergesort and quicksort.
The algorithm is as follows (from wikipedia):
function insertionSort(array A)
for i from 1 to length[A]-1 do
value := A[i]
j := i-1
while j >= 0 and A[j] > value do
A[j+1] := A[j]
j := j-1
done
A[j+1] = value
done
Writing the algorithm for integers will suffice.
| #Perl | Perl |
sub insertion_sort {
my (@list) = @_;
foreach my $i (1 .. $#list) {
my $j = $i;
my $k = $list[$i];
while ( $j > 0 && $k < $list[$j - 1]) {
$list[$j] = $list[$j - 1];
$j--;
}
$list[$j] = $k;
}
return @list;
}
my @a = insertion_sort(4, 65, 2, -31, 0, 99, 83, 782, 1);
print "@a\n";
|
http://rosettacode.org/wiki/Sorting_algorithms/Heapsort | Sorting algorithms/Heapsort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Heapsort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
Heapsort is an in-place sorting algorithm with worst case and average complexity of O(n logn).
The basic idea is to turn the array into a binary heap structure, which has the property that it allows efficient retrieval and removal of the maximal element.
We repeatedly "remove" the maximal element from the heap, thus building the sorted list from back to front.
A heap sort requires random access, so can only be used on an array-like data structure.
Pseudocode:
function heapSort(a, count) is
input: an unordered array a of length count
(first place a in max-heap order)
heapify(a, count)
end := count - 1
while end > 0 do
(swap the root(maximum value) of the heap with the
last element of the heap)
swap(a[end], a[0])
(decrement the size of the heap so that the previous
max value will stay in its proper place)
end := end - 1
(put the heap back in max-heap order)
siftDown(a, 0, end)
function heapify(a,count) is
(start is assigned the index in a of the last parent node)
start := (count - 2) / 2
while start ≥ 0 do
(sift down the node at index start to the proper place
such that all nodes below the start index are in heap
order)
siftDown(a, start, count-1)
start := start - 1
(after sifting down the root all nodes/elements are in heap order)
function siftDown(a, start, end) is
(end represents the limit of how far down the heap to sift)
root := start
while root * 2 + 1 ≤ end do (While the root has at least one child)
child := root * 2 + 1 (root*2+1 points to the left child)
(If the child has a sibling and the child's value is less than its sibling's...)
if child + 1 ≤ end and a[child] < a[child + 1] then
child := child + 1 (... then point to the right child instead)
if a[root] < a[child] then (out of max-heap order)
swap(a[root], a[child])
root := child (repeat to continue sifting down the child now)
else
return
Write a function to sort a collection of integers using heapsort.
| #uBasic.2F4tH | uBasic/4tH | PRINT "Heap sort:"
n = FUNC (_InitArray)
PROC _ShowArray (n)
PROC _Heapsort (n)
PROC _ShowArray (n)
PRINT
END
_Heapsort PARAM(1) ' Heapsort
LOCAL(1)
PROC _Heapify (a@)
b@ = a@ - 1
DO WHILE b@ > 0
PROC _Swap (b@, 0)
PROC _Siftdown (0, b@)
b@ = b@ - 1
LOOP
RETURN
_Heapify PARAM(1)
LOCAL(1)
b@ = (a@ - 2) / 2
DO WHILE b@ > -1
PROC _Siftdown (b@, a@)
b@ = b@ - 1
LOOP
RETURN
_Siftdown PARAM(2)
LOCAL(2)
c@ = a@
DO WHILE ((c@ * 2) + 1) < (b@)
d@ = c@ * 2 + 1
IF d@+1 < b@ IF @(d@) < @(d@+1) THEN d@ = d@ + 1
WHILE @(c@) < @(d@)
PROC _Swap (d@, c@)
c@ = d@
LOOP
RETURN
_Swap PARAM(2) ' Swap two array elements
PUSH @(a@)
@(a@) = @(b@)
@(b@) = POP()
RETURN
_InitArray ' Init example array
PUSH 4, 65, 2, -31, 0, 99, 2, 83, 782, 1
FOR i = 0 TO 9
@(i) = POP()
NEXT
RETURN (i)
_ShowArray PARAM (1) ' Show array subroutine
FOR i = 0 TO a@-1
PRINT @(i),
NEXT
PRINT
RETURN |
http://rosettacode.org/wiki/Sorting_algorithms/Merge_sort | Sorting algorithms/Merge sort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
The merge sort is a recursive sort of order n*log(n).
It is notable for having a worst case and average complexity of O(n*log(n)), and a best case complexity of O(n) (for pre-sorted input).
The basic idea is to split the collection into smaller groups by halving it until the groups only have one element or no elements (which are both entirely sorted groups).
Then merge the groups back together so that their elements are in order.
This is how the algorithm gets its divide and conquer description.
Task
Write a function to sort a collection of integers using the merge sort.
The merge sort algorithm comes in two parts:
a sort function and
a merge function
The functions in pseudocode look like this:
function mergesort(m)
var list left, right, result
if length(m) ≤ 1
return m
else
var middle = length(m) / 2
for each x in m up to middle - 1
add x to left
for each x in m at and after middle
add x to right
left = mergesort(left)
right = mergesort(right)
if last(left) ≤ first(right)
append right to left
return left
result = merge(left, right)
return result
function merge(left,right)
var list result
while length(left) > 0 and length(right) > 0
if first(left) ≤ first(right)
append first(left) to result
left = rest(left)
else
append first(right) to result
right = rest(right)
if length(left) > 0
append rest(left) to result
if length(right) > 0
append rest(right) to result
return result
See also
the Wikipedia entry: merge sort
Note: better performance can be expected if, rather than recursing until length(m) ≤ 1, an insertion sort is used for length(m) smaller than some threshold larger than 1. However, this complicates the example code, so it is not shown here.
| #PARI.2FGP | PARI/GP | mergeSort(v)={
if(#v<2, return(v));
my(m=#v\2,left=vector(m,i,v[i]),right=vector(#v-m,i,v[m+i]));
left=mergeSort(left);
right=mergeSort(right);
merge(left, right)
};
merge(u,v)={
my(ret=vector(#u+#v),i=1,j=1);
for(k=1,#ret,
if(i<=#u & (j>#v | u[i]<v[j]),
ret[k]=u[i];
i++
,
ret[k]=v[j];
j++
)
);
ret
}; |
http://rosettacode.org/wiki/Sorting_algorithms/Quicksort | Sorting algorithms/Quicksort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Quicksort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
Task
Sort an array (or list) elements using the quicksort algorithm.
The elements must have a strict weak order and the index of the array can be of any discrete type.
For languages where this is not possible, sort an array of integers.
Quicksort, also known as partition-exchange sort, uses these steps.
Choose any element of the array to be the pivot.
Divide all other elements (except the pivot) into two partitions.
All elements less than the pivot must be in the first partition.
All elements greater than the pivot must be in the second partition.
Use recursion to sort both partitions.
Join the first sorted partition, the pivot, and the second sorted partition.
The best pivot creates partitions of equal length (or lengths differing by 1).
The worst pivot creates an empty partition (for example, if the pivot is the first or last element of a sorted array).
The run-time of Quicksort ranges from O(n log n) with the best pivots, to O(n2) with the worst pivots, where n is the number of elements in the array.
This is a simple quicksort algorithm, adapted from Wikipedia.
function quicksort(array)
less, equal, greater := three empty arrays
if length(array) > 1
pivot := select any element of array
for each x in array
if x < pivot then add x to less
if x = pivot then add x to equal
if x > pivot then add x to greater
quicksort(less)
quicksort(greater)
array := concatenate(less, equal, greater)
A better quicksort algorithm works in place, by swapping elements within the array, to avoid the memory allocation of more arrays.
function quicksort(array)
if length(array) > 1
pivot := select any element of array
left := first index of array
right := last index of array
while left ≤ right
while array[left] < pivot
left := left + 1
while array[right] > pivot
right := right - 1
if left ≤ right
swap array[left] with array[right]
left := left + 1
right := right - 1
quicksort(array from first index to right)
quicksort(array from left to last index)
Quicksort has a reputation as the fastest sort. Optimized variants of quicksort are common features of many languages and libraries. One often contrasts quicksort with merge sort, because both sorts have an average time of O(n log n).
"On average, mergesort does fewer comparisons than quicksort, so it may be better when complicated comparison routines are used. Mergesort also takes advantage of pre-existing order, so it would be favored for using sort() to merge several sorted arrays. On the other hand, quicksort is often faster for small arrays, and on arrays of a few distinct values, repeated many times." — http://perldoc.perl.org/sort.html
Quicksort is at one end of the spectrum of divide-and-conquer algorithms, with merge sort at the opposite end.
Quicksort is a conquer-then-divide algorithm, which does most of the work during the partitioning and the recursive calls. The subsequent reassembly of the sorted partitions involves trivial effort.
Merge sort is a divide-then-conquer algorithm. The partioning happens in a trivial way, by splitting the input array in half. Most of the work happens during the recursive calls and the merge phase.
With quicksort, every element in the first partition is less than or equal to every element in the second partition. Therefore, the merge phase of quicksort is so trivial that it needs no mention!
This task has not specified whether to allocate new arrays, or sort in place. This task also has not specified how to choose the pivot element. (Common ways to are to choose the first element, the middle element, or the median of three elements.) Thus there is a variety among the following implementations.
| #Nim | Nim | proc quickSortImpl[T](a: var openarray[T], start, stop: int) =
if stop - start > 0:
let pivot = a[start]
var left = start
var right = stop
while left <= right:
while cmp(a[left], pivot) < 0:
inc(left)
while cmp(a[right], pivot) > 0:
dec(right)
if left <= right:
swap(a[left], a[right])
inc(left)
dec(right)
quickSortImpl(a, start, right)
quickSortImpl(a, left, stop)
proc quickSort[T](a: var openarray[T]) =
quickSortImpl(a, 0, a.len - 1)
var a = @[4, 65, 2, -31, 0, 99, 2, 83, 782]
a.quickSort()
echo a |
http://rosettacode.org/wiki/Sorting_algorithms/Insertion_sort | Sorting algorithms/Insertion sort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Insertion sort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
An O(n2) sorting algorithm which moves elements one at a time into the correct position.
The algorithm consists of inserting one element at a time into the previously sorted part of the array, moving higher ranked elements up as necessary.
To start off, the first (or smallest, or any arbitrary) element of the unsorted array is considered to be the sorted part.
Although insertion sort is an O(n2) algorithm, its simplicity, low overhead, good locality of reference and efficiency make it a good choice in two cases:
small n,
as the final finishing-off algorithm for O(n logn) algorithms such as mergesort and quicksort.
The algorithm is as follows (from wikipedia):
function insertionSort(array A)
for i from 1 to length[A]-1 do
value := A[i]
j := i-1
while j >= 0 and A[j] > value do
A[j+1] := A[j]
j := j-1
done
A[j+1] = value
done
Writing the algorithm for integers will suffice.
| #Phix | Phix | function insertion_sort(sequence s)
object temp
integer j
for i=2 to length(s) do
temp = s[i]
j = i-1
while j>=1 and s[j]>temp do
s[j+1] = s[j]
j -= 1
end while
s[j+1] = temp
end for
return s
end function
constant s = {4, 15, "delta", 2, -31, 0, "alpha", 19, "gamma", 2, 13, "beta", 782, 1}
puts(1,"Before: ") ?s
puts(1,"After: ") ?insertion_sort(s)
|
http://rosettacode.org/wiki/Sorting_algorithms/Heapsort | Sorting algorithms/Heapsort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Heapsort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
Heapsort is an in-place sorting algorithm with worst case and average complexity of O(n logn).
The basic idea is to turn the array into a binary heap structure, which has the property that it allows efficient retrieval and removal of the maximal element.
We repeatedly "remove" the maximal element from the heap, thus building the sorted list from back to front.
A heap sort requires random access, so can only be used on an array-like data structure.
Pseudocode:
function heapSort(a, count) is
input: an unordered array a of length count
(first place a in max-heap order)
heapify(a, count)
end := count - 1
while end > 0 do
(swap the root(maximum value) of the heap with the
last element of the heap)
swap(a[end], a[0])
(decrement the size of the heap so that the previous
max value will stay in its proper place)
end := end - 1
(put the heap back in max-heap order)
siftDown(a, 0, end)
function heapify(a,count) is
(start is assigned the index in a of the last parent node)
start := (count - 2) / 2
while start ≥ 0 do
(sift down the node at index start to the proper place
such that all nodes below the start index are in heap
order)
siftDown(a, start, count-1)
start := start - 1
(after sifting down the root all nodes/elements are in heap order)
function siftDown(a, start, end) is
(end represents the limit of how far down the heap to sift)
root := start
while root * 2 + 1 ≤ end do (While the root has at least one child)
child := root * 2 + 1 (root*2+1 points to the left child)
(If the child has a sibling and the child's value is less than its sibling's...)
if child + 1 ≤ end and a[child] < a[child + 1] then
child := child + 1 (... then point to the right child instead)
if a[root] < a[child] then (out of max-heap order)
swap(a[root], a[child])
root := child (repeat to continue sifting down the child now)
else
return
Write a function to sort a collection of integers using heapsort.
| #Vala | Vala | void swap(int[] array, int i1, int i2) {
if (array[i1] == array[i2])
return;
var tmp = array[i1];
array[i1] = array[i2];
array[i2] = tmp;
}
void shift_down(int[] heap, int i, int max) {
int i_big, c1, c2;
while (i < max) {
i_big = i;
c1 = (2 * i) + 1;
c2 = c1 + 1;
if (c1 < max && heap[c1] > heap[i_big])
i_big = c1;
if (c2 < max && heap[c2] > heap[i_big])
i_big = c2;
if (i_big == i) return;
swap(heap, i, i_big);
i = i_big;
}
}
void to_heap(int[] array) {
int i = (array.length / 2) - 1;
while (i >= 0) {
shift_down(array, i, array.length);
--i;
}
}
void heap_sort(int[] array) {
to_heap(array);
int end = array.length - 1;
while (end > 0) {
swap(array, 0, end);
shift_down(array, 0, end);
--end;
}
}
void main() {
int[] data = {
12, 11, 15, 10, 9,
1, 2, 13, 3, 14,
4, 5, 6, 7, 8
};
heap_sort(data);
foreach (int i in data) {
stdout.printf("%d ", i);
}
} |
http://rosettacode.org/wiki/Sorting_algorithms/Merge_sort | Sorting algorithms/Merge sort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
The merge sort is a recursive sort of order n*log(n).
It is notable for having a worst case and average complexity of O(n*log(n)), and a best case complexity of O(n) (for pre-sorted input).
The basic idea is to split the collection into smaller groups by halving it until the groups only have one element or no elements (which are both entirely sorted groups).
Then merge the groups back together so that their elements are in order.
This is how the algorithm gets its divide and conquer description.
Task
Write a function to sort a collection of integers using the merge sort.
The merge sort algorithm comes in two parts:
a sort function and
a merge function
The functions in pseudocode look like this:
function mergesort(m)
var list left, right, result
if length(m) ≤ 1
return m
else
var middle = length(m) / 2
for each x in m up to middle - 1
add x to left
for each x in m at and after middle
add x to right
left = mergesort(left)
right = mergesort(right)
if last(left) ≤ first(right)
append right to left
return left
result = merge(left, right)
return result
function merge(left,right)
var list result
while length(left) > 0 and length(right) > 0
if first(left) ≤ first(right)
append first(left) to result
left = rest(left)
else
append first(right) to result
right = rest(right)
if length(left) > 0
append rest(left) to result
if length(right) > 0
append rest(right) to result
return result
See also
the Wikipedia entry: merge sort
Note: better performance can be expected if, rather than recursing until length(m) ≤ 1, an insertion sort is used for length(m) smaller than some threshold larger than 1. However, this complicates the example code, so it is not shown here.
| #Pascal | Pascal | program MergeSortDemo;
{$IFDEF FPC}
{$MODE DELPHI}
{$ENDIF}
type
TIntArray = array of integer;
function merge(left, right: TIntArray): TIntArray;
var
i, j: integer;
begin
j := 0;
setlength(Result, length(left) + length(right));
while (length(left) > 0) and (length(right) > 0) do
begin
if left[0] <= right[0] then
begin
Result[j] := left[0];
inc(j);
for i := low(left) to high(left) - 1 do
left[i] := left[i+1];
setlength(left, length(left) - 1);
end
else
begin
Result[j] := right[0];
inc(j);
for i := low(right) to high(right) - 1 do
right[i] := right[i+1];
setlength(right, length(right) - 1);
end;
end;
if length(left) > 0 then
for i := low(left) to high(left) do
Result[j + i] := left[i];
j := j + length(left);
if length(right) > 0 then
for i := low(right) to high(right) do
Result[j + i] := right[i];
end;
function mergeSort(m: TIntArray): TIntArray;
var
left, right: TIntArray;
i, middle: integer;
begin
setlength(Result, length(m));
if length(m) = 1 then
Result[0] := m[0]
else if length(m) > 1 then
begin
middle := length(m) div 2;
setlength(left, middle);
setlength(right, length(m)-middle);
for i := low(left) to high(left) do
left[i] := m[i];
for i := low(right) to high(right) do
right[i] := m[middle+i];
left := mergeSort(left);
right := mergeSort(right);
Result := merge(left, right);
end;
end;
var
data: TIntArray;
i: integer;
begin
setlength(data, 8);
Randomize;
writeln('The data before sorting:');
for i := low(data) to high(data) do
begin
data[i] := Random(high(data));
write(data[i]:4);
end;
writeln;
data := mergeSort(data);
writeln('The data after sorting:');
for i := low(data) to high(data) do
begin
write(data[i]:4);
end;
writeln;
end. |
http://rosettacode.org/wiki/Sorting_algorithms/Quicksort | Sorting algorithms/Quicksort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Quicksort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
Task
Sort an array (or list) elements using the quicksort algorithm.
The elements must have a strict weak order and the index of the array can be of any discrete type.
For languages where this is not possible, sort an array of integers.
Quicksort, also known as partition-exchange sort, uses these steps.
Choose any element of the array to be the pivot.
Divide all other elements (except the pivot) into two partitions.
All elements less than the pivot must be in the first partition.
All elements greater than the pivot must be in the second partition.
Use recursion to sort both partitions.
Join the first sorted partition, the pivot, and the second sorted partition.
The best pivot creates partitions of equal length (or lengths differing by 1).
The worst pivot creates an empty partition (for example, if the pivot is the first or last element of a sorted array).
The run-time of Quicksort ranges from O(n log n) with the best pivots, to O(n2) with the worst pivots, where n is the number of elements in the array.
This is a simple quicksort algorithm, adapted from Wikipedia.
function quicksort(array)
less, equal, greater := three empty arrays
if length(array) > 1
pivot := select any element of array
for each x in array
if x < pivot then add x to less
if x = pivot then add x to equal
if x > pivot then add x to greater
quicksort(less)
quicksort(greater)
array := concatenate(less, equal, greater)
A better quicksort algorithm works in place, by swapping elements within the array, to avoid the memory allocation of more arrays.
function quicksort(array)
if length(array) > 1
pivot := select any element of array
left := first index of array
right := last index of array
while left ≤ right
while array[left] < pivot
left := left + 1
while array[right] > pivot
right := right - 1
if left ≤ right
swap array[left] with array[right]
left := left + 1
right := right - 1
quicksort(array from first index to right)
quicksort(array from left to last index)
Quicksort has a reputation as the fastest sort. Optimized variants of quicksort are common features of many languages and libraries. One often contrasts quicksort with merge sort, because both sorts have an average time of O(n log n).
"On average, mergesort does fewer comparisons than quicksort, so it may be better when complicated comparison routines are used. Mergesort also takes advantage of pre-existing order, so it would be favored for using sort() to merge several sorted arrays. On the other hand, quicksort is often faster for small arrays, and on arrays of a few distinct values, repeated many times." — http://perldoc.perl.org/sort.html
Quicksort is at one end of the spectrum of divide-and-conquer algorithms, with merge sort at the opposite end.
Quicksort is a conquer-then-divide algorithm, which does most of the work during the partitioning and the recursive calls. The subsequent reassembly of the sorted partitions involves trivial effort.
Merge sort is a divide-then-conquer algorithm. The partioning happens in a trivial way, by splitting the input array in half. Most of the work happens during the recursive calls and the merge phase.
With quicksort, every element in the first partition is less than or equal to every element in the second partition. Therefore, the merge phase of quicksort is so trivial that it needs no mention!
This task has not specified whether to allocate new arrays, or sort in place. This task also has not specified how to choose the pivot element. (Common ways to are to choose the first element, the middle element, or the median of three elements.) Thus there is a variety among the following implementations.
| #Nix | Nix |
let
qs = l:
if l == [] then []
else
with builtins;
let x = head l;
xs = tail l;
low = filter (a: a < x) xs;
high = filter (a: a >= x) xs;
in qs low ++ [x] ++ qs high;
in
qs [4 65 2 (-31) 0 99 83 782]
|
http://rosettacode.org/wiki/Sorting_algorithms/Insertion_sort | Sorting algorithms/Insertion sort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Insertion sort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
An O(n2) sorting algorithm which moves elements one at a time into the correct position.
The algorithm consists of inserting one element at a time into the previously sorted part of the array, moving higher ranked elements up as necessary.
To start off, the first (or smallest, or any arbitrary) element of the unsorted array is considered to be the sorted part.
Although insertion sort is an O(n2) algorithm, its simplicity, low overhead, good locality of reference and efficiency make it a good choice in two cases:
small n,
as the final finishing-off algorithm for O(n logn) algorithms such as mergesort and quicksort.
The algorithm is as follows (from wikipedia):
function insertionSort(array A)
for i from 1 to length[A]-1 do
value := A[i]
j := i-1
while j >= 0 and A[j] > value do
A[j+1] := A[j]
j := j-1
done
A[j+1] = value
done
Writing the algorithm for integers will suffice.
| #PHP | PHP | function insertionSort(&$arr){
for($i=0;$i<count($arr);$i++){
$val = $arr[$i];
$j = $i-1;
while($j>=0 && $arr[$j] > $val){
$arr[$j+1] = $arr[$j];
$j--;
}
$arr[$j+1] = $val;
}
}
$arr = array(4,2,1,6,9,3,8,7);
insertionSort($arr);
echo implode(',',$arr); |
http://rosettacode.org/wiki/Sorting_algorithms/Heapsort | Sorting algorithms/Heapsort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Heapsort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
Heapsort is an in-place sorting algorithm with worst case and average complexity of O(n logn).
The basic idea is to turn the array into a binary heap structure, which has the property that it allows efficient retrieval and removal of the maximal element.
We repeatedly "remove" the maximal element from the heap, thus building the sorted list from back to front.
A heap sort requires random access, so can only be used on an array-like data structure.
Pseudocode:
function heapSort(a, count) is
input: an unordered array a of length count
(first place a in max-heap order)
heapify(a, count)
end := count - 1
while end > 0 do
(swap the root(maximum value) of the heap with the
last element of the heap)
swap(a[end], a[0])
(decrement the size of the heap so that the previous
max value will stay in its proper place)
end := end - 1
(put the heap back in max-heap order)
siftDown(a, 0, end)
function heapify(a,count) is
(start is assigned the index in a of the last parent node)
start := (count - 2) / 2
while start ≥ 0 do
(sift down the node at index start to the proper place
such that all nodes below the start index are in heap
order)
siftDown(a, start, count-1)
start := start - 1
(after sifting down the root all nodes/elements are in heap order)
function siftDown(a, start, end) is
(end represents the limit of how far down the heap to sift)
root := start
while root * 2 + 1 ≤ end do (While the root has at least one child)
child := root * 2 + 1 (root*2+1 points to the left child)
(If the child has a sibling and the child's value is less than its sibling's...)
if child + 1 ≤ end and a[child] < a[child + 1] then
child := child + 1 (... then point to the right child instead)
if a[root] < a[child] then (out of max-heap order)
swap(a[root], a[child])
root := child (repeat to continue sifting down the child now)
else
return
Write a function to sort a collection of integers using heapsort.
| #VBA | VBA | Sub SiftDown(list() As Integer, start As Long, eend As Long)
Dim root As Long : root = start
Dim lb As Long : lb = LBound(list)
Dim temp As Integer
While root * 2 + 1 <= eend
Dim child As Long : child = root * 2 + 1
If child + 1 <= eend Then
If list(lb + child) < list(lb + child + 1) Then
child = child + 1
End If
End If
If list(lb + root) < list(lb + child) Then
temp = list(lb + root)
list(lb + root) = list(lb + child)
list(lb + child) = temp
root = child
Else
Exit Sub
End If
Wend
End Sub
Sub HeapSort(list() As Integer)
Dim lb As Long : lb = LBound(list)
Dim count As Long : count = UBound(list) - lb + 1
Dim start As Long : start = (count - 2) \ 2
Dim eend As Long : eend = count - 1
While start >= 0
SiftDown list(), start, eend
start = start - 1
Wend
Dim temp As Integer
While eend > 0
temp = list(lb + eend)
list(lb + eend) = list(lb)
list(lb) = temp
eend = eend - 1
SiftDown list(), 0, eend
Wend
End Sub |
http://rosettacode.org/wiki/Sorting_algorithms/Heapsort | Sorting algorithms/Heapsort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Heapsort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
Heapsort is an in-place sorting algorithm with worst case and average complexity of O(n logn).
The basic idea is to turn the array into a binary heap structure, which has the property that it allows efficient retrieval and removal of the maximal element.
We repeatedly "remove" the maximal element from the heap, thus building the sorted list from back to front.
A heap sort requires random access, so can only be used on an array-like data structure.
Pseudocode:
function heapSort(a, count) is
input: an unordered array a of length count
(first place a in max-heap order)
heapify(a, count)
end := count - 1
while end > 0 do
(swap the root(maximum value) of the heap with the
last element of the heap)
swap(a[end], a[0])
(decrement the size of the heap so that the previous
max value will stay in its proper place)
end := end - 1
(put the heap back in max-heap order)
siftDown(a, 0, end)
function heapify(a,count) is
(start is assigned the index in a of the last parent node)
start := (count - 2) / 2
while start ≥ 0 do
(sift down the node at index start to the proper place
such that all nodes below the start index are in heap
order)
siftDown(a, start, count-1)
start := start - 1
(after sifting down the root all nodes/elements are in heap order)
function siftDown(a, start, end) is
(end represents the limit of how far down the heap to sift)
root := start
while root * 2 + 1 ≤ end do (While the root has at least one child)
child := root * 2 + 1 (root*2+1 points to the left child)
(If the child has a sibling and the child's value is less than its sibling's...)
if child + 1 ≤ end and a[child] < a[child + 1] then
child := child + 1 (... then point to the right child instead)
if a[root] < a[child] then (out of max-heap order)
swap(a[root], a[child])
root := child (repeat to continue sifting down the child now)
else
return
Write a function to sort a collection of integers using heapsort.
| #Wren | Wren | var siftDown = Fn.new { |a, start, end|
var root = start
while (root*2 + 1 <= end) {
var child = root*2 + 1
if (child + 1 <= end && a[child] < a[child+1]) child = child + 1
if (a[root] < a[child]) {
var t = a[root]
a[root] = a[child]
a[child] = t
root = child
} else {
return
}
}
}
var heapify = Fn.new { |a, count|
var start = ((count - 2)/2).floor
while (start >= 0) {
siftDown.call(a, start, count - 1)
start = start - 1
}
}
var heapSort = Fn.new { |a|
var count = a.count
heapify.call(a, count)
var end = count - 1
while (end > 0) {
var t = a[end]
a[end] = a[0]
a[0] = t
end = end - 1
siftDown.call(a, 0, end)
}
}
var as = [ [4, 65, 2, -31, 0, 99, 2, 83, 782, 1], [7, 5, 2, 6, 1, 4, 2, 6, 3] ]
for (a in as) {
System.print("Before: %(a)")
heapSort.call(a)
System.print("After : %(a)")
System.print()
} |
http://rosettacode.org/wiki/Sorting_algorithms/Merge_sort | Sorting algorithms/Merge sort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
The merge sort is a recursive sort of order n*log(n).
It is notable for having a worst case and average complexity of O(n*log(n)), and a best case complexity of O(n) (for pre-sorted input).
The basic idea is to split the collection into smaller groups by halving it until the groups only have one element or no elements (which are both entirely sorted groups).
Then merge the groups back together so that their elements are in order.
This is how the algorithm gets its divide and conquer description.
Task
Write a function to sort a collection of integers using the merge sort.
The merge sort algorithm comes in two parts:
a sort function and
a merge function
The functions in pseudocode look like this:
function mergesort(m)
var list left, right, result
if length(m) ≤ 1
return m
else
var middle = length(m) / 2
for each x in m up to middle - 1
add x to left
for each x in m at and after middle
add x to right
left = mergesort(left)
right = mergesort(right)
if last(left) ≤ first(right)
append right to left
return left
result = merge(left, right)
return result
function merge(left,right)
var list result
while length(left) > 0 and length(right) > 0
if first(left) ≤ first(right)
append first(left) to result
left = rest(left)
else
append first(right) to result
right = rest(right)
if length(left) > 0
append rest(left) to result
if length(right) > 0
append rest(right) to result
return result
See also
the Wikipedia entry: merge sort
Note: better performance can be expected if, rather than recursing until length(m) ≤ 1, an insertion sort is used for length(m) smaller than some threshold larger than 1. However, this complicates the example code, so it is not shown here.
| #Perl | Perl | sub merge_sort {
my @x = @_;
return @x if @x < 2;
my $m = int @x / 2;
my @a = merge_sort(@x[0 .. $m - 1]);
my @b = merge_sort(@x[$m .. $#x]);
for (@x) {
$_ = !@a ? shift @b
: !@b ? shift @a
: $a[0] <= $b[0] ? shift @a
: shift @b;
}
@x;
}
my @a = (4, 65, 2, -31, 0, 99, 83, 782, 1);
@a = merge_sort @a;
print "@a\n"; |
http://rosettacode.org/wiki/Sorting_algorithms/Quicksort | Sorting algorithms/Quicksort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Quicksort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
Task
Sort an array (or list) elements using the quicksort algorithm.
The elements must have a strict weak order and the index of the array can be of any discrete type.
For languages where this is not possible, sort an array of integers.
Quicksort, also known as partition-exchange sort, uses these steps.
Choose any element of the array to be the pivot.
Divide all other elements (except the pivot) into two partitions.
All elements less than the pivot must be in the first partition.
All elements greater than the pivot must be in the second partition.
Use recursion to sort both partitions.
Join the first sorted partition, the pivot, and the second sorted partition.
The best pivot creates partitions of equal length (or lengths differing by 1).
The worst pivot creates an empty partition (for example, if the pivot is the first or last element of a sorted array).
The run-time of Quicksort ranges from O(n log n) with the best pivots, to O(n2) with the worst pivots, where n is the number of elements in the array.
This is a simple quicksort algorithm, adapted from Wikipedia.
function quicksort(array)
less, equal, greater := three empty arrays
if length(array) > 1
pivot := select any element of array
for each x in array
if x < pivot then add x to less
if x = pivot then add x to equal
if x > pivot then add x to greater
quicksort(less)
quicksort(greater)
array := concatenate(less, equal, greater)
A better quicksort algorithm works in place, by swapping elements within the array, to avoid the memory allocation of more arrays.
function quicksort(array)
if length(array) > 1
pivot := select any element of array
left := first index of array
right := last index of array
while left ≤ right
while array[left] < pivot
left := left + 1
while array[right] > pivot
right := right - 1
if left ≤ right
swap array[left] with array[right]
left := left + 1
right := right - 1
quicksort(array from first index to right)
quicksort(array from left to last index)
Quicksort has a reputation as the fastest sort. Optimized variants of quicksort are common features of many languages and libraries. One often contrasts quicksort with merge sort, because both sorts have an average time of O(n log n).
"On average, mergesort does fewer comparisons than quicksort, so it may be better when complicated comparison routines are used. Mergesort also takes advantage of pre-existing order, so it would be favored for using sort() to merge several sorted arrays. On the other hand, quicksort is often faster for small arrays, and on arrays of a few distinct values, repeated many times." — http://perldoc.perl.org/sort.html
Quicksort is at one end of the spectrum of divide-and-conquer algorithms, with merge sort at the opposite end.
Quicksort is a conquer-then-divide algorithm, which does most of the work during the partitioning and the recursive calls. The subsequent reassembly of the sorted partitions involves trivial effort.
Merge sort is a divide-then-conquer algorithm. The partioning happens in a trivial way, by splitting the input array in half. Most of the work happens during the recursive calls and the merge phase.
With quicksort, every element in the first partition is less than or equal to every element in the second partition. Therefore, the merge phase of quicksort is so trivial that it needs no mention!
This task has not specified whether to allocate new arrays, or sort in place. This task also has not specified how to choose the pivot element. (Common ways to are to choose the first element, the middle element, or the median of three elements.) Thus there is a variety among the following implementations.
| #Objeck | Objeck |
class QuickSort {
function : Main(args : String[]) ~ Nil {
array := [1, 3, 5, 7, 9, 8, 6, 4, 2];
Sort(array);
each(i : array) {
array[i]->PrintLine();
};
}
function : Sort(array : Int[]) ~ Nil {
size := array->Size();
if(size <= 1) {
return;
};
Sort(array, 0, size - 1);
}
function : native : Sort(array : Int[], low : Int, high : Int) ~ Nil {
i := low; j := high;
pivot := array[low + (high-low)/2];
while(i <= j) {
while(array[i] < pivot) {
i+=1;
};
while(array[j] > pivot) {
j-=1;
};
if (i <= j) {
temp := array[i];
array[i] := array[j];
array[j] := temp;
i+=1; j-=1;
};
};
if(low < j) {
Sort(array, low, j);
};
if(i < high) {
Sort(array, i, high);
};
}
}
|
http://rosettacode.org/wiki/Sorting_algorithms/Insertion_sort | Sorting algorithms/Insertion sort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Insertion sort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
An O(n2) sorting algorithm which moves elements one at a time into the correct position.
The algorithm consists of inserting one element at a time into the previously sorted part of the array, moving higher ranked elements up as necessary.
To start off, the first (or smallest, or any arbitrary) element of the unsorted array is considered to be the sorted part.
Although insertion sort is an O(n2) algorithm, its simplicity, low overhead, good locality of reference and efficiency make it a good choice in two cases:
small n,
as the final finishing-off algorithm for O(n logn) algorithms such as mergesort and quicksort.
The algorithm is as follows (from wikipedia):
function insertionSort(array A)
for i from 1 to length[A]-1 do
value := A[i]
j := i-1
while j >= 0 and A[j] > value do
A[j+1] := A[j]
j := j-1
done
A[j+1] = value
done
Writing the algorithm for integers will suffice.
| #PicoLisp | PicoLisp | (de insertionSort (Lst)
(for (I (cdr Lst) I (cdr I))
(for (J Lst (n== J I) (cdr J))
(T (> (car J) (car I))
(rot J (offset I J)) ) ) )
Lst ) |
http://rosettacode.org/wiki/Sorting_algorithms/Heapsort | Sorting algorithms/Heapsort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Heapsort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
Heapsort is an in-place sorting algorithm with worst case and average complexity of O(n logn).
The basic idea is to turn the array into a binary heap structure, which has the property that it allows efficient retrieval and removal of the maximal element.
We repeatedly "remove" the maximal element from the heap, thus building the sorted list from back to front.
A heap sort requires random access, so can only be used on an array-like data structure.
Pseudocode:
function heapSort(a, count) is
input: an unordered array a of length count
(first place a in max-heap order)
heapify(a, count)
end := count - 1
while end > 0 do
(swap the root(maximum value) of the heap with the
last element of the heap)
swap(a[end], a[0])
(decrement the size of the heap so that the previous
max value will stay in its proper place)
end := end - 1
(put the heap back in max-heap order)
siftDown(a, 0, end)
function heapify(a,count) is
(start is assigned the index in a of the last parent node)
start := (count - 2) / 2
while start ≥ 0 do
(sift down the node at index start to the proper place
such that all nodes below the start index are in heap
order)
siftDown(a, start, count-1)
start := start - 1
(after sifting down the root all nodes/elements are in heap order)
function siftDown(a, start, end) is
(end represents the limit of how far down the heap to sift)
root := start
while root * 2 + 1 ≤ end do (While the root has at least one child)
child := root * 2 + 1 (root*2+1 points to the left child)
(If the child has a sibling and the child's value is less than its sibling's...)
if child + 1 ≤ end and a[child] < a[child + 1] then
child := child + 1 (... then point to the right child instead)
if a[root] < a[child] then (out of max-heap order)
swap(a[root], a[child])
root := child (repeat to continue sifting down the child now)
else
return
Write a function to sort a collection of integers using heapsort.
| #zkl | zkl | fcn heapSort(a){ // in place
n := a.len();
foreach start in ([(n-2)/2 .. 0,-1])
{ siftDown(a, start, n-1) }
foreach end in ([n-1 .. 1,-1]){
a.swap(0, end);
siftDown(a, 0, end-1);
}
a
}
fcn siftDown(a, start, end){
while((child := start*2 + 1) <= end){
if(child < end and a[child]<a[child+1]) child+=1;
if(a[start] >= a[child]) return();
a.swap(start, child);
start = child;
}
} |
http://rosettacode.org/wiki/Sorting_algorithms/Merge_sort | Sorting algorithms/Merge sort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
The merge sort is a recursive sort of order n*log(n).
It is notable for having a worst case and average complexity of O(n*log(n)), and a best case complexity of O(n) (for pre-sorted input).
The basic idea is to split the collection into smaller groups by halving it until the groups only have one element or no elements (which are both entirely sorted groups).
Then merge the groups back together so that their elements are in order.
This is how the algorithm gets its divide and conquer description.
Task
Write a function to sort a collection of integers using the merge sort.
The merge sort algorithm comes in two parts:
a sort function and
a merge function
The functions in pseudocode look like this:
function mergesort(m)
var list left, right, result
if length(m) ≤ 1
return m
else
var middle = length(m) / 2
for each x in m up to middle - 1
add x to left
for each x in m at and after middle
add x to right
left = mergesort(left)
right = mergesort(right)
if last(left) ≤ first(right)
append right to left
return left
result = merge(left, right)
return result
function merge(left,right)
var list result
while length(left) > 0 and length(right) > 0
if first(left) ≤ first(right)
append first(left) to result
left = rest(left)
else
append first(right) to result
right = rest(right)
if length(left) > 0
append rest(left) to result
if length(right) > 0
append rest(right) to result
return result
See also
the Wikipedia entry: merge sort
Note: better performance can be expected if, rather than recursing until length(m) ≤ 1, an insertion sort is used for length(m) smaller than some threshold larger than 1. However, this complicates the example code, so it is not shown here.
| #Phix | Phix | with javascript_semantics
function merge(sequence left, sequence right)
sequence result = {}
while length(left)>0 and length(right)>0 do
if left[1]<=right[1] then
result = append(result, left[1])
left = left[2..$]
else
result = append(result, right[1])
right = right[2..$]
end if
end while
return result & left & right
end function
function mergesort(sequence m)
if length(m)<=1 then return m end if
integer middle = floor(length(m)/2)
sequence left = mergesort(m[1..middle]),
right = mergesort(m[middle+1..$])
if left[$]<=right[1] then
return left & right
elsif right[$]<=left[1] then
return right & left
end if
return merge(left, right)
end function
constant s = shuffle(tagset(10))
? s
? mergesort(deep_copy(s))
|
http://rosettacode.org/wiki/Sorting_algorithms/Quicksort | Sorting algorithms/Quicksort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Quicksort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
Task
Sort an array (or list) elements using the quicksort algorithm.
The elements must have a strict weak order and the index of the array can be of any discrete type.
For languages where this is not possible, sort an array of integers.
Quicksort, also known as partition-exchange sort, uses these steps.
Choose any element of the array to be the pivot.
Divide all other elements (except the pivot) into two partitions.
All elements less than the pivot must be in the first partition.
All elements greater than the pivot must be in the second partition.
Use recursion to sort both partitions.
Join the first sorted partition, the pivot, and the second sorted partition.
The best pivot creates partitions of equal length (or lengths differing by 1).
The worst pivot creates an empty partition (for example, if the pivot is the first or last element of a sorted array).
The run-time of Quicksort ranges from O(n log n) with the best pivots, to O(n2) with the worst pivots, where n is the number of elements in the array.
This is a simple quicksort algorithm, adapted from Wikipedia.
function quicksort(array)
less, equal, greater := three empty arrays
if length(array) > 1
pivot := select any element of array
for each x in array
if x < pivot then add x to less
if x = pivot then add x to equal
if x > pivot then add x to greater
quicksort(less)
quicksort(greater)
array := concatenate(less, equal, greater)
A better quicksort algorithm works in place, by swapping elements within the array, to avoid the memory allocation of more arrays.
function quicksort(array)
if length(array) > 1
pivot := select any element of array
left := first index of array
right := last index of array
while left ≤ right
while array[left] < pivot
left := left + 1
while array[right] > pivot
right := right - 1
if left ≤ right
swap array[left] with array[right]
left := left + 1
right := right - 1
quicksort(array from first index to right)
quicksort(array from left to last index)
Quicksort has a reputation as the fastest sort. Optimized variants of quicksort are common features of many languages and libraries. One often contrasts quicksort with merge sort, because both sorts have an average time of O(n log n).
"On average, mergesort does fewer comparisons than quicksort, so it may be better when complicated comparison routines are used. Mergesort also takes advantage of pre-existing order, so it would be favored for using sort() to merge several sorted arrays. On the other hand, quicksort is often faster for small arrays, and on arrays of a few distinct values, repeated many times." — http://perldoc.perl.org/sort.html
Quicksort is at one end of the spectrum of divide-and-conquer algorithms, with merge sort at the opposite end.
Quicksort is a conquer-then-divide algorithm, which does most of the work during the partitioning and the recursive calls. The subsequent reassembly of the sorted partitions involves trivial effort.
Merge sort is a divide-then-conquer algorithm. The partioning happens in a trivial way, by splitting the input array in half. Most of the work happens during the recursive calls and the merge phase.
With quicksort, every element in the first partition is less than or equal to every element in the second partition. Therefore, the merge phase of quicksort is so trivial that it needs no mention!
This task has not specified whether to allocate new arrays, or sort in place. This task also has not specified how to choose the pivot element. (Common ways to are to choose the first element, the middle element, or the median of three elements.) Thus there is a variety among the following implementations.
| #Objective-C | Objective-C | void quicksortInPlace(NSMutableArray *array, NSInteger first, NSInteger last, NSComparator comparator) {
if (first >= last) return;
id pivot = array[(first + last) / 2];
NSInteger left = first;
NSInteger right = last;
while (left <= right) {
while (comparator(array[left], pivot) == NSOrderedAscending)
left++;
while (comparator(array[right], pivot) == NSOrderedDescending)
right--;
if (left <= right)
[array exchangeObjectAtIndex:left++ withObjectAtIndex:right--];
}
quicksortInPlace(array, first, right, comparator);
quicksortInPlace(array, left, last, comparator);
}
NSArray* quicksort(NSArray *unsorted, NSComparator comparator) {
NSMutableArray *a = [NSMutableArray arrayWithArray:unsorted];
quicksortInPlace(a, 0, a.count - 1, comparator);
return a;
}
int main(int argc, const char * argv[]) {
@autoreleasepool {
NSArray *a = @[ @1, @3, @5, @7, @9, @8, @6, @4, @2 ];
NSLog(@"Unsorted: %@", a);
NSLog(@"Sorted: %@", quicksort(a, ^(id x, id y) { return [x compare:y]; }));
NSArray *b = @[ @"Emil", @"Peg", @"Helen", @"Juergen", @"David", @"Rick", @"Barb", @"Mike", @"Tom" ];
NSLog(@"Unsorted: %@", b);
NSLog(@"Sorted: %@", quicksort(b, ^(id x, id y) { return [x compare:y]; }));
}
return 0;
} |
http://rosettacode.org/wiki/Sorting_algorithms/Insertion_sort | Sorting algorithms/Insertion sort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Insertion sort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
An O(n2) sorting algorithm which moves elements one at a time into the correct position.
The algorithm consists of inserting one element at a time into the previously sorted part of the array, moving higher ranked elements up as necessary.
To start off, the first (or smallest, or any arbitrary) element of the unsorted array is considered to be the sorted part.
Although insertion sort is an O(n2) algorithm, its simplicity, low overhead, good locality of reference and efficiency make it a good choice in two cases:
small n,
as the final finishing-off algorithm for O(n logn) algorithms such as mergesort and quicksort.
The algorithm is as follows (from wikipedia):
function insertionSort(array A)
for i from 1 to length[A]-1 do
value := A[i]
j := i-1
while j >= 0 and A[j] > value do
A[j+1] := A[j]
j := j-1
done
A[j+1] = value
done
Writing the algorithm for integers will suffice.
| #PL.2FI | PL/I |
insert_sort: proc(array);
dcl array(*) fixed bin(31);
dcl (i,j,tmp,h,l) fixed bin(31);
l = lbound(array, 1);
h = hbound(array, 1);
do i = l + 1 to h;
tmp = array(i);
do j = i - 1 by -1 while(j > l - 1 & array(j) > tmp);
array(j + 1) = array(j);
end;
array(j + 1) = tmp;
end;
end insert_sort;
|
http://rosettacode.org/wiki/Sorting_algorithms/Merge_sort | Sorting algorithms/Merge sort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
The merge sort is a recursive sort of order n*log(n).
It is notable for having a worst case and average complexity of O(n*log(n)), and a best case complexity of O(n) (for pre-sorted input).
The basic idea is to split the collection into smaller groups by halving it until the groups only have one element or no elements (which are both entirely sorted groups).
Then merge the groups back together so that their elements are in order.
This is how the algorithm gets its divide and conquer description.
Task
Write a function to sort a collection of integers using the merge sort.
The merge sort algorithm comes in two parts:
a sort function and
a merge function
The functions in pseudocode look like this:
function mergesort(m)
var list left, right, result
if length(m) ≤ 1
return m
else
var middle = length(m) / 2
for each x in m up to middle - 1
add x to left
for each x in m at and after middle
add x to right
left = mergesort(left)
right = mergesort(right)
if last(left) ≤ first(right)
append right to left
return left
result = merge(left, right)
return result
function merge(left,right)
var list result
while length(left) > 0 and length(right) > 0
if first(left) ≤ first(right)
append first(left) to result
left = rest(left)
else
append first(right) to result
right = rest(right)
if length(left) > 0
append rest(left) to result
if length(right) > 0
append rest(right) to result
return result
See also
the Wikipedia entry: merge sort
Note: better performance can be expected if, rather than recursing until length(m) ≤ 1, an insertion sort is used for length(m) smaller than some threshold larger than 1. However, this complicates the example code, so it is not shown here.
| #PHP | PHP | function mergesort($arr){
if(count($arr) == 1 ) return $arr;
$mid = count($arr) / 2;
$left = array_slice($arr, 0, $mid);
$right = array_slice($arr, $mid);
$left = mergesort($left);
$right = mergesort($right);
return merge($left, $right);
}
function merge($left, $right){
$res = array();
while (count($left) > 0 && count($right) > 0){
if($left[0] > $right[0]){
$res[] = $right[0];
$right = array_slice($right , 1);
}else{
$res[] = $left[0];
$left = array_slice($left, 1);
}
}
while (count($left) > 0){
$res[] = $left[0];
$left = array_slice($left, 1);
}
while (count($right) > 0){
$res[] = $right[0];
$right = array_slice($right, 1);
}
return $res;
}
$arr = array( 1, 5, 2, 7, 3, 9, 4, 6, 8);
$arr = mergesort($arr);
echo implode(',',$arr); |
http://rosettacode.org/wiki/Sorting_algorithms/Quicksort | Sorting algorithms/Quicksort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Quicksort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
Task
Sort an array (or list) elements using the quicksort algorithm.
The elements must have a strict weak order and the index of the array can be of any discrete type.
For languages where this is not possible, sort an array of integers.
Quicksort, also known as partition-exchange sort, uses these steps.
Choose any element of the array to be the pivot.
Divide all other elements (except the pivot) into two partitions.
All elements less than the pivot must be in the first partition.
All elements greater than the pivot must be in the second partition.
Use recursion to sort both partitions.
Join the first sorted partition, the pivot, and the second sorted partition.
The best pivot creates partitions of equal length (or lengths differing by 1).
The worst pivot creates an empty partition (for example, if the pivot is the first or last element of a sorted array).
The run-time of Quicksort ranges from O(n log n) with the best pivots, to O(n2) with the worst pivots, where n is the number of elements in the array.
This is a simple quicksort algorithm, adapted from Wikipedia.
function quicksort(array)
less, equal, greater := three empty arrays
if length(array) > 1
pivot := select any element of array
for each x in array
if x < pivot then add x to less
if x = pivot then add x to equal
if x > pivot then add x to greater
quicksort(less)
quicksort(greater)
array := concatenate(less, equal, greater)
A better quicksort algorithm works in place, by swapping elements within the array, to avoid the memory allocation of more arrays.
function quicksort(array)
if length(array) > 1
pivot := select any element of array
left := first index of array
right := last index of array
while left ≤ right
while array[left] < pivot
left := left + 1
while array[right] > pivot
right := right - 1
if left ≤ right
swap array[left] with array[right]
left := left + 1
right := right - 1
quicksort(array from first index to right)
quicksort(array from left to last index)
Quicksort has a reputation as the fastest sort. Optimized variants of quicksort are common features of many languages and libraries. One often contrasts quicksort with merge sort, because both sorts have an average time of O(n log n).
"On average, mergesort does fewer comparisons than quicksort, so it may be better when complicated comparison routines are used. Mergesort also takes advantage of pre-existing order, so it would be favored for using sort() to merge several sorted arrays. On the other hand, quicksort is often faster for small arrays, and on arrays of a few distinct values, repeated many times." — http://perldoc.perl.org/sort.html
Quicksort is at one end of the spectrum of divide-and-conquer algorithms, with merge sort at the opposite end.
Quicksort is a conquer-then-divide algorithm, which does most of the work during the partitioning and the recursive calls. The subsequent reassembly of the sorted partitions involves trivial effort.
Merge sort is a divide-then-conquer algorithm. The partioning happens in a trivial way, by splitting the input array in half. Most of the work happens during the recursive calls and the merge phase.
With quicksort, every element in the first partition is less than or equal to every element in the second partition. Therefore, the merge phase of quicksort is so trivial that it needs no mention!
This task has not specified whether to allocate new arrays, or sort in place. This task also has not specified how to choose the pivot element. (Common ways to are to choose the first element, the middle element, or the median of three elements.) Thus there is a variety among the following implementations.
| #OCaml | OCaml | let rec quicksort gt = function
| [] -> []
| x::xs ->
let ys, zs = List.partition (gt x) xs in
(quicksort gt ys) @ (x :: (quicksort gt zs))
let _ =
quicksort (>) [4; 65; 2; -31; 0; 99; 83; 782; 1] |
http://rosettacode.org/wiki/Sorting_algorithms/Insertion_sort | Sorting algorithms/Insertion sort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Insertion sort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
An O(n2) sorting algorithm which moves elements one at a time into the correct position.
The algorithm consists of inserting one element at a time into the previously sorted part of the array, moving higher ranked elements up as necessary.
To start off, the first (or smallest, or any arbitrary) element of the unsorted array is considered to be the sorted part.
Although insertion sort is an O(n2) algorithm, its simplicity, low overhead, good locality of reference and efficiency make it a good choice in two cases:
small n,
as the final finishing-off algorithm for O(n logn) algorithms such as mergesort and quicksort.
The algorithm is as follows (from wikipedia):
function insertionSort(array A)
for i from 1 to length[A]-1 do
value := A[i]
j := i-1
while j >= 0 and A[j] > value do
A[j+1] := A[j]
j := j-1
done
A[j+1] = value
done
Writing the algorithm for integers will suffice.
| #PL.2FM | PL/M | 100H:
/* INSERTION SORT ON 16-BIT INTEGERS */
INSERTION$SORT: PROCEDURE (AP, LEN);
DECLARE (AP, LEN, I, J, V, A BASED AP) ADDRESS;
DO I = 1 TO LEN-1;
V = A(I);
J = I;
DO WHILE J > 0 AND A(J-1) > V;
A(J) = A(J-1);
J = J-1;
END;
A(J) = V;
END;
END INSERTION$SORT;
/* CP/M CALLS AND FUNCTION TO PRINT INTEGERS */
BDOS: PROCEDURE (FN, ARG);
DECLARE FN BYTE, ARG ADDRESS;
GO TO 5;
END BDOS;
PRINT$NUMBER: PROCEDURE (N);
DECLARE S (7) BYTE INITIAL ('..... $');
DECLARE (N, P) ADDRESS, C BASED P BYTE;
P = .S(5);
DIGIT:
P = P-1;
C = N MOD 10 + '0';
N = N / 10;
IF N > 0 THEN GO TO DIGIT;
CALL BDOS(9, P);
END PRINT$NUMBER;
/* SORT AN ARRAY */
DECLARE NUMBERS (11) ADDRESS INITIAL (4, 65, 2, 31, 0, 99, 2, 8, 3, 782, 1);
CALL INSERTION$SORT(.NUMBERS, LENGTH(NUMBERS));
/* PRINT THE SORTED ARRAY */
DECLARE N BYTE;
DO N = 0 TO LAST(NUMBERS);
CALL PRINT$NUMBER(NUMBERS(N));
END;
CALL BDOS(0,0);
EOF |
http://rosettacode.org/wiki/Sorting_algorithms/Merge_sort | Sorting algorithms/Merge sort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
The merge sort is a recursive sort of order n*log(n).
It is notable for having a worst case and average complexity of O(n*log(n)), and a best case complexity of O(n) (for pre-sorted input).
The basic idea is to split the collection into smaller groups by halving it until the groups only have one element or no elements (which are both entirely sorted groups).
Then merge the groups back together so that their elements are in order.
This is how the algorithm gets its divide and conquer description.
Task
Write a function to sort a collection of integers using the merge sort.
The merge sort algorithm comes in two parts:
a sort function and
a merge function
The functions in pseudocode look like this:
function mergesort(m)
var list left, right, result
if length(m) ≤ 1
return m
else
var middle = length(m) / 2
for each x in m up to middle - 1
add x to left
for each x in m at and after middle
add x to right
left = mergesort(left)
right = mergesort(right)
if last(left) ≤ first(right)
append right to left
return left
result = merge(left, right)
return result
function merge(left,right)
var list result
while length(left) > 0 and length(right) > 0
if first(left) ≤ first(right)
append first(left) to result
left = rest(left)
else
append first(right) to result
right = rest(right)
if length(left) > 0
append rest(left) to result
if length(right) > 0
append rest(right) to result
return result
See also
the Wikipedia entry: merge sort
Note: better performance can be expected if, rather than recursing until length(m) ≤ 1, an insertion sort is used for length(m) smaller than some threshold larger than 1. However, this complicates the example code, so it is not shown here.
| #Picat | Picat | % True if S is a sorted copy of L, using merge sort
msort([],[]).
msort([X],[X]).
msort(U,S) :-
split(U, L, R),
msort(L, SL),
msort(R, SR),
merge(SL, SR, S).
% split(LIST,L,R)
% Alternate elements of LIST in L and R
split([],[],[]).
split([X],[X],[]).
split([L,R|T],[L|LT],[R|RT]) :-
split( T, LT, RT ).
% merge( LS, RS, M )
% Assuming LS and RS are sorted, True if M is the sorted merge of the two
merge([],RS,RS).
merge(LS,[],LS).
merge([L|LS],[R|RS],[L|T]) :-
L @=< R,
merge(LS,[R|RS],T).
merge([L|LS],[R|RS],[R|T]) :-
L @> R,
merge([L|LS],RS,T). |
http://rosettacode.org/wiki/Sorting_algorithms/Quicksort | Sorting algorithms/Quicksort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Quicksort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
Task
Sort an array (or list) elements using the quicksort algorithm.
The elements must have a strict weak order and the index of the array can be of any discrete type.
For languages where this is not possible, sort an array of integers.
Quicksort, also known as partition-exchange sort, uses these steps.
Choose any element of the array to be the pivot.
Divide all other elements (except the pivot) into two partitions.
All elements less than the pivot must be in the first partition.
All elements greater than the pivot must be in the second partition.
Use recursion to sort both partitions.
Join the first sorted partition, the pivot, and the second sorted partition.
The best pivot creates partitions of equal length (or lengths differing by 1).
The worst pivot creates an empty partition (for example, if the pivot is the first or last element of a sorted array).
The run-time of Quicksort ranges from O(n log n) with the best pivots, to O(n2) with the worst pivots, where n is the number of elements in the array.
This is a simple quicksort algorithm, adapted from Wikipedia.
function quicksort(array)
less, equal, greater := three empty arrays
if length(array) > 1
pivot := select any element of array
for each x in array
if x < pivot then add x to less
if x = pivot then add x to equal
if x > pivot then add x to greater
quicksort(less)
quicksort(greater)
array := concatenate(less, equal, greater)
A better quicksort algorithm works in place, by swapping elements within the array, to avoid the memory allocation of more arrays.
function quicksort(array)
if length(array) > 1
pivot := select any element of array
left := first index of array
right := last index of array
while left ≤ right
while array[left] < pivot
left := left + 1
while array[right] > pivot
right := right - 1
if left ≤ right
swap array[left] with array[right]
left := left + 1
right := right - 1
quicksort(array from first index to right)
quicksort(array from left to last index)
Quicksort has a reputation as the fastest sort. Optimized variants of quicksort are common features of many languages and libraries. One often contrasts quicksort with merge sort, because both sorts have an average time of O(n log n).
"On average, mergesort does fewer comparisons than quicksort, so it may be better when complicated comparison routines are used. Mergesort also takes advantage of pre-existing order, so it would be favored for using sort() to merge several sorted arrays. On the other hand, quicksort is often faster for small arrays, and on arrays of a few distinct values, repeated many times." — http://perldoc.perl.org/sort.html
Quicksort is at one end of the spectrum of divide-and-conquer algorithms, with merge sort at the opposite end.
Quicksort is a conquer-then-divide algorithm, which does most of the work during the partitioning and the recursive calls. The subsequent reassembly of the sorted partitions involves trivial effort.
Merge sort is a divide-then-conquer algorithm. The partioning happens in a trivial way, by splitting the input array in half. Most of the work happens during the recursive calls and the merge phase.
With quicksort, every element in the first partition is less than or equal to every element in the second partition. Therefore, the merge phase of quicksort is so trivial that it needs no mention!
This task has not specified whether to allocate new arrays, or sort in place. This task also has not specified how to choose the pivot element. (Common ways to are to choose the first element, the middle element, or the median of three elements.) Thus there is a variety among the following implementations.
| #Octave | Octave | function f=quicksort(v) % v must be a column vector
f = v; n=length(v);
if(n > 1)
vl = min(f); vh = max(f); % min, max
p = (vl+vh)*0.5; % pivot
ia = find(f < p); ib = find(f == p); ic=find(f > p);
f = [quicksort(f(ia)); f(ib); quicksort(f(ic))];
end
endfunction
N=30; v=rand(N,1); tic,u=quicksort(v); toc
u |
http://rosettacode.org/wiki/Sorting_algorithms/Cocktail_sort_with_shifting_bounds | Sorting algorithms/Cocktail sort with shifting bounds |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Cocktail sort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
The cocktail sort is an improvement on the Bubble Sort.
A cocktail sort is also known as:
cocktail shaker sort
happy hour sort
bidirectional bubble sort
a bubble sort variation
a selection sort variation
ripple sort
shuffle sort
shuttle sort
The improvement is basically that values "bubble" (migrate) both directions through the
array, because on each iteration the cocktail sort bubble sorts once
forwards and once backwards.
After ii passes, the first ii and the
last ii elements in the array are in their correct
positions, and don't have to be checked (again).
By shortening the part of the array that is sorted each time, the number of
comparisons can be halved.
Pseudocode for the 2nd algorithm (from
Wikipedia) with an added comment and changed indentations:
function A = cocktailShakerSort(A)
% `beginIdx` and `endIdx` marks the first and last index to check.
beginIdx = 1;
endIdx = length(A) - 1;
while beginIdx <= endIdx
newBeginIdx = endIdx;
newEndIdx = beginIdx;
for ii = beginIdx:endIdx
if A(ii) > A(ii + 1)
[A(ii+1), A(ii)] = deal(A(ii), A(ii+1));
newEndIdx = ii;
end
end
% decreases `endIdx` because the elements after `newEndIdx` are in correct order
endIdx = newEndIdx - 1;
% (FOR (below) decrements the II index by -1.
for ii = endIdx:-1:beginIdx
if A(ii) > A(ii + 1)
[A(ii+1), A(ii)] = deal(A(ii), A(ii+1));
newBeginIdx = ii;
end
end
% increases `beginIdx` because the elements before `newBeginIdx` are in correct order.
beginIdx = newBeginIdx + 1;
end
end
% indicates a comment, and deal indicates a swap.
Task
Implement a cocktail sort and optionally show the sorted output here on this page.
See the discussion page for some timing comparisons.
Related task
cocktail sort
| #11l | 11l | F cocktailshiftingbounds(&A)
V beginIdx = 0
V endIdx = A.len - 1
L beginIdx <= endIdx
V newBeginIdx = endIdx
V newEndIdx = beginIdx
L(ii) beginIdx .< endIdx
I A[ii] > A[ii + 1]
swap(&A[ii + 1], &A[ii])
newEndIdx = ii
endIdx = newEndIdx
L(ii) (endIdx .< beginIdx - 1).step(-1)
I A[ii] > A[ii + 1]
swap(&A[ii + 1], &A[ii])
newBeginIdx = ii
beginIdx = newBeginIdx + 1
V test1 = [7, 6, 5, 9, 8, 4, 3, 1, 2, 0]
cocktailshiftingbounds(&test1)
print(test1) |
http://rosettacode.org/wiki/Sorting_algorithms/Insertion_sort | Sorting algorithms/Insertion sort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Insertion sort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
An O(n2) sorting algorithm which moves elements one at a time into the correct position.
The algorithm consists of inserting one element at a time into the previously sorted part of the array, moving higher ranked elements up as necessary.
To start off, the first (or smallest, or any arbitrary) element of the unsorted array is considered to be the sorted part.
Although insertion sort is an O(n2) algorithm, its simplicity, low overhead, good locality of reference and efficiency make it a good choice in two cases:
small n,
as the final finishing-off algorithm for O(n logn) algorithms such as mergesort and quicksort.
The algorithm is as follows (from wikipedia):
function insertionSort(array A)
for i from 1 to length[A]-1 do
value := A[i]
j := i-1
while j >= 0 and A[j] > value do
A[j+1] := A[j]
j := j-1
done
A[j+1] = value
done
Writing the algorithm for integers will suffice.
| #PowerShell | PowerShell | function insertionSort($arr){
for($i=0;$i -lt $arr.length;$i++){
$val = $arr[$i]
$j = $i-1
while($j -ge 0 -and $arr[$j] -gt $val){
$arr[$j+1] = $arr[$j]
$j--
}
$arr[$j+1] = $val
}
}
$arr = @(4,2,1,6,9,3,8,7)
insertionSort($arr)
$arr -join "," |
http://rosettacode.org/wiki/Sorting_algorithms/Merge_sort | Sorting algorithms/Merge sort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
The merge sort is a recursive sort of order n*log(n).
It is notable for having a worst case and average complexity of O(n*log(n)), and a best case complexity of O(n) (for pre-sorted input).
The basic idea is to split the collection into smaller groups by halving it until the groups only have one element or no elements (which are both entirely sorted groups).
Then merge the groups back together so that their elements are in order.
This is how the algorithm gets its divide and conquer description.
Task
Write a function to sort a collection of integers using the merge sort.
The merge sort algorithm comes in two parts:
a sort function and
a merge function
The functions in pseudocode look like this:
function mergesort(m)
var list left, right, result
if length(m) ≤ 1
return m
else
var middle = length(m) / 2
for each x in m up to middle - 1
add x to left
for each x in m at and after middle
add x to right
left = mergesort(left)
right = mergesort(right)
if last(left) ≤ first(right)
append right to left
return left
result = merge(left, right)
return result
function merge(left,right)
var list result
while length(left) > 0 and length(right) > 0
if first(left) ≤ first(right)
append first(left) to result
left = rest(left)
else
append first(right) to result
right = rest(right)
if length(left) > 0
append rest(left) to result
if length(right) > 0
append rest(right) to result
return result
See also
the Wikipedia entry: merge sort
Note: better performance can be expected if, rather than recursing until length(m) ≤ 1, an insertion sort is used for length(m) smaller than some threshold larger than 1. However, this complicates the example code, so it is not shown here.
| #PicoLisp | PicoLisp | (de alt (List)
(if List (cons (car List) (alt (cddr List))) ()) )
(de merge (L1 L2)
(cond
((not L2) L1)
((< (car L1) (car L2))
(cons (car L1) (merge L2 (cdr L1))))
(T (cons (car L2) (merge L1 (cdr L2)))) ) )
(de mergesort (List)
(if (cdr List)
(merge (mergesort (alt List)) (mergesort (alt (cdr List))))
List) )
(mergesort (8 1 5 3 9 0 2 7 6 4)) |
http://rosettacode.org/wiki/Sorting_algorithms/Quicksort | Sorting algorithms/Quicksort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Quicksort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
Task
Sort an array (or list) elements using the quicksort algorithm.
The elements must have a strict weak order and the index of the array can be of any discrete type.
For languages where this is not possible, sort an array of integers.
Quicksort, also known as partition-exchange sort, uses these steps.
Choose any element of the array to be the pivot.
Divide all other elements (except the pivot) into two partitions.
All elements less than the pivot must be in the first partition.
All elements greater than the pivot must be in the second partition.
Use recursion to sort both partitions.
Join the first sorted partition, the pivot, and the second sorted partition.
The best pivot creates partitions of equal length (or lengths differing by 1).
The worst pivot creates an empty partition (for example, if the pivot is the first or last element of a sorted array).
The run-time of Quicksort ranges from O(n log n) with the best pivots, to O(n2) with the worst pivots, where n is the number of elements in the array.
This is a simple quicksort algorithm, adapted from Wikipedia.
function quicksort(array)
less, equal, greater := three empty arrays
if length(array) > 1
pivot := select any element of array
for each x in array
if x < pivot then add x to less
if x = pivot then add x to equal
if x > pivot then add x to greater
quicksort(less)
quicksort(greater)
array := concatenate(less, equal, greater)
A better quicksort algorithm works in place, by swapping elements within the array, to avoid the memory allocation of more arrays.
function quicksort(array)
if length(array) > 1
pivot := select any element of array
left := first index of array
right := last index of array
while left ≤ right
while array[left] < pivot
left := left + 1
while array[right] > pivot
right := right - 1
if left ≤ right
swap array[left] with array[right]
left := left + 1
right := right - 1
quicksort(array from first index to right)
quicksort(array from left to last index)
Quicksort has a reputation as the fastest sort. Optimized variants of quicksort are common features of many languages and libraries. One often contrasts quicksort with merge sort, because both sorts have an average time of O(n log n).
"On average, mergesort does fewer comparisons than quicksort, so it may be better when complicated comparison routines are used. Mergesort also takes advantage of pre-existing order, so it would be favored for using sort() to merge several sorted arrays. On the other hand, quicksort is often faster for small arrays, and on arrays of a few distinct values, repeated many times." — http://perldoc.perl.org/sort.html
Quicksort is at one end of the spectrum of divide-and-conquer algorithms, with merge sort at the opposite end.
Quicksort is a conquer-then-divide algorithm, which does most of the work during the partitioning and the recursive calls. The subsequent reassembly of the sorted partitions involves trivial effort.
Merge sort is a divide-then-conquer algorithm. The partioning happens in a trivial way, by splitting the input array in half. Most of the work happens during the recursive calls and the merge phase.
With quicksort, every element in the first partition is less than or equal to every element in the second partition. Therefore, the merge phase of quicksort is so trivial that it needs no mention!
This task has not specified whether to allocate new arrays, or sort in place. This task also has not specified how to choose the pivot element. (Common ways to are to choose the first element, the middle element, or the median of three elements.) Thus there is a variety among the following implementations.
| #Oforth | Oforth | [ 5, 8, 2, 3, 4, 1 ] sort |
http://rosettacode.org/wiki/Sorting_algorithms/Cocktail_sort_with_shifting_bounds | Sorting algorithms/Cocktail sort with shifting bounds |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Cocktail sort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
The cocktail sort is an improvement on the Bubble Sort.
A cocktail sort is also known as:
cocktail shaker sort
happy hour sort
bidirectional bubble sort
a bubble sort variation
a selection sort variation
ripple sort
shuffle sort
shuttle sort
The improvement is basically that values "bubble" (migrate) both directions through the
array, because on each iteration the cocktail sort bubble sorts once
forwards and once backwards.
After ii passes, the first ii and the
last ii elements in the array are in their correct
positions, and don't have to be checked (again).
By shortening the part of the array that is sorted each time, the number of
comparisons can be halved.
Pseudocode for the 2nd algorithm (from
Wikipedia) with an added comment and changed indentations:
function A = cocktailShakerSort(A)
% `beginIdx` and `endIdx` marks the first and last index to check.
beginIdx = 1;
endIdx = length(A) - 1;
while beginIdx <= endIdx
newBeginIdx = endIdx;
newEndIdx = beginIdx;
for ii = beginIdx:endIdx
if A(ii) > A(ii + 1)
[A(ii+1), A(ii)] = deal(A(ii), A(ii+1));
newEndIdx = ii;
end
end
% decreases `endIdx` because the elements after `newEndIdx` are in correct order
endIdx = newEndIdx - 1;
% (FOR (below) decrements the II index by -1.
for ii = endIdx:-1:beginIdx
if A(ii) > A(ii + 1)
[A(ii+1), A(ii)] = deal(A(ii), A(ii+1));
newBeginIdx = ii;
end
end
% increases `beginIdx` because the elements before `newBeginIdx` are in correct order.
beginIdx = newBeginIdx + 1;
end
end
% indicates a comment, and deal indicates a swap.
Task
Implement a cocktail sort and optionally show the sorted output here on this page.
See the discussion page for some timing comparisons.
Related task
cocktail sort
| #360_Assembly | 360 Assembly | * Cocktail sort with shifting bounds 10/05/2020
COCKSHIS CSECT
USING COCKSHIS,R13 base register
B 72(R15) skip savearea
DC 17F'0' savearea
SAVE (14,12) save previous context
ST R13,4(R15) link backward
ST R15,8(R13) link forward
LR R13,R15 set addressability
* Sort
LA R0,1 1
ST R0,BEGIDX begIdx=LBound(A)
L R0,N n
BCTR R0,0 n-1
ST R0,ENDIDX endIdx=UBound(A)-1
L R1,BEGIDX begIdx
DO WHILE=(C,R1,LE,ENDIDX) while begIdx<=endIdx
MVC NWBEGIDX,ENDIDX nwbegIdx=endIdx
MVC NWENDIDX,BEGIDX nwendIdx=begIdx
L RI,BEGIDX i=begIdx
DO WHILE=(C,RI,LE,ENDIDX) do i=1 to endIdx
LR R1,RI i
SLA R1,2 .
LA R2,A-4(R1) @a(i)
LA R3,A(R1) @a(i+1)
L R4,0(R2) r4=a(i)
L R5,0(R3) r5=a(i+1)
IF CR,R4,GT,R5 THEN if a(i)>a(i+1) then
ST R5,0(R2) a(i)=r5
ST R4,0(R3) a(i+1)=r4
ST RI,NWENDIDX nwendIdx=i
ENDIF , end if
LA RI,1(RI) i=i+1
ENDDO , end do
L R1,NWENDIDX nwendIdx
BCTR R1,0 -1
ST R1,ENDIDX endIdx=nwendIdx-1
LR RI,R1 endIdx
DO WHILE=(C,RI,GE,BEGIDX) do i=endIdx to begIdx by -1
LR R1,RI i
SLA R1,2 .
LA R2,A-4(R1) @a(i)
LA R3,A(R1) @a(i+1)
L R4,0(R2) r4=a(i)
L R5,0(R3) r5=a(i+1)
IF CR,R4,GT,R5 THEN if a(i)>a(i+1) then
ST R5,0(R2) a(i)=r5
ST R4,0(R3) a(i+1)=r4
ST RI,NWBEGIDX nwbegIdx=i
ENDIF , end if
BCTR RI,0 i=i-1
ENDDO , end do
L R1,NWBEGIDX nwbegIdx
LA R1,1(R1) +1
ST R1,BEGIDX begIdx=nwbegIdx+1
ENDDO , endwhile
* Display sorted list
LA R3,PG pgi=0
LA RI,1 i=1
DO WHILE=(C,RI,LE,N) do i=1 to n
LR R1,RI i
SLA R1,2 .
L R2,A-4(R1) a(i)
XDECO R2,XDEC edit a(i)
MVC 0(4,R3),XDEC+8 output a(i)
LA R3,4(R3) pgi=pgi+4
LA RI,1(RI) i=i+1
ENDDO , end do
XPRNT PG,L'PG print buffer
L R13,4(0,R13) restore previous savearea pointer
RETURN (14,12),RC=0 restore registers from calling save
A DC F'4',F'65',F'2',F'-31',F'0',F'99',F'2',F'83'
DC F'782',F'1',F'45',F'82',F'69',F'82',F'104',F'58'
DC F'88',F'112',F'89',F'74'
N DC A((N-A)/L'A) number of items of a
PG DC CL80' ' buffer
XDEC DS CL12 temp for xdeco
BEGIDX DS F begIdx
ENDIDX DS F endIdx
NWBEGIDX DS F nwbegIdx
NWENDIDX DS F nwendIdx
REGEQU
RI EQU 6 i
END COCKSHIS |
http://rosettacode.org/wiki/Sorting_algorithms/Cocktail_sort_with_shifting_bounds | Sorting algorithms/Cocktail sort with shifting bounds |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Cocktail sort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
The cocktail sort is an improvement on the Bubble Sort.
A cocktail sort is also known as:
cocktail shaker sort
happy hour sort
bidirectional bubble sort
a bubble sort variation
a selection sort variation
ripple sort
shuffle sort
shuttle sort
The improvement is basically that values "bubble" (migrate) both directions through the
array, because on each iteration the cocktail sort bubble sorts once
forwards and once backwards.
After ii passes, the first ii and the
last ii elements in the array are in their correct
positions, and don't have to be checked (again).
By shortening the part of the array that is sorted each time, the number of
comparisons can be halved.
Pseudocode for the 2nd algorithm (from
Wikipedia) with an added comment and changed indentations:
function A = cocktailShakerSort(A)
% `beginIdx` and `endIdx` marks the first and last index to check.
beginIdx = 1;
endIdx = length(A) - 1;
while beginIdx <= endIdx
newBeginIdx = endIdx;
newEndIdx = beginIdx;
for ii = beginIdx:endIdx
if A(ii) > A(ii + 1)
[A(ii+1), A(ii)] = deal(A(ii), A(ii+1));
newEndIdx = ii;
end
end
% decreases `endIdx` because the elements after `newEndIdx` are in correct order
endIdx = newEndIdx - 1;
% (FOR (below) decrements the II index by -1.
for ii = endIdx:-1:beginIdx
if A(ii) > A(ii + 1)
[A(ii+1), A(ii)] = deal(A(ii), A(ii+1));
newBeginIdx = ii;
end
end
% increases `beginIdx` because the elements before `newBeginIdx` are in correct order.
beginIdx = newBeginIdx + 1;
end
end
% indicates a comment, and deal indicates a swap.
Task
Implement a cocktail sort and optionally show the sorted output here on this page.
See the discussion page for some timing comparisons.
Related task
cocktail sort
| #AArch64_Assembly | AArch64 Assembly |
/* ARM assembly AARCH64 Raspberry PI 3B */
/* program cocktailSortbound64.s */
/*******************************************/
/* Constantes file */
/*******************************************/
/* for this file see task include a file in language AArch64 assembly */
.include "../includeConstantesARM64.inc"
/*********************************/
/* Initialized data */
/*********************************/
.data
szMessSortOk: .asciz "Table sorted.\n"
szMessSortNok: .asciz "Table not sorted !!!!!.\n"
sMessResult: .asciz "Value : @ \n"
szCarriageReturn: .asciz "\n"
.align 4
//TableNumber: .quad 1,3,6,2,5,9,10,8,4,7
TableNumber: .quad 10,9,8,7,6,-5,4,3,2,1
.equ NBELEMENTS, (. - TableNumber) / 8
/*********************************/
/* UnInitialized data */
/*********************************/
.bss
sZoneConv: .skip 24
/*********************************/
/* code section */
/*********************************/
.text
.global main
main: // entry of program
ldr x0,qAdrTableNumber // address number table
mov x1,0
mov x2,NBELEMENTS // number of élements
bl cocktailSortBound
ldr x0,qAdrTableNumber // address number table
bl displayTable
ldr x0,qAdrTableNumber // address number table
mov x1,NBELEMENTS // number of élements
bl isSorted // control sort
cmp x0,1 // sorted ?
beq 1f
ldr x0,qAdrszMessSortNok // no !! error sort
bl affichageMess
b 100f
1: // yes
ldr x0,qAdrszMessSortOk
bl affichageMess
100: // standard end of the program
mov x0,0 // return code
mov x8,EXIT // request to exit program
svc 0 // perform the system call
qAdrsZoneConv: .quad sZoneConv
qAdrszCarriageReturn: .quad szCarriageReturn
qAdrsMessResult: .quad sMessResult
qAdrTableNumber: .quad TableNumber
qAdrszMessSortOk: .quad szMessSortOk
qAdrszMessSortNok: .quad szMessSortNok
/******************************************************************/
/* control sorted table */
/******************************************************************/
/* x0 contains the address of table */
/* x1 contains the number of elements > 0 */
/* x0 return 0 if not sorted 1 if sorted */
isSorted:
stp x2,lr,[sp,-16]! // save registers
stp x3,x4,[sp,-16]! // save registers
mov x2,0
ldr x4,[x0,x2,lsl 3]
1:
add x2,x2,1
cmp x2,x1
bge 99f
ldr x3,[x0,x2, lsl 3]
cmp x3,x4
blt 98f
mov x4,x3
b 1b
98:
mov x0,0 // not sorted
b 100f
99:
mov x0,1 // sorted
100:
ldp x3,x4,[sp],16 // restaur 2 registers
ldp x2,lr,[sp],16 // restaur 2 registers
ret // return to address lr x30
/******************************************************************/
/* cocktail sort Bound */
/******************************************************************/
/* x0 contains the address of table */
/* x1 contains the first element */
/* x2 contains the number of element */
cocktailSortBound:
stp x1,lr,[sp,-16]! // save registers
stp x2,x3,[sp,-16]! // save registers
stp x4,x5,[sp,-16]! // save registers
stp x6,x7,[sp,-16]! // save registers
stp x8,x9,[sp,-16]! // save registers
sub x2,x2,2 // compute endidx = n - 2
// and r1 = beginidx
1: // start loop 1
cmp x1,x2
bgt 100f
mov x8,x1 // newbeginidx
mov x7,x2 // newendidx
mov x3,x1 // start index
2: // start loop 2
add x4,x3,1
ldr x5,[x0,x3,lsl 3] // load value A[j]
ldr x6,[x0,x4,lsl 3] // load value A[j+1]
cmp x6,x5 // compare value
bge 3f
str x6,[x0,x3,lsl 3] // if smaller inversion
str x5,[x0,x4,lsl 3]
mov x7,x3 // and mov indice to newendidx
3:
add x3,x3,1 // increment index j
cmp x3,x2 // end ?
ble 2b // no -> loop 2
sub x2,x7,1 // endidx = newendidx - 1
bl displayTable
mov x3,x2 // indice
4:
add x4,x3,1
ldr x5,[x0,x3,lsl 3] // load value A[j]
ldr x6,[x0,x4,lsl 3] // load value A[j+1]
cmp x6,x5 // compare value
bge 5f
str x6,[x0,x3,lsl 3] // if smaller inversion
str x5,[x0,x4,lsl 3]
mov x8,x3 // newbeginidx = indice
5:
sub x3,x3,1 // decrement index j
cmp x3,x1 // end ?
bge 4b // no -> loop 2
add x1,x8,1 // beginidx = newbeginidx
b 1b // loop 1
100:
ldp x8,x9,[sp],16 // restaur 2 registers
ldp x6,x7,[sp],16 // restaur 2 registers
ldp x4,x5,[sp],16 // restaur 2 registers
ldp x2,x3,[sp],16 // restaur 2 registers
ldp x1,lr,[sp],16 // restaur 2 registers
ret // return to address lr x30
/******************************************************************/
/* Display table elements */
/******************************************************************/
/* x0 contains the address of table */
displayTable:
stp x1,lr,[sp,-16]! // save registers
stp x2,x3,[sp,-16]! // save registers
mov x2,x0 // table address
mov x3,0
1: // loop display table
ldr x0,[x2,x3,lsl 3]
ldr x1,qAdrsZoneConv
bl conversion10S // décimal conversion
ldr x0,qAdrsMessResult
ldr x1,qAdrsZoneConv
bl strInsertAtCharInc // insert result at @ character
bl affichageMess // display message
add x3,x3,1
cmp x3,NBELEMENTS - 1
ble 1b
ldr x0,qAdrszCarriageReturn
bl affichageMess
mov x0,x2 // table address
100:
ldp x2,x3,[sp],16 // restaur 2 registers
ldp x1,lr,[sp],16 // restaur 2 registers
ret // return to address lr x30
/********************************************************/
/* File Include fonctions */
/********************************************************/
/* for this file see task include a file in language AArch64 assembly */
.include "../includeARM64.inc"
|
http://rosettacode.org/wiki/Sorting_algorithms/Insertion_sort | Sorting algorithms/Insertion sort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Insertion sort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
An O(n2) sorting algorithm which moves elements one at a time into the correct position.
The algorithm consists of inserting one element at a time into the previously sorted part of the array, moving higher ranked elements up as necessary.
To start off, the first (or smallest, or any arbitrary) element of the unsorted array is considered to be the sorted part.
Although insertion sort is an O(n2) algorithm, its simplicity, low overhead, good locality of reference and efficiency make it a good choice in two cases:
small n,
as the final finishing-off algorithm for O(n logn) algorithms such as mergesort and quicksort.
The algorithm is as follows (from wikipedia):
function insertionSort(array A)
for i from 1 to length[A]-1 do
value := A[i]
j := i-1
while j >= 0 and A[j] > value do
A[j+1] := A[j]
j := j-1
done
A[j+1] = value
done
Writing the algorithm for integers will suffice.
| #Prolog | Prolog | insert_sort(L1,L2) :-
insert_sort_intern(L1,[],L2).
insert_sort_intern([],L,L).
insert_sort_intern([H|T],L1,L) :-
insert(L1,H,L2),
insert_sort_intern(T,L2,L).
insert([],X,[X]).
insert([H|T],X,[X,H|T]) :-
X =< H,
!.
insert([H|T],X,[H|T2]) :-
insert(T,X,T2). |
http://rosettacode.org/wiki/Sorting_algorithms/Merge_sort | Sorting algorithms/Merge sort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
The merge sort is a recursive sort of order n*log(n).
It is notable for having a worst case and average complexity of O(n*log(n)), and a best case complexity of O(n) (for pre-sorted input).
The basic idea is to split the collection into smaller groups by halving it until the groups only have one element or no elements (which are both entirely sorted groups).
Then merge the groups back together so that their elements are in order.
This is how the algorithm gets its divide and conquer description.
Task
Write a function to sort a collection of integers using the merge sort.
The merge sort algorithm comes in two parts:
a sort function and
a merge function
The functions in pseudocode look like this:
function mergesort(m)
var list left, right, result
if length(m) ≤ 1
return m
else
var middle = length(m) / 2
for each x in m up to middle - 1
add x to left
for each x in m at and after middle
add x to right
left = mergesort(left)
right = mergesort(right)
if last(left) ≤ first(right)
append right to left
return left
result = merge(left, right)
return result
function merge(left,right)
var list result
while length(left) > 0 and length(right) > 0
if first(left) ≤ first(right)
append first(left) to result
left = rest(left)
else
append first(right) to result
right = rest(right)
if length(left) > 0
append rest(left) to result
if length(right) > 0
append rest(right) to result
return result
See also
the Wikipedia entry: merge sort
Note: better performance can be expected if, rather than recursing until length(m) ≤ 1, an insertion sort is used for length(m) smaller than some threshold larger than 1. However, this complicates the example code, so it is not shown here.
| #PL.2FI | PL/I | MERGE: PROCEDURE (A,LA,B,LB,C);
/* Merge A(1:LA) with B(1:LB), putting the result in C
B and C may share the same memory, but not with A.
*/
DECLARE (A(*),B(*),C(*)) BYADDR POINTER;
DECLARE (LA,LB) BYVALUE NONASGN FIXED BIN(31);
DECLARE (I,J,K) FIXED BIN(31);
DECLARE (SX) CHAR(58) VAR BASED (PX);
DECLARE (SY) CHAR(58) VAR BASED (PY);
DECLARE (PX,PY) POINTER;
I=1; J=1; K=1;
DO WHILE ((I <= LA) & (J <= LB));
PX=A(I); PY=B(J);
IF(SX <= SY) THEN
DO; C(K)=A(I); K=K+1; I=I+1; END;
ELSE
DO; C(K)=B(J); K=K+1; J=J+1; END;
END;
DO WHILE (I <= LA);
C(K)=A(I); I=I+1; K=K+1;
END;
RETURN;
END MERGE;
MERGESORT: PROCEDURE (AP,N) RECURSIVE ;
/* Sort the array AP containing N pointers to strings */
DECLARE (AP(*)) BYADDR POINTER;
DECLARE (N) BYVALUE NONASGN FIXED BINARY(31);
DECLARE (M,I) FIXED BINARY;
DECLARE AMP1(1) POINTER BASED(PAM);
DECLARE (pX,pY,PAM) POINTER;
DECLARE SX CHAR(58) VAR BASED(pX);
DECLARE SY CHAR(58) VAR BASED(pY);
IF (N=1) THEN RETURN;
M = trunc((N+1)/2);
IF (M>1) THEN CALL MERGESORT(AP,M);
PAM=ADDR(AP(M+1));
IF (N-M > 1) THEN CALL MERGESORT(AMP1,N-M);
pX=AP(M); pY=AP(M+1);
IF SX <= SY then return; /* Skip Merge */
DO I=1 to M; TP(I)=AP(I); END;
CALL MERGE(TP,M,AMP1,N-M,AP);
RETURN;
END MERGESORT; |
http://rosettacode.org/wiki/Sorting_algorithms/Quicksort | Sorting algorithms/Quicksort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Quicksort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
Task
Sort an array (or list) elements using the quicksort algorithm.
The elements must have a strict weak order and the index of the array can be of any discrete type.
For languages where this is not possible, sort an array of integers.
Quicksort, also known as partition-exchange sort, uses these steps.
Choose any element of the array to be the pivot.
Divide all other elements (except the pivot) into two partitions.
All elements less than the pivot must be in the first partition.
All elements greater than the pivot must be in the second partition.
Use recursion to sort both partitions.
Join the first sorted partition, the pivot, and the second sorted partition.
The best pivot creates partitions of equal length (or lengths differing by 1).
The worst pivot creates an empty partition (for example, if the pivot is the first or last element of a sorted array).
The run-time of Quicksort ranges from O(n log n) with the best pivots, to O(n2) with the worst pivots, where n is the number of elements in the array.
This is a simple quicksort algorithm, adapted from Wikipedia.
function quicksort(array)
less, equal, greater := three empty arrays
if length(array) > 1
pivot := select any element of array
for each x in array
if x < pivot then add x to less
if x = pivot then add x to equal
if x > pivot then add x to greater
quicksort(less)
quicksort(greater)
array := concatenate(less, equal, greater)
A better quicksort algorithm works in place, by swapping elements within the array, to avoid the memory allocation of more arrays.
function quicksort(array)
if length(array) > 1
pivot := select any element of array
left := first index of array
right := last index of array
while left ≤ right
while array[left] < pivot
left := left + 1
while array[right] > pivot
right := right - 1
if left ≤ right
swap array[left] with array[right]
left := left + 1
right := right - 1
quicksort(array from first index to right)
quicksort(array from left to last index)
Quicksort has a reputation as the fastest sort. Optimized variants of quicksort are common features of many languages and libraries. One often contrasts quicksort with merge sort, because both sorts have an average time of O(n log n).
"On average, mergesort does fewer comparisons than quicksort, so it may be better when complicated comparison routines are used. Mergesort also takes advantage of pre-existing order, so it would be favored for using sort() to merge several sorted arrays. On the other hand, quicksort is often faster for small arrays, and on arrays of a few distinct values, repeated many times." — http://perldoc.perl.org/sort.html
Quicksort is at one end of the spectrum of divide-and-conquer algorithms, with merge sort at the opposite end.
Quicksort is a conquer-then-divide algorithm, which does most of the work during the partitioning and the recursive calls. The subsequent reassembly of the sorted partitions involves trivial effort.
Merge sort is a divide-then-conquer algorithm. The partioning happens in a trivial way, by splitting the input array in half. Most of the work happens during the recursive calls and the merge phase.
With quicksort, every element in the first partition is less than or equal to every element in the second partition. Therefore, the merge phase of quicksort is so trivial that it needs no mention!
This task has not specified whether to allocate new arrays, or sort in place. This task also has not specified how to choose the pivot element. (Common ways to are to choose the first element, the middle element, or the median of three elements.) Thus there is a variety among the following implementations.
| #Ol | Ol |
(define (quicksort l ??)
(if (null? l)
'()
(append (quicksort (filter (lambda (x) (?? (car l) x)) (cdr l)) ??)
(list (car l))
(quicksort (filter (lambda (x) (not (?? (car l) x))) (cdr l)) ??))))
(print
(quicksort (list 1 3 5 9 8 6 4 3 2) >))
(print
(quicksort (iota 100) >))
(print
(quicksort (iota 100) <))
|
http://rosettacode.org/wiki/Sorting_algorithms/Cocktail_sort_with_shifting_bounds | Sorting algorithms/Cocktail sort with shifting bounds |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Cocktail sort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
The cocktail sort is an improvement on the Bubble Sort.
A cocktail sort is also known as:
cocktail shaker sort
happy hour sort
bidirectional bubble sort
a bubble sort variation
a selection sort variation
ripple sort
shuffle sort
shuttle sort
The improvement is basically that values "bubble" (migrate) both directions through the
array, because on each iteration the cocktail sort bubble sorts once
forwards and once backwards.
After ii passes, the first ii and the
last ii elements in the array are in their correct
positions, and don't have to be checked (again).
By shortening the part of the array that is sorted each time, the number of
comparisons can be halved.
Pseudocode for the 2nd algorithm (from
Wikipedia) with an added comment and changed indentations:
function A = cocktailShakerSort(A)
% `beginIdx` and `endIdx` marks the first and last index to check.
beginIdx = 1;
endIdx = length(A) - 1;
while beginIdx <= endIdx
newBeginIdx = endIdx;
newEndIdx = beginIdx;
for ii = beginIdx:endIdx
if A(ii) > A(ii + 1)
[A(ii+1), A(ii)] = deal(A(ii), A(ii+1));
newEndIdx = ii;
end
end
% decreases `endIdx` because the elements after `newEndIdx` are in correct order
endIdx = newEndIdx - 1;
% (FOR (below) decrements the II index by -1.
for ii = endIdx:-1:beginIdx
if A(ii) > A(ii + 1)
[A(ii+1), A(ii)] = deal(A(ii), A(ii+1));
newBeginIdx = ii;
end
end
% increases `beginIdx` because the elements before `newBeginIdx` are in correct order.
beginIdx = newBeginIdx + 1;
end
end
% indicates a comment, and deal indicates a swap.
Task
Implement a cocktail sort and optionally show the sorted output here on this page.
See the discussion page for some timing comparisons.
Related task
cocktail sort
| #Action.21 | Action! | PROC PrintArray(INT ARRAY a INT size)
INT i
Put('[)
FOR i=0 TO size-1
DO
IF i>0 THEN Put(' ) FI
PrintI(a(i))
OD
Put(']) PutE()
RETURN
PROC CoctailShakerSort(INT ARRAY a INT size)
INT begIdx,endIdx,newBegIdx,newEndIdx,i,tmp
begIdx=0 endIdx=size-2
WHILE begIdx<=endIdx
DO
newBegIdx=endIdx
newEndIdx=begIdx
i=begIdx
WHILE i<=endIdx
DO
IF a(i)>a(i+1) THEN
tmp=a(i) a(i)=a(i+1) a(i+1)=tmp
newEndIdx=i
FI
i==+1
OD
endIdx=newEndIdx-1
i=endIdx
WHILE i>=begIdx
DO
IF a(i)>a(i+1) THEN
tmp=a(i) a(i)=a(i+1) a(i+1)=tmp
newBegIdx=i
FI
i==-1
OD
begIdx=newBegIdx+1
OD
RETURN
PROC Test(INT ARRAY a INT size)
PrintE("Array before sort:")
PrintArray(a,size)
CoctailShakerSort(a,size)
PrintE("Array after sort:")
PrintArray(a,size)
PutE()
RETURN
PROC Main()
INT ARRAY
a(10)=[1 4 65535 0 3 7 4 8 20 65530],
b(21)=[10 9 8 7 6 5 4 3 2 1 0
65535 65534 65533 65532 65531
65530 65529 65528 65527 65526],
c(8)=[101 102 103 104 105 106 107 108],
d(12)=[1 65535 1 65535 1 65535 1
65535 1 65535 1 65535]
Test(a,10)
Test(b,21)
Test(c,8)
Test(d,12)
RETURN |
http://rosettacode.org/wiki/Sorting_algorithms/Cocktail_sort_with_shifting_bounds | Sorting algorithms/Cocktail sort with shifting bounds |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Cocktail sort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
The cocktail sort is an improvement on the Bubble Sort.
A cocktail sort is also known as:
cocktail shaker sort
happy hour sort
bidirectional bubble sort
a bubble sort variation
a selection sort variation
ripple sort
shuffle sort
shuttle sort
The improvement is basically that values "bubble" (migrate) both directions through the
array, because on each iteration the cocktail sort bubble sorts once
forwards and once backwards.
After ii passes, the first ii and the
last ii elements in the array are in their correct
positions, and don't have to be checked (again).
By shortening the part of the array that is sorted each time, the number of
comparisons can be halved.
Pseudocode for the 2nd algorithm (from
Wikipedia) with an added comment and changed indentations:
function A = cocktailShakerSort(A)
% `beginIdx` and `endIdx` marks the first and last index to check.
beginIdx = 1;
endIdx = length(A) - 1;
while beginIdx <= endIdx
newBeginIdx = endIdx;
newEndIdx = beginIdx;
for ii = beginIdx:endIdx
if A(ii) > A(ii + 1)
[A(ii+1), A(ii)] = deal(A(ii), A(ii+1));
newEndIdx = ii;
end
end
% decreases `endIdx` because the elements after `newEndIdx` are in correct order
endIdx = newEndIdx - 1;
% (FOR (below) decrements the II index by -1.
for ii = endIdx:-1:beginIdx
if A(ii) > A(ii + 1)
[A(ii+1), A(ii)] = deal(A(ii), A(ii+1));
newBeginIdx = ii;
end
end
% increases `beginIdx` because the elements before `newBeginIdx` are in correct order.
beginIdx = newBeginIdx + 1;
end
end
% indicates a comment, and deal indicates a swap.
Task
Implement a cocktail sort and optionally show the sorted output here on this page.
See the discussion page for some timing comparisons.
Related task
cocktail sort
| #ALGOL_60 | ALGOL 60 | begin
comment Sorting algorithms/Cocktail sort with shifting bounds - Algol 60;
integer nA;
nA:=20;
begin
integer array A[1:nA];
procedure cocktailsort(lb,ub);
value lb,ub; integer lb,ub;
begin
integer i,lbx,ubx;
boolean swapped;
lbx:=lb; ubx:=ub-1; swapped :=true;
for i:=1 while swapped do begin
procedure swap(i); value i; integer i;
begin
integer temp;
temp :=A[i];
A[i] :=A[i+1];
A[i+1]:=temp;
swapped:=true
end swap;
swapped:=false;
for i:=lbx step 1 until ubx do if A[i]>A[i+1] then swap(i);
if swapped
then begin
for i:=ubx step -1 until lbx do if A[i]>A[i+1] then swap(i);
ubx:=ubx-1; lbx:=lbx+1
end
end
end cocktailsort;
procedure inittable(lb,ub);
value lb,ub; integer lb,ub;
begin
integer i;
for i:=lb step 1 until ub do A[i]:=entier(rand*100)
end inittable;
procedure writetable(lb,ub);
value lb,ub; integer lb,ub;
begin
integer i;
for i:=lb step 1 until ub do outinteger(1,A[i]);
outstring(1,"\n")
end writetable;
nA:=20;
inittable(1,nA);
writetable(1,nA);
cocktailsort(1,nA);
writetable(1,nA)
end
end |
http://rosettacode.org/wiki/Sorting_algorithms/Insertion_sort | Sorting algorithms/Insertion sort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Insertion sort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
An O(n2) sorting algorithm which moves elements one at a time into the correct position.
The algorithm consists of inserting one element at a time into the previously sorted part of the array, moving higher ranked elements up as necessary.
To start off, the first (or smallest, or any arbitrary) element of the unsorted array is considered to be the sorted part.
Although insertion sort is an O(n2) algorithm, its simplicity, low overhead, good locality of reference and efficiency make it a good choice in two cases:
small n,
as the final finishing-off algorithm for O(n logn) algorithms such as mergesort and quicksort.
The algorithm is as follows (from wikipedia):
function insertionSort(array A)
for i from 1 to length[A]-1 do
value := A[i]
j := i-1
while j >= 0 and A[j] > value do
A[j+1] := A[j]
j := j-1
done
A[j+1] = value
done
Writing the algorithm for integers will suffice.
| #PureBasic | PureBasic | Procedure insertionSort(Array a(1))
Protected low, high
Protected firstIndex, lastIndex = ArraySize(a())
If lastIndex > firstIndex + 1
low = firstIndex + 1
While low <= lastIndex
high = low
While high > firstIndex
If a(high) < a(high - 1)
Swap a(high), a(high - 1)
Else
Break
EndIf
high - 1
Wend
low + 1
Wend
EndIf
EndProcedure |
http://rosettacode.org/wiki/Sorting_algorithms/Merge_sort | Sorting algorithms/Merge sort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
The merge sort is a recursive sort of order n*log(n).
It is notable for having a worst case and average complexity of O(n*log(n)), and a best case complexity of O(n) (for pre-sorted input).
The basic idea is to split the collection into smaller groups by halving it until the groups only have one element or no elements (which are both entirely sorted groups).
Then merge the groups back together so that their elements are in order.
This is how the algorithm gets its divide and conquer description.
Task
Write a function to sort a collection of integers using the merge sort.
The merge sort algorithm comes in two parts:
a sort function and
a merge function
The functions in pseudocode look like this:
function mergesort(m)
var list left, right, result
if length(m) ≤ 1
return m
else
var middle = length(m) / 2
for each x in m up to middle - 1
add x to left
for each x in m at and after middle
add x to right
left = mergesort(left)
right = mergesort(right)
if last(left) ≤ first(right)
append right to left
return left
result = merge(left, right)
return result
function merge(left,right)
var list result
while length(left) > 0 and length(right) > 0
if first(left) ≤ first(right)
append first(left) to result
left = rest(left)
else
append first(right) to result
right = rest(right)
if length(left) > 0
append rest(left) to result
if length(right) > 0
append rest(right) to result
return result
See also
the Wikipedia entry: merge sort
Note: better performance can be expected if, rather than recursing until length(m) ≤ 1, an insertion sort is used for length(m) smaller than some threshold larger than 1. However, this complicates the example code, so it is not shown here.
| #PowerShell | PowerShell |
function MergeSort([object[]] $SortInput)
{
# The base case exits for minimal lists that are sorted by definition
if ($SortInput.Length -le 1) {return $SortInput}
# Divide and conquer
[int] $midPoint = $SortInput.Length/2
# The @() operators ensure a single result remains typed as an array
[object[]] $left = @(MergeSort @($SortInput[0..($midPoint-1)]))
[object[]] $right = @(MergeSort @($SortInput[$midPoint..($SortInput.Length-1)]))
# Merge
[object[]] $result = @()
while (($left.Length -gt 0) -and ($right.Length -gt 0))
{
if ($left[0] -lt $right[0])
{
$result += $left[0]
# Use an if/else rather than accessing the array range as $array[1..0]
if ($left.Length -gt 1){$left = $left[1..$($left.Length-1)]}
else {$left = @()}
}
else
{
$result += $right[0]
# Without the if/else, $array[1..0] would return the whole array when $array.Length == 1
if ($right.Length -gt 1){$right = $right[1..$($right.Length-1)]}
else {$right = @()}
}
}
# If we get here, either $left or $right is an empty array (or both are empty!). Since the
# rest of the unmerged array is already sorted, we can simply string together what we have.
# This line outputs the concatenated result. An explicit 'return' statement is not needed.
$result + $left + $right
}
|
http://rosettacode.org/wiki/Sorting_algorithms/Quicksort | Sorting algorithms/Quicksort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Quicksort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
Task
Sort an array (or list) elements using the quicksort algorithm.
The elements must have a strict weak order and the index of the array can be of any discrete type.
For languages where this is not possible, sort an array of integers.
Quicksort, also known as partition-exchange sort, uses these steps.
Choose any element of the array to be the pivot.
Divide all other elements (except the pivot) into two partitions.
All elements less than the pivot must be in the first partition.
All elements greater than the pivot must be in the second partition.
Use recursion to sort both partitions.
Join the first sorted partition, the pivot, and the second sorted partition.
The best pivot creates partitions of equal length (or lengths differing by 1).
The worst pivot creates an empty partition (for example, if the pivot is the first or last element of a sorted array).
The run-time of Quicksort ranges from O(n log n) with the best pivots, to O(n2) with the worst pivots, where n is the number of elements in the array.
This is a simple quicksort algorithm, adapted from Wikipedia.
function quicksort(array)
less, equal, greater := three empty arrays
if length(array) > 1
pivot := select any element of array
for each x in array
if x < pivot then add x to less
if x = pivot then add x to equal
if x > pivot then add x to greater
quicksort(less)
quicksort(greater)
array := concatenate(less, equal, greater)
A better quicksort algorithm works in place, by swapping elements within the array, to avoid the memory allocation of more arrays.
function quicksort(array)
if length(array) > 1
pivot := select any element of array
left := first index of array
right := last index of array
while left ≤ right
while array[left] < pivot
left := left + 1
while array[right] > pivot
right := right - 1
if left ≤ right
swap array[left] with array[right]
left := left + 1
right := right - 1
quicksort(array from first index to right)
quicksort(array from left to last index)
Quicksort has a reputation as the fastest sort. Optimized variants of quicksort are common features of many languages and libraries. One often contrasts quicksort with merge sort, because both sorts have an average time of O(n log n).
"On average, mergesort does fewer comparisons than quicksort, so it may be better when complicated comparison routines are used. Mergesort also takes advantage of pre-existing order, so it would be favored for using sort() to merge several sorted arrays. On the other hand, quicksort is often faster for small arrays, and on arrays of a few distinct values, repeated many times." — http://perldoc.perl.org/sort.html
Quicksort is at one end of the spectrum of divide-and-conquer algorithms, with merge sort at the opposite end.
Quicksort is a conquer-then-divide algorithm, which does most of the work during the partitioning and the recursive calls. The subsequent reassembly of the sorted partitions involves trivial effort.
Merge sort is a divide-then-conquer algorithm. The partioning happens in a trivial way, by splitting the input array in half. Most of the work happens during the recursive calls and the merge phase.
With quicksort, every element in the first partition is less than or equal to every element in the second partition. Therefore, the merge phase of quicksort is so trivial that it needs no mention!
This task has not specified whether to allocate new arrays, or sort in place. This task also has not specified how to choose the pivot element. (Common ways to are to choose the first element, the middle element, or the median of three elements.) Thus there is a variety among the following implementations.
| #ooRexx | ooRexx | a = .array~Of(4, 65, 2, -31, 0, 99, 83, 782, 1)
say 'before:' a~toString( ,', ')
a = quickSort(a)
say ' after:' a~toString( ,', ')
exit
::routine quickSort
use arg arr -- the array to be sorted
less = .array~new
pivotList = .array~new
more = .array~new
if arr~items <= 1 then
return arr
else do
pivot = arr[1]
do i over arr
if i < pivot then
less~append(i)
else if i > pivot then
more~append(i)
else
pivotList~append(i)
end
less = quickSort(less)
more = quickSort(more)
return less~~appendAll(pivotList)~~appendAll(more)
end |
http://rosettacode.org/wiki/Sorting_algorithms/Cocktail_sort_with_shifting_bounds | Sorting algorithms/Cocktail sort with shifting bounds |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Cocktail sort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
The cocktail sort is an improvement on the Bubble Sort.
A cocktail sort is also known as:
cocktail shaker sort
happy hour sort
bidirectional bubble sort
a bubble sort variation
a selection sort variation
ripple sort
shuffle sort
shuttle sort
The improvement is basically that values "bubble" (migrate) both directions through the
array, because on each iteration the cocktail sort bubble sorts once
forwards and once backwards.
After ii passes, the first ii and the
last ii elements in the array are in their correct
positions, and don't have to be checked (again).
By shortening the part of the array that is sorted each time, the number of
comparisons can be halved.
Pseudocode for the 2nd algorithm (from
Wikipedia) with an added comment and changed indentations:
function A = cocktailShakerSort(A)
% `beginIdx` and `endIdx` marks the first and last index to check.
beginIdx = 1;
endIdx = length(A) - 1;
while beginIdx <= endIdx
newBeginIdx = endIdx;
newEndIdx = beginIdx;
for ii = beginIdx:endIdx
if A(ii) > A(ii + 1)
[A(ii+1), A(ii)] = deal(A(ii), A(ii+1));
newEndIdx = ii;
end
end
% decreases `endIdx` because the elements after `newEndIdx` are in correct order
endIdx = newEndIdx - 1;
% (FOR (below) decrements the II index by -1.
for ii = endIdx:-1:beginIdx
if A(ii) > A(ii + 1)
[A(ii+1), A(ii)] = deal(A(ii), A(ii+1));
newBeginIdx = ii;
end
end
% increases `beginIdx` because the elements before `newBeginIdx` are in correct order.
beginIdx = newBeginIdx + 1;
end
end
% indicates a comment, and deal indicates a swap.
Task
Implement a cocktail sort and optionally show the sorted output here on this page.
See the discussion page for some timing comparisons.
Related task
cocktail sort
| #ARM_Assembly | ARM Assembly |
/* ARM assembly Raspberry PI */
/* program cocktailSortBound.s */
/* REMARK 1 : this program use routines in a include file
see task Include a file language arm assembly
for the routine affichageMess conversion10
see at end of this program the instruction include */
/* for constantes see task include a file in arm assembly */
/************************************/
/* Constantes */
/************************************/
.include "../constantes.inc"
/*********************************/
/* Initialized data */
/*********************************/
.data
szMessSortOk: .asciz "Table sorted.\n"
szMessSortNok: .asciz "Table not sorted !!!!!.\n"
sMessResult: .asciz "Value : @ \n"
szCarriageReturn: .asciz "\n"
.align 4
TableNumber: .int 1,3,6,2,5,9,10,8,4,7
#TableNumber: .int 10,9,8,7,6,-5,4,3,2,1
.equ NBELEMENTS, (. - TableNumber) / 4
/*********************************/
/* UnInitialized data */
/*********************************/
.bss
sZoneConv: .skip 24
/*********************************/
/* code section */
/*********************************/
.text
.global main
main: @ entry of program
1:
ldr r0,iAdrTableNumber @ address number table
mov r1,#0
mov r2,#NBELEMENTS @ number of élements
bl cocktailSortBound
ldr r0,iAdrTableNumber @ address number table
bl displayTable
ldr r0,iAdrTableNumber @ address number table
mov r1,#NBELEMENTS @ number of élements
bl isSorted @ control sort
cmp r0,#1 @ sorted ?
beq 2f
ldr r0,iAdrszMessSortNok @ no !! error sort
bl affichageMess
b 100f
2: @ yes
ldr r0,iAdrszMessSortOk
bl affichageMess
100: @ standard end of the program
mov r0, #0 @ return code
mov r7, #EXIT @ request to exit program
svc #0 @ perform the system call
iAdrszCarriageReturn: .int szCarriageReturn
iAdrsMessResult: .int sMessResult
iAdrTableNumber: .int TableNumber
iAdrszMessSortOk: .int szMessSortOk
iAdrszMessSortNok: .int szMessSortNok
/******************************************************************/
/* control sorted table */
/******************************************************************/
/* r0 contains the address of table */
/* r1 contains the number of elements > 0 */
/* r0 return 0 if not sorted 1 if sorted */
isSorted:
push {r2-r4,lr} @ save registers
mov r2,#0
ldr r4,[r0,r2,lsl #2]
1:
add r2,#1
cmp r2,r1
movge r0,#1
bge 100f
ldr r3,[r0,r2, lsl #2]
cmp r3,r4
movlt r0,#0
blt 100f
mov r4,r3
b 1b
100:
pop {r2-r4,lr}
bx lr @ return
/******************************************************************/
/* cocktail Sort */
/******************************************************************/
/* r0 contains the address of table */
/* r1 contains the first element */
/* r2 contains the number of element */
cocktailSortBound:
push {r1-r9,lr} @ save registers
sub r2,r2,#2 @ compute endidx = n - 2
@ and r1= beginidx
1: @ start loop 1
cmp r1,r2 @ compare endidx beginidx
bgt 100f
mov r8,r1 @ newbeginidx
mov r7,r2 @ newendidx
mov r3,r1 @ indice
2: @ start loop 2
add r4,r3,#1
ldr r5,[r0,r3,lsl #2] @ load value A[j]
ldr r6,[r0,r4,lsl #2] @ load value A[j+1]
cmp r6,r5 @ compare value
strlt r6,[r0,r3,lsl #2] @ if smaller inversion
strlt r5,[r0,r4,lsl #2]
movlt r7,r3 @ and mov indice to newendidx
add r3,#1 @ increment indice
cmp r3,r2 @ end ?
ble 2b @ no -> loop 2
sub r2,r7,#1 @ endidx = newendidx
//bl displayTable
mov r3,r2 @ indice
3:
add r4,r3,#1
ldr r5,[r0,r3,lsl #2] @ load value A[j]
ldr r6,[r0,r4,lsl #2] @ load value A[j+1]
cmp r6,r5 @ compare value
strlt r6,[r0,r3,lsl #2] @ if smaller inversion
strlt r5,[r0,r4,lsl #2]
movlt r8,r3 @ newbeginidx = indice
sub r3,#1 @ decrement indice
cmp r3,r1 @ end ?
bge 3b @ no -> loop 3
//bl displayTable
add r1,r8,#1 @ beginidx = newbeginidx + 1
b 1b @ loop 1
100:
pop {r1-r9,lr}
bx lr @ return
/******************************************************************/
/* Display table elements */
/******************************************************************/
/* r0 contains the address of table */
displayTable:
push {r0-r3,lr} @ save registers
mov r2,r0 @ table address
mov r3,#0
1: @ loop display table
ldr r0,[r2,r3,lsl #2]
ldr r1,iAdrsZoneConv @
bl conversion10S @ décimal conversion
ldr r0,iAdrsMessResult
ldr r1,iAdrsZoneConv @ insert conversion
bl strInsertAtCharInc
bl affichageMess @ display message
add r3,#1
cmp r3,#NBELEMENTS - 1
ble 1b
ldr r0,iAdrszCarriageReturn
bl affichageMess
100:
pop {r0-r3,lr}
bx lr
iAdrsZoneConv: .int sZoneConv
/***************************************************/
/* ROUTINES INCLUDE */
/***************************************************/
.include "../affichage.inc"
|
http://rosettacode.org/wiki/Sorting_algorithms/Insertion_sort | Sorting algorithms/Insertion sort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Insertion sort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
An O(n2) sorting algorithm which moves elements one at a time into the correct position.
The algorithm consists of inserting one element at a time into the previously sorted part of the array, moving higher ranked elements up as necessary.
To start off, the first (or smallest, or any arbitrary) element of the unsorted array is considered to be the sorted part.
Although insertion sort is an O(n2) algorithm, its simplicity, low overhead, good locality of reference and efficiency make it a good choice in two cases:
small n,
as the final finishing-off algorithm for O(n logn) algorithms such as mergesort and quicksort.
The algorithm is as follows (from wikipedia):
function insertionSort(array A)
for i from 1 to length[A]-1 do
value := A[i]
j := i-1
while j >= 0 and A[j] > value do
A[j+1] := A[j]
j := j-1
done
A[j+1] = value
done
Writing the algorithm for integers will suffice.
| #Python | Python | def insertion_sort(L):
for i in xrange(1, len(L)):
j = i-1
key = L[i]
while j >= 0 and L[j] > key:
L[j+1] = L[j]
j -= 1
L[j+1] = key |
http://rosettacode.org/wiki/Sorting_algorithms/Merge_sort | Sorting algorithms/Merge sort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
The merge sort is a recursive sort of order n*log(n).
It is notable for having a worst case and average complexity of O(n*log(n)), and a best case complexity of O(n) (for pre-sorted input).
The basic idea is to split the collection into smaller groups by halving it until the groups only have one element or no elements (which are both entirely sorted groups).
Then merge the groups back together so that their elements are in order.
This is how the algorithm gets its divide and conquer description.
Task
Write a function to sort a collection of integers using the merge sort.
The merge sort algorithm comes in two parts:
a sort function and
a merge function
The functions in pseudocode look like this:
function mergesort(m)
var list left, right, result
if length(m) ≤ 1
return m
else
var middle = length(m) / 2
for each x in m up to middle - 1
add x to left
for each x in m at and after middle
add x to right
left = mergesort(left)
right = mergesort(right)
if last(left) ≤ first(right)
append right to left
return left
result = merge(left, right)
return result
function merge(left,right)
var list result
while length(left) > 0 and length(right) > 0
if first(left) ≤ first(right)
append first(left) to result
left = rest(left)
else
append first(right) to result
right = rest(right)
if length(left) > 0
append rest(left) to result
if length(right) > 0
append rest(right) to result
return result
See also
the Wikipedia entry: merge sort
Note: better performance can be expected if, rather than recursing until length(m) ≤ 1, an insertion sort is used for length(m) smaller than some threshold larger than 1. However, this complicates the example code, so it is not shown here.
| #Prolog | Prolog | % msort( L, S )
% True if S is a sorted copy of L, using merge sort
msort( [], [] ).
msort( [X], [X] ).
msort( U, S ) :- split(U, L, R), msort(L, SL), msort(R, SR), merge(SL, SR, S).
% split( LIST, L, R )
% Alternate elements of LIST in L and R
split( [], [], [] ).
split( [X], [X], [] ).
split( [L,R|T], [L|LT], [R|RT] ) :- split( T, LT, RT ).
% merge( LS, RS, M )
% Assuming LS and RS are sorted, True if M is the sorted merge of the two
merge( [], RS, RS ).
merge( LS, [], LS ).
merge( [L|LS], [R|RS], [L|T] ) :- L =< R, merge( LS, [R|RS], T).
merge( [L|LS], [R|RS], [R|T] ) :- L > R, merge( [L|LS], RS, T). |
http://rosettacode.org/wiki/Sorting_algorithms/Quicksort | Sorting algorithms/Quicksort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Quicksort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
Task
Sort an array (or list) elements using the quicksort algorithm.
The elements must have a strict weak order and the index of the array can be of any discrete type.
For languages where this is not possible, sort an array of integers.
Quicksort, also known as partition-exchange sort, uses these steps.
Choose any element of the array to be the pivot.
Divide all other elements (except the pivot) into two partitions.
All elements less than the pivot must be in the first partition.
All elements greater than the pivot must be in the second partition.
Use recursion to sort both partitions.
Join the first sorted partition, the pivot, and the second sorted partition.
The best pivot creates partitions of equal length (or lengths differing by 1).
The worst pivot creates an empty partition (for example, if the pivot is the first or last element of a sorted array).
The run-time of Quicksort ranges from O(n log n) with the best pivots, to O(n2) with the worst pivots, where n is the number of elements in the array.
This is a simple quicksort algorithm, adapted from Wikipedia.
function quicksort(array)
less, equal, greater := three empty arrays
if length(array) > 1
pivot := select any element of array
for each x in array
if x < pivot then add x to less
if x = pivot then add x to equal
if x > pivot then add x to greater
quicksort(less)
quicksort(greater)
array := concatenate(less, equal, greater)
A better quicksort algorithm works in place, by swapping elements within the array, to avoid the memory allocation of more arrays.
function quicksort(array)
if length(array) > 1
pivot := select any element of array
left := first index of array
right := last index of array
while left ≤ right
while array[left] < pivot
left := left + 1
while array[right] > pivot
right := right - 1
if left ≤ right
swap array[left] with array[right]
left := left + 1
right := right - 1
quicksort(array from first index to right)
quicksort(array from left to last index)
Quicksort has a reputation as the fastest sort. Optimized variants of quicksort are common features of many languages and libraries. One often contrasts quicksort with merge sort, because both sorts have an average time of O(n log n).
"On average, mergesort does fewer comparisons than quicksort, so it may be better when complicated comparison routines are used. Mergesort also takes advantage of pre-existing order, so it would be favored for using sort() to merge several sorted arrays. On the other hand, quicksort is often faster for small arrays, and on arrays of a few distinct values, repeated many times." — http://perldoc.perl.org/sort.html
Quicksort is at one end of the spectrum of divide-and-conquer algorithms, with merge sort at the opposite end.
Quicksort is a conquer-then-divide algorithm, which does most of the work during the partitioning and the recursive calls. The subsequent reassembly of the sorted partitions involves trivial effort.
Merge sort is a divide-then-conquer algorithm. The partioning happens in a trivial way, by splitting the input array in half. Most of the work happens during the recursive calls and the merge phase.
With quicksort, every element in the first partition is less than or equal to every element in the second partition. Therefore, the merge phase of quicksort is so trivial that it needs no mention!
This task has not specified whether to allocate new arrays, or sort in place. This task also has not specified how to choose the pivot element. (Common ways to are to choose the first element, the middle element, or the median of three elements.) Thus there is a variety among the following implementations.
| #Oz | Oz | declare
fun {QuickSort Xs}
case Xs of nil then nil
[] Pivot|Xr then
fun {IsSmaller X} X < Pivot end
Smaller Larger
in
{List.partition Xr IsSmaller ?Smaller ?Larger}
{Append {QuickSort Smaller} Pivot|{QuickSort Larger}}
end
end
in
{Show {QuickSort [3 1 4 1 5 9 2 6 5]}} |
http://rosettacode.org/wiki/Sorting_algorithms/Cocktail_sort_with_shifting_bounds | Sorting algorithms/Cocktail sort with shifting bounds |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Cocktail sort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
The cocktail sort is an improvement on the Bubble Sort.
A cocktail sort is also known as:
cocktail shaker sort
happy hour sort
bidirectional bubble sort
a bubble sort variation
a selection sort variation
ripple sort
shuffle sort
shuttle sort
The improvement is basically that values "bubble" (migrate) both directions through the
array, because on each iteration the cocktail sort bubble sorts once
forwards and once backwards.
After ii passes, the first ii and the
last ii elements in the array are in their correct
positions, and don't have to be checked (again).
By shortening the part of the array that is sorted each time, the number of
comparisons can be halved.
Pseudocode for the 2nd algorithm (from
Wikipedia) with an added comment and changed indentations:
function A = cocktailShakerSort(A)
% `beginIdx` and `endIdx` marks the first and last index to check.
beginIdx = 1;
endIdx = length(A) - 1;
while beginIdx <= endIdx
newBeginIdx = endIdx;
newEndIdx = beginIdx;
for ii = beginIdx:endIdx
if A(ii) > A(ii + 1)
[A(ii+1), A(ii)] = deal(A(ii), A(ii+1));
newEndIdx = ii;
end
end
% decreases `endIdx` because the elements after `newEndIdx` are in correct order
endIdx = newEndIdx - 1;
% (FOR (below) decrements the II index by -1.
for ii = endIdx:-1:beginIdx
if A(ii) > A(ii + 1)
[A(ii+1), A(ii)] = deal(A(ii), A(ii+1));
newBeginIdx = ii;
end
end
% increases `beginIdx` because the elements before `newBeginIdx` are in correct order.
beginIdx = newBeginIdx + 1;
end
end
% indicates a comment, and deal indicates a swap.
Task
Implement a cocktail sort and optionally show the sorted output here on this page.
See the discussion page for some timing comparisons.
Related task
cocktail sort
| #Arturo | Arturo | cocktailShiftSort: function [items][
a: new items
beginIdx: 0
endIdx: (size a)-2
while [beginIdx =< endIdx][
newBeginIdx: endIdx
newEndIdx: beginIdx
loop beginIdx..endIdx 'i [
if a\[i] > a\[i+1] [
tmp: a\[i]
a\[i]: a\[i+1]
a\[i+1]: tmp
newEndIdx: i
]
]
endIdx: newEndIdx - 1
loop endIdx..beginIdx 'i [
if a\[i] > a\[i+1] [
tmp: a\[i]
a\[i]: a\[i+1]
a\[i+1]: tmp
newBeginIdx: i
]
]
beginIdx: newBeginIdx - 1
]
return a
]
print cocktailShiftSort [3 1 2 8 5 7 9 4 6] |
http://rosettacode.org/wiki/Sorting_algorithms/Insertion_sort | Sorting algorithms/Insertion sort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Insertion sort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
An O(n2) sorting algorithm which moves elements one at a time into the correct position.
The algorithm consists of inserting one element at a time into the previously sorted part of the array, moving higher ranked elements up as necessary.
To start off, the first (or smallest, or any arbitrary) element of the unsorted array is considered to be the sorted part.
Although insertion sort is an O(n2) algorithm, its simplicity, low overhead, good locality of reference and efficiency make it a good choice in two cases:
small n,
as the final finishing-off algorithm for O(n logn) algorithms such as mergesort and quicksort.
The algorithm is as follows (from wikipedia):
function insertionSort(array A)
for i from 1 to length[A]-1 do
value := A[i]
j := i-1
while j >= 0 and A[j] > value do
A[j+1] := A[j]
j := j-1
done
A[j+1] = value
done
Writing the algorithm for integers will suffice.
| #Qi | Qi | (define insert
X [] -> [X]
X [Y|Ys] -> [X Y|Ys] where (<= X Y)
X [Y|Ys] -> [Y|(insert X Ys)])
(define insertion-sort
[] -> []
[X|Xs] -> (insert X (insertion-sort Xs)))
(insertion-sort [6 8 5 9 3 2 1 4 7])
|
http://rosettacode.org/wiki/Sorting_algorithms/Merge_sort | Sorting algorithms/Merge sort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
The merge sort is a recursive sort of order n*log(n).
It is notable for having a worst case and average complexity of O(n*log(n)), and a best case complexity of O(n) (for pre-sorted input).
The basic idea is to split the collection into smaller groups by halving it until the groups only have one element or no elements (which are both entirely sorted groups).
Then merge the groups back together so that their elements are in order.
This is how the algorithm gets its divide and conquer description.
Task
Write a function to sort a collection of integers using the merge sort.
The merge sort algorithm comes in two parts:
a sort function and
a merge function
The functions in pseudocode look like this:
function mergesort(m)
var list left, right, result
if length(m) ≤ 1
return m
else
var middle = length(m) / 2
for each x in m up to middle - 1
add x to left
for each x in m at and after middle
add x to right
left = mergesort(left)
right = mergesort(right)
if last(left) ≤ first(right)
append right to left
return left
result = merge(left, right)
return result
function merge(left,right)
var list result
while length(left) > 0 and length(right) > 0
if first(left) ≤ first(right)
append first(left) to result
left = rest(left)
else
append first(right) to result
right = rest(right)
if length(left) > 0
append rest(left) to result
if length(right) > 0
append rest(right) to result
return result
See also
the Wikipedia entry: merge sort
Note: better performance can be expected if, rather than recursing until length(m) ≤ 1, an insertion sort is used for length(m) smaller than some threshold larger than 1. However, this complicates the example code, so it is not shown here.
| #PureBasic | PureBasic | Procedure display(List m())
ForEach m()
Print(LSet(Str(m()), 3," "))
Next
PrintN("")
EndProcedure
;overwrites list m() with the merger of lists ma() and mb()
Procedure merge(List m(), List ma(), List mb())
FirstElement(m())
Protected ma_elementExists = FirstElement(ma())
Protected mb_elementExists = FirstElement(mb())
Repeat
If ma() <= mb()
m() = ma(): NextElement(m())
ma_elementExists = NextElement(ma())
Else
m() = mb(): NextElement(m())
mb_elementExists = NextElement(mb())
EndIf
Until Not (ma_elementExists And mb_elementExists)
If ma_elementExists
Repeat
m() = ma(): NextElement(m())
Until Not NextElement(ma())
ElseIf mb_elementExists
Repeat
m() = mb(): NextElement(m())
Until Not NextElement(mb())
EndIf
EndProcedure
Procedure mergesort(List m())
Protected NewList ma()
Protected NewList mb()
If ListSize(m()) > 1
Protected current, middle = (ListSize(m()) / 2 ) - 1
FirstElement(m())
While current <= middle
AddElement(ma())
ma() = m()
NextElement(m()): current + 1
Wend
PreviousElement(m())
While NextElement(m())
AddElement(mb())
mb() = m()
Wend
mergesort(ma())
mergesort(mb())
LastElement(ma()): FirstElement(mb())
If ma() <= mb()
FirstElement(m())
FirstElement(ma())
Repeat
m() = ma(): NextElement(m())
Until Not NextElement(ma())
Repeat
m() = mb(): NextElement(m())
Until Not NextElement(mb())
Else
merge(m(), ma(), mb())
EndIf
EndIf
EndProcedure
If OpenConsole()
Define i
NewList x()
For i = 1 To 21: AddElement(x()): x() = Random(60): Next
display(x())
mergesort(x())
display(x())
Print(#CRLF$ + #CRLF$ + "Press ENTER to exit")
Input()
CloseConsole()
EndIf |
http://rosettacode.org/wiki/Sorting_algorithms/Quicksort | Sorting algorithms/Quicksort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Quicksort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
Task
Sort an array (or list) elements using the quicksort algorithm.
The elements must have a strict weak order and the index of the array can be of any discrete type.
For languages where this is not possible, sort an array of integers.
Quicksort, also known as partition-exchange sort, uses these steps.
Choose any element of the array to be the pivot.
Divide all other elements (except the pivot) into two partitions.
All elements less than the pivot must be in the first partition.
All elements greater than the pivot must be in the second partition.
Use recursion to sort both partitions.
Join the first sorted partition, the pivot, and the second sorted partition.
The best pivot creates partitions of equal length (or lengths differing by 1).
The worst pivot creates an empty partition (for example, if the pivot is the first or last element of a sorted array).
The run-time of Quicksort ranges from O(n log n) with the best pivots, to O(n2) with the worst pivots, where n is the number of elements in the array.
This is a simple quicksort algorithm, adapted from Wikipedia.
function quicksort(array)
less, equal, greater := three empty arrays
if length(array) > 1
pivot := select any element of array
for each x in array
if x < pivot then add x to less
if x = pivot then add x to equal
if x > pivot then add x to greater
quicksort(less)
quicksort(greater)
array := concatenate(less, equal, greater)
A better quicksort algorithm works in place, by swapping elements within the array, to avoid the memory allocation of more arrays.
function quicksort(array)
if length(array) > 1
pivot := select any element of array
left := first index of array
right := last index of array
while left ≤ right
while array[left] < pivot
left := left + 1
while array[right] > pivot
right := right - 1
if left ≤ right
swap array[left] with array[right]
left := left + 1
right := right - 1
quicksort(array from first index to right)
quicksort(array from left to last index)
Quicksort has a reputation as the fastest sort. Optimized variants of quicksort are common features of many languages and libraries. One often contrasts quicksort with merge sort, because both sorts have an average time of O(n log n).
"On average, mergesort does fewer comparisons than quicksort, so it may be better when complicated comparison routines are used. Mergesort also takes advantage of pre-existing order, so it would be favored for using sort() to merge several sorted arrays. On the other hand, quicksort is often faster for small arrays, and on arrays of a few distinct values, repeated many times." — http://perldoc.perl.org/sort.html
Quicksort is at one end of the spectrum of divide-and-conquer algorithms, with merge sort at the opposite end.
Quicksort is a conquer-then-divide algorithm, which does most of the work during the partitioning and the recursive calls. The subsequent reassembly of the sorted partitions involves trivial effort.
Merge sort is a divide-then-conquer algorithm. The partioning happens in a trivial way, by splitting the input array in half. Most of the work happens during the recursive calls and the merge phase.
With quicksort, every element in the first partition is less than or equal to every element in the second partition. Therefore, the merge phase of quicksort is so trivial that it needs no mention!
This task has not specified whether to allocate new arrays, or sort in place. This task also has not specified how to choose the pivot element. (Common ways to are to choose the first element, the middle element, or the median of three elements.) Thus there is a variety among the following implementations.
| #PARI.2FGP | PARI/GP | quickSort(v)={
if(#v<2, return(v));
my(less=List(),more=List(),same=List(),pivot);
pivot=median([v[random(#v)+1],v[random(#v)+1],v[random(#v)+1]]); \\ Middle-of-three
for(i=1,#v,
if(v[i]<pivot,
listput(less, v[i]),
if(v[i]==pivot, listput(same, v[i]), listput(more, v[i]))
)
);
concat(quickSort(Vec(less)), concat(Vec(same), quickSort(Vec(more))))
};
median(v)={
vecsort(v)[#v>>1]
}; |
http://rosettacode.org/wiki/Sorting_algorithms/Cocktail_sort_with_shifting_bounds | Sorting algorithms/Cocktail sort with shifting bounds |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Cocktail sort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
The cocktail sort is an improvement on the Bubble Sort.
A cocktail sort is also known as:
cocktail shaker sort
happy hour sort
bidirectional bubble sort
a bubble sort variation
a selection sort variation
ripple sort
shuffle sort
shuttle sort
The improvement is basically that values "bubble" (migrate) both directions through the
array, because on each iteration the cocktail sort bubble sorts once
forwards and once backwards.
After ii passes, the first ii and the
last ii elements in the array are in their correct
positions, and don't have to be checked (again).
By shortening the part of the array that is sorted each time, the number of
comparisons can be halved.
Pseudocode for the 2nd algorithm (from
Wikipedia) with an added comment and changed indentations:
function A = cocktailShakerSort(A)
% `beginIdx` and `endIdx` marks the first and last index to check.
beginIdx = 1;
endIdx = length(A) - 1;
while beginIdx <= endIdx
newBeginIdx = endIdx;
newEndIdx = beginIdx;
for ii = beginIdx:endIdx
if A(ii) > A(ii + 1)
[A(ii+1), A(ii)] = deal(A(ii), A(ii+1));
newEndIdx = ii;
end
end
% decreases `endIdx` because the elements after `newEndIdx` are in correct order
endIdx = newEndIdx - 1;
% (FOR (below) decrements the II index by -1.
for ii = endIdx:-1:beginIdx
if A(ii) > A(ii + 1)
[A(ii+1), A(ii)] = deal(A(ii), A(ii+1));
newBeginIdx = ii;
end
end
% increases `beginIdx` because the elements before `newBeginIdx` are in correct order.
beginIdx = newBeginIdx + 1;
end
end
% indicates a comment, and deal indicates a swap.
Task
Implement a cocktail sort and optionally show the sorted output here on this page.
See the discussion page for some timing comparisons.
Related task
cocktail sort
| #AutoHotkey | AutoHotkey | cocktailShakerSort(A){
beginIdx := 1
endIdx := A.Count() - 1
while (beginIdx <= endIdx) {
newBeginIdx := endIdx
newEndIdx := beginIdx
ii := beginIdx
while (ii <= endIdx) {
if (A[ii] > A[ii + 1]) {
tempVal := A[ii], A[ii] := A[ii+1], A[ii+1] := tempVal
newEndIdx := ii
}
ii++
}
endIdx := newEndIdx - 1
ii := endIdx
while (ii >= beginIdx) {
if (A[ii] > A[ii + 1]) {
tempVal := A[ii], A[ii] := A[ii+1], A[ii+1] := tempVal
newBeginIdx := ii
}
ii--
}
beginIdx := newBeginIdx + 1
}
} |
http://rosettacode.org/wiki/Sorting_algorithms/Insertion_sort | Sorting algorithms/Insertion sort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Insertion sort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
An O(n2) sorting algorithm which moves elements one at a time into the correct position.
The algorithm consists of inserting one element at a time into the previously sorted part of the array, moving higher ranked elements up as necessary.
To start off, the first (or smallest, or any arbitrary) element of the unsorted array is considered to be the sorted part.
Although insertion sort is an O(n2) algorithm, its simplicity, low overhead, good locality of reference and efficiency make it a good choice in two cases:
small n,
as the final finishing-off algorithm for O(n logn) algorithms such as mergesort and quicksort.
The algorithm is as follows (from wikipedia):
function insertionSort(array A)
for i from 1 to length[A]-1 do
value := A[i]
j := i-1
while j >= 0 and A[j] > value do
A[j+1] := A[j]
j := j-1
done
A[j+1] = value
done
Writing the algorithm for integers will suffice.
| #Quackery | Quackery | [ [] swap witheach
[ swap 2dup findwith
[ over > ] [ ]
nip stuff ] ] is insertionsort ( [ --> [ ) |
http://rosettacode.org/wiki/Sorting_algorithms/Merge_sort | Sorting algorithms/Merge sort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
The merge sort is a recursive sort of order n*log(n).
It is notable for having a worst case and average complexity of O(n*log(n)), and a best case complexity of O(n) (for pre-sorted input).
The basic idea is to split the collection into smaller groups by halving it until the groups only have one element or no elements (which are both entirely sorted groups).
Then merge the groups back together so that their elements are in order.
This is how the algorithm gets its divide and conquer description.
Task
Write a function to sort a collection of integers using the merge sort.
The merge sort algorithm comes in two parts:
a sort function and
a merge function
The functions in pseudocode look like this:
function mergesort(m)
var list left, right, result
if length(m) ≤ 1
return m
else
var middle = length(m) / 2
for each x in m up to middle - 1
add x to left
for each x in m at and after middle
add x to right
left = mergesort(left)
right = mergesort(right)
if last(left) ≤ first(right)
append right to left
return left
result = merge(left, right)
return result
function merge(left,right)
var list result
while length(left) > 0 and length(right) > 0
if first(left) ≤ first(right)
append first(left) to result
left = rest(left)
else
append first(right) to result
right = rest(right)
if length(left) > 0
append rest(left) to result
if length(right) > 0
append rest(right) to result
return result
See also
the Wikipedia entry: merge sort
Note: better performance can be expected if, rather than recursing until length(m) ≤ 1, an insertion sort is used for length(m) smaller than some threshold larger than 1. However, this complicates the example code, so it is not shown here.
| #Python | Python | from heapq import merge
def merge_sort(m):
if len(m) <= 1:
return m
middle = len(m) // 2
left = m[:middle]
right = m[middle:]
left = merge_sort(left)
right = merge_sort(right)
return list(merge(left, right)) |
http://rosettacode.org/wiki/Sorting_algorithms/Quicksort | Sorting algorithms/Quicksort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Quicksort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
Task
Sort an array (or list) elements using the quicksort algorithm.
The elements must have a strict weak order and the index of the array can be of any discrete type.
For languages where this is not possible, sort an array of integers.
Quicksort, also known as partition-exchange sort, uses these steps.
Choose any element of the array to be the pivot.
Divide all other elements (except the pivot) into two partitions.
All elements less than the pivot must be in the first partition.
All elements greater than the pivot must be in the second partition.
Use recursion to sort both partitions.
Join the first sorted partition, the pivot, and the second sorted partition.
The best pivot creates partitions of equal length (or lengths differing by 1).
The worst pivot creates an empty partition (for example, if the pivot is the first or last element of a sorted array).
The run-time of Quicksort ranges from O(n log n) with the best pivots, to O(n2) with the worst pivots, where n is the number of elements in the array.
This is a simple quicksort algorithm, adapted from Wikipedia.
function quicksort(array)
less, equal, greater := three empty arrays
if length(array) > 1
pivot := select any element of array
for each x in array
if x < pivot then add x to less
if x = pivot then add x to equal
if x > pivot then add x to greater
quicksort(less)
quicksort(greater)
array := concatenate(less, equal, greater)
A better quicksort algorithm works in place, by swapping elements within the array, to avoid the memory allocation of more arrays.
function quicksort(array)
if length(array) > 1
pivot := select any element of array
left := first index of array
right := last index of array
while left ≤ right
while array[left] < pivot
left := left + 1
while array[right] > pivot
right := right - 1
if left ≤ right
swap array[left] with array[right]
left := left + 1
right := right - 1
quicksort(array from first index to right)
quicksort(array from left to last index)
Quicksort has a reputation as the fastest sort. Optimized variants of quicksort are common features of many languages and libraries. One often contrasts quicksort with merge sort, because both sorts have an average time of O(n log n).
"On average, mergesort does fewer comparisons than quicksort, so it may be better when complicated comparison routines are used. Mergesort also takes advantage of pre-existing order, so it would be favored for using sort() to merge several sorted arrays. On the other hand, quicksort is often faster for small arrays, and on arrays of a few distinct values, repeated many times." — http://perldoc.perl.org/sort.html
Quicksort is at one end of the spectrum of divide-and-conquer algorithms, with merge sort at the opposite end.
Quicksort is a conquer-then-divide algorithm, which does most of the work during the partitioning and the recursive calls. The subsequent reassembly of the sorted partitions involves trivial effort.
Merge sort is a divide-then-conquer algorithm. The partioning happens in a trivial way, by splitting the input array in half. Most of the work happens during the recursive calls and the merge phase.
With quicksort, every element in the first partition is less than or equal to every element in the second partition. Therefore, the merge phase of quicksort is so trivial that it needs no mention!
This task has not specified whether to allocate new arrays, or sort in place. This task also has not specified how to choose the pivot element. (Common ways to are to choose the first element, the middle element, or the median of three elements.) Thus there is a variety among the following implementations.
| #Pascal | Pascal |
{ X is array of LongInt }
Procedure QuickSort ( Left, Right : LongInt );
Var
i, j,
tmp, pivot : LongInt; { tmp & pivot are the same type as the elements of array }
Begin
i:=Left;
j:=Right;
pivot := X[(Left + Right) shr 1]; // pivot := X[(Left + Rigth) div 2]
Repeat
While pivot > X[i] Do inc(i); // i:=i+1;
While pivot < X[j] Do dec(j); // j:=j-1;
If i<=j Then Begin
tmp:=X[i];
X[i]:=X[j];
X[j]:=tmp;
dec(j); // j:=j-1;
inc(i); // i:=i+1;
End;
Until i>j;
If Left<j Then QuickSort(Left,j);
If i<Right Then QuickSort(i,Right);
End;
|
http://rosettacode.org/wiki/Sorting_algorithms/Cocktail_sort_with_shifting_bounds | Sorting algorithms/Cocktail sort with shifting bounds |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Cocktail sort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
The cocktail sort is an improvement on the Bubble Sort.
A cocktail sort is also known as:
cocktail shaker sort
happy hour sort
bidirectional bubble sort
a bubble sort variation
a selection sort variation
ripple sort
shuffle sort
shuttle sort
The improvement is basically that values "bubble" (migrate) both directions through the
array, because on each iteration the cocktail sort bubble sorts once
forwards and once backwards.
After ii passes, the first ii and the
last ii elements in the array are in their correct
positions, and don't have to be checked (again).
By shortening the part of the array that is sorted each time, the number of
comparisons can be halved.
Pseudocode for the 2nd algorithm (from
Wikipedia) with an added comment and changed indentations:
function A = cocktailShakerSort(A)
% `beginIdx` and `endIdx` marks the first and last index to check.
beginIdx = 1;
endIdx = length(A) - 1;
while beginIdx <= endIdx
newBeginIdx = endIdx;
newEndIdx = beginIdx;
for ii = beginIdx:endIdx
if A(ii) > A(ii + 1)
[A(ii+1), A(ii)] = deal(A(ii), A(ii+1));
newEndIdx = ii;
end
end
% decreases `endIdx` because the elements after `newEndIdx` are in correct order
endIdx = newEndIdx - 1;
% (FOR (below) decrements the II index by -1.
for ii = endIdx:-1:beginIdx
if A(ii) > A(ii + 1)
[A(ii+1), A(ii)] = deal(A(ii), A(ii+1));
newBeginIdx = ii;
end
end
% increases `beginIdx` because the elements before `newBeginIdx` are in correct order.
beginIdx = newBeginIdx + 1;
end
end
% indicates a comment, and deal indicates a swap.
Task
Implement a cocktail sort and optionally show the sorted output here on this page.
See the discussion page for some timing comparisons.
Related task
cocktail sort
| #C | C | #include <stdio.h>
#include <string.h>
void swap(char* p1, char* p2, size_t size) {
for (; size-- > 0; ++p1, ++p2) {
char tmp = *p1;
*p1 = *p2;
*p2 = tmp;
}
}
void cocktail_shaker_sort(void* base, size_t count, size_t size,
int (*cmp)(const void*, const void*)) {
char* begin = base;
char* end = base + size * count;
if (end == begin)
return;
for (end -= size; begin < end; ) {
char* new_begin = end;
char* new_end = begin;
for (char* p = begin; p < end; p += size) {
char* q = p + size;
if (cmp(p, q) > 0) {
swap(p, q, size);
new_end = p;
}
}
end = new_end;
for (char* p = end; p > begin; p -= size) {
char* q = p - size;
if (cmp(q, p) > 0) {
swap(p, q, size);
new_begin = p;
}
}
begin = new_begin;
}
}
int string_compare(const void* p1, const void* p2) {
const char* const* s1 = p1;
const char* const* s2 = p2;
return strcmp(*s1, *s2);
}
void print(const char** a, size_t len) {
for (size_t i = 0; i < len; ++i)
printf("%s ", a[i]);
printf("\n");
}
int main() {
const char* a[] = { "one", "two", "three", "four", "five",
"six", "seven", "eight" };
const size_t len = sizeof(a)/sizeof(a[0]);
printf("before: ");
print(a, len);
cocktail_shaker_sort(a, len, sizeof(char*), string_compare);
printf("after: ");
print(a, len);
return 0;
} |
http://rosettacode.org/wiki/Sorting_algorithms/Insertion_sort | Sorting algorithms/Insertion sort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Insertion sort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
An O(n2) sorting algorithm which moves elements one at a time into the correct position.
The algorithm consists of inserting one element at a time into the previously sorted part of the array, moving higher ranked elements up as necessary.
To start off, the first (or smallest, or any arbitrary) element of the unsorted array is considered to be the sorted part.
Although insertion sort is an O(n2) algorithm, its simplicity, low overhead, good locality of reference and efficiency make it a good choice in two cases:
small n,
as the final finishing-off algorithm for O(n logn) algorithms such as mergesort and quicksort.
The algorithm is as follows (from wikipedia):
function insertionSort(array A)
for i from 1 to length[A]-1 do
value := A[i]
j := i-1
while j >= 0 and A[j] > value do
A[j+1] := A[j]
j := j-1
done
A[j+1] = value
done
Writing the algorithm for integers will suffice.
| #R | R | insertionsort <- function(x)
{
for(i in 2:(length(x)))
{
value <- x[i]
j <- i - 1
while(j >= 1 && x[j] > value)
{
x[j+1] <- x[j]
j <- j-1
}
x[j+1] <- value
}
x
}
insertionsort(c(4, 65, 2, -31, 0, 99, 83, 782, 1)) # -31 0 1 2 4 65 83 99 782 |
http://rosettacode.org/wiki/Sorting_algorithms/Merge_sort | Sorting algorithms/Merge sort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
The merge sort is a recursive sort of order n*log(n).
It is notable for having a worst case and average complexity of O(n*log(n)), and a best case complexity of O(n) (for pre-sorted input).
The basic idea is to split the collection into smaller groups by halving it until the groups only have one element or no elements (which are both entirely sorted groups).
Then merge the groups back together so that their elements are in order.
This is how the algorithm gets its divide and conquer description.
Task
Write a function to sort a collection of integers using the merge sort.
The merge sort algorithm comes in two parts:
a sort function and
a merge function
The functions in pseudocode look like this:
function mergesort(m)
var list left, right, result
if length(m) ≤ 1
return m
else
var middle = length(m) / 2
for each x in m up to middle - 1
add x to left
for each x in m at and after middle
add x to right
left = mergesort(left)
right = mergesort(right)
if last(left) ≤ first(right)
append right to left
return left
result = merge(left, right)
return result
function merge(left,right)
var list result
while length(left) > 0 and length(right) > 0
if first(left) ≤ first(right)
append first(left) to result
left = rest(left)
else
append first(right) to result
right = rest(right)
if length(left) > 0
append rest(left) to result
if length(right) > 0
append rest(right) to result
return result
See also
the Wikipedia entry: merge sort
Note: better performance can be expected if, rather than recursing until length(m) ≤ 1, an insertion sort is used for length(m) smaller than some threshold larger than 1. However, this complicates the example code, so it is not shown here.
| #Quackery | Quackery | [ [] temp put
[ dup [] != while
over [] != while
over 0 peek
over 0 peek
> not if dip
[ 1 split
temp take
rot join
temp put ]
again ]
join
temp take swap join ] is merge ( [ [ --> [ )
[ dup size 2 < if done
dup size 2 / split
swap recurse
swap recurse
merge ] is mergesort ( [ --> [ ) |
http://rosettacode.org/wiki/Sorting_algorithms/Quicksort | Sorting algorithms/Quicksort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Quicksort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
Task
Sort an array (or list) elements using the quicksort algorithm.
The elements must have a strict weak order and the index of the array can be of any discrete type.
For languages where this is not possible, sort an array of integers.
Quicksort, also known as partition-exchange sort, uses these steps.
Choose any element of the array to be the pivot.
Divide all other elements (except the pivot) into two partitions.
All elements less than the pivot must be in the first partition.
All elements greater than the pivot must be in the second partition.
Use recursion to sort both partitions.
Join the first sorted partition, the pivot, and the second sorted partition.
The best pivot creates partitions of equal length (or lengths differing by 1).
The worst pivot creates an empty partition (for example, if the pivot is the first or last element of a sorted array).
The run-time of Quicksort ranges from O(n log n) with the best pivots, to O(n2) with the worst pivots, where n is the number of elements in the array.
This is a simple quicksort algorithm, adapted from Wikipedia.
function quicksort(array)
less, equal, greater := three empty arrays
if length(array) > 1
pivot := select any element of array
for each x in array
if x < pivot then add x to less
if x = pivot then add x to equal
if x > pivot then add x to greater
quicksort(less)
quicksort(greater)
array := concatenate(less, equal, greater)
A better quicksort algorithm works in place, by swapping elements within the array, to avoid the memory allocation of more arrays.
function quicksort(array)
if length(array) > 1
pivot := select any element of array
left := first index of array
right := last index of array
while left ≤ right
while array[left] < pivot
left := left + 1
while array[right] > pivot
right := right - 1
if left ≤ right
swap array[left] with array[right]
left := left + 1
right := right - 1
quicksort(array from first index to right)
quicksort(array from left to last index)
Quicksort has a reputation as the fastest sort. Optimized variants of quicksort are common features of many languages and libraries. One often contrasts quicksort with merge sort, because both sorts have an average time of O(n log n).
"On average, mergesort does fewer comparisons than quicksort, so it may be better when complicated comparison routines are used. Mergesort also takes advantage of pre-existing order, so it would be favored for using sort() to merge several sorted arrays. On the other hand, quicksort is often faster for small arrays, and on arrays of a few distinct values, repeated many times." — http://perldoc.perl.org/sort.html
Quicksort is at one end of the spectrum of divide-and-conquer algorithms, with merge sort at the opposite end.
Quicksort is a conquer-then-divide algorithm, which does most of the work during the partitioning and the recursive calls. The subsequent reassembly of the sorted partitions involves trivial effort.
Merge sort is a divide-then-conquer algorithm. The partioning happens in a trivial way, by splitting the input array in half. Most of the work happens during the recursive calls and the merge phase.
With quicksort, every element in the first partition is less than or equal to every element in the second partition. Therefore, the merge phase of quicksort is so trivial that it needs no mention!
This task has not specified whether to allocate new arrays, or sort in place. This task also has not specified how to choose the pivot element. (Common ways to are to choose the first element, the middle element, or the median of three elements.) Thus there is a variety among the following implementations.
| #Perl | Perl |
sub quick_sort {
return @_ if @_ < 2;
my $p = splice @_, int rand @_, 1;
quick_sort(grep $_ < $p, @_), $p, quick_sort(grep $_ >= $p, @_);
}
my @a = (4, 65, 2, -31, 0, 99, 83, 782, 1);
@a = quick_sort @a;
print "@a\n";
|
http://rosettacode.org/wiki/Sorting_algorithms/Cocktail_sort_with_shifting_bounds | Sorting algorithms/Cocktail sort with shifting bounds |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Cocktail sort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
The cocktail sort is an improvement on the Bubble Sort.
A cocktail sort is also known as:
cocktail shaker sort
happy hour sort
bidirectional bubble sort
a bubble sort variation
a selection sort variation
ripple sort
shuffle sort
shuttle sort
The improvement is basically that values "bubble" (migrate) both directions through the
array, because on each iteration the cocktail sort bubble sorts once
forwards and once backwards.
After ii passes, the first ii and the
last ii elements in the array are in their correct
positions, and don't have to be checked (again).
By shortening the part of the array that is sorted each time, the number of
comparisons can be halved.
Pseudocode for the 2nd algorithm (from
Wikipedia) with an added comment and changed indentations:
function A = cocktailShakerSort(A)
% `beginIdx` and `endIdx` marks the first and last index to check.
beginIdx = 1;
endIdx = length(A) - 1;
while beginIdx <= endIdx
newBeginIdx = endIdx;
newEndIdx = beginIdx;
for ii = beginIdx:endIdx
if A(ii) > A(ii + 1)
[A(ii+1), A(ii)] = deal(A(ii), A(ii+1));
newEndIdx = ii;
end
end
% decreases `endIdx` because the elements after `newEndIdx` are in correct order
endIdx = newEndIdx - 1;
% (FOR (below) decrements the II index by -1.
for ii = endIdx:-1:beginIdx
if A(ii) > A(ii + 1)
[A(ii+1), A(ii)] = deal(A(ii), A(ii+1));
newBeginIdx = ii;
end
end
% increases `beginIdx` because the elements before `newBeginIdx` are in correct order.
beginIdx = newBeginIdx + 1;
end
end
% indicates a comment, and deal indicates a swap.
Task
Implement a cocktail sort and optionally show the sorted output here on this page.
See the discussion page for some timing comparisons.
Related task
cocktail sort
| #C.2B.2B | C++ | #include <algorithm>
#include <cassert>
#include <iostream>
#include <iterator>
#include <vector>
// This only works for random access iterators
template <typename iterator>
void cocktail_shaker_sort(iterator begin, iterator end) {
if (begin == end)
return;
for (--end; begin < end; ) {
iterator new_begin = end;
iterator new_end = begin;
for (iterator i = begin; i < end; ++i) {
iterator j = i + 1;
if (*j < *i) {
std::iter_swap(i, j);
new_end = i;
}
}
end = new_end;
for (iterator i = end; i > begin; --i) {
iterator j = i - 1;
if (*i < *j) {
std::iter_swap(i, j);
new_begin = i;
}
}
begin = new_begin;
}
}
template <typename iterator>
void print(iterator begin, iterator end) {
if (begin == end)
return;
std::cout << *begin++;
while (begin != end)
std::cout << ' ' << *begin++;
std::cout << '\n';
}
int main() {
std::vector<int> v{5, 1, -6, 12, 3, 13, 2, 4, 0, 15};
std::cout << "before: ";
print(v.begin(), v.end());
cocktail_shaker_sort(v.begin(), v.end());
assert(std::is_sorted(v.begin(), v.end()));
std::cout << "after: ";
print(v.begin(), v.end());
return 0;
} |
http://rosettacode.org/wiki/Sorting_algorithms/Insertion_sort | Sorting algorithms/Insertion sort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Insertion sort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
An O(n2) sorting algorithm which moves elements one at a time into the correct position.
The algorithm consists of inserting one element at a time into the previously sorted part of the array, moving higher ranked elements up as necessary.
To start off, the first (or smallest, or any arbitrary) element of the unsorted array is considered to be the sorted part.
Although insertion sort is an O(n2) algorithm, its simplicity, low overhead, good locality of reference and efficiency make it a good choice in two cases:
small n,
as the final finishing-off algorithm for O(n logn) algorithms such as mergesort and quicksort.
The algorithm is as follows (from wikipedia):
function insertionSort(array A)
for i from 1 to length[A]-1 do
value := A[i]
j := i-1
while j >= 0 and A[j] > value do
A[j+1] := A[j]
j := j-1
done
A[j+1] = value
done
Writing the algorithm for integers will suffice.
| #Racket | Racket |
#lang racket
(define (sort < l)
(define (insert x ys)
(match ys
[(list) (list x)]
[(cons y rst) (cond [(< x y) (cons x ys)]
[else (cons y (insert x rst))])]))
(foldl insert '() l)) |
http://rosettacode.org/wiki/Sorting_algorithms/Merge_sort | Sorting algorithms/Merge sort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
The merge sort is a recursive sort of order n*log(n).
It is notable for having a worst case and average complexity of O(n*log(n)), and a best case complexity of O(n) (for pre-sorted input).
The basic idea is to split the collection into smaller groups by halving it until the groups only have one element or no elements (which are both entirely sorted groups).
Then merge the groups back together so that their elements are in order.
This is how the algorithm gets its divide and conquer description.
Task
Write a function to sort a collection of integers using the merge sort.
The merge sort algorithm comes in two parts:
a sort function and
a merge function
The functions in pseudocode look like this:
function mergesort(m)
var list left, right, result
if length(m) ≤ 1
return m
else
var middle = length(m) / 2
for each x in m up to middle - 1
add x to left
for each x in m at and after middle
add x to right
left = mergesort(left)
right = mergesort(right)
if last(left) ≤ first(right)
append right to left
return left
result = merge(left, right)
return result
function merge(left,right)
var list result
while length(left) > 0 and length(right) > 0
if first(left) ≤ first(right)
append first(left) to result
left = rest(left)
else
append first(right) to result
right = rest(right)
if length(left) > 0
append rest(left) to result
if length(right) > 0
append rest(right) to result
return result
See also
the Wikipedia entry: merge sort
Note: better performance can be expected if, rather than recursing until length(m) ≤ 1, an insertion sort is used for length(m) smaller than some threshold larger than 1. However, this complicates the example code, so it is not shown here.
| #R | R | mergesort <- function(m)
{
merge_ <- function(left, right)
{
result <- c()
while(length(left) > 0 && length(right) > 0)
{
if(left[1] <= right[1])
{
result <- c(result, left[1])
left <- left[-1]
} else
{
result <- c(result, right[1])
right <- right[-1]
}
}
if(length(left) > 0) result <- c(result, left)
if(length(right) > 0) result <- c(result, right)
result
}
len <- length(m)
if(len <= 1) m else
{
middle <- length(m) / 2
left <- m[1:floor(middle)]
right <- m[floor(middle+1):len]
left <- mergesort(left)
right <- mergesort(right)
if(left[length(left)] <= right[1])
{
c(left, right)
} else
{
merge_(left, right)
}
}
}
mergesort(c(4, 65, 2, -31, 0, 99, 83, 782, 1)) # -31 0 1 2 4 65 83 99 782 |
http://rosettacode.org/wiki/Sorting_algorithms/Quicksort | Sorting algorithms/Quicksort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Quicksort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
Task
Sort an array (or list) elements using the quicksort algorithm.
The elements must have a strict weak order and the index of the array can be of any discrete type.
For languages where this is not possible, sort an array of integers.
Quicksort, also known as partition-exchange sort, uses these steps.
Choose any element of the array to be the pivot.
Divide all other elements (except the pivot) into two partitions.
All elements less than the pivot must be in the first partition.
All elements greater than the pivot must be in the second partition.
Use recursion to sort both partitions.
Join the first sorted partition, the pivot, and the second sorted partition.
The best pivot creates partitions of equal length (or lengths differing by 1).
The worst pivot creates an empty partition (for example, if the pivot is the first or last element of a sorted array).
The run-time of Quicksort ranges from O(n log n) with the best pivots, to O(n2) with the worst pivots, where n is the number of elements in the array.
This is a simple quicksort algorithm, adapted from Wikipedia.
function quicksort(array)
less, equal, greater := three empty arrays
if length(array) > 1
pivot := select any element of array
for each x in array
if x < pivot then add x to less
if x = pivot then add x to equal
if x > pivot then add x to greater
quicksort(less)
quicksort(greater)
array := concatenate(less, equal, greater)
A better quicksort algorithm works in place, by swapping elements within the array, to avoid the memory allocation of more arrays.
function quicksort(array)
if length(array) > 1
pivot := select any element of array
left := first index of array
right := last index of array
while left ≤ right
while array[left] < pivot
left := left + 1
while array[right] > pivot
right := right - 1
if left ≤ right
swap array[left] with array[right]
left := left + 1
right := right - 1
quicksort(array from first index to right)
quicksort(array from left to last index)
Quicksort has a reputation as the fastest sort. Optimized variants of quicksort are common features of many languages and libraries. One often contrasts quicksort with merge sort, because both sorts have an average time of O(n log n).
"On average, mergesort does fewer comparisons than quicksort, so it may be better when complicated comparison routines are used. Mergesort also takes advantage of pre-existing order, so it would be favored for using sort() to merge several sorted arrays. On the other hand, quicksort is often faster for small arrays, and on arrays of a few distinct values, repeated many times." — http://perldoc.perl.org/sort.html
Quicksort is at one end of the spectrum of divide-and-conquer algorithms, with merge sort at the opposite end.
Quicksort is a conquer-then-divide algorithm, which does most of the work during the partitioning and the recursive calls. The subsequent reassembly of the sorted partitions involves trivial effort.
Merge sort is a divide-then-conquer algorithm. The partioning happens in a trivial way, by splitting the input array in half. Most of the work happens during the recursive calls and the merge phase.
With quicksort, every element in the first partition is less than or equal to every element in the second partition. Therefore, the merge phase of quicksort is so trivial that it needs no mention!
This task has not specified whether to allocate new arrays, or sort in place. This task also has not specified how to choose the pivot element. (Common ways to are to choose the first element, the middle element, or the median of three elements.) Thus there is a variety among the following implementations.
| #Phix | Phix | with javascript_semantics
function quick_sort(sequence x)
--
-- put x into ascending order using recursive quick sort
--
integer n = length(x)
if n<2 then
return x -- already sorted (trivial case)
end if
integer mid = floor((n+1)/2),
last = 1
object midval = x[mid]
x[mid] = x[1]
for i=2 to n do
object xi = x[i]
if xi<midval then
last += 1
x[i] = x[last]
x[last] = xi
end if
end for
return quick_sort(x[2..last]) & {midval} & quick_sort(x[last+1..n])
end function
?quick_sort({5,"oranges","and",3,"apples"})
|
http://rosettacode.org/wiki/Sorting_algorithms/Cocktail_sort_with_shifting_bounds | Sorting algorithms/Cocktail sort with shifting bounds |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Cocktail sort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
The cocktail sort is an improvement on the Bubble Sort.
A cocktail sort is also known as:
cocktail shaker sort
happy hour sort
bidirectional bubble sort
a bubble sort variation
a selection sort variation
ripple sort
shuffle sort
shuttle sort
The improvement is basically that values "bubble" (migrate) both directions through the
array, because on each iteration the cocktail sort bubble sorts once
forwards and once backwards.
After ii passes, the first ii and the
last ii elements in the array are in their correct
positions, and don't have to be checked (again).
By shortening the part of the array that is sorted each time, the number of
comparisons can be halved.
Pseudocode for the 2nd algorithm (from
Wikipedia) with an added comment and changed indentations:
function A = cocktailShakerSort(A)
% `beginIdx` and `endIdx` marks the first and last index to check.
beginIdx = 1;
endIdx = length(A) - 1;
while beginIdx <= endIdx
newBeginIdx = endIdx;
newEndIdx = beginIdx;
for ii = beginIdx:endIdx
if A(ii) > A(ii + 1)
[A(ii+1), A(ii)] = deal(A(ii), A(ii+1));
newEndIdx = ii;
end
end
% decreases `endIdx` because the elements after `newEndIdx` are in correct order
endIdx = newEndIdx - 1;
% (FOR (below) decrements the II index by -1.
for ii = endIdx:-1:beginIdx
if A(ii) > A(ii + 1)
[A(ii+1), A(ii)] = deal(A(ii), A(ii+1));
newBeginIdx = ii;
end
end
% increases `beginIdx` because the elements before `newBeginIdx` are in correct order.
beginIdx = newBeginIdx + 1;
end
end
% indicates a comment, and deal indicates a swap.
Task
Implement a cocktail sort and optionally show the sorted output here on this page.
See the discussion page for some timing comparisons.
Related task
cocktail sort
| #FreeBASIC | FreeBASIC |
Sub cocktailShakerSort(bs() As Long)
Dim As Long i, lb = Lbound(bs), ub = Ubound(bs) -1
Dim As Long newlb, newub, tmp
Do While lb <= ub
newlb = ub
newub = lb
For i = lb To ub
If bs(i) > bs(i + 1) Then
tmp = bs(i): bs(i) = bs(i + 1): bs(i + 1) = tmp
newub = i
End If
Next i
ub = newub - 1
For i = ub To lb Step -1
If bs(i) > bs(i + 1) Then
tmp = bs(i): bs(i) = bs(i + 1): bs(i + 1) = tmp
newlb = i
End If
Next i
lb = newlb + 1
Loop
End Sub
'--- Programa Principal ---
Dim As Long i, array(-7 To 7)
Dim As Long a = Lbound(array), b = Ubound(array)
Randomize Timer
For i = a To b : array(i) = i : Next i
For i = a To b
Swap array(i), array(Int(Rnd * (b - a + 1)) + a)
Next i
Print "unsort ";
For i = a To b : Print Using "####"; array(i); : Next i
cocktailShakerSort(array()) ' ordenar el array
Print !"\n sort ";
For i = a To b : Print Using "####"; array(i); : Next i
Print !"\n--- terminado, pulsa RETURN---"
Sleep
|
http://rosettacode.org/wiki/Sorting_algorithms/Insertion_sort | Sorting algorithms/Insertion sort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Insertion sort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
An O(n2) sorting algorithm which moves elements one at a time into the correct position.
The algorithm consists of inserting one element at a time into the previously sorted part of the array, moving higher ranked elements up as necessary.
To start off, the first (or smallest, or any arbitrary) element of the unsorted array is considered to be the sorted part.
Although insertion sort is an O(n2) algorithm, its simplicity, low overhead, good locality of reference and efficiency make it a good choice in two cases:
small n,
as the final finishing-off algorithm for O(n logn) algorithms such as mergesort and quicksort.
The algorithm is as follows (from wikipedia):
function insertionSort(array A)
for i from 1 to length[A]-1 do
value := A[i]
j := i-1
while j >= 0 and A[j] > value do
A[j+1] := A[j]
j := j-1
done
A[j+1] = value
done
Writing the algorithm for integers will suffice.
| #Raku | Raku | sub insertion_sort ( @a is copy ) {
for 1 .. @a.end -> $i {
my $value = @a[$i];
my $j;
loop ( $j = $i-1; $j >= 0 and @a[$j] > $value; $j-- ) {
@a[$j+1] = @a[$j];
}
@a[$j+1] = $value;
}
return @a;
}
my @data = 22, 7, 2, -5, 8, 4;
say 'input = ' ~ @data;
say 'output = ' ~ @data.&insertion_sort;
|
http://rosettacode.org/wiki/Sorting_algorithms/Merge_sort | Sorting algorithms/Merge sort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
The merge sort is a recursive sort of order n*log(n).
It is notable for having a worst case and average complexity of O(n*log(n)), and a best case complexity of O(n) (for pre-sorted input).
The basic idea is to split the collection into smaller groups by halving it until the groups only have one element or no elements (which are both entirely sorted groups).
Then merge the groups back together so that their elements are in order.
This is how the algorithm gets its divide and conquer description.
Task
Write a function to sort a collection of integers using the merge sort.
The merge sort algorithm comes in two parts:
a sort function and
a merge function
The functions in pseudocode look like this:
function mergesort(m)
var list left, right, result
if length(m) ≤ 1
return m
else
var middle = length(m) / 2
for each x in m up to middle - 1
add x to left
for each x in m at and after middle
add x to right
left = mergesort(left)
right = mergesort(right)
if last(left) ≤ first(right)
append right to left
return left
result = merge(left, right)
return result
function merge(left,right)
var list result
while length(left) > 0 and length(right) > 0
if first(left) ≤ first(right)
append first(left) to result
left = rest(left)
else
append first(right) to result
right = rest(right)
if length(left) > 0
append rest(left) to result
if length(right) > 0
append rest(right) to result
return result
See also
the Wikipedia entry: merge sort
Note: better performance can be expected if, rather than recursing until length(m) ≤ 1, an insertion sort is used for length(m) smaller than some threshold larger than 1. However, this complicates the example code, so it is not shown here.
| #Racket | Racket |
#lang racket
(define (merge xs ys)
(cond [(empty? xs) ys]
[(empty? ys) xs]
[(match* (xs ys)
[((list* a as) (list* b bs))
(cond [(<= a b) (cons a (merge as ys))]
[ (cons b (merge xs bs))])])]))
(define (merge-sort xs)
(match xs
[(or (list) (list _)) xs]
[_ (define-values (ys zs) (split-at xs (quotient (length xs) 2)))
(merge (merge-sort ys) (merge-sort zs))]))
|
http://rosettacode.org/wiki/Sorting_algorithms/Quicksort | Sorting algorithms/Quicksort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Quicksort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
Task
Sort an array (or list) elements using the quicksort algorithm.
The elements must have a strict weak order and the index of the array can be of any discrete type.
For languages where this is not possible, sort an array of integers.
Quicksort, also known as partition-exchange sort, uses these steps.
Choose any element of the array to be the pivot.
Divide all other elements (except the pivot) into two partitions.
All elements less than the pivot must be in the first partition.
All elements greater than the pivot must be in the second partition.
Use recursion to sort both partitions.
Join the first sorted partition, the pivot, and the second sorted partition.
The best pivot creates partitions of equal length (or lengths differing by 1).
The worst pivot creates an empty partition (for example, if the pivot is the first or last element of a sorted array).
The run-time of Quicksort ranges from O(n log n) with the best pivots, to O(n2) with the worst pivots, where n is the number of elements in the array.
This is a simple quicksort algorithm, adapted from Wikipedia.
function quicksort(array)
less, equal, greater := three empty arrays
if length(array) > 1
pivot := select any element of array
for each x in array
if x < pivot then add x to less
if x = pivot then add x to equal
if x > pivot then add x to greater
quicksort(less)
quicksort(greater)
array := concatenate(less, equal, greater)
A better quicksort algorithm works in place, by swapping elements within the array, to avoid the memory allocation of more arrays.
function quicksort(array)
if length(array) > 1
pivot := select any element of array
left := first index of array
right := last index of array
while left ≤ right
while array[left] < pivot
left := left + 1
while array[right] > pivot
right := right - 1
if left ≤ right
swap array[left] with array[right]
left := left + 1
right := right - 1
quicksort(array from first index to right)
quicksort(array from left to last index)
Quicksort has a reputation as the fastest sort. Optimized variants of quicksort are common features of many languages and libraries. One often contrasts quicksort with merge sort, because both sorts have an average time of O(n log n).
"On average, mergesort does fewer comparisons than quicksort, so it may be better when complicated comparison routines are used. Mergesort also takes advantage of pre-existing order, so it would be favored for using sort() to merge several sorted arrays. On the other hand, quicksort is often faster for small arrays, and on arrays of a few distinct values, repeated many times." — http://perldoc.perl.org/sort.html
Quicksort is at one end of the spectrum of divide-and-conquer algorithms, with merge sort at the opposite end.
Quicksort is a conquer-then-divide algorithm, which does most of the work during the partitioning and the recursive calls. The subsequent reassembly of the sorted partitions involves trivial effort.
Merge sort is a divide-then-conquer algorithm. The partioning happens in a trivial way, by splitting the input array in half. Most of the work happens during the recursive calls and the merge phase.
With quicksort, every element in the first partition is less than or equal to every element in the second partition. Therefore, the merge phase of quicksort is so trivial that it needs no mention!
This task has not specified whether to allocate new arrays, or sort in place. This task also has not specified how to choose the pivot element. (Common ways to are to choose the first element, the middle element, or the median of three elements.) Thus there is a variety among the following implementations.
| #PHP | PHP | function quicksort($arr){
$lte = $gt = array();
if(count($arr) < 2){
return $arr;
}
$pivot_key = key($arr);
$pivot = array_shift($arr);
foreach($arr as $val){
if($val <= $pivot){
$lte[] = $val;
} else {
$gt[] = $val;
}
}
return array_merge(quicksort($lte),array($pivot_key=>$pivot),quicksort($gt));
}
$arr = array(1, 3, 5, 7, 9, 8, 6, 4, 2);
$arr = quicksort($arr);
echo implode(',',$arr); |
http://rosettacode.org/wiki/Sorting_algorithms/Cocktail_sort_with_shifting_bounds | Sorting algorithms/Cocktail sort with shifting bounds |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Cocktail sort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
The cocktail sort is an improvement on the Bubble Sort.
A cocktail sort is also known as:
cocktail shaker sort
happy hour sort
bidirectional bubble sort
a bubble sort variation
a selection sort variation
ripple sort
shuffle sort
shuttle sort
The improvement is basically that values "bubble" (migrate) both directions through the
array, because on each iteration the cocktail sort bubble sorts once
forwards and once backwards.
After ii passes, the first ii and the
last ii elements in the array are in their correct
positions, and don't have to be checked (again).
By shortening the part of the array that is sorted each time, the number of
comparisons can be halved.
Pseudocode for the 2nd algorithm (from
Wikipedia) with an added comment and changed indentations:
function A = cocktailShakerSort(A)
% `beginIdx` and `endIdx` marks the first and last index to check.
beginIdx = 1;
endIdx = length(A) - 1;
while beginIdx <= endIdx
newBeginIdx = endIdx;
newEndIdx = beginIdx;
for ii = beginIdx:endIdx
if A(ii) > A(ii + 1)
[A(ii+1), A(ii)] = deal(A(ii), A(ii+1));
newEndIdx = ii;
end
end
% decreases `endIdx` because the elements after `newEndIdx` are in correct order
endIdx = newEndIdx - 1;
% (FOR (below) decrements the II index by -1.
for ii = endIdx:-1:beginIdx
if A(ii) > A(ii + 1)
[A(ii+1), A(ii)] = deal(A(ii), A(ii+1));
newBeginIdx = ii;
end
end
% increases `beginIdx` because the elements before `newBeginIdx` are in correct order.
beginIdx = newBeginIdx + 1;
end
end
% indicates a comment, and deal indicates a swap.
Task
Implement a cocktail sort and optionally show the sorted output here on this page.
See the discussion page for some timing comparisons.
Related task
cocktail sort
| #Go | Go | package main
import (
"fmt"
"math/rand"
"time"
)
// translation of pseudo-code
func cocktailShakerSort(a []int) {
var begin = 0
var end = len(a) - 2
for begin <= end {
newBegin := end
newEnd := begin
for i := begin; i <= end; i++ {
if a[i] > a[i+1] {
a[i+1], a[i] = a[i], a[i+1]
newEnd = i
}
}
end = newEnd - 1
for i := end; i >= begin; i-- {
if a[i] > a[i+1] {
a[i+1], a[i] = a[i], a[i+1]
newBegin = i
}
}
begin = newBegin + 1
}
}
// from the RC Cocktail sort task (no optimizations)
func cocktailSort(a []int) {
last := len(a) - 1
for {
swapped := false
for i := 0; i < last; i++ {
if a[i] > a[i+1] {
a[i], a[i+1] = a[i+1], a[i]
swapped = true
}
}
if !swapped {
return
}
swapped = false
for i := last - 1; i >= 0; i-- {
if a[i] > a[i+1] {
a[i], a[i+1] = a[i+1], a[i]
swapped = true
}
}
if !swapped {
return
}
}
}
func main() {
// First make sure the routines are working correctly.
a := []int{21, 4, -9, 62, -7, 107, -62, 4, 0, -170}
fmt.Println("Original array:", a)
b := make([]int, len(a))
copy(b, a) // as sorts mutate array in place
cocktailSort(a)
fmt.Println("Cocktail sort :", a)
cocktailShakerSort(b)
fmt.Println("C/Shaker sort :", b)
// timing comparison code
rand.Seed(time.Now().UnixNano())
fmt.Println("\nRelative speed of the two sorts")
fmt.Println(" N x faster (CSS v CS)")
fmt.Println("----- -------------------")
const runs = 10 // average over 10 runs say
for _, n := range []int{1000, 2000, 4000, 8000, 10000, 20000} {
sum := 0.0
for i := 1; i <= runs; i++ {
// get 'n' random numbers in range [0, 100,000]
// with every other number being negated
nums := make([]int, n)
for i := 0; i < n; i++ {
rn := rand.Intn(100000)
if i%2 == 1 {
rn = -rn
}
nums[i] = rn
}
// copy the array
nums2 := make([]int, n)
copy(nums2, nums)
start := time.Now()
cocktailSort(nums)
elapsed := time.Since(start)
start2 := time.Now()
cocktailShakerSort(nums2)
elapsed2 := time.Since(start2)
sum += float64(elapsed) / float64(elapsed2)
}
fmt.Printf(" %2dk %0.3f\n", n/1000, sum/runs)
}
} |
http://rosettacode.org/wiki/Sorting_algorithms/Insertion_sort | Sorting algorithms/Insertion sort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Insertion sort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
An O(n2) sorting algorithm which moves elements one at a time into the correct position.
The algorithm consists of inserting one element at a time into the previously sorted part of the array, moving higher ranked elements up as necessary.
To start off, the first (or smallest, or any arbitrary) element of the unsorted array is considered to be the sorted part.
Although insertion sort is an O(n2) algorithm, its simplicity, low overhead, good locality of reference and efficiency make it a good choice in two cases:
small n,
as the final finishing-off algorithm for O(n logn) algorithms such as mergesort and quicksort.
The algorithm is as follows (from wikipedia):
function insertionSort(array A)
for i from 1 to length[A]-1 do
value := A[i]
j := i-1
while j >= 0 and A[j] > value do
A[j+1] := A[j]
j := j-1
done
A[j+1] = value
done
Writing the algorithm for integers will suffice.
| #Rascal | Rascal | import List;
public list[int] insertionSort(a){
for(i <- [0..size(a)-1]){
v = a[i];
j = i-1;
while(j >= 0 && a[j] > v){
a[j+1] = a[j];
j -= 1;
}
a[j+1] = v;
}
return a;
} |
http://rosettacode.org/wiki/Sorting_algorithms/Merge_sort | Sorting algorithms/Merge sort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
The merge sort is a recursive sort of order n*log(n).
It is notable for having a worst case and average complexity of O(n*log(n)), and a best case complexity of O(n) (for pre-sorted input).
The basic idea is to split the collection into smaller groups by halving it until the groups only have one element or no elements (which are both entirely sorted groups).
Then merge the groups back together so that their elements are in order.
This is how the algorithm gets its divide and conquer description.
Task
Write a function to sort a collection of integers using the merge sort.
The merge sort algorithm comes in two parts:
a sort function and
a merge function
The functions in pseudocode look like this:
function mergesort(m)
var list left, right, result
if length(m) ≤ 1
return m
else
var middle = length(m) / 2
for each x in m up to middle - 1
add x to left
for each x in m at and after middle
add x to right
left = mergesort(left)
right = mergesort(right)
if last(left) ≤ first(right)
append right to left
return left
result = merge(left, right)
return result
function merge(left,right)
var list result
while length(left) > 0 and length(right) > 0
if first(left) ≤ first(right)
append first(left) to result
left = rest(left)
else
append first(right) to result
right = rest(right)
if length(left) > 0
append rest(left) to result
if length(right) > 0
append rest(right) to result
return result
See also
the Wikipedia entry: merge sort
Note: better performance can be expected if, rather than recursing until length(m) ≤ 1, an insertion sort is used for length(m) smaller than some threshold larger than 1. However, this complicates the example code, so it is not shown here.
| #Raku | Raku | sub merge_sort ( @a ) {
return @a if @a <= 1;
my $m = @a.elems div 2;
my @l = flat merge_sort @a[ 0 ..^ $m ];
my @r = flat merge_sort @a[ $m ..^ @a ];
return flat @l, @r if @l[*-1] !after @r[0];
return flat gather {
take @l[0] before @r[0] ?? @l.shift !! @r.shift
while @l and @r;
take @l, @r;
}
}
my @data = 6, 7, 2, 1, 8, 9, 5, 3, 4;
say 'input = ' ~ @data;
say 'output = ' ~ @data.&merge_sort; |
http://rosettacode.org/wiki/Sorting_algorithms/Quicksort | Sorting algorithms/Quicksort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Quicksort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
Task
Sort an array (or list) elements using the quicksort algorithm.
The elements must have a strict weak order and the index of the array can be of any discrete type.
For languages where this is not possible, sort an array of integers.
Quicksort, also known as partition-exchange sort, uses these steps.
Choose any element of the array to be the pivot.
Divide all other elements (except the pivot) into two partitions.
All elements less than the pivot must be in the first partition.
All elements greater than the pivot must be in the second partition.
Use recursion to sort both partitions.
Join the first sorted partition, the pivot, and the second sorted partition.
The best pivot creates partitions of equal length (or lengths differing by 1).
The worst pivot creates an empty partition (for example, if the pivot is the first or last element of a sorted array).
The run-time of Quicksort ranges from O(n log n) with the best pivots, to O(n2) with the worst pivots, where n is the number of elements in the array.
This is a simple quicksort algorithm, adapted from Wikipedia.
function quicksort(array)
less, equal, greater := three empty arrays
if length(array) > 1
pivot := select any element of array
for each x in array
if x < pivot then add x to less
if x = pivot then add x to equal
if x > pivot then add x to greater
quicksort(less)
quicksort(greater)
array := concatenate(less, equal, greater)
A better quicksort algorithm works in place, by swapping elements within the array, to avoid the memory allocation of more arrays.
function quicksort(array)
if length(array) > 1
pivot := select any element of array
left := first index of array
right := last index of array
while left ≤ right
while array[left] < pivot
left := left + 1
while array[right] > pivot
right := right - 1
if left ≤ right
swap array[left] with array[right]
left := left + 1
right := right - 1
quicksort(array from first index to right)
quicksort(array from left to last index)
Quicksort has a reputation as the fastest sort. Optimized variants of quicksort are common features of many languages and libraries. One often contrasts quicksort with merge sort, because both sorts have an average time of O(n log n).
"On average, mergesort does fewer comparisons than quicksort, so it may be better when complicated comparison routines are used. Mergesort also takes advantage of pre-existing order, so it would be favored for using sort() to merge several sorted arrays. On the other hand, quicksort is often faster for small arrays, and on arrays of a few distinct values, repeated many times." — http://perldoc.perl.org/sort.html
Quicksort is at one end of the spectrum of divide-and-conquer algorithms, with merge sort at the opposite end.
Quicksort is a conquer-then-divide algorithm, which does most of the work during the partitioning and the recursive calls. The subsequent reassembly of the sorted partitions involves trivial effort.
Merge sort is a divide-then-conquer algorithm. The partioning happens in a trivial way, by splitting the input array in half. Most of the work happens during the recursive calls and the merge phase.
With quicksort, every element in the first partition is less than or equal to every element in the second partition. Therefore, the merge phase of quicksort is so trivial that it needs no mention!
This task has not specified whether to allocate new arrays, or sort in place. This task also has not specified how to choose the pivot element. (Common ways to are to choose the first element, the middle element, or the median of three elements.) Thus there is a variety among the following implementations.
| #Picat | Picat | qsort([]) = [].
qsort([H|T]) = qsort([E : E in T, E =< H])
++ [H] ++
qsort([E : E in T, E > H]). |
http://rosettacode.org/wiki/Sorting_algorithms/Cocktail_sort_with_shifting_bounds | Sorting algorithms/Cocktail sort with shifting bounds |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Cocktail sort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
The cocktail sort is an improvement on the Bubble Sort.
A cocktail sort is also known as:
cocktail shaker sort
happy hour sort
bidirectional bubble sort
a bubble sort variation
a selection sort variation
ripple sort
shuffle sort
shuttle sort
The improvement is basically that values "bubble" (migrate) both directions through the
array, because on each iteration the cocktail sort bubble sorts once
forwards and once backwards.
After ii passes, the first ii and the
last ii elements in the array are in their correct
positions, and don't have to be checked (again).
By shortening the part of the array that is sorted each time, the number of
comparisons can be halved.
Pseudocode for the 2nd algorithm (from
Wikipedia) with an added comment and changed indentations:
function A = cocktailShakerSort(A)
% `beginIdx` and `endIdx` marks the first and last index to check.
beginIdx = 1;
endIdx = length(A) - 1;
while beginIdx <= endIdx
newBeginIdx = endIdx;
newEndIdx = beginIdx;
for ii = beginIdx:endIdx
if A(ii) > A(ii + 1)
[A(ii+1), A(ii)] = deal(A(ii), A(ii+1));
newEndIdx = ii;
end
end
% decreases `endIdx` because the elements after `newEndIdx` are in correct order
endIdx = newEndIdx - 1;
% (FOR (below) decrements the II index by -1.
for ii = endIdx:-1:beginIdx
if A(ii) > A(ii + 1)
[A(ii+1), A(ii)] = deal(A(ii), A(ii+1));
newBeginIdx = ii;
end
end
% increases `beginIdx` because the elements before `newBeginIdx` are in correct order.
beginIdx = newBeginIdx + 1;
end
end
% indicates a comment, and deal indicates a swap.
Task
Implement a cocktail sort and optionally show the sorted output here on this page.
See the discussion page for some timing comparisons.
Related task
cocktail sort
| #Groovy | Groovy | class CocktailSort {
static void main(String[] args) {
Integer[] array = [ 5, 1, -6, 12, 3, 13, 2, 4, 0, 15 ]
println("before: " + Arrays.toString(array))
cocktailSort(array)
println("after: " + Arrays.toString(array))
}
// Sorts an array of elements that implement the Comparable interface
static void cocktailSort(Object[] array) {
int begin = 0
int end = array.length
if (end == 0) {
return
}
for (--end; begin < end; ) {
int new_begin = end
int new_end = begin
for (int i = begin; i < end; ++i) {
Comparable c1 = (Comparable)array[i]
Comparable c2 = (Comparable)array[i + 1]
if (c1 > c2) {
swap(array, i, i + 1)
new_end = i
}
}
end = new_end
for (int i = end; i > begin; --i) {
Comparable c1 = (Comparable)array[i - 1]
Comparable c2 = (Comparable)array[i]
if (c1 > c2) {
swap(array, i, i - 1)
new_begin = i
}
}
begin = new_begin
}
}
private static void swap(Object[] array, int i, int j) {
Object tmp = array[i]
array[i] = array[j]
array[j] = tmp
}
} |
http://rosettacode.org/wiki/Sorting_algorithms/Insertion_sort | Sorting algorithms/Insertion sort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Insertion sort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
An O(n2) sorting algorithm which moves elements one at a time into the correct position.
The algorithm consists of inserting one element at a time into the previously sorted part of the array, moving higher ranked elements up as necessary.
To start off, the first (or smallest, or any arbitrary) element of the unsorted array is considered to be the sorted part.
Although insertion sort is an O(n2) algorithm, its simplicity, low overhead, good locality of reference and efficiency make it a good choice in two cases:
small n,
as the final finishing-off algorithm for O(n logn) algorithms such as mergesort and quicksort.
The algorithm is as follows (from wikipedia):
function insertionSort(array A)
for i from 1 to length[A]-1 do
value := A[i]
j := i-1
while j >= 0 and A[j] > value do
A[j+1] := A[j]
j := j-1
done
A[j+1] = value
done
Writing the algorithm for integers will suffice.
| #REALbasic | REALbasic | Sub InsertionSort(theList() as Integer)
for insertionElementIndex as Integer = 1 to UBound(theList)
dim insertionElement as Integer = theList(insertionElementIndex)
dim j as Integer = insertionElementIndex - 1
while (j >= 0) and (insertionElement < theList(j))
theList(j + 1) = theList(j)
j = j - 1
wend
theList(j + 1) = insertionElement
next
End Sub |
http://rosettacode.org/wiki/Sorting_algorithms/Merge_sort | Sorting algorithms/Merge sort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
The merge sort is a recursive sort of order n*log(n).
It is notable for having a worst case and average complexity of O(n*log(n)), and a best case complexity of O(n) (for pre-sorted input).
The basic idea is to split the collection into smaller groups by halving it until the groups only have one element or no elements (which are both entirely sorted groups).
Then merge the groups back together so that their elements are in order.
This is how the algorithm gets its divide and conquer description.
Task
Write a function to sort a collection of integers using the merge sort.
The merge sort algorithm comes in two parts:
a sort function and
a merge function
The functions in pseudocode look like this:
function mergesort(m)
var list left, right, result
if length(m) ≤ 1
return m
else
var middle = length(m) / 2
for each x in m up to middle - 1
add x to left
for each x in m at and after middle
add x to right
left = mergesort(left)
right = mergesort(right)
if last(left) ≤ first(right)
append right to left
return left
result = merge(left, right)
return result
function merge(left,right)
var list result
while length(left) > 0 and length(right) > 0
if first(left) ≤ first(right)
append first(left) to result
left = rest(left)
else
append first(right) to result
right = rest(right)
if length(left) > 0
append rest(left) to result
if length(right) > 0
append rest(right) to result
return result
See also
the Wikipedia entry: merge sort
Note: better performance can be expected if, rather than recursing until length(m) ≤ 1, an insertion sort is used for length(m) smaller than some threshold larger than 1. However, this complicates the example code, so it is not shown here.
| #REBOL | REBOL | msort: function [a compare] [msort-do merge] [
if (length? a) < 2 [return a]
; define a recursive Msort-do function
msort-do: function [a b l] [mid] [
either l < 4 [
if l = 3 [msort-do next b next a 2]
merge a b 1 next b l - 1
] [
mid: make integer! l / 2
msort-do b a mid
msort-do skip b mid skip a mid l - mid
merge a b mid skip b mid l - mid
]
]
; function Merge is the key part of the algorithm
merge: func [a b lb c lc] [
until [
either (compare first b first c) [
change/only a first b
b: next b
a: next a
zero? lb: lb - 1
] [
change/only a first c
c: next c
a: next a
zero? lc: lc - 1
]
]
loop lb [
change/only a first b
b: next b
a: next a
]
loop lc [
change/only a first c
c: next c
a: next a
]
]
msort-do a copy a length? a
a
] |
http://rosettacode.org/wiki/Sorting_algorithms/Quicksort | Sorting algorithms/Quicksort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Quicksort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
Task
Sort an array (or list) elements using the quicksort algorithm.
The elements must have a strict weak order and the index of the array can be of any discrete type.
For languages where this is not possible, sort an array of integers.
Quicksort, also known as partition-exchange sort, uses these steps.
Choose any element of the array to be the pivot.
Divide all other elements (except the pivot) into two partitions.
All elements less than the pivot must be in the first partition.
All elements greater than the pivot must be in the second partition.
Use recursion to sort both partitions.
Join the first sorted partition, the pivot, and the second sorted partition.
The best pivot creates partitions of equal length (or lengths differing by 1).
The worst pivot creates an empty partition (for example, if the pivot is the first or last element of a sorted array).
The run-time of Quicksort ranges from O(n log n) with the best pivots, to O(n2) with the worst pivots, where n is the number of elements in the array.
This is a simple quicksort algorithm, adapted from Wikipedia.
function quicksort(array)
less, equal, greater := three empty arrays
if length(array) > 1
pivot := select any element of array
for each x in array
if x < pivot then add x to less
if x = pivot then add x to equal
if x > pivot then add x to greater
quicksort(less)
quicksort(greater)
array := concatenate(less, equal, greater)
A better quicksort algorithm works in place, by swapping elements within the array, to avoid the memory allocation of more arrays.
function quicksort(array)
if length(array) > 1
pivot := select any element of array
left := first index of array
right := last index of array
while left ≤ right
while array[left] < pivot
left := left + 1
while array[right] > pivot
right := right - 1
if left ≤ right
swap array[left] with array[right]
left := left + 1
right := right - 1
quicksort(array from first index to right)
quicksort(array from left to last index)
Quicksort has a reputation as the fastest sort. Optimized variants of quicksort are common features of many languages and libraries. One often contrasts quicksort with merge sort, because both sorts have an average time of O(n log n).
"On average, mergesort does fewer comparisons than quicksort, so it may be better when complicated comparison routines are used. Mergesort also takes advantage of pre-existing order, so it would be favored for using sort() to merge several sorted arrays. On the other hand, quicksort is often faster for small arrays, and on arrays of a few distinct values, repeated many times." — http://perldoc.perl.org/sort.html
Quicksort is at one end of the spectrum of divide-and-conquer algorithms, with merge sort at the opposite end.
Quicksort is a conquer-then-divide algorithm, which does most of the work during the partitioning and the recursive calls. The subsequent reassembly of the sorted partitions involves trivial effort.
Merge sort is a divide-then-conquer algorithm. The partioning happens in a trivial way, by splitting the input array in half. Most of the work happens during the recursive calls and the merge phase.
With quicksort, every element in the first partition is less than or equal to every element in the second partition. Therefore, the merge phase of quicksort is so trivial that it needs no mention!
This task has not specified whether to allocate new arrays, or sort in place. This task also has not specified how to choose the pivot element. (Common ways to are to choose the first element, the middle element, or the median of three elements.) Thus there is a variety among the following implementations.
| #PicoLisp | PicoLisp | (de quicksort (L)
(if (cdr L)
(let Pivot (car L)
(append (quicksort (filter '((A) (< A Pivot)) (cdr L)))
(filter '((A) (= A Pivot)) L )
(quicksort (filter '((A) (> A Pivot)) (cdr L)))) )
L) ) |
http://rosettacode.org/wiki/Sorting_algorithms/Cocktail_sort_with_shifting_bounds | Sorting algorithms/Cocktail sort with shifting bounds |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Cocktail sort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
The cocktail sort is an improvement on the Bubble Sort.
A cocktail sort is also known as:
cocktail shaker sort
happy hour sort
bidirectional bubble sort
a bubble sort variation
a selection sort variation
ripple sort
shuffle sort
shuttle sort
The improvement is basically that values "bubble" (migrate) both directions through the
array, because on each iteration the cocktail sort bubble sorts once
forwards and once backwards.
After ii passes, the first ii and the
last ii elements in the array are in their correct
positions, and don't have to be checked (again).
By shortening the part of the array that is sorted each time, the number of
comparisons can be halved.
Pseudocode for the 2nd algorithm (from
Wikipedia) with an added comment and changed indentations:
function A = cocktailShakerSort(A)
% `beginIdx` and `endIdx` marks the first and last index to check.
beginIdx = 1;
endIdx = length(A) - 1;
while beginIdx <= endIdx
newBeginIdx = endIdx;
newEndIdx = beginIdx;
for ii = beginIdx:endIdx
if A(ii) > A(ii + 1)
[A(ii+1), A(ii)] = deal(A(ii), A(ii+1));
newEndIdx = ii;
end
end
% decreases `endIdx` because the elements after `newEndIdx` are in correct order
endIdx = newEndIdx - 1;
% (FOR (below) decrements the II index by -1.
for ii = endIdx:-1:beginIdx
if A(ii) > A(ii + 1)
[A(ii+1), A(ii)] = deal(A(ii), A(ii+1));
newBeginIdx = ii;
end
end
% increases `beginIdx` because the elements before `newBeginIdx` are in correct order.
beginIdx = newBeginIdx + 1;
end
end
% indicates a comment, and deal indicates a swap.
Task
Implement a cocktail sort and optionally show the sorted output here on this page.
See the discussion page for some timing comparisons.
Related task
cocktail sort
| #Java | Java | import java.util.*;
public class CocktailSort {
public static void main(String[] args) {
Integer[] array = new Integer[]{ 5, 1, -6, 12, 3, 13, 2, 4, 0, 15 };
System.out.println("before: " + Arrays.toString(array));
cocktailSort(array);
System.out.println("after: " + Arrays.toString(array));
}
// Sorts an array of elements that implement the Comparable interface
public static void cocktailSort(Object[] array) {
int begin = 0;
int end = array.length;
if (end == 0)
return;
for (--end; begin < end; ) {
int new_begin = end;
int new_end = begin;
for (int i = begin; i < end; ++i) {
Comparable c1 = (Comparable)array[i];
Comparable c2 = (Comparable)array[i + 1];
if (c1.compareTo(c2) > 0) {
swap(array, i, i + 1);
new_end = i;
}
}
end = new_end;
for (int i = end; i > begin; --i) {
Comparable c1 = (Comparable)array[i - 1];
Comparable c2 = (Comparable)array[i];
if (c1.compareTo(c2) > 0) {
swap(array, i, i - 1);
new_begin = i;
}
}
begin = new_begin;
}
}
private static void swap(Object[] array, int i, int j) {
Object tmp = array[i];
array[i] = array[j];
array[j] = tmp;
}
} |
http://rosettacode.org/wiki/Sorting_algorithms/Insertion_sort | Sorting algorithms/Insertion sort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Insertion sort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
An O(n2) sorting algorithm which moves elements one at a time into the correct position.
The algorithm consists of inserting one element at a time into the previously sorted part of the array, moving higher ranked elements up as necessary.
To start off, the first (or smallest, or any arbitrary) element of the unsorted array is considered to be the sorted part.
Although insertion sort is an O(n2) algorithm, its simplicity, low overhead, good locality of reference and efficiency make it a good choice in two cases:
small n,
as the final finishing-off algorithm for O(n logn) algorithms such as mergesort and quicksort.
The algorithm is as follows (from wikipedia):
function insertionSort(array A)
for i from 1 to length[A]-1 do
value := A[i]
j := i-1
while j >= 0 and A[j] > value do
A[j+1] := A[j]
j := j-1
done
A[j+1] = value
done
Writing the algorithm for integers will suffice.
| #REBOL | REBOL |
; This program works with REBOL version R2 and R3, to make it work with Red
; change the word func to function
insertion-sort: func [
a [block!]
/local i [integer!] j [integer!] n [integer!]
value [integer! string! date!]
][
i: 2
n: length? a
while [i <= n][
value: a/:i
j: i
while [ all [ 1 < j
value < a/(j - 1) ]][
a/:j: a/(j - 1)
j: j - 1
]
a/:j: value
i: i + 1
]
a
]
probe insertion-sort [4 2 1 6 9 3 8 7]
probe insertion-sort [ "---Monday's Child Is Fair of Face (by Mother Goose)---"
"Monday's child is fair of face;"
"Tuesday's child is full of grace;"
"Wednesday's child is full of woe;"
"Thursday's child has far to go;"
"Friday's child is loving and giving;"
"Saturday's child works hard for a living;"
"But the child that is born on the Sabbath day"
"Is blithe and bonny, good and gay."]
; just by adding the date! type to the local variable value the same function can sort dates.
probe insertion-sort [12-Jan-2015 11-Jan-2015 11-Jan-2016 12-Jan-2014]
|
http://rosettacode.org/wiki/Sorting_algorithms/Merge_sort | Sorting algorithms/Merge sort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
The merge sort is a recursive sort of order n*log(n).
It is notable for having a worst case and average complexity of O(n*log(n)), and a best case complexity of O(n) (for pre-sorted input).
The basic idea is to split the collection into smaller groups by halving it until the groups only have one element or no elements (which are both entirely sorted groups).
Then merge the groups back together so that their elements are in order.
This is how the algorithm gets its divide and conquer description.
Task
Write a function to sort a collection of integers using the merge sort.
The merge sort algorithm comes in two parts:
a sort function and
a merge function
The functions in pseudocode look like this:
function mergesort(m)
var list left, right, result
if length(m) ≤ 1
return m
else
var middle = length(m) / 2
for each x in m up to middle - 1
add x to left
for each x in m at and after middle
add x to right
left = mergesort(left)
right = mergesort(right)
if last(left) ≤ first(right)
append right to left
return left
result = merge(left, right)
return result
function merge(left,right)
var list result
while length(left) > 0 and length(right) > 0
if first(left) ≤ first(right)
append first(left) to result
left = rest(left)
else
append first(right) to result
right = rest(right)
if length(left) > 0
append rest(left) to result
if length(right) > 0
append rest(right) to result
return result
See also
the Wikipedia entry: merge sort
Note: better performance can be expected if, rather than recursing until length(m) ≤ 1, an insertion sort is used for length(m) smaller than some threshold larger than 1. However, this complicates the example code, so it is not shown here.
| #REXX | REXX | /*REXX pgm sorts a stemmed array (numbers and/or chars) using the merge─sort algorithm.*/
call init /*sinfully initialize the @ array. */
call show 'before sort' /*show the "before" array elements. */
say copies('▒', 75) /*display a separator line to the term.*/
call merge # /*invoke the merge sort for the array*/
call show ' after sort' /*show the "after" array elements. */
exit 0 /*stick a fork in it, we're all done. */
/*──────────────────────────────────────────────────────────────────────────────────────*/
init: @.=; @.1= '---The seven deadly sins---' ; @.4= "avarice" ; @.7= 'gluttony'
@.2= '===========================' ; @.5= "wrath" ; @.8= 'sloth'
@.3= 'pride' ; @.6= "envy" ; @.9= 'lust'
do #=1 until @.#==''; end; #= #-1; return /*#: # of entries in @ array.*/
/*──────────────────────────────────────────────────────────────────────────────────────*/
show: do j=1 for #; say right('element',20) right(j,length(#)) arg(1)":" @.j; end; return
/*──────────────────────────────────────────────────────────────────────────────────────*/
merge: procedure expose @. !.; parse arg n, L; if L=='' then do; !.=; L= 1; end
if n==1 then return; h= L + 1
if n==2 then do; if @.L>@.h then do; [email protected]; @[email protected]; @.L=_; end; return; end
m= n % 2 /* [↑] handle case of two items.*/
call merge n-m, L+m /*divide items to the left ···*/
call merger m, L, 1 /* " " " " right ···*/
i= 1; j= L + m
do k=L while k<j /*whilst items on right exist ···*/
if j==L+n | !.i<[email protected] then do; @.k= !.i; i= i + 1; end
else do; @.k= @.j; j= j + 1; end
end /*k*/
return
/*──────────────────────────────────────────────────────────────────────────────────────*/
merger: procedure expose @. !.; parse arg n,L,T
if n==1 then do; !.T= @.L; return; end
if n==2 then do; h= L + 1; q= T + 1; !.q= @.L; !.T= @.h; return; end
m= n % 2 /* [↑] handle case of two items.*/
call merge m, L /*divide items to the left ···*/
call merger n-m, L+m, m+T /* " " " " right ···*/
i= L; j= m + T
do k=T while k<j /*whilst items on left exist ···*/
if j==T+n | @.i<=!.j then do; !.k= @.i; i= i + 1; end
else do; !.k= !.j; j= j + 1; end
end /*k*/
return |
http://rosettacode.org/wiki/Sorting_algorithms/Quicksort | Sorting algorithms/Quicksort |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Quicksort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
Task
Sort an array (or list) elements using the quicksort algorithm.
The elements must have a strict weak order and the index of the array can be of any discrete type.
For languages where this is not possible, sort an array of integers.
Quicksort, also known as partition-exchange sort, uses these steps.
Choose any element of the array to be the pivot.
Divide all other elements (except the pivot) into two partitions.
All elements less than the pivot must be in the first partition.
All elements greater than the pivot must be in the second partition.
Use recursion to sort both partitions.
Join the first sorted partition, the pivot, and the second sorted partition.
The best pivot creates partitions of equal length (or lengths differing by 1).
The worst pivot creates an empty partition (for example, if the pivot is the first or last element of a sorted array).
The run-time of Quicksort ranges from O(n log n) with the best pivots, to O(n2) with the worst pivots, where n is the number of elements in the array.
This is a simple quicksort algorithm, adapted from Wikipedia.
function quicksort(array)
less, equal, greater := three empty arrays
if length(array) > 1
pivot := select any element of array
for each x in array
if x < pivot then add x to less
if x = pivot then add x to equal
if x > pivot then add x to greater
quicksort(less)
quicksort(greater)
array := concatenate(less, equal, greater)
A better quicksort algorithm works in place, by swapping elements within the array, to avoid the memory allocation of more arrays.
function quicksort(array)
if length(array) > 1
pivot := select any element of array
left := first index of array
right := last index of array
while left ≤ right
while array[left] < pivot
left := left + 1
while array[right] > pivot
right := right - 1
if left ≤ right
swap array[left] with array[right]
left := left + 1
right := right - 1
quicksort(array from first index to right)
quicksort(array from left to last index)
Quicksort has a reputation as the fastest sort. Optimized variants of quicksort are common features of many languages and libraries. One often contrasts quicksort with merge sort, because both sorts have an average time of O(n log n).
"On average, mergesort does fewer comparisons than quicksort, so it may be better when complicated comparison routines are used. Mergesort also takes advantage of pre-existing order, so it would be favored for using sort() to merge several sorted arrays. On the other hand, quicksort is often faster for small arrays, and on arrays of a few distinct values, repeated many times." — http://perldoc.perl.org/sort.html
Quicksort is at one end of the spectrum of divide-and-conquer algorithms, with merge sort at the opposite end.
Quicksort is a conquer-then-divide algorithm, which does most of the work during the partitioning and the recursive calls. The subsequent reassembly of the sorted partitions involves trivial effort.
Merge sort is a divide-then-conquer algorithm. The partioning happens in a trivial way, by splitting the input array in half. Most of the work happens during the recursive calls and the merge phase.
With quicksort, every element in the first partition is less than or equal to every element in the second partition. Therefore, the merge phase of quicksort is so trivial that it needs no mention!
This task has not specified whether to allocate new arrays, or sort in place. This task also has not specified how to choose the pivot element. (Common ways to are to choose the first element, the middle element, or the median of three elements.) Thus there is a variety among the following implementations.
| #PL.2FI | PL/I | DCL (T(20)) FIXED BIN(31); /* scratch space of length N */
QUICKSORT: PROCEDURE (A,AMIN,AMAX,N) RECURSIVE ;
DECLARE (A(*)) FIXED BIN(31);
DECLARE (N,AMIN,AMAX) FIXED BIN(31) NONASGN;
DECLARE (I,J,IA,IB,IC,PIV) FIXED BIN(31);
DECLARE (P,Q) POINTER;
DECLARE (AP(1)) FIXED BIN(31) BASED(P);
IF(N <= 1)THEN RETURN;
IA=0; IB=0; IC=N+1;
PIV=(AMIN+AMAX)/2;
DO I=1 TO N;
IF(A(I) < PIV)THEN DO;
IA+=1; A(IA)=A(I);
END; ELSE IF(A(I) > PIV) THEN DO;
IC-=1; T(IC)=A(I);
END; ELSE DO;
IB+=1; T(IB)=A(I);
END;
END;
DO I=1 TO IB; A(I+IA)=T(I); END;
DO I=IC TO N; A(I)=T(N+IC-I); END;
P=ADDR(A(IC));
IC=N+1-IC;
IF(IA > 1) THEN CALL QUICKSORT(A, AMIN, PIV-1,IA);
IF(IC > 1) THEN CALL QUICKSORT(AP,PIV+1,AMAX, IC);
RETURN;
END QUICKSORT;
MINMAX: PROC(A,AMIN,AMAX,N);
DCL (AMIN,AMAX) FIXED BIN(31),
(N,A(*)) FIXED BIN(31) NONASGN ;
DCL (I,X,Y) FIXED BIN(31);
AMIN=A(N); AMAX=AMIN;
DO I=1 TO N-1;
X=A(I); Y=A(I+1);
IF (X < Y)THEN DO;
IF (X < AMIN) THEN AMIN=X;
IF (Y > AMAX) THEN AMAX=Y;
END; ELSE DO;
IF (X > AMAX) THEN AMAX=X;
IF (Y < AMIN) THEN AMIN=Y;
END;
END;
RETURN;
END MINMAX;
CALL MINMAX(A,AMIN,AMAX,N);
CALL QUICKSORT(A,AMIN,AMAX,N); |
http://rosettacode.org/wiki/Sorting_algorithms/Cocktail_sort_with_shifting_bounds | Sorting algorithms/Cocktail sort with shifting bounds |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Cocktail sort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
The cocktail sort is an improvement on the Bubble Sort.
A cocktail sort is also known as:
cocktail shaker sort
happy hour sort
bidirectional bubble sort
a bubble sort variation
a selection sort variation
ripple sort
shuffle sort
shuttle sort
The improvement is basically that values "bubble" (migrate) both directions through the
array, because on each iteration the cocktail sort bubble sorts once
forwards and once backwards.
After ii passes, the first ii and the
last ii elements in the array are in their correct
positions, and don't have to be checked (again).
By shortening the part of the array that is sorted each time, the number of
comparisons can be halved.
Pseudocode for the 2nd algorithm (from
Wikipedia) with an added comment and changed indentations:
function A = cocktailShakerSort(A)
% `beginIdx` and `endIdx` marks the first and last index to check.
beginIdx = 1;
endIdx = length(A) - 1;
while beginIdx <= endIdx
newBeginIdx = endIdx;
newEndIdx = beginIdx;
for ii = beginIdx:endIdx
if A(ii) > A(ii + 1)
[A(ii+1), A(ii)] = deal(A(ii), A(ii+1));
newEndIdx = ii;
end
end
% decreases `endIdx` because the elements after `newEndIdx` are in correct order
endIdx = newEndIdx - 1;
% (FOR (below) decrements the II index by -1.
for ii = endIdx:-1:beginIdx
if A(ii) > A(ii + 1)
[A(ii+1), A(ii)] = deal(A(ii), A(ii+1));
newBeginIdx = ii;
end
end
% increases `beginIdx` because the elements before `newBeginIdx` are in correct order.
beginIdx = newBeginIdx + 1;
end
end
% indicates a comment, and deal indicates a swap.
Task
Implement a cocktail sort and optionally show the sorted output here on this page.
See the discussion page for some timing comparisons.
Related task
cocktail sort
| #Julia | Julia | module CocktailShakerSorts
using Base.Order, Base.Sort
import Base.Sort: sort!
export CocktailShakerSort
struct CocktailSortAlg <: Algorithm end
const CocktailShakerSort = CocktailSortAlg()
function sort!(A::AbstractVector, lo::Int, hi::Int, a::CocktailSortAlg, ord::Ordering)
if lo > 1 || hi < length(A)
return sort!(view(A, lo:hi), 1, length(A), a, ord)
end
forward, beginindex, endindex = ord isa ForwardOrdering, 1, length(A) - 1
while beginindex <= endindex
newbegin, newend = endindex, beginindex
for idx in beginindex:endindex
if (forward && A[idx] > A[idx + 1]) || (!forward && A[idx] < A[idx + 1])
A[idx + 1], A[idx] = A[idx], A[idx + 1]
newend = idx
end
end
# end has another in correct place, so narrow end by 1
endindex = newend - 1
for idx in endindex:-1:beginindex
if (forward && A[idx] > A[idx + 1]) || (!forward && A[idx] < A[idx + 1])
A[idx + 1], A[idx] = A[idx], A[idx + 1]
newbegin = idx
end
end
# beginning has another in correct place, so narrow beginning by 1
beginindex = newbegin + 1
end
A
end
end # module
using .CocktailShakerSorts
using BenchmarkTools
cocktailshakersort!(v) = sort!(v; alg=CocktailShakerSort)
arr = [5, 8, 2, 0, 6, 1, 9, 3, 4]
println(arr, " => ", sort(arr, alg=CocktailShakerSort), " => ",
sort(arr, alg=CocktailShakerSort, rev=true))
println("\nUsing default sort, which is Quicksort with integers:")
@btime sort!([5, 8, 2, 0, 6, 1, 9, 3, 4])
println("\nUsing CocktailShakerSort:")
@btime cocktailshakersort!([5, 8, 2, 0, 6, 1, 9, 3, 4])
|
http://rosettacode.org/wiki/Sorting_algorithms/Cocktail_sort_with_shifting_bounds | Sorting algorithms/Cocktail sort with shifting bounds |
Sorting Algorithm
This is a sorting algorithm. It may be applied to a set of data in order to sort it.
For comparing various sorts, see compare sorts.
For other sorting algorithms, see sorting algorithms, or:
O(n logn) sorts
Heap sort |
Merge sort |
Patience sort |
Quick sort
O(n log2n) sorts
Shell Sort
O(n2) sorts
Bubble sort |
Cocktail sort |
Cocktail sort with shifting bounds |
Comb sort |
Cycle sort |
Gnome sort |
Insertion sort |
Selection sort |
Strand sort
other sorts
Bead sort |
Bogo sort |
Common sorted list |
Composite structures sort |
Custom comparator sort |
Counting sort |
Disjoint sublist sort |
External sort |
Jort sort |
Lexicographical sort |
Natural sorting |
Order by pair comparisons |
Order disjoint list items |
Order two numerical lists |
Object identifier (OID) sort |
Pancake sort |
Quickselect |
Permutation sort |
Radix sort |
Ranking methods |
Remove duplicate elements |
Sleep sort |
Stooge sort |
[Sort letters of a string] |
Three variable sort |
Topological sort |
Tree sort
This page uses content from Wikipedia. The original article was at Cocktail sort. The list of authors can be seen in the page history. As with Rosetta Code, the text of Wikipedia is available under the GNU FDL. (See links for details on variance)
The cocktail sort is an improvement on the Bubble Sort.
A cocktail sort is also known as:
cocktail shaker sort
happy hour sort
bidirectional bubble sort
a bubble sort variation
a selection sort variation
ripple sort
shuffle sort
shuttle sort
The improvement is basically that values "bubble" (migrate) both directions through the
array, because on each iteration the cocktail sort bubble sorts once
forwards and once backwards.
After ii passes, the first ii and the
last ii elements in the array are in their correct
positions, and don't have to be checked (again).
By shortening the part of the array that is sorted each time, the number of
comparisons can be halved.
Pseudocode for the 2nd algorithm (from
Wikipedia) with an added comment and changed indentations:
function A = cocktailShakerSort(A)
% `beginIdx` and `endIdx` marks the first and last index to check.
beginIdx = 1;
endIdx = length(A) - 1;
while beginIdx <= endIdx
newBeginIdx = endIdx;
newEndIdx = beginIdx;
for ii = beginIdx:endIdx
if A(ii) > A(ii + 1)
[A(ii+1), A(ii)] = deal(A(ii), A(ii+1));
newEndIdx = ii;
end
end
% decreases `endIdx` because the elements after `newEndIdx` are in correct order
endIdx = newEndIdx - 1;
% (FOR (below) decrements the II index by -1.
for ii = endIdx:-1:beginIdx
if A(ii) > A(ii + 1)
[A(ii+1), A(ii)] = deal(A(ii), A(ii+1));
newBeginIdx = ii;
end
end
% increases `beginIdx` because the elements before `newBeginIdx` are in correct order.
beginIdx = newBeginIdx + 1;
end
end
% indicates a comment, and deal indicates a swap.
Task
Implement a cocktail sort and optionally show the sorted output here on this page.
See the discussion page for some timing comparisons.
Related task
cocktail sort
| #Kotlin | Kotlin | fun <T> swap(array: Array<T>, i: Int, j: Int) {
val temp = array[i]
array[i] = array[j]
array[j] = temp
}
fun <T> cocktailSort(array: Array<T>) where T : Comparable<T> {
var begin = 0
var end = array.size
if (end == 0) {
return
}
--end
while (begin < end) {
var newBegin = end
var newEnd = begin
for (i in begin until end) {
val c1 = array[i]
val c2 = array[i + 1]
if (c1 > c2) {
swap(array, i, i + 1)
newEnd = i
}
}
end = newEnd
for (i in end downTo begin + 1) {
val c1 = array[i - 1]
val c2 = array[i]
if (c1 > c2) {
swap(array, i, i - 1)
newBegin = i
}
}
begin = newBegin
}
}
fun main() {
val array: Array<Int> = intArrayOf(5, 1, -6, 12, 3, 13, 2, 4, 0, 15).toList().toTypedArray()
println("before: ${array.contentToString()}")
cocktailSort(array)
println("after: ${array.contentToString()}")
} |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.