Explore a world of data structures in Swift. Learn how to use data structures to organize, analyze, and manipulate data.
- iOS 8.0+ / Mac OS X 10.9+
- Xcode 7.2+
- If you need help, use Stack Overflow. (Tag 'cosmicmind')
- If you'd like to ask a general question, use Stack Overflow.
- If you found a bug, and can provide steps to reliably reproduce it, open an issue.
- If you have a feature request, open an issue.
- If you want to contribute, submit a pull request.
Embedded frameworks require a minimum deployment target of iOS 8 or OS X Mavericks (10.9).
Visit the Installation page to learn how to install Algorithm using CocoaPods and Carthage.
Algorithm is a growing project and will encounter changes throughout its development. It is recommended that the Changelog be reviewed prior to updating versions.
- Probability
- DoublyLinkedList
- Stack
- Queue
- Deque
- RedBlackTree
- SortedSet
- SortedMultiSet
- SortedDictionary
- SortedMultiDictionary
Probability is a core feature. Your application may be completely catered to your users' habits and usage. To demonstrate this wonderful feature, let's look at some examples:
Determining the probability of rolling a 3 using a die of 6 numbers.
let die: Array<Int> = Array<Int>(arrayLiteral: 1, 2, 3, 4, 5, 6)
print(die.probabilityOf(3)) // Output: 0.166666666666667The expected value of rolling a 3 or 6 with 100 trials using a die of 6 numbers.
let die: Array<Int> = Array<Int>(arrayLiteral: 1, 2, 3, 4, 5, 6)
print(die.expectedValueOf(100, elements: 3, 6)) // Output: 33.3333333333333The above examples are quite simple. They use basic calculations to determine the probability of an outcome (X). What if you have a complicated condition? To solve this problem, it is possible to pass in blocks that return a boolean value. Each block may execute any operations it pleases, so long as it returns a "true" or "false". The "true" values contribute to the likelihood of an outcome, "false" results do not. Below is an example to demonstrate this feature.
let die: Array<Int> = Array<Int>(arrayLiteral: 1, 2, 3, 4, 5, 6)
let probabilityOfX: Double = die.probabilityOf { (number: Int) in
if 5 < number || 0 == number % 3 {
// Do more.
return true
}
return false
}
if 0.33 < probabilityOfX {
// Do something.
}The DoublyLinkedList data structure is excellent for large growing collections of data. Below is an example of its usage.
let listA: DoublyLinkedList<Int> = DoublyLinkedList<Int>()
listA.insertAtFront(3)
listA.insertAtFront(2)
listA.insertAtFront(1)
let listB: DoublyLinkedList<Int> = DoublyLinkedList<Int>()
listB.insertAtBack(4)
listB.insertAtBack(5)
listB.insertAtBack(6)
let listC: DoublyLinkedList<Int> = listA + listB
listC.cursorToFront()
repeat {
print(listC.cursor)
} while nil != listC.next
// Output:
// 1
// 2
// 3
// 4
// 5
// 6The Stack data structure is a container of objects that are inserted and removed according to the last-in-first-out (LIFO) principle. Below is an example of its usage.
let stack: Stack<Int> = Stack<Int>()
stack.push(1)
stack.push(2)
stack.push(3)
while !stack.isEmpty {
print(stack.pop())
}
// Output:
// 3
// 2
// 1The Queue data structure is a container of objects that are inserted and removed according to the first-in-first-out (FIFO) principle. Below is an example of its usage.
let queue: Queue<Int> = Queue<Int>()
queue.enqueue(1)
queue.enqueue(2)
queue.enqueue(3)
while !queue.isEmpty {
print(queue.dequeue())
}
// Output:
// 1
// 2
// 3The Deque data structure is a container of objects that are inserted and removed according to the first-in-first-out (FIFO) and last-in-first-out (LIFO) principle. Essentially, a Deque is a Stack and Queue combined. Below are examples of its usage.
let dequeA: Deque<Int> = Deque<Int>()
dequeA.insertAtBack(1)
dequeA.insertAtBack(2)
dequeA.insertAtBack(3)
while !dequeA.isEmpty {
print(dequeA.removeAtFront())
}
// Output:
// 1
// 2
// 3
let dequeB: Deque<Int> = Deque<Int>()
dequeB.insertAtBack(4)
dequeB.insertAtBack(5)
dequeB.insertAtBack(6)
while !dequeB.isEmpty {
print(dequeB.removeAtBack())
}
// Output:
// 6
// 5
// 4A RedBlackTree is a Balanced Binary Search Tree that maintains insert, remove, update, and search operations in a complexity of O(logn). The following implementation of a RedBlackTree also includes an order-statistic, which allows the data structure to be accessed using subscripts like an array or dictionary. RedBlackTrees may store unique keys or non-unique key values. Below is an example of its usage.
let rbA: RedBlackTree<Int, Int> = RedBlackTree<Int, Int>(uniqueKeys: true)
for var i: Int = 1000; 0 < i; --i {
rbA.insert(1, value: 1)
rbA.insert(2, value: 2)
rbA.insert(3, value: 3)
}
print(rbA.count) // Output: 3SortedSets are a powerful data structure for algorithm and analysis design. Elements within a SortedSet are unique and insert, remove, and search operations have a complexity of O(logn). The following implementation of a SortedSet also includes an order-statistic, which allows the data structure to be accessed using an index subscript like an array. Below are examples of its usage.
let setA: SortedSet<Int> = SortedSet<Int>(elements: 1, 2, 3) // Sorted: [1, 2, 3]
let setB: SortedSet<Int> = SortedSet<Int>(elements: 4, 3, 6) // Sorted: [3, 4, 6]
let setC: SortedSet<Int> = SortedSet<Int>(elements: 7, 1, 2) // Sorted: [1, 2, 7]
let setD: SortedSet<Int> = SortedSet<Int>(elements: 1, 7) // Sorted: [1, 7]
let setE: SortedSet<Int> = SortedSet<Int>(elements: 1, 6, 7) // Sorted: [1, 6, 7]
// Union.
print((setA + setB).count) // Output: 5
print(setA.union(setB).count) // Output: 5
// Intersect.
print(setC.intersect(setD).count) // Output: 2
// Subset.
print(setD < setC) // true
print(setD.isSubsetOf(setC)) // true
// Superset.
print(setD > setC) // false
print(setD.isSupersetOf(setC)) // false
// Contains.
print(setE.contains(setA.first!)) // true
// Probability.
print(setE.probabilityOf(setA.first!, setA.last!)) // 0.333333333333333A SortedMultiSet is identical to a SortedSet, except that a SortedMultiSet allows non-unique elements. Look at SortedSet for examples of its usage.
A SortedDictionary is a powerful data structure that maintains a sorted set of keys with value pairs. Keys within a SortedDictionary are unique and insert, remove, update, and search operations have a complexity of O(logn).
A SortedMultiDictionary is identical to a SortedDictionary, except that a SortedMultiDictionary allows non-unique keys. Below is an example of its usage.
struct Student {
var name: String
}
let dict: SortedMultiDictionary<String, Student> = SortedMultiDictionary<String, Student>()
// Do something with an alphabetically SortedMultiDictionary of Student structs.
for student in students {
dict.insert(student.name, value: student)
}Copyright (C) 2015 - 2016, Daniel Dahan and CosmicMind, Inc. http://cosmicmind.io. All rights reserved.
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