"DynamicArray"(Data Structure)

"DynamicArray"

represents a dynamically extensible array where the elements are general expressions.

Details

• An extensible array is useful for continuously appending elements, as well as for efficient element extraction and updating.
•  CreateDataStructure[ "DynamicArray"] create a new empty "DynamicArray" CreateDataStructure[ "DynamicArray",elems] create a new "DynamicArray" containing elems Typed[x,"DynamicArray"] give x the type "DynamicArray"
• For a data structure of type "DynamicArray", the following operations can be used:
•  ds["Append",x] append x to ds time: O(1) ds["Copy"] return a copy of ds time: O(n) ds["Drop",i] drop the i part of ds time: O(n) ds["DropAll"] drop all the elements from ds time: O(n) ds["DropLast"] drop the last element of ds time: O(1) ds["Elements"] return a list of the elements of ds time: O(n) ds["EmptyQ"] True, if ds has no elements time: O(1) ds["Fold",fun,init] apply fun to the elements of ds, starting with init, accumulating a result time: O(n) ds["Insert",x,i ] insert x into ds at position i time: O(1) ds["JoinBack",elems ] join elems to the back of ds time: O(nelems) ds["Length"] the number of elements stored in ds time: O(1) ds["Part",i] give the i part of ds time: O(1) ds["SetPart",i,elem] update the i part of ds time: O(1) ds["SwapPart",i,j] swap the i and j parts of ds time: O(1) ds["Visualization"] return a visualization of ds time: O(n)
• The following functions are also supported:
•  dsi===dsj True, if dsi equals dsj ds["Part",i]=val set i element of ds to val FullForm[ds] full form of ds Information[ds] information about ds InputForm[ds] input form of ds Normal[ds] convert ds to a normal expression

Examples

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Basic Examples(2)

A new "DynamicArray" can be created with CreateDataStructure:

Elements can be appended:

Return the length:

Extract the first element:

Change an element:

The element has updated:

Return an expression version of ds:

It is fast to append:

A visualization of the data structure can be generated:

Sum all the elements:

Scope(1)

Information(1)

A new "DynamicArray" can be created with CreateDataStructure:

Information about the data structure ds:

Applications(11)

Reverse(1)

A simple function that carries out an in-place reverse of a "DynamicArray":

A sample data structure to use:

Reverse the elements:

Bubble Sort(1)

Bubble sort is a simple sorting algorithm that is easy to code but typically has poor performance:

A sample data structure to use:

Sort the elements:

The data structure is sorted in place:

Insertion Sort(1)

Insertion sort is a simple sorting algorithm that is easy to code and typically has poor performance for large arrays, but can be useful for small arrays:

A sample data structure to use:

Sort the elements:

The data structure is sorted in place:

Quicksort(1)

Quicksort is an efficient sorting algorithm. This basic implementation uses nested functions:

A sample data structure to use:

Sort the elements:

The data structure is sorted in place:

Merge Sort(1)

Merge sort is an efficient sorting algorithm. This is a simple implementation that uses a workspace:

A sample data structure to use:

Sort the elements:

The data structure is sorted in place:

Heapsort(1)

Heapsort is an efficient sorting algorithm that works in place by constructing a heap:

A sample data structure to use:

The elements are sorted in place:

Timsort(1)

Timsort is a hybrid and efficient sorting algorithm:

A sample data structure to use:

The elements are sorted in place:

Fisher–Yates Shuffle(1)

The FisherYates shuffle generates a random permutation of a finite sequence:

A sample array to use for the shuffle:

Apply the shuffle:

Palindrome(1)

An array is a palindrome if it is symmetric around the middle:

This is not a palindrome:

This is a palindrome:

Quickselect(1)

Quickselect is a selection algorithm related to the Quicksort algorithm. It returns the k smallest element in a list:

A sample data structure to use:

The third smallest element is 7:

Heap(1)

A heap is a tree-based data structure where the value stored at children is smaller than that stored in their parents (for a min heap). It is commonly used to implement a priority queue and typically implemented with an array rather than a tree.

The following converts an array into a heap:

A sample data structure to use:

This converts the array into a heap; it is hard to see the heap property:

This function generates a tree:

A visualization makes it easier to see the min heap property:

Properties & Relations(1)

"FixedArray"(1)

Many algorithms that work for "DynamicArray" also work for "FixedArray".