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Data structures and algorithms (C # implementation) series --- AVLTree (II)
// --------------- Override --------------------
Public override void AttachKey (object _ obj)
{
If (! IsEmpty ())
Throw new Exception ("My: this node must be a empty tree node! ");
This. key = _ obj;
Data structures and algorithms (C # implementation) series --- tree (III)
Heavenkiller (original)
// Overwrite Object. Equals () --- reference type realization
Public override bool Equals (object _ obj)
{
If (_ obj = null)
Return false; // this cannot be null
If (! (This. GetType () = _ obj. GetType ()))
Return false; // The type is not equal.
Tree tmpObj = (Tre
1 Sequence decompression: through * to pass the match*a, B = somelist, First, *mid, last = Somelist, a, *b = Somelist2 using bidirectional queues: From collections import dequeQ = deque (maxlen=5) can be fixed lengthQ = deque () can also be any lengthcan be inserted and removed from both ends, append, Appendleft, pop, popleft3 finding the largest or smallest n elements: using heapq (heap queue)HEAPQ. nlargest (N, Alist) heapq. nsmallest (n, alist) is suitable when n is relatively smallYou can al
(e e);//replace element in collection * "9" void Add (e e);//At the previous position of the current index or the current Adds a new element to the collection at the back of the index position. *//whether or not to add new elements before or after the current index position depends on whether you are traversing sequentially or in reverse order * If it is {@link#next}, insert at the previous position of the current position *//if it is {@link#previous} to inser
Title: Define the Fibonacci sequence as follows:/0 N=0F (n) = 1 n=1\ f (n-1) +f (n-2) n=2Enter N to find the nth item of the sequence in the quickest way.#include Data structures and algorithms-string Fibonacci to find the nth item
Package Com.js.ai.modules.pointwall.testxfz;class ordarray{private long[] a;private int nelems;public OrdArray (int max ) {a=new long[max];nelems=0;} public int size () {return nelems;} Insert method public void Insert (Long value) {int j;for (j=0;j Data structures and algorithms: the dichotomy Demo
True
Second, collections. Ordereddict: Dictionary with OrderOrdereddict internally maintains a doubly linked list to record the order in which key values are inserted, update the key value does not affect the original order, insert key value is inserted at the end, so its memory consumption is twice times the normal dictionary ,From collections Import ORDEREDDICTD = Ordereddict () d[' a '] = 1d[' c '] = 3d[' b '] = 2print (d, D.items ())
Ordereddict (' A ', 1), (' C ', 3)
1. The principle of hill sorting2. Code implementationdefShell_sort (alist): N=Len (alist)#Initial StepGap = N/2 whileGap >0:#Insert Sort by step forIinchRange (Gap, N): J=I#Insert Sort whileJ>=gap andALIST[J-GAP] >Alist[j]: alist[j-GAP], alist[j] = alist[j], alist[j-Gap] J-=Gap#get a new step sizeGap = GAP/2alist= [54,26,93,17,77,31,44,55,20]shell_sort (alist)Print(alist)Attention:(1) Hill sort uses the idea of splitting up and merging, splitting apart3. Complexity of TimeOp
List operation code is small but more error-prone, is more suitable for the interview place.
Code implementation
/** * Source Name: Mylinklist.java * Date: 2014-09-05 * program function: Java list operation * Copyright: [emailprotected] * A2bgeek */import Java.util.Sta Ck;public class Mylinklist {class Linknode"Data structures and Algorithms" Java l
node is now
Point to the head of the now node's next pointer;
Set the now node to the head of the new rollover completion node header now;
Point to head now, and so on, the next pointer to the previous node of the now node.
3. Two points search common scenes
Finding a number in an ordered sequence;
For example, given an array of arr, determine if the integer m is in arr (Train of thought: Determine the size of the mid-to-m re
efficiency: In a merge sort, the maximum value of this secondary storage space is not more than N, so the spatial complexity of the merge algorithm is θ (n) in order to combine the sub-sequences to use additional storage space.Time efficiency: The merging algorithm is a typical divide-and-conquer algorithm with a time complexity of 0 (n log n). 3. Algorithm examplesMergesort.javaPackage Com.test.sort.merge;public class MergeSort {/** * @param args */public static void main (string[] args) {//TO
" definition of algorithmic time complexity"At the time of the algorithm analysis, the total number of executions of the statement T (N) is a function of the problem size n, which then analyzes the change of T (n) with N and determines the order of magnitude of T (N). The time complexity of the algorithm, which is the time measurement of the algorithm, is recorded as: T (n) = O (f (n)). It indicates that with the increase of the problem size n, the growth rate of the algorithm execution time is
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