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Description: 常用的线性数据结构: 包括线性表、环形列表、队列、双端队列、单链表、双端链表、堆、栈、字符串数组等。非常有用，值得参考。-commonly used linear data structure : Table includes linear and circular table, queue, queue-end, single-linked list, double-linked list, heap, stack, as a string array. Very useful and valuable reference.
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Size: 40431 |
Author: 许友来 |
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Description: 这是我刚刚学习C#时候编写的连连看小游戏,现在看来已经有点简单了.它的实现方式是控件数组,也就是声明了一堆Label.现在拿出来供后来者学习-just learning C# 1000 block of Terry Avenue when prepared by the small game, it now appears a bit simple. It is the way to achieve the control array is a heap of Label statement. Now up for later learning
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Size: 11391 |
Author: 中子豆 |
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Description: 通过堆（heap）排序法对关键字成员为实数的结构体一维数组进行排序计算和数值模拟。-through the reactor (heap) the keyword method of ranking members of the real structure of the one-dimensional array by calculated and Numerical simulation.
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Size: 1506 |
Author: lsx |
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Description: 1）实现以下常用的内部排序算法并对它们的时间效率进行比较：
必做（6种）：起泡排序、直接插入排序、简单选择排序、快速排序、希尔排序、堆排序；
选做：折半插入、二路归并、基数排序等等；
2）函数首部要求：void XXXXSort(char **list, int len, int n, int *c, int *s)
其中：
a) XXXXSort为排序函数名，具体如下：
起泡排序BubbleSort
直接插入排序InsertSort
简单选择排序SelectSort
快速排序QuickSort
希尔排序ShellSort
堆排序HeapSort
折半插入BInsertSort
二路归并Merge2Sort
基数排序RadixSort
b) list为二维字符数组的头指针，该二维数组的规格为：char list[n][len] 每行用于存放一个字符串（最大长度为len-1），共n行；
c) c用于返回关键字比较次数；
d) s用于返回移动次数；
3）要求把各种排序函数做成函数库（文件名统一为：sort.c），用统一提供的主程序进行调用和测评。
-a) achieve the following commonly used internal sorting algorithm as well as their time efficiency comparison : regimen (6) : bubble sort, direct insertion sequence and simple choice sorting, quick sort, Hill, ranked Heap Sort; elected to do : half of insertion, two-way merge. Sort base, and so on; 2) function first requirement : void XXXXSort (char ** list, int len, int n, int * c, int * s) which : a) XXXXSort sort of a function name, as follows : bubble sort BubbleSort direct insertion sort InsertSort simple choice ranking Sele ctSort Quick Sort QuickSort Hill Sorting ShellSort Heap Sort HeapS ort half insert BInsertSort two-way merge Merge2Sort radix sort Radi xSort b) list for the two-dimensional array of characters in the first indicator, the two-dimensional array specifications : cha
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Size: 10289 |
Author: 战天 |
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Description: 迄今为止见过的最方便的huffman编码，效率很高
一个外国人写的，很具有研究价值
Constructing a Huffman Tree according to the number of times each symbol appears in the data stream:
1) Create an array of N nodes, representing N possible symbols (ranging between 0 and N-1).
2) Set the value of each node to the number of times that its symbol appears in the data stream.
3) Create a Minimum-Heap of N nodes.
4) Add every node whose value is greater than zero to the heap.
5) Extract the best two nodes in the heap.
6) Create a parent node whose children are the two extracted nodes.
7) Add the parent node to the heap.
8) Repeat the previous three steps N-1 times (until only 1 node remains in the heap).
9) Extract the last node in the heap.
The array created in the first step stores the leaves of the tree, and is used in order to encode the data stream.
The node extracted in the last step is in fact the root of the tree, and is used in order to decode the data stream.
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Size: 17786 |
Author: 游弋人生 |
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Description: 常用的线性数据结构: 包括线性表、环形列表、队列、双端队列、单链表、双端链表、堆、栈、字符串数组等。非常有用，值得参考。-commonly used linear data structure : Table includes linear and circular table, queue, queue-end, single-linked list, double-linked list, heap, stack, as a string array. Very useful and valuable reference.
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Size: 39936 |
Author: 许友来 |
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Description: 堆排列实现的方法，可以作为简单的堆排列模块使用-Heap with the realization of the method can be used as a simple heap array module using
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Size: 1024 |
Author: 张秦龙 |
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Description: 迄今为止见过的最方便的huffman编码，效率很高
一个外国人写的，很具有研究价值
Constructing a Huffman Tree according to the number of times each symbol appears in the data stream:
1) Create an array of N nodes, representing N possible symbols (ranging between 0 and N-1).
2) Set the value of each node to the number of times that its symbol appears in the data stream.
3) Create a Minimum-Heap of N nodes.
4) Add every node whose value is greater than zero to the heap.
5) Extract the best two nodes in the heap.
6) Create a parent node whose children are the two extracted nodes.
7) Add the parent node to the heap.
8) Repeat the previous three steps N-1 times (until only 1 node remains in the heap).
9) Extract the last node in the heap.
The array created in the first step stores the leaves of the tree, and is used in order to encode the data stream.
The node extracted in the last step is in fact the root of the tree, and is used in order to decode the data stream.-So far seen the most convenient huffman coding, efficient write a foreigner, I have research value Constructing a Huffman Tree according to the number of times each symbol appears in the data stream: 1) Create an array of N nodes , representing N possible symbols (ranging between 0 and N-1) .2) Set the value of each node to the number of times that its symbol appears in the data stream.3) Create a Minimum-Heap of N nodes.4) Add every node whose value is greater than zero to the heap.5) Extract the best two nodes in the heap.6) Create a parent node whose children are the two extracted nodes.7) Add the parent node to the heap.8) Repeat the previous three steps N-1 times (until only 1 node remains in the heap) .9) Extract the last node in the heap.The array created in the first step stores the leaves of the tree, and is used in order to encode the data stream.The node extracted in the last step is in fact the root of the tree, and is used in order to decode the data stream.
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Size: 17408 |
Author: 游弋人生 |
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Description: Heapsort
1.A heap is a binary tree satisfying the followingconditions:
-This tree is completely balanced.
-If the height of this binary tree is h, then leaves can be at level h or level h-1.
-All leaves at level h are as far to the left as possible.
-The data associated with all descendants of a node are smaller than the datum associated with this node.
Implementation
1.using a linear array not a binary tree.
-The sons of A(h) are A(2h) and A(2h+1).
2.time complexity: O(n log n)
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Size: 196608 |
Author: 黃文岩 |
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Description: circular queue by heap array
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Size: 1024 |
Author: kellyjo |
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Description: stack by heap array
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Size: 1024 |
Author: kellyjo |
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Description: multiplication of matrix by heap array
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Size: 149504 |
Author: kellyjo |
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Description: 5种不同的排序方法，marge排序,基数排序，交换排序，快速排序,heap排序,另外还包括基数排序字母.测试包括,随机和手动,随机测试的是5种排序的时间,和不同大小的数组,都分别排序两边,一边是排序无顺序的数字,第2边是排序已经有顺序的数字,来测试排序的时间，手动就是自己输入数字来进行排序-5 different ranking methods, marge sort, radix sort, exchange sort, quick sort, heap sort, radix sort the letter also included. Testing, including random and manual, random testing is the five kinds of sorting time, and different sizes array, were all sort on both sides, one side is the number of unordered sort, 2 side is the order of the figures have been sorted, to test the sorting of the time, manual input was their number to be sorted
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Size: 13312 |
Author: lai ni |
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Description: 堆的基本操作，插入删除，把数组变为小根堆，并检查是否为小根堆，用小根堆排序的方法按降序对大小为n的数组进行排序。-The basic operation of the heap, insert delete the array into a heap of small roots, and check the heap for small roots, roots with a small heap sort in descending order by means of an array of size n sort.
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Size: 1024 |
Author: 依枫 |
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Description: 堆积排序(Heapsort)是指利用堆积树（堆）这种资料结构所设计的一种排序算法，可以利用数组的特点快速定位指定索引的元素。
-Heap sort (Heapsort) is the use of stacked tree (heap) data structure designed such a sorting algorithm can take advantage of the characteristics of the array elements quickly locate the specified index.
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Size: 1024 |
Author: mfeng |
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Description: A simple priority queue, array priority queue, and a binary heap. Used for implementation with databases written in java.
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Size: 4096 |
Author: ptf4u07 |
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Description: 这个代码包含了简单的堆操作，包括堆的保持，键堆，以及利用堆这个数据结构排序, IDE为苹果的Xcode-this code show the heap related operation, include keeping a heap, building a heap, using heap to sort an array. The IDE is Xcode on Apple Mac
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Size: 321536 |
Author: zhangjing |
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Description: The heapsort algorithm can be divided into two parts.
In the first step, a heap is built out of the data.
In the second step, a sorted array is created by repeatedly removing the largest element from the heap, and inserting it into the array. The heap is reconstructed after each removal. Once all objects have been removed from the heap, we have a sorted array. The direction of the sorted elements can be varied by choosing a min-heap or max-heap in step one.
Heapsort can be performed in place. The array can be split into two parts, the sorted array and the heap.The heap s invariant is preserved after each extraction, so the only cost is that of extraction.
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Size: 6144 |
Author: subodh |
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Description: It s required to design an Abstract Data Type (ADT) Java implementation for the
Heap Trees data structure that includes the following operations:
1. Constructor and display operations
2. Creating a Heap Tree a given array
3. Adding an element to the Heap Tree
4. Deleting an Element the Heap Tree
5. Sorting the array of elements using the Heap sort algorithm -It s required to design an Abstract Data Type (ADT) Java implementation for the
Heap Trees data structure that includes the following operations:
1. Constructor and display operations
2. Creating a Heap Tree a given array
3. Adding an element to the Heap Tree
4. Deleting an Element the Heap Tree
5. Sorting the array of elements using the Heap sort algorithm
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Size: 8192 |
Author: tamer |
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Description: 这里需要做一个假设：对于数组中下标为i的节点其左子树和右子树都是保持最大堆性质的堆。在假设成立的前提上，经过这一个维护函数维护过的堆才能够保证是一个最大堆。(There is a hypothesis that the left subtree and the right subtree of the node with the subscript of I in the array are the heaps that maintain the maximum heap properties. On the premise of assumption, the heap that has been maintained through this maintenance function can be guaranteed to be the largest heap.)
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Size: 1024 |
Author: hope17 |
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