| Blog信息 |
|
blog名称:小鸟吹烟
日志总数:157
评论数量:424
留言数量:-1
访问次数:1257965
建立时间:2006年10月23日 |
| |
|
 [J2SE]排序
心得体会, 软件技术
tone 发表于 2007/3/6 13:53:31 |
|
protected void orderSort(List route) { //按分数排序 //此方法会自动将LIST中两个字段从头到未全部比较并排序,把rou2-rou1实现降序排列 Collections.sort(route,new Comparator(){ public int compare(Object arg0, Object arg1) { Route rou1=(Route)arg0; Route rou2=(Route)arg1; return ( rou2.getTotal().hashCode()-rou1.getTotal().hashCode() ); }} ); }
orderSort(route);//进行排序Iterator rouIt=route.iterator(); |
|
|
回复:排序
心得体会, 软件技术
tone发表评论于2007/3/6 14:29:14 |
| 冒泡排序法
package test;
public class BubbleSort {
public static void main(String[] args){
int []array = {4,3,5,1,2}; //声明一个整型数组，并初始化
String str = "这几个数的排序为:"; //声明一个String类型的变量str,并初始化
int temp; //声明一个整型变量
for(int j=array.length-1;j>0;j--) { //交换两个相邻的数
for(int i=0;i<j;i++){
if(array[i]>array[i+1]){
temp = array[i];
array[i] = array[i+1];
array[i+1] = temp;
}
}
}
System.out.println(str);
for(int serial = 0;serial < array.length;serial++){
System.out.println(array[serial]); //打印数组
}
}
}
以下为blog主人的回复：
|
|
|
回复:排序
心得体会, 软件技术
tone发表评论于2007/3/6 14:22:08 |
| 三种简单排序算法分别的冒泡法,选择排序法和插入法.
三种排序算法的最差运行效率都要达到O(n*n)
1冒泡排序法:
void bubbleSort(Type* arr,long len)/*bubble sort algorithm*/
{
long i=0,j=0;/*iterator value*/
assertF(arr!=NULL,"In bubble sort,arr is NULL\n");
for (i=len;i>1;i--)
for(j=0;j<i-1;j++)
if(arr[j]>arr[j+1])swapArrData(arr,j,j+1);
}
从数组的后面位置开始,如果发现有比前面一个位置处的数更小的元素,则把交换这两个数的位置,形成一个类似轻的气泡在水中上升的排序过程.
2插入排序法:
void insertSort(Type* arr,long len)/*InsertSort algorithm*/
{
long i=0,j=0;/*iterator value*/
Type tmpData;
assertF(arr!=NULL,"In InsertSort sort,arr is NULL\n");
for(i=1;i<len;i++)
{
j=i;
tmpData=arr[i];
while(tmpData<arr[j-1]&&j>0)
{
arr[j]=arr[j-1];
j--;
}
arr[j]=tmpData;
}
}
插入排序算法思路是:
假定这个数组的序是排好的,然后从头往后,如果有数比当前外层元素的值大,则将这个数的位置往后挪,直到当前外层元素的值大于或等于它前面的位置为止.这具算法在排完前k个数之后,可以保证a[1…k]是局部有序的,保证了插入过程的正确性.
3选择排序法:
void selectionSort(Type* arr,long len)
{
long i=0,j=0;/*iterator value*/
long maxPos;
assertF(arr!=NULL,"In InsertSort sort,arr is NULL\n");
for(i=len-1;i>=1;i--)
{
maxPos=i;
for(j=0;j<i;j++)
if(arr[maxPos]<arr[j])maxPos=j;
if(maxPos!=i)swapArrData(arr,maxPos,i);
}
}
选择排序法的第一层循环从起始元素开始选到倒数第二个元素,主要是在每次进入的第二层循环之前,将外层循环的下标赋值给临时变量,接下来的第二层循环中,如果发现有比这个最小位置处的元素更小的元素,则将那个更小的元素的下标赋给临时变量,最后,在二层循环退出后,如果临时变量改变,则说明,有比当前外层循环位置更小的元素,需要将这两个元素交换.
由于这三种算法相对简单,运行效率也比较低,在元素个数比较少的时候用一个问题也是不大的.但当要排序的元素个数>=10000时,基本已经失去的使用价值,在当前的主流机器上,
10000个元素时,排序的时间单位差不多是秒.(相对而言,)
而到了100000个元素的时候,排序的时间单位已经是分钟了,此时,快速排序的运行时间单位
仍是百分之一秒呢.
参:
http://blog.csdn.net/EmilMatthew/archive/2005/09/04/471018.aspx |
|
|
回复:排序
心得体会, 软件技术
tone发表评论于2007/3/6 14:11:07 |
| 堆结构的实现
包括最大值堆和最小值堆:
接口:
package org.rut.util.structure.heap;
/** * @author treeroot * @since 2006-1-31 * @version 1.0 */public interface Heap { /** * return the top element of the heap * @return top element */ Object get(); /** * remove the top element of the heap and return it * the heap must be fixed. * @return top element */ Object remove(); /** * reset the top element * @param obj the new top element */ void set(Object obj); /** * add a element to the heap. * if no comparator is set, the obj must be implments comparable interface * @param obj the element to be added */ void add(Object obj); /** * if the heap is empty return true; * @return true if heap is empty,else false */ boolean isEmpty(); /** * clear the heap */ void clear();}
package org.rut.util.structure.heap;
import java.util.Comparator;
/** * @author treeroot * @since 2006-1-31 * @version 1.0 */public abstract class AbstractHeap implements Heap {
private int size;
private Object[] queue = new Object[128];
private Comparator comp;
public AbstractHeap() { this(new Comparable[0]); }
public AbstractHeap(Comparable[] elements) { init(elements); }
public AbstractHeap(Comparator comp, Object[] elements) { this.comp = comp; if (this.comp == null) throw new IllegalArgumentException("compartor can't be null"); init(elements); }
private void init(Object[] elements) { for(int i=0;i<elements.length;i++) add(elements[i]); }
/* * (non-Javadoc) * * @see org.rut.util.structure.heap.Heap#get() */ public Object get() { return queue[1]; }
/* * (non-Javadoc) * * @see org.rut.util.structure.heap.Heap#remove() */ public Object remove() { Object ret = queue[1]; queue[1] = queue[size]; queue[size--] = null; // Drop extra reference to prevent memory leak fixDown(1); return ret; }
/* * (non-Javadoc) * * @see org.rut.util.structure.heap.Heap#set(java.lang.Object) */ public void set(Object obj) { check(obj); queue[1] = obj; fixDown(1); }
/* * (non-Javadoc) * * @see org.rut.util.structure.heap.Heap#add(java.lang.Object) */ public void add(Object obj) { check(obj); if (++size == queue.length) { Object[] newQueue = new Object[2 * queue.length]; System.arraycopy(queue, 0, newQueue, 0, size); queue = newQueue; } queue[size] = obj; fixUp(size); }
/* * (non-Javadoc) * * @see org.rut.util.structure.heap.Heap#isEmpty() */ public boolean isEmpty() { return size == 0; }
/* * (non-Javadoc) * * @see org.rut.util.structure.heap.Heap#clear() */ public void clear() { for (int i = 1; i <= size; i++) queue[i] = null; size = 0; } //check the type private void check(Object element) { if (this.comp == null) { if (!(element instanceof Comparable)) throw new IllegalArgumentException( "element must be Comparble when no Comparator is set"); } } //compare may be override by subclass protected int compare(int i,int j){ if(comp!=null) return comp.compare(queue[i],queue[j]); return ((Comparable)queue[i]).compareTo(queue[j]); } //fixup private void fixUp(int k) { while (k > 1) { int j = k >> 1; if (compare(j,k)<=0) break; Object tmp = queue[j]; queue[j] = queue[k]; queue[k] = tmp; k = j; } } //fixdown private void fixDown(int k) { int j; while ((j = k << 1) <= size) { if (j < size && compare(j,j+1)>0 ) j++; // j indexes smallest kid if (compare(k,j)<=0) //不用交换 break; Object tmp = queue[j]; queue[j] = queue[k]; queue[k] = tmp; k = j; } }
}
最大值堆:
package org.rut.util.structure.heap;
import java.util.Comparator;
/** * @author treeroot * @since 2006-1-31 * @version 1.0 */public class MaxHeap extends AbstractHeap implements Heap{ public MaxHeap() { super(); }
public MaxHeap(Comparable[] elements) { super(elements); }
public MaxHeap(Comparator comp, Object[] elements) { super(comp,elements); }
/* (non-Javadoc) * @see org.rut.util.structure.heap.AbstractHeap#compare(int, int) */ protected int compare(int i, int j) { return super.compare(j, i); //use compare(j,i) instead of -compare(i,j) }}
最小值堆(默认就是):
package org.rut.util.structure.heap;
import java.util.Comparator;
/** * @author treeroot * @since 2006-1-31 * @version 1.0 */public class MinHeap extends AbstractHeap implements Heap{ public MinHeap() { super(); }
public MinHeap(Comparable[] elements) { super(elements); }
public MinHeap(Comparator comp, Object[] elements) { super(comp,elements); } /* (non-Javadoc) * @see org.rut.util.structure.heap.AbstractHeap#compare(int, int) */ protected int compare(int i, int j) { return super.compare(i, j); }}
Trackback: http://tb.blog.csdn.net/TrackBack.aspx?PostId=631478 |
|
|
回复:排序
心得体会, 软件技术
tone发表评论于2007/3/6 14:08:13 |
| package org.rut.util.algorithm.support;
import org.rut.util.algorithm.SortUtil;/** * @author treeroot * @since 2006-2-2 * @version 1.0 */public class InsertSort implements SortUtil.Sort{
/* (non-Javadoc) * @see org.rut.util.algorithm.SortUtil.Sort#sort(int[]) */ public void sort(int[] data) { int temp; for(int i=1;i<data.length;i++){ for(int j=i;(j>0)&&(data[j]<data[j-1]);j--){ SortUtil.swap(data,j,j-1); } } }
}冒泡排序:
package org.rut.util.algorithm.support;
import org.rut.util.algorithm.SortUtil;
/** * @author treeroot * @since 2006-2-2 * @version 1.0 */public class BubbleSort implements SortUtil.Sort{
/* (non-Javadoc) * @see org.rut.util.algorithm.SortUtil.Sort#sort(int[]) */ public void sort(int[] data) { int temp; for(int i=0;i<data.length;i++){ for(int j=data.length-1;j>i;j--){ if(data[j]<data[j-1]){ SortUtil.swap(data,j,j-1); } } } }
}
选择排序:
package org.rut.util.algorithm.support;
import org.rut.util.algorithm.SortUtil;
/** * @author treeroot * @since 2006-2-2 * @version 1.0 */public class SelectionSort implements SortUtil.Sort {
/* * (non-Javadoc) * * @see org.rut.util.algorithm.SortUtil.Sort#sort(int[]) */ public void sort(int[] data) { int temp; for (int i = 0; i < data.length; i++) { int lowIndex = i; for (int j = data.length - 1; j > i; j--) { if (data[j] < data[lowIndex]) { lowIndex = j; } } SortUtil.swap(data,i,lowIndex); } }
}
Shell排序:
package org.rut.util.algorithm.support;
import org.rut.util.algorithm.SortUtil;
/** * @author treeroot * @since 2006-2-2 * @version 1.0 */public class ShellSort implements SortUtil.Sort{
/* (non-Javadoc) * @see org.rut.util.algorithm.SortUtil.Sort#sort(int[]) */ public void sort(int[] data) { for(int i=data.length/2;i>2;i/=2){ for(int j=0;j<i;j++){ insertSort(data,j,i); } } insertSort(data,0,1); }
/** * @param data * @param j * @param i */ private void insertSort(int[] data, int start, int inc) { int temp; for(int i=start+inc;i<data.length;i+=inc){ for(int j=i;(j>=inc)&&(data[j]<data[j-inc]);j-=inc){ SortUtil.swap(data,j,j-inc); } } }
}
快速排序:
package org.rut.util.algorithm.support;
import org.rut.util.algorithm.SortUtil;
/** * @author treeroot * @since 2006-2-2 * @version 1.0 */public class QuickSort implements SortUtil.Sort{
/* (non-Javadoc) * @see org.rut.util.algorithm.SortUtil.Sort#sort(int[]) */ public void sort(int[] data) { quickSort(data,0,data.length-1); } private void quickSort(int[] data,int i,int j){ int pivotIndex=(i+j)/2; //swap SortUtil.swap(data,pivotIndex,j); int k=partition(data,i-1,j,data[j]); SortUtil.swap(data,k,j); if((k-i)>1) quickSort(data,i,k-1); if((j-k)>1) quickSort(data,k+1,j); } /** * @param data * @param i * @param j * @return */ private int partition(int[] data, int l, int r,int pivot) { do{ while(data[++l]<pivot); while((r!=0)&&data[--r]>pivot); SortUtil.swap(data,l,r); } while(l<r); SortUtil.swap(data,l,r); return l; }
}改进后的快速排序:
package org.rut.util.algorithm.support;
import org.rut.util.algorithm.SortUtil;
/** * @author treeroot * @since 2006-2-2 * @version 1.0 */public class ImprovedQuickSort implements SortUtil.Sort {
private static int MAX_STACK_SIZE=4096; private static int THRESHOLD=10; /* (non-Javadoc) * @see org.rut.util.algorithm.SortUtil.Sort#sort(int[]) */ public void sort(int[] data) { int[] stack=new int[MAX_STACK_SIZE]; int top=-1; int pivot; int pivotIndex,l,r; stack[++top]=0; stack[++top]=data.length-1; while(top>0){ int j=stack[top--]; int i=stack[top--]; pivotIndex=(i+j)/2; pivot=data[pivotIndex]; SortUtil.swap(data,pivotIndex,j); //partition l=i-1; r=j; do{ while(data[++l]<pivot); while((r!=0)&&(data[--r]>pivot)); SortUtil.swap(data,l,r); } while(l<r); SortUtil.swap(data,l,r); SortUtil.swap(data,l,j); if((l-i)>THRESHOLD){ stack[++top]=i; stack[++top]=l-1; } if((j-l)>THRESHOLD){ stack[++top]=l+1; stack[++top]=j; } } //new InsertSort().sort(data); insertSort(data); } /** * @param data */ private void insertSort(int[] data) { int temp; for(int i=1;i<data.length;i++){ for(int j=i;(j>0)&&(data[j]<data[j-1]);j--){ SortUtil.swap(data,j,j-1); } } }
}
归并排序:
package org.rut.util.algorithm.support;
import org.rut.util.algorithm.SortUtil;
/** * @author treeroot * @since 2006-2-2 * @version 1.0 */public class MergeSort implements SortUtil.Sort{
/* (non-Javadoc) * @see org.rut.util.algorithm.SortUtil.Sort#sort(int[]) */ public void sort(int[] data) { int[] temp=new int[data.length]; mergeSort(data,temp,0,data.length-1); } private void mergeSort(int[] data,int[] temp,int l,int r){ int mid=(l+r)/2; if(l==r) return ; mergeSort(data,temp,l,mid); mergeSort(data,temp,mid+1,r); for(int i=l;i<=r;i++){ temp[i]=data[i]; } int i1=l; int i2=mid+1; for(int cur=l;cur<=r;cur++){ if(i1==mid+1) data[cur]=temp[i2++]; else if(i2>r) data[cur]=temp[i1++]; else if(temp[i1]<temp[i2]) data[cur]=temp[i1++]; else data[cur]=temp[i2++]; } }
}
改进后的归并排序:
package org.rut.util.algorithm.support;
import org.rut.util.algorithm.SortUtil;
/** * @author treeroot * @since 2006-2-2 * @version 1.0 */public class ImprovedMergeSort implements SortUtil.Sort {
private static final int THRESHOLD = 10;
/* * (non-Javadoc) * * @see org.rut.util.algorithm.SortUtil.Sort#sort(int[]) */ public void sort(int[] data) { int[] temp=new int[data.length]; mergeSort(data,temp,0,data.length-1); }
private void mergeSort(int[] data, int[] temp, int l, int r) { int i, j, k; int mid = (l + r) / 2; if (l == r) return; if ((mid - l) >= THRESHOLD) mergeSort(data, temp, l, mid); else insertSort(data, l, mid - l + 1); if ((r - mid) > THRESHOLD) mergeSort(data, temp, mid + 1, r); else insertSort(data, mid + 1, r - mid);
for (i = l; i <= mid; i++) { temp[i] = data[i]; } for (j = 1; j <= r - mid; j++) { temp[r - j + 1] = data[j + mid]; } int a = temp[l]; int b = temp[r]; for (i = l, j = r, k = l; k <= r; k++) { if (a < b) { data[k] = temp[i++]; a = temp[i]; } else { data[k] = temp[j--]; b = temp[j]; } } }
/** * @param data * @param l * @param i */ private void insertSort(int[] data, int start, int len) { for(int i=start+1;i<start+len;i++){ for(int j=i;(j>start) && data[j]<data[j-1];j--){ SortUtil.swap(data,j,j-1); } } }
}堆排序:
package org.rut.util.algorithm.support;
import org.rut.util.algorithm.SortUtil;
/** * @author treeroot * @since 2006-2-2 * @version 1.0 */public class HeapSort implements SortUtil.Sort{
/* (non-Javadoc) * @see org.rut.util.algorithm.SortUtil.Sort#sort(int[]) */ public void sort(int[] data) { MaxHeap h=new MaxHeap(); h.init(data); for(int i=0;i<data.length;i++) h.remove(); System.arraycopy(h.queue,1,data,0,data.length); }
private static class MaxHeap{ void init(int[] data){ this.queue=new int[data.length+1]; for(int i=0;i<data.length;i++){ queue[++size]=data[i]; fixUp(size); } } private int size=0;
private int[] queue; public int get() { return queue[1]; }
public void remove() { SortUtil.swap(queue,1,size--); fixDown(1); } //fixdown private void fixDown(int k) { int j; while ((j = k << 1) <= size) { if (j < size && queue[j]<queue[j+1]) j++; if (queue[k]>queue[j]) //不用交换 break; SortUtil.swap(queue,j,k); k = j; } } private void fixUp(int k) { while (k > 1) { int j = k >> 1; if (queue[j]>queue[k]) break; SortUtil.swap(queue,j,k); k = j; } }
}
}
SortUtil:
package org.rut.util.algorithm;
import org.rut.util.algorithm.support.BubbleSort;import org.rut.util.algorithm.support.HeapSort;import org.rut.util.algorithm.support.ImprovedMergeSort;import org.rut.util.algorithm.support.ImprovedQuickSort;import org.rut.util.algorithm.support.InsertSort;import org.rut.util.algorithm.support.MergeSort;import org.rut.util.algorithm.support.QuickSort;import org.rut.util.algorithm.support.SelectionSort;import org.rut.util.algorithm.support.ShellSort;
/** * @author treeroot * @since 2006-2-2 * @version 1.0 */public class SortUtil { public final static int INSERT = 1;
public final static int BUBBLE = 2;
public final static int SELECTION = 3;
public final static int SHELL = 4;
public final static int QUICK = 5;
public final static int IMPROVED_QUICK = 6;
public final static int MERGE = 7;
public final static int IMPROVED_MERGE = 8;
public final static int HEAP = 9;
public static void sort(int[] data) { sort(data, IMPROVED_QUICK); } private static String[] name={ "insert","bubble","selection","shell","quick","improved_quick","merge","improved_merge","heap" }; private static Sort[] impl=new Sort[]{ new InsertSort(), new BubbleSort(), new SelectionSort(), new ShellSort(), new QuickSort(), new ImprovedQuickSort(), new MergeSort(), new ImprovedMergeSort(), new HeapSort() };
public static String toString(int algorithm){ return name[algorithm-1]; } public static void sort(int[] data, int algorithm) { impl[algorithm-1].sort(data); }
public static interface Sort { public void sort(int[] data); }
public static void swap(int[] data, int i, int j) { int temp = data[i]; data[i] = data[j]; data[j] = temp; }} |
|
|
回复:排序
心得体会, 软件技术
tone发表评论于2007/3/6 14:06:04 |
| class sort { java.lang.Comparable d[]; sort(java.lang.Comparable data[]) { d=data; } public void quickSort(int l,int r) { if(l>=r) return; int k=(l+r)/2; int last=l; swap(k,r); for(int i=l;i<r;i++) if(d[i].compareTo(d[r])==-1) swap(last++,i); //partition swap(last,r); quickSort(l,last-1); quickSort(last+1,r); } private void swap(int a,int b) { java.lang.Comparable t=d[a]; d[a]=d[b]; d[b]=t; } public static void main(String s[]) { //for test Integer t[]={ new Integer(4), new Integer(1), new Integer(3) }; new sort(t).quickSort(0,t.length-1); for(int i=0;i<t.length;i++) System.out.print(t[i]+" "); System.out.println(); } } 这里使用的是快排，算法复杂度o(nlogn)是平均状况下的。类的使用方法在main里面已经演示了，需要注意的是：为了模拟c++的template，我用了java.lang.Comparable接口，所以在使用基本数据类型的使用要用类封装。例如，int的封装类是Integer，double的封装类是Double。 |
|
|
回复:排序
心得体会, 软件技术
tone发表评论于2007/3/6 14:01:15 |
| import java.util. Arrays ; public class ArrayDemo1 { public static void main( String args[]) { int vec[] = {37, 47, 23, -5, 19, 56}; Arrays .sort(vec); for ( int i = 0; i < vec. length ; i++) { System .out.println(vec[i]); } } }
初始化一个整数数组然后调用Arrays.sort升序排序那个数组 |
|
» 1 »
|
如果你忍了，欺负你的人将来可能就进监狱了。如果你反击，欺负你的人将来可能就获选十大杰出青年了。