Many resources are needed to download a project. Please understand that we have to compensate our server costs. Thank you in advance. Project price only 1 $
You can buy this project and download/modify it how often you want.
/******************************************************************************
* Confidential Proprietary *
* (c) Copyright Haifeng Li 2011, All Rights Reserved *
******************************************************************************/
package smile.sort;
/**
* Some useful functions such as swap and swif-down used in many sorting
* algorithms.
*
* @author Haifeng Li
*/
public class SortUtils {
/**
* Swap two positions.
*/
public static void swap(int arr[], int i, int j) {
int a = arr[i];
arr[i] = arr[j];
arr[j] = a;
}
/**
* Swap two positions.
*/
public static void swap(float arr[], int i, int j) {
float a = arr[i];
arr[i] = arr[j];
arr[j] = a;
}
/**
* Swap two positions.
*/
public static void swap(double arr[], int i, int j) {
double a;
a = arr[i];
arr[i] = arr[j];
arr[j] = a;
}
/**
* Swap two positions.
*/
public static void swap(Object arr[], int i, int j) {
Object a;
a = arr[i];
arr[i] = arr[j];
arr[j] = a;
}
/**
* To restore the max-heap condition when a node's priority is increased.
* We move up the heap, exchaning the node at position k with its parent
* (at postion k/2) if necessary, continuing as long as a[k/2] < a[k] or
* until we reach the top of the heap.
*/
public static void siftUp(int[] arr, int k) {
while (k > 1 && arr[k/2] < arr[k]) {
swap(arr, k, k/2);
k = k/2;
}
}
/**
* To restore the max-heap condition when a node's priority is increased.
* We move up the heap, exchaning the node at position k with its parent
* (at postion k/2) if necessary, continuing as long as a[k/2] < a[k] or
* until we reach the top of the heap.
*/
public static void siftUp(float[] arr, int k) {
while (k > 1 && arr[k/2] < arr[k]) {
swap(arr, k, k/2);
k = k/2;
}
}
/**
* To restore the max-heap condition when a node's priority is increased.
* We move up the heap, exchaning the node at position k with its parent
* (at postion k/2) if necessary, continuing as long as a[k/2] < a[k] or
* until we reach the top of the heap.
*/
public static void siftUp(double[] arr, int k) {
while (k > 1 && arr[k/2] < arr[k]) {
swap(arr, k, k/2);
k = k/2;
}
}
/**
* To restore the max-heap condition when a node's priority is increased.
* We move up the heap, exchaning the node at position k with its parent
* (at postion k/2) if necessary, continuing as long as a[k/2] < a[k] or
* until we reach the top of the heap.
*/
public static > void siftUp(T[] arr, int k) {
while (k > 1 && arr[k/2].compareTo(arr[k]) < 0) {
swap(arr, k, k/2);
k = k/2;
}
}
/**
* To restore the max-heap condition when a node's priority is decreased.
* We move down the heap, exchanging the node at position k with the larger
* of that node's two children if necessary and stopping when the node at
* k is not smaller than either child or the bottom is reached. Note that
* if n is even and k is n/2, then the node at k has only one child -- this
* case must be treated properly.
*/
public static void siftDown(int[] arr, int k, int n) {
while (2*k <= n) {
int j = 2 * k;
if (j < n && arr[j] < arr[j + 1]) {
j++;
}
if (arr[k] >= arr[j]) {
break;
}
swap(arr, k, j);
k = j;
}
}
/**
* To restore the max-heap condition when a node's priority is decreased.
* We move down the heap, exchanging the node at position k with the larger
* of that node's two children if necessary and stopping when the node at
* k is not smaller than either child or the bottom is reached. Note that
* if n is even and k is n/2, then the node at k has only one child -- this
* case must be treated properly.
*/
public static void siftDown(float[] arr, int k, int n) {
while (2*k <= n) {
int j = 2 * k;
if (j < n && arr[j] < arr[j + 1]) {
j++;
}
if (arr[k] >= arr[j]) {
break;
}
swap(arr, k, j);
k = j;
}
}
/**
* To restore the max-heap condition when a node's priority is decreased.
* We move down the heap, exchanging the node at position k with the larger
* of that node's two children if necessary and stopping when the node at
* k is not smaller than either child or the bottom is reached. Note that
* if n is even and k is n/2, then the node at k has only one child -- this
* case must be treated properly.
*/
public static void siftDown(double[] arr, int k, int n) {
while (2*k <= n) {
int j = 2 * k;
if (j < n && arr[j] < arr[j + 1]) {
j++;
}
if (arr[k] >= arr[j]) {
break;
}
swap(arr, k, j);
k = j;
}
}
/**
* To restore the max-heap condition when a node's priority is decreased.
* We move down the heap, exchanging the node at position k with the larger
* of that node's two children if necessary and stopping when the node at
* k is not smaller than either child or the bottom is reached. Note that
* if n is even and k is n/2, then the node at k has only one child -- this
* case must be treated properly.
*/
public static > void siftDown(T[] arr, int k, int n) {
while (2*k <= n) {
int j = 2 * k;
if (j < n && arr[j].compareTo(arr[j + 1]) < 0) {
j++;
}
if (arr[k].compareTo(arr[j]) >= 0) {
break;
}
SortUtils.swap(arr, k, j);
k = j;
}
}
}