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2023-03-11
java语言实现权重随机算法完整实例
前言
现在app就是雨后春笋,嗖嗖的往外冒啊,有经验的、没经验的、有资历的、没资历的都想着创业,创业的90%以上都要做一个app出来,好像成了创业的标配。
做了app就得推广啊,怎么推,发券送钱是最多用的被不可少的了,现在好多产品或者运营都要求能够随机出优惠券的金额,但是呢又不能过于随机,送出去的券都是钱吗,投资人的钱,是吧。
所以,在随机生成的金额中就要求,小额度的几率要大,大额度的几率要小,比如说3元的70%,5块的25%,10块的5%,这个样子的概率去生成优惠券,这个怎么办呢?
对于上述的问题,直接用我们的Random.next(Integer range);就不够了。因为这个伪随机不带权重,3,5,10出现的概率都是一样的。
实现思路
还是拿上述的例子,3出现的概率是70%,我们给他的权重赋值为70,5出现的概率为25%,我们给他的权重赋值为25,10出现的概率为5%,我们给他的权重赋值为5.
我们按照顺序计算出权重的加和,把当前数字出现的权重加和前的值作为其权重范围的起点值,把加和后的值作为其权重范围的终点值。
这样的话,我们就可以使用Random.next(100)来做随机数,然后判断随机数落在的范围,然后映射到对应的优惠券数值即可。
java实现
package com.nggirl.test.weight.random;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Random;
public class WeightRandom {
public static void main(String[] args){
WeightRandom wr = new WeightRandom();
wr.initWeight(new String[]{
"1","2","3","4"
}
, new Integer[]{
100,100,200,600
}
);
Random r = new Random();
for (int i = 0; i < 10; i++){
Integer rv = r.nextint(wr.getMaxRandomValue());
System.out.println(rv);
System.out.println(wr.getElementByRandomValue(rv).getKey() + " " + rv);
}
HashMap
keyCount.put("1", 0);
keyCount.put("2", 0);
keyCount.put("3", 0);
keyCount.put("4", 0);
for (int i = 0; i < 10000; i++){
Integer rv = r.nextint(wr.getMaxRandomValue());
String key = wr.getElementByRandomValue(rv).getKey();
keyCount.put(key, keyCount.get(key).intValue()+1);
}
System.out.println("");
}
private List
public void initWeight(String[] keys, Integer[] weights){
if(keys == null || weights == null || keys.length != weights.length){
return;
}
weightElements = new ArrayList
for (int i=0; i< keys.length; i++){
weightElements.add(new WeightElement(keys[i], weights[i]));
}
rangeWeightElemnts();
printRvs();
}
private void rangeWeightElemnts(){
if(weightElements.size() == 0){
return;
}
WeightElement ele0 = weightElements.get(0);
ele0.setThresholdLow(0);
ele0.setThresholdHigh(ele0.getWeight());
for (int i = 1; i < weightElements.size(); i++){
WeightElement curElement = weightElements.get(i);
WeightElement preElement = weightElements.get(i - 1);
curElement.setThresholdLow(preElement.getThresholdHigh());
curElement.setThresholdHigh(curElement.getThresholdLow() + curElement.getWeight());
}
}
public WeightElement getElementByRandomValue(Integer rv){
//因为元素权重范围有序递增,所以这里可以改为二分查找
for (WeightElement e:weightElements){
if(rv >= e.getThresholdLow() && rv < e.getThresholdHigh()){
return e;
}
}
return null;
}
public Integer getMaxRandomValue(){
if(weightElements == null || weightElements.size() == 0){
return null;
}
return weightElements.get(weightElements.size() - 1).getThresholdHigh();
}
public void printRvs(){
for (WeightElement e:weightElements){
System.out.println(e.toString());
}
}
static class WeightElement{
/**
* 元素标记
*/
private String key;
/**
* 元素权重
*/
private Integer weight;
/**
* 权重对应随机数范围低线
*/
private Integer thresholdLow;
/**
* 权重对应随机数范围高线
*/
private Integer thresholdHigh;
public WeightElement(){
}
public WeightElement(Integer weight){
this.key = weight.toString();
this.weight = weight;
}
public WeightElement(String key, Integer weight){
this.key = key;
this.weight = weight;
}
public String getKey() {
return key;
}
public void setKey(String key) {
this.key = key;
}
public Integer getWeight() {
return weight;
}
public void setWeight(Integer weight) {
this.weight = weight;
}
public Integer getThresholdLow() {
return thresholdLow;
}
public void setThresholdLow(Integer thresholdLow) {
this.thresholdLow = thresholdLow;
}
public Integer getThresholdHigh() {
return thresholdHigh;
}
public void setThresholdHigh(Integer thresholdHigh) {
this.thresholdHigh = thresholdHigh;
}
public String toString(){
return "key:"+this.key + " weight:" + this.weight + " low:"+this.thresholdLow+" heigh:"+this.thresholdHigh;
}
}
}
结果:
2 102
876
4 876
二分法的实现
public WeightElement getElementByRandomValue(Integer rv){
if(rv < 0 || rv > getMaxRandomValue()-1){
return null;
}
//此时rv必然在0 - getMaxRandomValue()-1范围内,
//也就是必然能够命中某一个值
int start = 0, end = weightElements.size() - 1;
int index = weightElements.size()/2;
while(true){
if(rv < weightElements.get(index).getThresholdLow()){
end = index - 1;
} else if(rv >= weightElements.get(index).getThresholdHigh()){
start = index + 1;
} else{
return weightElements.get(index);
}
index = (start + end)/2;
}
}
下面再分享一则实例,加强对权重随机算法的理解,一次到位!
权重随机算法在抽奖,资源调度等系统中应用还是比较广泛的,一个简单的按照权重来随机的实现,权重为几个随机对象(分类)的命中的比例,权重设置越高命中越容易,之和可以不等于100;
简单实现代码如下:
import java.util.ArrayList;
import java.util.List;
import java.util.Random;
public class WeightRandom {
static List
private static Random random = new Random();
public static void initData() {
WeightCategory wc1 = new WeightCategory("A",60);
WeightCategory wc2 = new WeightCategory("B",20);
WeightCategory wc3 = new WeightCategory("C",20);
categorys.add(wc1);
categorys.add(wc2);
categorys.add(wc3);
}
public static void main(String[] args) {
initData();
Integer weightSum = 0;
for (WeightCategory wc : categorys) {
weightSum += wc.getWeight();
}
if (weightSum <= 0) {
System.err.println("Error: weightSum=" + weightSum.toString());
return;
}
Integer n = random.nextint(weightSum);
// n in [0, weightSum)
Integer m = 0;
for (WeightCategory wc : categorys) {
if (m <= n &IbaLS& n < m + wc.getWeight()) {
System.out.println("This Random Category is "+wc.getCategory());
break;
}
m += wc.getWeight();
}
}
}
class WeightCategory {
private String category;
private Integer weight;
public WeightCategory() {
super();
}
public WeightCategory(String category, Integer weight) {
super();
this.setCategory(category);
this.setWeight(weight);
}
public Integer getWeight() {
return weight;
}
public void setWeight(Integer weight) {
this.weight = weight;
}
public String getCategory() {
return category;
}
public void setCategory(String category) {
this.category = category;
}
}
结果:
总结
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