java语言实现权重随机算法完整实例
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2023-12-13 19:31:58
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...
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<string, integer> keycount = new hashmap<string, integer>();
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<weightelement> weightelements;
public void initweight(string[] keys, integer[] weights){
if(keys == null || weights == null || keys.length != weights.length){
return;
}
weightelements = new arraylist<weightelement>();
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<weightcategory> categorys = new arraylist<weightcategory>();
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 && 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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