非常感谢http://www.blogjava.net/lishunli/archive/2012/10/17/389763.html?spm=5176.100239.blogcont44578.3.08gLRn
不同概率的抽奖技术学习 https://www.itkc8.com
工作中有遇到一些抽奖的活动,但是你懂得,抽奖物品的概率肯定不是一样,你会发现好的东西很难抽到,经常抽到一些垃圾的东西,嘿嘿,这就是本文要说的,我们要控制抽奖物品的概率。还有顺便说一句,网上这种小程序几乎没有,很多都是等概率的抽奖balabala…
需求很简单,为了更加形象,这里我们列一个表格来显示我们抽奖的物品和对应的概率(没有边框,大家凑合着看看吧,不想改造Octopress的样式了)
序号物品名称物品ID抽奖概率1物品1P10.22物品2P20.13物品3P30.44物品4P40.35物品5P50.06物品6P6-0.17物品7P70.008数据很简单,那么就直接看代码了
VO类,具体对应就是上面表格里的内容
(Gift.java)download
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 package org.usc.usc.lottery; public class Gift { private int index; private String gitfId; private String giftName; private double probability; public Gift(int index, String gitfId, String giftName, double probability) { this.index = index; this.gitfId = gitfId; this.giftName = giftName; this.probability = probability; } public int getIndex() { return index; } public void setIndex(int index) { this.index = index; } public String getGitfId() { return gitfId; } public void setGitfId(String gitfId) { this.gitfId = gitfId; } public String getGiftName() { return giftName; } public void setGiftName(String giftName) { this.giftName = giftName; } public double getProbability() { return probability; } public void setProbability(double probability) { this.probability = probability; } @Override public String toString() { return "Gift [index=" + index + ", gitfId=" + gitfId + ", giftName=" + giftName + ", probability=" + probability + "]"; } }工具类,真正的不同概率的抽奖就在这里
(LotteryUtil.java)download
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 package org.usc.usc.lottery; import java.util.ArrayList; import java.util.Collections; import java.util.List; /** * 不同概率抽奖工具包 * * @author Shunli */ public class LotteryUtil { /** * 抽奖 * * @param orignalRates * 原始的概率列表,保证顺序和实际物品对应 * @return * 物品的索引 */ public static int lottery(List<Double> orignalRates) { if (orignalRates == null || orignalRates.isEmpty()) { return -1; } int size = orignalRates.size(); // 计算总概率,这样可以保证不一定总概率是1 double sumRate = 0d; for (double rate : orignalRates) { sumRate += rate; } // 计算每个物品在总概率的基础下的概率情况 List<Double> sortOrignalRates = new ArrayList<Double>(size); Double tempSumRate = 0d; for (double rate : orignalRates) { tempSumRate += rate; sortOrignalRates.add(tempSumRate / sumRate); } // 根据区块值来获取抽取到的物品索引 double nextDouble = Math.random(); sortOrignalRates.add(nextDouble); Collections.sort(sortOrignalRates); return sortOrignalRates.indexOf(nextDouble); } }测试类,测试上面的抽奖是否成功,n次抽奖看抽奖结果
(LotteryTest.java)download
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 package org.usc.usc.lottery; import java.util.ArrayList; import java.util.HashMap; import java.util.List; import java.util.Map; import java.util.Map.Entry; /** * 不同概率抽奖 * * @author ShunLi */ public class LotteryTest { public static void main(String[] args) { List<Gift> gifts = new ArrayList<Gift>(); // 序号==物品Id==物品名称==概率 gifts.add(new Gift(1, "P1", "物品1", 0.2d)); gifts.add(new Gift(2, "P2", "物品2", 0.2d)); gifts.add(new Gift(3, "P3", "物品3", 0.4d)); gifts.add(new Gift(4, "P4", "物品4", 0.3d)); gifts.add(new Gift(5, "P5", "物品5", 0d)); gifts.add(new Gift(6, "P6", "物品6", -0.1d)); gifts.add(new Gift(7, "P7", "物品7", 0.008d)); List<Double> orignalRates = new ArrayList<Double>(gifts.size()); for (Gift gift : gifts) { double probability = gift.getProbability(); if (probability < 0) { probability = 0; } orignalRates.add(probability); } // // test // for (int i = 0; i < 10000; i++) { // try { // Gift tuple = gifts.get(LotteryUtil.lottery(orignalRates)); // System.out.println(tuple); // } catch (Exception e) { // System.out.println("lottery failed, please check it!"); // } // } // statistics Map<Integer, Integer> count = new HashMap<Integer, Integer>(); double num = 1000000; for (int i = 0; i < num; i++) { int orignalIndex = LotteryUtil.lottery(orignalRates); Integer value = count.get(orignalIndex); count.put(orignalIndex, value == null ? 1 : value + 1); } for (Entry<Integer, Integer> entry : count.entrySet()) { System.out.println(gifts.get(entry.getKey()) + ", count=" + entry.getValue() + ", probability=" + entry.getValue() / num); } } }结果
1 2 3 4 5 2 3 4 5 Gift [index=1, gitfId=P1, giftName=物品1, probability=0.2], count=199139, probability=0.199139 Gift [index=2, gitfId=P2, giftName=物品2, probability=0.1], count=99328, probability=0.099328 Gift [index=3, gitfId=P3, giftName=物品3, probability=0.4], count=396575, probability=0.396575 Gift [index=4, gitfId=P4, giftName=物品4, probability=0.3], count=296997, probability=0.296997 Gift [index=7, gitfId=P7, giftName=物品7, probability=0.0080], count=7961, probability=0.007961
不同概率的抽奖原理很简单 就是把0到1的区间分块,而分块的依据就是物品占整个的比重,再根据随机数种子来产生0-1中间的某个数,来判断这个数是落在哪个区间上,而对应的就是抽到了那个物品。随机数理论上是概率均等的,产生的每个数理论上也应该概率均等,那么相应的区间所含数的多少就体现了抽奖物品概率的不同。(p.s. 当然数目是数不清楚的,具体抽象话了点)
这个实例的数据可以说明 1. 概率可以是负数和0,当然实际上中应该不会(p.s. 正常情况下可能真的有0,比如抽个iphone5,当然是抽不到的了,这个时候,构建礼物(List gifts)的时候最好就不要加这个进去),还有可以把负数的处理放到抽奖工具类(LotteryUtil)中; 2. 所有礼物加起来的概率可以不是1,可以认为这里的概率是一个权重;
不同概率的抽奖技术学习 https://www.itkc8.com
