今天爲你們寫個小程序。java
工做中有遇到一些抽獎的活動,可是你懂得,抽獎物品的機率確定不是同樣,你會發現好的東西很難抽到,常常抽到一些垃圾的東西,嘿嘿,這就是本文要說的,咱們要控制抽獎物品的機率。還有順便說一句,網上這種小程序幾乎沒有,不少都是等機率的抽獎balabala…git
需求很簡單,爲了更加形象,這裏咱們列一個表格來顯示咱們抽獎的物品和對應的機率(沒有邊框,你們湊合着看看吧,不想改造Octopress的樣式了)github
序號 | 物品名稱 | 物品ID | 抽獎機率 |
1 | 物品1 | P1 | 0.2 |
2 | 物品2 | P2 | 0.1 |
3 | 物品3 | P3 | 0.4 |
4 | 物品4 | P4 | 0.3 |
5 | 物品5 | P5 | 0.0 |
6 | 物品6 | P6 | -0.1 |
7 | 物品7 | P7 | 0.008 |
數據很簡單,那麼就直接看代碼了小程序
VO類,具體對應就是上面表格裏的內容dom
(Gift.java)downloadiphone
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packageorg.usc.usc.lottery; publicclassGift { privateintindex; privateStringgitfId; privateStringgiftName; privatedoubleprobability; publicGift(intindex, StringgitfId, StringgiftName, doubleprobability) { this.index = index; this.gitfId = gitfId; this.giftName = giftName; this.probability = probability; } publicintgetIndex() { returnindex; } publicvoidsetIndex(intindex) { this.index = index; } publicStringgetGitfId() { returngitfId; } publicvoidsetGitfId(StringgitfId) { this.gitfId = gitfId; } publicStringgetGiftName() { returngiftName; } publicvoidsetGiftName(StringgiftName) { this.giftName = giftName; } publicdoublegetProbability() { returnprobability; } publicvoidsetProbability(doubleprobability) { this.probability = probability; } @Override publicStringtoString() { return"Gift [index=" + index + ", gitfId=" + gitfId + ", giftName=" + giftName + ", probability=" + probability + "]"; } } |
工具類,真正的不一樣機率的抽獎就在這裏ide
(LotteryUtil.java)download工具
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packageorg.usc.usc.lottery; import java.util.ArrayList; import java.util.Collections; import java.util.List; /** * 不一樣機率抽獎工具包 * * @author Shunli */ publicclassLotteryUtil { /** * 抽獎 * * @param orignalRates * 原始的機率列表,保證順序和實際物品對應 * @return * 物品的索引 */ publicstaticintlottery(List<Double> orignalRates) { if (orignalRates == null || orignalRates.isEmpty()) { return -1; } intsize = orignalRates.size(); // 計算總機率,這樣能夠保證不必定總機率是1 doublesumRate = 0d; for (doublerate : orignalRates) { sumRate += rate; } // 計算每一個物品在總機率的基礎下的機率狀況 List<Double> sortOrignalRates = newArrayList<Double>(size); DoubletempSumRate = 0d; for (doublerate : orignalRates) { tempSumRate += rate; sortOrignalRates.add(tempSumRate / sumRate); } // 根據區塊值來獲取抽取到的物品索引 doublenextDouble = Math.random(); sortOrignalRates.add(nextDouble); Collections.sort(sortOrignalRates); returnsortOrignalRates.indexOf(nextDouble); } } |
測試類,測試上面的抽獎是否成功,n次抽獎看抽獎結果學習
(LotteryTest.java)download測試
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packageorg.usc.usc.lottery; import java.util.ArrayList; import java.util.HashMap; import java.util.List; import java.util.Map; import java.util.Map.Entry; /** * 不一樣機率抽獎 * * @author ShunLi */ publicclassLotteryTest { publicstaticvoidmain(String[] args) { List<Gift> gifts = newArrayList<Gift>(); // 序號==物品Id==物品名稱==機率 gifts.add(newGift(1, "P1", "物品1", 0.2d)); gifts.add(newGift(2, "P2", "物品2", 0.2d)); gifts.add(newGift(3, "P3", "物品3", 0.4d)); gifts.add(newGift(4, "P4", "物品4", 0.3d)); gifts.add(newGift(5, "P5", "物品5", 0d)); gifts.add(newGift(6, "P6", "物品6", -0.1d)); gifts.add(newGift(7, "P7", "物品7", 0.008d)); List<Double> orignalRates = newArrayList<Double>(gifts.size()); for (Giftgift : gifts) { doubleprobability = 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 = newHashMap<Integer, Integer>(); doublenum = 1000000; for (inti = 0; i < num; i++) { intorignalIndex = LotteryUtil.lottery(orignalRates); Integervalue = 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); } } } |
結果
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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 |
不一樣機率的抽獎原理很簡單
就是把0到1的區間分塊,而分塊的依據就是物品佔整個的比重,再根據隨機數種子來產生0-1中間的某個數,來判斷這個數是落在哪一個區間上,而對應的就是抽到了那個物品。隨機數理論上是機率均等的,產生的每一個數理論上也應該機率均等,那麼相應的區間所含數的多少就體現了抽獎物品機率的不一樣。(p.s. 固然數目是數不清楚的,具體抽象話了點)
這個實例的數據能夠說明
1. 機率能夠是負數和0,固然實際上中應該不會(p.s. 正常狀況下可能真的有0,好比抽個iphone5,固然是抽不到的了,這個時候,構建禮物(List gifts)的時候最好就不要加這個進去),還有能夠把負數的處理放到抽獎工具類(LotteryUtil)中;
2. 全部禮物加起來的機率能夠不是1,能夠認爲這裏的機率是一個權重;
小小分享了,卻是以爲你們能夠本身先想一想,若是你來寫這樣的小程序,如何來寫,有沒有其它的創意和想法?若是有什麼建議或問題的話,能夠經過微博 http://weibo.com/lishunli 聯繫到我,你們一塊兒交流學習。