PokemonGo完美度算法！是风姐还是松岛枫？--工地斗天地斗天马座

最近很流行ｐｏｋｅｍｏｎ　ｇｏ啊　楼主最喜欢和智爷人兽合一的忍蛙啊。。希望下一季塞妹还在智爷身边

大街小巷都在玩，自从靖国神社在第一天就被中国万家占领后，楼主一个朋友在马路上玩，被日本人问，你们中国人都开作弊器的吧，真是五味杂呈

哎，老任要是解锁，我想大多数玩家还是乐意感受这个游戏本来的用意的。。。也不能怪老任，当年在内地小神游事件惭遭滑铁卢。。。。５０下载一次游戏都卖不出去。。后话了

言归正传

发现大家有个很严重的误区，不是ｃｐ越高宠越好，看到很多攻略都这么说，不是坑人么。。。

首先大家要了解下完美度是个什么东西，举个例子

现在你抓到一只ａａａ　ｃｐ为７６０　ｄｕｓｔ为８００

对于不同的宠　都有一个不同的成长列表

比如这制ａａａ在ｄｕｓｔ为８００的时候　一共可以升级四次　给出数据，每次

ｄｕｓｔ　　ｍｉｎＣｐ　　　ｍａｘＣｐ　　ｈｐ

８００　　６８０　　　　　７４０　　　３８～４４

８００　　７００　　　　　７８０　　　４０～５０

８００　　７４０　　　　　８２０　　　４５～５５

８００　　７５０　　　　　８４０　　　５０～６０

８００　　７８０　　　　　８６０　　　５５～６５

因为ｇｏ中宠物等级是隐藏的，所以你只能根据数据去大概判断你的宠属于哪个区间

现在给出的例子是最极端的，正好有三个区间都符合你的概率，所以这个时候你的完美度就可能会有３种，分别是

（ｙｏｕｒＣｐ－ｍｉｎＣｐ）　／(ｍａｘＣｐ－ｍｉｎＣｐ)

（７６０－７００）／（７８０－７００）　　０.７５

（７６０－７４０）／（８２０－７４０）　　０.３４

（７６０－７５０）／（８４０－７５０）　　０.１１

看到这里大家都懂了吧，对于同一组数据碰到极端情况是会同时符合三个区间，这个时候根本算不出你的宠到底是什么完美度，可能是凤姐，也可能是松岛枫！！！

给出一个网站有数据的　http://pokemongo.gamepress.gg/pokemon/54

好了　现在开始贴代码

首先建出ｂａｓｉｃＶａｌｕｅ的属性类

package lobs.jibunn.mb.pokemon;public class BasicValue {   protected int dust;    protected double MaxCp;    protected double MinCp;    protected double CurrentCp;public int getDust() {return dust;}public void setDust(int dust) {this.dust = dust;}public double getMaxCp() {return MaxCp;}public void setMaxCp(double maxCp) {MaxCp = maxCp;}public double getMinCp() {return MinCp;}public void setMinCp(double minCp) {MinCp = minCp;}public double getCurrentCp() {return CurrentCp;}public void setCurrentCp(double currentCp) {CurrentCp = currentCp;}public BasicValue(int dust,double fuck,double minCp, double maxCp) {setMaxCp(maxCp);setMinCp(minCp);setDust(dust);setCurrentCp(fuck);}}

然后给出ｐｏｋｅｍｏｎ的工厂抽象类，对于每个不同的我们都再分别建模

package lobs.jibunn.mb.pokemon;import java.util.ArrayList;import java.util.List;public abstract class Pokemon {    List<BasicValue> bvList;        public void initialPokemon() {    <span style="white-space:pre"></span>bvList = null;    }    public abstract List getBvList();}

楼主目前只录入了几组数据，先拿楼主的９８火伊布做例子

建出火伊布实体类，继承工厂类

<pre name="code" class="java">package lobs.jibunn.mb.pokemon;import java.util.ArrayList;import java.util.List;public class Flareon extends Pokemon {    List<BasicValue> bvList;public Flareon() {bvList = new ArrayList<BasicValue>();}@Overridepublic List getBvList() {bvList.add(new BasicValue(200, 1, 31.99, 37.40));bvList.add(new BasicValue(200, 1.5, 66.12, 77.29));bvList.add(new BasicValue(200, 2, 100.24, 117.19));bvList.add(new BasicValue(200, 2.5, 134.37, 157.08));bvList.add(new BasicValue(400, 3, 168.50, 196.98));bvList.add(new BasicValue(400, 3.5, 202.62, 236.87));bvList.add(new BasicValue(400, 4, 236.75, 276.77));bvList.add(new BasicValue(400, 4.5, 270.88, 316.66));bvList.add(new BasicValue(600, 5, 305.00, 356.56));bvList.add(new BasicValue(600, 5.5, 339.13, 396.45));bvList.add(new BasicValue(600, 6, 373.26, 436.35));bvList.add(new BasicValue(600, 6.5, 407.38, 476.24));bvList.add(new BasicValue(800, 7, 441.51, 516.14));bvList.add(new BasicValue(800, 7.5, 475.64, 556.03));bvList.add(new BasicValue(800, 8, 509.76, 595.92));bvList.add(new BasicValue(800, 8.5, 543.89, 635.82));bvList.add(new BasicValue(1000, 9, 578.01, 675.71));bvList.add(new BasicValue(1000, 9.5, 612.14, 715.61));bvList.add(new BasicValue(1000, 10, 646.27, 755.50));bvList.add(new BasicValue(1000, 10.5, 678.56, 793.25));bvList.add(new BasicValue(1300, 11, 710.85, 831.00));bvList.add(new BasicValue(1300, 11.5, 743.14, 868.75));bvList.add(new BasicValue(1300, 12, 775.43, 906.50));bvList.add(new BasicValue(1300, 12.5, 807.72, 944.25));bvList.add(new BasicValue(1600, 13, 840.01, 982.00));bvList.add(new BasicValue(1600, 13.5, 872.30, 1019.74));bvList.add(new BasicValue(1600, 14, 904.59, 1057.49));bvList.add(new BasicValue(1600, 14.5, 936.88, 1095.24));bvList.add(new BasicValue(1900, 15, 969.17, 1132.99));bvList.add(new BasicValue(1900, 15.5, 1001.46, 1170.74));bvList.add(new BasicValue(1900, 16, 1033.75, 1208.49));bvList.add(new BasicValue(1900, 16.5, 1066.04, 1246.24));bvList.add(new BasicValue(2200, 17, 1098.34, 1283.98));bvList.add(new BasicValue(2200, 17.5, 1130.63, 1321.73));bvList.add(new BasicValue(2200, 18, 1162.92, 1359.48));bvList.add(new BasicValue(2200, 18.5, 1195.21, 1397.23));bvList.add(new BasicValue(2500, 19, 1227.50, 1434.98));bvList.add(new BasicValue(2500, 19.5, 1259.79, 1472.73));bvList.add(new BasicValue(2500, 20, 1292.08, 1510.48));bvList.add(new BasicValue(2500, 20.5, 1324.37, 1548.22));bvList.add(new BasicValue(3000, 21, 1356.70, 1586.02));bvList.add(new BasicValue(3000, 21.5, 1388.99, 1623.77));bvList.add(new BasicValue(3000, 22, 1421.33, 1661.57));bvList.add(new BasicValue(3000, 22.5, 1453.62, 1699.32));bvList.add(new BasicValue(3500, 23, 1485.95, 1737.12));bvList.add(new BasicValue(3500, 23.5, 1518.24, 1774.86));bvList.add(new BasicValue(3500, 24, 1550.57, 1812.66));bvList.add(new BasicValue(3500, 24.5, 1582.86, 1850.41));bvList.add(new BasicValue(4000, 25, 1615.20, 1888.21));bvList.add(new BasicValue(4000, 25.5, 1647.49, 1925.96));bvList.add(new BasicValue(4000, 26, 1679.82, 1963.76));bvList.add(new BasicValue(4000, 26.5, 1712.11, 2001.51));bvList.add(new BasicValue(4500, 27, 1744.45, 2039.30));bvList.add(new BasicValue(4500, 27.5, 1776.74, 2077.05));bvList.add(new BasicValue(4500, 28, 1809.07, 2114.85));bvList.add(new BasicValue(4500, 28.5, 1841.36, 2152.60));bvList.add(new BasicValue(5000, 29, 1873.69, 2190.40));bvList.add(new BasicValue(5000, 29.5, 1905.98, 2228.15));bvList.add(new BasicValue(5000, 30, 1938.32, 2265.94));bvList.add(new BasicValue(5000, 30.5, 1954.46, 2284.82));bvList.add(new BasicValue(6000, 31, 1970.61, 2303.69));bvList.add(new BasicValue(6000, 31.5, 1986.75, 2322.57));bvList.add(new BasicValue(6000, 32, 2002.90, 2341.44));bvList.add(new BasicValue(6000, 32.5, 2019.04, 2360.31));bvList.add(new BasicValue(7000, 33, 2035.19, 2379.19));bvList.add(new BasicValue(7000, 33.5, 2051.33, 2398.06));bvList.add(new BasicValue(7000, 34, 2067.48, 2416.94));bvList.add(new BasicValue(7000, 34.5, 2083.62, 2435.81));bvList.add(new BasicValue(8000, 35, 2099.77, 2454.69));bvList.add(new BasicValue(8000, 35.5, 2115.91, 2473.56));bvList.add(new BasicValue(8000, 36, 2132.06, 2492.43));bvList.add(new BasicValue(8000, 36.5, 2148.20, 2511.31));bvList.add(new BasicValue(9000, 37, 2164.35, 2530.18));bvList.add(new BasicValue(9000, 37.5, 2180.49, 2549.06));bvList.add(new BasicValue(9000, 38, 2196.64, 2567.93));bvList.add(new BasicValue(9000, 38.5, 2212.78, 2586.80));bvList.add(new BasicValue(10000, 39, 2228.93, 2605.68));bvList.add(new BasicValue(10000, 39.5, 2245.07, 2624.55));bvList.add(new BasicValue(10000, 40, 2261.22, 2643.43));return bvList;}}

好了，万事齐全，就等开撸

具体算法也在这里实现，两个循环搞定～就这么暴力～最后输出所有的可能性

蓝色加大加粗的地方日后大家可以自己喂颗糖获取更精确数据，就是这样～当然当一组数据出现三次以后，你懂的～就他了～至于为什么是三～自己动脑子～

package lobs.jibunn.mb.jp.suanfa;import java.util.ArrayList;import java.util.List;import lobs.jibunn.mb.pokemon.BasicValue;import lobs.jibunn.mb.pokemon.Flareon;import lobs.jibunn.mb.pokemon.Pokemon;public class EviCalculator {static double[] possiblePerferction = new double[9];public static void main (String args[]) {Pokemon pokemon = new Flareon();List calList =pokemon.getBvList();List <BasicValue>calValue = new  <BasicValue>ArrayList();<span style="font-size:24px;color:#6633ff;"><strong><em><u>calValue.add(new BasicValue(941,1300,0,0));</u></em></strong></span>getPossibleCp(calValue,calList);}public static void getPossibleCp(List <BasicValue>calValue, List<BasicValue> calList) {        for(BasicValue bv : calList ) {for(int i = 0; i < calValue.size();i++) {if (bv.getDust() == calValue.get(i).getDust()&& bv.getMaxCp() > calValue.get(i).getCurrentCp()&& bv.getMinCp() < calValue.get(i).getCurrentCp()) {possiblePerferction[i] = (calValue.get(i).getCurrentCp() - bv.getMinCp())/(bv.getMaxCp()-bv.getMinCp()) ;System.out.println(possiblePerferction[i]);}}}}}