java模拟双色球统计红球篮球出号

本人由于连续多个月买双色球未中，气愤之下突发奇想，自己写了个双色球统计算法（菜鸟写得不好忘包涵）

该功能只是程序自动生成的选号，原本打算用网络爬虫来从360彩票网站爬取数据。即从360网站彩票随机工具随机生成100-10000注号码，然后爬到数据在进行统计（把出现频率最高和最低的号码剔除，以便能更准确的选择胆码。当然，这只是个人想法。呵呵，毕竟不会让这么多人随机中的(逆向思维，看着搞笑的别碰)）可是苦于技术不牛而只能自己手动生成号码。

代码如下:

package exercise3;

import java.text.SimpleDateFormat;
import java.util.ArrayList;
import java.util.Collections;
import java.util.Comparator;
import java.util.Date;
import java.util.HashMap;
import java.util.Iterator;
import java.util.List;
import java.util.Map;
import java.util.Map.Entry;
import java.util.Random;
import java.util.Set;

public class Test {
public static void main(String[] args) {
// int[] red = { 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 };
// int[] blue = { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16
// };
int[] red = { 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12, 15, 16, 17, 18, 19,
21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33 };// 杀码过滤后可能红球
int[] blue = { 1, 3, 4, 6, 7, 9, 10, 11, 12, 13 };// 杀码过滤后可能篮球

List<Map<String, Integer>> l = new ArrayList<Map<String, Integer>>();
System.out.println(new SimpleDateFormat("yyyy/MM/dd  hh:MM:ss")
.format(new Date()));
for (int k = 0; k < 100; k++) {
int ball[] = new int[7];
Map<String, Integer> m = new HashMap<String, Integer>();
for (int i = 0; i < ball.length - 1; i++) {
int index = new Random().nextInt(29);// 红球杀去4个码
ball[i] = red[index];
for (int j = 0; j < i; j++) {
if (ball[j] == ball[i]) {
i--;
break;
}
}
m.put("红球" + (i + 1), ball[i]);
}
ball[6] = blue[new Random().nextInt(10)];// 篮球杀去6个码
m.put("篮球7", ball[6]);
l.add(m);
}

Map<String, Integer> count = new HashMap<String, Integer>();
for (Map<String, Integer> map : l) {
for (int mm = 1; mm <= 7; mm++) {
String str = mm <= 6 ? "红球" : "篮球";
String next = mm <= 6 ? "红球" : "篮球";
str = str + mm;
Integer ii = count.get(next + map.get(str));
Integer num = ii;
if (num == null) {
num = 0;
}
String color = mm <= 6 ? "红球" : "篮球";
color += map.get(str);
count.put(color, num + 1);
}

}

hashMapSort(count);

// Set<Entry<String, Integer>> entrys = count.entrySet();
// for (Iterator<Map.Entry<String, Integer>>
// iter=entrys.iterator();iter.hasNext();) {
// Map.Entry<String, Integer> entry = iter.next();
// System.out.println(entry.getKey() + ":" + entry.getValue());
// }

System.out.println(new SimpleDateFormat("yyyy/MM/dd  hh:MM:ss")
.format(new Date()));

}

// 对HashMap(或Hashtable,LinkedHashMap)按照value的值升序:
public static void hashMapSort(Map<String, Integer> map) {
List<Map.Entry<String, Integer>> mappingList = null;

// 通过ArrayList构造函数把map.entrySet()转换成list
mappingList = new ArrayList<Map.Entry<String, Integer>>(map.entrySet());
// 通过比较器实现比较排序
Collections.sort(mappingList,
new Comparator<Map.Entry<String, Integer>>() {
public int compare(Map.Entry<String, Integer> mapping1,
Map.Entry<String, Integer> mapping2) {
return mapping1.getValue().compareTo(
mapping2.getValue());
}
});

// for (Map.Entry<String, Integer> mapping : mappingList) {
// System.out.println(mapping.getKey() + ":" + mapping.getValue());
// }
for (int i = 0; i < mappingList.size(); i++) {
Map.Entry<String, Integer> mapping = mappingList.get(i);
System.out.print(mapping.getKey() + ":" + mapping.getValue()
+ "\t\t");
if (i % 3 == 2) {
System.out.println();
}
}
System.out.println();
}

}

如果有大牛看到，莫要嘲笑小弟。小弟也是鼓着勇气写的文章~

模拟100注统计结果

模拟1000注统计结果

当数据量很大的时候，基本每个号码都趋于稳定。这就是出现的频率近似概率的结果了