private g_game_ball_result DynmicAssignment(g_game_ball_result entity, List <int> source, int count)
{
Type type = typeof(g_game_ball_result);
//取得属性集合
PropertyInfo[] pi = type.GetProperties();
foreach (PropertyInfo item in pi)
{
if (item.Name.Contains("b_"))
{
int result = 0;
bool isInt = int.TryParse(item.Name.Split('_')[1], out result);
if (isInt && result <= count)
{
item.SetValue(entity, Convert.ChangeType(source[result - 1], item.PropertyType), null);
}
}
}
return(entity);
}
/// <summary>
/// 此种统计方式为统计 开奖号码个数 * 总号码个数列 的彩种
/// </summary>
/// <param name="gameTypeId">彩种ID</param>
/// <param name="summaryCount">统计期数(30,50,80)</param>
public void Analysis1(int gameTypeId, int summaryCount)
{
using (var conn = (new DapperDb()).DbConnection)
{
var analysis = new LotteryResultAnalysisRepository(conn, null);
List <g_game_type_result> results = analysis.GetLotteryResult(gameTypeId, summaryCount).OrderBy(p => p.open_reward_time_ts).ToList();
if (results != null && results.Count > 0)
{
#region
string expect_no = results.OrderByDescending(p => p.expect_no).FirstOrDefault().expect_no;
//获取最近一期的编号，如果不存在才开始统计
bool isExist = analysis.CheckAnalysisIsExist(summaryCount, gameTypeId, expect_no);
if (isExist)
{
return;
}
List <string> strRewardNos = results.Select(p => p.win_reward_no).ToList();
//初始化 summary_count 期 ball_count 个开奖号码个数的开奖号码集合
List <List <int> > rewardNos = new List <List <int> >();
for (int i = 0; i < strRewardNos.Count; i++)
{
List <int> rewardNo = new List <int>();
string[] strRewardNo = strRewardNos[i].Split(',');
for (int j = 0; j < strRewardNo.Length; j++)
{
rewardNo.Add(Convert.ToInt32(strRewardNo[j]) - left_offset);
}
rewardNos.Add(rewardNo);
}
//声明一个统计用的2维泛型集合并初始化值为-1
List <List <int> > summary = new List <List <int> >();
for (int i = 0; i < summaryCount; i++)
{
List <int> prize_number = new List <int>();
//生成 中奖号码个数*总号码个数列
for (int j = 0; j < total_balls_count * prize_balls_count; j++)
{
prize_number.Add(-1);
}
summary.Add(prize_number);
}
try
{
//把每一期的中奖号码赋值到统计集合中
for (int i = 0; i < summary.Count; i++)
{
//有多少中奖号码即循环几次赋值
for (int k = 0; k < prize_balls_count; k++)
{
//Console.Write("中奖值为:" + inits[i][k]);
//inits[i][k] 的值为具体第i期的第k个中奖号码值。
//inits[0][0] 即为 第1期第1个中奖号码,i为第几期,k为第几个号码
int prize_number = rewardNos[i][k];
//total_balls_count * k 为第k个中奖号的偏移量，因为每个中奖号码都需要占用所有号码的下标位置
int offset = total_balls_count * k;
//总偏移量为每一个中奖号码的偏移量加上本上的值。比如：假设总共10个号码
//第一个中奖号的偏移量为0*10，中奖号为7.即0+7=7；
//第二个中奖号的偏移量为1*10，中奖号为8，即10+8=18；
int total_offset = offset + prize_number;
//把每一个中奖号赋值到统计集合中
summary[i][total_offset] = prize_number;
}
}
}
catch (Exception ex)
{
LogHelper.WriteLog(typeof(Exception), "LotteryAnalysisService-> \r\n" + ex.StackTrace + "\r\n " + ex.Message + "\r\n " + ex.InnerException);
}
List <int> totals = new List <int>();
List <int> continuous = new List <int>();
List <int> max = new List <int>();
List <int> avg = new List <int>();
//按总列数循环总行数次，比较每一列的值
for (int i = 0; i < total_balls_count * prize_balls_count; i++)
{
//出现总次数
int total_count = 0;
//最大遗漏值
int max_miss_count = 0;
//最大连出值
int max_continuous_count = 0;
//当前遗漏值
int current_miss_count = 0;
//当前连出值
int current_continuous_count = 0;
int last_row = 0;
for (int j = 0; j < summary.Count; j++)
{
int current_value = summary[j][i];
if (current_value != -1)
{
//最后出现中奖号行数
last_row = j + 1;
//更新出现总次数
total_count++;
//更新当前连出值
current_continuous_count++;
//更新最大遗漏值
if (current_miss_count > max_miss_count)
{
max_miss_count = current_miss_count;
}
current_miss_count = 0;
}
else
{
//为默认值即为不是中奖号遗漏值
//更新当前
current_miss_count++;
//更新最大连出值
if (current_continuous_count > max_continuous_count)
{
max_continuous_count = current_continuous_count;
}
current_continuous_count = 0;
}
}
totals.Add(total_count);
continuous.Add(max_continuous_count);
max.Add(max_miss_count);
avg.Add(total_count != 0 ? (last_row - total_count) / total_count : 0);
}
List <g_game_ball_result> summaryDatas = new List <g_game_ball_result>();
for (int i = 0; i < prize_balls_count; i++)
{
List <int> _totals = totals.Skip(i * total_balls_count).Take(total_balls_count).ToList();
List <int> _continuous = continuous.Skip(i * total_balls_count).Take(total_balls_count).ToList();
List <int> _max = max.Skip(i * total_balls_count).Take(total_balls_count).ToList();
List <int> _avg = avg.Skip(i * total_balls_count).Take(total_balls_count).ToList();
g_game_ball_result total_data = new g_game_ball_result();
g_game_ball_result continue_data = new g_game_ball_result();
g_game_ball_result max_data = new g_game_ball_result();
g_game_ball_result avg_data = new g_game_ball_result();
total_data.game_type_id = gameTypeId;
total_data.expect_no = expect_no;
total_data.b_no = i + 1;
total_data.category = 1;
avg_data.game_type_id = gameTypeId;
avg_data.expect_no = expect_no;
avg_data.b_no = i + 1;
avg_data.category = 2;
max_data.game_type_id = gameTypeId;
max_data.expect_no = expect_no;
max_data.b_no = i + 1;
max_data.category = 3;
continue_data.game_type_id = gameTypeId;
continue_data.expect_no = expect_no;
continue_data.b_no = i + 1;
continue_data.category = 4;
DynmicAssignment(total_data, _totals, total_balls_count);
DynmicAssignment(continue_data, _continuous, total_balls_count);
DynmicAssignment(max_data, _max, total_balls_count);
DynmicAssignment(avg_data, _avg, total_balls_count);
summaryDatas.Add(total_data);
summaryDatas.Add(avg_data);
summaryDatas.Add(max_data);
summaryDatas.Add(continue_data);
}
if (summaryDatas.Count > 0)
{
analysis.Insert(summaryCount, summaryDatas);
}
#endregion
}
}
}
