/// <summary>
/// 分析一段日期的历史趋势，（通过号码集合分析历史趋势）
/// </summary>
/// <param name="dto"></param>
/// <returns></returns>
public List <FactorTrendCorrectRate> AnalyseHistoricalTrend(PermutationFactorHistoricalTrendAnalyseDto <byte> dto)
{
var trends = new List <FactorTrendCorrectRate>();
if (dto.Numbers.Count < dto.AnalyseNumberCount)
{
throw new Exception("分析历史趋势时，分析记录数量不能大于记录数量！");
}
var analyseNumbers = dto.Numbers.OrderByDescending(n => n.TimesValue).Skip(0).Take(dto.AnalyseNumberCount).ToList();
var factorResultDict = new Dictionary <int, List <PermutationFactorTrendConsecutiveDetails <byte> > >();
//先记录分析结果
for (int i = 0, maxCount = analyseNumbers.Count; i < maxCount; i++)
{
var timesValue = analyseNumbers[i].TimesValue;
var numbers = dto.Numbers.Where(n => n.TimesValue < timesValue).Select(n => n.Number).ToList();
var factorResults = Analyse(new PermutationFactorTrendAnalyseDto <byte>
{
Numbers = numbers,
PermutationFactors = dto.PermutationFactors,
AllowMinTimes = dto.AllowMinTimes,
NumbersTailCutCount = dto.NumbersTailCutCount,
AllowMinFactorCurrentConsecutiveTimes = dto.StartAllowMinFactorCurrentConsecutiveTimes,
AllowMaxInterval = dto.StartAllowMaxInterval
});
factorResultDict.Add(i, factorResults);
}
//允许的连续次数，由小到大
for (var consecutiveTimes = dto.StartAllowMinFactorCurrentConsecutiveTimes; consecutiveTimes <= dto.EndAllowMinFactorCurrentConsecutiveTimes; consecutiveTimes++)
{
//允许的间隔数，由大到小
for (var interval = dto.StartAllowMaxInterval; interval >= dto.EndAllowMaxInterval; interval--)
{
var resultCount = 0;
var successCount = 0;
var trend = new FactorTrendCorrectRate
{
//HistoricalTrendType = dto.HistoricalTrendType,
StartTimes = analyseNumbers[0].TimesValue,
//Items = new List<HistoricalTrendItem>(),
Location = dto.Location,
AllowConsecutiveTimes = consecutiveTimes,
AllowInterval = interval,
AnalyseNumberCount = dto.AnalyseNumberCount,
TypeDescription = dto.TypeDescription
};
trends.Add(trend);
for (int i = 0, maxCount = analyseNumbers.Count; i < maxCount; i++)
{
var number = analyseNumbers[i].Number;
var times = analyseNumbers[i].Times;
var factorResults = factorResultDict[i];
//结果是否正确
var success = false;
//对结果再分析
//1、按允许的最小因子当前连续次数和允许的最大间隔次数筛选
//2、先按最大连续次数然后按最小间隔次数排序
factorResults = factorResults
.Where(m => m.FactorCurrentConsecutiveTimes >= consecutiveTimes && m.Interval <= interval)
.OrderByDescending(t => t.FactorCurrentConsecutiveTimes)
.ThenBy(t => t.Interval).ToList();
var factorResult = factorResults.OrderByDescending(t => t.FactorCurrentConsecutiveTimes).FirstOrDefault();
if (factorResult == null)
{
continue;
}
var resultConsecutiveTimes = factorResult.FactorCurrentConsecutiveTimes;
var resultInterval = factorResult.Interval;
if (factorResult.PredictiveFactor != null && factorResult.PredictiveFactor.Count > 0)
{
resultCount++;
if (factorResult.PredictiveFactor.Contains(number))
{
successCount++;
success = true;
}
}
var trendItem = new HistoricalTrendItem
{
Times = times,
Number = number,
Success = success,
ResultConsecutiveTimes = resultConsecutiveTimes,
ResultInterval = resultInterval,
PredictiveFactor = factorResult.PredictiveFactor
};
//trend.Items.Add(trendItem);
/* 分析结果为也作记录
* var factorResult = factorResults.OrderByDescending(t => t.MaxConsecutiveTimes).FirstOrDefault();
* var factors = new List<byte>();
* var resultConsecutiveTimes = 0;
* var resultInterval = 0;
* if (factorResult != null)
* {
* factors = factorResult.PredictiveFactor;
* resultConsecutiveTimes = factorResult.MaxConsecutiveTimes;
* resultInterval = factorResult.MaxInterval;
* if (factorResult.PredictiveFactor != null && factorResult.PredictiveFactor.Count > 0)
* {
* resultCount++;
*
* if (factors.Contains(number))
* {
* successCount++;
* success = true;
* }
* }
* }
*
* var trendItem = new HistoricalTrendItem
* {
* Times = times,
* Number = number,
* Success = success,
* ResultConsecutiveTimes = resultConsecutiveTimes,
* ResultInterval = resultInterval,
* PredictiveFactor = factors
* };
*
* trend.Items.Add(trendItem);
*/
}
trend.AnalyticalCount = resultCount;
trend.CorrectCount = successCount;
trend.CorrectRate = trend.AnalyticalCount == 0 ? 0 : (double)trend.CorrectCount / trend.AnalyticalCount;
}
}
return(trends);
}
public List <FactorTrendCorrectRate> AnalyseHistoricalTrend_Old(PermutationFactorHistoricalTrendAnalyseDto <byte> dto)
{
var trends = new List <FactorTrendCorrectRate>();
if (dto.Numbers.Count < dto.AnalyseNumberCount)
{
throw new Exception("分析历史趋势时，分析记录数量不能大于记录数量！");
}
var analyseNumbers = dto.Numbers.OrderByDescending(n => n.TimesValue).Skip(0).Take(dto.AnalyseNumberCount).ToList();
//允许的连续次数，由小到大
for (var consecutiveTimes = dto.StartAllowMinFactorCurrentConsecutiveTimes; consecutiveTimes <= dto.EndAllowMinFactorCurrentConsecutiveTimes; consecutiveTimes++)
{
//允许的间隔数，由大到小
for (var interval = dto.StartAllowMaxInterval; interval >= dto.EndAllowMaxInterval; interval--)
{
var resultCount = 0;
var successCount = 0;
var trend = new FactorTrendCorrectRate
{
//HistoricalTrendType = dto.HistoricalTrendType,
StartTimes = analyseNumbers[0].TimesValue,
//Items = new List<HistoricalTrendItem>(),
Location = dto.Location,
AllowConsecutiveTimes = consecutiveTimes,
AllowInterval = interval,
AnalyseNumberCount = dto.AnalyseNumberCount,
TypeDescription = dto.TypeDescription
};
trends.Add(trend);
for (int i = 0, maxCount = analyseNumbers.Count; i < maxCount; i++)
{
var number = analyseNumbers[i].Number;
var times = analyseNumbers[i].Times;
var timesValue = analyseNumbers[i].TimesValue;
var numbers = dto.Numbers.Where(n => n.TimesValue < timesValue).Select(n => n.Number).ToList();
var factorResults = Analyse(new PermutationFactorTrendAnalyseDto <byte>
{
Numbers = numbers,
AllowMinTimes = dto.AllowMinTimes,
NumbersTailCutCount = dto.NumbersTailCutCount,
AllowMinFactorCurrentConsecutiveTimes = consecutiveTimes,
AllowMaxInterval = interval,
PermutationFactors = dto.PermutationFactors
});
//结果是否正确
var success = false;
//对结果再分析
var factorResult = factorResults.OrderByDescending(t => t.FactorCurrentConsecutiveTimes).FirstOrDefault();
var factors = new List <byte>();
var resultConsecutiveTimes = 0;
var resultInterval = 0;
if (factorResult != null)
{
factors = factorResult.PredictiveFactor;
resultConsecutiveTimes = factorResult.FactorCurrentConsecutiveTimes;
resultInterval = factorResult.Interval;
if (factorResult.PredictiveFactor != null && factorResult.PredictiveFactor.Count > 0)
{
resultCount++;
if (factors.Contains(number))
{
successCount++;
success = true;
}
}
}
var trendItem = new HistoricalTrendItem
{
Times = times,
Number = number,
Success = success,
ResultConsecutiveTimes = resultConsecutiveTimes,
ResultInterval = resultInterval,
PredictiveFactor = factors
};
trend.AnalyticalCount = resultCount;
trend.CorrectCount = successCount;
trend.CorrectRate = trend.AnalyticalCount == 0 ? 0 : (double)trend.CorrectCount / trend.AnalyticalCount;
//trend.Items.Add(trendItem);
}
}
}
return(trends);
}
