/// <summary>
/// 两个文件合并，本方法只适合计算站点不重复,且不相关的情况。
/// 信息只是简单的叠加。只有两个文件都有的信息块才会被合并。
/// </summary>
/// <param name="fileB"></param>
/// <param name="eraseNonCoord"> 是否清理非坐标的值和对应矩阵</param>
public static SinexFile Merge(SinexFile fileA, SinexFile fileB, bool eraseNonCoord = true)
{
if (eraseNonCoord)
{
fileA.CleanNonCoordSolutionValue();
fileB.CleanNonCoordSolutionValue();
}
SinexFile newFile = EmergeBasic(fileA, fileB);
//合并解算结果，不更新标准差
SinexMerger.MergeSolutionValue(newFile.SolutionEstimateBlock, fileA.SolutionEstimateBlock, fileB.SolutionEstimateBlock);
SinexMerger.MergeSolutionValue(newFile.SolutionAprioriBlock, fileA.SolutionAprioriBlock, fileB.SolutionAprioriBlock);
//统计数据的合并, 需要做一些叠加工作。
SinexStatistic statisticA = fileA.GetStatistic();
SinexStatistic statisticB = fileB.GetStatistic();
if (fileA.SolutionStattisticsBlock != null && fileB.SolutionStattisticsBlock != null)
{
newFile.SolutionStattisticsBlock.Items = fileA.GetStatistic().Merge(fileB.GetStatistic()).GetSolutionStatistics();
}
SinexStatistic statisticNew = newFile.GetStatistic();
double varFactorA = statisticNew.VarianceOfUnitWeight / statisticA.VarianceOfUnitWeight;
double varFactorB = statisticNew.VarianceOfUnitWeight / statisticB.VarianceOfUnitWeight;
//合并矩阵，协方差矩阵,前面已经判断并重新布置matrix了，此处只管合并。
MergeSolutionMatrix(newFile.SolutionMatrixEstimateCova, fileA.SolutionMatrixEstimateCova, varFactorA, fileB.SolutionMatrixEstimateCova, varFactorB, newFile.SolutionEstimateBlock);
MergeSolutionMatrix(newFile.SolutionMatrixAprioriCova, fileA.SolutionMatrixAprioriCova, varFactorA, fileB.SolutionMatrixAprioriCova, varFactorB, newFile.SolutionAprioriBlock);
return(newFile);
}
public static List <SolutionStatistic> GetSolutionStatistics(SinexStatistic sta)
{
List <SolutionStatistic> list = new List <SolutionStatistic>();
list.Add(new SolutionStatistic()
{
Name = StatisticLabel.CODE_MEASUREMENTS_SIGMA,
Val = sta.CodeMeasurementsSigma
});
list.Add(new SolutionStatistic()
{
Name = StatisticLabel.NUMBER_OF_DEGREES_OF_FREEDOM,
Val = sta.NumberOfDegreesOfFreedom
});
list.Add(new SolutionStatistic()
{
Name = StatisticLabel.NUMBER_OF_OBSERVATIONS,
Val = sta.NumberOfObservations
});
list.Add(new SolutionStatistic()
{
Name = StatisticLabel.NUMBER_OF_UNKNOWNS,
Val = sta.NumberOfUnknown
});
list.Add(new SolutionStatistic()
{
Name = StatisticLabel.PHASE_MEASUREMENTS_SIGMA,
Val = sta.PhaseMeasurementsSigma
});
list.Add(new SolutionStatistic()
{
Name = StatisticLabel.SAMPLING_INTERVAL_SECONDS,
Val = sta.SamplingIntervalSeconds
});
list.Add(new SolutionStatistic()
{
Name = StatisticLabel.SQUARE_SUM_OF_RESIDUALS_VTPV,
Val = sta.SquareSumOfResidualsVTPV
});
list.Add(new SolutionStatistic()
{
Name = StatisticLabel.VARIANCE_FACTOR,
Val = sta.VarianceOfUnitWeight
});
list.Add(new SolutionStatistic()
{
Name = StatisticLabel.WEIGHTED_SQUARE_SUM_OF_O_C,
Val = sta.WeightedSqureSumOfOMinusC
});
return(list);
}
/// <summary>
/// 获取统计信息
/// </summary>
/// <returns>文件统计信息</returns>
public SinexStatistic GetStatistic()
{
SinexStatistic sta = new SinexStatistic();
if (SolutionStattisticsBlock == null)
{
return(sta);
}
foreach (var item in SolutionStattisticsBlock.Items)
{
if (item.Name.Contains(StatisticLabel.CODE_MEASUREMENTS_SIGMA))
{
sta.CodeMeasurementsSigma = item.Val;
}
if (item.Name.Contains(StatisticLabel.NUMBER_OF_DEGREES_OF_FREEDOM))
{
sta.NumberOfDegreesOfFreedom = item.Val;
}
if (item.Name.Contains(StatisticLabel.NUMBER_OF_OBSERVATIONS))
{
sta.NumberOfObservations = item.Val;
}
if (item.Name.Contains(StatisticLabel.NUMBER_OF_UNKNOWNS))
{
sta.NumberOfUnknown = item.Val;
}
if (item.Name.Contains(StatisticLabel.PHASE_MEASUREMENTS_SIGMA))
{
sta.PhaseMeasurementsSigma = item.Val;
}
if (item.Name.Contains(StatisticLabel.SAMPLING_INTERVAL_SECONDS))
{
sta.SamplingIntervalSeconds = item.Val;
}
if (item.Name.Contains(StatisticLabel.SQUARE_SUM_OF_RESIDUALS_VTPV))
{
sta.SquareSumOfResidualsVTPV = item.Val;
}
if (item.Name.Contains(StatisticLabel.VARIANCE_FACTOR))
{
sta.VarianceOfUnitWeight = item.Val;
}
if (item.Name.Contains(StatisticLabel.WEIGHTED_SQUARE_SUM_OF_O_C))
{
sta.WeightedSqureSumOfOMinusC = item.Val;
}
}
return(sta);
}
/// <summary>
/// 合并两个统计信息产生一个新的。
/// 本方法假定两文件观测内容不重复，且独立不相关。
/// 单位权方差 = （单位权方差A * 自由度A + 单位权方差B * 自由度B）/（自由度A + 自由度B）
/// </summary>
/// <param name="one"></param>
/// <param name="other"></param>
/// <returns></returns>
public static SinexStatistic Merge(SinexStatistic one, SinexStatistic other)
{
return(new SinexStatistic()
{
NumberOfObservations = one.NumberOfObservations + other.NumberOfObservations,
NumberOfUnknown = one.NumberOfUnknown + other.NumberOfUnknown,
NumberOfDegreesOfFreedom = one.NumberOfDegreesOfFreedom + other.NumberOfDegreesOfFreedom,
VarianceOfUnitWeight = (one.VarianceOfUnitWeight * one.NumberOfDegreesOfFreedom
+ other.VarianceOfUnitWeight * other.NumberOfDegreesOfFreedom)
/ (one.NumberOfDegreesOfFreedom + other.NumberOfDegreesOfFreedom),
//以下处理方式尚未明确正确与否
CodeMeasurementsSigma = one.CodeMeasurementsSigma,
WeightedSqureSumOfOMinusC = one.WeightedSqureSumOfOMinusC,
PhaseMeasurementsSigma = one.PhaseMeasurementsSigma,
SamplingIntervalSeconds = one.SamplingIntervalSeconds,
SquareSumOfResidualsVTPV = one.SquareSumOfResidualsVTPV,
//PhaseMeasurementsSigma =
// (one.PhaseMeasurementsSigma * one.NumberOfDegreesOfFreedom
// + other.PhaseMeasurementsSigma * other.NumberOfDegreesOfFreedom)
// / (one.NumberOfDegreesOfFreedom + other.NumberOfDegreesOfFreedom),
});
}
/// <summary>
/// 合并两个统计信息产生一个新的。
/// 本方法假定两文件观测内容不重复，且独立不相关。
/// </summary>
/// <param name="other"></param>
public SinexStatistic Merge(SinexStatistic other)
{
return(Merge(this, other));
}
