public bool UseOutlierTrimmingAnalyzer()
        {
            bool result = true;

            foreach (KeyValuePair <string, double[]> entry in Dic_noiseFpiArr)
            {
                // do something with entry.Value or entry.Key
                OutlierTrimmingAnalyzer OtaFpi = new OutlierTrimmingAnalyzer();
                result &= OtaFpi.SetOriginalSeriesAndDoAnalysis(entry.Value);
                OtaFpi.GetConfidenceIntervals(out double LowerFpi, out double UpperFpi);
                Dic_FpiLower.TryAdd(entry.Key, LowerFpi);
                Dic_FpiUpper.TryAdd(entry.Key, UpperFpi);
                //StoreArrayAsResultCsv(LowerFpi, UpperFpi, "Ota\\" + "OtaFpi_" + entry.Key);
            }

            Efa_Dic_Double_Double_Ota Ea = new Efa_Dic_Double_Double_Ota();

            Ea.FilePath = AppDomain.CurrentDomain.BaseDirectory
                          + "Result\\Result_Summary\\" + "Result_Auto_Data_Ota" + ".xlsx";
            Ea.SheetName    = "Ota";
            Ea.Dic_FpiLower = Dic_FpiLower;
            Ea.Dic_FpiUpper = Dic_FpiUpper;
            Ea.CreateExcel();

            return(result);
        }
Пример #2
0
        public void UC01_RemainingErrorData()
        {
            double[] RemainingErrorComponent = new double[] {
                0.06, 0.04, -0.68, 1.14, 0.12, 0.12, -0.09, -0.31, -0.40, -0.29, 0.40, 0.38, -0.66, 0.09, 0.69, -0.39, -0.40, -0.10, 0.37, -0.52, -0.56, 0.82, 0.32, -0.49, -0.12, 0.43, 0.73, -0.68, -0.21, 0.88, 0.14, -0.68, 0.62, -0.73, 0.51, -0.46, -0.21, -0.52, 0.74, 0.28, -0.09, -0.20, 0.50, -0.59, -0.32, -0.60, 0.18, 0.61, 0.30, -0.16, 0.14, -0.81, 0.82, 0.26, -1.59, -0.48, 0.72, -0.54, 1.22, 0.23, -0.66, 0.37, 0.77, -0.41, -0.98, -0.93, 2.06, -0.34, -0.70, 1.13, 0.74, -0.39, -0.82, -0.56, -0.49, 0.53, 1.44, -0.32, 0.12, 1.18, 0.08, -0.61, -0.42, -0.39, -0.52, -0.69, 0.48, 0.89, 0.93, -0.49, -1.38, 0.23, 0.26, -0.02, 1.00, -0.52, -0.50, 0.13, 0.20, 0.16, 0.52, -0.60, 0.48, -0.54, -0.63, 0.30, 0.34, 0.48, 0.60, -0.39, -0.31, -0.33, 0.22, 0.16, -1.38, 0.47, 0.73, -0.30, 0.20, -0.63, 0.13, -0.26, -0.09, 0.17, 0.04, 0.11, 0.42, -0.13, -0.60, 0.00, 0.09, 0.40, -0.37, -0.18, 0.42, -0.27, 0.22, -0.69, 0.60, 0.76, -0.04, -0.66, 0.26, 0.39, 0.26, -0.68, 0.29, -0.22, -0.62, -0.18, -0.31, 0.01, 0.43, -0.02, 0.60, -0.28, -0.07, 0.56, -0.38, -0.28, 0.27, -0.36, -0.22, -0.17, -0.23, 0.09, 0.27, -0.34, 0.28, -0.18, 0.58, 0.68, -0.12, 0.12, 0.10, -0.60, 0.20, -0.34, 0.13, 0.16, -0.34, -0.09, 0.88, -0.70, -0.26, 0.30, 0.03, -0.36, 0.04, 0.56, -0.31, 0.09, -0.18, 0.62, -0.47, -0.46, 0.23, -0.42, 0.60, -0.04, -0.89, -0.34, 0.77, 0.66, -0.68, -0.26, -0.63, -0.41, -0.90, 0.13, 0.07, -0.66, 1.26, 0.17, -0.73, -1.11, -0.81, 2.11, 2.87, -0.26, -0.89, 2.59, 3.40, 1.19, 2.20, -2.90, -3.27, -1.96, 0.50, -0.98, -2.06, -0.99, 2.68, 1.23, -1.74, 0.61, -0.90, -1.00, 0.81, 1.09, 1.61, 0.10, -1.29, 0.10, -0.39, -2.54, -1.91, 0.24, 0.54, 0.80, -0.22, 0.28, 1.11, 2.66, -1.23, 0.77, 0.12, 0.36, -0.24, 1.13, 0.63, -1.54, 0.91, -1.72, -1.39, 1.06, 1.53, 1.72, -1.61, -3.83, 1.11, 0.59, 1.21, 0.02, -0.09, -0.42, 0.19, 0.09, -0.03, 0.37, 0.47, 0.71, -0.57, -1.29, -0.87, 0.86, 0.64, 0.24, -1.89, -0.58, 1.70, 0.42, 0.88, 0.67, 0.34, -0.26, -1.44, 0.33, 1.10, 0.61, -0.78, -0.17, -0.94, -0.67, 0.24, 0.57, 1.18, -1.43, -0.83, 1.37, -0.30, 0.11, -1.32, -0.54, -0.17, -0.07, -0.31, 1.23, -0.77, 0.43, 0.60, 0.13, -0.11, -1.16, 0.87, 1.18, -0.48, -1.41, 0.20, -0.18, 1.03, -0.14, 0.43, 0.01, 0.69, -1.06, -0.68, 0.06, 0.68, 0.12, 0.76, -0.02, -0.93, 0.76, -0.04, -0.12, -0.58, -0.54, 0.17, 0.62, -0.44, -0.26, -0.09, 0.62, 0.50, -0.37, -1.37, -0.84, 0.38, 1.02, 2.28, 0.87, -0.73, -1.18, -1.49, 0.90
            };
            double[] Outliers = new double[] { };
            double   Lower;
            double   Upper;
            double   Mad;

            OutlierTrimmingAnalyzer Oti = new OutlierTrimmingAnalyzer();

            Oti.SetOriginalSeriesAndDoAnalysis(RemainingErrorComponent);
            Oti.GetMad(out Mad);
            Oti.GetConfidenceIntervals(out Lower, out Upper);
            Oti.GetOutliers(out Outliers);
        }
        public bool UseOutlierTrimmingAnalyzer()
        {
            bool result = true;

            OutlierTrimmingAnalyzer OtaFpi = new OutlierTrimmingAnalyzer();

            result &= OtaFpi.SetOriginalSeriesAndDoAnalysis(noiseFpi);
            OtaFpi.GetConfidenceIntervals(out LowerFpi, out UpperFpi);
            StoreArrayAsResultCsv(LowerFpi, UpperFpi, "OtaFpi");

            OutlierTrimmingAnalyzer OtaMpi = new OutlierTrimmingAnalyzer();

            result &= OtaMpi.SetOriginalSeriesAndDoAnalysis(noiseMpi);
            OtaMpi.GetConfidenceIntervals(out LowerMpi, out UpperMpi);
            StoreArrayAsResultCsv(LowerMpi, UpperMpi, "OtaMpi");

            OutlierTrimmingAnalyzer OtaDpi = new OutlierTrimmingAnalyzer();

            result &= OtaDpi.SetOriginalSeriesAndDoAnalysis(noiseDpi);
            OtaDpi.GetConfidenceIntervals(out LowerDpi, out UpperDpi);
            StoreArrayAsResultCsv(LowerDpi, UpperDpi, "OtaDpi");

            OutlierTrimmingAnalyzer OtaCpi = new OutlierTrimmingAnalyzer();

            result &= OtaCpi.SetOriginalSeriesAndDoAnalysis(noiseCpi);
            OtaCpi.GetConfidenceIntervals(out LowerCpi, out UpperCpi);
            StoreArrayAsResultCsv(LowerCpi, UpperCpi, "OtaCpi");

            OutlierTrimmingAnalyzer OtaOpi = new OutlierTrimmingAnalyzer();

            result &= OtaOpi.SetOriginalSeriesAndDoAnalysis(noiseOpi);
            OtaOpi.GetConfidenceIntervals(out LowerOpi, out UpperOpi);
            StoreArrayAsResultCsv(LowerOpi, UpperOpi, "OtaOpi");

            OutlierTrimmingAnalyzer OtaSpi = new OutlierTrimmingAnalyzer();

            result &= OtaSpi.SetOriginalSeriesAndDoAnalysis(noiseSpi);
            OtaSpi.GetConfidenceIntervals(out LowerSpi, out UpperSpi);
            StoreArrayAsResultCsv(LowerSpi, UpperSpi, "OtaSpi");

            return(result);
        }