示例#1
0
        static void Main(string[] args)
        {
            string filename = Environment.GetEnvironmentVariable("TSF_NET_DIR") + "Sample_Periodic\\NorwichTemp2.csv";
            Dictionary<string, List<double>> inputData = ParseCSVRows(filename);
            ExcelApplicationWrapper excelApp = new ExcelApplicationWrapper();
            excelApp.OpenExcel();

            foreach (string q1 in inputData.Keys)
            {

                string strTab = q1 + ", trends";
                if (strTab.Length > 30)
                {
                    strTab = strTab.Substring(0, 30);
                }

                int c_maxIter = 2;
                List<DateTime> timeline = null;
                List<double> data = inputData[q1];
                //Done extracting and aggregating data for query q1

                int periodicityHint = 12;

                //Step1. Detect deviant patterns and outlying spikes

                //A slower much more precise model builder commented out here
                //AAdAdrWithShocks modelBuilder = new AAdAdrWithShocks(periodicityHint, 0.1, (List<int>) null, null);
                //modelBuilder.InterferenceLag = 12;

                AAdArapidEventDetector modelBuilder = new AAdArapidEventDetector(periodicityHint);
                IList<EventImpactTrace> detectionHistory = null;
                bool fOK = modelBuilder.EventDetectionLoop(data, 0, c_maxIter, false,
                    out detectionHistory);

                int fcastRange = 12;
                IList<IScalarDistribution> fullForecast = null;
                HoltWintersMultithreadedDimensionalityReduction forecaster =
                    new HoltWintersMultithreadedDimensionalityReduction(periodicityHint);

                IList<double> paramtrs = null;
                IList<double> residuals = null;
                try
                {
                    //Example of "full service" forecast, with expected values and predict distributions
                    forecaster.SingleThreadForecast(data, 0, fcastRange, "NONPARAMETRIC", 0.0, double.MaxValue,
                        out paramtrs, out fullForecast, out residuals);
                }
                catch (Exception outerException)
                {
                }

                //Preparing for ... and using Excel middleware to generate Excel chart programmatically
                Dictionary<Timestamp, double> dictSigmas = null;
                Dictionary<Timestamp, double> dictMeans = null;
                List<Timestamp> timeIndex = null;
                MakeForecastOnlyDictionaries
                (data.Count, fullForecast, out timeIndex, out dictMeans, out dictSigmas);

                //Cosmetics tweak
                dictMeans.Add(new Timestamp(data.Count - 1), data.Last());

                AddExcelChart(excelApp, detectionHistory.Last(), q1,
                            MakeDataDictionary(timeIndex, data), dictMeans, dictSigmas);

            }
            //excelApp.CloseExcel(); //Uncomment to get the workbook closed automatically
        }