Example #1
0
        public override IExplorerView Run()
        {
            Logger.WriteLine("MovingAverageAnalysis.Run()");
            SeriesList list = Explorer.CreateSelectedSeries();

            ReadSeriesList(list);
            view.Messages.Add(list.MissingRecordsMessage);

            SeriesList myList = new SeriesList();

            for (int i = 0; i < list.Count; i++)
            {
                if (Explorer.PlotRaw)
                {
                    myList.Add(list[i]);
                }
                if (Explorer.PlotMoving24HourAverage)
                {
                    Series s24 = Math.MovingAvearge(list[i], 24);
                    myList.Add(s24);
                }
                if (Explorer.PlotMoving120HourAverage)
                {
                    Series s120 = Math.MovingAvearge(list[i], 120);
                    myList.Add(s120);
                }
            }
            view.Title = "Moving Average\n" + list.Text.TitleText();
            view.SubTitle = list.MissingRecordsMessage;

            view.SeriesList = myList;
            view.DataTable = myList.ToDataTable(true);
            return view;
        }
Example #2
0
        /// <summary>
        /// Creates a list of water year based data all aligned to year 2000
        /// to allow comparison.
        /// </summary>
        /// <param name="list">intput series</param>
        /// <param name="years">water years</param>
        /// <param name="avg30yr">when true also includes 30 year average. If only 5 years are avaliable a 5 year average is created</param>
        /// <param name="beginningMonth">series starting month number</param>
        /// <returns></returns>
        public static SeriesList WaterYears(SeriesList list, int[] years, bool avg30yr, int beginningMonth, bool alwaysShiftTo2000 = false)
        {
            SeriesList wySeries = new SeriesList();
            for (int j = 0; j < list.Count; j++)
            {
                for (int i = 0; i < years.Length; i++)
                {
                    YearRange yr = new YearRange(years[i], beginningMonth);
                    Series s = list[j];
                    s.Clear();
                    s.Read(yr.DateTime1, yr.DateTime2);

                    Logger.WriteLine("Read() " + yr.ToString() + " count = " + s.Count);

                    foreach (string msg in s.Messages)
                    {
                        Logger.WriteLine(msg);
                    }
                    if (s.Count > 0 && s.CountMissing() != s.Count)
                    {
                        Series s2 = TimeSeries.Math.ShiftToYear(s, 2000);
                        if (years.Length == 1 && !alwaysShiftTo2000 && !avg30yr)
                        {
                            s2 = s;
                        }
                        if (list.HasMultipleSites)
                            s2.Appearance.LegendText = years[i].ToString() + "   " + list[j].Name;
                        else
                            s2.Appearance.LegendText = years[i].ToString();
                        wySeries.Add(s2);
                    }
                    else
                    {
                        Logger.WriteLine("year :" + years[i] + "skipping series with no data " + s.Name + " " + s.Parameter);
                    }

                }
                if (avg30yr)
                {
                     list[j].Read(DateTime.Now.Date.AddYears(-30), DateTime.Now.Date);
                    Series s30 = Math.MultiYearDailyAverage( list[j], beginningMonth);
                    if (s30.Count > 0)
                        wySeries.Add(s30);
                }
            }
            wySeries.Type = SeriesListType.WaterYears;
            if (wySeries.Count > 1)
            {
                wySeries.DateFormat = "MM/dd";
            }

            return wySeries;
        }
Example #3
0
        public override IExplorerView Run()
        {
            Logger.WriteLine("SummaryHydrographAnalysis.Run()");
            SeriesList list = Explorer.CreateSelectedSeries();

            ReadSeriesList(list);

            if (Explorer.SelectedSeries.Length == 1 && Explorer.MergeSelected)
            { // merge single Year Traces.
                list.RemoveMissing();
                var s = list.MergeYearlyScenarios();
                list = new SeriesList();
                list.Add(s);
            }

            view.Messages.Add(list.MissingRecordsMessage);

            string title = list.Text.TitleText();
            string subTitle = list.MissingRecordsMessage;

            SeriesList myList = new SeriesList();
            list.RemoveMissing();

            if (Explorer.AlsoPlotYear && list.Count == 1)
            {
                YearRange yearRng = new YearRange(Explorer.PlotYear, Explorer.BeginningMonth);
                DateTime t1 = yearRng.DateTime1;
                DateTime t2 = yearRng.DateTime2;

                Series s = Math.Subset(list[0], t1, t2);
                s.Appearance.LegendText = yearRng.Year.ToString();
                view.Messages.Add(yearRng.Year.ToString() + " included as separate series ");
                myList.Add(s);
                myList.Add(list.SummaryHydrograph(Explorer.ExceedanceLevels, t1,
                    Explorer.PlotMax, Explorer.PlotMin, Explorer.PlotAvg,true));//,true));
            }
            else
            {
                DateTime t = new DateTime(DateTime.Now.Year, Explorer.BeginningMonth, 1);
                myList = list.SummaryHydrograph(Explorer.ExceedanceLevels, t,
                    Explorer.PlotMax, Explorer.PlotMin, Explorer.PlotAvg,true);//,true);
            }

            Explorer.WriteProgressMessage("drawing graph", 80);
            view.Title = title;
            view.SubTitle = subTitle;
            view.SeriesList = myList;
            view.DataTable = myList.ToDataTable(true);
            //view.Draw();
            return view;
        }
Example #4
0
        public override IExplorerView Run()
        {
            SeriesList list = Explorer.CreateSelectedSeries();

            ReadSeriesList(list);
            if (Explorer.SelectedSeries.Length == 1 && Explorer.MergeSelected)
            { // merge single Year Traces.
                var s = list.MergeYearlyScenarios();
                list = new SeriesList();
                list.Add(s);
            }

            SeriesList myList = list;
            if (Explorer.StatisticalMethods != StatisticalMethods.None)
            {
                myList = list.AggregateAndSubset(Explorer.StatisticalMethods,
                    Explorer.MonthDayRange, Explorer.BeginningMonth);
            }

            Logger.WriteLine("Drawing Graph");

            if (myList.Count == 1 && myList[0].TimeInterval == TimeInterval.Monthly)
            {
                myList.DateFormat = "MMM-yyyy";
            }
            view.SeriesList = myList;
            string title = list.Text.TitleText();
            if (Explorer.SubtractFromBaseline)
                title = "Subtract Reference \n" + title;
            view.Title = title;
            view.SubTitle = list.MissingRecordsMessage;
            //view.DataTable = myList.CompositeTable;
            return view;
        }
Example #5
0
        public static SeriesList GetSeries(string[] sites, UsgsRealTimeParameter parameter)
        {
            SeriesList rval = new SeriesList();
            foreach (string site in sites)
            {
                UsgsRealTimeSeries s = new UsgsRealTimeSeries(site, parameter);
                rval.Add(s);
            }

            return rval;
        }
Example #6
0
        public void PiecewisePolynomialRatingEquationLindCouleeWasteway1()
        {
            PolynomialEquation eq1 = new PolynomialEquation(
            new double[]{0.0},-1.0, 1.86 ,"-1 < stage <= 1.86 ");

              PolynomialEquation eq2 = new PolynomialEquation(
            new double[]{-28.4314,15.2857},1.861, 2.00," 1.86 < stage <= 2.0");

              PolynomialEquation eq3 = new PolynomialEquation(
            new double[]{-0.3522,88.1421,-96.6995,31.4217,-2.3978},2.001, 6.00," 2.0 < stage <= 6.0 ");

              PolynomialEquation eq4 = new PolynomialEquation(
            new double[]{-769.4138,249.0490},6.001, 10.00," 6.0 < stage ");

              PolynomialEquation[] equationList = {eq1,eq2,eq3,eq4};

              Series s  = TestData.LindCouleeWW1DailyAverageStage2004;
              Series instant = TestData.LindCouleeWW1InstantanousStage2004;

              DateTime t1 = new DateTime(2004,1,2);
              DateTime t2 = new DateTime(2004,12,18); // at 12:00 am.. will capture 17th..not 18 th

              // compute polynomial based on daily average stage.
              Series p = Math.Polynomial(s,equationList,t1,t2);

              // compute instantanious flow first
              Series p2 = Math.Polynomial(instant,equationList,t1,t2);
              // get average second
              Series avg = Math.TimeWeightedDailyAverage(p2);

              SeriesList list = new SeriesList();
              list.Add(s);
              list.Add(p);
              list.Add(avg);

              list.WriteToConsole();
               //p.WriteToConsole();
        }
Example #7
0
        public void LindCoulee2004()
        {
            Series s = TestData.LindCouleeWW1InstantanousStage2004;
             //Point pt =  Math.Calculator.AverageForDay(s,DateTime.Parse("2004-12-20"));
             Series avg = Math.TimeWeightedDailyAverage(s);
             // Console.WriteLine("avg");
              //avg.WriteToConsole();
              Console.WriteLine(avg[0].DateTime.ToString("yyyy-MM-dd HH:mm:ss.ffff"));

            Console.WriteLine("Math.Calculator.DailyAverage(s).Count = "+avg.Count);

            Series dbAverage = TestData.LindCouleeWW1DailyAverageStage2004;
            Console.WriteLine("TestData.LindCouleeWW1DailyAverageStage2004.Count = "+dbAverage.Count);

              Series diff = avg - dbAverage;
              SeriesList list = new SeriesList();
              list.Add(avg);
              list.Add(dbAverage);
              list.Add(diff);
              list.WriteToConsole();

              Console.WriteLine("summing difference");
              double d = Math.Sum(diff);
              Assert.AreEqual(0,d,0.1); // actual is about 0.05
              Console.WriteLine("sum of differences = "+d);
              Console.WriteLine("sum of daily "+Math.Sum(avg));
              Assert.AreEqual(dbAverage.Count-1,avg.Count);
              for(int i=0;i<avg.Count; i++)
              {
               // database has one (missing) value at beginning we skip that in comparison
            Assert.AreEqual(dbAverage[i+1].ToString(),avg[i].ToString());
            Assert.AreEqual(dbAverage[i+1].Value,avg[i].Value,0.0001);
            Assert.AreEqual(dbAverage[i+1].DateTime.Ticks , avg[i].DateTime.Ticks,"on line "+i);
              }
        }
Example #8
0
        private void buttonGetEspData_Click(object sender, EventArgs e)
        {
            this.toolStripStatusLabel1.Text = "Downloading ESP data...";
            this.UseWaitCursor = true;
            string rfcURL = @"https://www.nwrfc.noaa.gov/chpsesp/ensemble/";

            if (this.radioButtonNFcast.Checked)
            {
                rfcURL += "natural/";
            }
            else
            {
                rfcURL += "watersupply/";
            }
            rfcURL += this.textBoxRfcNode.Text + ".ESPF" + this.comboBoxEspDay.SelectedItem.ToString() + ".csv";

            HttpWebRequest  req           = (HttpWebRequest)WebRequest.Create(rfcURL);
            HttpWebResponse resp          = (HttpWebResponse)req.GetResponse();
            StreamReader    sr            = new StreamReader(resp.GetResponseStream());
            string          rfcDataString = sr.ReadToEnd();

            List <string> rfcData = new List <string>();

            string[] rfcDataRows = rfcDataString.Split('\n');
            //this.labelEspFile.Text = rfcDataRows[0].ToString().Replace("FILE:","");
            //this.labelEspUpdated.Text = rfcDataRows[1].ToString().Replace("ISSUED:", "");
            yearList = rfcDataRows[6].Split(',').ToList();
            int colCount = yearList.Count();
            // Build SeriesList container
            SeriesList sList = new SeriesList();

            for (int i = 1; i < colCount; i++)
            {
                Series s = new Series();
                s.Name = yearList[i].ToString();
                sList.Add(s);
            }
            // Populate Series List
            for (int i = 7; i < rfcDataRows.Count() - 1; i++)
            {
                var rowData = rfcDataRows[i].Split(',');
                var t       = DateTime.Parse(rowData[0]);
                for (int j = 1; j < colCount; j++)
                {
                    sList[j - 1].Add(t, Convert.ToDouble(rowData[j]) * 1000.0);
                }
            }
            // Aggregate Series List to Daily
            espList = new SeriesList();
            foreach (var series in sList)
            {
                var s = Reclamation.TimeSeries.Math.DailyAverage(series);
                s.Name = series.Name;
                espList.Add(s);
            }
            // Create statistical Series
            var sMin = new Series("MIN");
            var sMax = new Series("MAX");
            var sAvg = new Series("AVG");
            var sP10 = new Series("P10");
            var sP25 = new Series("P25");
            var sP50 = new Series("P50");
            var sP75 = new Series("P75");
            var sP90 = new Series("P90");

            foreach (Point pt in espList[0])
            {
                DateTime      ithT    = pt.DateTime;
                List <double> ithVals = new List <double>();
                foreach (Series s in espList)
                {
                    ithVals.Add(s[ithT].Value);
                }
                sMin.Add(ithT, ithVals.Min());
                sAvg.Add(ithT, ithVals.Average());
                sMax.Add(ithT, ithVals.Max());
                ithVals.Sort();
                sP10.Add(ithT, ithVals[Convert.ToInt32(System.Math.Floor(ithVals.Count * 0.10))]);
                sP25.Add(ithT, ithVals[Convert.ToInt32(System.Math.Floor(ithVals.Count * 0.25))]);
                sP50.Add(ithT, ithVals[Convert.ToInt32(System.Math.Floor(ithVals.Count * 0.50))]);
                sP75.Add(ithT, ithVals[Convert.ToInt32(System.Math.Floor(ithVals.Count * 0.75))]);
                sP90.Add(ithT, ithVals[Convert.ToInt32(System.Math.Floor(ithVals.Count * 0.90))]);
            }
            yearList.AddRange(new List <string> {
                "MIN", "P10", "P25", "P50", "P75", "P90", "MAX", "AVG"
            });
            espList.Add(new SeriesList()
            {
                sMin, sP10, sP25, sP50, sP75, sP90, sMax, sAvg
            });

            // Finalize
            FillEspDropDown();
            this.toolStripStatusLabel1.Text = "Downloaded " + rfcDataRows[0].ToString().Replace("FILE:", "") +
                                              ". Updated " + rfcDataRows[1].ToString().Replace("ISSUED:", "");
            this.UseWaitCursor = false;
        }
Example #9
0
        public override IExplorerView Run()
        {
            Logger.WriteLine("TraceAnalysis.Run()");
            SeriesList list = Explorer.CreateSelectedSeries();

            ReadSeriesList(list);
            string title    = list.Text.TitleText();
            string subTitle = list.MissingRecordsMessage;

            // [JR] don't perform trace analysis if trace count < 10...
            if (list.Count < 10)
            {
                view.Messages.Add("Trace exceedance analysis is not available if trace count < 10");
                view.Title      = title;
                view.SubTitle   = subTitle;
                view.SeriesList = list;
                view.DataTable  = list.ToDataTable(true);
                return(view);
            }

            // This seems to be common between all the analysis options
            if (Explorer.SelectedSeries.Length == 1 && Explorer.MergeSelected)
            { // merge single Year Traces.
                list.RemoveMissing();
                var s = list.MergeYearlyScenarios();
                list = new SeriesList();
                list.Add(s);
            }
            view.Messages.Add(list.MissingRecordsMessage);
            list.RemoveMissing();

            // Initialize the output container
            SeriesList traceAnalysisList = new SeriesList();

            // Get exceedance curves
            if (Explorer.traceExceedanceAnalysis)
            {
                traceAnalysisList = getTraceExceedances(list,
                                                        Explorer.ExceedanceLevels, Explorer.AlsoPlotTrace,
                                                        Explorer.PlotTrace, Explorer.PlotMinTrace,
                                                        Explorer.PlotAvgTrace, Explorer.PlotMaxTrace);
            }

            // Get aggregated values
            if (Explorer.traceAggregationAnalysis)
            {
                string sumType = "";
                if (Explorer.sumCYRadio)
                {
                    sumType = "CY";
                }
                else if (Explorer.sumWYRadio)
                {
                    sumType = "WY";
                }
                else if (Explorer.sumCustomRangeRadio)
                {
                    sumType = "XX";
                }
                else
                {
                }
                traceAnalysisList = getTraceSums(list, sumType);
            }

            // [JR] Add other analysis/report building options here...

            Explorer.WriteProgressMessage("drawing graph", 80);
            view.Title      = title;
            view.SubTitle   = subTitle;
            view.SeriesList = traceAnalysisList;
            view.DataTable  = traceAnalysisList.ToDataTable(true);
            //view.Draw();
            return(view);
        }
Example #10
0
        /// <summary>
        /// converts DMS3 formated data for 'dayflag.exe' prorgram into SeriesList
        /// each series is named  instant_cbtt_pcode,
        /// for example  instant_jck_fb
        /// </summary>
        /// <param name="fileName"></param>
        /// <returns></returns>
        public static SeriesList HydrometDMS3DataToSeriesList(TextFile tf)
        {
            var rval = new SeriesList();

            for (int i = 1; i < tf.Length; i++) // skip first row (header)
            {
                if (tf[i].Length < 59)
                {
                    Console.WriteLine("Skipping invalid line: " + tf[i]);
                    continue;
                }
                var strDate = tf[i].Substring(0, 14);

                DateTime t;
                if (!DateTime.TryParseExact(strDate, "yyyyMMMdd HHmm", new CultureInfo("en-US"), System.Globalization.DateTimeStyles.None, out t))
                {
                    Console.WriteLine("Bad Date, Skipping line: " + tf[i]);
                    continue;
                }
                string cbtt        = tf[i].Substring(15, 8).Trim();
                string pcode       = tf[i].Substring(24, 9).Trim();
                string strValue    = tf[i].Substring(34, 10);
                string strFlagCode = tf[i].Substring(56, 3);
                double val         = 0;

                if (!double.TryParse(strValue, out val))
                {
                    Console.WriteLine("Error parsing double " + strValue);
                    continue;
                }

                string name = "instant_" + cbtt + "_" + pcode;
                name = name.ToLower();
                var    idx = rval.IndexOfTableName(name);
                Series s;
                if (idx >= 0)
                {
                    s = rval[idx];
                }
                else
                {
                    s                 = new Series();
                    s.SiteID          = cbtt;
                    s.Parameter       = pcode;
                    s.Name            = cbtt + "_" + pcode;
                    s.Name            = s.Name.ToLower();
                    s.Table.TableName = name;
                    rval.Add(s);
                }

                string flag = DayFiles.FlagFromCode(strFlagCode);
                if (s.IndexOf(t) < 0)
                {
                    s.Add(t, val, flag);
                }
                else
                {
                    Logger.WriteLine(s.SiteID + ":" + s.Parameter + "skipped duplicate datetime " + t.ToString());
                }
            }

            return(rval);
        }
        internal Series ConvertToDaily()
        {
            Series estimatedDaily = new Series();

            estimatedDaily.HasFlags     = true;
            estimatedDaily.TimeInterval = TimeInterval.Daily;


            if (FillMissingWithZero)
            {
                daily = Math.FillMissingWithZero(daily, daily.MinDateTime, daily.MaxDateTime);
            }
            else
            {
                daily.RemoveMissing();
            }
            //daily.RemoveMissing();

            //int[] levels = {5,10,20,30,40,50,60,70,80,90,95};
            //int[] levels = {10,20,30,40,50,60,70,80,90};

            List <int> levels = new List <int>();

            if (MedianOnly)
            {
                levels.Add(50);
            }
            else
            {
                for (int i = 5; i <= 95; i += 2)
                {
                    levels.Add(i);
                }
            }

            var sHydrograph            = Math.SummaryHydrograph(daily, levels.ToArray(), new DateTime(2008, 1, 1), false, false, false, false);//, false);
            var summaryHydrographTable = sHydrograph.ToDataTable(true);

            for (int i = 1; i < summaryHydrographTable.Columns.Count; i++)
            {
                summaryHydrographTable.Columns[i].ColumnName = levels[i - 1].ToString();
            }

            //DataTableOutput.Write(summaryHydrographTable, @"c:\temp\junk.csv", false);


            SeriesList monthlySum = new SeriesList();

            for (int i = 0; i < sHydrograph.Count; i++)
            {
                Series sum = Math.MonthlyValues(sHydrograph[i], Math.Sum);
                sum.Name = levels[i].ToString();
                monthlySum.Add(sum);
            }

            var monthlyExceedanceSums = monthlySum.ToDataTable(true);

            if (monthlySum.Count == 1 && levels.Count == 1)
            {
                monthlyExceedanceSums.Columns[1].ColumnName = levels[0].ToString();
            }

            var monthlyTable = monthly.Table;

            DateTime t  = monthly.MinDateTime;
            DateTime t2 = monthly.MaxDateTime;

            t2 = new DateTime(t2.Year, t2.Month, DateTime.DaysInMonth(t2.Year, t2.Month));


            while (t < t2)
            {
                var tm = new DateTime(t.Year, t.Month, 1);
                if (monthly.IndexOf(tm) < 0)
                {
                    estimatedDaily.AddMissing(t);
                }
                else
                {
                    double mv                = monthly[tm].Value;
                    double mvcfsdays         = mv / 1.98347;
                    double exceedanceValue   = 0;
                    int    exceedancePercent = LookupExceedance(monthlyExceedanceSums, t, mvcfsdays, out exceedanceValue);
                    double ratio             = 0;
                    if (exceedanceValue != 0)
                    {
                        ratio = mvcfsdays / exceedanceValue;
                    }
                    else
                    {
                        ratio = 0;
                    }

                    double shcfs = LookupSummaryHydrograph(summaryHydrographTable, t, exceedancePercent);

                    estimatedDaily.Add(t, shcfs * ratio, "scaled with " + exceedancePercent + "%");
                }
                t = t.AddDays(1);
            }

            VerifyWithMonthlyVolume(monthly, estimatedDaily);
            //  SmoothSpikes(monthly, daily, estimatedDaily);

            return(estimatedDaily);
        }
Example #12
0
        public override IExplorerView Run()
        {
            Logger.WriteLine("SummaryHydrographAnalysis.Run()");
            SeriesList list = Explorer.CreateSelectedSeries();

            ReadSeriesList(list);


            if (Explorer.SelectedSeries.Length == 1 && Explorer.MergeSelected)
            { // merge single Year Traces.
                list.RemoveMissing();
                var s = list.MergeYearlyScenarios();
                list = new SeriesList();
                list.Add(s);
            }

            view.Messages.Add(list.MissingRecordsMessage);

            string title    = list.Text.TitleText();
            string subTitle = list.MissingRecordsMessage;



            SeriesList myList = new SeriesList();

            list.RemoveMissing();

            if (Explorer.AlsoPlotYear && list.Count == 1)
            {
                int[]    yearsToPlot   = Explorer.PlotYear;
                int      xtraYearCount = 0;
                DateTime tSumHyd1      = DateTime.Now;
                DateTime tSumHyd2      = DateTime.Now;
                foreach (var year in yearsToPlot)
                {
                    YearRange yearRng = new YearRange(year, Explorer.BeginningMonth);
                    DateTime  t1      = yearRng.DateTime1;
                    DateTime  t2      = yearRng.DateTime2;
                    Series    s       = Math.Subset(list[0], t1, t2);

                    if (xtraYearCount == 0)//first series
                    {
                        s.Appearance.LegendText = yearRng.Year.ToString();
                        view.Messages.Add(yearRng.Year.ToString() + " included as separate series ");
                        myList.Add(s);
                        if (yearsToPlot.Length == 1)
                        {
                            myList.Add(list.SummaryHydrograph(Explorer.ExceedanceLevels, t1, Explorer.PlotMax, Explorer.PlotMin, Explorer.PlotAvg, true));
                        }
                        else
                        {
                            myList.Add(list.SummaryHydrograph(new int[] { }, t1, false, false, false, true));
                        }
                        tSumHyd1 = t1;
                        tSumHyd2 = t2;
                    }
                    else//every series
                    {
                        Series sDummy = new Series();
                        foreach (Point pt in s)
                        {
                            if (!(pt.DateTime.Month == 2 && pt.DateTime.Day == 29))   //sigh... leap days...
                            {
                                sDummy.Add(pt.DateTime.AddYears(tSumHyd1.Year - t1.Year), pt.Value);
                            }
                        }
                        sDummy.TimeInterval          = s.TimeInterval;
                        sDummy.Name                  = s.Name;
                        sDummy.Units                 = s.Units;
                        sDummy.Parameter             = s.Parameter;
                        sDummy.Appearance.LegendText = yearRng.Year.ToString();;
                        view.Messages.Add(yearRng.Year.ToString() + " included as separate series ");
                        myList.Add(sDummy);
                        if (xtraYearCount == yearsToPlot.Length - 1)//last series
                        {
                            myList.Add(list.SummaryHydrograph(Explorer.ExceedanceLevels, tSumHyd1, Explorer.PlotMax, Explorer.PlotMin, Explorer.PlotAvg, true));
                        }
                        else
                        {
                            myList.Add(list.SummaryHydrograph(new int[] { }, tSumHyd1, false, false, false, true));
                        }
                    }
                    xtraYearCount++;
                }
            }
            else
            {
                DateTime t = new DateTime(DateTime.Now.Year, Explorer.BeginningMonth, 1);
                myList = list.SummaryHydrograph(Explorer.ExceedanceLevels, t,
                                                Explorer.PlotMax, Explorer.PlotMin, Explorer.PlotAvg, true);//,true);
            }

            Explorer.WriteProgressMessage("drawing graph", 80);
            view.Title      = title;
            view.SubTitle   = subTitle;
            view.SeriesList = myList;
            view.DataTable  = myList.ToDataTable(true);
            //view.Draw();
            return(view);
        }
Example #13
0
        private void ReadFromHydromet()
        {
            //DateTime t1 = startDate.AddDays(minOffset); // usually negative..

            SeriesList list = new SeriesList();
            for (int i = 0; i < cbtt.Length; i++)
            {
                HydrometDailySeries s =
                    new HydrometDailySeries(cbtt[i], pcode[i], this.server);
                DateTime t1 = startDate.AddDays(daysOffset[i]);
                DateTime t2 = t1.AddDays(dayCount[i] - 1);

                if (!hasCount[i])
                {
                    t2 = endDate;
                }

                if (dayCount[i] < 1 && hasCount[i])
                {
                    Console.WriteLine("Warning: The number of days requested was " + dayCount[i] + "from hydromet");
                }

                s.Read(t1, t2);
                if (s.Count < dayCount[i] && hasCount[0])
                {
                    Console.WriteLine("Warning: the requested hydromet data is missing.");
                }

                list.Add(s);
            }

            //Reclamation.PNHydromet.HydrometDaily.BulkRead(cbtt, pcode, t1, startDate, false,server);

            //FormPrevew p = new FormPrevew(list);
            //p.ShowDialog();

            WriteToRiverwareFiles(list);
        }
Example #14
0
        internal Series ConvertToDaily()
        {
            Series estimatedDaily = new Series();
            estimatedDaily.HasFlags = true;
            estimatedDaily.TimeInterval = TimeInterval.Daily;

            if (FillMissingWithZero)
            {
                daily = Math.FillMissingWithZero(daily, daily.MinDateTime, daily.MaxDateTime);
            }
            else
            {
                daily.RemoveMissing();
            }
            //daily.RemoveMissing();

            //int[] levels = {5,10,20,30,40,50,60,70,80,90,95};
            //int[] levels = {10,20,30,40,50,60,70,80,90};

            List<int> levels = new List<int>();

            if (MedianOnly)
            {
                levels.Add(50);
            }
            else
            {
                for (int i = 5; i <= 95; i += 2)
                {
                    levels.Add(i);
                }
            }

            var sHydrograph = Math.SummaryHydrograph(daily, levels.ToArray(), new DateTime(2008, 1, 1), false, false, false, false);//, false);
            var summaryHydrographTable = sHydrograph.ToDataTable(true);

            for (int i = 1; i < summaryHydrographTable.Columns.Count; i++)
            {
                summaryHydrographTable.Columns[i].ColumnName = levels[i - 1].ToString();
            }

            //DataTableOutput.Write(summaryHydrographTable, @"c:\temp\junk.csv", false);

            SeriesList monthlySum = new SeriesList();
            for (int i = 0; i < sHydrograph.Count; i++)
            {
                Series sum = Math.MonthlyValues(sHydrograph[i], Math.Sum);
                sum.Name = levels[i].ToString();
                monthlySum.Add(sum);
            }

            var monthlyExceedanceSums = monthlySum.ToDataTable(true);
            if (monthlySum.Count == 1 && levels.Count == 1)
                monthlyExceedanceSums.Columns[1].ColumnName = levels[0].ToString();

            var monthlyTable = monthly.Table;

            DateTime t = monthly.MinDateTime;
            DateTime t2 = monthly.MaxDateTime;
            t2 = new DateTime(t2.Year, t2.Month, DateTime.DaysInMonth(t2.Year, t2.Month));

            while (t < t2)
            {
                var tm = new DateTime(t.Year, t.Month, 1);
                if (monthly.IndexOf(tm) < 0)
                {
                    estimatedDaily.AddMissing(t);
                }
                else
                {
                    double mv = monthly[tm].Value;
                    double mvcfsdays = mv / 1.98347;
                    double exceedanceValue = 0;
                    int exceedancePercent = LookupExceedance(monthlyExceedanceSums, t, mvcfsdays, out exceedanceValue);
                    double ratio = 0;
                    if (exceedanceValue != 0)
                        ratio = mvcfsdays / exceedanceValue;
                    else
                        ratio = 0;

                    double shcfs = LookupSummaryHydrograph(summaryHydrographTable, t, exceedancePercent);

                    estimatedDaily.Add(t, shcfs * ratio,"scaled with "+exceedancePercent+"%");
                }
                t = t.AddDays(1);
            }

            VerifyWithMonthlyVolume(monthly, estimatedDaily);
              //  SmoothSpikes(monthly, daily, estimatedDaily);

            return estimatedDaily;
        }
Example #15
0
        /// <summary>
        /// Create a Series List 
        /// </summary>
        /// <param name="input"></param> input from the command line
        /// <param name="interval"></param> time interval 
        /// <returns></returns>
        private SeriesList CreateSeriesList(CommandLineInput input, TimeInterval interval)
        {
            List<TimeSeriesName> names = new List<TimeSeriesName>();
            foreach (var cbtt in input.SiteList)
            {
                foreach (var pcode in input.Parameters)
                {
                    string sInterval = TimeSeriesName.GetTimeIntervalForTableName(interval);
                    TimeSeriesName tn = new TimeSeriesName(cbtt + "_" + pcode,sInterval);
                    names.Add(tn);
                }
            }

            var tableNames = (from n in names select n.GetTableName()).ToArray();

            var sc = m_db.GetSeriesCatalog("tablename in ('" + String.Join("','", tableNames) + "')");

            SeriesList sList = new SeriesList();
            foreach (var tn in names)
            {
                Series s = new Series();

                s.TimeInterval = interval;
                if (sc.Select("tablename = '" + tn.GetTableName() + "'").Length == 1)
                {
                    s = m_db.GetSeriesFromTableName(tn.GetTableName());
                }
                s.Table.TableName = tn.GetTableName();
                sList.Add(s);
            }
            return sList;
        }
Example #16
0
        private void ReadFromPisces()
        {
            Logger.WriteLine("opening " + m_dbName);
            SQLiteServer svr = new SQLiteServer(m_dbName);
            TimeSeriesDatabase db = new TimeSeriesDatabase(svr);

            SeriesList list = new SeriesList();

            for (int i = 0; i < m_seriesName.Count; i++)
            {
                Logger.WriteLine("looking for series '" + m_seriesName[i] + "'");
                var s = db.GetSeriesFromName(m_seriesName[i]);
                if (s != null)
                {
                    s.Read(m_t1, m_t2);
                    list.Add(s);
                }
                else
                {
                    throw new Exception("unable to find series '" + m_seriesName[i] + "' in pisces database '" + m_dbName + "'");
                }
            }

            WriteToRiverwareFiles(list);
        }
Example #17
0
        /// <summary>
        /// MLR Interpolation Report
        /// Look for '[JR]' in this method to find the code regions that could use a fix or more testing...
        /// </summary>
        /// <param name="sInputs"></param>
        /// <param name="t1"></param>
        /// <param name="t2"></param>
        /// <param name="months"></param>
        /// <param name="fitTolerance"></param>
        /// <param name="waterYear"></param>
        public static MultipleLinearRegressionResults MlrInterpolation(SeriesList sList,
                                                                       int[] months, double fitTolerance, bool fillSelectedMonths = false)
        {
            // KT if there is not enough data (for example only 1 pont ) need to ignore that data set?

            MultipleLinearRegressionResults rval = new MultipleLinearRegressionResults();
            // Populate SeriesLists
            var sListFill = new SeriesList();

            foreach (var item in sList)
            {
                sListFill.Add(item.Copy());
            }

            // Get dates to be filled with interpolated values
            var missing = sList[0].GetMissing();

            if (fillSelectedMonths) //overwrites the 'missing' variable with another Series that only contains the selected dates in the input
            {
                Series missingSubset = new Series();
                foreach (var row in missing)
                {
                    if (months.Contains(row.DateTime.Month))
                    {
                        missingSubset.Add(row);
                    }
                }
                missing = missingSubset;
            }

            // Delete common dates where at least 1 data point is missing for any of the input series
            // This is done because the MLR routine does not support missing data. Missing data causes
            // data misalignments and throws off the regression... This section also deletes data for
            // months that are not tagged in the input
            for (int i = sList[0].Count - 1; i >= 0; i--) //start from the bottom of the list to bypass indexing problems
            {
                for (int j = 0; j < sList.Count; j++)
                {
                    Point jthPt = sList[j][i];
                    if (jthPt.IsMissing || !months.Contains(jthPt.DateTime.Month))
                    {
                        for (int k = 0; k < sList.Count; k++) //delete this date from all Series in the list
                        {
                            sList[k].RemoveAt(i);
                        }
                        break;
                    }
                }
            }

            // Initialize MLR report and populate header
            List <string> mlrOut = new List <string>();

            mlrOut.Add("");
            mlrOut.Add("MLR Output\t\t\t\t\tRun Date: " + DateTime.Now);
            mlrOut.Add("Estimated Series: " + sList[0].Name);
            var sEstimators = "";

            for (int i = 1; i < sList.Count; i++)
            {
                sEstimators = sEstimators + sList[i].Name + ", ";
            }
            mlrOut.Add("Estimator Series: " + sEstimators.Remove(sEstimators.Length - 2));
            mlrOut.Add("Regression Date Range: " + sList[0].MinDateTime + " - " + sList[0].MaxDateTime);
            var monEstimators = "";

            foreach (var item in months)
            {
                monEstimators = monEstimators + item + ", ";
            }
            mlrOut.Add("Months Used: " + monEstimators.Remove(monEstimators.Length - 2));
            mlrOut.Add("");
            mlrOut.Add("====================================================================================");


            // Initialize output SeriesList
            var sOutList = new SeriesList();

            // Loop through each SeriesList combination for MLR
            for (int k = 1; k <= sList.Count - 1; k++)
            {
                AllPossibleCombination combinationData = new AllPossibleCombination(sList.Count - 1, k); //uses StackOverflow Class for combinations
                var combinationList = combinationData.GetCombinations();
                // Loop through each combination in the list and run MLR
                foreach (var combo in combinationList)
                {
                    // Build MLR method inputs
                    // xData is the different Series values that will be used to generate the MLR equation, all index > 0 in the SeriesList. Matrix format
                    // yData is the target Series values that is the target for MLR, index = 0 of the SeriesList. Vector format
                    double[][] xData = new double[sList[0].Count][];
                    double[]   yData = new double[sList[0].Count];
                    // Loop through the dates to populate the xData and the yData
                    for (int i = 0; i < sList[0].Count; i++)
                    {
                        var jthRow = new List <double>();
                        // Loop through each Series in SeriesList
                        for (int j = 0; j < combo.Count(); j++)
                        {
                            jthRow.Add(sList[combo[j]][i].Value);
                        }
                        xData[i] = jthRow.ToArray();
                        yData[i] = sList[0][i].Value;
                    }

                    // MLR via Math.Net.Numerics
                    double[] mlrCoeffs = MathNet.Numerics.LinearRegression.MultipleRegression.QR(xData, yData, true); //this is more stable than the method below
                    //double[] p2 = MathNet.Numerics.Fit.MultiDim(xData, yData, true); //this method is faster but less stable

                    // Evaluate fit
                    Series sModeled = sList[0].Clone();
                    // Equations are of the form y = x1(s1) + x2(s2) + ... + xN the loop handles the inner part of the equation if it exists x2(s2) + ...
                    //          while the lines before and after the loop handles the first and last terms x1(s1) and xN respectively
                    sModeled = sList[combo[0]] * mlrCoeffs[1];
                    for (int i = 2; i < mlrCoeffs.Count(); i++)
                    {
                        sModeled = sModeled + sList[combo[i - 1]] * mlrCoeffs[i];
                    }                                                                                     //magic number -1 is used so the correct corresponding Series is used with the correct mlr-coefficient
                    sModeled = sModeled + mlrCoeffs[0];
                    var rVal = MathNet.Numerics.GoodnessOfFit.R(sModeled.Values, sList[0].Values);        //this is the statistic reported by the FORTRAN code
                    var rSqd = MathNet.Numerics.GoodnessOfFit.RSquared(sModeled.Values, sList[0].Values); //this is the R-squared for model fit

                    // Fill missing dates and generate a SeriesList for final Series output
                    var sOut = new Series(); //initialize Series to be added to output SeriesList
                    foreach (var fillT in missing)
                    {
                        double fillVal;
                        try
                        {
                            // This evaluates the equation generated during the MLR estimation. Same equation-code format as above
                            fillVal = sListFill[combo[0]][fillT.DateTime].Value * mlrCoeffs[1];
                            for (int i = 2; i < mlrCoeffs.Count(); i++)
                            {
                                fillVal = fillVal + sListFill[combo[i - 1]][fillT.DateTime].Value * mlrCoeffs[i];
                            }
                            fillVal = fillVal + mlrCoeffs[0];
                            if (fillVal < 0.0)
                            {
                                sOut.Add(fillT.DateTime, Point.MissingValueFlag, "NoDataForInterpolation");
                            }
                            else
                            {
                                sOut.Add(fillT.DateTime, fillVal, rVal.ToString("F05"));
                            }                                                            //[JR] this assigns the R value as the flag, can be switched to R-Squared...
                        }
                        catch
                        { sOut.Add(fillT.DateTime, Point.MissingValueFlag, "NoDataForInterpolation"); }
                    }
                    // Add the output Series to a SeriesList
                    sOutList.Add(sOut);

                    // Populate report
                    mlrOut.Add("");
                    string equationString = "MLR Equation: " + sList[0].Name + " = ";
                    for (int ithCoeff = 1; ithCoeff < mlrCoeffs.Count(); ithCoeff++)
                    {
                        equationString = equationString + mlrCoeffs[ithCoeff].ToString("F04") + "("
                                         + sList[combo[ithCoeff - 1]].Name + ") + ";
                    }
                    equationString = equationString + mlrCoeffs[0].ToString("F04");
                    mlrOut.Add(equationString);
                    mlrOut.Add("Correlation Coefficient = " + rVal.ToString("F04"));
                    mlrOut.Add("R-Squared Coefficient = " + rSqd.ToString("F04"));
                    mlrOut.Add("MLR Estimates: ");
                    foreach (var item in sOut)
                    {
                        mlrOut.Add("\t\t" + item.ToString(true));
                    }
                    mlrOut.Add("");
                    mlrOut.Add("------------------------------------------------------------------------------------");
                }
            }


            // Generate MLR report
            //TextFile tf = new TextFile(mlrOut.ToArray());
            //var fn = FileUtility.GetTempFileName(".txt");
            //tf.SaveAs(fn);
            //System.Diagnostics.Process.Start(fn);
            rval.Report = mlrOut.ToArray();

            // Generate output Series
            var sOutFinal = sListFill[0].Copy();

            // Rmove the Points to be filled in the original input Series
            for (int i = missing.Count - 1; i >= 0; i--)
            {
                sOutFinal.RemoveAt(sOutFinal.IndexOf(missing[i].DateTime));
            }
            // Find the best fit out of all the estimated values
            // Loops through the dates
            foreach (var sRow in sOutList[0])
            {
                DateTime      estT      = sRow.DateTime;
                List <double> flagItems = new List <double>(); //container for flag values
                List <double> valItems  = new List <double>(); //container for estiamted values
                // Loops through each estimate
                for (int i = 0; i < sOutList.Count; i++)
                {
                    Point estPt = sOutList[i][estT];
                    valItems.Add(estPt.Value);
                    if (estPt.Value < 0.0) //add 0 correlation value if the estimated value < 0, [JR] this prevents the use of this routine to estimate negative values...
                    {
                        flagItems.Add(0.0);
                    }
                    else
                    {
                        flagItems.Add(Convert.ToDouble(estPt.Flag));
                    }
                }
                var maxFit     = flagItems.Max();
                var bestFitVal = valItems[flagItems.IndexOf(maxFit)];
                if (maxFit >= fitTolerance) //add the value if it exceeds the specified tolerance
                {
                    sOutFinal.Add(estT, bestFitVal, "E");
                }
                else //add missing since there is no acceptable estimate to fill this missing value
                {
                    sOutFinal.AddMissing(estT);
                }
            }
            //return sOutFinal;

            rval.EstimatedSeries = sOutFinal;
            return(rval);
        }
Example #18
0
        public void HydrometAutoUpdate()
        {
            var t1 = new DateTime(1980, 10, 1);
            var t2 = new DateTime(1980, 10, 2);
            Series s1 = new Reclamation.TimeSeries.Hydromet.HydrometDailySeries("jck", "af");
            s1.Read(t1, t2);
            int sdi1 = db.AddSeries(s1);

            Series s2 = new Reclamation.TimeSeries.Hydromet.HydrometDailySeries("pal", "af");
            s2.Read(t1, t2);
            int sdi2 = db.AddSeries(s2);

            s1 = db.GetSeries(sdi1);
            s2 = db.GetSeries(sdi2);

            HydrometInfoUtility.AutoUpdate = true;
            t2 = t2.AddHours(24);// reservoir contents are stored at midnight
            Console.WriteLine(t2);
            s1.Read(t1, t2);
            s2.Read(t1, t2);

            s1.WriteToConsole();
            Assert.AreEqual(515150.0, s1[0].Value);
            Assert.AreEqual(817782.0, s2[0].Value);
            Assert.AreEqual(3, s1.Count);
            Assert.AreEqual(3, s2.Count);

            SeriesList sl = new SeriesList();
            sl.Add(s1);
            sl.Add(s2);
            SimpleMathSeries c1 = new SimpleMathSeries("",sl,new MathOperation[]{ MathOperation.Add});
            SimpleMathSeries c2 = new SimpleMathSeries("",sl, new MathOperation[] {MathOperation.Subtract});

            int sdi3 = db.AddSeries(c1);
            int sdi4 = db.AddSeries(c2);

            Series s3 = db.GetSeries(sdi3);
            Series s4 = db.GetSeries(sdi4);

            s3.Read(t1, t2);
            s4.Read(t1, t2);

            Assert.AreEqual(515150.0 + 817782.0, s3[0].Value);
            Assert.AreEqual(515150.0 - 817782.0, s4[0].Value);
        }
Example #19
0
 /// <summary>
 /// Update Selected Series or folders
 /// Enabled only for Series or Folders selected NOT both at the
 /// same time
 /// </summary>
 /// <param name="sender"></param>
 /// <param name="e"></param>
 private void toolStripMenuUpdate_Click(object sender, EventArgs e)
 {
     if (tree1.SelectedFolders.Length == 0)
     {
         Series[] list = tree1.GetSelectedSeries();
         ProcessSelectedSeries(SeriesProcess.Update,list);
     }
     else if (tree1.SelectedFolders.Length == 1)
     {
         SeriesList list = new SeriesList();
         foreach (Series s in tree1.GetSeriesRecursive())
         {
             list.Add(s);
         }
         ProcessSelectedSeries(SeriesProcess.Update, list.ToArray());
     }
     else
     {
         MessageBox.Show("Please select a single folder to update.");
     }
         
 }
Example #20
0
 private void CalculateClick(object sender, EventArgs e)
 {
     if (tree1.SelectedFolders.Length == 0)
     {
         Series[] list = tree1.GetSelectedSeries();
         ProcessSelectedSeries(SeriesProcess.Calculate,list);
     }
     else if (tree1.SelectedFolders.Length == 1)
     {
         SeriesList list = new SeriesList();
         foreach (Series s in tree1.GetSeriesRecursive())
         {
             if (s.Expression != "") // only perform calculations on calculation series with a valid expression
             { list.Add(s); }
         }
         if (list.Count > 0)
         { ProcessSelectedSeries(SeriesProcess.Calculate, list.ToArray()); }
         else
         {
             MessageBox.Show("No Calculation Series found in folder.");
             ClearDisplay();
             return;
         }
     }
     else
     {
         MessageBox.Show("Please select a single folder to calculate.");
         ClearDisplay();
         return;
     }
     
     //tree1_SelectionChanged(this, EventArgs.Empty);
     DrawBasedOnTreeSelection();
 }
Example #21
0
        public static Series MLRInterpolationPisces(double fitTolerance, params Series[] s)
        {
            SeriesList sList = new SeriesList();
            foreach (var item in s)
            { sList.Add(item); }
            var sOut = Reclamation.TimeSeries.Estimation.MultipleLinearRegression.MlrInterpolation(sList,
                new int[] { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 }, fitTolerance);

            return sOut.EstimatedSeries;
        }
        private void ClassificationScenario(TrainingParameters td, List <TrainingElement> data, List <TrainingElement> testData)
        {
            //translate class numbers to network-intelligible matrices
            for (int i = 0; i < data.Count; i++)
            {
                var output = data[i].DesiredOutput;
                switch (output.At(0, 0))
                {
                case 1:
                    output = Matrix <double> .Build.DenseOfArray(new double[, ] {
                        { 1 }, { 0 }, { 0 }
                    });

                    break;

                case 2:
                    output = Matrix <double> .Build.DenseOfArray(new double[, ] {
                        { 0 }, { 1 }, { 0 }
                    });

                    break;

                case 3:
                    output = Matrix <double> .Build.DenseOfArray(new double[, ] {
                        { 0 }, { 0 }, { 1 }
                    });

                    break;
                }
                data[i].DesiredOutput = output;
            }

            for (int i = 0; i < testData.Count; i++)
            {
                var output = testData[i].DesiredOutput;
                switch (output.At(0, 0))
                {
                case 1:
                    output = Matrix <double> .Build.DenseOfArray(new double[, ] {
                        { 1 }, { 0 }, { 0 }
                    });

                    break;

                case 2:
                    output = Matrix <double> .Build.DenseOfArray(new double[, ] {
                        { 0 }, { 1 }, { 0 }
                    });

                    break;

                case 3:
                    output = Matrix <double> .Build.DenseOfArray(new double[, ] {
                        { 0 }, { 0 }, { 1 }
                    });

                    break;
                }
                testData[i].DesiredOutput = output;
            }


            Network.Gatherer = new ClassificationGatherer(testData, data);

            int           iterations         = td.Iterat;
            List <double> errorsAverage      = new List <double>(new double[td.Epochs]);
            List <double> testerErrorAverage = new List <double>(new double[td.Epochs]);
            List <double> accuracyAveragesV  = new List <double>(new double[td.Epochs]);
            List <double> accuracyAveragesT  = new List <double>(new double[td.Epochs]);

            for (int i = 0; i < iterations; i++)
            {
                Network.Train(td.LearningRate, td.Epochs, td.Momentum, data);


                for (int j = 0; j < Network.Errors.Count; j++)
                {
                    errorsAverage[j]      += Network.Errors[j];
                    testerErrorAverage[j] += ((ClassificationGatherer)Network.Gatherer).TestErrors[j];
                    accuracyAveragesV[j]  += ((ClassificationGatherer)Network.Gatherer).AccuracyListV[j];
                    accuracyAveragesT[j]  += ((ClassificationGatherer)Network.Gatherer).AccuracyListT[j];
                }
            }

            //Calculate average properties
            for (int j = 0; j < Network.Errors.Count; j++)
            {
                errorsAverage[j]      /= iterations;
                testerErrorAverage[j] /= iterations;
                accuracyAveragesV[j]  /= iterations;
                accuracyAveragesT[j]  /= iterations;
            }

            IList <DataPoint> points           = new List <DataPoint>();
            IList <DataPoint> pointsTestError  = new List <DataPoint>();
            IList <DataPoint> pointsAccurracyV = new List <DataPoint>();
            IList <DataPoint> pointsAccuracyT  = new List <DataPoint>();

            for (int i = 0; i < Network.Errors.Count; i++)
            {
                points.Add(new DataPoint(i + 1, errorsAverage[i]));
                pointsTestError.Add(new DataPoint(i + 1, testerErrorAverage[i]));
                pointsAccuracyT.Add(new DataPoint(i + 1, accuracyAveragesT[i]));
                pointsAccurracyV.Add(new DataPoint(i + 1, accuracyAveragesV[i]));
            }

            //calculate error matrix
            List <Tuple <int, int> > DesiredAndActualOutputs = new List <Tuple <int, int> >();

            foreach (var telem in testData)
            {
                var desired = ((ClassificationGatherer)Network.Gatherer).ConvertMatrixToClass(telem.DesiredOutput);
                var gotten  = ((ClassificationGatherer)Network.Gatherer).ConvertMatrixToClass(Network.ForwardPropagation(telem.Input));
                DesiredAndActualOutputs.Add(new Tuple <int, int>(desired, gotten));
            }

            int[,] ErrorMatrix = new int[3, 3];

            foreach (var tupel in DesiredAndActualOutputs)
            {
                ErrorMatrix[tupel.Item1 - 1, tupel.Item2 - 1]++;
            }

            WindowDataGrid wdg = new WindowDataGrid(ErrorMatrix);

            wdg.Show();


            SeriesList.Add(new OxyPlot.Wpf.LineSeries
            {
                ItemsSource = points,
                Title       = $"Training error Learning rate: {td.LearningRate}, momentum: {td.Momentum}, hidden neuron count: {Network.Layers[0].NeuronCount}"
            });
            SeriesList.Add(new OxyPlot.Wpf.LineSeries
            {
                ItemsSource = pointsTestError,
                Title       = $"Validation error Learning rate: {td.LearningRate}, momentum: {td.Momentum}, hidden neuron count: {Network.Layers[0].NeuronCount}"
            });

            SeriesList2.Add(new OxyPlot.Wpf.LineSeries
            {
                ItemsSource = pointsAccuracyT,
                Title       = $"Training set accuracy Learning rate: {td.LearningRate}, momentum: {td.Momentum}, hidden neuron count: {Network.Layers[0].NeuronCount}"
            });
            SeriesList2.Add(new OxyPlot.Wpf.LineSeries
            {
                ItemsSource = pointsAccurracyV,
                Title       = $"Validation set accuracy Learning rate: {td.LearningRate}, momentum: {td.Momentum}, hidden neuron count: {Network.Layers[0].NeuronCount}"
            });
        }
Example #23
0
        /// <summary>
        /// Computes rule curve in terms of 'required' storage
        /// by subracting space from the total available space
        /// </summary>
        /// <param name="t1"></param>
        /// <param name="t2"></param>
        /// <param name="totalSpace"></param>
        /// <returns></returns>
        public SeriesList CalculateFixedRuleCurve(DateTime t1, DateTime t2,double totalSpace)
        {
            var rval = new SeriesList();

                Series s = CreateRuleLine(0, t1, t2);
                s = Max(-s + totalSpace,0);
                rval.Add(s);

            return rval;
        }
Example #24
0
        private DataTable GetTimeSeries()
        {
            HydrometHost svr = HydrometInfoUtility.HydrometServerFromPreferences();

            string query = comboBoxInputs.Text.Trim();

            if (m_db == TimeInterval.Daily)
            {
                if (CbttOnly(query))
                {
                    string[] pcodes = HydrometInfoUtility.ArchiveParameters(query);
                    if (pcodes.Length > 0)
                    {
                        query = query + " " + String.Join(",", pcodes);
                    }
                }
                string[] tokens = query.Split(' ');
                if (tokens.Length != 2)
                {
                    return(new DataTable());
                }

                string cbtt  = tokens[0];
                string pcode = tokens[1];
                Series s     = new HydrometDailySeries(cbtt, pcode, HydrometInfoUtility.HydrometServerFromPreferences());
                var    sl    = new SeriesList();
                sl.Add(s);

                int beginningMonth = 1;
                if (checkBoxWaterYear.Checked)
                {
                    beginningMonth = 10;
                }

                var wyList = PiscesAnalysis.WaterYears(sl, this.yearSelector1.SelectedYears, false, beginningMonth, true);

                if (checkBoxCelsius.Checked)
                {
                    for (int i = 0; i < wyList.Count; i++)
                    {
                        s = wyList[i];
                        if (s.Units.ToLower() == "degrees f")
                        {
                            Reclamation.TimeSeries.Math.ConvertUnits(s, "degrees C");
                        }
                    }
                }

                // remove months outside selected range
                var list = FilterBySelectedRange(this.monthRangePicker1.MonthDayRange, wyList);


                return(list.ToDataTable(true));
                // return HydrometUtility.ArchiveTable(svr,query, T1, T2);
            }
            //else
            //    if (m_db == HydrometDataBase.Dayfiles)
            //    {

            //        if (CbttOnly(query))
            //        {
            //            string[] pcodes = Hydromet.DayfileParameters(query);
            //            if (pcodes.Length > 0)
            //            {
            //                query = query + " " + String.Join(",", pcodes);
            //            }
            //        }
            //        return HydrometUtility.DayFilesTable(svr,query, T1, T2);
            //    }
            //    else
            //        if (m_db == HydrometDataBase.MPoll)
            //        {

            //            return HydrometUtility.MPollTable(svr,query, T1, T2);
            //        }

            return(new DataTable());
        }
Example #25
0
        /// <summary>
        /// Finds all series in the expression.
        /// </summary>
        /// <returns></returns>
        private SeriesList SeriesInExpression(string expresion)
        {
            var sl = new SeriesList();
            string[] variables = m_VariableParser.GetAllVariables(expresion);
            for (int i = 0; i < variables.Length; i++)
            {
                var alias = variables[i];
                //if (Regex.IsMatch(alias, "\".+\""))
                //{// strip double quotes
                //    alias = alias.Substring(1, alias.Length - 2);
                //}
                var v = VariableResolver.Lookup(alias,defaultTimeInterval);
                if (v.IsSeries)
                {
                    sl.Add(v.Series);
                }
            }

            return sl;
        }
Example #26
0
        public SeriesList CalculateVariableRuleCurves(DateTime t1, DateTime t2, double totalSpace, double percent)
        {
            var rval = new SeriesList();
            if (m_fillType == FillType.Fixed)
                return rval;

            var levels = FcPlotDataSet.GetVariableForecastLevels(curveName);
            for (int i = 0; i < levels.Length; i++)
            {

                Series s = CreateRuleLine(levels[i], t1, t2) * percent;
                s = -s + totalSpace;

                s = Max(s, 0);
                rval.Add(s);
            }

            return rval;
        }
Example #27
0
        private void buttonRefresh_Click(object sender, EventArgs e)
        {
            try
            {
                timeSeriesGraph1.AnnotationOnMouseMove = checkBoxAnnotate.Checked;
                Cursor = Cursors.WaitCursor;
                Application.DoEvents();
                string pcodeOrig = DeterminePcode();

                timeSeriesGraph1.Clear();

                string cbttOrig = comboBoxCbtt.Text.Trim();
                string cbtt = cbttOrig, pcode = pcodeOrig;

                var seriesList = new List <string>();
                if ((cbttOrig.Trim() == "" || pcodeOrig.Trim() == "") && textBoxMultiple.Text == "")
                {
                    return;
                }
                else
                {
                    if (!checkBoxUseList.Checked)
                    {
                        UserPreference.Save("Snowgg->cbtt", cbttOrig);
                        UserPreference.Save("Snowgg->pcode", comboBoxPcode.Text.Trim());
                        seriesList.Add(cbttOrig + "_" + pcodeOrig);
                    }
                    else
                    {
                        var seriesItems = textBoxMultiple.Text.Split(',');
                        foreach (string item in seriesItems)
                        {
                            if (item.Trim().Split(' ').Length == 2)
                            {
                                seriesList.Add(item.Trim().Split(' ')[0] + "_" + item.Trim().Split(' ')[1]);
                            }
                        }
                    }
                }

                int[]      waterYears            = this.yearSelector1.SelectedYears;
                SeriesList finalSeriesCollection = new SeriesList();
                foreach (string series in seriesList)
                {
                    cbtt = series.Split('_')[0];
                    comboBoxCbtt.Text  = cbtt;
                    pcode              = series.Split('_')[1];
                    comboBoxPcode.Text = pcode;
                    var server = HydrometInfoUtility.HydrometServerFromPreferences();
                    var range  = monthRangePicker1.MonthDayRange;

                    Series s;
                    if (this.checkBoxUseInstant.Checked)
                    {
                        s = new HydrometInstantSeries(cbtt, pcode, server);
                    }
                    else
                    {
                        s = new HydrometDailySeries(cbtt, pcode, server);
                    }
                    var sl = new SeriesList();
                    sl.Add(s);

                    // get wy data
                    var wyList = new SeriesList();
                    if (cySelected)
                    {
                        wyList = PiscesAnalysis.WaterYears(sl, waterYears, false, 1, true);
                    }
                    else
                    {
                        wyList = PiscesAnalysis.WaterYears(sl, waterYears, false, 10, true);
                    }

                    foreach (Series item in wyList)
                    {
                        item.Name = cbtt + " " + pcode;
                        // remove missing data points
                        var missingItems = item.Table.Select("value = 998877");
                        foreach (var row in missingItems)
                        {
                            item.RemoveAt(item.IndexOf(Convert.ToDateTime(row.ItemArray[0])));
                        }
                    }

                    // apply deltas and add stats if toggled
                    wyList = ApplyDeltas(wyList, waterYears);
                    AddStatistics(wyList);

                    if (checkBoxGP.Checked)
                    {
                        GPAverage(cbtt, server, range, wyList);
                    }

                    var mp = ReadMpollData(pcode, cbtt);
                    mp.RemoveMissing();
                    if (mp.Count > 0)
                    {
                        wyList.Add(mp);
                    }

                    // remove months outside selected range
                    var list = FilterBySelectedRange(range, wyList);
                    finalSeriesCollection.Add(list);
                }

                // Set series line colors
                var uniqueSeriesNames  = new List <string>();
                var uniqueSeriesColors = new List <string>();
                int colorCounter       = 0;
                foreach (var item in finalSeriesCollection)
                {
                    // set line color by year which is identified in the legendtext field
                    if (!uniqueSeriesNames.Contains(item.Appearance.LegendText) && !item.Appearance.LegendText.Contains("%") &&
                        !item.Appearance.LegendText.Contains("avg") && !item.Appearance.LegendText.Contains("max") && !item.Appearance.LegendText.Contains("min"))
                    {
                        uniqueSeriesNames.Add(item.Appearance.LegendText);//.Name);
                        uniqueSeriesColors.Add(snowGgColors[colorCounter]);
                        colorCounter = (colorCounter + 1) % snowGgColors.Count;
                    }
                }
                foreach (var item in finalSeriesCollection)
                {
                    try
                    {
                        int colIdx = uniqueSeriesNames.IndexOf(item.Appearance.LegendText);//.Name);
                        item.Appearance.Color = uniqueSeriesColors[colIdx];
                    }
                    catch
                    {
                        item.Appearance.Color = "Black";
                    }
                }

                this.timeSeriesGraph1.AnalysisType = AnalysisType.WaterYears;
                this.timeSeriesGraph1.Series       = finalSeriesCollection;
                if (seriesList.Count == 1)
                {
                    this.timeSeriesGraph1.Title = HydrometInfoUtility.LookupSiteDescription(cbtt) + "  Elevation:" + HydrometInfoUtility.LookupElevation(cbtt);
                }
                //timeSeriesGraph1.GraphSettings = GetGraphSettings();

                this.timeSeriesGraph1.Draw(true);

                comboBoxCbtt.Text  = cbttOrig;
                comboBoxPcode.Text = pcodeOrig;

                timeSeriesGraph1.GraphSettings = GetGraphSettings();
            }
            finally
            {
                Cursor = Cursors.Default;
            }
        }
Example #28
0
        /// <summary>
        /// Creates a list of water year based data all aligned to year 2000
        /// to allow comparison.
        /// </summary>
        /// <param name="list">intput series</param>
        /// <param name="years">water years</param>
        /// <param name="avg30yr">when true also includes 30 year average. </param>
        /// <param name="beginningMonth">series starting month number</param>
        /// <returns></returns>
        public static SeriesList WaterYears(SeriesList list, int[] years, bool avg30yr,
                                            int beginningMonth, bool alwaysShiftTo2000, DateTime?startOf30YearAvearge = null)
        {
            SeriesList wySeries = new SeriesList();

            for (int j = 0; j < list.Count; j++)
            {
                for (int i = 0; i < years.Length; i++)
                {
                    YearRange yr = new YearRange(years[i], beginningMonth);
                    Series    s  = list[j];
                    s.Clear();
                    s.Read(yr.DateTime1, yr.DateTime2);

                    Logger.WriteLine("Read() " + yr.ToString() + " count = " + s.Count);

                    foreach (string msg in s.Messages)
                    {
                        Logger.WriteLine(msg);
                    }
                    if (s.Count > 0 && s.CountMissing() != s.Count)
                    {
                        Series s2 = TimeSeries.Math.ShiftToYear(s, 2000);
                        if (years.Length == 1 && !alwaysShiftTo2000 && !avg30yr)
                        {
                            s2 = s;
                        }
                        if (list.HasMultipleSites)
                        {
                            s2.Appearance.LegendText = years[i].ToString() + "   " + list[j].Name;
                        }
                        else
                        {
                            s2.Appearance.LegendText = years[i].ToString();
                        }
                        wySeries.Add(s2);
                    }
                    else
                    {
                        Logger.WriteLine("year :" + years[i] + "skipping series with no data " + s.Name + " " + s.Parameter);
                    }
                }
                if (avg30yr)
                {
                    DateTime start = DateTime.Now.Date.AddYears(-30);
                    if (startOf30YearAvearge.HasValue)
                    {
                        start = startOf30YearAvearge.Value;
                    }

                    DateTime end = start.AddYears(30);
                    list[j].Read(start, end);
                    Series s30 = Math.MultiYearDailyAverage(list[j], beginningMonth);
                    if (s30.Count > 0)
                    {
                        wySeries.Add(s30);
                    }
                }
            }
            wySeries.Type = SeriesListType.WaterYears;
            if (wySeries.Count > 1)
            {
                wySeries.DateFormat = "MM/dd";
            }

            return(wySeries);
        }
Example #29
0
        private void AddStatistics(SeriesList wyList)
        {
            bool anyStats = checkBoxMax.Checked || checkBoxMin.Checked || checkBoxAvg.Checked || checkBoxPctls.Checked;

            if (!anyStats)
            {
                return;
            }

            int y1 = 1990;
            int y2 = 2011;

            int[] pctls = new int[] { };

            int.TryParse(this.textBoxWY1.Text, out y1);
            int.TryParse(this.textBoxWY2.Text, out y2);

            if (checkBoxPctls.Checked)
            {
                try
                {
                    string   values = textBoxPctls.Text;
                    string[] tokens = values.Split(',');
                    pctls = Array.ConvertAll <string, int>(tokens, int.Parse);
                }
                catch
                {
                    pctls = new int[] { 10, 50, 90 };
                }
            }


            DateTime t1, t2;

            if (cySelected)
            {
                t1 = new DateTime(y1, 1, 1);
                t2 = new DateTime(y2, 12, 31);
            }
            else
            {
                t1 = new DateTime(y1 - 1, 10, 1);
                t2 = new DateTime(y2, 9, 30);
            }

            var    server = HydrometInfoUtility.HydrometServerFromPreferences();
            Series s;

            if (this.checkBoxUseInstant.Checked)
            {
                s = new HydrometInstantSeries(comboBoxCbtt.Text.Trim(), DeterminePcode(), server);
            }
            else
            {
                s = new HydrometDailySeries(comboBoxCbtt.Text.Trim(), DeterminePcode(), server);
            }
            s.Read(t1, t2);
            s.RemoveMissing();
            s.Appearance.LegendText = "";

            YearRange yr;

            if (cySelected)
            {
                yr = new YearRange(2000, 1);
            }
            else
            {
                yr = new YearRange(2000, 10);
            }
            var list = Math.SummaryHydrograph(s, pctls, yr.DateTime1, checkBoxMax.Checked, checkBoxMin.Checked, checkBoxAvg.Checked, false); //, false);


            wyList.Add(list);
        }
Example #30
0
        /// <summary>
        /// Build a SeriesList with the trace exceedances
        /// </summary>
        /// <param name="sListIn"></param>
        /// <param name="excLevels"></param>
        /// <param name="xtraTraceCheck"></param>
        /// <param name="xtraTrace"></param>
        /// <returns></returns>
        private SeriesList getTraceExceedances(SeriesList sListIn, int[] excLevels, bool xtraTraceCheck, string xtraTrace,
                                               bool plotMinTrace, bool plotAvgTrace, bool plotMaxTrace)
        {
            SeriesList traceAnalysisList = new SeriesList();

            // Define the index numbers from the serieslist wrt the selected exceedance level
            List <int> sExcIdxs = new List <int>();

            foreach (var item in excLevels)
            {
                var sNew = new Series();
                sNew.TimeInterval = sListIn[0].TimeInterval;
                sNew.Units        = sListIn[0].Units;
                sNew.ScenarioName = item + "%Exceedance";
                traceAnalysisList.Add(sNew);
                int excIdx;
                if (item > 50)
                {
                    excIdx = Convert.ToInt16(System.Math.Ceiling(sListIn.Count * (100.0 - Convert.ToDouble(item)) / 100.0));
                }
                else
                {
                    excIdx = Convert.ToInt16(System.Math.Floor(sListIn.Count * (100.0 - Convert.ToDouble(item)) / 100.0));
                }
                sExcIdxs.Add(excIdx);
            }

            // Add min trace if selected
            if (plotMinTrace)
            {
                var sNew = new Series();
                sNew.TimeInterval = sListIn[0].TimeInterval;
                sNew.Units        = sListIn[0].Units;
                sNew.ScenarioName = "Min";
                traceAnalysisList.Add(sNew);
                sExcIdxs.Add(0);
            }

            // Add max trace if selected
            if (plotMaxTrace)
            {
                var sNew = new Series();
                sNew.TimeInterval = sListIn[0].TimeInterval;
                sNew.Units        = sListIn[0].Units;
                sNew.ScenarioName = "Max";
                traceAnalysisList.Add(sNew);
                sExcIdxs.Add(sListIn.Count - 1);
            }

            // Define average trace container
            var sAvg = new Series();

            sAvg.TimeInterval = sListIn[0].TimeInterval;
            sAvg.Units        = sListIn[0].Units;
            sAvg.ScenarioName = "Avg";

            // Populate the output serieslist with the exceddance curves
            var dTab = sListIn.ToDataTable(true);

            for (int i = 0; i < dTab.Rows.Count; i++)
            {
                var      dRow   = dTab.Rows[i];
                DateTime t      = DateTime.Parse(dRow[0].ToString());
                var      values = dRow.ItemArray;
                // Put the ith timestep values in a C# List and sort by ascending
                var valList = new List <double>();
                var valSum  = 0.0;
                for (int j = 1; j < values.Length; j++)
                {
                    valList.Add(Convert.ToDouble(values[j].ToString()));
                    valSum += Convert.ToDouble(values[j].ToString());
                }
                valList.Sort();
                // Grab the index corresponding to the selected exceedance level and populate the output serieslist
                for (int j = 0; j < sExcIdxs.Count; j++)
                {
                    traceAnalysisList[j].Add(t, valList[sExcIdxs[j]], "interpolated");
                }
                // Populate the average trace series
                if (plotAvgTrace)
                {
                    sAvg.Add(t, valSum / valList.Count, "interpolated");
                }
            }

            // Add average trace if selected
            if (plotAvgTrace)
            {
                traceAnalysisList.Add(sAvg);
            }

            // Add an extra reference trace if defined
            if (xtraTraceCheck)
            {
                //xtraTrace contains the run name "Name"
                var scenarioTable       = Explorer.Database.GetSelectedScenarios();
                var selectedScenarioRow = scenarioTable.Select("[Name] = '" + xtraTrace + "'")[0];
                int selectedIdx         = scenarioTable.Rows.IndexOf(selectedScenarioRow);
                //scenariosTable.Rows.IndexOf(
                if (xtraTrace == "")
                {
                    throw new Exception("Select an additional trace that is between 1 and the total number of traces");
                }
                else
                {
                    traceAnalysisList.Add(sListIn[selectedIdx]);
                }
            }

            return(traceAnalysisList);
        }
Example #31
0
        /// <summary>
        /// MLR Interpolation Report
        /// Look for '[JR]' in this method to find the code regions that could use a fix or more testing...
        /// </summary>
        /// <param name="sInputs"></param>
        /// <param name="t1"></param>
        /// <param name="t2"></param>
        /// <param name="months"></param>
        /// <param name="fitTolerance"></param>
        /// <param name="waterYear"></param>
        public static MultipleLinearRegressionResults MlrInterpolation(SeriesList sList, 
            int[] months, double fitTolerance, bool fillSelectedMonths = false)
        {
            // KT if there is not enough data (for example only 1 pont ) need to ignore that data set?

            MultipleLinearRegressionResults rval = new MultipleLinearRegressionResults();
            // Populate SeriesLists
            var sListFill = new SeriesList();
            foreach (var item in sList)
            {
                sListFill.Add(item.Copy());
            }

            // Get dates to be filled with interpolated values
            var missing = sList[0].GetMissing();
            if (fillSelectedMonths) //overwrites the 'missing' variable with another Series that only contains the selected dates in the input
            {
                Series missingSubset = new Series();
                foreach (var row in missing)
                {
                    if (months.Contains(row.DateTime.Month))
                    { missingSubset.Add(row); }
                }
                missing = missingSubset;
            }

            // Delete common dates where at least 1 data point is missing for any of the input series
            // This is done because the MLR routine does not support missing data. Missing data causes
            // data misalignments and throws off the regression... This section also deletes data for
            // months that are not tagged in the input
            for (int i = sList[0].Count - 1; i >= 0; i--) //start from the bottom of the list to bypass indexing problems
            {
                for (int j = 0; j < sList.Count; j++)
                {
                    Point jthPt = sList[j][i];
                    if (jthPt.IsMissing || !months.Contains(jthPt.DateTime.Month))
                    {
                        for (int k = 0; k < sList.Count; k++) //delete this date from all Series in the list
                        { sList[k].RemoveAt(i); }
                        break;
                    }
                }
            }

            // Initialize MLR report and populate header
            List<string> mlrOut = new List<string>();
            mlrOut.Add("");
            mlrOut.Add("MLR Output\t\t\t\t\tRun Date: " + DateTime.Now);
            mlrOut.Add("Estimated Series: " + sList[0].Name);
            var sEstimators = "";
            for (int i = 1; i < sList.Count; i++)
            { sEstimators = sEstimators + sList[i].Name + ", "; }
            mlrOut.Add("Estimator Series: " + sEstimators.Remove(sEstimators.Length - 2));
            mlrOut.Add("Regression Date Range: " + sList[0].MinDateTime + " - " + sList[0].MaxDateTime);
            var monEstimators = "";
            foreach (var item in months)
            { monEstimators = monEstimators + item + ", "; }
            mlrOut.Add("Months Used: " + monEstimators.Remove(monEstimators.Length - 2));
            mlrOut.Add("");
            mlrOut.Add("====================================================================================");

            // Initialize output SeriesList
            var sOutList = new SeriesList();

            // Loop through each SeriesList combination for MLR
            for (int k = 1; k <= sList.Count - 1; k++)
            {
                AllPossibleCombination combinationData = new AllPossibleCombination(sList.Count - 1, k); //uses StackOverflow Class for combinations
                var combinationList = combinationData.GetCombinations();
                // Loop through each combination in the list and run MLR
                foreach (var combo in combinationList)
                {
                    // Build MLR method inputs
                    // xData is the different Series values that will be used to generate the MLR equation, all index > 0 in the SeriesList. Matrix format
                    // yData is the target Series values that is the target for MLR, index = 0 of the SeriesList. Vector format
                    double[][] xData = new double[sList[0].Count][];
                    double[] yData = new double[sList[0].Count];
                    // Loop through the dates to populate the xData and the yData
                    for (int i = 0; i < sList[0].Count; i++)
                    {
                        var jthRow = new List<double>();
                        // Loop through each Series in SeriesList
                        for (int j = 0; j < combo.Count(); j++)
                        { jthRow.Add(sList[combo[j]][i].Value); }
                        xData[i] = jthRow.ToArray();
                        yData[i] = sList[0][i].Value;
                    }

                    // MLR via Math.Net.Numerics
                    double[] mlrCoeffs = MathNet.Numerics.LinearRegression.MultipleRegression.QR(xData, yData, true); //this is more stable than the method below
                    //double[] p2 = MathNet.Numerics.Fit.MultiDim(xData, yData, true); //this method is faster but less stable

                    // Evaluate fit
                    Series sModeled = sList[0].Clone();
                    // Equations are of the form y = x1(s1) + x2(s2) + ... + xN the loop handles the inner part of the equation if it exists x2(s2) + ...
                    //          while the lines before and after the loop handles the first and last terms x1(s1) and xN respectively
                    sModeled = sList[combo[0]] * mlrCoeffs[1];
                    for (int i = 2; i < mlrCoeffs.Count(); i++)
                    { sModeled = sModeled + sList[combo[i - 1]] * mlrCoeffs[i]; } //magic number -1 is used so the correct corresponding Series is used with the correct mlr-coefficient
                    sModeled = sModeled + mlrCoeffs[0];
                    var rVal = MathNet.Numerics.GoodnessOfFit.R(sModeled.Values, sList[0].Values);//this is the statistic reported by the FORTRAN code
                    var rSqd = MathNet.Numerics.GoodnessOfFit.RSquared(sModeled.Values, sList[0].Values); //this is the R-squared for model fit

                    // Fill missing dates and generate a SeriesList for final Series output
                    var sOut = new Series(); //initialize Series to be added to output SeriesList
                    foreach (var fillT in missing)
                    {
                        double fillVal;
                        try
                        {
                            // This evaluates the equation generated during the MLR estimation. Same equation-code format as above
                            fillVal = sListFill[combo[0]][fillT.DateTime].Value * mlrCoeffs[1];
                            for (int i = 2; i < mlrCoeffs.Count(); i++)
                            { fillVal = fillVal + sListFill[combo[i - 1]][fillT.DateTime].Value * mlrCoeffs[i]; }
                            fillVal = fillVal + mlrCoeffs[0];
                            if (fillVal < 0.0)
                            { sOut.Add(fillT.DateTime, Point.MissingValueFlag, "NoDataForInterpolation"); }
                            else
                            { sOut.Add(fillT.DateTime, fillVal, rVal.ToString("F05")); } //[JR] this assigns the R value as the flag, can be switched to R-Squared...
                        }
                        catch
                        { sOut.Add(fillT.DateTime, Point.MissingValueFlag, "NoDataForInterpolation"); }
                    }
                    // Add the output Series to a SeriesList
                    sOutList.Add(sOut);

                    // Populate report
                    mlrOut.Add("");
                    string equationString = "MLR Equation: " + sList[0].Name + " = ";
                    for (int ithCoeff = 1; ithCoeff < mlrCoeffs.Count(); ithCoeff++)
                    {
                        equationString = equationString + mlrCoeffs[ithCoeff].ToString("F04") + "("
                          + sList[combo[ithCoeff - 1]].Name + ") + ";
                    }
                    equationString = equationString + mlrCoeffs[0].ToString("F04");
                    mlrOut.Add(equationString);
                    mlrOut.Add("Correlation Coefficient = " + rVal.ToString("F04"));
                    mlrOut.Add("R-Squared Coefficient = " + rSqd.ToString("F04"));
                    mlrOut.Add("MLR Estimates: ");
                    foreach (var item in sOut)
                    { mlrOut.Add("\t\t" + item.ToString(true)); }
                    mlrOut.Add("");
                    mlrOut.Add("------------------------------------------------------------------------------------");
                }
            }

            // Generate MLR report
            //TextFile tf = new TextFile(mlrOut.ToArray());
            //var fn = FileUtility.GetTempFileName(".txt");
            //tf.SaveAs(fn);
            //System.Diagnostics.Process.Start(fn);
            rval.Report = mlrOut.ToArray();

            // Generate output Series
            var sOutFinal = sListFill[0].Copy();
            // Rmove the Points to be filled in the original input Series
            for (int i = missing.Count - 1; i >= 0; i--)
            { sOutFinal.RemoveAt(sOutFinal.IndexOf(missing[i].DateTime)); }
            // Find the best fit out of all the estimated values
            // Loops through the dates
            foreach (var sRow in sOutList[0])
            {
                DateTime estT = sRow.DateTime;
                List<double> flagItems = new List<double>();//container for flag values
                List<double> valItems = new List<double>();//container for estiamted values
                // Loops through each estimate
                for (int i = 0; i < sOutList.Count; i++)
                {
                    Point estPt = sOutList[i][estT];
                    valItems.Add(estPt.Value);
                    if (estPt.Value < 0.0) //add 0 correlation value if the estimated value < 0, [JR] this prevents the use of this routine to estimate negative values...
                    { flagItems.Add(0.0); }
                    else
                    { flagItems.Add(Convert.ToDouble(estPt.Flag)); }
                }
                var maxFit = flagItems.Max();
                var bestFitVal = valItems[flagItems.IndexOf(maxFit)];
                if (maxFit >= fitTolerance) //add the value if it exceeds the specified tolerance
                { sOutFinal.Add(estT, bestFitVal, "E"); }
                else //add missing since there is no acceptable estimate to fill this missing value
                { sOutFinal.AddMissing(estT); }
            }
            //return sOutFinal;

            rval.EstimatedSeries = sOutFinal;
            return rval;
        }
Example #32
0
        private void buttonGo_Click(object sender, EventArgs e)
        {
            Cursor = Cursors.WaitCursor;
            Application.DoEvents();
            try
            {
                int wy1 = Convert.ToInt32(textBoxYear.Text);
                int wy2 = Convert.ToInt32(textBoxEndYear.Text);

                string cbtt  = textBoxCbtt.Text;
                string pcode = textBoxPcode.Text;

                var s = Reclamation.TimeSeries.Math.HydrometDaily(cbtt, pcode);

                var t1 = new DateTime(wy1 - 1, 10, 1);
                var t2 = new DateTime(wy2, 9, 30);

                s.Read(t1, t2);

                var list = new SeriesList();

                if (checkBoxTotal.Checked)
                {
                    var rval = Reclamation.TimeSeries.Math.MonthlySum(s);
                    rval.Units = "CFS";
                    list.Add(rval);
                }

                if (checkBoxTotalAF.Checked)
                {
                    var tmp = s.Copy();
                    Reclamation.TimeSeries.Math.Multiply(tmp, 1.98347);
                    var rval = Reclamation.TimeSeries.Math.MonthlySum(tmp);
                    rval.Units = "Acre-Feet";
                    list.Add(rval);
                }

                if (checkBoxAverage.Checked)
                {
                    var rval = Reclamation.TimeSeries.Math.MonthlyAverage(s);
                    rval.Units = "CFS";
                    list.Add(rval);
                }

                if (checkBoxAverageAF.Checked)
                {
                    var tmp = s.Copy();
                    Reclamation.TimeSeries.Math.Multiply(tmp, 1.98347);
                    var rval = Reclamation.TimeSeries.Math.MonthlyAverage(tmp);
                    rval.Units = "Acre-Feet";
                    list.Add(rval);
                }

                if (checkBoxChange.Checked)
                {
                    var start = Reclamation.TimeSeries.Math.StartOfMonth(s);
                    var end   = Reclamation.TimeSeries.Math.EndOfMonth(s);
                    var rval  = end - start;// Reclamation.TimeSeries.Math.Add(end, start, true);
                    list.Add(rval);
                }

                if (checkBoxMax.Checked)
                {
                    var rval = Reclamation.TimeSeries.Math.MonthlyMax(s);
                    list.Add(rval);
                }

                if (checkBoxMin.Checked)
                {
                    var rval = Reclamation.TimeSeries.Math.MonthlyMin(s);
                    list.Add(rval);
                }

                if (checkBoxFirstMonth.Checked)
                {
                    var rval = Reclamation.TimeSeries.Math.StartOfMonth(s);
                    list.Add(rval);
                }

                if (checkBoxEndMonth.Checked)
                {
                    var rval = Reclamation.TimeSeries.Math.EndOfMonth(s);
                    list.Add(rval);
                }

                view.SeriesList = list;
                view.Draw();
            }
            finally
            {
                Cursor = Cursors.Default;
            }
        }
Example #33
0
        /// <summary>
        /// ComputeTargets method uses the a Rule curve, forecast, and historical average
        /// to project flood target levels through the forecast period.
        /// computes a target Seriesuses the current forecast and forecast volume period
        /// </summary>
        /// <param name="pt"></param>
        /// <param name="waterYear"></param>
        /// <param name="start"></param>
        /// <param name="optionalPercents"></param>
        /// <returns></returns>
        public static SeriesList ComputeTargets(FloodControlPoint pt,
                                                int waterYear, Point start, int[] optionalPercents, bool dashed, bool forecastOverride, string forecastValIn)
        {
            string cbtt = pt.StationFC;

            SeriesList rval = new SeriesList();

            Series forecast      = new Series();
            int    forecastMonth = 0;
            double forecastValue = 0;

            if (forecastOverride)
            {
                forecastMonth = DateTime.Now.Month;// System.Math.Min(1, DateTime.Now.Month);
                forecastValue = Convert.ToDouble(forecastValIn);
            }
            else
            {
                //calculate forecast of most recent month
                forecast      = GetLatestForecast(cbtt, waterYear);
                forecastMonth = MonthOfLastForecast(forecast);

                //if no forecast cannot compute target
                if (forecastMonth == 0)
                {
                    return(rval);
                }
                //value of forecast to use for percent of average
                forecastValue = forecast[forecastMonth - 1].Value;
            }
            // average runoff  month - end(typically July) volume

            if (cbtt.ToLower() == "hgh")
            {
                var avg30yrQU = Get30YearAverageSeries(pt.DailyStationQU, "qu", 5);

                // sum volume for the forecast period (may,sep)

                var    t  = new DateTime(start.DateTime.Year, 5, 1);
                var    t2 = new DateTime(start.DateTime.Year, 9, 30);
                double historicalAverageResidual = SumResidual(avg30yrQU, t, t2);
                double percent = forecastValue / historicalAverageResidual;

                var x = HGHTarget(pt, forecastValue, start.DateTime, t);
                x.Name = "Forecast " + (100 * percent).ToString("F0") + "% " + (forecastValue / 1000.0).ToString("F0");;
                rval.Add(x);
                for (int i = 0; i < optionalPercents.Length; i++)
                {
                    var fc = historicalAverageResidual * optionalPercents[i] / 100.0;
                    x      = HGHTarget(pt, fc, start.DateTime, t);
                    x.Name = "Target (" + optionalPercents[i].ToString("F0") + "%) " + (fc / 1000.0).ToString("F0");
                    rval.Add(x);
                }
            }
            else
            {
                rval.Add(GetTargets(pt, waterYear, start, optionalPercents, forecastMonth, forecastValue, dashed));
            }

            return(rval);
        }
Example #34
0
        private SeriesList CreateSeriesList()
        {
            var interval = m_formatter.Interval;
            TimeSeriesName[] names = GetTimeSeriesName(m_collection, interval);

            var tableNames = (from n in names select n.GetTableName()).ToArray();

            var sc = db.GetSeriesCatalog("tablename in ('" + String.Join("','", tableNames) + "')");

            SeriesList sList = new SeriesList();
            foreach (var tn in names)
            {
                Series s = new Series();

                s.TimeInterval = interval;
                if (sc.Select("tablename = '" + tn.GetTableName() + "'").Length == 1)
                {
                    s = db.GetSeriesFromTableName(tn.GetTableName());
                }
                s.Table.TableName = tn.GetTableName();
                sList.Add(s);
            }
            return sList;
        }
Example #35
0
        /// <summary>
        /// Build a SeriesList with custom aggregation
        /// </summary>
        /// <param name="sListIn"></param>
        /// <param name="sumType"></param>
        /// <returns></returns>
        private SeriesList getTraceSums(SeriesList sListIn, string aggType)
        {
            SeriesList traceAnalysisList = new SeriesList();

            foreach (var s in sListIn)
            {
                var sNew = new Series();
                if (aggType == "CY")
                {
                    sNew = Reclamation.TimeSeries.Math.AnnualSum(s,
                        new MonthDayRange(1, 1, 12, 31), 1);
                }
                else if (aggType == "WY")
                {
                    sNew = Reclamation.TimeSeries.Math.AnnualSum(s,
                        new MonthDayRange(10, 1, 9, 30), 10);
                }
                else if (aggType == "XX")
                {
                    sNew = Reclamation.TimeSeries.Math.AnnualSum(s,
                        Explorer.MonthDayRange, Explorer.MonthDayRange.Month1);
                }
                else
                { view.Messages.Add(""); }
                sNew.TimeInterval = s.TimeInterval;
                sNew.Units = s.Units;
                traceAnalysisList.Add(sNew);
            }
            return traceAnalysisList;
        }
Example #36
0
        /// <summary>
        /// converts Daily formated data for 'arcimport.exe' prorgram into SeriesList
        /// each series is named  daily_cbtt_pcode,
        /// for example  daily_jck_fb
        /// </summary>
        /// <param name="fileName"></param>
        /// <returns></returns>
        public static SeriesList HydrometDailyDataToSeriesList(TextFile tf)
        {
            var rval = new SeriesList();

            for (int i = 1; i < tf.Length; i++) // skip first row (header)
            {
                var      fmt     = "MM/dd/yyyy";
                var      strDate = tf[i].Substring(0, fmt.Length);
                DateTime t;
                if (!DateTime.TryParseExact(strDate, fmt, new CultureInfo("en-US"), System.Globalization.DateTimeStyles.None, out t))
                {
                    Console.WriteLine("Bad Date, Skipping line: " + tf[i]);
                    continue;
                }

                /*
                 * 07/28/2016 CKVY         MN        998877.00     40.91
                 */
                string cbtt     = tf[i].Substring(11, 12).Trim().ToLower();
                string pcode    = tf[i].Substring(24, 9).Trim().ToLower();
                string strValue = tf[i].Substring(34, 10);
                double val      = 0;

                if (!double.TryParse(strValue, out val))
                {
                    Console.WriteLine("Error parsing double " + strValue);
                    continue;
                }

                string name = "daily_" + cbtt + "_" + pcode;
                name = name.ToLower();
                var    idx = rval.IndexOfTableName(name);
                Series s;
                if (idx >= 0)
                {
                    s = rval[idx];
                }
                else
                {
                    s = new Series();
                    s.TimeInterval    = TimeInterval.Daily;
                    s.SiteID          = cbtt;
                    s.Parameter       = pcode;
                    s.Name            = cbtt + "_" + pcode;
                    s.Name            = s.Name.ToLower();
                    s.Table.TableName = name;
                    rval.Add(s);
                }

                string flag = "";
                if (s.IndexOf(t) < 0)
                {
                    s.Add(t, val, flag);
                }
                else
                {
                    Logger.WriteLine(s.SiteID + ":" + s.Parameter + "skipped duplicate datetime " + t.ToString());
                }
            }

            return(rval);
        }
Example #37
0
        public override IExplorerView Run()
        {
            Logger.WriteLine("TraceAnalysis.Run()");
            SeriesList list = Explorer.CreateSelectedSeries();

            ReadSeriesList(list);
            string title = list.Text.TitleText();
            string subTitle = list.MissingRecordsMessage;

            // [JR] don't perform trace analysis if trace count < 10...
            if (list.Count < 10)
            {
                view.Messages.Add("Trace exceedance analysis is not available if trace count < 10");
                view.Title = title;
                view.SubTitle = subTitle;
                view.SeriesList = list;
                view.DataTable = list.ToDataTable(true);
                return view;
            }

            // This seems to be common between all the analysis options
            if (Explorer.SelectedSeries.Length == 1 && Explorer.MergeSelected)
            { // merge single Year Traces.
                list.RemoveMissing();
                var s = list.MergeYearlyScenarios();
                list = new SeriesList();
                list.Add(s);
            }
            view.Messages.Add(list.MissingRecordsMessage);
            list.RemoveMissing();

            // Initialize the output container
            SeriesList traceAnalysisList = new SeriesList();

            // Get exceedance curves
            if (Explorer.traceExceedanceAnalysis)
            {
                traceAnalysisList = getTraceExceedances(list,
                    Explorer.ExceedanceLevels, Explorer.AlsoPlotTrace,
                    Explorer.PlotTrace, Explorer.PlotMinTrace,
                    Explorer.PlotAvgTrace, Explorer.PlotMaxTrace);
            }

            // Get aggregated values
            if (Explorer.traceAggregationAnalysis)
            {
                string sumType = "";
                if (Explorer.sumCYRadio)
                { sumType = "CY"; }
                else if (Explorer.sumWYRadio)
                { sumType = "WY"; }
                else if (Explorer.sumCustomRangeRadio)
                { sumType = "XX"; }
                else
                { }
                traceAnalysisList = getTraceSums(list, sumType);
            }

            // [JR] Add other analysis/report building options here...

            Explorer.WriteProgressMessage("drawing graph", 80);
            view.Title = title;
            view.SubTitle = subTitle;
            view.SeriesList = traceAnalysisList;
            view.DataTable = traceAnalysisList.ToDataTable(true);
            //view.Draw();
            return view;
        }
Example #38
0
 public void Add(Series s)
 {
     seriesList.Add(s);
 }
Example #39
0
        /// <summary>
        /// Reads TextFile into a Series List
        /// </summary>
        /// <param name="tf"></param>
        /// <returns></returns>
        internal static SeriesList FileToSeriesList(TextFile tf)
        {
            SeriesList rval = new SeriesList();

            /*
             * cbtt,pc,Year,month,value,flag,oldValue,oldFlag
             * ARK, PM,2018,JAN,1.00,M,5.36,M
             */

            for (int i = 1; i < tf.Length; i++) // skip first row (header)
            {
                var tokens = tf[i].Split(',');
                if (tokens.Length != 8)
                {
                    Console.WriteLine("Skipping invalid line: " + tf[i]);
                    continue;
                }
                var      siteid    = tokens[0].ToLower();
                var      parameter = tokens[1].ToLower();
                DateTime t;
                if (!ParseDate(tokens[2], tokens[3], out t))
                {
                    Console.WriteLine("Error Parsing date " + tf[i]);
                    continue;
                }

                double val = 0;
                if (!double.TryParse(tokens[4], out val))
                {
                    Console.WriteLine("Error Parsing value: " + tokens[4]);
                    continue;
                }

                var flag = tokens[5];

                string name = "monthly_" + siteid + "_" + parameter;
                var    idx  = rval.IndexOfTableName(name);
                Series s;
                if (idx >= 0)
                {
                    s = rval[idx];
                }
                else
                {
                    s = new Series();
                    s.TimeInterval    = TimeInterval.Monthly;
                    s.SiteID          = siteid;
                    s.Parameter       = parameter;
                    s.Name            = siteid + "_" + parameter;
                    s.Name            = s.Name.ToLower();
                    s.Table.TableName = name;
                    rval.Add(s);
                }
                if (s.IndexOf(t) < 0)
                {
                    s.Add(t, val, flag);
                }
                else
                {
                    Logger.WriteLine(s.SiteID + ":" + s.Parameter + "skipped duplicate datetime " + t.ToString());
                }
            }
            return(rval);
        }
Example #40
0
        /// <summary>
        /// Build a SeriesList with the trace exceedances
        /// </summary>
        /// <param name="sListIn"></param>
        /// <param name="excLevels"></param>
        /// <param name="xtraTraceCheck"></param>
        /// <param name="xtraTrace"></param>
        /// <returns></returns>
        private SeriesList getTraceExceedances(SeriesList sListIn, int[] excLevels, bool xtraTraceCheck, string xtraTrace,
            bool plotMinTrace, bool plotAvgTrace, bool plotMaxTrace)
        {
            SeriesList traceAnalysisList = new SeriesList();

            // Define the index numbers from the serieslist wrt the selected exceedance level
            List<int> sExcIdxs = new List<int>();
            foreach (var item in excLevels)
            {
                var sNew = new Series();
                sNew.TimeInterval = sListIn[0].TimeInterval;
                sNew.Units = sListIn[0].Units;
                sNew.ScenarioName = item + "%Exceedance";
                traceAnalysisList.Add(sNew);
                int excIdx;
                if (item > 50)
                { excIdx = Convert.ToInt16(System.Math.Ceiling(sListIn.Count * (100.0 - Convert.ToDouble(item)) / 100.0)); }
                else
                { excIdx = Convert.ToInt16(System.Math.Floor(sListIn.Count * (100.0 - Convert.ToDouble(item)) / 100.0)); }
                sExcIdxs.Add(excIdx);
            }

            // Add min trace if selected
            if (plotMinTrace)
            {
                var sNew = new Series();
                sNew.TimeInterval = sListIn[0].TimeInterval;
                sNew.Units = sListIn[0].Units;
                sNew.ScenarioName = "Min";
                traceAnalysisList.Add(sNew);
                sExcIdxs.Add(0);
            }

            // Add max trace if selected
            if (plotMaxTrace)
            {
                var sNew = new Series();
                sNew.TimeInterval = sListIn[0].TimeInterval;
                sNew.Units = sListIn[0].Units;
                sNew.ScenarioName = "Max";
                traceAnalysisList.Add(sNew);
                sExcIdxs.Add(sListIn.Count - 1);
            }

            // Define average trace container
            var sAvg = new Series();
            sAvg.TimeInterval = sListIn[0].TimeInterval;
            sAvg.Units = sListIn[0].Units;
            sAvg.ScenarioName = "Avg";

            // Populate the output serieslist with the exceddance curves
            var dTab = sListIn.ToDataTable(true);
            for (int i = 0; i < dTab.Rows.Count; i++)
            {
                var dRow = dTab.Rows[i];
                DateTime t = DateTime.Parse(dRow[0].ToString());
                var values = dRow.ItemArray;
                // Put the ith timestep values in a C# List and sort by ascending
                var valList = new List<double>();
                var valSum = 0.0;
                for (int j = 1; j < values.Length; j++)
                {
                    valList.Add(Convert.ToDouble(values[j].ToString()));
                    valSum += Convert.ToDouble(values[j].ToString());
                }
                valList.Sort();
                // Grab the index corresponding to the selected exceedance level and populate the output serieslist
                for (int j = 0; j < sExcIdxs.Count; j++)
                { traceAnalysisList[j].Add(t, valList[sExcIdxs[j]],"interpolated"); }
                // Populate the average trace series
                if (plotAvgTrace)
                { sAvg.Add(t, valSum / valList.Count, "interpolated"); }
            }

            // Add average trace if selected
            if (plotAvgTrace)
            { traceAnalysisList.Add(sAvg); }

            // Add an extra reference trace if defined
            if (xtraTraceCheck)
            {
                //xtraTrace contains the run name "Name"
                var scenarioTable = Explorer.Database.GetSelectedScenarios();
                var selectedScenarioRow = scenarioTable.Select("[Name] = '" + xtraTrace + "'")[0];
                int selectedIdx = scenarioTable.Rows.IndexOf(selectedScenarioRow);
                //scenariosTable.Rows.IndexOf(
                if (xtraTrace == "")
                { throw new Exception("Select an additional trace that is between 1 and the total number of traces"); }
                else
                { traceAnalysisList.Add(sListIn[selectedIdx]); }
            }

            return traceAnalysisList;
        }
Example #41
0
        private void buttonRefresh_Click(object sender, EventArgs e)
        {
            try
            {
                timeSeriesGraph1.AnnotationOnMouseMove = checkBoxAnnotate.Checked;
                Cursor = Cursors.WaitCursor;
                Application.DoEvents();
                string pcode = DeterminePcode();

                timeSeriesGraph1.Clear();

                string cbtt = comboBoxCbtt.Text.Trim();

                if (cbtt.Trim() == "" || pcode.Trim() == "")
                {
                    return;
                }

                UserPreference.Save("Snowgg->cbtt", cbtt);
                UserPreference.Save("Snowgg->pcode", comboBoxPcode.Text.Trim());

                int[] waterYears = this.yearSelector1.SelectedYears;
                var   server     = HydrometInfoUtility.HydrometServerFromPreferences();
                var   range      = monthRangePicker1.MonthDayRange;

                Series s  = new HydrometDailySeries(cbtt, pcode, server);
                var    sl = new SeriesList();
                sl.Add(s);

                var wyList = PiscesAnalysis.WaterYears(sl, waterYears, false, 10, true);

                AddStatistics(wyList);

                if (checkBoxGP.Checked)
                {
                    GPAverage(cbtt, server, range, wyList);
                }

                var mp = ReadMpollData(pcode, cbtt);
                mp.RemoveMissing();
                if (mp.Count > 0)
                {
                    wyList.Add(mp);
                }

                // remove months outside selected range
                var list = FilterBySelectedRange(range, wyList);

                this.timeSeriesGraph1.AnalysisType = AnalysisType.WaterYears;
                this.timeSeriesGraph1.Series       = list;
                this.timeSeriesGraph1.Title        = HydrometInfoUtility.LookupSiteDescription(cbtt) + "  Elevation:" + HydrometInfoUtility.LookupElevation(cbtt);
                this.timeSeriesGraph1.Draw(true);


                timeSeriesGraph1.GraphSettings = GetGraphSettings();
            }
            finally
            {
                Cursor = Cursors.Default;
            }
        }