コード例 #1
0
ファイル: Form1.cs プロジェクト: Jungwon/ZedGraph
        private void CreateGraph_NegativeHorizontalBars( ZedGraphControl z1 )
        {
            GraphPane myPane = z1.GraphPane;

            PointPairList list = new PointPairList();
            Random rand = new Random();

            for ( int i = 0; i < 20; i++ )
            {
                list.Add( rand.NextDouble() * 200.0 - 100.0, (double) i + 1.0, 50.0 );
            }

            list.Sort( SortType.XValues );

            HiLowBarItem myBar = myPane.AddHiLowBar( "histogram", list, Color.Blue );
            myBar.Bar.Fill = new Fill( Color.Blue );
            myPane.BarSettings.MinClusterGap = 0.0f;
            myPane.YAxis.MajorGrid.IsZeroLine = false;

            myPane.BarSettings.Base = BarBase.Y;

            LineObj line = new LineObj( Color.Black, 0, 50, 1, 50 );
            line.Location.CoordinateFrame = CoordType.XChartFractionYScale;
            myPane.GraphObjList.Add( line );

            z1.AxisChange();
        }
コード例 #2
0
ファイル: Form1.cs プロジェクト: Jungwon/ZedGraph
        // Simple plot with interpolated difference curve
        private void CreateGraph_DifferencePlot( ZedGraphControl z1 )
        {
            GraphPane myPane = z1.GraphPane;

            // Generate the first data set
            PointPairList list1 = new PointPairList();
            for ( int i = 0; i < 13; i++ )
            {
                double x = i + 11.0;
                double y = 150.0 * ( 1.0 + Math.Sin( i * 0.3 ) );
                list1.Add( x, y );
            }

            // Generate a second data set that is unrelated to the first
            PointPairList list2 = new PointPairList();
            for ( int i = 0; i < 15; i++ )
            {
                double x = i * 1.2 + 10.0;
                double y = 250.0 * ( 1.0 + Math.Sin( x * 0.5 ) );

                list2.Add( x, y );
            }

            // Make sure the data are sorted and monotonically increasing
            list1.Sort();
            list2.Sort();
            // Get the lower and upper limit of the data
            // This code can throw an exception if either list is empty
            double xMin = Math.Min( list1[0].X, list2[0].X );
            double xMax = Math.Max( list1[list1.Count - 1].X, list2[list2.Count - 1].X );

            // Create a new list that will hold the difference points
            PointPairList diffList = new PointPairList();

            // Select the number of points for the new difference curve
            // This is completely arbitrary, but more points will make it smoother in the
            // case of SplineInterpolation
            const int count = 50;

            // Loop for each data point to be created in the new PointPairList
            for ( int i=0; i<count; i++ )
            {
                // Calculated X values are evenly spaced
                double x = xMin + (double) i * ( xMax - xMin ) / count;

                // Use spline interpolation to create the Y values for the new curve
                // Note that this allows extrapolation beyond the actual data available
                // A tension value of 0.5 is used, but anywhere between 0 and 1 is reasonable
                //double y = list1.InterpolateX( x );
                double y1 = list1.InterpolateX( x );
                double y2 = list2.SplineInterpolateX( x, 0.5 );

                // Add the new Point to the list taking the difference between the Y values
                // If either value is Missing, it means that a point was extrapolated beyond
                // the available data, which is not allowed for SplineInterpolateX()
                // This won't happen with InterpolateX, since it allows extrapolation
                if ( y1 == PointPair.Missing || y2 == PointPair.Missing )
                    diffList.Add( x, PointPair.Missing, PointPair.Missing );
                else
                    diffList.Add( x, y1 - y2, (y1-y2) > 0 ? 1 : 0 );
            }

            // Create the three curves -- two datasets, plus a difference curve
            LineItem diffCurve = myPane.AddCurve( "diff", diffList, Color.Red, SymbolType.None );
            LineItem myCurve1 = myPane.AddCurve( "curve", list1, Color.Blue, SymbolType.Diamond );
            LineItem myCurve2 = myPane.AddCurve( "curve 2", list2, Color.Green, SymbolType.Circle );
            Color[] colors = { Color.Red, Color.Green };
            diffCurve.Line.Fill = new Fill( colors, 90 );
            diffCurve.Line.Fill.RangeMin = 0;
            diffCurve.Line.Fill.RangeMax = 1;
            diffCurve.Line.Fill.Type = FillType.GradientByZ;

            //diffCurve.Line.GradientFill = new Fill( colors, 90 );
            //diffCurve.Line.GradientFill.RangeMin = -100;
            //diffCurve.Line.GradientFill.RangeMax = 200;

            //diffCurve.Line.IsOptimizedDraw = true;

            // Add some "pretty" stuff (optional)
            myCurve1.Symbol.Fill = new Fill( Color.White );
            myCurve2.Symbol.Fill = new Fill( Color.White );
            diffCurve.Line.Width = 2.0f;
            //diffCurve.Symbol.Fill = new Fill( Color.White );
            myPane.Title.Text = "Interpolated Data Curve";
            myPane.XAxis.Title.Text = "Period";
            myPane.YAxis.Title.Text = "Response";
            myPane.Legend.FontSpec.Size = 14;
            myPane.Fill = new Fill( Color.WhiteSmoke, Color.Lavender, 0F );
            myPane.Chart.Fill = new Fill( Color.FromArgb( 255, 255, 245 ),
               Color.FromArgb( 255, 255, 190 ), 90F );

            XDate xx = new XDate( 2007, 11, 9 );
            XDate x2 = new XDate( 2007, 11, 9 );
            XDate x3 = new XDate( 2007, 11, 9, 1, 1, 1 );

            object junk = new object();

            int i1 = xx.CompareTo( xx );
            int i2 = xx.CompareTo( x2 );
            int i3 = xx.CompareTo( x3 );
            int i4 = x2.CompareTo( xx );
            int i5 = x2.CompareTo( x3 );
            int i6 = x3.CompareTo( x2 );
            int i7 = x3.CompareTo( junk );

            z1.IsAntiAlias = true;
            z1.AxisChange();
        }
コード例 #3
0
        private void GraphSeparators(PointPairList endpoints)
        {
            PointPairList points = new PointPairList();
            endpoints.Sort(SortType.XValues);

            points.Add(endpoints[0]);
            for (int counter = 0; counter < endpoints.Count - 1; counter++)
            {
                points.Add(endpoints[counter].X, 0);
                points.Add(endpoints[counter + 1].X, 0);
                points.Add(endpoints[counter + 1]);
            }

            LineItem separator = new LineItem("Separator", points, Color.Blue, SymbolType.None);
            curves.Add(separator);
        }
コード例 #4
0
ファイル: frmModel.cs プロジェクト: wrbrooks/VB3
        /// <summary>
        /// given a mlr model, vary the threshold by increments to find model sensitivity and specificity
        /// for each increment - these become roc plotting points for the model.  also, save the roc trace 
        /// data for passing to the caller for table display.  plotting points need to be sorted and aggregated
        /// (weedppl(ppl)) for calculating auc (area-under-curve via integration)
        /// </summary>
        /// <param name="model">given mlr model</param>
        /// <param name="rocTableVals"></param>
        /// <returns>null if number of pts lt 10, otherwise a pointpair list fro plotting</returns>
        private PointPairList ROCpoints(MLRIndividual model, out List<object> rocTableVals)
        {
            const int interations = 50;

            //vary the decision threshold by increments
            //calculate the ROC point for the decision threshold increment
            //accumulate points for all increments and return pointpairlist

            PointPairList ppl = new PointPairList();
            PointPair pp = new PointPair();
            ROCParameters rocParameters = null;
            List<object> rocTableVal = new List<object>();

            double maxPred = model.PredictedValues.Max();
            double minPred = model.PredictedValues.Min();
            double inc = (maxPred - minPred) / (double)interations;
            double threshold = minPred;

            while (threshold < maxPred)
            {
                threshold += inc;
                pp = ROCpoint(model, threshold, out rocParameters);
                if (!pp.IsInvalid)
                {
                    ppl.Add(pp);
                    rocTableVal.Add(rocParameters.ROCPars);
                }

            }

            rocTableVals = rocTableVal;

            //how many points is the minimum???
            if (ppl.Count > 10)
            {
                //sort for integral calc
                ppl.Sort();
                //get rid of multiple X datapoints
                ppl = weedppl(ppl);
                return ppl;
            }
            else
            {
                return null;
            }
        }
コード例 #5
0
ファイル: View.cs プロジェクト: apravdivy/MagistrSolution
        public void SendSolvingResultType2Mass(Dictionary<string, RKResults> results, IFunctionExecuter fe)
        {
            List<double> divZ;
            List<double> divZ2;
            List<double> divT;
            List<ResPointViewType2> list;
            var p = new PointPairList();

            mainForm.DrawCurves(results);

            var r = new Dictionary<string, List<ResPointViewType2>>();

            foreach (string s in results.Keys)
            {
                ResolveType2(results[s], fe, out divT, out divZ, out divZ2, out list);

                r.Add(s, list);
                if (divZ.Count > 0)
                {
                    p.Add(divZ[0], divZ2[0]);
                }
            }

            p.Sort(SortType.YValues);
            //p.Sort(ZedGraph.SortType.XValues);

            ShowResultType2Mass(p, r);
        }