# publicCenterSpace/Syncfusion-Charting

### Subversion checkout URL

You can clone with HTTPS or Subversion.

Added syncfusion / nmath charting support code and examples

commit b43713c178baf4f88fdb7d5ef5135b78a9827404 1 parent 5226c12
authored

Showing 3 changed files with 7,710 additions and 0 deletions.

1. +154 0 Examples.cs
2. +4,719 0 NMathChart.cs
3. +2,837 0 NMathStatsChart.cs
154 Examples.cs
 ... ... @@ -0,0 +1,154 @@ 1 +﻿using System; 2 +using System.Collections.Generic; 3 +using System.Drawing; 4 +using System.Text; 5 +using System.Windows.Forms; 6 + 7 +using CenterSpace.NMath.Analysis; 8 +using CenterSpace.NMath.Core; 9 +using CenterSpace.NMath.Stats; 10 +using CenterSpace.NMath.Charting.Syncfusion; 11 + 12 +using Syncfusion.Windows.Forms.Chart; 13 + 14 + 15 +namespace CenterSpace.NMath.Charting.Syncfusion 16 +{ 17 + class Examples 18 + { 19 + static void Main( string[] args ) 20 + { 21 + // Class NMathChart and NMathStatsChart provide static methods for plotting NMath 22 + // types using Syncfusion Essential Chart for Windows Forms controls. 23 + 24 + // EXAMPLE 1: CURVE FITTING 25 + 26 + // This NMath code fits a 4-parameter logistic function to data measuring the evolution 27 + // of an algal bloom in the Adriatic Sea. 28 + DoubleVector x = new DoubleVector( 11, 15, 18, 23, 26, 31, 39, 44, 54, 64, 74 ); 29 + DoubleVector y = new DoubleVector( 0.00476, 0.0105, 0.0207, 0.0619, 0.337, 0.74, 1.7, 2.45, 3.5, 4.5, 5.09 ); 30 + DoubleVector start = new DoubleVector( 4, 0.1 ); 31 + OneVariableFunctionFitter fitter = 32 + new OneVariableFunctionFitter ( AnalysisFunctions.FourParameterLogistic ); 33 + DoubleVector solution = fitter.Fit( x, y, start ); 34 + 35 + // For prototyping and debugging console applications, Show() plots common NMath types 36 + // and displays the chart in a default form. 37 + int numInterpolatedValues = 100; 38 + NMathChart.Show( fitter, x, y, solution, numInterpolatedValues ); 39 + 40 + // The default look of the chart is governed by static properties: DefaultSize, 41 + // DefaultTitleFont, DefaultAxisTitleFont, DefaultMajorGridLineColor, and DefaultMarker. 42 + 43 + // For more control, ToChart() returns an instance of Syncfusion.Windows.Forms.Chart.ChartControl, 44 + // which can be customized as desired. 45 + ChartControl chart = NMathChart.ToChart( fitter, x, y, solution, numInterpolatedValues ); 46 + chart.Titles[0].Text = "Algal Bloom in the Adriatic Sea"; 47 + chart.PrimaryXAxis.Title = "Days"; 48 + chart.PrimaryYAxis.Title = "Size (mm2)"; 49 + chart.Series[0].Text = "Observed"; 50 + chart.Series[1].Text = "Fitted 4PL"; 51 + chart.BackColor = Color.Beige; 52 + NMathChart.Show( chart ); 53 + 54 + // If you are developing a Windows Forms application using the Designer, add a ChartControl 55 + // to your form, then update it with an NMath object using the appropriate Update() function 56 + // after initialization. 57 + 58 + // InitializeComponent(); 59 + // NMathChart.Update( ref this.chart1, fitter, x, y, solution, numInterpolatedValues ); 60 + 61 + 62 + // EXAMPLE 2: FFT 63 + 64 + // This chart shows a complex signal vector with three component sine waves. 65 + int n = 100; 66 + DoubleVector t = new DoubleVector( n, 0, 0.1 ); 67 + DoubleVector signal = new DoubleVector( n ); 68 + for( int i = 0; i < n; i++ ) 69 + { 70 + signal[i] = Math.Sin( 2 * Math.PI * t[i] ) + 2 * Math.Sin( 2 * Math.PI * 2 * t[i] ) + 3 * Math.Sin( 2 * Math.PI * 3 * t[i] ); 71 + } 72 + chart = NMathChart.ToChart( signal, new NMathChart.Unit( 0, 0.1, "Time (s)" ) ); 73 + chart.Titles[0].Text = "Signal"; 74 + chart.ChartArea.PrimaryYAxis.Title = "Voltage"; 75 + NMathChart.Show( chart ); 76 + 77 + // We use NMath to compute the forward discrete fourier transform, then plot the power in the frequency domain. 78 + DoubleForward1DFFT fft = new DoubleForward1DFFT( n ); 79 + fft.FFTInPlace( signal ); 80 + DoubleSymmetricSignalReader reader = fft.GetSignalReader( signal ); 81 + DoubleComplexVector unpacked = reader.UnpackSymmetricHalfToVector(); 82 + chart = NMathChart.ToChart( unpacked, new NMathChart.Unit( 0, 0.1, "Frequency (Hz)" ) ); 83 + chart.Titles[0].Text = "FFT"; 84 + chart.ChartArea.PrimaryYAxis.Title = "Power"; 85 + NMathChart.Show( chart ); 86 + 87 + 88 + // EXAMPLE 3: PEAK FINDING 89 + 90 + // NMath class PeakFinderSavitzkyGolay uses smooth Savitzky-Golay derivatives to find peaks in data. 91 + // A peak is defined as a smoothed derivative zero crossing. 92 + double step_size = 0.1; 93 + x = new DoubleVector( 1000, 0.01, step_size ); 94 + y = NMathFunctions.Sin( x ) / x; 95 + int width = 5; 96 + int polynomial_degree = 4; 97 + PeakFinderSavitzkyGolay pf = new PeakFinderSavitzkyGolay( y, width, polynomial_degree ); 98 + pf.AbscissaInterval = step_size; 99 + pf.SlopeSelectivity = 0; 100 + pf.RootFindingTolerance = 0.0001; 101 + pf.LocatePeaks(); 102 + 103 + // Plot the peaks. 104 + double xmin = 20; 105 + double xmax = 50; 106 + NMathChart.Show( pf, xmin, xmax ); 107 + 108 + 109 + // EXAMPLE 4: K-MEANS CLUSTERING 110 + 111 + // The k-means clustering method assigns data points into k groups such that the sum of squares from points 112 + // to the computed cluster centers is minimized. Here we cluster 30 points in 3-dimensional space into 5 clusters. 113 + DoubleMatrix data = new DoubleMatrix( @"30 x 3 [ 114 + 0.62731478808400 0.71654239725005 0.11461282117064 115 + 0.69908013774534 0.51131144816890 0.66485556714021 116 + 0.39718395379261 0.77640121193349 0.36537389168912 117 + 0.41362889533818 0.48934547589850 0.14004445653473 118 + 0.65521294635567 0.18590445122522 0.56677280030311 119 + 0.83758509883186 0.70063540514612 0.82300831429067 120 + 0.37160803224266 0.98270880190626 0.67394863209536 121 + 0.42525315848265 0.80663774928874 0.99944730494940 122 + 0.59466337145257 0.70356765500360 0.96163640714857 123 + 0.56573857208571 0.48496371932457 0.05886216545559 124 + 1.36031117091978 1.43187338560697 1.73265064912939 125 + 1.54851281373460 1.63426595631548 1.42222658611939 126 + 1.26176956987179 1.80302634023193 1.96136999885631 127 + 1.59734484793384 1.08388100700103 1.07205923855201 128 + 1.04927799659601 1.94546278791039 1.55340796803039 129 + 1.57105749438466 1.91594245989412 1.29198392114244 130 + 1.70085723323733 1.60198742363800 1.85796351308408 131 + 1.96228825871716 1.25356057873233 1.33575513868621 132 + 1.75051823194427 1.87345080554039 1.68020385037051 133 + 1.73999304537847 1.51340070999628 1.05344442131849 134 + 2.35665553727760 2.67000386489368 2.90898934903532 135 + 2.49830459603553 2.20087641229516 2.59624713810572 136 + 2.43444053822029 2.27308816154697 2.32895530216404 137 + 2.56245841710735 2.62623463865051 2.47819442572535 138 + 2.61662113016546 2.53685169481751 2.59717077926034 139 + 2.11333998089856 2.05950405092050 2.16144875489995 140 + 2.89825174061313 2.08896175947532 2.82947425087386 141 + 2.75455137523865 2.27130817438170 2.95612240635488 142 + 2.79112319571067 2.40907231577105 2.59554799520203 143 + 2.81495206793323 2.47404145037448 2.02874821321149 ]" ); 144 + KMeansClustering km = new KMeansClustering( data ); 145 + ClusterSet clusters = km.Cluster( 5 ); 146 + 147 + // We have to specify which plane to plot. 148 + int xColIndex = 0; 149 + int yColIndex = 1; 150 + NMathStatsChart.Show( clusters, data, xColIndex, yColIndex ); 151 + 152 + } 153 + } 154 +}
4,719 NMathChart.cs
4,719 additions, 0 deletions not shown
2,837 NMathStatsChart.cs
2,837 additions, 0 deletions not shown