SCOTTPLOT Archives - 13 중 10 번째 페이지

[C#/WINFORM/SCOTTPLOT] 분위수 차트 만들기

■ 분위수 차트를 만드는 방법을 보여준다. ▶ MainForm.cs


using System;
using System.Windows.Forms;

using ScottPlot;
using ScottPlot.Statistics;

namespace TestProject
{
    /// <summary>
    /// 메인 폼
    /// </summary>
    public partial class MainForm : Form
    {
        //////////////////////////////////////////////////////////////////////////////////////////////////// Constructor
        ////////////////////////////////////////////////////////////////////////////////////////// Public

        #region 생성자 - MainForm()

        /// <summary>
        /// 생성자
        /// </summary>
        public MainForm()
        {
            InitializeComponent();

            Plot plot = new Plot(800, 600);

            Random random = new Random(0);

            int pointCount = 500;

            double[] xValueArray = DataGen.Consecutive(pointCount);
            double[] yValueArray = DataGen.Random(random, pointCount);

            double secondSeptile = Common.Quantile(yValueArray, 2, 7);

            plot.Title("2번째 7분위수");

            plot.AddScatter(xValueArray, yValueArray, lineWidth : 0, markerShape : MarkerShape.openCircle);

            plot.AddHorizontalLine(secondSeptile, width : 3, style : LineStyle.Dash);

            this.formsPlot.Reset(plot);

            this.formsPlot.Refresh();
        }

        #endregion
    }
}

using System;

using System.Windows.Forms;

using ScottPlot;

using ScottPlot.Statistics;

namespace TestProject

{

/// <summary>

/// 메인 폼

/// </summary>

public partial class MainForm : Form

{

//////////////////////////////////////////////////////////////////////////////////////////////////// Constructor

////////////////////////////////////////////////////////////////////////////////////////// Public

#region 생성자 - MainForm()

/// <summary>

/// 생성자

/// </summary>

public MainForm()

{

InitializeComponent();

Plot plot = new Plot(800, 600);

Random random = new Random(0);

int pointCount = 500;

double[] xValueArray = DataGen.Consecutive(pointCount);

double[] yValueArray = DataGen.Random(random, pointCount);

double secondSeptile = Common.Quantile(yValueArray, 2, 7);

plot.Title("2번째 7분위수");

plot.AddScatter(xValueArray, yValueArray, lineWidth : 0, markerShape : MarkerShape.openCircle);

plot.AddHorizontalLine(secondSeptile, width : 3, style : LineStyle.Dash);

this.formsPlot.Reset(plot);

this.formsPlot.Refresh();

}

#endregion

}

TestProject.zip

[C#/WINFORM/SCOTTPLOT] Common 클래스 : Percentile 정적 메소드를 사용해 백분위수 구하기

■ Common 클래스의 Percentile 정적 메소드를 사용해 백분위수를 구하는 방법을 보여준다. ▶ 예제 코드 (C#)


using System;

using ScottPlot;
using ScottPlot.Statistics;

Random random = new Random(0);

int pointCount = 500;

double[] valueArray = DataGen.Random(random, pointCount);

double tenthPercentile = Common.Percentile(valueArray, 10);

using System;

using ScottPlot;

using ScottPlot.Statistics;

Random random = new Random(0);

int pointCount = 500;

double[] valueArray = DataGen.Random(random, pointCount);

double tenthPercentile = Common.Percentile(valueArray, 10);

[C#/WINFORM/SCOTTPLOT] 백분위수 차트 만들기

■ 백분위수 차트를 만드는 방법을 보여준다. ▶ MainForm.cs


using System;
using System.Windows.Forms;

using ScottPlot;
using ScottPlot.Statistics;

namespace TestProject
{
    /// <summary>
    /// 메인 폼
    /// </summary>
    public partial class MainForm : Form
    {
        //////////////////////////////////////////////////////////////////////////////////////////////////// Constructor
        ////////////////////////////////////////////////////////////////////////////////////////// Public

        #region 생성자 - MainForm()

        /// <summary>
        /// 생성자
        /// </summary>
        public MainForm()
        {
            InitializeComponent();

            Plot plot = new Plot(800, 600);

            Random random = new Random(0);

            int pointCount = 500;

            double[] xValueArray = DataGen.Consecutive(pointCount);
            double[] yValueArray = DataGen.Random(random, pointCount);

            double tenthPercentile = Common.Percentile(yValueArray, 10);

            plot.Title("10%");

            plot.AddScatter(xValueArray, yValueArray, lineWidth : 0, markerShape : MarkerShape.openCircle);

            plot.AddHorizontalLine(tenthPercentile, width : 3, style : LineStyle.Dash);

            this.formsPlot.Reset(plot);

            this.formsPlot.Refresh();
        }

        #endregion
    }
}

using System;

using System.Windows.Forms;

using ScottPlot;

using ScottPlot.Statistics;

namespace TestProject

{

/// <summary>

/// 메인 폼

/// </summary>

public partial class MainForm : Form

{

//////////////////////////////////////////////////////////////////////////////////////////////////// Constructor

////////////////////////////////////////////////////////////////////////////////////////// Public

#region 생성자 - MainForm()

/// <summary>

/// 생성자

/// </summary>

public MainForm()

{

InitializeComponent();

Plot plot = new Plot(800, 600);

Random random = new Random(0);

int pointCount = 500;

double[] xValueArray = DataGen.Consecutive(pointCount);

double[] yValueArray = DataGen.Random(random, pointCount);

double tenthPercentile = Common.Percentile(yValueArray, 10);

plot.Title("10%");

plot.AddScatter(xValueArray, yValueArray, lineWidth : 0, markerShape : MarkerShape.openCircle);

plot.AddHorizontalLine(tenthPercentile, width : 3, style : LineStyle.Dash);

this.formsPlot.Reset(plot);

this.formsPlot.Refresh();

}

#endregion

}

TestProject.zip

[C#/WINFORM/SCOTTPLOT] LinearRegressionLine 클래스 : 선형 회귀 값 구하기

■ LinearRegressionLine 클래스를 사용해 선형 회귀 값을 구하는 방법을 보여준다. ▶ 예제 코드 (C#)


using System;

using ScottPlot;
using ScottPlot.Statistics;

double[] yValueArray = DataGen.NoisyLinear(null, pointCount : 100, noise : 30);
double[] xValueArray = DataGen.Consecutive(yValueArray.Length);

LinearRegressionLine line = new LinearRegressionLine(xValueArray, yValueArray);

Console.WriteLine($"Y = {line.slope:0.0000}x + {line.offset:0.0} (R² = {line.rSquared:0.0000})");

using System;

using ScottPlot;

using ScottPlot.Statistics;

double[] yValueArray = DataGen.NoisyLinear(null, pointCount : 100, noise : 30);

double[] xValueArray = DataGen.Consecutive(yValueArray.Length);

LinearRegressionLine line = new LinearRegressionLine(xValueArray, yValueArray);

Console.WriteLine($"Y = {line.slope:0.0000}x + {line.offset:0.0} (R² = {line.rSquared:0.0000})");

[C#/WINFORM/SCOTTPLOT] DataGen 클래스 : NoisyLinear 정적 메소드를 사용해 잡음을 갖는 선형 배열 만들기

■ DataGen 클래스의 NoisyLinear 정적 메소드를 사용해 잡음을 갖는 선형 배열을 만드는 방법을 보여준다. ▶ 예제 코드 (C#)


using ScottPlot;

double[] valueArray = DataGen.NoisyLinear(null, pointCount : 100, noise : 30);

using ScottPlot;

double[] valueArray = DataGen.NoisyLinear(null, pointCount : 100, noise : 30);

[C#/WINFORM/SCOTTPLOT] Common 클래스 : NthOrderStatistic 정적 메소드를 사용해 N차 통계 값 구하기

■ Common 클래스의 NthOrderStatistic 정적 메소드를 사용해 N차 통계 값을 구하는 방법을 보여준다. ▶ 예제 코드 (C#)


using System;

using ScottPlot;
using ScottPlot.Statistics;

Random random = new Random(0);

int pointCount = 500;

double[] valueArray = DataGen.Random(random, pointCount);

int n = 200;

double nthValue = Common.NthOrderStatistic(valueArray, n);

using System;

using ScottPlot;

using ScottPlot.Statistics;

Random random = new Random(0);

int pointCount = 500;

double[] valueArray = DataGen.Random(random, pointCount);

int n = 200;

double nthValue = Common.NthOrderStatistic(valueArray, n);

[C#/WINFORM/SCOTTPLOT] N차 통계 차트 만들기

■ N차 통계 차트를 만드는 방법을 보여준다. ▶ MainForm.cs


using System;
using System.Windows.Forms;

using ScottPlot;
using ScottPlot.Statistics;

namespace TestProject
{
    /// <summary>
    /// 메인 폼
    /// </summary>
    public partial class MainForm : Form
    {
        //////////////////////////////////////////////////////////////////////////////////////////////////// Constructor
        ////////////////////////////////////////////////////////////////////////////////////////// Public

        #region 생성자 - MainForm()

        /// <summary>
        /// 생성자
        /// </summary>
        public MainForm()
        {
            InitializeComponent();

            Plot plot = new Plot(800, 600);

            Random random = new Random(0);

            int pointCount = 500;

            double[] xValueArray = DataGen.Consecutive(pointCount);
            double[] yValueArray = DataGen.Random(random, pointCount);

            int n = 200;

            double nthValue = Common.NthOrderStatistic(yValueArray, n);

            plot.Title($"{pointCount}개 중에서 {n}번째로 작은 값");

            plot.AddScatter(xValueArray, yValueArray, lineWidth : 0, markerShape : MarkerShape.openCircle);

            plot.AddHorizontalLine(nthValue, width : 3, style : LineStyle.Dash);

            this.formsPlot.Reset(plot);

            this.formsPlot.Refresh();
        }

        #endregion
    }
}

using System;

using System.Windows.Forms;

using ScottPlot;

using ScottPlot.Statistics;

namespace TestProject

{

/// <summary>

/// 메인 폼

/// </summary>

public partial class MainForm : Form

{

//////////////////////////////////////////////////////////////////////////////////////////////////// Constructor

////////////////////////////////////////////////////////////////////////////////////////// Public

#region 생성자 - MainForm()

/// <summary>

/// 생성자

/// </summary>

public MainForm()

{

InitializeComponent();

Plot plot = new Plot(800, 600);

Random random = new Random(0);

int pointCount = 500;

double[] xValueArray = DataGen.Consecutive(pointCount);

double[] yValueArray = DataGen.Random(random, pointCount);

int n = 200;

double nthValue = Common.NthOrderStatistic(yValueArray, n);

plot.Title($"{pointCount}개 중에서 {n}번째로 작은 값");

plot.AddScatter(xValueArray, yValueArray, lineWidth : 0, markerShape : MarkerShape.openCircle);

plot.AddHorizontalLine(nthValue, width : 3, style : LineStyle.Dash);

this.formsPlot.Reset(plot);

this.formsPlot.Refresh();

}

#endregion

}

TestProject.zip

[C#/WINFORM/SCOTTPLOT] 선형 회귀 차트 만들기

■ 선형 회귀 차트를 만드는 방법을 보여준다. ▶ MainForm.cs


using System.Windows.Forms;

using ScottPlot;
using ScottPlot.Statistics;

namespace TestProject
{
    /// <summary>
    /// 메인 폼
    /// </summary>
    public partial class MainForm : Form
    {
        //////////////////////////////////////////////////////////////////////////////////////////////////// Constructor
        ////////////////////////////////////////////////////////////////////////////////////////// Public

        #region 생성자 - MainForm()

        /// <summary>
        /// 생성자
        /// </summary>
        public MainForm()
        {
            InitializeComponent();

            Plot plot = new Plot(800, 600);

            double[] yValueArray = DataGen.NoisyLinear(null, pointCount : 100, noise : 30);
            double[] xValueArray = DataGen.Consecutive(yValueArray.Length);

            double x1 = xValueArray[0];
            double x2 = xValueArray[xValueArray.Length - 1];

            LinearRegressionLine line = new LinearRegressionLine(xValueArray, yValueArray);

            plot.Title($"선형 회귀\nY = {line.slope:0.0000}x + {line.offset:0.0} (R² = {line.rSquared:0.0000})");
            plot.AddScatter(xValueArray, yValueArray, lineWidth : 0);
            plot.AddLine(line.slope, line.offset, (x1, x2), lineWidth : 2);

            this.formsPlot.Reset(plot);

            this.formsPlot.Refresh();
        }

        #endregion
    }
}

using System.Windows.Forms;

using ScottPlot;

using ScottPlot.Statistics;

namespace TestProject

{

/// <summary>

/// 메인 폼

/// </summary>

public partial class MainForm : Form

{

//////////////////////////////////////////////////////////////////////////////////////////////////// Constructor

////////////////////////////////////////////////////////////////////////////////////////// Public

#region 생성자 - MainForm()

/// <summary>

/// 생성자

/// </summary>

public MainForm()

{

InitializeComponent();

Plot plot = new Plot(800, 600);

double[] yValueArray = DataGen.NoisyLinear(null, pointCount : 100, noise : 30);

double[] xValueArray = DataGen.Consecutive(yValueArray.Length);

double x1 = xValueArray[0];

double x2 = xValueArray[xValueArray.Length - 1];

LinearRegressionLine line = new LinearRegressionLine(xValueArray, yValueArray);

plot.Title($"선형 회귀\nY = {line.slope:0.0000}x + {line.offset:0.0} (R² = {line.rSquared:0.0000})");

plot.AddScatter(xValueArray, yValueArray, lineWidth : 0);

plot.AddLine(line.slope, line.offset, (x1, x2), lineWidth : 2);

this.formsPlot.Reset(plot);

this.formsPlot.Refresh();

}

#endregion

}

TestProject.zip

[C#/WINFORM/SCOTTPLOT] Common 클래스 : CumulativeSum 정적 메소드를 사용해 누적 값 배열 만들기

■ Common 클래스의 CumulativeSum 정적 메소드를 사용해 누적 값 배열을 만드는 방법을 보여준다. ▶ 예제 코드 (C#)


using System;

using ScottPlot;
using ScottPlot.Statistics;

Random random = new Random(0);

double[] valueArray = DataGen.RandomNormal(random, pointCount : 1000, mean : 50, stdDev : 20);

(double[] histogramArray, double[] binEdgeArray) = Common.Histogram(valueArray, min : 0, max : 100, binSize : 1, density : true);

double[] cphArray = Common.CumulativeSum(histogramArray);

using System;

using ScottPlot;

using ScottPlot.Statistics;

Random random = new Random(0);

double[] valueArray = DataGen.RandomNormal(random, pointCount : 1000, mean : 50, stdDev : 20);

(double[] histogramArray, double[] binEdgeArray) = Common.Histogram(valueArray, min : 0, max : 100, binSize : 1, density : true);

double[] cphArray = Common.CumulativeSum(histogramArray);

[C#/WINFORM/SCOTTPLOT] 누적 확률 히스토그램 차트 만들기

■ 누적 확률 히스토그램 차트를 만드는 방법을 보여준다. ▶ MainForm.cs


using System;
using System.Linq;
using System.Windows.Forms;

using ScottPlot;
using ScottPlot.Statistics;

namespace TestProject
{
    /// <summary>
    /// 메인 폼
    /// </summary>
    public partial class MainForm : Form
    {
        //////////////////////////////////////////////////////////////////////////////////////////////////// Constructor
        ////////////////////////////////////////////////////////////////////////////////////////// Public

        #region 생성자 - MainForm()

        /// <summary>
        /// 생성자
        /// </summary>
        public MainForm()
        {
            InitializeComponent();

            Plot plot = new Plot(800, 600);

            Random random = new Random(0);

            double[] valueArray1 = DataGen.RandomNormal(random, pointCount : 1000, mean : 50, stdDev : 20);
            double[] valueArray2 = DataGen.RandomNormal(random, pointCount : 1000, mean : 45, stdDev : 25);

            (double[] histogramArray1, double[] binEdgeArray) = Common.Histogram(valueArray1, min : 0, max : 100, binSize : 1, density : true);
            (double[] histogramArray2, _                    ) = Common.Histogram(valueArray2, min : 0, max : 100, binSize : 1, density : true);

            double[] cphArray1 = Common.CumulativeSum(histogramArray1);
            double[] cphArray2 = Common.CumulativeSum(histogramArray2);

            double[] leftEdgeArray = binEdgeArray.Take(binEdgeArray.Length - 1).ToArray();

            plot.AddScatterStep(xs : leftEdgeArray, ys : cphArray1, label : "샘플 A");
            plot.AddScatterStep(xs : leftEdgeArray, ys : cphArray2, label : "샘플 B");

            plot.Title("누적 확률 히스토그램");
            plot.Legend();
            plot.XAxis.Label("확률(분수)");
            plot.YAxis.Label("값(단위)");
            plot.SetAxisLimits(yMin : 0, yMax : 1);

            this.formsPlot.Reset(plot);

            this.formsPlot.Refresh();
        }

        #endregion
    }
}

using System;

using System.Linq;

using System.Windows.Forms;

using ScottPlot;

using ScottPlot.Statistics;

namespace TestProject

{

/// <summary>

/// 메인 폼

/// </summary>

public partial class MainForm : Form

{

//////////////////////////////////////////////////////////////////////////////////////////////////// Constructor

////////////////////////////////////////////////////////////////////////////////////////// Public

#region 생성자 - MainForm()

/// <summary>

/// 생성자

/// </summary>

public MainForm()

{

InitializeComponent();

Plot plot = new Plot(800, 600);

Random random = new Random(0);

double[] valueArray1 = DataGen.RandomNormal(random, pointCount : 1000, mean : 50, stdDev : 20);

double[] valueArray2 = DataGen.RandomNormal(random, pointCount : 1000, mean : 45, stdDev : 25);

(double[] histogramArray1, double[] binEdgeArray) = Common.Histogram(valueArray1, min : 0, max : 100, binSize : 1, density : true);

(double[] histogramArray2, _ ) = Common.Histogram(valueArray2, min : 0, max : 100, binSize : 1, density : true);

double[] cphArray1 = Common.CumulativeSum(histogramArray1);

double[] cphArray2 = Common.CumulativeSum(histogramArray2);

double[] leftEdgeArray = binEdgeArray.Take(binEdgeArray.Length - 1).ToArray();

plot.AddScatterStep(xs : leftEdgeArray, ys : cphArray1, label : "샘플 A");

plot.AddScatterStep(xs : leftEdgeArray, ys : cphArray2, label : "샘플 B");

plot.Title("누적 확률 히스토그램");

plot.Legend();

plot.XAxis.Label("확률(분수)");

plot.YAxis.Label("값(단위)");

plot.SetAxisLimits(yMin : 0, yMax : 1);

this.formsPlot.Reset(plot);

this.formsPlot.Refresh();

}

#endregion

}

TestProject.zip

[C#/WINFORM/SCOTTPLOT] 다중 히스토그램 차트 만들기

■ 다중 히스토그램 차트를 만드는 방법을 보여준다. ▶ MainForm.cs


using System;
using System.Drawing;
using System.Linq;
using System.Windows.Forms;

using ScottPlot;
using ScottPlot.Plottable;
using ScottPlot.Statistics;

namespace TestProject
{
    /// <summary>
    /// 메인 폼
    /// </summary>
    public partial class MainForm : Form
    {
        //////////////////////////////////////////////////////////////////////////////////////////////////// Constructor
        ////////////////////////////////////////////////////////////////////////////////////////// Public

        #region 생성자 - MainForm()

        /// <summary>
        /// 생성자
        /// </summary>
        public MainForm()
        {
            InitializeComponent();

            Plot plot = new Plot(800, 600);

            Random random = new Random(0);

            double[] maleHeightArray   = DataGen.RandomNormal(random, pointCount : 2345, mean : 178.4, stdDev : 7.6);
            double[] femaleHeightArray = DataGen.RandomNormal(random, pointCount : 1234, mean : 164.7, stdDev : 7.1);

            (double[] malePropabilityArray  , double[] binEdgeArray) = Common.Histogram(maleHeightArray  , min : 140, max : 210, binSize : 1, density : true);
            (double[] femalePropabilityArray, _                    ) = Common.Histogram(femaleHeightArray, min : 140, max : 210, binSize : 1, density : true);

            double[] leftEdgeArray = binEdgeArray.Take(binEdgeArray.Length - 1).ToArray();

            malePropabilityArray   = malePropabilityArray.Select(x => x * 100).ToArray();
            femalePropabilityArray = femalePropabilityArray.Select(x => x * 100).ToArray();

            BarPlot maleBarPlot = plot.AddBar(values : malePropabilityArray, positions : leftEdgeArray);

            maleBarPlot.BarWidth        = 1;
            maleBarPlot.BorderLineWidth = 0;
            maleBarPlot.FillColor       = Color.FromArgb(50, Color.Blue);

            BarPlot femaleBarPlot = plot.AddBar(values : femalePropabilityArray, positions : leftEdgeArray);

            femaleBarPlot.BarWidth        = 1;
            femaleBarPlot.BorderLineWidth = 0;
            femaleBarPlot.FillColor       = Color.FromArgb(50, Color.Red);

            double[] maleProbabilityDensityArray = Common.ProbabilityDensity(maleHeightArray, binEdgeArray, percent : true);

            plot.AddScatterLines
            (
                xs        : binEdgeArray,
                ys        : maleProbabilityDensityArray,
                color     : Color.FromArgb(150, Color.Blue),
                lineWidth : 3,
                label     : $"남성(n={maleHeightArray.Length:N0})"
            );

            double[] femaleProbabilityDensityArray = Common.ProbabilityDensity(femaleHeightArray, binEdgeArray, percent : true);

            plot.AddScatterLines
            (
                xs        : binEdgeArray,
                ys        : femaleProbabilityDensityArray,
                color     : Color.FromArgb(150, Color.Red),
                lineWidth : 3,
                label     : $"여성(n={femaleHeightArray.Length:N0})"
            );

            plot.Title("성별 인간 신장");
            plot.XLabel("신장(cm)");
            plot.YLabel("확률(%)");
            plot.Legend(location : Alignment.UpperLeft);
            plot.SetAxisLimits(yMin : 0);

            this.formsPlot.Reset(plot);

            this.formsPlot.Refresh();
        }

        #endregion
    }
}

using System;

using System.Drawing;

using System.Linq;

using System.Windows.Forms;

using ScottPlot;

using ScottPlot.Plottable;

using ScottPlot.Statistics;

namespace TestProject

{

/// <summary>

/// 메인 폼

/// </summary>

public partial class MainForm : Form

{

//////////////////////////////////////////////////////////////////////////////////////////////////// Constructor

////////////////////////////////////////////////////////////////////////////////////////// Public

#region 생성자 - MainForm()

/// <summary>

/// 생성자

/// </summary>

public MainForm()

{

InitializeComponent();

Plot plot = new Plot(800, 600);

Random random = new Random(0);

double[] maleHeightArray = DataGen.RandomNormal(random, pointCount : 2345, mean : 178.4, stdDev : 7.6);

double[] femaleHeightArray = DataGen.RandomNormal(random, pointCount : 1234, mean : 164.7, stdDev : 7.1);

(double[] malePropabilityArray , double[] binEdgeArray) = Common.Histogram(maleHeightArray , min : 140, max : 210, binSize : 1, density : true);

(double[] femalePropabilityArray, _ ) = Common.Histogram(femaleHeightArray, min : 140, max : 210, binSize : 1, density : true);

double[] leftEdgeArray = binEdgeArray.Take(binEdgeArray.Length - 1).ToArray();

malePropabilityArray = malePropabilityArray.Select(x => x * 100).ToArray();

femalePropabilityArray = femalePropabilityArray.Select(x => x * 100).ToArray();

BarPlot maleBarPlot = plot.AddBar(values : malePropabilityArray, positions : leftEdgeArray);

maleBarPlot.BarWidth = 1;

maleBarPlot.BorderLineWidth = 0;

maleBarPlot.FillColor = Color.FromArgb(50, Color.Blue);

BarPlot femaleBarPlot = plot.AddBar(values : femalePropabilityArray, positions : leftEdgeArray);

femaleBarPlot.BarWidth = 1;

femaleBarPlot.BorderLineWidth = 0;

femaleBarPlot.FillColor = Color.FromArgb(50, Color.Red);

double[] maleProbabilityDensityArray = Common.ProbabilityDensity(maleHeightArray, binEdgeArray, percent : true);

plot.AddScatterLines

(

xs : binEdgeArray,

ys : maleProbabilityDensityArray,

color : Color.FromArgb(150, Color.Blue),

lineWidth : 3,

label : $"남성(n={maleHeightArray.Length:N0})"

);

double[] femaleProbabilityDensityArray = Common.ProbabilityDensity(femaleHeightArray, binEdgeArray, percent : true);

plot.AddScatterLines

(

xs : binEdgeArray,

ys : femaleProbabilityDensityArray,

color : Color.FromArgb(150, Color.Red),

lineWidth : 3,

label : $"여성(n={femaleHeightArray.Length:N0})"

);

plot.Title("성별 인간 신장");

plot.XLabel("신장(cm)");

plot.YLabel("확률(%)");

plot.Legend(location : Alignment.UpperLeft);

plot.SetAxisLimits(yMin : 0);

this.formsPlot.Reset(plot);

this.formsPlot.Refresh();

}

#endregion

}

TestProject.zip

[C#/WINFORM/SCOTTPLOT] 레이블이 지정된 평균 및 표준편차가 있는 히스토그램 차트 만들기

■ 레이블이 지정된 평균 및 표준편차가 있는 히스토그램 차트를 만드는 방법을 보여준다. ▶ MainForm.cs


using System;
using System.Drawing;
using System.Linq;
using System.Windows.Forms;

using ScottPlot;
using ScottPlot.Plottable;
using ScottPlot.Statistics;

namespace TestProject
{
    /// <summary>
    /// 메인 폼
    /// </summary>
    public partial class MainForm : Form
    {
        //////////////////////////////////////////////////////////////////////////////////////////////////// Constructor
        ////////////////////////////////////////////////////////////////////////////////////////// Public

        #region 생성자 - MainForm()

        /// <summary>
        /// 생성자
        /// </summary>
        public MainForm()
        {
            InitializeComponent();

            Plot plot = new Plot(800, 600);

            Random random = new Random(0);

            double[] valueArray = DataGen.RandomNormal(random, pointCount : 1234, mean : 178.4, stdDev : 7.6);

            (double[] countArray, double[] binEdgeArray) = Common.Histogram(valueArray, min : 140, max : 220, binSize : 1);

            double[] leftEdgeArray = binEdgeArray.Take(binEdgeArray.Length - 1).ToArray();

            BarPlot barPlot = plot.AddBar(values : countArray, positions : leftEdgeArray);

            barPlot.BorderLineWidth = 0;
            barPlot.FillColor       = ColorTranslator.FromHtml("#9bc3eb");

            double[] smoothEdgeArray = DataGen.Range(start : binEdgeArray.First(), stop : binEdgeArray.Last(), step : 0.1, includeStop : true);

            double[] smoothDensityArray = Common.ProbabilityDensity(valueArray, smoothEdgeArray, percent : true);

            ScatterPlot scatterPlot = plot.AddScatterLines
            (
                xs        : smoothEdgeArray,
                ys        : smoothDensityArray,
                lineWidth : 2,
                label     : "확률"
            );

            scatterPlot.YAxisIndex = 1;

            plot.YAxis2.Ticks(true);

            BasicStats basicStats = new BasicStats(valueArray);

            plot.AddVerticalLine(basicStats.Mean, Color.Black, 2, LineStyle.Solid, "평균");

            plot.AddVerticalLine(basicStats.Mean - basicStats.StDev, Color.Black, 2, LineStyle.Dash, "1 SD");
            plot.AddVerticalLine(basicStats.Mean + basicStats.StDev, Color.Black, 2, LineStyle.Dash);

            plot.AddVerticalLine(basicStats.Mean - basicStats.StDev * 2, Color.Black, 2, LineStyle.Dot, "2 SD");
            plot.AddVerticalLine(basicStats.Mean + basicStats.StDev * 2, Color.Black, 2, LineStyle.Dot);

            plot.AddVerticalLine(basicStats.Min, Color.Gray, 1, LineStyle.Dash, "최소/최대");
            plot.AddVerticalLine(basicStats.Max, Color.Gray, 1, LineStyle.Dash);

            plot.Legend(location : Alignment.UpperRight);

            plot.Title("성인 남성 신장");
            plot.XAxis.Label("신장(cm)");
            plot.YAxis.Label("횟수(#)");
            plot.YAxis2.Label("확률(%)");
            plot.SetAxisLimits(yMin : 0);
            plot.SetAxisLimits(yMin : 0, yAxisIndex : 1);

            this.formsPlot.Reset(plot);

            this.formsPlot.Refresh();
        }

        #endregion
    }
}

using System;

using System.Drawing;

using System.Linq;

using System.Windows.Forms;

using ScottPlot;

using ScottPlot.Plottable;

using ScottPlot.Statistics;

namespace TestProject

{

/// <summary>

/// 메인 폼

/// </summary>

public partial class MainForm : Form

{

//////////////////////////////////////////////////////////////////////////////////////////////////// Constructor

////////////////////////////////////////////////////////////////////////////////////////// Public

#region 생성자 - MainForm()

/// <summary>

/// 생성자

/// </summary>

public MainForm()

{

InitializeComponent();

Plot plot = new Plot(800, 600);

Random random = new Random(0);

double[] valueArray = DataGen.RandomNormal(random, pointCount : 1234, mean : 178.4, stdDev : 7.6);

(double[] countArray, double[] binEdgeArray) = Common.Histogram(valueArray, min : 140, max : 220, binSize : 1);

double[] leftEdgeArray = binEdgeArray.Take(binEdgeArray.Length - 1).ToArray();

BarPlot barPlot = plot.AddBar(values : countArray, positions : leftEdgeArray);

barPlot.BorderLineWidth = 0;

barPlot.FillColor = ColorTranslator.FromHtml("#9bc3eb");

double[] smoothEdgeArray = DataGen.Range(start : binEdgeArray.First(), stop : binEdgeArray.Last(), step : 0.1, includeStop : true);

double[] smoothDensityArray = Common.ProbabilityDensity(valueArray, smoothEdgeArray, percent : true);

ScatterPlot scatterPlot = plot.AddScatterLines

(

xs : smoothEdgeArray,

ys : smoothDensityArray,

lineWidth : 2,

label : "확률"

);

scatterPlot.YAxisIndex = 1;

plot.YAxis2.Ticks(true);

BasicStats basicStats = new BasicStats(valueArray);

plot.AddVerticalLine(basicStats.Mean, Color.Black, 2, LineStyle.Solid, "평균");

plot.AddVerticalLine(basicStats.Mean - basicStats.StDev, Color.Black, 2, LineStyle.Dash, "1 SD");

plot.AddVerticalLine(basicStats.Mean + basicStats.StDev, Color.Black, 2, LineStyle.Dash);

plot.AddVerticalLine(basicStats.Mean - basicStats.StDev * 2, Color.Black, 2, LineStyle.Dot, "2 SD");

plot.AddVerticalLine(basicStats.Mean + basicStats.StDev * 2, Color.Black, 2, LineStyle.Dot);

plot.AddVerticalLine(basicStats.Min, Color.Gray, 1, LineStyle.Dash, "최소/최대");

plot.AddVerticalLine(basicStats.Max, Color.Gray, 1, LineStyle.Dash);

plot.Legend(location : Alignment.UpperRight);

plot.Title("성인 남성 신장");

plot.XAxis.Label("신장(cm)");

plot.YAxis.Label("횟수(#)");

plot.YAxis2.Label("확률(%)");

plot.SetAxisLimits(yMin : 0);

plot.SetAxisLimits(yMin : 0, yAxisIndex : 1);

this.formsPlot.Reset(plot);

this.formsPlot.Refresh();

}

#endregion

}

TestProject.zip

[C#/WINFORM/SCOTTPLOT] 다축 히스토그램 차트 만들기

■ 다축 히스토그램 차트를 만드는 방법을 보여준다. ▶ MainForm.cs


using System;
using System.Drawing;
using System.Linq;
using System.Windows.Forms;

using ScottPlot;
using ScottPlot.Plottable;
using ScottPlot.Statistics;

namespace TestProject
{
    /// <summary>
    /// 메인 폼
    /// </summary>
    public partial class MainForm : Form
    {
        //////////////////////////////////////////////////////////////////////////////////////////////////// Constructor
        ////////////////////////////////////////////////////////////////////////////////////////// Public

        #region 생성자 - MainForm()

        /// <summary>
        /// 생성자
        /// </summary>
        public MainForm()
        {
            InitializeComponent();

            Plot plot = new Plot(800, 600);

            Random random = new Random(0);

            double[] valueArray = DataGen.RandomNormal(random, pointCount : 1234, mean : 178.4, stdDev : 7.6);

            (double[] countArray, double[] binEdgeArray) = Common.Histogram(valueArray, min : 140, max : 220, binSize : 1);

            double[] leftEdgeArray = binEdgeArray.Take(binEdgeArray.Length - 1).ToArray();

            BarPlot barPlot = plot.AddBar(values : countArray, positions : leftEdgeArray);

            barPlot.BarWidth        = 0.6;
            barPlot.BorderLineWidth = 0;
            barPlot.FillColor       = ColorTranslator.FromHtml("#9bc3eb");

            double[] densityArray = Common.ProbabilityDensity(valueArray, binEdgeArray, percent : true);

            ScatterPlot scatterPlot = plot.AddScatterLines(xs : binEdgeArray, ys : densityArray, lineWidth : 2);

            scatterPlot.YAxisIndex = 1;

            plot.Title("성인 남성 신장");
            plot.XAxis.Label("신장(cm)");
            plot.YAxis.Label("횟수(#)");
            plot.YAxis2.Color(scatterPlot.Color);
            plot.YAxis2.Ticks(true);
            plot.YAxis2.Label("확률(%)");
            plot.SetAxisLimits(yMin : 0);
            plot.SetAxisLimits(yMin : 0, yAxisIndex : 1);

            this.formsPlot.Reset(plot);

            this.formsPlot.Refresh();
        }

        #endregion
    }
}

using System;

using System.Drawing;

using System.Linq;

using System.Windows.Forms;

using ScottPlot;

using ScottPlot.Plottable;

using ScottPlot.Statistics;

namespace TestProject

{

/// <summary>

/// 메인 폼

/// </summary>

public partial class MainForm : Form

{

//////////////////////////////////////////////////////////////////////////////////////////////////// Constructor

////////////////////////////////////////////////////////////////////////////////////////// Public

#region 생성자 - MainForm()

/// <summary>

/// 생성자

/// </summary>

public MainForm()

{

InitializeComponent();

Plot plot = new Plot(800, 600);

Random random = new Random(0);

double[] valueArray = DataGen.RandomNormal(random, pointCount : 1234, mean : 178.4, stdDev : 7.6);

(double[] countArray, double[] binEdgeArray) = Common.Histogram(valueArray, min : 140, max : 220, binSize : 1);

double[] leftEdgeArray = binEdgeArray.Take(binEdgeArray.Length - 1).ToArray();

BarPlot barPlot = plot.AddBar(values : countArray, positions : leftEdgeArray);

barPlot.BarWidth = 0.6;

barPlot.BorderLineWidth = 0;

barPlot.FillColor = ColorTranslator.FromHtml("#9bc3eb");

double[] densityArray = Common.ProbabilityDensity(valueArray, binEdgeArray, percent : true);

ScatterPlot scatterPlot = plot.AddScatterLines(xs : binEdgeArray, ys : densityArray, lineWidth : 2);

scatterPlot.YAxisIndex = 1;

plot.Title("성인 남성 신장");

plot.XAxis.Label("신장(cm)");

plot.YAxis.Label("횟수(#)");

plot.YAxis2.Color(scatterPlot.Color);

plot.YAxis2.Ticks(true);

plot.YAxis2.Label("확률(%)");

plot.SetAxisLimits(yMin : 0);

plot.SetAxisLimits(yMin : 0, yAxisIndex : 1);

this.formsPlot.Reset(plot);

this.formsPlot.Refresh();

}

#endregion

}

TestProject.zip

[C#/WINFORM/SCOTTPLOT] Common 클래스 : ProbabilityDensity 정적 메소드를 사용해 확률 밀도 배열 만들기

■ Common 클래스의 ProbabilityDensity 정적 메소드를 사용해 확률 밀도 배열을 만드는 방법을 보여준다. ▶ 예제 코드 (C#)


using System;
using System.Linq;

using ScottPlot;
using ScottPlot.Statistics;

Random random = new Random(0);

double[] valueArray = DataGen.RandomNormal(random, pointCount : 1234, mean : 178.4, stdDev : 7.6);

(double[] countArray, double[] binEdgeArray) = Common.Histogram(valueArray, min : 140, max : 220, binSize : 1);

double[] densityArray = Common.ProbabilityDensity(valueArray, binEdgeArray, percent : true);

using System;

using System.Linq;

using ScottPlot;

using ScottPlot.Statistics;

Random random = new Random(0);

double[] valueArray = DataGen.RandomNormal(random, pointCount : 1234, mean : 178.4, stdDev : 7.6);

(double[] countArray, double[] binEdgeArray) = Common.Histogram(valueArray, min : 140, max : 220, binSize : 1);

double[] densityArray = Common.ProbabilityDensity(valueArray, binEdgeArray, percent : true);

[C#/WINFORM/SCOTTPLOT] Common 클래스 : Histogram 정적 메소드를 사용해 히스토그램 데이터 만들기

■ Common 클래스의 Histogram 정적 메소드를 사용해 히스토그램 데이터를 만드는 방법을 보여준다. ▶ 예제 코드 (C#)


using System;
using System.Linq;

using ScottPlot;
using ScottPlot.Statistics;

Random random = new Random(0);

double[] valueArray = DataGen.RandomNormal(random, pointCount : 1234, mean : 178.4, stdDev : 7.6);

(double[] countArray, double[] binEdgeArray) = Common.Histogram(valueArray, min : 140, max : 220, binSize : 1);

double[] leftEdgeArray = binEdgeArray.Take(binEdgeArray.Length - 1).ToArray();

using System;

using System.Linq;

using ScottPlot;

using ScottPlot.Statistics;

Random random = new Random(0);

double[] valueArray = DataGen.RandomNormal(random, pointCount : 1234, mean : 178.4, stdDev : 7.6);

(double[] countArray, double[] binEdgeArray) = Common.Histogram(valueArray, min : 140, max : 220, binSize : 1);

double[] leftEdgeArray = binEdgeArray.Take(binEdgeArray.Length - 1).ToArray();

[C#/WINFORM/SCOTTPLOT] DataGen 클래스 : RandomNormal 정적 메소드를 표준 분포 배열 만들기

■ DataGen 클래스의 RandomNormal 정적 메소드를 표준 분포 배열을 만드는 방법을 보여준다. ▶ 예제 코드 (C#)


using System;

using ScottPlot;

Random random = new Random(0);

double[] valueArray = DataGen.RandomNormal(random, pointCount : 1234, mean : 178.4, stdDev : 7.6);

using System;

using ScottPlot;

Random random = new Random(0);

double[] valueArray = DataGen.RandomNormal(random, pointCount : 1234, mean : 178.4, stdDev : 7.6);

[C#/WINFORM/SCOTTPLOT] DataGen 클래스 : Range 정적 메소드를 사용해 범위값 배열 만들기

■ DataGen 클래스의 Range 정적 메소드를 사용해 범위값 배열을 만드는 방법을 보여준다. ▶ 예제 코드 (C#)


using ScottPlot;

double[] xValueArray = DataGen.Range(-5, 5, 0.5);
double[] yValueArray = DataGen.Range(-5, 5, 0.5);

using ScottPlot;

double[] xValueArray = DataGen.Range(-5, 5, 0.5);

double[] yValueArray = DataGen.Range(-5, 5, 0.5);

[C#/WINFORM/SCOTTPLOT] DataGen 클래스 : RandomWalk 정적 메소드를 사용해 임의 값 배열 만들기

■ DataGen 클래스의 RandomWalk 정적 메소드를 사용해 임의 값 배열을 만드는 방법을 보여준다. ▶ 예제 코드 (C#)


using ScottPlot;

double[] valueArray = DataGen.RandomWalk(1000000);

using ScottPlot;

double[] valueArray = DataGen.RandomWalk(1000000);

[C#/WINFORM/SCOTTPLOT] DataGen 클래스 : Cos 정적 메소드를 사용해 코사인 값 배열 만들기

■ DataGen 클래스의 Cos 정적 메소드를 사용해 코사인 값 배열을 만드는 방법을 보여준다. ▶ 예제 코드 (C#)


using ScottPlot;

double[] cosineValueArray = DataGen.Cos(100);

using ScottPlot;

double[] cosineValueArray = DataGen.Cos(100);

[C#/WINFORM/SCOTTPLOT] DataGen 클래스 : Sin 정적 메소드를 사용해 사인 값 배열 만들기

■ DataGen 클래스의 Sin 정적 메소드를 사용해 사인 값 배열을 만드는 방법을 보여준다. ▶ 예제 코드 (C#)


using ScottPlot;

double[] sineValueArray = DataGen.Sin(100);

using ScottPlot;

double[] sineValueArray = DataGen.Sin(100);

[C#/WINFORM/SCOTTPLOT] DataGen 클래스 : Consecutive 정적 메소드를 사용해 연속 값을 갖는 배열 만들기

■ DataGen 클래스의 Consecutive 정적 메소드를 사용해 연속 값을 갖는 배열을 만드는 방법을 보여준다. ▶ 예제 코드 (C#)


using ScottPlot;

double[] xValueArray = DataGen.Consecutive(100);

using ScottPlot;

double[] xValueArray = DataGen.Consecutive(100);

[C#/WINFORM/SCOTTPLOT] 히스토그램 확률 차트 만들기

■ 히스토그램 확률 차트를 만드는 방법을 보여준다. ▶ MainForm.cs


using System;
using System.Drawing;
using System.Linq;
using System.Windows.Forms;

using ScottPlot;
using ScottPlot.Plottable;
using ScottPlot.Statistics;

namespace TestProject
{
    /// <summary>
    /// 메인 폼
    /// </summary>
    public partial class MainForm : Form
    {
        //////////////////////////////////////////////////////////////////////////////////////////////////// Constructor
        ////////////////////////////////////////////////////////////////////////////////////////// Public

        #region 생성자 - MainForm()

        /// <summary>
        /// 생성자
        /// </summary>
        public MainForm()
        {
            InitializeComponent();

            Plot plot = new Plot(800, 600);

            Random random = new Random(0);

            double[] valueArray = DataGen.RandomNormal(random, pointCount : 1234, mean : 178.4, stdDev : 7.6);

            (double[] probabilityArray, double[] binEdgeArray) = Common.Histogram(valueArray, min : 140, max : 220, binSize : 1, density : true);

            double[] leftEdgeArray = binEdgeArray.Take(binEdgeArray.Length - 1).ToArray();

            BarPlot barPlot = plot.AddBar(values : probabilityArray, positions : leftEdgeArray);

            barPlot.BarWidth    = 1;
            barPlot.FillColor   = ColorTranslator.FromHtml("#9bc3eb");
            barPlot.BorderColor = ColorTranslator.FromHtml("#82add9");

            double[] densityArray = Common.ProbabilityDensity(valueArray, binEdgeArray);

            plot.AddScatterLines(xs : binEdgeArray, ys : densityArray, color : Color.Black, lineWidth : 2, lineStyle : LineStyle.Dash);

            plot.Title("성인 남성 신장");
            plot.XAxis.Label("신장(cm)");
            plot.YAxis.Label("확률");
            plot.SetAxisLimits(yMin : 0);

            this.formsPlot.Reset(plot);

            this.formsPlot.Refresh();
        }

        #endregion
    }
}

using System;

using System.Drawing;

using System.Linq;

using System.Windows.Forms;

using ScottPlot;

using ScottPlot.Plottable;

using ScottPlot.Statistics;

namespace TestProject

{

/// <summary>

/// 메인 폼

/// </summary>

public partial class MainForm : Form

{

//////////////////////////////////////////////////////////////////////////////////////////////////// Constructor

////////////////////////////////////////////////////////////////////////////////////////// Public

#region 생성자 - MainForm()

/// <summary>

/// 생성자

/// </summary>

public MainForm()

{

InitializeComponent();

Plot plot = new Plot(800, 600);

Random random = new Random(0);

double[] valueArray = DataGen.RandomNormal(random, pointCount : 1234, mean : 178.4, stdDev : 7.6);

(double[] probabilityArray, double[] binEdgeArray) = Common.Histogram(valueArray, min : 140, max : 220, binSize : 1, density : true);

double[] leftEdgeArray = binEdgeArray.Take(binEdgeArray.Length - 1).ToArray();

BarPlot barPlot = plot.AddBar(values : probabilityArray, positions : leftEdgeArray);

barPlot.BarWidth = 1;

barPlot.FillColor = ColorTranslator.FromHtml("#9bc3eb");

barPlot.BorderColor = ColorTranslator.FromHtml("#82add9");

double[] densityArray = Common.ProbabilityDensity(valueArray, binEdgeArray);

plot.AddScatterLines(xs : binEdgeArray, ys : densityArray, color : Color.Black, lineWidth : 2, lineStyle : LineStyle.Dash);

plot.Title("성인 남성 신장");

plot.XAxis.Label("신장(cm)");

plot.YAxis.Label("확률");

plot.SetAxisLimits(yMin : 0);

this.formsPlot.Reset(plot);

this.formsPlot.Refresh();

}

#endregion

}

TestProject.zip

[C#/WINFORM/SCOTTPLOT] Plot 클래스 : AddBar 메소드를 사용해 히스토그램 차트 만들기

■ Plot 클래스의 AddBar 메소드를 사용해 히스토그램 차트를 만드는 방법을 보여준다. ▶ MainForm.cs


using System.Windows.Forms;

using ScottPlot;
using ScottPlot.Plottable;

namespace TestProject
{
    /// <summary>
    /// 메인 폼
    /// </summary>
    public partial class MainForm : Form
    {
        //////////////////////////////////////////////////////////////////////////////////////////////////// Constructor
        ////////////////////////////////////////////////////////////////////////////////////////// Public

        #region 생성자 - MainForm()

        /// <summary>
        /// 생성자
        /// </summary>
        public MainForm()
        {
            InitializeComponent();

            Plot plot = new Plot(800, 600);

            double[] countArray    = new double[] { 0, 0, 20, 50, 100, 50, 20, 0, 0 };
            double[] positionArray = new double[] { 0, 1, 2 , 3 , 4  , 5 , 6 , 7, 8 };

            BarPlot barPlot = plot.AddBar(values : countArray, positions : positionArray);

            barPlot.BarWidth = 1;

            plot.XAxis.Label("X축");
            plot.XAxis.MinimumTickSpacing(1);
            plot.YAxis.Label("Y축");
            plot.SetAxisLimits(yMin : 0);

            this.formsPlot.Reset(plot);

            this.formsPlot.Refresh();
        }

        #endregion
    }
}

using System.Windows.Forms;

using ScottPlot;

using ScottPlot.Plottable;

namespace TestProject

{

/// <summary>

/// 메인 폼

/// </summary>

public partial class MainForm : Form

{

//////////////////////////////////////////////////////////////////////////////////////////////////// Constructor

////////////////////////////////////////////////////////////////////////////////////////// Public

#region 생성자 - MainForm()

/// <summary>

/// 생성자

/// </summary>

public MainForm()

{

InitializeComponent();

Plot plot = new Plot(800, 600);

double[] countArray = new double[] { 0, 0, 20, 50, 100, 50, 20, 0, 0 };

double[] positionArray = new double[] { 0, 1, 2 , 3 , 4 , 5 , 6 , 7, 8 };

BarPlot barPlot = plot.AddBar(values : countArray, positions : positionArray);

barPlot.BarWidth = 1;

plot.XAxis.Label("X축");

plot.XAxis.MinimumTickSpacing(1);

plot.YAxis.Label("Y축");

plot.SetAxisLimits(yMin : 0);

this.formsPlot.Reset(plot);

this.formsPlot.Refresh();

}

#endregion

}

TestProject.zip

[C#/WINFORM/SCOTTPLOT] Plot 클래스 : AddBar 메소드를 사용해 히스토그램 차트 만들기

■ Plot 클래스의 AddBar 메소드를 사용해 히스토그램 차트를 만드는 방법을 보여준다. ▶ MainForm.cs


using System;
using System.Linq;
using System.Windows.Forms;

using ScottPlot;
using ScottPlot.Plottable;
using ScottPlot.Statistics;

namespace TestProject
{
    /// <summary>
    /// 메인 폼
    /// </summary>
    public partial class MainForm : Form
    {
        //////////////////////////////////////////////////////////////////////////////////////////////////// Constructor
        ////////////////////////////////////////////////////////////////////////////////////////// Public

        #region 생성자 - MainForm()

        /// <summary>
        /// 생성자
        /// </summary>
        public MainForm()
        {
            InitializeComponent();

            Plot plot = new Plot(800, 600);

            Random rand = new Random(0);

            double[] valueArray = DataGen.RandomNormal(rand, pointCount : 1234, mean : 178.4, stdDev : 7.6);

            (double[] countArray, double[] binEdgeArray) = Common.Histogram(valueArray, min : 140, max : 220, binSize : 1);

            double[] leftEdgeArray = binEdgeArray.Take(binEdgeArray.Length - 1).ToArray();

            BarPlot barPlot = plot.AddBar(values: countArray, positions: leftEdgeArray);

            barPlot.BarWidth = 1;

            plot.YAxis.Label("횟수(#)");
            plot.XAxis.Label("신장(cm)");
            plot.SetAxisLimits(yMin : 0);

            this.formsPlot.Reset(plot);

            this.formsPlot.Refresh();
        }

        #endregion
    }
}

using System;

using System.Linq;

using System.Windows.Forms;

using ScottPlot;

using ScottPlot.Plottable;

using ScottPlot.Statistics;

namespace TestProject

{

/// <summary>

/// 메인 폼

/// </summary>

public partial class MainForm : Form

{

//////////////////////////////////////////////////////////////////////////////////////////////////// Constructor

////////////////////////////////////////////////////////////////////////////////////////// Public

#region 생성자 - MainForm()

/// <summary>

/// 생성자

/// </summary>

public MainForm()

{

InitializeComponent();

Plot plot = new Plot(800, 600);

Random rand = new Random(0);

double[] valueArray = DataGen.RandomNormal(rand, pointCount : 1234, mean : 178.4, stdDev : 7.6);

(double[] countArray, double[] binEdgeArray) = Common.Histogram(valueArray, min : 140, max : 220, binSize : 1);

double[] leftEdgeArray = binEdgeArray.Take(binEdgeArray.Length - 1).ToArray();

BarPlot barPlot = plot.AddBar(values: countArray, positions: leftEdgeArray);

barPlot.BarWidth = 1;

plot.YAxis.Label("횟수(#)");

plot.XAxis.Label("신장(cm)");

plot.SetAxisLimits(yMin : 0);

this.formsPlot.Reset(plot);

this.formsPlot.Refresh();

}

#endregion

}

TestProject.zip

[C#/WINFORM/SCOTTPLOT] ColorblindFriendly 팔레트 사용하기

■ ColorblindFriendly 팔레트를 사용하는 방법을 보여준다. ▶ MainForm.cs


using System.Windows.Forms;

using ScottPlot;

namespace TestProject
{
    /// <summary>
    /// 메인 폼
    /// </summary>
    public partial class MainForm : Form
    {
        //////////////////////////////////////////////////////////////////////////////////////////////////// Constructor
        ////////////////////////////////////////////////////////////////////////////////////////// Public

        #region 생성자 - MainForm()

        /// <summary>
        /// 생성자
        /// </summary>
        public MainForm()
        {
            InitializeComponent();

            Plot plot = new Plot(800, 600);

            plot.Palette = Palette.ColorblindFriendly;

            for(int i = 0; i < plot.Palette.Count(); i++)
            {
                double[] xValueArray = DataGen.Consecutive(100);
                double[] yValueArray = DataGen.Sin(100, phase : -i * .5 / plot.Palette.Count());

                plot.AddScatterLines(xValueArray, yValueArray, lineWidth : 3);
            }

            plot.Title($"{plot.Palette}");
            plot.AxisAuto(0, 0.1);

            this.formsPlot.Reset(plot);

            this.formsPlot.Refresh();
        }

        #endregion
    }
}

using System.Windows.Forms;

using ScottPlot;

namespace TestProject

{

/// <summary>

/// 메인 폼

/// </summary>

public partial class MainForm : Form

{

//////////////////////////////////////////////////////////////////////////////////////////////////// Constructor

////////////////////////////////////////////////////////////////////////////////////////// Public

#region 생성자 - MainForm()

/// <summary>

/// 생성자

/// </summary>

public MainForm()

{

InitializeComponent();

Plot plot = new Plot(800, 600);

plot.Palette = Palette.ColorblindFriendly;

for(int i = 0; i < plot.Palette.Count(); i++)

{

double[] xValueArray = DataGen.Consecutive(100);

double[] yValueArray = DataGen.Sin(100, phase : -i * .5 / plot.Palette.Count());

plot.AddScatterLines(xValueArray, yValueArray, lineWidth : 3);

}

plot.Title($"{plot.Palette}");

plot.AxisAuto(0, 0.1);

this.formsPlot.Reset(plot);

this.formsPlot.Refresh();

}

#endregion

}

TestProject.zip