public MainComponentMethod(InitialAnalysMultidimensionalData IAM,
ref List <InitialStatisticalAnalys> ML, ref List <double[]> undolist, ref TreeView treeView1)
{
this.IAM = IAM;
this.ML = ML;
this.undolist = undolist;
this.treeView1 = treeView1;
DataTabPage = TapPageCreate();
SetData();
if (IAM.n == 2)
{
Correlation_RegressionAnalysis CRA = new Correlation_RegressionAnalysis(new List <InitialStatisticalAnalys>()
{
IAM.ISA[0], IAM.ISA[1]
},
new List <int>()
{
0, 1
}, RegresTypeName.LineRegresion);
picture.Image = PaintData.Paintf(CRA, picture.Width, picture.Height);
}
}
private InitialAnalysMultidimensionalData ReversTransform(InitialAnalysMultidimensionalData IAMIndepended, double[,] eightvector)
{
double[,] eightvectorClone = new double[eightvector.GetLength(1), IAMIndepended.Xall.GetLength(1)];
for (int r = 0; r < eightvectorClone.GetLength(0); r++)
{
for (int c = 0; c < eightvectorClone.GetLength(1); c++)
{
eightvectorClone[r, c] = eightvector[r, c];
}
}
double[,] X = Matrix.MultiplicMatrix(IAMIndepended.Xall, Matrix.TranspMatrix(eightvectorClone));
InitialAnalysMultidimensionalData result = new InitialAnalysMultidimensionalData(X, -1);
if (IAM.n == 2)
{
double corel = IAM.K[0, 1];
double fi = Math.Atan(2 * corel * IAM.ISA[0].Gx.Q * IAM.ISA[1].Gx.Q /
(Math.Pow(IAM.ISA[0].Gx.Q, 2) - Math.Pow(IAM.ISA[1].Gx.Q, 2))) / 2;
picture.Image = PaintData.RotateImage(new Bitmap(picture.Image), -fi);
}
return(result);
}
public Classterization(InitialAnalysMultidimensionalData IAM,
ref List <InitialStatisticalAnalys> ML, ref List <double[]> undolist, ref TreeView treeView1)
{
this.IAM = IAM;
this.ML = ML;
this.undolist = undolist;
this.treeView1 = treeView1;
Data = new List <double[]>();
for (int i = 0; i < IAM.N; i++)
{
double[] value = new double[IAM.n];
for (int j = 0; j < IAM.n; j++)
{
value[j] = IAM.Xall[i, j];
}
Data.Add(value);
}
InitializeComponent();
SetData();
if (IAM.n == 2)
{
chart.Series.Add(PaintData.CorelPaint(IAM.ISA[0].unsortl, IAM.ISA[1].unsortl, Color.Blue, ""));
chart.Series.Add(ClassterCenterSer);
}
}
static public void DrawClassters(Chart chart, Classter[] classters)
{
for (int i = 0; i < classters.Length; i++)
{
chart.Series.Add(PaintData.CorelPaint(classters[i].IAM.ISA[0].unsortl, classters[i].IAM.ISA[1].unsortl,
PaintData.HsvToRgb(360.0 * i / classters.Length, 1, 1), "Класстер: " + (i + 1).ToString()));
}
}
private void Classterizate_Click(object sender, EventArgs e)
{
Classter.ChangeD(TypeDComboBox.Text);
Classter.ChangeDSS(TypeDSSComboBox.Text);
Classter.VFound(IAM);
if (MethodComboBox.SelectedIndex == 0)
{
if (Classters.Count < 2)
{
return;
}
KAverage();
}
else if (MethodComboBox.SelectedIndex == 1)
{
AdditionalInformationForm AIF = new AdditionalInformationForm("Введіть K");
int index;
try
{ index = Convert.ToInt32(AIF.getString()); }
catch
{ return; }
AgmomerativClassterizate(index > 1 ? index : 2);
}
if (IAM.n == 2)
{
chart.Series[0].Enabled = chart.Series[1].Enabled = Classterizate.Visible = false;
}
int MaxGroup = -1;
for (int j = 0; j < ML.Count; j++)
{
MaxGroup = Math.Max(MaxGroup, ML[j].Group);
}
for (int i = 0; i < Classters.Count; i++)
{
InitialStatisticalAnalys[] ISA = Classters[i].ToISA(MaxGroup + i + 1);
if (IAM.n == 2)
{
chart.Series.Add(
PaintData.CorelPaint(ISA[0].unsortl, ISA[1].unsortl, GetColor(i),
"Classter" + (i + 1).ToString()));
chart.Series[chart.Series.Count - 1].MarkerSize = 10;
}
for (int j = 0; j < ISA.Length; j++)
{
ML.Add(ISA[j]);
undolist.Add(ML[ML.Count - 1].unsortl);
}
}
WraitData.RefreshList(treeView1, ML);
Classter.QFound(Classters.ToArray());
ShowQ(Classter.Q);
}
private void CorelAreachartPaint(InitialAnalysMultidimensionalData IAM, Color CorelCol, Color GistCol, Chart CorelChart, Color ColLine)
{
for (int i = 0; i < IAM.n; i++)
{
for (int j = 0; j < IAM.n; j++)
{
string ChartAreaName = j.ToString() + "_" + i.ToString();
ChartArea ChartArea1 = new ChartArea(ChartAreaName);
ChartArea1.AxisX.LabelStyle.Enabled = false;
ChartArea1.AxisY.LabelStyle.Enabled = false;
CorelChart.ChartAreas.Add(ChartArea1);
var po = CorelAreachart.ChartAreas[0].Position;
Series ser;
if (i != j)
{
InitialStatisticalAnalys ISAX = new InitialStatisticalAnalys(InitialStatisticalAnalys.StandData(IAM.ISA[i].unsortl, IAM.ISA[i].Gx.Q, IAM.ISA[i].Mx.Q));
InitialStatisticalAnalys ISAY = new InitialStatisticalAnalys(InitialStatisticalAnalys.StandData(IAM.ISA[j].unsortl, IAM.ISA[j].Gx.Q, IAM.ISA[j].Mx.Q));
ser = PaintData.CorelPaint(ISAX.unsortl, ISAY.unsortl, CorelCol, ChartAreaName);
ser.MarkerStyle = MarkerStyle.Circle;
CorelChart.Series.Add(ser);
double Sz = 0;
if (Correlation_RegressionAnalysis.KorelationZnach(IAM.K[i, j], IAM.N, IAM.ISA[0].alf.Q))
{
List <Data> Param = Correlation_RegressionAnalysis.RegresParamFound(
ISAX,
ISAY,
IAM.K[i, j], RegresTypeName.LineRegresion, ref Sz);
Series serReg = PaintData.LineRegresPaint(ISAX.Min.Q,
ISAX.Max.Q,
Param[0].Q,
Param[1].Q,
ColLine,
ChartAreaName + "Line");
serReg.ChartArea = ChartAreaName;
CorelChart.Series.Add(serReg);
}
}
else
{
ser = PaintData.GistogPaint(IAM.ISA[i], GistCol, ChartAreaName);
CorelChart.Series.Add(ser);
}
ser.ChartArea = ChartAreaName;
}
}
}
private void BottomValueToolStripMenuItem_Click(object sender, EventArgs e)
{
try { MinimalDispersValue = Convert.ToDouble(MinimalDispers.Text); }
catch { MinimalDispersValue = 0; }
if (IAM.n == 2)
{
double corel = IAM.K[0, 1];
double fi = Math.Atan(2 * corel * IAM.ISA[0].Gx.Q * IAM.ISA[1].Gx.Q /
(Math.Pow(IAM.ISA[0].Gx.Q, 2) - Math.Pow(IAM.ISA[1].Gx.Q, 2))) / 2;
picture.Image = PaintData.RotateImage(new Bitmap(picture.Image), fi);
}
double[,] Xallstandart = new double[IAM.Xall.GetLength(0), IAM.Xall.GetLength(1)];
for (int i = 0; i < IAM.Xall.GetLength(0); i++)
{
for (int j = 0; j < IAM.Xall.GetLength(1); j++)
{
Xallstandart[i, j] = (IAM.Xall[i, j] - IAM.Ex[j]) /* / IAM.ISA[j].Gx.Q*/;
}
}
double[,] X = Matrix.MultiplicMatrix(Xallstandart, IAM.eightvector);
int MaxGroup = -1;
for (int j = 0; j < ML.Count; j++)
{
MaxGroup = Math.Max(MaxGroup, ML[j].Group);
}
List <int> index = new List <int>();
for (int i = 0; i < IAM.n; i++)
{
List <double> Data = new List <double>();
for (int j = 0; j < IAM.N; j++)
{
Data.Add(X[j, i]);
}
InitialStatisticalAnalys ISA = new InitialStatisticalAnalys(Data, MaxGroup + 1);
if (ISA.Dx.Q >= MinimalDispersValue)
{
ML.Add(ISA);
index.Add(ML.Count - 1);
undolist.Add(ML[ML.Count - 1].unsortl);
}
}
WraitData.RefreshList(treeView1, ML);
IAMIndepended = new InitialAnalysMultidimensionalData(ML, index, -1);
IAMIndependedToRevers = new InitialAnalysMultidimensionalData(X, 1);
ReversTransformValueToolStripMenuItem.Visible = true;
Procent = new double[IAM.n];
for (int c = 0; c < IAM.n; c++)
{
for (int r = 0; r < IAMIndepended.Xall.GetLength(1); r++)
{
Procent[c] += Math.Pow(IAM.eightvector[r, c], 2);
}
Procent[c] *= 100;
}
DataGridView.Rows.Clear();
SetData();
SetNextData();
}
static public void Repaint(InitialStatisticalAnalys gr, InitialStatisticalAnalys gr2, Correlation_RegressionAnalysis CRA, Chart chart1, Chart chart2)
{
chart1.ChartAreas[0].AxisX.LabelStyle.Format = "###,##0.000";
chart1.ChartAreas[0].AxisY.LabelStyle.Format = "###,##0.000";
chart2.ChartAreas[0].AxisX.LabelStyle.Format = "###,##0.000";
chart2.ChartAreas[0].AxisY.LabelStyle.Format = "###,##0.000";
///++++++++++++++++++++++++++++++++++++++++++++++
///GISTOGAMA_PAINT
///++++++++++++++++++++++++++++++++++++++++++++++
chart1.Series.Clear();
chart2.Series.Clear();
if (CRA.f == null)
{
return;
}
chart1.Series.Add(CorelPaint(gr.unsortl, gr2.unsortl, Color.DarkBlue, "f"));
chart1.ChartAreas[0].AxisX.Minimum = gr.Min.Q - gr.Len.Q * 0.05;
chart1.ChartAreas[0].AxisX.Maximum = gr.Max.Q + gr.Len.Q * 0.05;
chart1.ChartAreas[0].AxisX.Interval = Math.Round(gr.Len.Q * 0.1, 3);
chart1.ChartAreas[0].AxisY.Interval = Math.Round(gr2.Len.Q * 0.1, 3);
chart1.ChartAreas[0].AxisY.Minimum = gr2.Min.Q - gr2.Len.Q * 0.05;
chart1.ChartAreas[0].AxisY.Maximum = gr2.Max.Q + gr2.Len.Q * 0.05;
chart2.ChartAreas[0].AxisX.Minimum = chart2.ChartAreas[0].AxisY.Minimum = 0;
chart2.ChartAreas[0].AxisX.Maximum = CRA.f.GetLength(0);
chart2.ChartAreas[0].AxisY.Maximum = CRA.f.GetLength(1);
chart2.ChartAreas[0].AxisX.Interval = chart2.ChartAreas[0].AxisY.Interval = 100;
chart1.Titles[0].Text = "y";
chart1.Titles[1].Text = "x";
chart2.Titles[0].Text = "x";
chart2.Titles[1].Text = "y";
chart2.ChartAreas[0].AxisY.CustomLabels.Clear();
/*for (int j = 0; j < CRA.f.GetLength(0); j++)
* {
* string str2 = "";
* for (int k = 0; k < CRA.f.GetLength(1); k++)
* {
* str2 = "f" + j.ToString() + "_" + k.ToString();
* chart2.Series.Add(str2);
* chart2.Series[str2].ChartType = System.Windows.Forms.DataVisualization.Charting.SeriesChartType.Point;
* chart2.Series[str2].MarkerStyle = MarkerStyle.Square;
* chart2.Series[str2].IsVisibleInLegend = false;
* chart2.Series[str2].MarkerSize = (chart2.Size.Width - 20 + k * 10) / CRA.f.GetLength(0);
* //chart2.Series[str2]["PixelPointWidth"] = "200";//PointWidth
* double z = CRA.f[j, k];
* if (z > 0.07)
* chart2.Series[str2].Color = Color.Black;
* else
* {
* int r = 255 - (int)(255 * CRA.f[j, k] / 0.07);
* chart2.Series[str2].Color = Color.FromArgb(r, r, r);
* }
* //chart2.Series[str2].Color = Color.FromArgb(r, r, r);
* //chart2.Series[str2]["StackedGroupName"] = "Group" + j.ToString();
* chart2.Series[str2].Points.AddXY(j + 0.5,
* k + 0.5);
* }
* }*/
Image d = PaintData.Paintf(CRA, 1000, 1000);
NamedImage ni = new NamedImage("backimage", d);
chart2.Images.Add(ni);
chart2.ChartAreas[0].BackImageAlignment = ChartImageAlignmentStyle.Center;
chart2.ChartAreas[0].BackImageWrapMode = ChartImageWrapMode.Scaled;
chart2.ChartAreas[0].BackImage = "backimage";
if (CRA.Doubl == true && CRA.Nezal == true)
{
chart1.Series.Add("Лін Рег" + ":" + CRA.RegresTypeVib);
chart1.Series["Лін Рег" + ":" + CRA.RegresTypeVib].ChartType = System.Windows.Forms.DataVisualization.Charting.SeriesChartType.Line;
chart1.Series["Лін Рег" + ":" + CRA.RegresTypeVib].Color = Color.Yellow;
chart1.Series["Лін Рег" + ":" + CRA.RegresTypeVib].BorderWidth = 3;
if (CRA.RegresTypeVib == RegresTypeName.LineRegresion)
{
//CRA.ABTeil
///teilor
chart1.Series.Add("Лін Рег Тейл");
chart1.Series["Лін Рег Тейл"].ChartType = System.Windows.Forms.DataVisualization.Charting.SeriesChartType.Line;
chart1.Series["Лін Рег Тейл"].Color = Color.Green;
chart1.Series["Лін Рег Тейл"].Points.AddXY(gr.Min.Q, CRA.ABTeil[0] + gr.Min.Q * CRA.ABTeil[1]);
chart1.Series["Лін Рег Тейл"].BorderWidth = 3;
chart1.Series["Лін Рег Тейл"].Points.AddXY(gr.Max.Q, CRA.ABTeil[0] + gr.Max.Q * CRA.ABTeil[1]);
}
chart1.Series.Add("Тол меж");
chart1.Series["Тол меж"].ChartType = System.Windows.Forms.DataVisualization.Charting.SeriesChartType.Line;
chart1.Series["Тол меж"].Color = Color.DarkRed;
chart1.Series["Тол меж"].BorderWidth = 2;
chart1.Series.Add("Тол меж2");
chart1.Series["Тол меж2"].ChartType = System.Windows.Forms.DataVisualization.Charting.SeriesChartType.Line;
chart1.Series["Тол меж2"].Color = chart1.Series["Тол меж"].Color;
chart1.Series["Тол меж2"].IsVisibleInLegend = false;
chart1.Series["Тол меж2"].BorderWidth = 2;
chart1.Series.Add("Дов інтр");
chart1.Series["Дов інтр"].ChartType = System.Windows.Forms.DataVisualization.Charting.SeriesChartType.Line;
chart1.Series["Дов інтр"].Color = Color.DarkMagenta;
chart1.Series["Дов інтр"].BorderWidth = 2;
chart1.Series.Add("Дов інтр2");
chart1.Series["Дов інтр2"].ChartType = System.Windows.Forms.DataVisualization.Charting.SeriesChartType.Line;
chart1.Series["Дов інтр2"].Color = chart1.Series["Дов інтр"].Color;
chart1.Series["Дов інтр2"].IsVisibleInLegend = false;
chart1.Series["Дов інтр2"].BorderWidth = 2;
if (CRA.RegresTypeVib != RegresTypeName.ParabRegresion)
{
for (double x0 = gr.Min.Q; x0 <= gr.Max.Q; x0 += gr.Len.Q * 0.005)
{
double Sx0 = Math.Sqrt(CRA.Szal * (1 + 1.0 / gr.l.Count) + CRA.Q[1].QSigma * Math.Pow(x0 - gr.Mx.Q, 2));
if (CRA.RegresTypeVib == RegresTypeName.LineRegresion)
{
chart1.Series["Дов інтр"].Points.AddXY(x0, RegresType.Model(x0, CRA.Q, CRA.RegresTypeVib) - CRA.T * Sx0);
chart1.Series["Дов інтр2"].Points.AddXY(x0, RegresType.Model(x0, CRA.Q, CRA.RegresTypeVib) + CRA.T * Sx0);
}
chart1.Series["Тол меж"].Points.AddXY(x0, RegresType.Model(x0, CRA.Q, CRA.RegresTypeVib) - CRA.T * CRA.Szal);
chart1.Series["Тол меж2"].Points.AddXY(x0, RegresType.Model(x0, CRA.Q, CRA.RegresTypeVib) + CRA.T * CRA.Szal);
}
for (double x0 = gr.Min.Q; x0 <= gr.Max.Q; x0 += gr.Len.Q * 0.005)
{
chart1.Series["Лін Рег" + ":" + CRA.RegresTypeVib].Points.AddXY(x0, RegresType.Model(x0, CRA.Q, CRA.RegresTypeVib));
}
}
else if (CRA.RegresTypeVib == RegresTypeName.ParabRegresion)
{
double x2 = InitialStatisticalAnalys.StartMoment(gr.l, 2);
double x3 = InitialStatisticalAnalys.StartMoment(gr.l, 3);
double x4 = InitialStatisticalAnalys.StartMoment(gr.l, 4);
double Tt = Distributions.StudentQuantile(1 - gr.alf.Q / 2, gr.unsortl.Length - 3);
for (double x0 = gr.Min.Q; x0 <= gr.Max.Q; x0 += gr.Len.Q * 0.005)
{
double Sx0 = Math.Sqrt(Math.Pow(CRA.Szal2, 2) * (1 + 1.0 / gr.l.Count) +
Math.Pow(CRA.Q[4].QSigma * Correlation_RegressionAnalysis.fi1F(x0, gr.Mx.Q), 2) +
Math.Pow(CRA.Q[5].QSigma * Correlation_RegressionAnalysis.fi2F(x0, gr.Dx.Q, gr.Mx.Q, x2, x3), 2));
/*
* chart1.Series["Дов інтр"].Points.AddXY(x0, RegresType.Model(x0, CRA.Q, CRA.RegresTypeVib) - CRA.T * Sx0);
* chart1.Series["Дов інтр2"].Points.AddXY(x0, RegresType.Model(x0, CRA.Q, CRA.RegresTypeVib) + CRA.T * Sx0);*/
chart1.Series["Дов інтр"].Points.AddXY(x0, CRA.Q[3].Q + CRA.Q[4].Q * Correlation_RegressionAnalysis.fi1F(x0, gr.Mx.Q)
+ CRA.Q[5].Q * Correlation_RegressionAnalysis.fi2F(x0, gr.Dx.Q, gr.Mx.Q, x2, x3)
- Tt * Sx0);
chart1.Series["Дов інтр2"].Points.AddXY(x0, CRA.Q[3].Q + CRA.Q[4].Q * Correlation_RegressionAnalysis.fi1F(x0, gr.Mx.Q)
+ CRA.Q[5].Q * Correlation_RegressionAnalysis.fi2F(x0, gr.Dx.Q, gr.Mx.Q, x2, x3)
+ Tt * Sx0);
chart1.Series["Тол меж"].Points.AddXY(x0, CRA.Q[3].Q + CRA.Q[4].Q * Correlation_RegressionAnalysis.fi1F(x0, gr.Mx.Q)
+ CRA.Q[5].Q * Correlation_RegressionAnalysis.fi2F(x0, gr.Dx.Q, gr.Mx.Q, x2, x3)
- Tt * CRA.Szal2);
chart1.Series["Тол меж2"].Points.AddXY(x0, CRA.Q[3].Q + CRA.Q[4].Q * Correlation_RegressionAnalysis.fi1F(x0, gr.Mx.Q)
+ CRA.Q[5].Q * Correlation_RegressionAnalysis.fi2F(x0, gr.Dx.Q, gr.Mx.Q, x2, x3)
+ Tt * CRA.Szal2);
}
for (double x0 = gr.Min.Q; x0 <= gr.Max.Q; x0 += gr.Len.Q * 0.005)
{
chart1.Series["Лін Рег" + ":" + CRA.RegresTypeVib].Points.AddXY(x0, CRA.Q[3].Q + CRA.Q[4].Q * Correlation_RegressionAnalysis.fi1F(x0, gr.Mx.Q)
+ CRA.Q[5].Q * Correlation_RegressionAnalysis.fi2F(x0, gr.Dx.Q, gr.Mx.Q, x2, x3));
}
}
}
}
