private void HToolStripMenuItem_Click(object sender, EventArgs e)
{
bool[] KTurnOn = KTurnOnFound();
int w = 0;
foreach (bool b in KTurnOn)
{
if (!b)
{
w++;
}
}
double[,] SubK = InitialAnalysMultidimensionalData.SubK(IAM.K, KTurnOn);
double[,] T = TFound(SubK, KTurnOn);
double T_alf_v = Distributions.StudentQuantile(1 - IAM.ISA[0].alf.Q / 2, IAM.N - w - 2);
bool[,] H = new bool[T.GetLength(0), T.GetLength(1)];
for (int i = 0; i < H.GetLength(0); i++)
{
for (int j = 0; j < H.GetLength(1); j++)
{
if (Math.Abs(T[i, j]) <= T_alf_v)
{
H[i, j] = true;
}
}
}
WraitH(CorelDataGridView, H, KTurnOn);
}
internal VisualisationMultiDataForm(InitialAnalysMultidimensionalData IAM)
{
this.IAM = IAM;
InitializeComponent();
WindowState = FormWindowState.Maximized;
HeatMappictureBox.SizeMode = PictureBoxSizeMode.AutoSize;
}
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);
}
}
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);
}
private void TToolStripMenuItem_Click(object sender, EventArgs e)
{
bool[] KTurnOn = KTurnOnFound();
double[,] SubK = InitialAnalysMultidimensionalData.SubK(IAM.K, KTurnOn);
double[,] T = TFound(SubK, KTurnOn);
WraitK(CorelDataGridView, T, KTurnOn);
}
private double S0ij(InitialAnalysMultidimensionalData X, InitialAnalysMultidimensionalData Y, int i, int j, double N1, double N2)
{
double rez = 0;
double xij = 0,
yij = 0,
xi = 0,
xj = 0,
yi = 0,
yj = 0;
xi = X.ISA[i].unsortl.Sum();
yi = Y.ISA[i].unsortl.Sum();
xj = X.ISA[j].unsortl.Sum();
yj = Y.ISA[j].unsortl.Sum();
for (int L = 0; L < N1; L++)
{
xij += X.ISA[i].unsortl[L] * X.ISA[j].unsortl[L];
}
for (int L = 0; L < N2; L++)
{
yij += Y.ISA[i].unsortl[L] * Y.ISA[j].unsortl[L];
}
rez = -(xi + yi) * (xj + yj) / (N1 + N2);
rez += xij + yij;
rez /= N1 + N2 - 2;
return(rez);
}
internal object[] SaveData(InitialAnalysMultidimensionalData IAMD)
{
this.ISA = IAMD.ISA;
type = 2;
comboBox1.Items.Clear();
Namelabel.Text = "Створення " + IAMD.ISA.Count + "-мірних даних";/*
* comboBox1.Items.AddRange(Regex.Split(RegresTypeName.TypeRegresion, "\n"));
* comboBox1.SelectedIndex = 0;*/
comboBox1.Visible = false;
Q1label.Visible = true;
Q1textBox.Visible = true;
Q2label.Visible = true;
Q2textBox.Visible = true;
Q3label.Visible = false;
Q3textBox.Visible = false;
Nlabel.Visible = true;
NtextBox.Visible = true;
Nlabel.Text = "sigma e";
NtextBox.Text = "10";
Q1label.Text = "A";
Q1textBox.Text = "";
Q2label.Text = "A0";
Q2textBox.Text = "";
Q3label.Text = "c";
Q3textBox.Text = "1";
if (this.ShowDialog() != System.Windows.Forms.DialogResult.OK)
{
return(null);
}
return(new object[] { RezDat, comboBox2.SelectedIndex });
}
public Classification(InitialAnalysMultidimensionalData IAM, int index)
{
this.IAM = IAM;
n = IAM.n - 1;
InitializeComponent();
InitializeData(index);
NewDataDataGridView.ColumnCount = n;
NewDataDataGridView.Rows.Add();
}
private double[,] xdF(InitialAnalysMultidimensionalData IAMD)
{
double[,] rez = new double[1, IAMD.n];
for (int i = 0; i < IAMD.E.Length; i++)
{
rez[0, i] = IAMD.E[i];
}
return(rez);
}
public FactorAnalysisMethod(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();
}
public Data SravnSredF(InitialAnalysMultidimensionalData X, InitialAnalysMultidimensionalData Y)
{
Data rez = new Data();
double[,] S0 = S0F(X, Y);
double[,] S1 = S1F(X, Y);
rez.Name = "Рівність багатомірних середніх при рівності DC матриці";
rez.Q = -(N1 + N2 - 2 - n / 2) * Math.Log(Matrix.Determinant(S1) / Matrix.Determinant(S0));
rez.QKvant = Hi.HIF(X.ISA[0].alf.Q, n);
rez.H = rez.Q <= rez.QKvant;
return(rez);
}
public void IAMFound()
{
double[,] X = new double[data.Count, n];
for (int c = 0; c < n; c++)
{
for (int r = 0; r < data.Count; r++)
{
X[r, c] = data[r][c];
}
}
IAM = new InitialAnalysMultidimensionalData(X, -1);
}
private double[,] S0F(InitialAnalysMultidimensionalData X, InitialAnalysMultidimensionalData Y)
{
int n = X.ISA.Count;
double[,] rez = new double[n, n];
for (int i = 0; i < n; i++)
{
for (int j = 0; j < n; j++)
{
rez[i, j] = S0ij(X, Y, i, j, X.ISA[0].unsortl.Length, Y.ISA[0].unsortl.Length);
}
}
return(rez);
}
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;
}
}
}
static public double Normalf(InitialAnalysMultidimensionalData IAM, double[] X)
{
double[,] Xm = new double[1, IAM.n];
double[,] E = new double[1, IAM.n];
for (int c = 0; c < IAM.n; c++)
{
E[0, c] = IAM.Ex[c];
Xm[0, c] = X[c] - IAM.Ex[c];
}
double znam = Math.Sqrt(Math.Pow(2 * Math.PI, IAM.n) * Matrix.Determinant(IAM.DC));
double[,] XEX = Matrix.MultiplicNumber(Matrix.MultiplicMatrix(
Matrix.MultiplicMatrix(Xm, Matrix.InverseMatrix(IAM.DC)), Matrix.TranspMatrix(Xm))
, -0.5);
return(Math.Exp(XEX[0, 0]) / znam);
}
private void CorelatioDataGridView_ColumnHeaderMouseDoubleClick(object sender, DataGridViewCellMouseEventArgs e)
{
bool[] b = new bool[CorelDataGridView.ColumnCount];
int size = 0;
for (int i = 0; i < CorelDataGridView.ColumnCount; i++)
{
if (CorelDataGridView[i, i].Style.BackColor != Color.Red)
{
size++;
b[i] = true;
}
}
if (CorelDataGridView[e.ColumnIndex, 0].Style.BackColor != Color.Red)
{
b[e.ColumnIndex] = false;
size--;
if (size < 2)
{
return;
}
for (int i = 0; i < CorelDataGridView.ColumnCount; i++)
{
CorelDataGridView[i, e.ColumnIndex].Style.BackColor = Color.Red;
CorelDataGridView[e.ColumnIndex, i].Style.BackColor = Color.Red;
CorelDataGridView[i, e.ColumnIndex].Value = "";
CorelDataGridView[e.ColumnIndex, i].Value = "";
}
}
else
{
b[e.ColumnIndex] = true;
size++;
for (int i = 0; i < CorelDataGridView.ColumnCount; i++)
{
if (b[i])
{
CorelDataGridView[i, e.ColumnIndex].Style.BackColor = Color.Green;
CorelDataGridView[e.ColumnIndex, i].Style.BackColor = Color.Green;
}
}
}
CorelDataGridView.TopLeftHeaderCell.Value
= Math.Round(Distributions.StudentQuantile(1 - IAM.ISA[0].alf.Q / 2, IAM.N - (b.Length - size) - 2), 4).ToString();
double[,] SubK = InitialAnalysMultidimensionalData.SubK(IAM.K, b);
WraitK(CorelDataGridView, SubK, b);
}
static public double[,] VFound(InitialAnalysMultidimensionalData IAM)
{
double[,] result = new double[IAM.n, IAM.n];
for (int k = 0; k < IAM.n; k++)
{
for (int p = 0; p < IAM.n; p++)
{
for (int i = 0; i < IAM.N; i++)
{
result[k, p] += (IAM.ISA[k].unsortl[i] - IAM.ISA[k].Mx.Q) *
(IAM.ISA[p].unsortl[i] - IAM.ISA[p].Mx.Q);
}
}
}
V = result;
return(result);
}
private void ReversTransformValueToolStripMenuItem_Click(object sender, EventArgs e)
{
InitialAnalysMultidimensionalData IAMReverse = ReversTransform(IAMIndepended, IAM.eightvector);
int MaxGroup = -1;
for (int j = 0; j < ML.Count; j++)
{
MaxGroup = Math.Max(MaxGroup, ML[j].Group);
}
for (int i = 0; i < IAMReverse.n; i++)
{
IAMReverse.ISA[i].Group = MaxGroup + 1;
ML.Add(IAMReverse.ISA[i]);
undolist.Add(ML[ML.Count - 1].unsortl);
}
WraitData.RefreshList(treeView1, ML);
}
private double[,] SdF(InitialAnalysMultidimensionalData IAMD)
{
double[,] rez;
double[,] X = new double[IAMD.N, IAMD.n];
double[,] XT;
double[,] Ex = xdF(IAMD);
for (int i = 0; i < IAMD.n; i++)
{
for (int l = 0; l < IAMD.N; l++)
{
X[l, i] = IAMD.ISA[i].unsortl[l] - Ex[0, i];
}
}
XT = Matrix.TranspMatrix(X);
rez = Matrix.MultiplicMatrix(XT, X);
rez = Matrix.MultiplicNumber(rez, 1.0 / (IAMD.N - 1));
return(rez);
}
public UniformityDoubleMultidimensionalData(List <InitialStatisticalAnalys> ISA, List <List <int> > ind)
{
X = new InitialAnalysMultidimensionalData(ISA, ind[0], 0);
Y = new InitialAnalysMultidimensionalData(ISA, ind[1], 0);
n = ind[0].Count;
N1 = ISA[ind[0][0]].unsortl.Length;
N2 = ISA[ind[1][0]].unsortl.Length;
for (int i = 1; i < n; i++)
{
if (N1 != ISA[ind[0][i]].unsortl.Length || N2 != ISA[ind[0][i]].unsortl.Length)
{
MessageBox.Show("Not correct input data", "Error", MessageBoxButtons.OK, MessageBoxIcon.Error);
return;
}
}
Refresh();
}
private void ParalCoordchartPaint(InitialAnalysMultidimensionalData IAM, Chart ParalCoordchart)
{
ParalCoordchart.Series.Clear();
for (int row = 0; row < IAM.N; row++)
{
Color color = Color.Red;//ColorFromHSV((360.0 * row / IAM.N),1,1);
Series Line = new Series(row.ToString());
Line.ChartType = System.Windows.Forms.DataVisualization.Charting.SeriesChartType.Line;
Line.Color = color;
for (int col = 0; col < IAM.n; col++)
{
Line.Points.AddXY(col + 1, 2 * (IAM.ISA[col].unsortl[row] - IAM.ISA[col].Min.Q) / IAM.ISA[col].Len.Q - 1);
}
ParalCoordchart.Series.Add(Line);
}
ParalCoordchart.ChartAreas[0].AxisY.Minimum = -1;
ParalCoordchart.ChartAreas[0].AxisY.Maximum = 1;
ParalCoordchart.ChartAreas[0].AxisX.Minimum = 1;
ParalCoordchart.ChartAreas[0].AxisX.Maximum = IAM.n;
}
private void UppperValueToolStripMenuItem_Click(object sender, EventArgs e)
{
bool[] KTurnOn = KTurnOnFound();
int w = 0;
foreach (bool b in KTurnOn)
{
if (!b)
{
w++;
}
}
double[,] SubK = InitialAnalysMultidimensionalData.SubK(IAM.K, KTurnOn);
double[,] V2 = new double[SubK.GetLength(0), SubK.GetLength(1)];
double[,] BV = new double[SubK.GetLength(0), SubK.GetLength(1)];
double U = Distributions.NormalQuantile(1 - IAM.ISA[0].alf.Q / 2);
U /= (IAM.N - w - 3);
for (int col = 0; col < SubK.GetLength(1); col++)
{
for (int row = 0; row < SubK.GetLength(0); row++)
{
if (KTurnOn[col] && KTurnOn[row])
{
V2[row, col] = Math.Log((1 + SubK[row, col]) / (1 - SubK[row, col])) / 2 + U;
double exp = Math.Exp(2 * V2[row, col]);
if (double.IsInfinity(exp))
{
BV[row, col] = 1;
}
else
{
BV[row, col] = (exp - 1.0) / (exp + 1.0);
}
}
}
}
WraitK(CorelDataGridView, BV, KTurnOn);
}
private void RadarchartPaint(InitialAnalysMultidimensionalData IAM, Color RadarCol, int n, Chart RadarChart)
{
Font font = new Font("Times New Roman", 14.0f);
RadarChart.ChartAreas.Clear();
RadarChart.Series.Clear();
RadarChart.Titles.Clear();
for (int i = 0; i < n && i + NumRadaraData < IAM.N; i++)
{
string ChartAreaName = i.ToString();
Title titl = new Title((i + 1 + NumRadaraData).ToString(), Docking.Bottom, font, Color.DarkBlue);
titl.DockedToChartArea = ChartAreaName;
RadarChart.Titles.Add(titl);
ChartArea ChartArea1 = new ChartArea(ChartAreaName);
ChartArea1.AxisY.Maximum = 1;
ChartArea1.AxisX.LabelStyle.Enabled = false;
ChartArea1.AxisY.LabelStyle.Enabled = false;
ChartArea1.AxisY.MajorGrid.Enabled = false;
RadarChart.ChartAreas.Add(ChartArea1);
Series ser = new Series(ChartAreaName + "_Ser");
ser.ChartType = System.Windows.Forms.DataVisualization.Charting.SeriesChartType.Radar;
ser["PointWidth"] = "1";
ser.BorderWidth = 1;
ser.Color = RadarCol;
ser.BorderColor = Color.Black;
for (int col = 0; col < IAM.n; col++)
{
ser.Points.AddXY(col, (IAM.ISA[col].unsortl[i + NumRadaraData] - IAM.ISA[col].Min.Q) / IAM.ISA[col].Len.Q);
}
ser.ChartArea = ChartAreaName;
RadarChart.Series.Add(ser);
}
}
private void HeatMappictureBoxPaint(InitialAnalysMultidimensionalData IAM, Color MaxValueCol, PictureBox HeatMapPuctureBox)
{
Font font = new Font("Times New Roman", 14.0f);
int width = panel1.Width - 20;
int height = 25 * IAM.N;
double stepcol = width / IAM.n;
double steprow = height / IAM.N;
Bitmap BM = new Bitmap(width, height);
using (Graphics gr = Graphics.FromImage(BM))
{
for (int row = 0; row < IAM.N; row++)
{
for (int col = 0; col < IAM.n; col++)
{
double s = (IAM.ISA[col].unsortl[row] - IAM.ISA[col].Min.Q) / IAM.ISA[col].Len.Q;
if (s == 0)
{
}
SolidBrush f = new SolidBrush(
Color.FromArgb(
255 - (int)((255 - MaxValueCol.R) * s),
255 - (int)((255 - MaxValueCol.G) * s),
255 - (int)((255 - MaxValueCol.B) * s)));
gr.FillRectangle(f,
(float)(col * stepcol),
(float)(row * steprow),
(float)((col + 1) * stepcol),
(float)((row + 1) * steprow));
}
gr.DrawString((row + 1).ToString(), font, Brushes.Green, 10, (float)(row * steprow));
}
gr.Dispose();
}
HeatMapPuctureBox.Image = BM;
}
public SubCorelationClass(InitialAnalysMultidimensionalData IAM)
{
this.IAM = IAM;
CorelTabPage = TapPageCreate();
}
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();
}
