public Matrix compress(int k)
{
//Setting up compression matrix
int rows = matrix.RowCount;
int cols = matrix.ColumnCount;
Matrix VK = new Matrix(cols, k);
Matrix UK = new Matrix(rows, k);
double SK;
Matrix Ak = new Matrix(rows, cols);
//Begin compressing matrix according to algorithm
Console.WriteLine("Compressing matrix... K = " + k);
for (int i = 0; i < k; i++)
{
//Making V, U, and S for compressed matrix
VK = v.GetColumnVector(i).ToColumnMatrix();
UK = u.GetColumnVector(i).ToColumnMatrix();
SK = d[i, i];
//Performing operations on V, U, S
VK.Transpose();
UK = UK.Multiply(VK);
UK.Multiply(SK);
Ak.Add(UK);
}
//Returning data
SV1 = d[0, 0];
SVK1 = d[k + 1, k + 1];
Console.WriteLine("SV1: " + d[0, 0] + " SVK1: " + d[k + 1, k + 1]);
return Ak;
}
public Regression(double[] xdata, double[] ydata, int degree)
{
int numberOfSamples = xdata.Length;
//Define the results
coefficients = new double[degree + 1];
predicted = new double[numberOfSamples];
//Set up X and Y Matricies
Matrix YMatrix = new Matrix(ydata, numberOfSamples);
Matrix XMatrix = new Matrix(numberOfSamples, degree + 1);
XMatrix.SetColumnVector(new Vector(numberOfSamples, 1.0), 0);
for (int i = 0; i < degree; i++)
{
XMatrix.SetColumnVector(new Vector(RaisePower(xdata, i + 1)), i + 1);
}
//Do the calcs
Matrix XTranspose = Matrix.Transpose(XMatrix);
Matrix Temp = (XTranspose * XMatrix).Inverse();
Matrix hat = XMatrix.Multiply(Temp).Multiply(XTranspose);
Matrix result = Temp.Multiply(XTranspose * YMatrix);
//Get the coefficients
coefficients = result.GetColumnVector(0);
//Calculate the predicted values
Matrix Y = new Matrix(ydata, ydata.Count());
predicted = hat.Multiply(Y).GetColumnVector(0);
}
public void calc2DCoords()
{
// From http://en.wikipedia.org/wiki/3D_projection#Perspective_projection :
//
// Point(X|Y|X) a{x,y,z} The point in 3D space that is to be projected.
// Cube.Camera(X|Y|X) c{x,y,z} The location of the camera.
// Cube.Theta(X|Y|X) 0{x,y,z} The rotation of the camera. When c{x,y,z}=<0,0,0>, and 0{x,y,z}=<0,0,0>, the 3D vector <1,2,0> is projected to the 2D vector <1,2>.
// Cube.Viewer(X|Y|X) e{x,y,z} The viewer's position relative to the display surface.
// Bsub(X|Y) b{x,y} The 2D projection of a.
//
double BsubX, BsubY;
Matrix convMat1, convMat2, convMat3, convMat4, convMat41, convMat42, DsubXYZ;
double CosThetaX = Math.Cos(Cube.ThetaX); double SinThetaX = Math.Sin(Cube.ThetaX);
double CosThetaY = Math.Cos(Cube.ThetaY); double SinThetaY = Math.Sin(Cube.ThetaY);
double CosThetaZ = Math.Cos(Cube.ThetaZ); double SinThetaZ = Math.Sin(Cube.ThetaZ);
convMat1 = new Matrix(new double[][] {
new double[] { 1, 0, 0 },
new double[] { 0, CosThetaX, ((-1)*(SinThetaX)) },
new double[] { 0, SinThetaX, CosThetaX }
});
convMat2 = new Matrix(new double[][] {
new double[] { CosThetaY, 0, SinThetaY },
new double[] { 0, 1, 0 },
new double[] { ((-1)*(SinThetaY)), 0, CosThetaY }
});
convMat3 = new Matrix(new double[][] {
new double[] { CosThetaZ, ((-1)*(SinThetaZ)), 0 },
new double[] { SinThetaZ, CosThetaZ, 0 },
new double[] { 0, 0, 1 }
});
convMat41 = new Matrix(new double[][] {
new double[] { X3 },
new double[] { Y3 },
new double[] { Z3 }
});
convMat42 = new Matrix(new double[][] {
new double[] { Cube.CameraX },
new double[] { Cube.CameraY },
new double[] { Cube.CameraZ }
});
convMat4 = convMat41.Clone();
convMat4.Subtract(convMat42);
DsubXYZ = ((convMat1.Multiply(convMat2)).Multiply(convMat3)).Multiply(convMat4);
BsubX = (DsubXYZ[0, 0] - Cube.ViewerX) / (Cube.ViewerZ / DsubXYZ[2, 0]);
BsubY = (DsubXYZ[1, 0] - Cube.ViewerY) / (Cube.ViewerZ / DsubXYZ[2, 0]);
X2 = (int)((BsubX * 50) + 250);
Y2 = (int)((BsubY * 50) + 250);
// Can include Math.Sqrt() here if needed. Math.Sqrt() is slow so its omitted. Doesn't change anything.
distanceFromViewer = Math.Pow((X3 - Cube.ViewerX), 2) + Math.Pow((Y3 - Cube.ViewerY), 2) + Math.Pow((Z3 - Cube.ViewerZ), 2);
}
public static double[] cameraTransform(double PointX, double PointY, double PointZ)
{
// From http://en.wikipedia.org/wiki/3D_projection#Perspective_projection :
//
// Point(X|Y|X) a{x,y,z} The point in 3D space that is to be projected.
// Cube.Camera(X|Y|X) c{x,y,z} The location of the camera.
// Cube.Theta(X|Y|X) θ{x,y,z} The rotation of the camera. When c{x,y,z}=<0,0,0>, and 0{x,y,z}=<0,0,0>, the 3D vector <1,2,0> is projected to the 2D vector <1,2>.
// Cube.Viewer(X|Y|X) e{x,y,z} The viewer's position relative to the display surface.
// Bsub(X|Y) b{x,y} The 2D projection of a.
//
// "First, we define a point DsubXYZ as a translation of point a{x,y,z} into a coordinate system defined by
// c{x,y,z}. This is achieved by subtracting c{x,y,z} from a{x,y,z} and then applying a vector rotation matrix
// using -θ{x,y,z} to the result. This transformation is often called a camera transform (note that these
// calculations assume a left-handed system of axes)."
MathNet.Numerics.LinearAlgebra.Matrix convMat1, convMat2, convMat3, convMat4, convMat41, convMat42, DsubXYZ;
double CosThetaX = Math.Cos(Camera.RotationX); double SinThetaX = Math.Sin(Camera.RotationX);
double CosThetaY = Math.Cos(Camera.RotationY); double SinThetaY = Math.Sin(Camera.RotationY);
double CosThetaZ = Math.Cos(Camera.RotationZ); double SinThetaZ = Math.Sin(Camera.RotationZ);
convMat1 = new MathNet.Numerics.LinearAlgebra.Matrix(new double[][] {
new double[] { 1, 0, 0 },
new double[] { 0, CosThetaX, ((-1)*(SinThetaX)) },
new double[] { 0, SinThetaX, CosThetaX }
});
convMat2 = new MathNet.Numerics.LinearAlgebra.Matrix(new double[][] {
new double[] { CosThetaY, 0, SinThetaY },
new double[] { 0, 1, 0 },
new double[] { ((-1)*(SinThetaY)), 0, CosThetaY }
});
convMat3 = new MathNet.Numerics.LinearAlgebra.Matrix(new double[][] {
new double[] { CosThetaZ, ((-1)*(SinThetaZ)), 0 },
new double[] { SinThetaZ, CosThetaZ, 0 },
new double[] { 0, 0, 1 }
});
convMat41 = new MathNet.Numerics.LinearAlgebra.Matrix(new double[][] {
new double[] { PointX },
new double[] { PointY },
new double[] { PointZ }
});
convMat42 = new MathNet.Numerics.LinearAlgebra.Matrix(new double[][] {
new double[] { Camera.X },
new double[] { Camera.Y },
new double[] { Camera.Z }
});
convMat4 = convMat41.Clone();
convMat4.Subtract(convMat42);
DsubXYZ = ((convMat1.Multiply(convMat2)).Multiply(convMat3)).Multiply(convMat4);
double[] returnVals = new double[3];
returnVals[0] = DsubXYZ[0, 0]; returnVals[1] = DsubXYZ[1, 0]; returnVals[2] = DsubXYZ[2, 0];
return returnVals;
}
public void TrainSet(IEnumerable<Example> testData)
{
double lambda = 0.0;
double m = 1.0;
var a = new Vector<double>[3];
var d = new Vector<double>[3];
Delta0.Clear();
Delta1.Clear();
foreach (var sample in testData)
{
m = (double)sample.X.Count;
a[0] = sample.X;
a[1] = Theta0.Multiply(a[0]).Map(SpecialFunctions.Logistic);
a[2] = Theta1.Multiply(a[1]).Map(SpecialFunctions.Logistic);
d[2] = a[2] - sample.Y;
d[1] = BackPropogate(Theta1, a[1], d[2]);
// d[0] = BackPropogate(Theta0, a[0], d[1]);
Delta1 = Delta1 + d[2].ToColumnMatrix().Multiply(a[1].ToColumnMatrix());
Delta0 = Delta0 + d[1].ToColumnMatrix().Multiply(a[0].ToColumnMatrix());
}
var D0 = Delta0.Multiply(1/m);// ignoring regularisation + Theta0.Multiply(lambda);
var D1 = Delta1.Multiply(1/m);
var unrolledTheta0 = (Theta0.RowCount*Theta0.ColumnCount);
var unrolledTheta1 = (Theta1.RowCount + Theta1.ColumnCount);
var thetaVec = new double[unrolledTheta0 + unrolledTheta1];
var DVec = new double[unrolledTheta0 + unrolledTheta1];
Theta0.ToColumnWiseArray().CopyTo(thetaVec,0);
Theta1.ToColumnWiseArray().CopyTo(thetaVec, unrolledTheta1);
D0.ToColumnWiseArray().CopyTo(DVec,0);
D1.ToColumnWiseArray().CopyTo(DVec,unrolledTheta1);
//lbfgsb.ComputeMin(BananaFunction, BananaFunctionGradient, initialGuess);
}
public ILinearRegressionModel BuildModel(Matrix<double> matrixX, Vector<double> vectorY, ILinearRegressionParams regressionParams)
{
var weightsVector = Vector<double>.Build.DenseOfArray(
Enumerable.Range(0, matrixX.ColumnCount)
.Select(fIdx => randomizer.NextDoubleInRange(weightsMin, weightsMax))
.ToArray());
double previousIterError = double.PositiveInfinity;
for (int iterNo = 0; iterNo < iterations; iterNo++)
{
var vectorYHat = matrixX.Multiply(weightsVector);
var diffVector = vectorYHat.Subtract(vectorY);
var currentIterError = diffVector.Select(Math.Abs).Sum();
if ((currentIterError <= stopLerningError) ||
currentIterError.AlmostEqual(previousIterError, 5))
{
break;
}
for (int weightIdx = 0; weightIdx < weightsVector.Count; weightIdx++)
{
var diffSums = 0.0;
for (int rowIdx = 0; rowIdx < matrixX.RowCount; rowIdx++)
{
diffSums += diffVector[rowIdx] * matrixX.Row(rowIdx)[weightIdx];
}
var newWeightValue = CalculateWeightUpdate(
matrixX,
regressionParams,
diffSums,
weightsVector[weightIdx]);
weightsVector[weightIdx] = newWeightValue;
}
previousIterError = currentIterError;
}
return new LinearRegressionModel(weightsVector);
}
/// <summary>
/// Count the number of black/white transitions for a single ellipse
/// </summary>
/// <param name="e">Ellipse</param>
/// <param name="matrix">Affine ellipse frame that transforms the ellipse to a circle located at origin</param>
/// <param name="gray">Binary image</param>
/// <returns>The number of black/white transitions found</returns>
private int CountBinaryTransitions(DetectedEllipse e, Matrix matrix, Emgu.CV.Image<Gray, byte> gray) {
// Generate points on circle
double r = e.Ellipse.MCvBox2D.size.Height * 0.5;
double t_step = (2 * Math.PI) / _number_circle_points;
System.Drawing.Rectangle rect = new System.Drawing.Rectangle(System.Drawing.Point.Empty, gray.Size);
int count_transitions = 0;
double last_intensity = 0;
for (double t = 0; t <= 2 * Math.PI; t += t_step) {
Vector v = new Vector(new double[] { r * Math.Cos(t), r * Math.Sin(t), 1.0 });
Vector x = matrix.Multiply(v.ToColumnMatrix()).GetColumnVector(0);
System.Drawing.Point p = new System.Drawing.Point((int)Math.Round(x[0]), (int)Math.Round(x[1]));
if (rect.Contains(p)) {
if (t == 0) {
last_intensity = gray[p].Intensity;
} else {
double i = gray[p].Intensity;
if (i != last_intensity) {
count_transitions += 1;
last_intensity = i;
}
}
}
}
return count_transitions;
}
private Matrix<float> getHidden(Matrix<float> data, Func<float, float> f)
{
// calculate hidden probabilities or states
Matrix<float> hidden = data.Multiply(this.weights).Map(logistic, Zeros.Include).Map(f);
// reset bias
hidden.SetColumn(0, Vector<float>.Build.Dense(hidden.RowCount, 1.0f));
return hidden;
}
public Vector3DHomogeneous TransformBy(Matrix<double> m)
{
return new Vector3DHomogeneous(m.Multiply(this.ToVector()));
}
protected void Page_Load(object sender, EventArgs e)
{
Matrix PCmatrix = (Matrix)stream.get("PCmatrix");
String[] features = (String[])stream.get("selectedFeatures");
System.Data.DataSet ds = (System.Data.DataSet)registry.GetDataset((string)stream.get("dataSetName"));
//retrieve dataset table (assume one for now)
System.Data.DataTable dt = ds.Tables[0];
//raw data
double[,] rawData = new double[dt.Rows.Count, features.Count()];
for (int i = 0; i < dt.Rows.Count; i++)
{
for (int j = 0; j < features.Count(); j++)
rawData[i, j] = (double)dt.Rows[i].ItemArray.ElementAt(dt.Columns[features[j]].Ordinal);
}
//Create matrix to hold data for PCA
Matrix X = new Matrix(rawData);
//Remove mean
Vector columnVector;
for (int i = 0; i < X.ColumnCount; i++)
{
columnVector = X.GetColumnVector(i);
X.SetColumnVector(columnVector.Subtract(columnVector.Average()), i);
}
//get first two PCs
Matrix xy = new Matrix(PCmatrix.RowCount,2);
xy.SetColumnVector(PCmatrix.GetColumnVector(0),0);
xy.SetColumnVector(PCmatrix.GetColumnVector(1),1);
//project
Matrix projected = X.Multiply(xy);
DataPoint point;
Projection.Series.Clear();
Projection.Legends.Clear();
//if a label column is selected
String LabelColumnName = LabelColumn.Text;
if (!LabelColumnName.Equals(""))
{
//get labels
int labelColumnIndex = dt.Columns[LabelColumnName].Ordinal;
List<String> labels = new List<String>();
String item;
for (int i = 0; i < dt.Rows.Count; i++)
{
item = (String)dt.Rows[i].ItemArray.ElementAt(labelColumnIndex);
if (!labels.Contains(item))
labels.Add(item);
}
Projection.Legends.Add(LabelColumnName);
System.Drawing.Font font = Projection.Legends[LabelColumnName].Font = new System.Drawing.Font(Projection.Legends[LabelColumnName].Font.Name, 14);
//Configure series
foreach (String label in labels)
{
Projection.Series.Add(label);
Projection.Series[label].LegendText = label;
Projection.Series[label].IsXValueIndexed = false;
Projection.Series[label].ChartType = SeriesChartType.Point;
Projection.Series[label].MarkerSize = 8;
}
//Add points
for (int i = 0; i < projected.RowCount; i++)
{
point = new DataPoint(projected[i, 0], projected[i, 1]);
String label = dt.Rows[i].ItemArray[labelColumnIndex].ToString();
Projection.Series[label].Points.Add(point);
}
}
else
{
//Single plot graph
Projection.Series.Add("series1");
Projection.Series[0].IsXValueIndexed = false;
Projection.Series[0].ChartType = SeriesChartType.Point;
Projection.Series[0].MarkerSize = 8;
for (int i = 0; i < projected.RowCount; i++)
{
point = new DataPoint(projected[i, 0], projected[i, 1]);
Projection.Series[0].Points.Add(point);
}
}
}
/// <summary>
/// Returns a DataEntry containing the coordinates of the i-th entry
/// computed with the eigenvectors as basis vectors.
/// </summary>
/// <param name="key">
/// The index of the entry
/// </param>
/// <returns>
/// A <see cref="DataEntry"/> with the coordinates
/// </returns>
public DataEntry GetCoordinate(int key)
{
Matrix m = new Matrix(2, num_params);
m.SetRowVector(base1, 0);
m.SetRowVector(base2, 1);
Matrix coord = m.Multiply(vector_map[key].ToColumnMatrix());
Debug.Assert(coord.RowCount == 2 && coord.ColumnCount == 1);
return new DataEntry (key, coord[0,0], coord[1,0], null);
}
// CONTROL ADDITION -------------------------------------------------------------------------------------------------------------
Control addcontrol(string[, ,] controlarray, HtmlTableCell cell, HtmlTableRow row, int col_traverse, int row_traverse)
{
// Generic return object
Control returncontrol = new Control();
// Specific object generation methods
switch(controlarray[col_traverse, row_traverse, 0])
{
case "LABEL": // Label control
{
// Create new control
Label newlabel = new Label();
// Set control properties
newlabel.Font.Name = "Arial"; newlabel.Font.Size = 11;
newlabel.ID = "control_" + col_traverse + "_" + row_traverse;
// Add control
cell.Controls.Add(newlabel);
returncontrol = newlabel;
break;
}
case "TEXTBOX":
{
// Create new control
TextBox newtextbox = new TextBox();
Label newlabel = new Label();
// Set textbox control properties
newtextbox.Font.Name = "Arial"; newtextbox.Font.Size = 11;
newtextbox.ID = "control_" + col_traverse + "_" + row_traverse;
newtextbox.Width = Unit.Pixel(Convert.ToInt16(cell.Width.Substring(0,cell.Width.Length-2))*cell.ColSpan - 2*(layouttable.Border + layouttable.CellPadding));
// Set label control properties
newlabel.Font.Name = "Arial"; newlabel.Font.Size = 11;
// Add control
cell.Controls.Add(newlabel);
cell.Controls.Add(new LiteralControl("<br><br>"));
cell.Controls.Add(newtextbox);
// Return label for text fill
//returncontrol = newtextbox;
returncontrol = newlabel;
break;
}
case "MULTISELECT":
{
// Create new control
ListBox newlistbox = new ListBox();
Label newlabel = new Label();
// Set listbox control properties
newlistbox.Font.Name = "Arial"; newlistbox.Font.Size = 11;
newlistbox.ID = "control_" + col_traverse + "_" + row_traverse;
newlistbox.Width = Unit.Pixel(Convert.ToInt16(cell.Width.Substring(0, cell.Width.Length - 2)) * cell.ColSpan - 2 * (layouttable.Border + layouttable.CellPadding));
newlistbox.SelectionMode = ListSelectionMode.Multiple;
// Set label control properties
newlabel.Font.Name = "Arial"; newlabel.Font.Size = 11;
newlabel.ID = "control_" + col_traverse + "_" + row_traverse + "_label";
// Add control
cell.Controls.Add(newlabel);
cell.Controls.Add(new LiteralControl("<br><br>"));
cell.Controls.Add(newlistbox);
// Return label for text fill
//returncontrol = newtextbox;
returncontrol = newlistbox;
break;
}
case "IMAGE":
{
// Create new control
Image newimage = new Image();
// Set control properties
newimage.ID = "control_" + col_traverse + "_" + row_traverse;
newimage.Width = Unit.Pixel(Convert.ToInt16(cell.Width.Substring(0, cell.Width.Length - 2)) * cell.ColSpan - 2 * (layouttable.Border + layouttable.CellPadding));
newimage.Height = Unit.Pixel(Convert.ToInt16(row.Height.Substring(0, row.Height.Length - 2)) * cell.RowSpan - 2 * (layouttable.Border + layouttable.CellPadding));
// Add control
cell.Controls.Add(newimage);
returncontrol = newimage;
break;
}
case "TABLE":
{
// Enclose table in panel
Panel tablepanel = new Panel();
tablepanel.ScrollBars = ScrollBars.Both;
tablepanel.Width = Unit.Pixel(Convert.ToInt16(cell.Width.Substring(0, cell.Width.Length - 2)) * cell.ColSpan - (layouttable.Border + layouttable.CellPadding));
tablepanel.Height = Unit.Pixel(Convert.ToInt16(row.Height.Substring(0, row.Height.Length - 2)) * cell.RowSpan - (layouttable.Border + layouttable.CellPadding));
// Create new control
GridView newtable = new GridView();
// Set control properties
newtable.ID = "control_" + col_traverse + "_" + row_traverse;
newtable.Width = Unit.Pixel((int)(tablepanel.Width.Value - 17));
newtable.Height = Unit.Pixel((int)(tablepanel.Height.Value - 17));
newtable.Font.Name = "Arial"; newtable.Font.Size = 11;
newtable.HeaderStyle.BackColor = System.Drawing.Color.Silver;
newtable.RowStyle.BackColor = System.Drawing.Color.White;
newtable.RowStyle.HorizontalAlign = HorizontalAlign.Center;
// Add control
tablepanel.Controls.Add(newtable);
cell.Controls.Add(tablepanel);
returncontrol = tablepanel;
break;
}
case "SCATTERPLOT":
{
Chart Projection = new Chart();
Series newseries = new Series();
newseries.ChartType = SeriesChartType.Point;
Projection.ChartAreas.Add(new ChartArea());
Projection.ChartAreas[0].AxisY.Title = "Second Principal Component";
Projection.ChartAreas[0].AxisX.Title = "First Principal Component";
Projection.Width = Unit.Pixel(Convert.ToInt16(cell.Width.Substring(0, cell.Width.Length - 2)) * cell.ColSpan - 2 * (layouttable.Border + layouttable.CellPadding));
Projection.Height = Unit.Pixel(Convert.ToInt16(row.Height.Substring(0, row.Height.Length - 2)) * cell.RowSpan - 2 * (layouttable.Border + layouttable.CellPadding));
DataMiningApp.Analysis.ParameterStream stream;
Registry.Registry registry;
stream = DataMiningApp.Analysis.ParameterStream.getStream(Session);
registry = Registry.Registry.getRegistry(Session);
Matrix PCmatrix = (Matrix)stream.get("PCmatrix");
String[] features = (String[])stream.get("selectedFeatures");
System.Data.DataSet ds = (System.Data.DataSet)registry.GetDataset((string)stream.get("dataSetName"));
//retrieve dataset table (assume one for now)
System.Data.DataTable dt = ds.Tables[0];
//raw data
double[,] rawData = new double[dt.Rows.Count, features.Count()];
for (int i = 0; i < dt.Rows.Count; i++)
{
for (int j = 0; j < features.Count(); j++)
rawData[i, j] = (double)dt.Rows[i].ItemArray.ElementAt(dt.Columns[features[j]].Ordinal);
}
//Create matrix to hold data for PCA
Matrix X = new Matrix(rawData);
//Remove mean
Vector columnVector;
for (int i = 0; i < X.ColumnCount; i++)
{
columnVector = X.GetColumnVector(i);
X.SetColumnVector(columnVector.Subtract(columnVector.Average()), i);
}
//get first two PCs
Matrix xy = new Matrix(PCmatrix.RowCount, 2);
xy.SetColumnVector(PCmatrix.GetColumnVector(0), 0);
xy.SetColumnVector(PCmatrix.GetColumnVector(1), 1);
//project
Matrix projected = X.Multiply(xy);
DataPoint point;
Projection.Series.Clear();
Projection.Legends.Clear();
//if a label column is selected
String LabelColumnName = "Species";
if (!LabelColumnName.Equals(""))
{
//get labels
int labelColumnIndex = dt.Columns[LabelColumnName].Ordinal;
List<String> labels = new List<String>();
String item;
for (int i = 0; i < dt.Rows.Count; i++)
{
item = (String)dt.Rows[i].ItemArray.ElementAt(labelColumnIndex);
if (!labels.Contains(item))
labels.Add(item);
}
Legend mylegend = Projection.Legends.Add(LabelColumnName);
mylegend.TableStyle = LegendTableStyle.Wide;
Projection.Legends[0].Docking = Docking.Bottom;
System.Drawing.Font font = Projection.Legends[LabelColumnName].Font = new System.Drawing.Font(Projection.Legends[LabelColumnName].Font.Name, 14);
//Configure series
foreach (String label in labels)
{
Projection.Series.Add(label);
Projection.Series[label].LegendText = label;
Projection.Series[label].IsXValueIndexed = false;
Projection.Series[label].ChartType = SeriesChartType.Point;
Projection.Series[label].MarkerSize = 8;
}
//Add points
for (int i = 0; i < projected.RowCount; i++)
{
point = new DataPoint(projected[i, 0], projected[i, 1]);
String label = dt.Rows[i].ItemArray[labelColumnIndex].ToString();
Projection.Series[label].Points.Add(point);
}
}
else
{
//Single plot graph
Projection.Series.Add("series1");
Projection.Series[0].IsXValueIndexed = false;
Projection.Series[0].ChartType = SeriesChartType.Point;
Projection.Series[0].MarkerSize = 8;
for (int i = 0; i < projected.RowCount; i++)
{
point = new DataPoint(projected[i, 0], projected[i, 1]);
Projection.Series[0].Points.Add(point);
}
}
cell.Controls.Add(Projection);
returncontrol = Projection;
/*
// Create new control
Chart chartcontrol = new Chart();
// Set chart width and height
chartcontrol.Width = Unit.Pixel(Convert.ToInt16(cell.Width.Substring(0, cell.Width.Length - 2)) * cell.ColSpan - 2 * (layouttable.Border + layouttable.CellPadding));
chartcontrol.Height = Unit.Pixel(Convert.ToInt16(row.Height.Substring(0, row.Height.Length - 2)) * cell.RowSpan - 2 * (layouttable.Border + layouttable.CellPadding));
// Needed so server knows where to store temporary image
chartcontrol.ImageStorageMode = ImageStorageMode.UseImageLocation;
ChartArea mychartarea = new ChartArea();
chartcontrol.ChartAreas.Add(mychartarea);
Series myseries = new Series();
myseries.Name = "Series";
chartcontrol.Series.Add(myseries);
chartcontrol.Series["Series"].ChartType = SeriesChartType.Point;
// Add control
cell.Controls.Add(chartcontrol);
returncontrol = chartcontrol;
*/
break;
}
case "LINEPLOT":
{
DataMiningApp.Analysis.ParameterStream stream = DataMiningApp.Analysis.ParameterStream.getStream(Session);
Vector Weights = (Vector)stream.get("Weights");
Chart VariancePlot = new Chart();
VariancePlot.Width = Unit.Pixel(Convert.ToInt16(cell.Width.Substring(0, cell.Width.Length - 2)) * cell.ColSpan - 2 * (layouttable.Border + layouttable.CellPadding));
VariancePlot.Height = Unit.Pixel(Convert.ToInt16(row.Height.Substring(0, row.Height.Length - 2)) * cell.RowSpan - 2 * (layouttable.Border + layouttable.CellPadding));
VariancePlot.Palette = ChartColorPalette.EarthTones;
Series dataseries = new Series();
dataseries.ChartType = SeriesChartType.Line;
dataseries.MarkerColor = System.Drawing.Color.Black;
dataseries.MarkerBorderWidth = 3;
dataseries.MarkerBorderColor = System.Drawing.Color.Black;
VariancePlot.Series.Add(dataseries);
VariancePlot.ChartAreas.Add(new ChartArea());
VariancePlot.ChartAreas[0].AxisY.Title = "Variance Explained";
VariancePlot.ChartAreas[0].AxisX.Title = "Principal Component";
for (int i = 0; i < Weights.Length; i++)
VariancePlot.Series[0].Points.InsertY(i, Weights[i]);
cell.Controls.Add(VariancePlot);
returncontrol = VariancePlot;
break;
}
case "UPLOAD":
{
// Create new controls
Label uploadlabel = new Label();
FileUpload uploadcontrol = new FileUpload();
HiddenField savedfile = new HiddenField(); HiddenField savedpath = new HiddenField();
Button uploadbutton = new Button();
GridView uploadtable = new GridView();
// Create panel to enclose table to it can scroll without having to scroll entire window
Panel tablepanel = new Panel();
tablepanel.ScrollBars = ScrollBars.Both;
tablepanel.Width = Unit.Pixel(Convert.ToInt16(cell.Width.Substring(0, cell.Width.Length - 2)) * cell.ColSpan - (layouttable.Border + layouttable.CellPadding));
tablepanel.Height = Unit.Pixel(Convert.ToInt16(row.Height.Substring(0, row.Height.Length - 2)) * cell.RowSpan - (layouttable.Border + layouttable.CellPadding));
// Set IDs for all controls (necessary to get information after postback on upload)
uploadlabel.ID = "control_" + col_traverse + "_" + row_traverse + "_label";
savedfile.ID = "control_" + col_traverse + "_" + row_traverse + "_savedfile";
savedpath.ID = "control_" + col_traverse + "_" + row_traverse + "_savedpath";
uploadcontrol.ID = "control_" + col_traverse + "_" + row_traverse;
uploadtable.ID = "control_" + col_traverse + "_" + row_traverse + "_table";
uploadbutton.ID = "control_" + col_traverse + "_" + row_traverse + "_button";
// Set control properties
uploadbutton.Text = "Load File";
uploadbutton.Font.Name = "Arial"; uploadbutton.Font.Size = 10;
uploadbutton.Width = 100;
uploadbutton.Click += new System.EventHandler(uploadbutton_Click);
uploadlabel.Font.Name = "Arial"; uploadlabel.Font.Size = 11;
uploadlabel.ForeColor = System.Drawing.Color.Black;
uploadcontrol.Width = Unit.Pixel((int)(tablepanel.Width.Value - 17) - (int)uploadbutton.Width.Value);
uploadtable.Width = Unit.Pixel((int)(tablepanel.Width.Value - 17));
uploadtable.Height = Unit.Pixel((int)(tablepanel.Height.Value - 17));
uploadtable.Font.Name = "Arial"; uploadtable.Font.Size = 11;
uploadtable.HeaderStyle.BackColor = System.Drawing.Color.Silver;
uploadtable.RowStyle.BackColor = System.Drawing.Color.White;
uploadtable.RowStyle.HorizontalAlign = HorizontalAlign.Center;
// Add controls to form and format
tablepanel.Controls.Add(uploadlabel);
tablepanel.Controls.Add(new LiteralControl("<br><br>"));
tablepanel.Controls.Add(uploadcontrol);
tablepanel.Controls.Add(uploadbutton);
tablepanel.Controls.Add(new LiteralControl("<br><br>"));
tablepanel.Controls.Add(uploadtable);
// Add controls to scrollable panel
cell.Controls.Add(tablepanel);
// Return uploadcontrol, even though this control itself does not need to be filled (need control type)
returncontrol = uploadcontrol;
break;
}
}
return returncontrol;
}
/// <summary>
/// Impeller vibration frequency calculater with Prohl method
/// </summary>
/// <param name="impeller">Input impeller</param>
/// <param name="state">State object</param>
private void ProhlCalculator(Impeller impeller, ProhlState state)
{
#if TRACER
watch.Start();
#endif
// the non-zero numbers of root state vector
const int ROOT_STATE_VECTOR_SIZE = 2;
var transferMatrix = new Matrix(4, 4);
var residualMatrix = new Matrix(2, 2);
//vibration frequency order
var rootStateVector = new Matrix[2]{
new Matrix(
new double[][]{
new double[] {0},
new double[] {0},
new double[] {1},
new double[] {0}
}
),
new Matrix(
new double[][]{
new double[] {0},
new double[] {0},
new double[] {0},
new double[] {1}
}
)
};
//section transfer matrix and hole transfer matrix(from root to end)
var sectionTransferMatrix = new Matrix(
new double[][]{
new double[] {1,1,1,1},
new double[] {0,1,1,1},
new double[] {0,0,1,1},
new double[] {1,1,1,1}
}
);
#if TRACER
long step1 = watch.ElapsedTicks;
#endif
double freq2 = state.Omega * state.Omega;
for (var j = 0; j < ROOT_STATE_VECTOR_SIZE; j++)
{
for (var i = 0; i < impeller.MSections.Count; i++)
{
double L = (i == 0 ? impeller.MSections[0].Position
: impeller.MSections[i].Position - impeller.MSections[i - 1].Position);
//L_EJ = L / EJ
double L_EJ = L / (impeller.E * impeller.MSections[i].InertiaMoment);
double m = impeller.MSections[i].Mass;
//freq2xm = freq2
double freq2xm = freq2 * m;
sectionTransferMatrix[3, 0] = freq2xm;
sectionTransferMatrix[0, 1] = L;
sectionTransferMatrix[3, 1] = freq2xm * L;
sectionTransferMatrix[0, 2] = L * L_EJ / 2;
sectionTransferMatrix[1, 2] = L_EJ;
sectionTransferMatrix[3, 2] = freq2xm * L * L_EJ / 2;
sectionTransferMatrix[0, 3] = L * L * L_EJ / 6;
sectionTransferMatrix[1, 3] = L * L_EJ / 2;
sectionTransferMatrix[2, 3] = L;
sectionTransferMatrix[3, 3] = 1 + freq2xm * L * L * L_EJ / 6;
transferMatrix = (i == 0 ? sectionTransferMatrix.Clone()
: sectionTransferMatrix.Multiply(transferMatrix));
}
state.TransferMatrix = transferMatrix;
state.StateVector = transferMatrix.Multiply(rootStateVector[j]);
for (var i = 0; i < state.EndStateVector.RowCount; i++)
{
if (state.EndStateVector[i, 0] == 0 )
{
if (residualMatrix[0, j] == 0)
{
residualMatrix[0, j] = state.StateVector[i, 0];
continue;
}
residualMatrix[1, j] = state.StateVector[i, 0];
break;
}
}
}
#if TRACER
long step2 = watch.ElapsedTicks;
watch.Reset();
System.Windows.MessageBox.Show(
"Run time" +
"\nstep1: " + step1 +
"\nstep2: " + (step2 - step1)
);
#endif
state.residualMoment = residualMatrix.Determinant();
}
