public static double Kurtosis(this double[] data)
{
var d = new DenseVector(data);
var num = new DenseVector(d.Count);
var denom = new DenseVector(d.Count);
d.CopyTo(num);
d.CopyTo(denom);
for (int i = 0; i < num.Count; i++)
{
num[i] = Math.Pow(d[i] - d.Mean(), 4);
denom[i] = Math.Pow(d[i] - d.Mean(), 2);
}
return (num.Sum()*num.Count)/(Math.Pow(denom.Sum(), 2));
}
public static DenseVector Normalize0to1(this DenseVector data)
{
var d = new DenseVector(data);
var result = new DenseVector(d.Count);
d.CopyTo(result);
return (DenseVector) (result - d.Min())/(d.Max() - d.Min());
}
public static double[] NormalizeZScore(this double[] data)
{
var d = new DenseVector(data);
var result = new DenseVector(d.Count);
d.CopyTo(result);
result = (DenseVector) ((result - d.Mean())/(d.StandardDeviation()));
return result.ToArray();
}
public static double[] NormalizeNeg1to1(this double[] data)
{
var d = new DenseVector(data);
var result = new DenseVector(d.Count);
d.CopyTo(result);
result = (DenseVector) (result - ((d.Max() + d.Min())/2))/((d.Max() - d.Min())/2);
return result.ToArray();
}
public static double[] Normalize0to1(this double[] data)
{
var returnData = new double[data.Length];
var d = new DenseVector(data);
var result = new DenseVector(d.Count);
d.CopyTo(result);
result = (DenseVector) (result - d.Min())/(d.Max() - d.Min());
return result.ToArray();
}
/// <summary>
/// Run example
/// </summary>
public void Run()
{
// Format vector output to console
var formatProvider = (CultureInfo)CultureInfo.InvariantCulture.Clone();
formatProvider.TextInfo.ListSeparator = " ";
// Create new empty vector
var vectorA = new DenseVector(10);
Console.WriteLine(@"Empty vector A");
Console.WriteLine(vectorA.ToString("#0.00\t", formatProvider));
Console.WriteLine();
// 1. Fill vector by data using indexer []
for (var i = 0; i < vectorA.Count; i++)
{
vectorA[i] = i;
}
Console.WriteLine(@"1. Fill vector by data using indexer []");
Console.WriteLine(vectorA.ToString("#0.00\t", formatProvider));
Console.WriteLine();
// 2. Fill vector by data using SetValues method
vectorA.SetValues(new[] { 9.0, 8.0, 7.0, 6.0, 5.0, 4.0, 3.0, 2.0, 1.0, 0.0 });
Console.WriteLine(@"2. Fill vector by data using SetValues method");
Console.WriteLine(vectorA.ToString("#0.00\t", formatProvider));
Console.WriteLine();
// 3. Convert Vector to double[]
var data = vectorA.ToArray();
Console.WriteLine(@"3. Convert vector to double array");
for (var i = 0; i < data.Length; i++)
{
Console.Write(data[i].ToString("#0.00\t", formatProvider) + @" ");
}
Console.WriteLine();
Console.WriteLine();
// 4. Convert Vector to column matrix. A matrix based on this vector in column form (one single column)
var columnMatrix = vectorA.ToColumnMatrix();
Console.WriteLine(@"4. Convert vector to column matrix");
Console.WriteLine(columnMatrix.ToString("#0.00\t", formatProvider));
Console.WriteLine();
// 5. Convert Vector to row matrix. A matrix based on this vector in row form (one single row)
var rowMatrix = vectorA.ToRowMatrix();
Console.WriteLine(@"5. Convert vector to row matrix");
Console.WriteLine(rowMatrix.ToString("#0.00\t", formatProvider));
Console.WriteLine();
// 6. Clone vector
var cloneA = vectorA.Clone();
Console.WriteLine(@"6. Clone vector");
Console.WriteLine(cloneA.ToString("#0.00\t", formatProvider));
Console.WriteLine();
// 7. Clear vector
cloneA.Clear();
Console.WriteLine(@"7. Clear vector");
Console.WriteLine(cloneA.ToString("#0.00\t", formatProvider));
Console.WriteLine();
// 8. Copy part of vector into another vector. If you need to copy all data then use CopoTy(vector) method.
vectorA.CopyTo(cloneA, 3, 3, 4);
Console.WriteLine(@"8. Copy part of vector into another vector");
Console.WriteLine(cloneA.ToString("#0.00\t", formatProvider));
Console.WriteLine();
// 9. Get part of vector as another vector
var subvector = vectorA.SubVector(0, 5);
Console.WriteLine(@"9. Get subvector");
Console.WriteLine(subvector.ToString("#0.00\t", formatProvider));
Console.WriteLine();
// 10. Enumerator usage
Console.WriteLine(@"10. Enumerator usage");
foreach (var value in vectorA)
{
Console.Write(value.ToString("#0.00\t", formatProvider) + @" ");
}
Console.WriteLine();
Console.WriteLine();
// 11. Indexed enumerator usage
Console.WriteLine(@"11. Enumerator usage");
foreach (var value in vectorA.GetIndexedEnumerator())
{
Console.WriteLine(@"Index = {0}; Value = {1}", value.Item1, value.Item2.ToString("#0.00\t", formatProvider));
}
Console.WriteLine();
}
public override void Init()
{
//ParametersVector = new DenseVector(24);
//for(int i = 0; i < 12; ++i)
//{
// ParametersVector.At(i, CameraLeft.At(i / 4, i & 3));
// ParametersVector.At(i + 12, CameraRight.At(i / 4, i & 3));
//}
// Parameters:
// Full: [fx, fy, s, px, py, eaX, eaY, eaZ, Cx, Cy, Cz]
// Center fixed: [fx, fy, s, eaX, eaY, eaZ, Cx, Cy, Cz]
ParametersVector = new DenseVector(_cameraParamsCount * 2);
if(_fxIdx >= 0) ParametersVector.At(_fxIdx, CalibrationData.Data.CalibrationLeft.At(0, 0));
if(_fyIdx >= 0) ParametersVector.At(_fyIdx, CalibrationData.Data.CalibrationLeft.At(1, 1));
if(_skIdx >= 0) ParametersVector.At(_skIdx, CalibrationData.Data.CalibrationLeft.At(0, 1));
if(_pxIdx >= 0) ParametersVector.At(_pxIdx, CalibrationData.Data.CalibrationLeft.At(0, 2));
if(_pyIdx >= 0) ParametersVector.At(_pyIdx, CalibrationData.Data.CalibrationLeft.At(1, 2));
Vector<double> euler = new DenseVector(3);
RotationConverter.MatrixToEuler(euler, CalibrationData.Data.RotationLeft);
if(_euXIdx >= 0) ParametersVector.At(_euXIdx, euler.At(0));
if(_euYIdx >= 0) ParametersVector.At(_euYIdx, euler.At(1));
if(_euZIdx >= 0) ParametersVector.At(_euZIdx, euler.At(2));
if(_cXIdx >= 0) ParametersVector.At(_cXIdx, CalibrationData.Data.TranslationLeft.At(0));
if(_cYIdx >= 0) ParametersVector.At(_cYIdx, CalibrationData.Data.TranslationLeft.At(1));
if(_cZIdx >= 0) ParametersVector.At(_cZIdx, CalibrationData.Data.TranslationLeft.At(2));
int n0 = _cameraParamsCount;
if(_fxIdx >= 0) ParametersVector.At(_fxIdx + n0, CalibrationData.Data.CalibrationRight.At(0, 0));
if(_fyIdx >= 0) ParametersVector.At(_fyIdx + n0, CalibrationData.Data.CalibrationRight.At(1, 1));
if(_skIdx >= 0) ParametersVector.At(_skIdx + n0, CalibrationData.Data.CalibrationRight.At(0, 1));
if(_pxIdx >= 0) ParametersVector.At(_pxIdx + n0, CalibrationData.Data.CalibrationRight.At(0, 2));
if(_pyIdx >= 0) ParametersVector.At(_pyIdx + n0, CalibrationData.Data.CalibrationRight.At(1, 2));
RotationConverter.MatrixToEuler(euler, CalibrationData.Data.RotationRight);
if(_euXIdx >= 0) ParametersVector.At(_euXIdx + n0, euler.At(0));
if(_euYIdx >= 0) ParametersVector.At(_euYIdx + n0, euler.At(1));
if(_euZIdx >= 0) ParametersVector.At(_euZIdx + n0, euler.At(2));
if(_cXIdx >= 0) ParametersVector.At(_cXIdx + n0, CalibrationData.Data.TranslationRight.At(0));
if(_cYIdx >= 0) ParametersVector.At(_cYIdx + n0, CalibrationData.Data.TranslationRight.At(1));
if(_cZIdx >= 0) ParametersVector.At(_cZIdx + n0, CalibrationData.Data.TranslationRight.At(2));
//_imgCenterLeft = new Vector2(CalibrationData.Data.CalibrationLeft.At(0, 2),
// CalibrationData.Data.CalibrationLeft.At(1, 2));
//_imgCenterRight = new Vector2(CalibrationData.Data.CalibrationRight.At(0, 2),
// CalibrationData.Data.CalibrationRight.At(1, 2));
ResultsVector = new DenseVector(ParametersVector.Count + CalibGrids.Count * 12);
BestResultVector = new DenseVector(ResultsVector.Count);
ParametersVector.CopySubVectorTo(ResultsVector, 0, 0, ParametersVector.Count);
_grids = new RealGridData[CalibGrids.Count];
int N = ParametersVector.Count;
for(int i = 0; i < CalibGrids.Count; ++i)
{
ResultsVector.At(N + i * 12, CalibGrids[i].TopLeft.X);
ResultsVector.At(N + i * 12 + 1, CalibGrids[i].TopLeft.Y);
ResultsVector.At(N + i * 12 + 2, CalibGrids[i].TopLeft.Z);
ResultsVector.At(N + i * 12 + 3, CalibGrids[i].TopRight.X);
ResultsVector.At(N + i * 12 + 4, CalibGrids[i].TopRight.Y);
ResultsVector.At(N + i * 12 + 5, CalibGrids[i].TopRight.Z);
ResultsVector.At(N + i * 12 + 6, CalibGrids[i].BotLeft.X);
ResultsVector.At(N + i * 12 + 7, CalibGrids[i].BotLeft.Y);
ResultsVector.At(N + i * 12 + 8, CalibGrids[i].BotLeft.Z);
ResultsVector.At(N + i * 12 + 9, CalibGrids[i].BotRight.X);
ResultsVector.At(N + i * 12 + 10, CalibGrids[i].BotRight.Y);
ResultsVector.At(N + i * 12 + 11, CalibGrids[i].BotRight.Z);
_grids[i] = new RealGridData();
_grids[i].Columns = CalibGrids[i].Columns;
_grids[i].Rows = CalibGrids[i].Rows;
}
ResultsVector.CopyTo(BestResultVector);
_coeffMatch = MatchedPointsLeft.Count > 0 ? Math.Sqrt(MatchErrorCoeff * 0.5 / (double)MatchedPointsLeft.Count) : 0;
_coeffImages = Math.Sqrt(ImagesErrorCoeff * 0.5 / (double)(CalibPointsLeft.Count + CalibPointsRight.Count));
_coeffGrids = Math.Sqrt(GridsErrorCoeff * (CalibPointsLeft.Count + CalibPointsRight.Count) / (double)(CalibGrids.Count * 12));
_coeffTriang = Math.Sqrt(TriangulationErrorCoeff * 0.33 / (double)CalibPointsLeft.Count);
_currentErrorVector = new DenseVector(
MatchedPointsLeft.Count * 2 + // Matched
CalibPointsLeft.Count * 3 + // Triangulation
CalibPointsLeft.Count * 2 + CalibPointsRight.Count * 2 + // Image
CalibGrids.Count * 12); // Grids
_J = new DenseMatrix(_currentErrorVector.Count, ResultsVector.Count);
_Jt = new DenseMatrix(ResultsVector.Count, _currentErrorVector.Count);
_JtJ = new DenseMatrix(ResultsVector.Count, ResultsVector.Count);
_Jte = new DenseVector(ResultsVector.Count);
_delta = new DenseVector(ResultsVector.Count);
_reals = new Vector<double>[CalibPointsLeft.Count];
_imgsLeft = new Vector<double>[CalibPointsLeft.Count];
_imgsRight = new Vector<double>[CalibPointsRight.Count];
_triangulation.UseLinearEstimationOnly = true;
_triangulation.PointsLeft = new List<Vector<double>>(CalibPointsLeft.Count);
_triangulation.PointsRight = new List<Vector<double>>(CalibPointsLeft.Count);
for(int i = 0; i < CalibPointsLeft.Count; ++i)
{
_triangulation.PointsLeft.Add(CalibPointsLeft[i].Img.ToMathNetVector3());
_triangulation.PointsRight.Add(CalibPointsRight[i].Img.ToMathNetVector3());
}
UseCovarianceMatrix = false;
DumpingMethodUsed = DumpingMethod.Multiplicative;
UpdateAll();
_lam = 1e-3f;
_lastResidiual = _currentResidiual;
Solver = new SvdSolver();
}
public override void Init()
{
ResultsVector = new DenseVector(ParametersVector.Count + CalibrationGrids.Count * 12);
BestResultVector = new DenseVector(ParametersVector.Count + CalibrationGrids.Count * 12);
ParametersVector.CopySubVectorTo(ResultsVector, 0, 0, 12);
for(int i = 0; i < CalibrationGrids.Count; ++i)
{
ResultsVector.At(12 + i * 12, CalibrationGrids[i].TopLeft.X);
ResultsVector.At(12 + i * 12 + 1, CalibrationGrids[i].TopLeft.Y);
ResultsVector.At(12 + i * 12 + 2, CalibrationGrids[i].TopLeft.Z);
ResultsVector.At(12 + i * 12 + 3, CalibrationGrids[i].TopRight.X);
ResultsVector.At(12 + i * 12 + 4, CalibrationGrids[i].TopRight.Y);
ResultsVector.At(12 + i * 12 + 5, CalibrationGrids[i].TopRight.Z);
ResultsVector.At(12 + i * 12 + 6, CalibrationGrids[i].BotLeft.X);
ResultsVector.At(12 + i * 12 + 7, CalibrationGrids[i].BotLeft.Y);
ResultsVector.At(12 + i * 12 + 8, CalibrationGrids[i].BotLeft.Z);
ResultsVector.At(12 + i * 12 + 9, CalibrationGrids[i].BotRight.X);
ResultsVector.At(12 + i * 12 + 10, CalibrationGrids[i].BotRight.Y);
ResultsVector.At(12 + i * 12 + 11, CalibrationGrids[i].BotRight.Z);
}
ResultsVector.CopyTo(BestResultVector);
_grids = new List<RealGridData>(CalibrationGrids);
_gridErrorCoef = Math.Sqrt((double)CalibrationPoints.Count / (double)(CalibrationGrids.Count * 12.0));
_currentErrorVector = new DenseVector(CalibrationGrids.Count * 12 + CalibrationPoints.Count * 2);
_J = new DenseMatrix(_currentErrorVector.Count, ResultsVector.Count);
_Jt = new DenseMatrix(ResultsVector.Count, _currentErrorVector.Count);
_JtJ = new DenseMatrix(ResultsVector.Count, ResultsVector.Count);
_Jte = new DenseVector(ResultsVector.Count);
_delta = new DenseVector(ResultsVector.Count);
_Lx = new DenseVector(CalibrationPoints.Count);
_Ly = new DenseVector(CalibrationPoints.Count);
_M = new DenseVector(CalibrationPoints.Count);
_reals = new Vector3[CalibrationPoints.Count];
UpdateAll();
//if(DumpingMethodUsed == DumpingMethod.Additive)
//{
// // Compute initial lambda lam = 10^-3*diag(J'J)/size(J'J)
// ComputeJacobian(_J);
// _J.TransposeToOther(_Jt);
// _Jt.MultiplyToOther(_J, _JtJ);
// _lam = 1e-3f * _JtJ.Trace() / (double)_JtJ.ColumnCount;
//}
//else
if(DumpingMethodUsed == DumpingMethod.Multiplicative)
{
_lam = 1e-3f;
}
else
_lam = 0.0;
_lastResidiual = _currentResidiual;
Solver = new SvdSolver();
}