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(); }