public void SetPreprocessingModel(MultivariatePreprocessingModel val) { _preprocessingData = val; }
/// <summary> /// Exports a table to a PLS2CalibrationSet /// </summary> /// <param name="table">The table where the calibration model is stored.</param> /// <param name="calibrationSet"></param> public static void Export( DataTable table, out PLS1CalibrationModel calibrationSet) { int numberOfX = GetNumberOfX(table); int numberOfY = GetNumberOfY(table); int numberOfFactors = GetNumberOfFactors(table); calibrationSet = new PLS1CalibrationModel(); calibrationSet.NumberOfX = numberOfX; calibrationSet.NumberOfY = numberOfY; calibrationSet.NumberOfFactors = numberOfFactors; MultivariatePreprocessingModel preprocessSet = new MultivariatePreprocessingModel(); MultivariateContentMemento plsMemo = table.GetTableProperty("Content") as MultivariateContentMemento; if (plsMemo != null) { preprocessSet.PreprocessOptions = plsMemo.SpectralPreprocessing; } calibrationSet.SetPreprocessingModel(preprocessSet); Altaxo.Collections.AscendingIntegerCollection sel = new Altaxo.Collections.AscendingIntegerCollection(); Altaxo.Data.DataColumn col; col = table[GetXOfX_ColumnName()]; if (col == null || !(col is INumericColumn)) { NotFound(GetXOfX_ColumnName()); } preprocessSet.XOfX = Altaxo.Calc.LinearAlgebra.DataColumnWrapper.ToROVector((INumericColumn)col, numberOfX); col = table[GetXMean_ColumnName()]; if (col == null) { NotFound(GetXMean_ColumnName()); } preprocessSet.XMean = Altaxo.Calc.LinearAlgebra.DataColumnWrapper.ToROVector(col, numberOfX); col = table[GetXScale_ColumnName()]; if (col == null) { NotFound(GetXScale_ColumnName()); } preprocessSet.XScale = Altaxo.Calc.LinearAlgebra.DataColumnWrapper.ToROVector(col, numberOfX); sel.Clear(); col = table[GetYMean_ColumnName()]; if (col == null) { NotFound(GetYMean_ColumnName()); } sel.Add(table.DataColumns.GetColumnNumber(col)); preprocessSet.YMean = DataColumnWrapper.ToROVector(col, numberOfY); sel.Clear(); col = table[GetYScale_ColumnName()]; if (col == null) { NotFound(GetYScale_ColumnName()); } sel.Add(table.DataColumns.GetColumnNumber(col)); preprocessSet.YScale = DataColumnWrapper.ToROVector(col, numberOfY); for (int yn = 0; yn < numberOfY; yn++) { sel.Clear(); for (int i = 0; i < numberOfFactors; i++) { string colname = GetXWeight_ColumnName(yn, i); col = table[colname]; if (col == null) { NotFound(colname); } sel.Add(table.DataColumns.GetColumnNumber(col)); } calibrationSet.XWeights[yn] = DataTableWrapper.ToRORowMatrix(table.DataColumns, sel, numberOfX); sel.Clear(); for (int i = 0; i < numberOfFactors; i++) { string colname = GetXLoad_ColumnName(yn, i); col = table[colname]; if (col == null) { NotFound(colname); } sel.Add(table.DataColumns.GetColumnNumber(col)); } calibrationSet.XLoads[yn] = DataTableWrapper.ToRORowMatrix(table.DataColumns, sel, numberOfX); sel.Clear(); for (int i = 0; i < numberOfFactors; i++) { string colname = GetYLoad_ColumnName(yn, i); col = table[colname]; if (col == null) { NotFound(colname); } sel.Add(table.DataColumns.GetColumnNumber(col)); } calibrationSet.YLoads[yn] = DataTableWrapper.ToRORowMatrix(table.DataColumns, sel, numberOfY); sel.Clear(); col = table[GetCrossProduct_ColumnName(yn)]; if (col == null) { NotFound(GetCrossProduct_ColumnName()); } sel.Add(table.DataColumns.GetColumnNumber(col)); calibrationSet.CrossProduct[yn] = DataTableWrapper.ToRORowMatrix(table.DataColumns, sel, numberOfFactors); } }
/// <summary> /// Exports a table to a PLS2CalibrationSet /// </summary> /// <param name="table">The table where the calibration model is stored.</param> /// <param name="calibrationSet"></param> public static void Export( DataTable table, out PCRCalibrationModel calibrationSet) { int numberOfX = GetNumberOfX(table); int numberOfY = GetNumberOfY(table); int numberOfFactors = GetNumberOfFactors(table); int numberOfMeasurements = GetNumberOfMeasurements(table); calibrationSet = new PCRCalibrationModel(); calibrationSet.NumberOfX = numberOfX; calibrationSet.NumberOfY = numberOfY; calibrationSet.NumberOfFactors = numberOfFactors; MultivariatePreprocessingModel preprocessSet = new MultivariatePreprocessingModel(); MultivariateContentMemento plsMemo = table.GetTableProperty("Content") as MultivariateContentMemento; if (plsMemo != null) preprocessSet.PreprocessOptions = plsMemo.SpectralPreprocessing; calibrationSet.SetPreprocessingModel(preprocessSet); Altaxo.Collections.AscendingIntegerCollection sel = new Altaxo.Collections.AscendingIntegerCollection(); Altaxo.Data.DataColumn col; col = table.DataColumns.TryGetColumn(GetXOfX_ColumnName()); if (col == null || !(col is INumericColumn)) NotFound(GetXOfX_ColumnName()); preprocessSet.XOfX = Altaxo.Calc.LinearAlgebra.DataColumnWrapper.ToROVector((INumericColumn)col, numberOfX); col = table.DataColumns.TryGetColumn(GetXMean_ColumnName()); if (col == null) NotFound(GetXMean_ColumnName()); preprocessSet.XMean = Altaxo.Calc.LinearAlgebra.DataColumnWrapper.ToROVector(col, numberOfX); col = table.DataColumns.TryGetColumn(GetXScale_ColumnName()); if (col == null) NotFound(GetXScale_ColumnName()); preprocessSet.XScale = Altaxo.Calc.LinearAlgebra.DataColumnWrapper.ToROVector(col, numberOfX); sel.Clear(); col = table.DataColumns.TryGetColumn(GetYMean_ColumnName()); if (col == null) NotFound(GetYMean_ColumnName()); sel.Add(table.DataColumns.GetColumnNumber(col)); preprocessSet.YMean = DataColumnWrapper.ToROVector(col, numberOfY); sel.Clear(); col = table.DataColumns.TryGetColumn(GetYScale_ColumnName()); if (col == null) NotFound(GetYScale_ColumnName()); sel.Add(table.DataColumns.GetColumnNumber(col)); preprocessSet.YScale = DataColumnWrapper.ToROVector(col, numberOfY); sel.Clear(); for (int i = 0; i < numberOfFactors; i++) { string colname = GetXScore_ColumnName(i); col = table.DataColumns.TryGetColumn(colname); if (col == null) NotFound(colname); sel.Add(table.DataColumns.GetColumnNumber(col)); } calibrationSet.XScores = DataTableWrapper.ToROColumnMatrix(table.DataColumns, sel, numberOfMeasurements); sel.Clear(); for (int i = 0; i < numberOfFactors; i++) { string colname = GetXLoad_ColumnName(i); col = table.DataColumns.TryGetColumn(colname); if (col == null) NotFound(colname); sel.Add(table.DataColumns.GetColumnNumber(col)); } calibrationSet.XLoads = DataTableWrapper.ToRORowMatrix(table.DataColumns, sel, numberOfX); sel.Clear(); for (int i = 0; i < numberOfY; i++) { string colname = GetYLoad_ColumnName(i); col = table.DataColumns.TryGetColumn(colname); if (col == null) NotFound(colname); sel.Add(table.DataColumns.GetColumnNumber(col)); } calibrationSet.YLoads = DataTableWrapper.ToROColumnMatrix(table.DataColumns, sel, numberOfMeasurements); sel.Clear(); col = table.DataColumns.TryGetColumn(GetCrossProduct_ColumnName()); if (col == null) NotFound(GetCrossProduct_ColumnName()); calibrationSet.CrossProduct = Altaxo.Calc.LinearAlgebra.DataColumnWrapper.ToROVector(col, numberOfFactors); }
/// <summary> /// Preprocesses the x and y matrices before usage in multivariate calibrations. /// </summary> /// <param name="preprocessOptions">Information how to preprocess the data.</param> /// <param name="spectralRegions">Array of ascending indices representing the starting indices of spectral regions.</param> /// <param name="matrixX">Matrix of spectra.</param> /// <param name="matrixY">Matrix of concentrations.</param> /// <returns>The collected data about proprocessing.</returns> public static MultivariatePreprocessingModel PreprocessForAnalysis( SpectralPreprocessingOptions preprocessOptions, int[] spectralRegions, IMatrix matrixX, IMatrix matrixY) { MultivariatePreprocessingModel data = new MultivariatePreprocessingModel(); data.PreprocessOptions = (SpectralPreprocessingOptions)preprocessOptions.Clone(); data.SpectralRegions = spectralRegions; IVector meanX, scaleX; PreprocessSpectraForAnalysis(preprocessOptions,spectralRegions,matrixX,out meanX, out scaleX); data.XMean = meanX; data.XScale = scaleX; IVector meanY, scaleY; PreprocessYForAnalysis(matrixY,out meanY, out scaleY); data.YMean = meanY; data.YScale = scaleY; return data; }
public void SetPreprocessingModel(MultivariatePreprocessingModel val) { _preprocessingData = val; }