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;
}
