void Initialize(bool docAlso)
{
if (_view != null)
{
_view.IndependentColor = _doc.IndependentColor;
_view.StrokePen = _doc.Pen;
_view.IndependentSize = _doc.IndependentSymbolSize;
_view.LineSymbolGap = _doc.SymbolGap;
_view.ShowEndBars = _doc.ShowEndBars;
_view.DoNotShiftIndependentVariable = _doc.DoNotShiftIndependentVariable;
_view.IsHorizontalStyle = _doc.IsHorizontalStyle;
_tempSymbolSize = _doc.SymbolSize;
_view.InitializeSymbolSizeList(new string[] { Serialization.GUIConversion.ToString(_tempSymbolSize) }, 0);
_tempSkipFreq = _doc.SkipFrequency;
_view.SkipFrequency = Serialization.GUIConversion.ToString(_tempSkipFreq);
// Errors
_tempPosErrorColumn = _doc.PositiveErrorColumn;
_tempNegErrorColumn = _doc.NegativeErrorColumn;
string posError = null == _tempPosErrorColumn ? string.Empty : _tempPosErrorColumn.FullName;
string negError = null == _tempNegErrorColumn ? string.Empty : _tempNegErrorColumn.FullName;
_view.IndependentNegativeError = !object.ReferenceEquals(_tempPosErrorColumn, _tempNegErrorColumn);
_view.PositiveError = posError;
_view.NegativeError = negError;
}
}
/// <summary>
/// Creates and fills the column header vector.
/// </summary>
private void GetColumnHeaderVector()
{
// find out if there is a y property column or not
_columnHeaderColumn = null;
if (null != _selectedPropertyColumns && _selectedPropertyColumns.Count > 0)
{
// then use the first numeric column as y column that you find
for (int i = 0; i < _selectedPropertyColumns.Count; i++)
{
if (_sourceTable.PropCols[_selectedPropertyColumns[i]] is INumericColumn)
{
_columnHeaderColumn = (INumericColumn)_sourceTable.PropCols[_selectedPropertyColumns[i]];
break;
}
}
}
if (null != _columnHeaderColumn)
{
double[] arr = new double[_participatingDataColumns.Count];
for (int i = 0; i < _participatingDataColumns.Count; ++i)
{
arr[i] = _columnHeaderColumn[_participatingDataColumns[i]];
}
_columnHeaderVector = VectorMath.ToVector(arr);
}
}
/// <summary>
/// Creates an <see cref="INumericColumnProxy"/> from a given column.
/// </summary>
/// <param name="column">The column.</param>
/// <returns>An instance of <see cref="INumericColumnProxy"/>. The type of instance returned depends on the type of the provided column (e.g. whether the column is part of the document or not).</returns>
public static INumericColumnProxy FromColumn(INumericColumn column)
{
if (column is IDocumentLeafNode)
return NumericColumnProxy.FromColumn(column);
else
return NumericColumnProxyForStandaloneColumns.FromColumn(column);
}
public void Dispose()
{
_col = null;
_srctable = null;
_selectedColumns = null;
_selectedRows = null;
}
public static NumericColumnProxyForStandaloneColumns FromColumn(INumericColumn column)
{
var colAsDocumentNode = column as IDocumentLeafNode;
if (null != colAsDocumentNode)
throw new ArgumentException(string.Format("column does implement {0}. The actual type of column is {1}", typeof(IDocumentLeafNode), column.GetType()));
return new NumericColumnProxyForStandaloneColumns(column); ;
}
/// <summary>
/// Creates an <see cref="INumericColumnProxy"/> from a given column.
/// </summary>
/// <param name="column">The column.</param>
/// <returns>An instance of <see cref="INumericColumnProxy"/>. The type of instance returned depends on the type of the provided column (e.g. whether the column is part of the document or not).</returns>
public static INumericColumnProxy FromColumn(INumericColumn column)
{
if (column is IDocumentLeafNode)
{
return(NumericColumnProxy.FromColumn(column));
}
else
{
return(NumericColumnProxyForStandaloneColumns.FromColumn(column));
}
}
public FitElement(INumericColumn xColumn, INumericColumn yColumn, int start, int count)
{
_independentVariables = new NumericColumnProxy[1];
_independentVariables[0] = new NumericColumnProxy(xColumn);
_dependentVariables = new NumericColumnProxy[1];
_dependentVariables[0] = new NumericColumnProxy(yColumn);
_errorEvaluation = new IVarianceScaling[1];
_errorEvaluation[0] = new ConstantVarianceScaling();
_rangeOfRows = PositiveIntegerRange.NewFromFirstAndCount(start, count);
}
public static NumericColumnProxyForStandaloneColumns FromColumn(INumericColumn column)
{
var colAsDocumentNode = column as IDocumentLeafNode;
if (null != colAsDocumentNode)
{
throw new ArgumentException(string.Format("column does implement {0}. The actual type of column is {1}", typeof(IDocumentLeafNode), column.GetType()));
}
return(new NumericColumnProxyForStandaloneColumns(column));
;
}
public static NumericColumnProxy FromColumn(INumericColumn column)
{
if (null == column)
{
throw new ArgumentNullException("column");
}
var colAsDocumentNode = column as IDocumentLeafNode;
if (null == colAsDocumentNode)
{
throw new ArgumentException(string.Format("column does not implement {0}. The actual type of column is {1}", typeof(IDocumentLeafNode), column.GetType()));
}
return(new NumericColumnProxy(colAsDocumentNode));
}
/// <summary>
/// Sets the ith dependent variable column. The column is hold by a reference aware of disposed events, so that it can be null if retrieved afterwards.
/// </summary>
/// <param name="i">Index.</param>
/// <param name="col">Dependent variable column to set.</param>
public void SetDependentVariable(int i, INumericColumn col)
{
this._dependentVariables[i] = new NumericColumnProxy(col);
if (col != null)
{
if (this._errorEvaluation[i] == null)
{
this._errorEvaluation[i] = new ConstantVarianceScaling();
}
}
else
{
this._errorEvaluation[i] = null;
}
}
/// <summary>
/// This returns a read-only vector of a <see cref="INumericColumn" />, but the data are copyied before. Thus, if you change the data
/// into the numeric column, the data of the returned vector is not influenced.
/// </summary>
/// <param name="col">The column to wrap.</param>
/// <returns>A read-only vector which contains data copied from the numeric column.</returns>
public static IROVector ToROVectorCopy(DataColumn col)
{
if (!(col is INumericColumn))
{
throw new ArgumentException("Argument col can not be wrapped to a vector because it is not a numeric column");
}
INumericColumn ncol = col as INumericColumn;
double[] vec = new double[col.Count];
for (int i = col.Count - 1; i >= 0; i--)
{
vec[i] = ncol[i];
}
return(VectorMath.ToROVector(vec));
}
void EhView_ChooseNegativeError(object sender, EventArgs e)
{
SingleColumnChoice choice = new SingleColumnChoice();
choice.SelectedColumn = _tempNegErrorColumn != null ? _tempNegErrorColumn as DataColumn: _doc.NegativeErrorColumn as DataColumn;
object choiceAsObject = choice;
if (Current.Gui.ShowDialog(ref choiceAsObject, "Select negative error column"))
{
choice = (SingleColumnChoice)choiceAsObject;
if (choice.SelectedColumn is INumericColumn)
{
_tempNegErrorColumn = (INumericColumn)choice.SelectedColumn;
_view.NegativeError = _tempNegErrorColumn.FullName;
}
}
}
/// <summary>
/// Creates and fills the row header vector.
/// </summary>
private void GetRowHeaderVector()
{
// find out if there is a xcolumn or not
int group = _sourceTable.DataColumns.GetColumnGroup(_participatingDataColumns[0]);
DataColumn xcol = _sourceTable.DataColumns.FindXColumnOfGroup(group);
_rowHeaderColumn = xcol as INumericColumn;
if (null != _rowHeaderColumn)
{
double[] arr = new double[_participatingDataRows.Count];
for (int i = 0; i < _participatingDataRows.Count; ++i)
{
arr[i] = _rowHeaderColumn[_participatingDataRows[i]];
}
_rowHeaderVector = VectorMath.ToVector(arr);
}
}
public IAscendingIntegerCollection CalculateValidNumericRows()
{
// also obtain the valid rows both of the independent and of the dependent variables
INumericColumn[] cols = new INumericColumn[_independentVariables.Length + _dependentVariables.Length];
int i;
AscendingIntegerCollection selectedCols = new AscendingIntegerCollection();
// note: for a fitting session all independent variables columns must
// be not null
int maxLength = int.MaxValue;
for (i = 0; i < _independentVariables.Length; i++)
{
cols[i] = _independentVariables[i].Document;
selectedCols.Add(i);
if (cols[i] is IDefinedCount)
{
maxLength = Math.Min(maxLength, ((IDefinedCount)cols[i]).Count);
}
}
// note: for a fitting session some of the dependent variables can be null
for (int j = 0; j < _dependentVariables.Length; ++j, ++i)
{
if (_dependentVariables[j] != null && _dependentVariables[j].Document != null)
{
cols[i] = _dependentVariables[j].Document;
selectedCols.Add(i);
if (cols[i] is IDefinedCount)
{
maxLength = Math.Min(maxLength, ((IDefinedCount)cols[i]).Count);
}
}
}
if (maxLength == int.MaxValue)
{
maxLength = 0;
}
maxLength = Math.Min(maxLength, this._rangeOfRows.End);
bool[] arr = Altaxo.Calc.LinearAlgebra.DataTableWrapper.GetValidNumericRows(cols, selectedCols, maxLength);
return(Altaxo.Calc.LinearAlgebra.DataTableWrapper.GetCollectionOfValidNumericRows(arr));
}
/// <summary>
/// Determines which of the rows of a set of columns is truly numeric, i.e. all columns in this row contains a value, which is not double.NaN.
/// </summary>
/// <param name="table">Array of numeric columns.</param>
/// <param name="selectedCols">The indizes of the columns in question into the collection.</param>
/// <param name="rowCount">The minimum row count of all the selected columns.</param>
/// <returns>A boolean array. If an element of the array is true at a given index, that row contains valid numeric values in all columns.</returns>
public static bool[] GetValidNumericRows(INumericColumn[] table, IAscendingIntegerCollection selectedCols, int rowCount)
{
// determine the number of valid rows
bool[] rowValid = new bool[rowCount];
for (int i = 0; i < rowCount; i++)
{
rowValid[i] = true;
}
for (int i = 0; i < selectedCols.Count; i++)
{
INumericColumn col = (INumericColumn)table[selectedCols[i]];
for (int j = 0; j < rowCount; j++)
{
if (double.IsNaN(col[j]))
{
rowValid[j] = false;
}
}
}
return(rowValid);
}
public bool MoveNext()
{
if (null != _col)
{
if (_nRow < _selectedRows.Count - 1)
{
++_nRow;
return(true);
}
else
{
++_nCol;
if (_nCol < _selectedColumns.Count)
{
_nRow = 0;
_col = (INumericColumn)_srctable.DataColumns[_selectedColumns[_nCol]];
return(true);
}
else
{
_col = null;
return(false);
}
}
}
else // _col is null
{
if (_nCol < 0)
{
_nCol = 0;
_nRow = 0;
_col = (INumericColumn)_srctable.DataColumns[_selectedColumns[_nCol]];
return(true);
}
}
return(false);
}
/// <summary>
/// Sets the ith dependent variable column. The column is hold by a reference aware of disposed events, so that it can be null if retrieved afterwards.
/// </summary>
/// <param name="i">Index.</param>
/// <param name="col">Dependent variable column to set.</param>
public void SetDependentVariable(int i, INumericColumn col)
{
this._dependentVariables[i] = new NumericColumnProxy(col);
if(col!=null)
{
if(this._errorEvaluation[i]==null)
this._errorEvaluation[i] = new ConstantVarianceScaling();
}
else
{
this._errorEvaluation[i] = null;
}
}
/// <summary>
/// Sets the ith independent variable column. The column is hold by a reference aware of disposed events, so that it can be null if retrieved afterwards.
/// </summary>
/// <param name="i">Index.</param>
/// <param name="col">Independent variable column to set.</param>
public void SetIndependentVariable(int i, INumericColumn col)
{
this._independentVariables[i] = new NumericColumnProxy(col);
this.OnChanged();
}
public FitElement(INumericColumn xColumn, INumericColumn yColumn, int start, int count)
{
_independentVariables = new NumericColumnProxy[1];
_independentVariables[0] = new NumericColumnProxy(xColumn);
_dependentVariables = new NumericColumnProxy[1];
_dependentVariables[0] = new NumericColumnProxy(yColumn);
_errorEvaluation = new IVarianceScaling[1];
_errorEvaluation[0] = new ConstantVarianceScaling();
_rangeOfRows = PositiveIntegerRange.NewFromFirstAndCount(start,count);
}
/// <summary>
/// Constructor by giving a numeric column.
/// </summary>
/// <param name="column">The numeric column to hold.</param>
public NumericColumnProxy(INumericColumn column)
: base(column)
{
}
/// <summary>
/// This returns a read-only vector of a <see cref="INumericColumn" />
/// </summary>
/// <param name="col">The column to wrap as a IVector.</param>
/// <param name="nStart">The starting index of the wrapped column.</param>
/// <param name="nRows">The number of rows to use for the vector.</param>
/// <returns>An IVector wrapping the <see cref="INumericColumn" />.</returns>
public static IROVector <double> ToROVector(this INumericColumn col, int nStart, int nRows)
{
return(new NumericColumnToROVectorWrapper(col, nStart, nRows));
}
public static string TestAgainstStandardDistribution(IList <double> sortedListOfData, LinearBinning binning, INumericColumn colBinPosition, INumericColumn colBinCounts)
{
var stb = new StringBuilder();
var stat = new Calc.Regression.QuickStatistics();
foreach (var v in sortedListOfData)
{
stat.Add(v);
}
// Test the probability against the normal distribution
// First make a fit of the normal distribution to get mu and sigma
// guess of mu
double guessedMu = stat.Mean;
double guessedSigma = stat.SampleStandardDeviation;
/*
* Altaxo.Calc.Regression.Nonlinear.SimpleNonlinearFit fit = new Altaxo.Calc.Regression.Nonlinear.SimpleNonlinearFit(
* delegate (double[] indep, double[] p, double[] res)
* {
* // 3 Parameter: mu and sigma
* res[0] = Calc.Probability.NormalDistribution.PDF(indep[0], p[0], p[1]);
* },
* new double[] { guessedMu, guessedSigma },
* colBinPosition,
* colProbabilityDensity,
* 0, // Start (first point)
* binning.Count // point count
* );
*
* fit.Fit();
*
* guessedMu = fit.GetParameter(0);
* guessedSigma = fit.GetParameter(1);
*
*/
// Test hypothesis that we have a normal distribution
double chiSquare = 0;
int degreesOfFreedom = binning.NumberOfBins - 1 - 2; // -2 because we lost two degrees of freedom in the previous fitting
for (int nBinIndex = 0; nBinIndex < binning.NumberOfBins; ++nBinIndex)
{
var bin = binning.Bins[nBinIndex];
double lowerBound = bin.LowerBound;
double upperBound = bin.UpperBound;
var probability = Calc.Probability.NormalDistribution.CDF(upperBound, guessedMu, guessedSigma) - Calc.Probability.NormalDistribution.CDF(lowerBound, guessedMu, guessedSigma);
double n0 = probability * sortedListOfData.Count;
chiSquare += RMath.Pow2(n0 - colBinCounts[nBinIndex]) / n0;
}
double chiSquareThreshold = Calc.Probability.ChiSquareDistribution.Quantile(0.95, degreesOfFreedom);
if (chiSquare <= chiSquareThreshold)
{
stb.AppendFormat("The hypothesis that this is a normal distribution with mu={0} and sigma={1} can not be rejected. ChiSquare ({2}) is less than ChiSquare needed to reject hypothesis ({3})", guessedMu, guessedSigma, chiSquare, chiSquareThreshold);
}
else
{
stb.AppendFormat("The hypothesis that this is a normal distribution with mu={0} and sigma={1} must be rejected with a confidence of {2}%. ChiSquare ({3}) is greater than ChiSquare needed to reject hypothesis ({4})", guessedMu, guessedSigma, 100 * Altaxo.Calc.Probability.ChiSquareDistribution.CDF(chiSquare, degreesOfFreedom), chiSquare, chiSquareThreshold);
}
return(stb.ToString());
}
void Initialize(bool docAlso)
{
if (_view != null)
{
_view.IndependentColor = _doc.IndependentColor;
_view.StrokePen = _doc.Pen;
_view.IndependentSize = _doc.IndependentSymbolSize;
_view.LineSymbolGap = _doc.SymbolGap;
_view.ShowEndBars = _doc.ShowEndBars;
_view.DoNotShiftIndependentVariable = _doc.DoNotShiftIndependentVariable;
_view.IsHorizontalStyle = _doc.IsHorizontalStyle;
_tempSymbolSize = _doc.SymbolSize;
_view.InitializeSymbolSizeList(new string[] { Serialization.GUIConversion.ToString(_tempSymbolSize) }, 0);
_tempSkipFreq = _doc.SkipFrequency;
_view.SkipFrequency = Serialization.GUIConversion.ToString(_tempSkipFreq);
// Errors
_tempPosErrorColumn = _doc.PositiveErrorColumn;
_tempNegErrorColumn = _doc.NegativeErrorColumn;
string posError = null == _tempPosErrorColumn ? string.Empty : _tempPosErrorColumn.FullName;
string negError = null == _tempNegErrorColumn ? string.Empty : _tempNegErrorColumn.FullName;
_view.IndependentNegativeError = !object.ReferenceEquals(_tempPosErrorColumn, _tempNegErrorColumn);
_view.PositiveError = posError;
_view.NegativeError = negError;
}
}
/// <summary>
/// Constructor by giving a numeric column.
/// </summary>
/// <param name="column">The numeric column to hold.</param>
protected NumericColumnProxyForStandaloneColumns(INumericColumn column)
{
_column = column;
}
/// <summary>
/// Creates and fills the column header vector.
/// </summary>
private void GetColumnHeaderVector()
{
// find out if there is a y property column or not
_columnHeaderColumn = null;
if (null != _selectedPropertyColumns && _selectedPropertyColumns.Count > 0)
{
// then use the first numeric column as y column that you find
for (int i = 0; i < _selectedPropertyColumns.Count; i++)
{
if (_sourceTable.PropCols[_selectedPropertyColumns[i]] is INumericColumn)
{
_columnHeaderColumn = (INumericColumn)_sourceTable.PropCols[_selectedPropertyColumns[i]];
break;
}
}
}
if (null != _columnHeaderColumn)
{
double[] arr = new double[_participatingDataColumns.Count];
for (int i = 0; i < _participatingDataColumns.Count; ++i)
arr[i] = _columnHeaderColumn[_participatingDataColumns[i]];
_columnHeaderVector = VectorMath.ToVector(arr);
}
}
protected void PaintXErrorBars(System.Drawing.Graphics g, IPlotArea layer, Altaxo.Graph.Gdi.Plot.Data.Processed2DPlotData pdata)
{
// Plot error bars for the independent variable (x)
PlotRangeList rangeList = pdata.RangeList;
PointF[] ptArray = pdata.PlotPointsInAbsoluteLayerCoordinates;
INumericColumn posErrCol = _positiveErrorColumn.Document;
INumericColumn negErrCol = _negativeErrorColumn.Document;
if (posErrCol == null && negErrCol == null)
{
return; // nothing to do if both error columns are null
}
System.Drawing.Drawing2D.GraphicsPath errorBarPath = new System.Drawing.Drawing2D.GraphicsPath();
Region oldClippingRegion = g.Clip;
Region newClip = (Region)oldClippingRegion.Clone();
foreach (PlotRange r in rangeList)
{
int lower = r.LowerBound;
int upper = r.UpperBound;
int offset = r.OffsetToOriginal;
for (int j = lower; j < upper; j++)
{
AltaxoVariant x = pdata.GetXPhysical(j + offset);
Logical3D lm = layer.GetLogical3D(pdata, j + offset);
lm.RX += _cachedLogicalShiftOfIndependent;
if (lm.IsNaN)
{
continue;
}
Logical3D lh = lm;
Logical3D ll = lm;
bool lhvalid = false;
bool llvalid = false;
if (posErrCol != null)
{
lh.RX = layer.XAxis.PhysicalVariantToNormal(x + Math.Abs(posErrCol[j + offset]));
lhvalid = !lh.IsNaN;
}
if (negErrCol != null)
{
ll.RX = layer.XAxis.PhysicalVariantToNormal(x - Math.Abs(negErrCol[j + offset]));
llvalid = !ll.IsNaN;
}
if (!(lhvalid || llvalid))
{
continue; // nothing to do for this point if both pos and neg logical point are invalid.
}
// now paint the error bar
if (_symbolGap) // if symbol gap, then clip the painting, exclude a rectangle of size symbolSize x symbolSize
{
double xlm, ylm;
layer.CoordinateSystem.LogicalToLayerCoordinates(lm, out xlm, out ylm);
newClip.Union(oldClippingRegion);
newClip.Exclude(new RectangleF((float)(xlm - _symbolSize / 2), (float)(ylm - _symbolSize / 2), _symbolSize, _symbolSize));
g.Clip = newClip;
}
if (lhvalid && llvalid)
{
errorBarPath.Reset();
layer.CoordinateSystem.GetIsoline(errorBarPath, ll, lm);
layer.CoordinateSystem.GetIsoline(errorBarPath, lm, lh);
g.DrawPath(_strokePen, errorBarPath);
}
else if (llvalid)
{
layer.CoordinateSystem.DrawIsoline(g, _strokePen, ll, lm);
}
else if (lhvalid)
{
layer.CoordinateSystem.DrawIsoline(g, _strokePen, lm, lh);
}
// now the end bars
if (_showEndBars)
{
if (lhvalid)
{
PointF outDir;
layer.CoordinateSystem.GetNormalizedDirection(lm, lh, 1, new Logical3D(0, 1), out outDir);
outDir.X *= _symbolSize / 2;
outDir.Y *= _symbolSize / 2;
double xlay, ylay;
layer.CoordinateSystem.LogicalToLayerCoordinates(lh, out xlay, out ylay);
// Draw a line from x,y to
g.DrawLine(_strokePen, (float)(xlay - outDir.X), (float)(ylay - outDir.Y), (float)(xlay + outDir.X), (float)(ylay + outDir.Y));
}
if (llvalid)
{
PointF outDir;
layer.CoordinateSystem.GetNormalizedDirection(lm, ll, 1, new Logical3D(0, 1), out outDir);
outDir.X *= _symbolSize / 2;
outDir.Y *= _symbolSize / 2;
double xlay, ylay;
layer.CoordinateSystem.LogicalToLayerCoordinates(ll, out xlay, out ylay);
// Draw a line from x,y to
g.DrawLine(_strokePen, (float)(xlay - outDir.X), (float)(ylay - outDir.Y), (float)(xlay + outDir.X), (float)(ylay + outDir.Y));
}
}
}
}
g.Clip = oldClippingRegion;
}
void EhView_ClearNegativeError(object sender, EventArgs e)
{
_tempNegErrorColumn = null;
_view.NegativeError = string.Empty;
}
/// <summary>
/// Creates and fills the row header vector.
/// </summary>
private void GetRowHeaderVector()
{
// find out if there is a xcolumn or not
int group = _sourceTable.DataColumns.GetColumnGroup(_participatingDataColumns[0]);
DataColumn xcol = _sourceTable.DataColumns.FindXColumnOfGroup(group);
_rowHeaderColumn = xcol as INumericColumn;
if (null != _rowHeaderColumn)
{
double[] arr = new double[_participatingDataRows.Count];
for (int i = 0; i < _participatingDataRows.Count; ++i)
arr[i] = _rowHeaderColumn[_participatingDataRows[i]];
_rowHeaderVector = VectorMath.ToVector(arr);
}
}
void EhView_ClearPositiveError(object sender, EventArgs e)
{
_tempPosErrorColumn = null;
_view.PositiveError = string.Empty;
}
public IAscendingIntegerCollection CalculateValidNumericRows()
{
// also obtain the valid rows both of the independent and of the dependent variables
INumericColumn[] cols = new INumericColumn[_independentVariables.Length + _dependentVariables.Length];
int i;
AscendingIntegerCollection selectedCols = new AscendingIntegerCollection();
// note: for a fitting session all independent variables columns must
// be not null
int maxLength = int.MaxValue;
for (i = 0; i < _independentVariables.Length; i++)
{
cols[i] = _independentVariables[i].Document;
selectedCols.Add(i);
if (cols[i] is IDefinedCount)
maxLength = Math.Min(maxLength, ((IDefinedCount)cols[i]).Count);
}
// note: for a fitting session some of the dependent variables can be null
for (int j = 0; j < _dependentVariables.Length; ++j, ++i)
{
if (_dependentVariables[j] != null && _dependentVariables[j].Document != null)
{
cols[i] = _dependentVariables[j].Document;
selectedCols.Add(i);
if (cols[i] is IDefinedCount)
maxLength = Math.Min(maxLength, ((IDefinedCount)cols[i]).Count);
}
}
if (maxLength == int.MaxValue)
maxLength = 0;
maxLength = Math.Min(maxLength, this._rangeOfRows.End);
bool[] arr = Altaxo.Calc.LinearAlgebra.DataTableWrapper.GetValidNumericRows(cols, selectedCols, maxLength);
return Altaxo.Calc.LinearAlgebra.DataTableWrapper.GetCollectionOfValidNumericRows(arr);
}
public static NumericColumnProxy FromColumn(INumericColumn column)
{
if (null == column)
throw new ArgumentNullException("column");
var colAsDocumentNode = column as IDocumentLeafNode;
if (null == colAsDocumentNode)
throw new ArgumentException(string.Format("column does not implement {0}. The actual type of column is {1}", typeof(IDocumentLeafNode), column.GetType()));
return new NumericColumnProxy(colAsDocumentNode);
}
/// <summary>
/// Constructor by giving a numeric column.
/// </summary>
/// <param name="column">The numeric column to hold.</param>
public NumericColumnProxy(INumericColumn column)
: base(column)
{
}
/// <summary>
/// This returns a vertical oriented, readonly matrix of a <see cref="DoubleColumn" />
/// </summary>
/// <param name="col">The column to wrap as a IVector.</param>
/// <param name="nRows">The number of rows to use for the vector.</param>
/// <returns>An vertical oriented <see cref="IROMatrix" /> wrapping the <see cref="DoubleColumn" />.</returns>
public static IROMatrix ToVertROMatrix(INumericColumn col, int nRows)
{
return(new NumericColumnToROVertMatrixWrapper((INumericColumn)col, nRows));
}
public void Reset()
{
_col = null;
_nCol = -1;
_nRow = 0;
}
/// <summary>
/// Gets the fractional index for merging of two tables.
/// </summary>
/// <param name="masterColumn">X-column of the master table.</param>
/// <param name="slaveColumn">X-column of the slave table.</param>
/// <returns>Array of fractional indices. Each item points into the slaveTable to the value that should be included in the master column at the item's index.</returns>
public static DoubleColumn GetFractionalIndex(INumericColumn masterColumn, INumericColumn slaveColumn)
{
if (!(masterColumn.Count.HasValue))
throw new ArgumentException("masterColumn has no defined count");
if (!(slaveColumn.Count.HasValue))
throw new ArgumentException("slaveColumn has no defined count");
int masterCount = masterColumn.Count.Value;
int slaveCount = slaveColumn.Count.Value;
var result = new DoubleColumn();
var dict = new SortedDictionary<double, int>();
for (int i = slaveCount - 1; i >= 0; i--)
dict[slaveColumn[i]] = i;
var sortedSlaveValues = dict.Keys.ToArray();
var sortedSlaveIndices = dict.Values.ToArray();
for (int masterIdx = 0; masterIdx < masterCount; masterIdx++)
{
var masterValue = masterColumn[masterIdx];
if (double.IsNaN(masterValue))
{
result[masterIdx] = double.NaN;
continue;
}
int dictIdx = Array.BinarySearch(sortedSlaveValues, masterValue);
if (dictIdx >= 0)
{
result[masterIdx] = sortedSlaveIndices[dictIdx];
continue;
}
// dictIdx was negative, we have to take the complement
dictIdx = ~dictIdx;
if (dictIdx >= sortedSlaveIndices.Length)
{
result[masterIdx] = double.NaN;
continue;
}
else if (dictIdx == 0)
{
result[masterIdx] = double.NaN;
continue;
}
else
{
int firstSlaveIdx = sortedSlaveIndices[dictIdx - 1];
int secondSlaveIdx = sortedSlaveIndices[dictIdx];
double firstSlaveValue = sortedSlaveValues[dictIdx - 1];
double secondSlaveValue = sortedSlaveValues[dictIdx];
double diff = secondSlaveValue - firstSlaveValue;
if (diff == 0)
{
result[masterIdx] = firstSlaveIdx;
continue;
}
else
{
result[masterIdx] = firstSlaveIdx + (secondSlaveIdx - firstSlaveIdx) * (masterValue - firstSlaveValue) / diff;
continue;
}
}
}
return result;
}
/// <summary>
/// This returns a vertical oriented, readonly matrix of a <see cref="DoubleColumn" />
/// </summary>
/// <param name="col">The column to wrap as a IVector.</param>
/// <param name="nRows">The number of rows to use for the vector.</param>
/// <returns>An vertical oriented <see cref="IROMatrix{Double}" /> wrapping the <see cref="DoubleColumn" />.</returns>
public static IROMatrix <double> ToVertROMatrix(this INumericColumn col, int nRows)
{
return(new NumericColumnToROVertMatrixWrapper(col, nRows));
}
protected override void OnPaint(PaintEventArgs e)
{
StringFormat leftJustified = new StringFormat(StringFormat.GenericTypographic);
// stringFormat.Alignment = StringAlignment.Center;
leftJustified.LineAlignment = StringAlignment.Center;
StringFormat rightJustified = new StringFormat(StringFormat.GenericTypographic);
rightJustified.Alignment = StringAlignment.Far;
rightJustified.LineAlignment = StringAlignment.Center;
StringFormat bothCentered = new StringFormat(StringFormat.GenericTypographic);
bothCentered.Alignment = StringAlignment.Center;
bothCentered.LineAlignment = StringAlignment.Center;
_fitBoxLocation = new Point(this.ClientSize.Width / 3, 0);
_fitBoxSize = new Size(this.ClientSize.Width / 3, _totalSlots * _slotHeight);
e.Graphics.DrawRectangle(_pen, _fitBoxLocation.X, _fitBoxLocation.Y, _fitBoxSize.Width, _fitBoxSize.Height - 1);
int currentY = 0;
// Draw the independent variables
for (int i = 0; i < _numberOfX; i++)
{
Point triangleStart = new Point(_fitBoxLocation.X, currentY + (1 * _slotHeight) / 4);
Point triangleMidst = new Point(_fitBoxLocation.X + _slotHeight / 2, currentY + _slotHeight / 2);
Point triangleEnd = new Point(_fitBoxLocation.X, currentY + (3 * _slotHeight) / 4);
e.Graphics.DrawLine(_pen, triangleStart, triangleMidst);
e.Graphics.DrawLine(_pen, triangleMidst, triangleEnd);
if (_fitElement.FitFunction != null)
{
e.Graphics.DrawString(
_fitElement.FitFunction.IndependentVariableName(i),
System.Windows.Forms.SystemInformation.MenuFont,
System.Drawing.Brushes.Black,
new Rectangle(_fitBoxLocation.X + _slotHeight / 2 + 2, currentY, _fitBoxSize.Width - 1 - _slotHeight / 2, _slotHeight),
leftJustified
);
}
currentY += _slotHeight;
}
// now draw the dependent variables
_DependentVariablesY = (_totalSlots - _numberOfY) * _slotHeight;
currentY = _DependentVariablesY;
_errorFunctionWidth = (6 * _slotHeight) / 4;
_errorFunctionX = _fitBoxLocation.X - _errorFunctionWidth / 2;
for (int i = 0; i < _numberOfY; i++)
{
Rectangle errorFuncRect = new Rectangle(
_errorFunctionX,
currentY,
_errorFunctionWidth,
_slotHeight - 1);
e.Graphics.FillRectangle(Brushes.WhiteSmoke, errorFuncRect);
e.Graphics.DrawRectangle(_pen, errorFuncRect);
if (_fitElement.ErrorEvaluation(i) != null)
{
e.Graphics.DrawString(_fitElement.ErrorEvaluation(i).ShortName,
System.Windows.Forms.SystemInformation.MenuFont,
System.Drawing.Brushes.Black,
errorFuncRect,
bothCentered);
}
if (_fitElement.FitFunction != null)
{
e.Graphics.DrawString(
_fitElement.FitFunction.DependentVariableName(i),
System.Windows.Forms.SystemInformation.MenuFont,
System.Drawing.Brushes.Black,
new Rectangle(_errorFunctionX + _errorFunctionWidth + (1 * _slotHeight) / 4, currentY, _fitBoxSize.Width - 1 - _slotHeight / 2, _slotHeight),
leftJustified
);
}
currentY += _slotHeight;
}
// now draw the internal parameters
currentY = 0;
for (int i = 0; i < _numberOfParameter; i++)
{
e.Graphics.DrawEllipse(_pen, _fitBoxLocation.X + _fitBoxSize.Width - _slotHeight / 4, currentY + _slotHeight / 4, _slotHeight / 2, _slotHeight / 2);
if (_fitElement.FitFunction != null)
{
e.Graphics.DrawString(
_fitElement.FitFunction.ParameterName(i),
System.Windows.Forms.SystemInformation.MenuFont,
System.Drawing.Brushes.Black,
new Rectangle(_fitBoxLocation.X, currentY, _fitBoxSize.Width - 1 - _slotHeight / 4, _slotHeight),
rightJustified
);
}
currentY += _slotHeight;
}
// now draw the external parameters
currentY = 0;
_externalParametersX = _fitBoxLocation.X + _fitBoxSize.Width + _slotHeight / 2;
_externalParametersWidth = this.ClientSize.Width - _externalParametersX;
for (int i = 0; i < _numberOfParameter; i++)
{
Rectangle rect = new Rectangle(_externalParametersX, currentY, _externalParametersWidth, _slotHeight);
System.Windows.Forms.ControlPaint.DrawBorder3D(e.Graphics,
rect.X - 2, rect.Y, rect.Width + 2, rect.Height,
System.Windows.Forms.Border3DStyle.Etched,
System.Windows.Forms.Border3DSide.All);
e.Graphics.DrawString(
_fitElement.ParameterName(i),
System.Windows.Forms.SystemInformation.MenuFont,
System.Drawing.Brushes.Black,
new Rectangle(_externalParametersX, currentY, _externalParametersWidth, _slotHeight),
leftJustified
);
currentY += _slotHeight;
}
// Draw the names of the independent columns
currentY = 0;
_VariablesX = 0;
_IndependentVariablesWidth = _fitBoxLocation.X - _slotHeight / 4;
for (int i = 0; i < _numberOfX; i++)
{
Rectangle rect = new Rectangle(0, currentY, _IndependentVariablesWidth, _slotHeight);
System.Windows.Forms.ControlPaint.DrawBorder3D(e.Graphics,
rect.X, rect.Y, rect.Width + 2, rect.Height,
System.Windows.Forms.Border3DStyle.Etched,
System.Windows.Forms.Border3DSide.All);
INumericColumn col = _fitElement.IndependentVariables(i);
if (col != null)
{
string name = col.FullName;
e.Graphics.DrawString(
name,
System.Windows.Forms.SystemInformation.MenuFont,
System.Drawing.Brushes.Black,
rect,
rightJustified
);
}
currentY += _slotHeight;
}
{
// draw the plot range
var plotRange = _fitElement.GetRowRange();
string rangestring = "Range: " + plotRange.Start.ToString() + " to " + (plotRange.IsInfinite ? "infinity" : plotRange.Last.ToString());
Rectangle rect = new Rectangle(0, currentY, _IndependentVariablesWidth, _slotHeight);
System.Windows.Forms.ControlPaint.DrawBorder3D(e.Graphics,
rect.X, rect.Y, rect.Width + 2, rect.Height,
System.Windows.Forms.Border3DStyle.Etched,
System.Windows.Forms.Border3DSide.All);
e.Graphics.DrawString(
rangestring,
System.Windows.Forms.SystemInformation.MenuFont,
System.Drawing.Brushes.Black,
rect,
rightJustified
);
}
// Draw the names of the dependent columns
currentY = _DependentVariablesY;
_DependentVariablesWidth = _errorFunctionX - (2 * _slotHeight) / 8;
for (int i = 0; i < _numberOfY; i++)
{
Rectangle rect = new Rectangle(0, currentY, _DependentVariablesWidth, _slotHeight);
System.Windows.Forms.ControlPaint.DrawBorder3D(e.Graphics,
rect.X, rect.Y, rect.Width + 2, rect.Height,
System.Windows.Forms.Border3DStyle.Etched,
System.Windows.Forms.Border3DSide.All);
INumericColumn col = _fitElement.DependentVariables(i);
if (col != null)
{
string name = col.FullName;
e.Graphics.DrawString(
name,
System.Windows.Forms.SystemInformation.MenuFont,
System.Drawing.Brushes.Black,
rect,
rightJustified
);
}
currentY += _slotHeight;
}
string fitFuncName = null;
if (_fitElement.FitFunction == null)
{
fitFuncName = "?";
}
else if (_fitElement.FitFunction is Altaxo.Scripting.IFitFunctionScriptText)
{
fitFuncName = (_fitElement.FitFunction as Altaxo.Scripting.IFitFunctionScriptText).FitFunctionName;
}
else
{
fitFuncName = _fitElement.FitFunction.ToString();
}
Rectangle fitFuncBox = new Rectangle(
_fitBoxLocation.X + _fitBoxSize.Width / 4,
_fitBoxLocation.Y + _fitBoxSize.Height / 4,
_fitBoxSize.Width / 2,
_fitBoxSize.Height / 2);
e.Graphics.DrawString(fitFuncName,
System.Windows.Forms.SystemInformation.MenuFont,
System.Drawing.Brushes.Black,
fitFuncBox
);
if (this._fitFunctionSelected)
{
e.Graphics.DrawRectangle(Pens.Red, fitFuncBox);
}
base.OnPaint(e);
}
void EhView_ChooseNegativeError(object sender, EventArgs e)
{
SingleColumnChoice choice = new SingleColumnChoice();
choice.SelectedColumn = _tempNegErrorColumn != null ? _tempNegErrorColumn as DataColumn: _doc.NegativeErrorColumn as DataColumn;
object choiceAsObject = choice;
if (Current.Gui.ShowDialog(ref choiceAsObject, "Select negative error column"))
{
choice = (SingleColumnChoice)choiceAsObject;
if (choice.SelectedColumn is INumericColumn)
{
_tempNegErrorColumn = (INumericColumn)choice.SelectedColumn;
_view.NegativeError = _tempNegErrorColumn.FullName;
}
}
}
/// <summary>
/// Sets the ith independent variable column. The column is hold by a reference aware of disposed events, so that it can be null if retrieved afterwards.
/// </summary>
/// <param name="i">Index.</param>
/// <param name="col">Independent variable column to set.</param>
public void SetIndependentVariable(int i, INumericColumn col)
{
this._independentVariables[i] = new NumericColumnProxy(col);
this.OnChanged();
}
/// <summary>
/// Constructor by giving a numeric column.
/// </summary>
/// <param name="column">The numeric column to hold.</param>
protected NumericColumnProxyForStandaloneColumns(INumericColumn column)
{
_column = column;
}
/// <summary>
/// Determines which of the rows of a set of columns is truly numeric, i.e. all columns in this row contains a value, which is not double.NaN.
/// </summary>
/// <param name="table">Array of numeric columns.</param>
/// <param name="selectedCols">The indizes of the columns in question into the collection.</param>
/// <param name="selectedRowIndices">The selected data row indices.</param>
/// <param name="rowCount">The minimum row count of all the selected columns.</param>
/// <returns>A boolean array. If an element of the array is true at a given index, that row contains valid numeric values in all columns.</returns>
public static bool[] GetValidNumericRows(INumericColumn[] table, IAscendingIntegerCollection selectedCols, IEnumerable<int> selectedRowIndices, int rowCount)
{
// determine the number of valid rows
bool[] rowValid = new bool[rowCount];
foreach (int i in selectedRowIndices)
rowValid[i] = true;
for (int i = 0; i < selectedCols.Count; i++)
{
INumericColumn col = (INumericColumn)table[selectedCols[i]];
for (int j = 0; j < rowCount; j++)
{
if (double.IsNaN(col[j]))
rowValid[j] = false;
}
}
return rowValid;
}
void EhView_ClearPositiveError(object sender, EventArgs e)
{
_tempPosErrorColumn = null;
_view.PositiveError = string.Empty;
}
public static string Fit(Altaxo.Graph.GUI.GraphController ctrl)
{
if (ctrl.CurrentPlotNumber < 0)
{
return("No active plot!");
}
IGPlotItem plotItem = ctrl.ActiveLayer.PlotItems.Flattened[ctrl.CurrentPlotNumber];
XYColumnPlotItem xyPlotItem = plotItem as XYColumnPlotItem;
if (xyPlotItem == null)
{
return("Active plot is not a X-Y Plot!");
}
INumericColumn xColumn = xyPlotItem.XYColumnPlotData.XColumn as INumericColumn;
INumericColumn yColumn = xyPlotItem.XYColumnPlotData.YColumn as INumericColumn;
if (xColumn == null)
{
return("The x-column is not numeric");
}
if (yColumn == null)
{
return("The y-column is not numeric");
}
Calc.Regression.Nonlinear.NonlinearFitDocument localdoc = ctrl.Doc.GetGraphProperty(FitDocumentPropertyName) as Calc.Regression.Nonlinear.NonlinearFitDocument;
if (localdoc == null)
{
if (_lastFitDocument == null)
{
localdoc = new Altaxo.Calc.Regression.Nonlinear.NonlinearFitDocument();
}
else
{
localdoc = (Altaxo.Calc.Regression.Nonlinear.NonlinearFitDocument)_lastFitDocument.Clone();
}
}
if (localdoc.FitEnsemble.Count == 0)
{
Calc.Regression.Nonlinear.FitElement fitele = new Altaxo.Calc.Regression.Nonlinear.FitElement(
xColumn,
yColumn,
xyPlotItem.XYColumnPlotData.PlotRangeStart,
xyPlotItem.XYColumnPlotData.PlotRangeLength);
localdoc.FitEnsemble.Add(fitele);
}
else // localdoc.FitEnsemble.Count>0
{
localdoc.FitEnsemble[0].SetIndependentVariable(0, xColumn);
localdoc.FitEnsemble[0].SetDependentVariable(0, yColumn);
localdoc.FitEnsemble[0].SetRowRange(xyPlotItem.XYColumnPlotData.PlotRangeStart, xyPlotItem.XYColumnPlotData.PlotRangeLength);
}
localdoc.FitContext = ctrl;
object fitdocasobject = localdoc;
if (true == Current.Gui.ShowDialog(ref fitdocasobject, "Non-linear fitting"))
{
// store the fit document in the graphs property
ctrl.Doc.SetGraphProperty(FitDocumentPropertyName, localdoc);
_lastFitDocument = (Altaxo.Calc.Regression.Nonlinear.NonlinearFitDocument)localdoc.Clone();
}
return(null);
}
void EhView_ClearNegativeError(object sender, EventArgs e)
{
_tempNegErrorColumn = null;
_view.NegativeError = string.Empty;
}
/// <summary>
/// This returns a read-only vector of a <see cref="INumericColumn" />
/// </summary>
/// <param name="col">The column to wrap as a IVector.</param>
/// <param name="nRows">The number of rows to use for the vector.</param>
/// <returns>An IVector wrapping the <see cref="INumericColumn" />.</returns>
public static IROVector ToROVector(INumericColumn col, int nRows)
{
return(new NumericColumnToROVectorWrapper(col, nRows));
}
/// <summary>
/// Gets the fractional index for merging of two tables.
/// </summary>
/// <param name="masterColumn">X-column of the master table.</param>
/// <param name="slaveColumn">X-column of the slave table.</param>
/// <returns>Array of fractional indices. Each item points into the slaveTable to the value that should be included in the master column at the item's index.</returns>
public static DoubleColumn GetFractionalIndex(INumericColumn masterColumn, INumericColumn slaveColumn)
{
if (!(masterColumn.Count.HasValue))
{
throw new ArgumentException("masterColumn has no defined count");
}
if (!(slaveColumn.Count.HasValue))
{
throw new ArgumentException("slaveColumn has no defined count");
}
int masterCount = masterColumn.Count.Value;
int slaveCount = slaveColumn.Count.Value;
var result = new DoubleColumn();
var dict = new SortedDictionary <double, int>();
for (int i = slaveCount - 1; i >= 0; i--)
{
dict[slaveColumn[i]] = i;
}
var sortedSlaveValues = dict.Keys.ToArray();
var sortedSlaveIndices = dict.Values.ToArray();
for (int masterIdx = 0; masterIdx < masterCount; masterIdx++)
{
var masterValue = masterColumn[masterIdx];
if (double.IsNaN(masterValue))
{
result[masterIdx] = double.NaN;
continue;
}
int dictIdx = Array.BinarySearch(sortedSlaveValues, masterValue);
if (dictIdx >= 0)
{
result[masterIdx] = sortedSlaveIndices[dictIdx];
continue;
}
// dictIdx was negative, we have to take the complement
dictIdx = ~dictIdx;
if (dictIdx >= sortedSlaveIndices.Length)
{
result[masterIdx] = double.NaN;
continue;
}
else if (dictIdx == 0)
{
result[masterIdx] = double.NaN;
continue;
}
else
{
int firstSlaveIdx = sortedSlaveIndices[dictIdx - 1];
int secondSlaveIdx = sortedSlaveIndices[dictIdx];
double firstSlaveValue = sortedSlaveValues[dictIdx - 1];
double secondSlaveValue = sortedSlaveValues[dictIdx];
double diff = secondSlaveValue - firstSlaveValue;
if (diff == 0)
{
result[masterIdx] = firstSlaveIdx;
continue;
}
else
{
result[masterIdx] = firstSlaveIdx + (secondSlaveIdx - firstSlaveIdx) * (masterValue - firstSlaveValue) / diff;
continue;
}
}
}
return(result);
}
/// <summary>
/// This returns a read-only vector of a <see cref="INumericColumn" /> for selected rows.
/// </summary>
/// <param name="col">The column to wrap as a IVector.</param>
/// <param name="selectedRows">The rows of the source column that are part of the vector.</param>
/// <returns>An IROVector wrapping the <see cref="INumericColumn" />.</returns>
public static IROVector ToROVector(INumericColumn col, IAscendingIntegerCollection selectedRows)
{
return(new NumericColumnSelectedRowsToROVectorWrapper(col, (IAscendingIntegerCollection)selectedRows.Clone()));
}
