/// <summary>
/// Copies the current parameters for the fit element with the provided index into the provided array.
/// </summary>
/// <param name="idxFitEle">Index of the fit element.</param>
/// <param name="parameters">Provided array to copy the current parameters to. Must have same size as NumberOfParameters for the given fit element.</param>
public void GetParameters(int idxFitEle, double[] parameters)
{
CachedFitElementInfo info = _cachedFitElementInfo[idxFitEle];
// copy of the parameter to the temporary array
for (int i = 0; i < info.Parameters.Length; i++)
{
int idx = info.ParameterMapping[i];
parameters[i] = idx >= 0 ? _cachedVaryingParameters[idx] : _constantParameters[-1 - idx];
}
}
/// <summary>
/// Calculates the jacobian values, i.e. the derivatives of the fitting values with respect to the parameters.
/// </summary>
/// <param name="parameter">The parameter used to calculate the values.</param>
/// <param name="outputValues">You must provide an array to hold the calculated values. Size of the array must be
/// at least <see cref="NumberOfData" />*<see cref="FitElement.NumberOfParameters" />.</param>
/// <param name="adata">Currently ignored.</param>
/// <remarks>The values of the fit elements are stored in the order from element_0 to element_n*m. If there is more
/// than one used dependent variable per fit element, the output values are stored in interleaved order. The derivatives
/// on one fitting value are stored in successive order.
/// </remarks>
public void EvaluateFitJacobian(double[] parameter, double[] outputValues, object adata)
{
outputValues.Initialize(); // make sure every element contains zero
int outputValuesPointer = 0;
for (int ele = 0; ele < _cachedFitElementInfo.Length; ele++)
{
CachedFitElementInfo info = _cachedFitElementInfo[ele];
FitElement fitEle = _fitEnsemble[ele];
// make sure, that the dimension of the DYs is ok
if (info.DYs == null || info.DYs.Length != fitEle.NumberOfDependentVariables || info.DYs[0].Length != fitEle.NumberOfParameters)
{
info.DYs = LinearAlgebra.JaggedArrayMath.GetMatrixArray(fitEle.NumberOfDependentVariables, fitEle.NumberOfParameters);
}
// copy of the parameter to the temporary array
for (int i = 0; i < info.Parameters.Length; i++)
{
int idx = info.ParameterMapping[i];
info.Parameters[i] = idx >= 0 ? parameter[idx] : _constantParameters[-1 - idx];
}
IAscendingIntegerCollection validRows = info.ValidRows;
int numValidRows = validRows.Count;
// Evaluate the function for all points
for (int i = 0; i < numValidRows; ++i)
{
for (int k = info.Xs.Length - 1; k >= 0; k--)
{
info.Xs[k] = fitEle.IndependentVariables(k)[validRows[i]];
}
((IFitFunctionWithGradient)fitEle.FitFunction).EvaluateGradient(info.Xs, info.Parameters, info.DYs);
// copy the evaluation result to the output array (interleaved)
for (int k = 0; k < info.DependentVariablesInUse.Length; ++k)
{
for (int l = 0; l < info.Parameters.Length; ++l)
{
int idx = info.ParameterMapping[l];
if (idx >= 0)
{
outputValues[outputValuesPointer + idx] += info.DYs[info.DependentVariablesInUse[k]][l];
}
}
outputValuesPointer += parameter.Length; // increase output pointer only by the varying (!) number of parameters
}
}
}
}
/// <summary>
/// Calculates the fitting values.
/// </summary>
/// <param name="parameter">The parameter used to calculate the values.</param>
/// <param name="outputValues">You must provide an array to hold the calculated values. Size of the array must be
/// at least <see cref="NumberOfData" />.</param>
/// <param name="calculateUnusedDependentVariablesAlso">If <c>true</c>, the unused dependent variables are also calculated (and plotted).</param>
/// <remarks>The values of the fit elements are stored in the order from element_0 to element_n. If there is more
/// than one used dependent variable per fit element, the output values are stored in interleaved order.
/// </remarks>
public void EvaluateFitValues(double[] parameter, double[] outputValues, bool calculateUnusedDependentVariablesAlso)
{
int outputValuesPointer = 0;
for (int ele = 0; ele < _cachedFitElementInfo.Length; ele++)
{
CachedFitElementInfo info = _cachedFitElementInfo[ele];
FitElement fitEle = _fitEnsemble[ele];
// copy of the parameter to the temporary array
for (int i = 0; i < info.Parameters.Length; i++)
{
int idx = info.ParameterMapping[i];
info.Parameters[i] = idx >= 0 ? parameter[idx] : _constantParameters[-1 - idx];
}
IAscendingIntegerCollection validRows = info.ValidRows;
int numValidRows = validRows.Count;
// Evaluate the function for all points
for (int i = 0; i < numValidRows; ++i)
{
for (int k = info.Xs.Length - 1; k >= 0; k--)
{
info.Xs[k] = fitEle.IndependentVariables(k)[validRows[i]];
}
fitEle.FitFunction.Evaluate(info.Xs, info.Parameters, info.Ys);
if (calculateUnusedDependentVariablesAlso)
{
// copy the evaluation result to the output array (interleaved)
for (int k = 0; k < fitEle.NumberOfDependentVariables; ++k)
{
outputValues[outputValuesPointer++] = info.Ys[k];
}
}
else
{
// copy the evaluation result to the output array (interleaved)
for (int k = 0; k < info.DependentVariablesInUse.Length; ++k)
{
outputValues[outputValuesPointer++] = info.Ys[info.DependentVariablesInUse[k]];
}
}
}
}
}
/// <summary>
/// Stores the dependent values of all elements in an array. The data
/// are stored from FitElement_0 to FitElement_n. For FitElements with more than one dependent
/// variable in use, the data are stored interleaved.
/// </summary>
/// <param name="values">The array used to store the values.</param>
public void GetDependentValues(double[] values)
{
int outputValuesPointer = 0;
for (int ele = 0; ele < _cachedFitElementInfo.Length; ele++)
{
CachedFitElementInfo info = _cachedFitElementInfo[ele];
FitElement fitEle = _fitEnsemble[ele];
IAscendingIntegerCollection validRows = info.ValidRows;
int numValidRows = validRows.Count;
// Evaluate the function for all points
for (int i = 0; i < numValidRows; ++i)
{
for (int j = 0; j < info.DependentVariablesInUse.Length; ++j)
{
values[outputValuesPointer++] = fitEle.DependentVariables(info.DependentVariablesInUse[j])[validRows[i]];
}
}
}
}
/// <summary>
/// Internal function to set up the cached data for the fitting procedure.
/// </summary>
/// <param name="paraSet">The set of parameters (the information which parameters are fixed is mainly used here).</param>
private void CalculateCachedData(ParameterSet paraSet)
{
// Preparation: Store the parameter names by name and index, and store
// all parameter values in _constantParameters
System.Collections.Hashtable paraNames = new System.Collections.Hashtable();
System.Collections.Hashtable varyingParaNames = new System.Collections.Hashtable();
_constantParameters = new double[paraSet.Count];
int numberOfVaryingParameters = 0;
for (int i = 0; i < paraSet.Count; ++i)
{
paraNames.Add(paraSet[i].Name, i);
_constantParameters[i] = paraSet[i].Parameter;
if (paraSet[i].Vary)
++numberOfVaryingParameters;
}
_cachedVaryingParameters = new double[numberOfVaryingParameters];
for (int i = 0, k = 0; i < paraSet.Count; ++i)
{
if (paraSet[i].Vary)
{
varyingParaNames.Add(paraSet[i].Name, k);
_cachedVaryingParameters[k++] = paraSet[i].Parameter;
}
}
_cachedNumberOfData = 0;
_cachedFitElementInfo = new CachedFitElementInfo[_fitEnsemble.Count];
for (int i = 0; i < _fitEnsemble.Count; i++)
{
CachedFitElementInfo info = new CachedFitElementInfo();
_cachedFitElementInfo[i] = info;
FitElement fitEle = _fitEnsemble[i];
info.ValidRows = fitEle.CalculateValidNumericRows();
info.Xs = new double[fitEle.NumberOfIndependentVariables];
info.Parameters = new double[fitEle.NumberOfParameters];
info.Ys = new double[fitEle.NumberOfDependentVariables];
// Calculate the number of used variables
int numVariablesUsed = 0;
for (int j = 0; j < fitEle.NumberOfDependentVariables; ++j)
{
if (fitEle.DependentVariables(j) != null)
++numVariablesUsed;
}
info.DependentVariablesInUse = new int[numVariablesUsed];
for (int j = 0, used = 0; j < fitEle.NumberOfDependentVariables; ++j)
{
if (fitEle.DependentVariables(j) != null)
info.DependentVariablesInUse[used++] = j;
}
// calculate the total number of data points
_cachedNumberOfData += numVariablesUsed * info.ValidRows.Count;
// now create the parameter mapping
info.ParameterMapping = new int[fitEle.NumberOfParameters];
for (int j = 0; j < info.ParameterMapping.Length; ++j)
{
if (!paraNames.Contains(fitEle.ParameterName(j)))
throw new ArgumentException(string.Format("ParameterSet does not contain parameter {0}, which is used by function[{1}]", fitEle.ParameterName(j), i));
int idx = (int)paraNames[fitEle.ParameterName(j)];
if (paraSet[idx].Vary)
{
info.ParameterMapping[j] = (int)varyingParaNames[fitEle.ParameterName(j)];
}
else
{
info.ParameterMapping[j] = -idx - 1;
}
}
}
_cachedDependentValues = new double[_cachedNumberOfData];
GetDependentValues(_cachedDependentValues);
if (this.HasToUseWeights())
{
_cachedWeights = new double[_cachedNumberOfData];
GetWeights(_cachedWeights);
}
else
_cachedWeights = null;
}
/// <summary>
/// Internal function to set up the cached data for the fitting procedure.
/// </summary>
/// <param name="paraSet">The set of parameters (the information which parameters are fixed is mainly used here).</param>
private void CalculateCachedData(ParameterSet paraSet)
{
// Preparation: Store the parameter names by name and index, and store
// all parameter values in _constantParameters
var paraNames = new System.Collections.Hashtable();
var varyingParaNames = new System.Collections.Hashtable();
_constantParameters = new double[paraSet.Count];
int numberOfVaryingParameters = 0;
for (int i = 0; i < paraSet.Count; ++i)
{
paraNames.Add(paraSet[i].Name, i);
_constantParameters[i] = paraSet[i].Parameter;
if (paraSet[i].Vary)
{
++numberOfVaryingParameters;
}
}
_cachedVaryingParameters = new double[numberOfVaryingParameters];
for (int i = 0, k = 0; i < paraSet.Count; ++i)
{
if (paraSet[i].Vary)
{
varyingParaNames.Add(paraSet[i].Name, k);
_cachedVaryingParameters[k++] = paraSet[i].Parameter;
}
}
_cachedNumberOfData = 0;
_cachedFitElementInfo = new CachedFitElementInfo[_fitEnsemble.Count];
for (int i = 0; i < _fitEnsemble.Count; i++)
{
var info = new CachedFitElementInfo();
_cachedFitElementInfo[i] = info;
FitElement fitEle = _fitEnsemble[i];
info.ValidRows = fitEle.CalculateValidNumericRows();
info.Xs = new double[fitEle.NumberOfIndependentVariables];
info.Parameters = new double[fitEle.NumberOfParameters];
info.Ys = new double[fitEle.NumberOfDependentVariables];
// Calculate the number of used variables
int numVariablesUsed = 0;
for (int j = 0; j < fitEle.NumberOfDependentVariables; ++j)
{
if (fitEle.DependentVariables(j) != null)
{
++numVariablesUsed;
}
}
info.DependentVariablesInUse = new int[numVariablesUsed];
for (int j = 0, used = 0; j < fitEle.NumberOfDependentVariables; ++j)
{
if (fitEle.DependentVariables(j) != null)
{
info.DependentVariablesInUse[used++] = j;
}
}
// calculate the total number of data points
_cachedNumberOfData += numVariablesUsed * info.ValidRows.Count;
// now create the parameter mapping
info.ParameterMapping = new int[fitEle.NumberOfParameters];
for (int j = 0; j < info.ParameterMapping.Length; ++j)
{
if (!paraNames.Contains(fitEle.ParameterName(j)))
{
throw new ArgumentException(string.Format("ParameterSet does not contain parameter {0}, which is used by function[{1}]", fitEle.ParameterName(j), i));
}
int idx = (int)paraNames[fitEle.ParameterName(j)];
if (paraSet[idx].Vary)
{
info.ParameterMapping[j] = (int)varyingParaNames[fitEle.ParameterName(j)];
}
else
{
info.ParameterMapping[j] = -idx - 1;
}
}
}
_cachedDependentValues = new double[_cachedNumberOfData];
GetDependentValues(_cachedDependentValues);
if (HasToUseWeights())
{
_cachedWeights = new double[_cachedNumberOfData];
GetWeights(_cachedWeights);
}
else
{
_cachedWeights = null;
}
}
