public NonlinearFitDocument(NonlinearFitDocument from)
{
_fitEnsemble = null == from._fitEnsemble ? null : (FitEnsemble)from._fitEnsemble.Clone();
_fitEnsemble.Changed += new EventHandler(EhFitEnsemble_Changed);
_currentParameters = null == from._currentParameters ? null : (ParameterSet)from._currentParameters.Clone();
// Note that the fit context is not cloned here.
}
public NonlinearFitDocument(NonlinearFitDocument from)
{
_fitEnsemble = null == from._fitEnsemble ? null : (FitEnsemble)from._fitEnsemble.Clone();
_fitEnsemble.ParentObject = this;
_currentParameters = null == from._currentParameters ? null : (ParameterSet)from._currentParameters.Clone();
// Note that the fit context is not cloned here.
}
public ParameterSetController(ParameterSet doc)
{
_doc = doc;
_doc.InitializationFinished += new EventHandler(EhInitializationFinished);
base.DescriptionText = "ParameterName Value Vary? Variance\r\n" +
"-------------------------------------------------------------------------------------------------------";
EhInitializationFinished(this, EventArgs.Empty);
}
public void CopyParametersBackTo(ParameterSet pset)
{
if (pset.Count != this._constantParameters.Length)
throw new ArgumentException("Length of parameter set pset does not match with cached length of parameter set");
int varyingPara = 0;
for (int i = 0; i < pset.Count; i++)
{
if (pset[i].Vary)
varyingPara++;
}
if (varyingPara != this._cachedVaryingParameters.Length)
throw new ArgumentException("Number of varying parameters in pset does not match cached number of varying parameters");
varyingPara = 0;
for (int i = 0; i < pset.Count; i++)
{
if (pset[i].Vary)
{
pset[i].Parameter = this._cachedVaryingParameters[varyingPara];
pset[i].Variance = _resultingCovariances == null ? 0 : Math.Sqrt(_resultingCovariances[varyingPara + varyingPara * _cachedVaryingParameters.Length]);
varyingPara++;
}
else
{
pset[i].Parameter = this._constantParameters[i];
pset[i].Variance = 0;
}
}
pset.OnInitializationFinished();
}
/// <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>
/// Constructor of the adapter.
/// </summary>
/// <param name="ensemble">The fit ensemble, i.e. the functions and data you intend to fit.</param>
/// <param name="paraSet">The set of initial parameter. Must contain a initial estimation of the parameters. Contains also information which
/// parameters can vary and which are fixed during the fitting procedure.</param>
public LevMarAdapter(FitEnsemble ensemble, ParameterSet paraSet)
{
_fitEnsemble = ensemble;
CalculateCachedData(paraSet);
}
public NonlinearFitDocument()
{
_fitEnsemble = new FitEnsemble();
_currentParameters = new ParameterSet();
_fitEnsemble.Changed += new EventHandler(EhFitEnsemble_Changed);
}
public object Clone()
{
ParameterSet result = new ParameterSet();
for (int i = 0; i < Count; ++i)
result.Add((ParameterSetElement)this[i].Clone());
return result;
}
public NonlinearFitDocument()
{
_fitEnsemble = new FitEnsemble() { ParentObject = this };
_currentParameters = new ParameterSet();
}
/// <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;
}
}
/// <summary>
/// Constructor of the adapter.
/// </summary>
/// <param name="ensemble">The fit ensemble, i.e. the functions and data you intend to fit.</param>
/// <param name="paraSet">The set of initial parameter. Must contain a initial estimation of the parameters. Contains also information which
/// parameters can vary and which are fixed during the fitting procedure.</param>
public LevMarAdapter(FitEnsemble ensemble, ParameterSet paraSet)
{
_fitEnsemble = ensemble;
CalculateCachedData(paraSet);
}
