diff --git a/auto/Wrap/doxygen_fit.i b/auto/Wrap/doxygen_fit.i
index d6ec5c38e8bdb69c5c49a263854bfab034e21063..e0079b8f6e87da1f98ff56efab8622b21db04a76 100644
--- a/auto/Wrap/doxygen_fit.i
+++ b/auto/Wrap/doxygen_fit.i
@@ -98,6 +98,84 @@ returns true if proposed value is in limits range
";
+// File: classBasicMinimizer.xml
+%feature("docstring") BasicMinimizer "
+
+The BasicMinimizer class is a base for all minimizers.
+
+C++ includes: BasicMinimizer.h
+";
+
+%feature("docstring") BasicMinimizer::BasicMinimizer "BasicMinimizer::BasicMinimizer(const std::string &minimizerName, const std::string &algorithmName=std::string())
+";
+
+%feature("docstring") BasicMinimizer::~BasicMinimizer "BasicMinimizer::~BasicMinimizer()
+";
+
+%feature("docstring") BasicMinimizer::minimize "void BasicMinimizer::minimize()
+
+run minimization
+";
+
+%feature("docstring") BasicMinimizer::minimizerName "std::string BasicMinimizer::minimizerName() const
+
+Returns name of the minimizer.
+";
+
+%feature("docstring") BasicMinimizer::algorithmName "std::string BasicMinimizer::algorithmName() const
+
+Returns name of the minimization algorithm.
+";
+
+%feature("docstring") BasicMinimizer::setAlgorithmName "void BasicMinimizer::setAlgorithmName(const std::string &algorithmName)
+
+Sets minimization algorithm.
+";
+
+%feature("docstring") BasicMinimizer::setParameter "void BasicMinimizer::setParameter(size_t index, const FitParameter *par)
+
+Sets internal minimizer parameter.
+";
+
+%feature("docstring") BasicMinimizer::setParameters "void BasicMinimizer::setParameters(const FitSuiteParameters ¶meters)
+
+Sets internal minimizer parameters using external parameter list.
+";
+
+%feature("docstring") BasicMinimizer::setChiSquaredFunction "void BasicMinimizer::setChiSquaredFunction(function_chi2_t fun_chi2, size_t nparameters)
+
+Sets chi squared function to minimize.
+";
+
+%feature("docstring") BasicMinimizer::setGradientFunction "void BasicMinimizer::setGradientFunction(function_gradient_t fun_gradient, size_t nparameters, size_t ndatasize)
+
+Sets gradient function to minimize.
+";
+
+%feature("docstring") BasicMinimizer::isGradientBasedAgorithm "virtual bool BasicMinimizer::isGradientBasedAgorithm()
+
+Returns true if type of algorithm is Levenberg-Marquardt or similar.
+";
+
+%feature("docstring") BasicMinimizer::getValueOfVariablesAtMinimum "std::vector< double > BasicMinimizer::getValueOfVariablesAtMinimum() const
+
+Returns values of parameters at the minimum.
+";
+
+%feature("docstring") BasicMinimizer::getErrorOfVariables "std::vector< double > BasicMinimizer::getErrorOfVariables() const
+
+Returns errors of variables at minimum.
+";
+
+%feature("docstring") BasicMinimizer::printResults "void BasicMinimizer::printResults() const
+
+Prints fit results.
+";
+
+%feature("docstring") BasicMinimizer::toResultString "std::string BasicMinimizer::toResultString() const
+";
+
+
// File: classMinimizerLibrary_1_1Catalogue.xml
%feature("docstring") MinimizerLibrary::Catalogue "";
@@ -122,6 +200,45 @@ Returns list of algorithm descriptions for given minimizer type.
";
+// File: classConfigurable.xml
+%feature("docstring") Configurable "
+
+The Configurable class is a base for storing (int,double,string) options.
+
+C++ includes: Configurable.h
+";
+
+%feature("docstring") Configurable::Configurable "Configurable::Configurable()
+";
+
+%feature("docstring") Configurable::Configurable "Configurable::Configurable(const Configurable &other)
+
+Returns true if option with such name already exists.
+";
+
+%feature("docstring") Configurable::addOption "Configurable::option_t Configurable::addOption(const std::string &optionName, T value, const std::string &description=std::string())
+";
+
+%feature("docstring") Configurable::option "Configurable::option_t Configurable::option(const std::string &optionName)
+";
+
+%feature("docstring") Configurable::option "const Configurable::option_t Configurable::option(const std::string &optionName) const
+";
+
+%feature("docstring") Configurable::optionValue "T Configurable::optionValue(const std::string &optionName) const
+";
+
+%feature("docstring") Configurable::setOptionValue "void Configurable::setOptionValue(const std::string &optionName, T value)
+
+Sets the value of option. Option should hold same value type already.
+";
+
+%feature("docstring") Configurable::toOptionString "std::string Configurable::toOptionString(const std::string &delimeter=\";\") const
+
+Returns string with all options using given delimeter.
+";
+
+
// File: classFitParameter.xml
%feature("docstring") FitParameter "
@@ -197,7 +314,7 @@ Clears all defined parameters.
Adds fit parameter.
";
-%feature("docstring") FitSuiteParameters::getParameters "std::vector<FitParameter*> FitSuiteParameters::getParameters()
+%feature("docstring") FitSuiteParameters::getParameters "std::vector<FitParameter*>& FitSuiteParameters::getParameters()
Returns all parameters.
";
@@ -511,6 +628,46 @@ Returns list of string with description of all available algorithms.
";
+// File: classMinimizerOption.xml
+%feature("docstring") MinimizerOption "
+
+The MinimizerOption class is intended to store a single option for minimization algorithm. Int, double, string values are available. Relies on https://github.com/mapbox/variant, will be switched to std::variant in C++-17.
+
+C++ includes: MinimizerOption.h
+";
+
+%feature("docstring") MinimizerOption::MinimizerOption "MinimizerOption::MinimizerOption(const std::string &name=std::string())
+";
+
+%feature("docstring") MinimizerOption::MinimizerOption "MinimizerOption::MinimizerOption(const std::string &name, const T &t, const std::string &descripion=std::string())
+";
+
+%feature("docstring") MinimizerOption::name "std::string MinimizerOption::name() const
+";
+
+%feature("docstring") MinimizerOption::description "std::string MinimizerOption::description() const
+";
+
+%feature("docstring") MinimizerOption::setDescription "void MinimizerOption::setDescription(const std::string &description)
+";
+
+%feature("docstring") MinimizerOption::value "MinimizerOption::variant_t & MinimizerOption::value()
+";
+
+%feature("docstring") MinimizerOption::defaultValue "MinimizerOption::variant_t & MinimizerOption::defaultValue()
+";
+
+%feature("docstring") MinimizerOption::get "T MinimizerOption::get() const
+
+Returns the option's value.
+";
+
+%feature("docstring") MinimizerOption::getDefault "T MinimizerOption::getDefault() const
+
+Returns the option's default value (i.e. used during construction)
+";
+
+
// File: classMinimizerOptions.xml
%feature("docstring") MinimizerOptions "
@@ -619,6 +776,61 @@ set option value
";
+// File: classMinuit2Minimizer.xml
+%feature("docstring") Minuit2Minimizer "
+
+The Minuit2Minimizer class is a wrapper for ROOT Minuit2 minimizer See Minuit2 user manual https://root.cern.ch/root/htmldoc/guides/minuit2/Minuit2.pdf.
+
+C++ includes: Minuit2Minimizer.h
+";
+
+%feature("docstring") Minuit2Minimizer::Minuit2Minimizer "Minuit2Minimizer::Minuit2Minimizer()
+";
+
+%feature("docstring") Minuit2Minimizer::~Minuit2Minimizer "Minuit2Minimizer::~Minuit2Minimizer()
+";
+
+%feature("docstring") Minuit2Minimizer::setStrategy "void Minuit2Minimizer::setStrategy(int value)
+
+Sets minimization strategy (0-low, 1-medium, 2-high minimization quality). At low quality number of function calls will be economized. Default value is 1.
+";
+
+%feature("docstring") Minuit2Minimizer::strategy "int Minuit2Minimizer::strategy() const
+";
+
+%feature("docstring") Minuit2Minimizer::setErrorDefinition "void Minuit2Minimizer::setErrorDefinition(double value)
+
+Sets error definition factor for parameter error calculation. If objective function (OF) is the usual chisquare function and if the user wants the usual one-standard-deviation errors, then the error definition should be 1.0. If OF is a negative-log-likelihood function, then 0.5. If OF is a chisquare, but the user wants two-standard-deviation errors, 4.0. Default value is 1.0.
+";
+
+%feature("docstring") Minuit2Minimizer::errorDefinition "double Minuit2Minimizer::errorDefinition() const
+
+Sets tolerance on the function value at the minimum. Minimization will stop when the estimated vertical distance to the minimum (EDM) is less than 0.001*tolerance*ErrorDef. Here ErrorDef=1.0 for chi squared fit and ErrorDef=0.5 for negative log likelihood fit. Default value is 0.01.
+";
+
+%feature("docstring") Minuit2Minimizer::setTolerance "void Minuit2Minimizer::setTolerance(double value)
+";
+
+%feature("docstring") Minuit2Minimizer::tolerance "double Minuit2Minimizer::tolerance() const
+
+Sets relative floating point arithmetic precision. Should be adjusted when the user knows that objectiove function value is not calculated to the nominal machine accuracy. Typical values are between 10^-5 and 10^-14. Default value is -1.0 (minimizer specific will be used).
+";
+
+%feature("docstring") Minuit2Minimizer::setPrecision "void Minuit2Minimizer::setPrecision(double value)
+";
+
+%feature("docstring") Minuit2Minimizer::precision "double Minuit2Minimizer::precision() const
+";
+
+%feature("docstring") Minuit2Minimizer::setPrintLevel "void Minuit2Minimizer::setPrintLevel(int value)
+
+Sets minimizer internal print level. Default value is 0 (silent).
+";
+
+%feature("docstring") Minuit2Minimizer::printLevel "int Minuit2Minimizer::printLevel() const
+";
+
+
// File: classROOTGeneticMinimizer.xml
%feature("docstring") ROOTGeneticMinimizer "
@@ -961,6 +1173,9 @@ return minimizer options
";
+// File: namespace_0D15.xml
+
+
// File: namespaceAlgorithmNames.xml
@@ -1011,6 +1226,18 @@ Returns string right-padded with blanks.
// File: AlgorithmNames_8h.xml
+// File: BasicMinimizer_8cpp.xml
+
+
+// File: BasicMinimizer_8h.xml
+
+
+// File: Configurable_8cpp.xml
+
+
+// File: Configurable_8h.xml
+
+
// File: IMinimizer_8cpp.xml
@@ -1029,12 +1256,24 @@ Returns string right-padded with blanks.
// File: MinimizerLibrary_8h.xml
+// File: MinimizerOption_8cpp.xml
+
+
+// File: MinimizerOption_8h.xml
+
+
// File: MinimizerOptions_8cpp.xml
// File: MinimizerOptions_8h.xml
+// File: Minuit2Minimizer_8cpp.xml
+
+
+// File: Minuit2Minimizer_8h.xml
+
+
// File: TrivialMinimizer_8cpp.xml
diff --git a/auto/Wrap/libBornAgainFit.py b/auto/Wrap/libBornAgainFit.py
index 75e77356966e9c6592ba47a5006cf30c2eaaca1d..cafc13b0db65ba2237cfa6a3b142aeabbf8876e1 100644
--- a/auto/Wrap/libBornAgainFit.py
+++ b/auto/Wrap/libBornAgainFit.py
@@ -2175,7 +2175,7 @@ class FitSuiteParameters(_object):
"""
getParameters(FitSuiteParameters self) -> std::vector< FitParameter *,std::allocator< FitParameter * > > &
- std::vector<FitParameter*> FitSuiteParameters::getParameters()
+ std::vector<FitParameter*>& FitSuiteParameters::getParameters()
Returns all parameters.
diff --git a/auto/Wrap/libBornAgainFit_wrap.cpp b/auto/Wrap/libBornAgainFit_wrap.cpp
index 26b7eae82ca4bdadbbede14bac8bd559ec492235..c9e94265072ab21e434176811dc2538e6e208e13 100644
--- a/auto/Wrap/libBornAgainFit_wrap.cpp
+++ b/auto/Wrap/libBornAgainFit_wrap.cpp
@@ -23476,7 +23476,7 @@ static PyMethodDef SwigMethods[] = {
{ (char *)"FitSuiteParameters_getParameters", _wrap_FitSuiteParameters_getParameters, METH_VARARGS, (char *)"\n"
"FitSuiteParameters_getParameters(FitSuiteParameters self) -> std::vector< FitParameter *,std::allocator< FitParameter * > > &\n"
"\n"
- "std::vector<FitParameter*> FitSuiteParameters::getParameters()\n"
+ "std::vector<FitParameter*>& FitSuiteParameters::getParameters()\n"
"\n"
"Returns all parameters. \n"
"\n"