mirror of
https://github.com/aportelli/LatAnalyze.git
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237 lines
9.1 KiB
C++
237 lines
9.1 KiB
C++
/*
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* XYStatData.hpp, part of LatAnalyze 3
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*
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* Copyright (C) 2013 - 2016 Antonin Portelli
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*
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* LatAnalyze 3 is free software: you can redistribute it and/or modify
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* it under the terms of the GNU General Public License as published by
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* the Free Software Foundation, either version 3 of the License, or
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* (at your option) any later version.
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*
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* LatAnalyze 3 is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with LatAnalyze 3. If not, see <http://www.gnu.org/licenses/>.
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*/
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#ifndef Latan_XYStatData_hpp_
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#define Latan_XYStatData_hpp_
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#include <LatAnalyze/Global.hpp>
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#include <LatAnalyze/FitInterface.hpp>
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#include <LatAnalyze/Minimizer.hpp>
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#include <LatAnalyze/Model.hpp>
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BEGIN_LATAN_NAMESPACE
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/******************************************************************************
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* object for fit result *
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******************************************************************************/
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class FitResult: public DVec
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{
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friend class XYStatData;
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friend class XYSampleData;
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friend class SampleFitResult;
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public:
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// constructors
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FitResult(void) = default;
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EIGEN_EXPR_CTOR(FitResult, FitResult, Base, MatExpr)
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// destructor
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virtual ~FitResult(void) = default;
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// access
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double getChi2(void) const;
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double getChi2PerDof(void) const;
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double getNDof(void) const;
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Index getNPar(void) const;
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double getPValue(void) const;
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const DoubleFunction & getModel(const Index j = 0) const;
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// IO
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void print(const bool printXsi = false,
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std::ostream &out = std::cout) const;
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private:
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double chi2_{0.};
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Index nDof_{0}, nPar_{0};
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std::vector<DoubleFunction> model_;
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std::vector<std::string> parName_;
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};
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/******************************************************************************
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* class for X vs. Y statistical data *
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******************************************************************************/
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class XYStatData: public FitInterface
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{
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public:
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// constructor
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XYStatData(void) = default;
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// destructor
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virtual ~XYStatData(void) = default;
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// data access
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double & x(const Index r, const Index i);
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const double & x(const Index r, const Index i) const;
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const DVec & x(const Index k) const;
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double & y(const Index k, const Index j);
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const double & y(const Index k, const Index j) const;
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void setXXVar(const Index i1, const Index i2, const DMat &m);
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void setYYVar(const Index j1, const Index j2, const DMat &m);
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void setXYVar(const Index i, const Index j, const DMat &m);
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void setXError(const Index i, const DVec &err);
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void setYError(const Index j, const DVec &err);
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template <typename... Ts>
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void setUnidimData(const DMat &xData, const Ts & ...yDatas);
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const DMat & getXXVar(const Index i1, const Index i2) const;
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const DMat & getYYVar(const Index j1, const Index j2) const;
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const DMat & getXYVar(const Index i, const Index j) const;
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DVec getXError(const Index i) const;
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DVec getYError(const Index j) const;
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DMat getTable(const Index i, const Index j) const;
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// get total fit variance matrix and its pseudo-inverse
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const DMat & getFitVarMat(void);
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const DMat & getFitVarMatPInv(void);
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// fit
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FitResult fit(std::vector<Minimizer *> &minimizer, const DVec &init,
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const std::vector<const DoubleModel *> &v);
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FitResult fit(Minimizer &minimizer, const DVec &init,
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const std::vector<const DoubleModel *> &v);
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template <typename... Ts>
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FitResult fit(std::vector<Minimizer *> &minimizer, const DVec &init,
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const DoubleModel &model, const Ts... models);
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template <typename... Ts>
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FitResult fit(Minimizer &minimizer, const DVec &init,
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const DoubleModel &model, const Ts... models);
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// residuals
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XYStatData getResiduals(const FitResult &fit);
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XYStatData getPartialResiduals(const FitResult &fit, const DVec &ref,
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const Index i);
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protected:
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// create data
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virtual void createXData(const std::string name, const Index nData);
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virtual void createYData(const std::string name);
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void resizeVarMat(void);
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private:
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// schedule buffer computation
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void scheduleXMapInit(void);
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void scheduleChi2DataVecInit(void);
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// buffer total fit variance matrix
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void updateFitVarMat(void);
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// buffer list of x vectors
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void updateXMap(void) const;
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// buffer chi^2 vectors
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void updateChi2DataVec(void);
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void updateChi2ModVec(const DVec p,
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const std::vector<const DoubleModel *> &v,
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const Index nPar, const Index nXDim);
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private:
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std::vector<std::map<Index, double>> yData_;
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// no map here for fit performance
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std::vector<DVec> xData_;
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std::vector<DVec> xMap_;
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Mat<DMat> xxVar_, yyVar_, xyVar_;
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DMat fitVar_, fitVarInv_;
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DVec chi2DataVec_, chi2ModVec_, chi2Vec_;
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DVec xBuf_;
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bool initXMap_{true};
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bool initChi2DataVec_{true};
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};
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/******************************************************************************
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* XYStatData template implementation *
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******************************************************************************/
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template <typename... Ts>
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void XYStatData::setUnidimData(const DMat &xData, const Ts & ...yDatas)
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{
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static_assert(static_or<std::is_assignable<DMat, Ts>::value...>::value,
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"y data arguments are not compatible with DMat");
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std::vector<const DMat *> yData{&yDatas...};
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FOR_VEC(xData, r)
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{
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x(r, 0) = xData(r);
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for (unsigned int j = 0; j < yData.size(); ++j)
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{
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y(r, j) = (*(yData[j]))(r);
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}
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}
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}
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template <typename... Ts>
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FitResult XYStatData::fit(std::vector<Minimizer *> &minimizer, const DVec &init,
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const DoubleModel &model, const Ts... models)
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{
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static_assert(static_or<std::is_assignable<DoubleModel &, Ts>::value...>::value,
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"model arguments are not compatible with DoubleModel");
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std::vector<const DoubleModel *> modelVector{&model, &models...};
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return fit(minimizer, init, modelVector);
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}
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template <typename... Ts>
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FitResult XYStatData::fit(Minimizer &minimizer, const DVec &init,
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const DoubleModel &model, const Ts... models)
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{
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static_assert(static_or<std::is_assignable<DoubleModel &, Ts>::value...>::value,
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"model arguments are not compatible with DoubleModel");
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std::vector<Minimizer *> mv{&minimizer};
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return fit(mv, init, model, models...);
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}
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/******************************************************************************
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* error check macros *
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******************************************************************************/
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#define checkVarMat(m, var)\
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if (((m).rows() != (var).rows()) or ((m).cols() != (var).cols()))\
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{\
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LATAN_ERROR(Size, "provided variance matrix has a wrong size"\
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" (expected " + strFrom((var).rows()) + "x"\
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+ strFrom((var).cols()) + ", got " + strFrom((m).rows())\
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+ "x" + strFrom((m).cols()) + ")");\
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}
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#define checkErrVec(err, var)\
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if ((err).size() != (var).rows())\
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{\
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LATAN_ERROR(Size, "provided error vector has a wrong size"\
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" (expected " + strFrom((var).rows()) + ", got "\
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+ strFrom((err).size()) + ")");\
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}
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#define checkModelVec(v)\
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if (static_cast<Index>((v).size()) != getNYDim())\
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{\
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LATAN_ERROR(Size, "provided model vector has a wrong size"\
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" (expected " + strFrom(getNYDim()) + ", got "\
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+ strFrom((v).size()) + ")");\
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}\
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for (unsigned int _i = 1; _i < (v).size(); ++_i)\
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{\
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if ((v)[_i]->getNArg() != getNXDim())\
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{\
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LATAN_ERROR(Size, "model " + strFrom(_i) + " has a wrong"\
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+ " number of argument (expected " + strFrom(getNXDim())\
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+ ", got " + strFrom((v)[_i]->getNArg()));\
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}\
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}\
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{\
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Index _nPar = (v)[0]->getNPar();\
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for (unsigned int _i = 1; _i < (v).size(); ++_i)\
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{\
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if ((v)[_i]->getNPar() != _nPar)\
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{\
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LATAN_ERROR(Size, "model " + strFrom(_i) + " has a wrong"\
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+ " number of parameter (expected " + strFrom(_nPar)\
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+ ", got " + strFrom((v)[_i]->getNPar()));\
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}\
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}\
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}
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END_LATAN_NAMESPACE
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#endif // Latan_XYStatData_hpp_
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