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/***************************************************************************

    File                 : NonLinearFit.cpp

    Project              : SciDAVis

    --------------------------------------------------------------------

    Copyright            : (C) 2006 by Ion Vasilief, Tilman Benkert

    Email (use @ for *)  : ion_vasilief*yahoo.fr, thzs*gmx.net

    Description          : NonLinearFit class

 

 ***************************************************************************/

 

/***************************************************************************

 *                                                                         *

 *  This program is free software; you can redistribute it and/or modify   *

 *  it under the terms of the GNU General Public License as published by   *

 *  the Free Software Foundation; either version 2 of the License, or      *

 *  (at your option) any later version.                                    *

 *                                                                         *

 *  This program is distributed in the hope that it will be useful,        *

 *  but WITHOUT ANY WARRANTY; without even the implied warranty of         *

 *  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the          *

 *  GNU General Public License for more details.                           *

 *                                                                         *

 *   You should have received a copy of the GNU General Public License     *

 *   along with this program; if not, write to the Free Software           *

 *   Foundation, Inc., 51 Franklin Street, Fifth Floor,                    *

 *   Boston, MA  02110-1301  USA                                           *

 *                                                                         *

 ***************************************************************************/

#include "NonLinearFit.h"

#include "MyParser.h"

#include "fit_gsl.h"

 

#include <QMessageBox>

 

        NonLinearFit::NonLinearFit(ApplicationWindow *parent, Graph *g)

: Fit(parent, g)

{

        init();

}

 

        NonLinearFit::NonLinearFit(ApplicationWindow *parent, Graph *g, const QString& curveTitle)

: Fit(parent, g)

{

        init();

        setDataFromCurve(curveTitle);

}

 

        NonLinearFit::NonLinearFit(ApplicationWindow *parent, Graph *g, const QString& curveTitle, double start, double end)

: Fit(parent, g)

{

        init();

        setDataFromCurve(curveTitle, start, end);

}

 

void NonLinearFit::init()

{

        setName(tr("NonLinear"));

        d_formula = QString::null;

        d_f = user_f;

        d_df = user_df;

        d_fdf = user_fdf;

        d_fsimplex = user_d;

        d_explanation = tr("Non-linear");

        d_init_err = false;

}

 

void NonLinearFit::setFormula(const QString& s)

{

        d_formula = s;

}

 

void NonLinearFit::setParametersList(const QStringList& lst)

{

        if ((int)lst.count() < 1)

        {

                QMessageBox::critical((ApplicationWindow *)parent(), tr("Fit Error"),

                                tr("You must provide a list containing at least one parameter for this type of fit. Operation aborted!"));

                d_init_err = true;

                return;

        }

 

        d_init_err = false;

        d_param_names = lst;

 

        if (d_p > 0)

        {//free previously allocated memory

                gsl_vector_free(d_param_init);

                gsl_matrix_free (covar);

                delete[] d_results;

        }

 

        d_p = (int)lst.count();

    d_min_points = d_p;

        d_param_init = gsl_vector_alloc(d_p);

        gsl_vector_set_all (d_param_init, 1.0);

 

        covar = gsl_matrix_alloc (d_p, d_p);

        d_results = new double[d_p];

 

        for (int i=0; i<d_p; i++)

                d_param_explain << "";

}

 

void NonLinearFit::calculateFitCurveData(double *par, double *X, double *Y)

{

    for (int i=0; i<d_p; i++)

        d_script->setDouble(par[i], d_param_names[i]);

 

    if (d_gen_function) {

        double X0 = d_x[0];

        double step = (d_x[d_n-1]-X0)/(d_points-1);

        for (int i=0; i<d_points; i++) {

            X[i] = X0+i*step;

            d_script->setDouble(X[i], "x");

            Y[i] = d_script->eval().toDouble();

        }

    } else {

        for (int i=0; i<d_points; i++) {

            X[i] = d_x[i];

            d_script->setDouble(X[i], "x");

            Y[i] = d_script->eval().toDouble();

        }

    }

}