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00029 #ifndef FIT_H
00030 #define FIT_H
00031
00032 #include <QObject>
00033
00034 #include "ApplicationWindow.h"
00035 #include "Filter.h"
00036
00037 #include <gsl/gsl_multifit_nlin.h>
00038 #include <gsl/gsl_multimin.h>
00039
00040 class Table;
00041 class Matrix;
00042
00044 class Fit : public Filter
00045 {
00046 Q_OBJECT
00047
00048 public:
00049
00050 typedef double (*fit_function_simplex)(const gsl_vector *, void *);
00051 typedef int (*fit_function)(const gsl_vector *, void *, gsl_vector *);
00052 typedef int (*fit_function_df)(const gsl_vector *, void *, gsl_matrix *);
00053 typedef int (*fit_function_fdf)(const gsl_vector *, void *, gsl_vector *, gsl_matrix *);
00054
00055 enum Algorithm{ScaledLevenbergMarquardt, UnscaledLevenbergMarquardt, NelderMeadSimplex};
00056 enum WeightingMethod{NoWeighting, Instrumental, Statistical, Dataset};
00057
00058 Fit(ApplicationWindow *parent, Graph *g = 0, const char * name = 0);
00059 ~Fit();
00060
00062 virtual void fit();
00063 virtual bool run(){return false;};
00064
00066 bool setWeightingData(WeightingMethod w, const QString& colName = QString::null);
00067
00068 void setDataCurve(int curve, double start, double end);
00069
00070 QString formula(){return d_formula;};
00071 int numParameters() {return d_p;}
00072
00073 void setInitialGuess(int parIndex, double val){gsl_vector_set(d_param_init, parIndex, val);};
00074 void setInitialGuesses(double *x_init);
00075
00076 virtual void guessInitialValues(){};
00077
00078 void setAlgorithm(Algorithm s){d_solver = s;};
00079
00081 void generateFunction(bool yes, int points = 100);
00082
00084 virtual QString legendInfo();
00085
00087 double* results(){return d_results;};
00088
00090 double* errors();
00091
00093 double chiSquare() {return chi_2;};
00094
00096 double rSquare();
00097
00099 void scaleErrors(bool yes = true){d_scale_errors = yes;};
00100
00101 Table* parametersTable(const QString& tableName);
00102 Matrix* covarianceMatrix(const QString& matrixName);
00103
00104 private:
00106 gsl_multimin_fminimizer * fitSimplex(gsl_multimin_function f, int &iterations, int &status);
00107
00109 gsl_multifit_fdfsolver * fitGSL(gsl_multifit_function_fdf f, int &iterations, int &status);
00110
00112 virtual void storeCustomFitResults(double *par);
00113
00114 protected:
00116 void insertFitFunctionCurve(const QString& name, double *x, double *y, int penWidth = 1);
00117
00119 virtual void generateFitCurve(double *par);
00120
00122 virtual void calculateFitCurveData(double *par, double *X, double *Y) { Q_UNUSED(par) Q_UNUSED(X) Q_UNUSED(Y) };
00123
00125 virtual QString logFitInfo(double *par, int iterations, int status, const QString& plotName);
00126
00127 fit_function d_f;
00128 fit_function_df d_df;
00129 fit_function_fdf d_fdf;
00130 fit_function_simplex d_fsimplex;
00131
00133 int d_p;
00134
00136 gsl_vector *d_param_init;
00137
00141 bool is_non_linear;
00142
00144 double *d_w;
00145
00147 QStringList d_param_names;
00148
00150 QStringList d_param_explain;
00151
00153 bool d_gen_function;
00154
00156 Algorithm d_solver;
00157
00159 QString d_formula;
00160
00162 gsl_matrix *covar;
00163
00165 WeightingMethod d_weihting;
00166
00168 QString weighting_dataset;
00169
00171 double *d_results;
00172
00174 double *d_errors;
00175
00177 double chi_2;
00178
00180 bool d_scale_errors;
00181 };
00182
00183 #endif