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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 enum FitType{BuiltIn = 0, Plugin = 1, User = 2};
00058
00059 Fit(ApplicationWindow *parent, Graph *g = 0, const QString& name = QString());
00060 Fit(ApplicationWindow *parent, Table *t, const QString& name = QString());
00061 ~Fit();
00062
00064 virtual void fit();
00065 virtual bool run(){fit(); return true;};
00066
00068 bool setWeightingData(WeightingMethod w, const QString& colName = QString::null);
00069
00070 void setDataCurve(int curve, double start, double end);
00071 bool setDataFromTable(Table *t, const QString& xColName, const QString& yColName, int from = 1, int to = -1);
00072
00073 QString resultFormula(){return d_result_formula;};
00074 QString formula(){return d_formula;};
00075 virtual void setFormula(const QString&){};
00076
00077 int numParameters(){return d_p;};
00078 QStringList parameterNames(){return d_param_names;};
00079 virtual void setParametersList(const QStringList&){};
00080 void setParameterExplanations(const QStringList& lst){d_param_explain = lst;};
00081
00082 double initialGuess(int parIndex){return gsl_vector_get(d_param_init, parIndex);};
00083 void setInitialGuess(int parIndex, double val){gsl_vector_set(d_param_init, parIndex, val);};
00084 void setInitialGuesses(double *x_init);
00085
00086 virtual void guessInitialValues(){};
00087
00088 void setParameterRange(int parIndex, double left, double right);
00089 void setAlgorithm(Algorithm s){d_solver = s;};
00090
00092 void generateFunction(bool yes, int points = 100);
00093
00095 virtual QString legendInfo();
00096
00098 double* results(){return d_results;};
00099
00101 double* residuals();
00102
00104 QwtPlotCurve* showResiduals();
00105
00106 void showPredictionLimits(double confidenceLevel);
00107 void showConfidenceLimits(double confidenceLevel);
00109 double lcl(int parIndex, double confidenceLevel);
00111 double ucl(int parIndex, double confidenceLevel);
00112
00114 double* errors();
00115
00117 double chiSquare() {return chi_2;};
00118
00120 double rSquare();
00121
00123 double adjustedRSquare(){return d_adjusted_r_square;};
00124
00126 double rss(){return d_rss;};
00127
00129 double rmse(){return sqrt(d_rss/(d_n - d_p));};
00130
00132 void scaleErrors(bool yes = true){d_scale_errors = yes;};
00133
00134 Table* parametersTable(const QString& tableName);
00135 void writeParametersToTable(Table *t, bool append = false);
00136
00137 Matrix* covarianceMatrix(const QString& matrixName);
00138
00139 bool save(const QString& fileName);
00140 bool load(const QString& fileName);
00141
00142 FitType type(){return d_fit_type;};
00143 void setType(FitType t){d_fit_type = t;};
00144
00145 QString fileName(){return d_file_name;};
00146 void setFileName(const QString& fn){d_file_name = fn;};
00147
00149 void freeMemory();
00150
00152 virtual double eval(double *, double){return 0.0;};
00153
00154 private:
00155 void init();
00156
00158 gsl_multimin_fminimizer * fitSimplex(gsl_multimin_function f, int &iterations, int &status);
00159
00161 gsl_multifit_fdfsolver * fitGSL(gsl_multifit_function_fdf f, int &iterations, int &status);
00162
00164 virtual void customizeFitResults(){};
00165
00166 protected:
00168 void initWorkspace(int par);
00170 void freeWorkspace();
00172 virtual FunctionCurve * insertFitFunctionCurve(const QString& name, double *x, double *y, int penWidth = 1);
00173
00175 virtual void generateFitCurve();
00176
00178 virtual void calculateFitCurveData(double *X, double *Y) {Q_UNUSED(X) Q_UNUSED(Y)};
00179
00181 virtual QString logFitInfo(int iterations, int status);
00182
00183 fit_function d_f;
00184 fit_function_df d_df;
00185 fit_function_fdf d_fdf;
00186 fit_function_simplex d_fsimplex;
00187
00189 int d_p;
00190
00192 gsl_vector *d_param_init;
00193
00197 bool is_non_linear;
00198
00200 double *d_w;
00201
00203 QStringList d_param_names;
00204
00206 QStringList d_param_explain;
00207
00209 bool d_gen_function;
00210
00212 Algorithm d_solver;
00213
00215 QString d_formula;
00216
00218 QString d_result_formula;
00219
00221 gsl_matrix *covar;
00222
00224 WeightingMethod d_weighting;
00225
00227 QString weighting_dataset;
00228
00230 double *d_results;
00231
00233 double *d_errors;
00234
00236 double *d_residuals;
00237
00239 double chi_2;
00240
00242 double d_rss;
00243
00245 double d_adjusted_r_square;
00246
00248 bool d_scale_errors;
00249
00251 Table *d_param_table;
00252
00254 Matrix *d_cov_matrix;
00255
00256 FitType d_fit_type;
00257
00259 QString d_file_name;
00260
00262 double *d_param_range_left;
00263
00265 double *d_param_range_right;
00266 };
00267
00268 #endif