#include <NonLinearFit.h>

Inheritance diagram for NonLinearFit:

Public Member Functions
	NonLinearFit (ApplicationWindow parent, Graph g)
	NonLinearFit (ApplicationWindow parent, Graph g, const QString &curveTitle)
	NonLinearFit (ApplicationWindow parent, Graph g, const QString &curveTitle, double start, double end)
void	setFormula (const QString &s)
void	setParametersList (const QStringList &lst)
Public Member Functions inherited from Fit
double	chiSquare ()
	Returns the sum of squares of the residuals from the best-fit line.
Matrix *	covarianceMatrix (const QString &matrixName)
double *	errors ()
	Returns a vector with the standard deviations of the results.
double	evaluate_d (const gsl_vector *x)
int	evaluate_df (const gsl_vector x, gsl_matrix J)
int	evaluate_f (const gsl_vector x, gsl_vector f)
	Fit (ApplicationWindow parent, Graph g=0, const char *name=0)
virtual void	fit ()
	Actually does the fit. Should be reimplemented in derived classes.
QString	formula ()
void	generateFunction (bool yes, int points=100)
	Specifies weather the result of the fit is a function curve.
virtual void	guessInitialValues ()
virtual QString	legendInfo ()
	Output string added to the plot as a new legend.
int	numParameters ()
Table *	parametersTable (const QString &tableName)
double *	results ()
	Returns a vector with the fit results.
double	rSquare ()
	Returns the coefficient of determination, R^2.
void	scaleErrors (bool yes=true)
	Specifies wheather the errors must be scaled with sqrt(chi_2/dof)
void	setAlgorithm (Algorithm s)
void	setDataCurve (int curve, double start, double end)
void	setInitialGuess (int parIndex, double val)
void	setInitialGuesses (double *x_init)
bool	setYErrorSource (ErrorSource err, const QString &colName=QString::null, bool fail_silently=false)
	Sets the data set to be used as source of Y errors.
	~Fit ()
Public Member Functions inherited from Filter
int	dataSize ()
	Returns the size of the fitted data set.
bool	error ()
	Filter (ApplicationWindow parent, Table t=0, const char *name=0)
	Filter (ApplicationWindow parent, Graph g=0, const char *name=0)
virtual bool	run ()
	Actually does the job. Should be reimplemented in derived classes.
void	setColor (int colorId)
	Sets the color of the output fit curve.
void	setColor (const QString &colorName)
	Sets the color of the output fit curve. Provided for convenience. To be used in scripts only!
bool	setDataFromCurve (const QString &curveTitle, Graph *g=0)
bool	setDataFromCurve (const QString &curveTitle, double from, double to, Graph *g=0)
void	setInterval (double from, double to)
	Changes the data range if the source curve was already assigned. Provided for convenience.
void	setMaximumIterations (int iter)
	Sets the maximum number of iterations to be performed during an iterative session.
void	setOutputPoints (int points)
	Sets the number of points in the output curve.
void	setOutputPrecision (int digits)
	Sets the precision used for the output.
void	setTolerance (double eps)
	Sets the tolerance used by the GSL routines.
virtual void	showLegend ()
	Adds a new legend to the plot. Calls virtual legendInfo()
	~Filter ()
Public Member Functions inherited from scripted
	scripted (ScriptingEnv *env)
void	scriptingChangeEvent (ScriptingChangeEvent *)
	~scripted ()

Private Member Functions
void	calculateFitCurveData (double par, double X, double *Y)
	Calculates the data for the output fit curve and store itin the X an Y vectors.
void	init ()

Additional Inherited Members
Public Types inherited from Fit
enum	Algorithm { ScaledLevenbergMarquardt, UnscaledLevenbergMarquardt, NelderMeadSimplex }
enum	ErrorSource { UnknownErrors, AssociatedErrors, PoissonErrors, CustomErrors }
typedef int(*	fit_function )(const gsl_vector , void , gsl_vector *)
typedef int(*	fit_function_df )(const gsl_vector , void , gsl_matrix *)
typedef int(*	fit_function_fdf )(const gsl_vector , void , gsl_vector , gsl_matrix )
typedef double(*	fit_function_simplex )(const gsl_vector , void )
Static Public Member Functions inherited from Fit
static double	evaluate_df_helper (double x, void *param)
Protected Slots inherited from Fit
void	scriptError (const QString &message, const QString &script_name, int line_number)
Protected Member Functions inherited from Fit
virtual void	generateFitCurve (double *par)
	Adds the result curve to the plot.
void	insertFitFunctionCurve (const QString &name, double x, double y, int penWidth=1)
	Adds the result curve as a FunctionCurve to the plot, if d_gen_function = true.
virtual QString	logFitInfo (double *par, int iterations, int status, const QString &plotName)
	Output string added to the result log.
Protected Member Functions inherited from Filter
QwtPlotCurve *	addResultCurve (double x, double y)
	Adds the result curve to the target output plot window. Creates a hidden table and frees the input data from memory.
virtual void	calculateOutputData (double X, double Y)
	Calculates the data for the output curve and store it in the X an Y vectors.
int	curveIndex (const QString &curveTitle, Graph *g)
	Performs checks and returns the index of the source data curve if OK, -1 otherwise.
virtual bool	isDataAcceptable ()
virtual QString	logInfo ()
	Output string added to the log pannel of the application.
virtual void	output ()
	Performs the data analysis and takes care of the output.
Protected Attributes inherited from Fit
double	chi_2
	The sum of squares of the residuals from the best-fit line.
gsl_matrix *	covar
	Covariance matrix.
fit_function_df	d_df
fit_function	d_f
fit_function_fdf	d_fdf
QString	d_formula
	The fit formula.
fit_function_simplex	d_fsimplex
bool	d_gen_function
	Specifies weather the result curve is a FunctionCurve or a normal curve with the same x values as the fit data.
int	d_p
	Number of fit parameters.
QStringList	d_param_explain
	Stores a list of short explanations for the significance of the fit parameters.
gsl_vector *	d_param_init
	Initial guesses for the fit parameters.
QStringList	d_param_names
	Names of the fit parameters.
double *	d_result_errors
	Stores standard deviations of the result parameters.
double *	d_results
	Stores the result parameters.
bool	d_scale_errors
	Specifies wheather the errors must be scaled with sqrt(chi_2/dof)
Script *	d_script
	Script used to evaluate user-defined functions.
Algorithm	d_solver
	Algorithm type.
QString	d_y_error_dataset
	The name of the dataset containing Y standard errors (if applicable).
ErrorSource	d_y_error_source
	Where standard errors of the input data are taken from.
double *	d_y_errors
	Standard deviations of Y input data.
bool	is_non_linear
	Tells whether the fitter uses non-linear/simplex fitting with an initial parameters set, that must be freed in the destructor.
Protected Attributes inherited from Filter
QwtPlotCurve *	d_curve
	The curve to be analysed.
int	d_curveColorIndex
	Color index of the result curve.
QString	d_explanation
	String explaining the operation in the comment of the result table and in the project explorer.
double	d_from
	Data interval.
Graph *	d_graph
	The graph where the result curve should be displayed.
bool	d_init_err
	Error flag telling if something went wrong during the initialization phase.
int	d_max_iterations
	Maximum number of iterations per fit.
int	d_min_points
	Minimum number of data points necessary to perform the operation.
int	d_n
	Size of the data arrays.
int	d_points
	Number of result points to de calculated and displayed in the output curve.
int	d_prec
	Precision (number of significant digits) used for the results output.
bool	d_sort_data
	Specifies if the filter needs sorted data as input.
Table *	d_table
	A table source of data.
double	d_to
double	d_tolerance
	GSL Tolerance, if ever needed...
double *	d_x
	x data set to be analysed
double *	d_y
	y data set to be analysed
Protected Attributes inherited from scripted
ScriptingEnv *	scriptEnv