align.cpp File Reference

Align 4 chambers with minuit. More...

#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <math.h>
#include "TROOT.h"
#include "TFile.h"
#include "TTree.h"
#include "TLeaf.h"
#include "TMinuit.h"
#include "GeoServer.h"

Defines
#define	TMAX   25000
	max.
Functions
void	linfit (double x[], double y[], int ndata, double sig[], int mwt, double *a, double *b, double *siga, double *sigb, double *chi2)
	Straight line fit from Numerical Recipes.
void	FCN (Int_t &npar, Double_t *gin, Double_t &f, Double_t *par, Int_t iflag)
	Minuit minimization fuction.
int	main (int argc, char *argv[])
	main program

---

Detailed Description

Align 4 chambers with minuit.

reads output tree of long.cpp

---

Define Documentation

#define TMAX   25000

max. number of tracks

---

Function Documentation

void FCN (  Int_t &  npar, Double_t *  gin, Double_t &  f, Double_t *  par, Int_t  iflag )

Minuit minimization fuction. Input parameters Parameters: npar  number of currently variable parameters. par  vector of (constant and variable) parameters. iflag  Indicates what is to be calculated (see example below). Output parameters Parameters: f  The calculated function value: chi-squared. gin  The (optional) vector of first derivatives).

void linfit (  double  x[], double  y[], int  ndata, double  sig[], int  mwt, double *  a, double *  b, double *  siga, double *  sigb, double *  chi2 )

Straight line fit from Numerical Recipes. Given a set of points x[0..ndata-1], y[0..ndata-1] with standard deviations sig[0..ndata-1], fit them to a straight line y = a+bx by minimizing chi-squared. Returned are a,b and their respective probable uncertainties siga and sigb, the chi-square chi2. If mwt = 0 on input, then the standard deviations are assumed to be unavailable: the normalization of chi2 is to unit standard deviation on all points. Note: This was copied from Numerical Recipes and modified: The arrays are 0-based and the goodness-of-fit is not computed. All float variables are now double. Parameters: x  the 0-based array of x values. y  the 0-based array of y values. ndata  the number of elements in x, y, and sig. sig  the 0-based array of y errors mwt  if set to 0, then the errors in sig are ignored. a  the intercept of the line. b  the slope of the line. siga  the error on the intercept. sigb  the error on the slope chi2  the chi-squared of the fit.

---