Root programming and data analysis

Transcription

1 Special Praktikum: Root programming and data analysis Ascii data: Co60.dat Ge detector t Preamplifier Shaping amp. MCA γ 60Co γ-source 1173 and 1333 kev Ascii data Ascii data: Each line: corresponds to a channel Number: the number of the statistics per channel

2 Procedure of the work Read the ascii data, creating histogram of the gamma-ray distribution Find two peaks Fit each peak by Gaussian Deduce the center of the Gaussian distribution (Mean in channel number) from the fitting Plot data (channel v.s. energy) Obtain the energy calibration Look into the Compton edge Macro name: Co60.CC Data name: Co60.dat Macro and data How to run the root macro Root[0]>.L Co60.C Root[1]> Co60Analysis( Co60.dat );

3 Step (a) Create a histogram by using TH1F class. Please use a pointer for the TH1F object The range of the histogram should be 0~10000 and the number of the bin should be Working on 1-dimensional histograms: Howtocreateahistogram a TH1F *h1 = new TH1F("h1","Eu152",10000,0.0,10000); Filling 1 entry to the bin 35 h1->fill(35); Filling 25 entries to the bin 70 h1->fill(70,25); Step (b) Create a canvas to draw the histogram by using TCanvas class. Working on TCanvas: How to create a TCanvas object TCanvas *c1 = new TCanvas("c1" "c1" ); TCanvas *c1 = new TCanvas("c1","c1",200,10,700,500); How to change a directory to the canvas c1->cd(); H t d t th How to update the canvas c1->update();

4 Steps (d) and (e) In the template, t the programs to open the data file and to read the data is already provided. Inside of the while-iteration, the data value is read. Inside of the while-iteration, the integer number iter is increased thus representing the channel number. Inside of the while-loop, fill the histogram. Outside of the while-iteration, draw the histogram on the canvas. Step (f) Ch kth hit Th h ldb t k i th hit Th Check the histogram. There should be two peaks in the histogram. These peaks correspond to the energies of 1173 and 1333 kev. Find the average value of the peak width.

5 Step (g) Create a TSpectrum object (for example, defined d as s) )for the peak search. The number of the peak can be defined as 2. The peak search can be performed by the Search() method of the TSpectrum object. For the Search() method, the width for the peak search can be defined by using the average width obtained in the procedure (f). Peak search on the histogram h1: How to define a TSpectrum object for two peaks TSpectrum *s = new TSpectrum(2); Peak serch on h1 with width=5 s->search(h1,5,"new"); How to get the peak position and copy to a float pointer *xpeaks float *xpeaks = s->getpositionx(); Steps (h) and (i) Below the line of the peak search, update the canvas. Check the histogram again. There should be markers on the peak if the g g p peak search is succeeded.

6 Step (j) Obtain the peak positions from the peak search by float *xpeaks = s- >GetPositionX();. The method GetPositionX() of the TSpectrum object gives the peak positions. If two peaks are found, xpeaks[0] and xpeaks[1] are the peak positions of the first and second peak, respectively. How to fit histograms and graphs by using TF1 How to create a Gaussian function with a range from x0 to x1 TF1 *func1 = new TF1("func1","gaus",x0,x1); How to create a linear function (1 st order) with a range from x0 to x1 TF1 *func1 = new TF1("func1","pol1",x0,x1); How to fit the histogram h1 by func1 h1->fit(func1, R ); How to fit the graph gr by func1 gr->fit(func1, R ); How to set the initial iti parameter n to value for fitting func1->setparameters(n,value);» For Gaussian» n=0: Constant» n=1: Mean» n=2: Sigma» For a linear fitting» n=0: Offset» n=1: Slope How to get the fitting results and copy to float z float z = func1->getparameter(n); Steps (k) and (l) Create a function for Gaussian fitting by using TF1 class. It should be used for the fitting of the low energy peak. The range of the function can be defined as between xpeaks[0]-50 and xpeaks[0]+50. Fit the first peak by using the function defined above. Observe also the fitting results on the terminal. If the fitting fails, set the initial parameters before performing fitting.

7 Step (m) Do the same procedure for the fitting of the second peak by creating another TF1 object. Steps (n), (o) and (p) Define two float array with two elements, x[2] and y[2] (already done in the macro). Copy the peak positions obtained from the fitting to x[0] and x[1]. Give corresponding energies for the peak to y[0] and y[1].

8 Step (q) Create another canvas, and the change the directory to the new canvas. Steps (r) and (s) Plot x[] and y[] by using the TGraph class. Check the plot. X-axis should be the channel number and the Y-axis the energy. How to create a plot with TGraph How to create a TGraph object, for example, x=1,2,3,4,5 and y = 15,26,37,48,59 float x[5],y[5]; x[0] = 1; x[1] = 2; x[2] = 3; x[3] = 4; x[4] = 5; y[0] = 15; y[1] = 26; y[2] = 37; y[3] = 48; y[4] = 59; TGraph gr = new TGraph(5,x,y); How to plot the data gr->draw( A* );

9 Steps (t) and (u) Create another function for the linear fitting with TF1 class, and fit the data point on the graph. Fitting results (just connecting the two data point in this case) should be shown on the terminal. Par_0 is the offset and Par_1 the slope. This is the energy calibration function for the histogram. Steps (v), (w) and (x) Observe the channel number of the Compton edge of the 1333 kev gamma-ray (Compton edge with the higher energy). Calculate the energy by using the energy calibration function. Compare the observed energy to the theoretical calculations. Do the same procedure for the other Compton edge.

10 Next special Praktikum: January Analyze data in stream by using ROOT tree Correlated data, 2 dimensional How to create 2D plots How to project the plot to axes How to make cut conditions in the analysis How to handle errors How to perform your own fitting