TTOFWFFit Class Reference

this class is intended to work on TTOFEvent TTrees More...

#include <TTOFWFFit.h>

Inheritance diagram for TTOFWFFit:

Collaboration diagram for TTOFWFFit:

Public Member Functions
	TTOFWFFit ()
	TTOFWFFit (int a_fitFunc)
	TTOFWFFit (std::string a_fileName)
void	readConfigFile (std::string a_fileName)
void	readCutFile (std::string a_fileName)
void	drawInvertedWFGraph (int a_evNum, bool a_clearGraph=true)
TGraph *	getInvertedWFTGraph (int a_evNum)
void	drawWFGraph (int a_evNum, bool a_clearGraph=true)
TGraph *	getWFTGraph (int a_evNum)
void	drawRandomInvertedWF (int a_rangeStart, int a_rangeEnd)
void	applyCutsToFile (std::string a_outFileName)
	function to apply cuts to data in tree More...
void	seperateFitsToFile (std::string a_outFileName)
	function to seperate fit data More...
void	runWFFitting ()
bool	passesCuts (TTOFEvent *a_event)
void	drawAnanyaWFTest (string a_WFFile, string a_WFName, double norm_1, double tau1_1, double tau2_1, double norm_2, double tau1_2, double tau2_2, double norm_3, double tau1_3, double tau2_3, double dt, bool a_drawAllExp=false)
void	drawAnanyaQuadWFTest (string a_WFFile, string a_WFName, double norm_1, double tau1_1, double tau2_1, double norm_2, double tau1_2, double tau2_2, double norm_3, double tau1_3, double tau2_3, double norm_4, double tau1_4, double tau2_4, double dt, bool a_drawAllExp=true, bool a_drawResidPlot=false)
void	drawAnanyaQuadWFTest (int a_evNum, double norm_1, double tau1_1, double tau2_1, double norm_2, double tau1_2, double tau2_2, double norm_3, double tau1_3, double tau2_3, double norm_4, double tau1_4, double tau2_4, double dt, bool a_drawAllExp=true)
void	drawAnanyaErfQuadWFTest (string a_WFFile, string a_WFName, double norm_1, double tau1_1, double tau2_1, double norm_2, double tau1_2, double tau2_2, double norm_3, double tau1_3, double tau2_3, double norm_4, double tau1_4, double tau2_4, double dt, bool a_drawAllExp=true)
TTree *	AnanyaWFTest (std::string a_outFileName, int a_numWF)
	This runs wf fitting with AnanyaFitFunc. More...
void	drawSingleQuadFitResult (std::string a_fitResultFile, std::string a_fitTreeName, int a_evNum)
void	drawSingleTriFitResults (TTree *a_fitResultTree, int a_wfNum)
TF1 *	loadAnanyaFitFunc ()
TF1 *	loadAnanyaQuadFitFunc ()
TF1 *	loadAnanyaQuadStatFitFunc ()
TF1 *	loadAnanyaErfQuadFitFunc ()
void	compareFitResults (std::string a_fitResultFile1, std::string a_fitResultFile2, std::string a_fitTreeName1, std::string a_fitTreeName2)
void	compareFitResults (std::string a_fitResultFile1, std::string a_fitResultFile2, std::string a_fitResultFile3, std::string a_fitTreeName1="fitTreeResults", std::string a_fitTreeName2="fitTreeResults", std::string a_fitTreeName3="fitTreeResults")
TH2 *	developWFStatGraphs (std::string a_outFile="wfStatGraphs.root", bool a_drawGraphs=false, double a_baseline=-1., double a_startSampleOffset=5)
TH2 *	genWFHist (bool a_drawGraphs=false, double a_baseline=-1., double a_startSampleOffset=5, std::string a_fileName="wfStats.root")
vector< double >	smoothWF (int a_evNum, int a_windowSize, int a_replace, int a_draw=1)
TGraph *	testSmoothing (int a_evNum, int a_windowSize, int a_iterations)
	does smoothing actually work? More...
vector< double >	getWFVec (int a_evNum, int a_range=0, int a_draw=1)
vector< std::complex< double > >	getWfFFT (vector< double > a_wfSeq)
unsigned long	upper_power_of_two (unsigned long v)
void	plotFFT (vector< std::complex< double >> &a_fHat)
void	doSingleFFT (int a_evNum, int a_range=0, int a_smooth=0)
void	doMultiFFT (int a_numWF, int a_smooth, int a_writeToFile=0, int a_range=0)
void	compareFFTTemplates (std::string a_FFTFileName1, std::string a_FFTFileName2, int a_yProjBin)
void	testUnderThreshold (int iEv)
	some test code for working out pulse processing More...
Public Member Functions inherited from PostProcBase< TTOFEvent >
	PostProcBase ()
	defualt constructor puts class into a working state More...
virtual int	addFile (string a_filename)
virtual int	addFilesFromDirectory (string a_dir, string a_ext)
virtual int	loadEvent (int a_eventNumber)
	loads a specified event into memory More...
virtual int	fileNotLoaded ()
	tests if a file is loaded and prinst a message if not More...
virtual int	clearFileState ()
virtual std::ostream &	printState (std::ostream &a_stream=std::cout)
virtual	~PostProcBase ()
TChain *	getTrees ()
	danger danger, use this if you know what you are doing. More...

Public Attributes
std::map< string, bool >	m_cutState
std::map< string, bool >	m_cutInv

Additional Inherited Members
Protected Attributes inherited from PostProcBase< TTOFEvent >
TChain *	m_trees
	for associating the trees from files More...
string	m_treeName
	for storing the name of the tree More...
string	m_branchName
	for storing the name of the branch More...
TTOFEvent *	m_currentEvent
	for storing the current event More...
vector< string >	m_loadedFiles
	for storing a list of loaded files More...
bool	m_hasFile
	flag for wheter a file has been loaded More...

Detailed Description

this class is intended to work on TTOFEvent TTrees

Constructor & Destructor Documentation

TTOFWFFit() [1/3]

TTOFWFFit::TTOFWFFit

(

)

Nothing to do here

TTOFWFFit() [2/3]

TTOFWFFit::TTOFWFFit

(

int

a_fitFunc

)

Depends on which fit function you want to be able to access a_fitFunc = 3 --> triple bi-exp, a_fitFunc = 4 --> quad bi-exp

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TTOFWFFit() [3/3]

TTOFWFFit::TTOFWFFit

(

std::string

a_fileName

)

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Member Function Documentation

AnanyaWFTest()

TTree * TTOFWFFit::AnanyaWFTest	(	std::string	a_outFileName,
		int	a_numWF
	)

This runs wf fitting with AnanyaFitFunc.

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applyCutsToFile()

void TTOFWFFit::applyCutsToFile

(

std::string

a_outFileName

)

function to apply cuts to data in tree

looping over data and saving data that passes cuts

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compareFFTTemplates()

void TTOFWFFit::compareFFTTemplates	(	std::string	a_FFTFileName1,
		std::string	a_FFTFileName2,
		int	a_yProjBin
	)

It needs two .root files with TH2 called "FFTTemplate" --> made to use after calling do MultiFFT If you have called doMultiFFT w/ a_writeToFile=1, then give it the file names and the bin # who's y-Proj you want to see

compareFitResults() [1/2]

void TTOFWFFit::compareFitResults	(	std::string	a_fitResultFile1,
		std::string	a_fitResultFile2,
		std::string	a_fitResultFile3,
		std::string	a_fitTreeName1 = "fitTreeResults",
		std::string	a_fitTreeName2 = "fitTreeResults",
		std::string	a_fitTreeName3 = "fitTreeResults"
	)

compareFitResults() [2/2]

void TTOFWFFit::compareFitResults	(	std::string	a_fitResultFile1,
		std::string	a_fitResultFile2,
		std::string	a_fitTreeName1,
		std::string	a_fitTreeName2
	)

developWFStatGraphs()

TH2 * TTOFWFFit::developWFStatGraphs	(	std::string	a_outFile = "wfStatGraphs.root",
		bool	a_drawGraphs = false,
		double	a_baseline = -1.,
		double	a_startSampleOffset = 5
	)

This function assumes that you have done all the cuts you want and plots several relevant graphs Generates a 2DHist of all waveforms in File (samples on the x axis, Normalized Amplitudes on the y-axis) Generates a median waveform Generates a modal waveform Calls developWFTemplate() to get an average waveform Plots all three statistical waveforms on the same graph if a baseline is specified it is used instead of attempting to estimate it from the data

get number of samples in WF

premature optimazation is the root of all evil reserve memory to avoid memory thrashing

this should never happen given the current processing mode

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doMultiFFT()

void TTOFWFFit::doMultiFFT	(	int	a_numWF,
		int	a_smooth,
		int	a_writeToFile = 0,
		int	a_range = 0
	)

a_smooth = 0 --> no smoothing to the WF, a_smooth = 1 --> the WF will be smoothed a_writeToFile=1 --> Writes the TH2 FFT Template to a ROOT File, a_writeToFile=0 (default) does not write The meaning of a_range changes depending on a_smooth If a_smooth=0 --> a_range=the sample up to which to get the Vector Seting a_range = 0 will take the full WF If a_smooth=1 --> a_range=the number at which you want to start replacing w/ smoothed WF

!Note, the smoothing filter size is hard-coded here!!

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doSingleFFT()

void TTOFWFFit::doSingleFFT	(	int	a_evNum,
		int	a_range = 0,
		int	a_smooth = 0
	)

a_range = the sample up to which to get the Vector, Seting a_range = 0 will take the full WF

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drawAnanyaErfQuadWFTest()

void TTOFWFFit::drawAnanyaErfQuadWFTest	(	string	a_WFFile,
		string	a_WFName,
		double	norm_1,
		double	tau1_1,
		double	tau2_1,
		double	norm_2,
		double	tau1_2,
		double	tau2_2,
		double	norm_3,
		double	tau1_3,
		double	tau2_3,
		double	norm_4,
		double	tau1_4,
		double	tau2_4,
		double	dt,
		bool	a_drawAllExp = true
	)

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drawAnanyaQuadWFTest() [1/2]

void TTOFWFFit::drawAnanyaQuadWFTest	(	int	a_evNum,
		double	norm_1,
		double	tau1_1,
		double	tau2_1,
		double	norm_2,
		double	tau1_2,
		double	tau2_2,
		double	norm_3,
		double	tau1_3,
		double	tau2_3,
		double	norm_4,
		double	tau1_4,
		double	tau2_4,
		double	dt,
		bool	a_drawAllExp = true
	)

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drawAnanyaQuadWFTest() [2/2]

void TTOFWFFit::drawAnanyaQuadWFTest	(	string	a_WFFile,
		string	a_WFName,
		double	norm_1,
		double	tau1_1,
		double	tau2_1,
		double	norm_2,
		double	tau1_2,
		double	tau2_2,
		double	norm_3,
		double	tau1_3,
		double	tau2_3,
		double	norm_4,
		double	tau1_4,
		double	tau2_4,
		double	dt,
		bool	a_drawAllExp = true,
		bool	a_drawResidPlot = false
	)

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drawAnanyaWFTest()

void TTOFWFFit::drawAnanyaWFTest	(	string	a_WFFile,
		string	a_WFName,
		double	norm_1,
		double	tau1_1,
		double	tau2_1,
		double	norm_2,
		double	tau1_2,
		double	tau2_2,
		double	norm_3,
		double	tau1_3,
		double	tau2_3,
		double	dt,
		bool	a_drawAllExp = false
	)

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drawInvertedWFGraph()

void TTOFWFFit::drawInvertedWFGraph	(	int	a_evNum,
		bool	a_clearGraph = true
	)

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drawRandomInvertedWF()

void TTOFWFFit::drawRandomInvertedWF	(	int	a_rangeStart,
		int	a_rangeEnd
	)

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drawSingleQuadFitResult()

void TTOFWFFit::drawSingleQuadFitResult	(	std::string	a_fitResultFile,
		std::string	a_fitTreeName,
		int	a_evNum
	)

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drawSingleTriFitResults()

void TTOFWFFit::drawSingleTriFitResults	(	TTree *	a_fitResultTree,
		int	a_wfNum
	)

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drawWFGraph()

void TTOFWFFit::drawWFGraph	(	int	a_evNum,
		bool	a_clearGraph = true
	)

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genWFHist()

TH2 * TTOFWFFit::genWFHist	(	bool	a_drawGraphs = false,
		double	a_baseline = -1.,
		double	a_startSampleOffset = 5,
		std::string	a_fileName = "wfStats.root"
	)

this function takes the loaded waveforms and creates a TH2 of their history with the start point being the subsample interpolated result

get number of samples in WF

this should never happen given the current processing mode

using floor here so that the offset is meaningfull

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getInvertedWFTGraph()

TGraph * TTOFWFFit::getInvertedWFTGraph

(

int

a_evNum

)

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getWfFFT()

vector< std::complex< double > > TTOFWFFit::getWfFFT

(

vector< double >

a_wfSeq

)

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getWFTGraph()

TGraph * TTOFWFFit::getWFTGraph

(

int

a_evNum

)

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getWFVec()

vector< double > TTOFWFFit::getWFVec	(	int	a_evNum,
		int	a_range = 0,
		int	a_draw = 1
	)

a_evNum = event number that you want to smooth a_windowSize = the size of the square wave for smoothing a_replace = the number at which you want to start replacing w/ smoothed WF a_draw = whether to draw the three graphs or not (a=1 is draw (default), all else will not draw) If you do not want to smooth the waveform before doing the FFT, you need to call this function

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loadAnanyaErfQuadFitFunc()

TF1 * TTOFWFFit::loadAnanyaErfQuadFitFunc

(

)

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loadAnanyaFitFunc()

TF1 * TTOFWFFit::loadAnanyaFitFunc

(

)

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loadAnanyaQuadFitFunc()

TF1 * TTOFWFFit::loadAnanyaQuadFitFunc

(

)

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loadAnanyaQuadStatFitFunc()

TF1 * TTOFWFFit::loadAnanyaQuadStatFitFunc

(

)

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passesCuts()

bool TTOFWFFit::passesCuts

(

TTOFEvent *

a_event

)

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plotFFT()

void TTOFWFFit::plotFFT

(

vector< std::complex< double >> &

a_fHat

)

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readConfigFile()

void TTOFWFFit::readConfigFile

(

std::string

a_fileName

)

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readCutFile()

void TTOFWFFit::readCutFile

(

std::string

a_fileName

)

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runWFFitting()

void TTOFWFFit::runWFFitting

(

)

seperateFitsToFile()

void TTOFWFFit::seperateFitsToFile

(

std::string

a_outFileName

)

function to seperate fit data

looping over data and saving data that passes cuts

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smoothWF()

vector< double > TTOFWFFit::smoothWF	(	int	a_evNum,
		int	a_windowSize,
		int	a_replace,
		int	a_draw = 1
	)

This function applies smoothing filter to waveform (requires addFile() before) Returns a vector of the combined vector (where elements a_replace and after are smoothed) Plots a TCanvas with three different TGraphs (if a_draw=1): Original WF, smoothed waveform, and Orig wf w/anything past the set point replaced w/ smoothed WF

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testSmoothing()

TGraph * TTOFWFFit::testSmoothing	(	int	a_evNum,
		int	a_windowSize,
		int	a_iterations
	)

does smoothing actually work?

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testUnderThreshold()

void TTOFWFFit::testUnderThreshold

(

int

iEv

)

some test code for working out pulse processing

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upper_power_of_two()

unsigned long TTOFWFFit::upper_power_of_two

(

unsigned long

v

)

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Member Data Documentation

m_cutInv

std::map<string, bool> TTOFWFFit::m_cutInv

if the cut state is set and the cutInv is 0 the test is for passesCut if the cut state is set and the cutInv is 1 the test is for !passesCut

m_cutState

std::map<string, bool> TTOFWFFit::m_cutState

this map reflects the possible cuts that can be applied to the data they are inactive by default. Currenty managed cuts are targetPSDNeutron (2D cut) startPSDNeutron (2D cut) targetPSDGamma (2D cut) startPSDGamma (2D cut) minStartLight targetLight coinTOF neutronEnergy targLightVsCoinTOF (2D cut)

---

The documentation for this class was generated from the following files:

• CAENDataProcAna/TaggedTOFAna/include/TTOFWFFit.h
• CAENDataProcAna/TaggedTOFAna/src/TTOFWFFit.cpp