XTCalibrationAlgorithm Class Reference

Class to perform xt calibration for drift chamber. More...

#include <XTCalibrationAlgorithm.h>

Inheritance diagram for XTCalibrationAlgorithm:

Public Types
enum	EResult {   c_OK ,   c_Iterate ,   c_NotEnoughData ,   c_Failure ,   c_Undefined }
	The result of calibration. More...

Public Member Functions
	XTCalibrationAlgorithm ()
	Constructor.
	~XTCalibrationAlgorithm ()
	Destructor.
void	setBField (bool bfield)
	set to use BField
void	setDebug (bool debug=false)
	Run in debug or silent.
void	setMinimumNDF (double ndf)
	set minimum number of degree of freedom requirement
void	setMinimumPval (double pval)
	set minimum Prob(Chi2) requirement
void	setXtMode (unsigned short mode=c_Chebyshev)
	set xt mode, 0 is polynimial, 1 is Chebshev polynomial
void	setStoreHisto (bool storeHist=false)
	set to store histogram or not.
void	enableTextOutput (bool output=true)
	Enable text output of calibration result.
void	setOutputFileName (std::string outputname)
	output file name
void	setHistFileName (const std::string &name)
	Set name for histogram output.
void	setLRSeparate (bool lr=true)
	Set LR separate mode (default is true).
void	setThreshold (double th=0.6)
	Set threshold for the fraction of fitted results.
std::string	getPrefix () const
	Get the prefix used for getting calibration data.
bool	checkPyExpRun (PyObject *pyObj)
	Checks that a PyObject can be successfully converted to an ExpRun type.
Calibration::ExpRun	convertPyExpRun (PyObject *pyObj)
	Performs the conversion of PyObject to ExpRun.
std::string	getCollectorName () const
	Alias for prefix.
void	setPrefix (const std::string &prefix)
	Set the prefix used to identify datastore objects.
void	setInputFileNames (PyObject *inputFileNames)
	Set the input file names used for this algorithm from a Python list.
PyObject *	getInputFileNames ()
	Get the input file names used for this algorithm and pass them out as a Python list of unicode strings.
std::vector< Calibration::ExpRun >	getRunListFromAllData () const
	Get the complete list of runs from inspection of collected data.
RunRange	getRunRangeFromAllData () const
	Get the complete RunRange from inspection of collected data.
IntervalOfValidity	getIovFromAllData () const
	Get the complete IoV from inspection of collected data.
void	fillRunToInputFilesMap ()
	Fill the mapping of ExpRun -> Files.
std::string	getGranularity () const
	Get the granularity of collected data.
EResult	execute (std::vector< Calibration::ExpRun > runs={}, int iteration=0, IntervalOfValidity iov=IntervalOfValidity())
	Runs calibration over vector of runs for a given iteration.
EResult	execute (PyObject *runs, int iteration=0, IntervalOfValidity iov=IntervalOfValidity())
	Runs calibration over Python list of runs. Converts to C++ and then calls the other execute() function.
std::list< Database::DBImportQuery > &	getPayloads ()
	Get constants (in TObjects) for database update from last execution.
std::list< Database::DBImportQuery >	getPayloadValues ()
	Get constants (in TObjects) for database update from last execution but passed by VALUE.
bool	commit ()
	Submit constants from last calibration into database.
bool	commit (std::list< Database::DBImportQuery > payloads)
	Submit constants from a (potentially previous) set of payloads.
const std::string &	getDescription () const
	Get the description of the algorithm (set by developers in constructor)
bool	loadInputJson (const std::string &jsonString)
	Load the m_inputJson variable from a string (useful from Python interface). The return bool indicates success or failure.
const std::string	dumpOutputJson () const
	Dump the JSON string of the output JSON object.
const std::vector< Calibration::ExpRun >	findPayloadBoundaries (std::vector< Calibration::ExpRun > runs, int iteration=0)
	Used to discover the ExpRun boundaries that you want the Python CAF to execute on. This is optional and only used in some.
template<>
std::shared_ptr< TTree >	getObjectPtr (const std::string &name, const std::vector< Calibration::ExpRun > &requestedRuns)
	Specialization of getObjectPtr<TTree>.

Protected Member Functions
EResult	calibrate () override
	Run algo on data.
void	createHisto ()
	Create histogram for calibration.
void	write ()
	Store calibrated constand.
void	storeHisto ()
	Store histogram to file.
void	prepare ()
	Prepare the calibration of XT.
EResult	checkConvergence ()
	Check the convergence of XT fit.
void	sanitaryCheck ()
	Check if there are any wrong xt functions.
void	setInputFileNames (std::vector< std::string > inputFileNames)
	Set the input file names used for this algorithm.
virtual bool	isBoundaryRequired (const Calibration::ExpRun &)
	Given the current collector data, make a decision about whether or not this run should be the start of a payload boundary.
virtual void	boundaryFindingSetup (std::vector< Calibration::ExpRun >, int)
	If you need to make some changes to your algorithm class before 'findPayloadBoundaries' is run, make them in this function.
virtual void	boundaryFindingTearDown ()
	Put your algorithm back into a state ready for normal execution if you need to.
const std::vector< Calibration::ExpRun > &	getRunList () const
	Get the list of runs for which calibration is called.
int	getIteration () const
	Get current iteration.
std::vector< std::string >	getVecInputFileNames () const
	Get the input file names used for this algorithm as a STL vector.
template<class T >
std::shared_ptr< T >	getObjectPtr (const std::string &name, const std::vector< Calibration::ExpRun > &requestedRuns)
	Get calibration data object by name and list of runs, the Merge function will be called to generate the overall object.
template<class T >
std::shared_ptr< T >	getObjectPtr (std::string name)
	Get calibration data object (for all runs the calibration is requested for) This function will only work during or after execute() has been called once.
template<>
shared_ptr< TTree >	getObjectPtr (const string &name, const vector< ExpRun > &requestedRuns)
	We cheekily cast the TChain to TTree for the returned pointer so that the user never knows Hopefully this doesn't cause issues if people do low level stuff to the tree...
std::string	getGranularityFromData () const
	Get the granularity of collected data.
void	saveCalibration (TClonesArray *data, const std::string &name)
	Store DBArray payload with given name with default IOV.
void	saveCalibration (TClonesArray *data, const std::string &name, const IntervalOfValidity &iov)
	Store DBArray with given name and custom IOV.
void	saveCalibration (TObject *data)
	Store DB payload with default name and default IOV.
void	saveCalibration (TObject *data, const IntervalOfValidity &iov)
	Store DB payload with default name and custom IOV.
void	saveCalibration (TObject *data, const std::string &name)
	Store DB payload with given name with default IOV.
void	saveCalibration (TObject *data, const std::string &name, const IntervalOfValidity &iov)
	Store DB payload with given name and custom IOV.
void	updateDBObjPtrs (const unsigned int event, const int run, const int experiment)
	Updates any DBObjPtrs by calling update(event) for DBStore.
void	setDescription (const std::string &description)
	Set algorithm description (in constructor)
void	clearCalibrationData ()
	Clear calibration data.
Calibration::ExpRun	getAllGranularityExpRun () const
	Returns the Exp,Run pair that means 'Everything'. Currently unused.
void	resetInputJson ()
	Clears the m_inputJson member variable.
void	resetOutputJson ()
	Clears the m_outputJson member variable.
template<class T >
void	setOutputJsonValue (const std::string &key, const T &value)
	Set a key:value pair for the outputJson object, expected to used internally during calibrate()
template<class T >
const T	getOutputJsonValue (const std::string &key) const
	Get a value using a key from the JSON output object, not sure why you would want to do this.
template<class T >
const T	getInputJsonValue (const std::string &key) const
	Get an input JSON value using a key. The normal exceptions are raised when the key doesn't exist.
const nlohmann::json &	getInputJsonObject () const
	Get the entire top level JSON object. We explicitly say this must be of object type so that we might pick.
bool	inputJsonKeyExists (const std::string &key) const
	Test for a key in the input JSON object.

Protected Attributes
std::vector< Calibration::ExpRun >	m_boundaries
	When using the boundaries functionality from isBoundaryRequired, this is used to store the boundaries. It is cleared when.

Private Member Functions
std::string	getExpRunString (Calibration::ExpRun &expRun) const
	Gets the "exp.run" string repr. of (exp,run)
std::string	getFullObjectPath (const std::string &name, Calibration::ExpRun expRun) const
	constructs the full TDirectory + Key name of an object in a TFile based on its name and exprun

Private Attributes
double	m_minNdf = 5
	minimum ndf required
double	m_minPval = 0.
	minimum pvalue required
bool	m_debug = false
	run in debug or silent
bool	m_storeHisto = true
	Store histogram or not.
bool	m_LRseparate = true
	Separate LR in calibration or mix.
bool	m_bField = true
	with b field or none
double	m_threshold = 0.6
	minimal requirement for the fraction of fitted results
TProfile *	m_hProf [56][2][20][10]
	Profile xt histo.
TH2F *	m_hist2d [56][2][20][10]
	2D histo of xt
TH2F *	m_hist2dDraw [56][20][10]
	2d histo for draw
TH1F *	m_hist2d_1 [56][2][20][10]
	1D xt histo, results of slice fit
TF1 *	m_xtFunc [56][2][20][10]
	XTFunction.
double	m_xtPrior [56][2][18][7][8]
	paremeters of XT before calibration
int	m_fitStatus [56][2][20][10]
	Fit flag.
bool	m_useSliceFit = false
	Use slice fit or profile.
int	m_minEntriesRequired = 5000
	minimum number of hit per hitosgram.
int	m_nAlphaBins
	number of alpha bins
int	m_nThetaBins
	number of theta bins
int	m_xtMode = c_Chebyshev
	Mode of xt; 0 is polynomial;1 is Chebyshev.
int	m_xtModePrior
	Mode of xt before calibration; 0 is polynomial;1 is Chebyshev.
float	m_lowerAlpha [18]
	Lower boundays of alpha bins.
float	m_upperAlpha [18]
	Upper boundays of alpha bins.
float	m_iAlpha [18]
	Represented alpha in alpha bins.
float	m_lowerTheta [7]
	Lower boundays of theta bins.
float	m_upperTheta [7]
	Upper boundays of theta bins.
float	m_iTheta [7]
	Represented theta in theta bins.
double	m_par6 [56]
	boundary parameter for fitting, semi-experiment number
bool	m_textOutput = false
	output text file if true
std::string	m_outputFileName = "xt_new.dat"
	Output xt filename.
std::string	m_histName = "histXT.root"
	root file name
DBObjPtr< CDCGeometry >	m_cdcGeo
	Geometry of CDC.
std::vector< std::string >	m_inputFileNames
	List of input files to the Algorithm, will initially be user defined but then gets the wildcards expanded during execute()
std::map< Calibration::ExpRun, std::vector< std::string > >	m_runsToInputFiles
	Map of Runs to input files. Gets filled when you call getRunRangeFromAllData, gets cleared when setting input files again.
std::string	m_granularityOfData
	Granularity of input data. This only changes when the input files change so it isn't specific to an execution.
ExecutionData	m_data
	Data specific to a SINGLE execution of the algorithm. Gets reset at the beginning of execution.
std::string	m_description {""}
	Description of the algorithm.
std::string	m_prefix {""}
	The name of the TDirectory the collector objects are contained within.
nlohmann::json	m_jsonExecutionInput = nlohmann::json::object()
	Optional input JSON object used to make decisions about how to execute the algorithm code.
nlohmann::json	m_jsonExecutionOutput = nlohmann::json::object()
	Optional output JSON object that can be set during the execution by the underlying algorithm code.

Static Private Attributes
static const Calibration::ExpRun	m_allExpRun = make_pair(-1, -1)
	allExpRun

Detailed Description

Class to perform xt calibration for drift chamber.

Definition at line 51 of file XTCalibrationAlgorithm.h.

Member Enumeration Documentation

EResult

enum EResult

inherited

The result of calibration.

Enumerator
c_OK	Finished successfully =0 in Python.
c_Iterate	Needs iteration =1 in Python.
c_NotEnoughData	Needs more data =2 in Python.
c_Failure	Failed =3 in Python.
c_Undefined	Not yet known (before execution) =4 in Python.

Definition at line 40 of file CalibrationAlgorithm.h.

                 {
      c_OK,           
      c_Iterate,      
      c_NotEnoughData,
      c_Failure,      
      c_Undefined     
    };

Constructor & Destructor Documentation

XTCalibrationAlgorithm()

XTCalibrationAlgorithm

(

)

Constructor.

Definition at line 31 of file XTCalibrationAlgorithm.cc.

                                               : CalibrationAlgorithm("CDCCalibrationCollector")
{
  setDescription(
    " -------------------------- XT Calibration Algorithm -------------------------\n"
  );
}

~XTCalibrationAlgorithm()

~XTCalibrationAlgorithm ( )

inline

Destructor.

Definition at line 57 of file XTCalibrationAlgorithm.h.

{}

Member Function Documentation

boundaryFindingSetup()

virtual void boundaryFindingSetup ( std::vector< Calibration::ExpRun >  , int    )

inlineprotectedvirtualinherited

If you need to make some changes to your algorithm class before 'findPayloadBoundaries' is run, make them in this function.

Reimplemented in TestBoundarySettingAlgorithm, TestCalibrationAlgorithm, PXDAnalyticGainCalibrationAlgorithm, PXDValidationAlgorithm, SVD3SampleCoGTimeCalibrationAlgorithm, SVD3SampleELSTimeCalibrationAlgorithm, and SVDCoGTimeCalibrationAlgorithm.

Definition at line 252 of file CalibrationAlgorithm.h.

{};

boundaryFindingTearDown()

virtual void boundaryFindingTearDown ( )

inlineprotectedvirtualinherited

Put your algorithm back into a state ready for normal execution if you need to.

Definition at line 257 of file CalibrationAlgorithm.h.

{};

calibrate()

CalibrationAlgorithm::EResult calibrate ( )

overrideprotectedvirtual

Run algo on data.

Implements CalibrationAlgorithm.

Definition at line 129 of file XTCalibrationAlgorithm.cc.

{
  gROOT->SetBatch(1);
  gPrintViaErrorHandler = true; // Suppress huge log output from TMinuit
  gErrorIgnoreLevel = 3001;
  B2INFO("Start calibration");
 
 
  const auto exprun = getRunList()[0];
  B2INFO("ExpRun used for DB Geometry : " << exprun.first << " " << exprun.second);
  updateDBObjPtrs(1, exprun.second, exprun.first);
  B2INFO("Creating CDCGeometryPar object");
  CDC::CDCGeometryPar::Instance(&(*m_cdcGeo));
 
  prepare();
  createHisto();
 
  B2INFO("Start Fitting");
  std::unique_ptr<XTFunction> xt;
  for (int l = 0; l < 56; ++l) {
    for (int lr = 0; lr < 2; ++lr) {
      for (int al = 0; al < m_nAlphaBins; ++al) {
        for (int th = 0; th < m_nThetaBins; ++th) {
          if (m_hist2d[l][lr][al][th]->GetEntries() < m_minEntriesRequired) {
            m_fitStatus[l][lr][al][th] = FitStatus::c_lowStat;
            continue;
          }
          double p0, p1, tmin;
          TF1* fpol1;
          if (m_useSliceFit) {
            m_hist2d[l][lr][al][th]->FitSlicesY(0, 0, -1, 5);
            m_hist2d_1[l][lr][al][th] = (TH1F*)gDirectory->Get(Form("h%d_%d_%d_%d_1", l, lr, al, th));
            if (!m_hist2d_1[l][lr][al][th]) {
              m_fitStatus[l][lr][al][th] = FitStatus::c_lowStat;
              B2WARNING("Error, not found results of slices fit");
              continue;
            }
            m_hist2d_1[l][lr][al][th]->Fit("pol1", "Q", "", 30, 60);
            fpol1 = (TF1*)m_hProf[l][lr][al][th]->GetFunction("pol1");
          } else {
            /*Set Error for low statistic bin*/
            for (int n = 0; n < m_hProf[l][lr][al][th]->GetNbinsX(); ++n) {
              if (m_hProf[l][lr][al][th]->GetBinEntries(n) < 5 && m_hProf[l][lr][al][th]->GetBinEntries(n) > 1) {
                m_hProf[l][lr][al][th]->SetBinError(n, 0.3 / m_hProf[l][lr][al][th]->GetBinEntries(n));
              }
            }
            m_hProf[l][lr][al][th]->Fit("pol1", "Q", "", 30, 60);
            fpol1 = (TF1*)m_hProf[l][lr][al][th]->GetFunction("pol1");
          }
 
          if (fpol1) {
            //determine tmin in fitting
            p0 = fpol1->GetParameter(0);
            p1 = fpol1->GetParameter(1);
            tmin = -1 * p0 / p1 + 15;
          } else {
            p0 = 0;
            p1 = 0.005;
            tmin = 12;
          }
 
          // B2INFO("layer " << l << ", lr " << lr << ", alpha "  << m_iAlpha[al] << ", theta " <<  m_iTheta[th]);
          if (m_useSliceFit) { // if slice fit results exist.
            xt.reset(new XTFunction(m_hist2d_1[l][lr][al][th], m_xtMode));
          } else { // from TProfile.
            xt.reset(new XTFunction(m_hProf[l][lr][al][th], m_xtMode));
          }
 
          if (m_bField) {
            int ial_old = 0;
            int ith_old = 0;
            for (int k = 0; k < m_nAlphaBins; ++k) {
              if (m_iAlpha[al] < m_upperAlpha[k]) {
                ial_old = k;
                break;
              }
            }
            for (int j = 0; j < m_nThetaBins; ++j) {
              if (m_iTheta[th] < m_upperTheta[j]) {
                ith_old = j;
                break;
              }
            }
 
            double p6 = m_xtPrior[l][lr][ial_old][ith_old][6];
            if (p6 > 400) {
              p6 = 400;
            }
 
            if (m_xtMode == m_xtModePrior) {
              xt->setXTParams(m_xtPrior[l][lr][ial_old][ith_old]);
              xt->setP6(p6);
            } else {
              xt->setXTParams(p0, p1, 0., 0., 0., 0., p6, m_xtPrior[l][lr][ial_old][ith_old][7]);
            }
            xt->setFitRange(tmin, p6 + 100);
          } else {
            xt->setXTParams(p0, p1, 0., 0., 0., 0., m_par6[l], 0.0001);
            xt->setFitRange(tmin, m_par6[l] + 100);
          }
          xt->setDebug(m_debug);
          xt->setBField(m_bField);
          xt->fitXT();
          if (xt->isValid() == false) {
            B2WARNING("Empty xt");
            m_fitStatus[l][lr][al][th] = c_fitFailure;
            continue;
          }
          if (xt->getFitStatus() != 1) {
            B2WARNING("Fit failed");
            m_fitStatus[l][lr][al][th] = c_fitFailure;
            continue;
          }
          if (xt->validate() == true) {
            m_fitStatus[l][lr][al][th] = xt->getFitStatus();
            m_xtFunc[l][lr][al][th] = (TF1*)xt->getXTFunction();
 
            if (m_useSliceFit) {
              m_hist2d_1[l][lr][al][th] = (TH1F*)xt->getFittedHisto();
            } else {
              m_hProf[l][lr][al][th] = (TProfile*)xt->getFittedHisto();
            }
          } else {
            m_fitStatus[l][lr][al][th] = c_fitFailure;
          }
        }
      }
    }
  }
  sanitaryCheck();
  write();
  storeHisto();
  return checkConvergence();
}

checkConvergence()

CalibrationAlgorithm::EResult checkConvergence ( )

protected

Check the convergence of XT fit.

Definition at line 285 of file XTCalibrationAlgorithm.cc.

{
 
  const int nTotal = 56 * 2 * m_nAlphaBins * m_nThetaBins;
  int nFitCompleted = 0;
  for (int l = 0; l < 56; ++l) {
    for (int lr = 0; lr < 2; ++lr) {
      for (int al = 0; al < m_nAlphaBins; ++al) {
        for (int th = 0; th < m_nThetaBins; ++th) {
          if (m_fitStatus[l][lr][al][th] == FitStatus::c_OK) {
            nFitCompleted++;
          }
        }
      }
    }
  }
 
  if (static_cast<double>(nFitCompleted) / nTotal < m_threshold) {
    B2WARNING("Less than " << m_threshold * 100 << " % of XTs were fitted.");
    return c_NotEnoughData;
  }
  return c_OK;
}

checkPyExpRun()

bool checkPyExpRun ( PyObject *  pyObj )

inherited

Checks that a PyObject can be successfully converted to an ExpRun type.

Checks if the PyObject can be converted to ExpRun.

Definition at line 28 of file CalibrationAlgorithm.cc.

{
  // Is it a sequence?
  if (PySequence_Check(pyObj)) {
    Py_ssize_t nObj = PySequence_Length(pyObj);
    // Does it have 2 objects in it?
    if (nObj != 2) {
      B2DEBUG(29, "ExpRun was a Python sequence which didn't have exactly 2 entries!");
      return false;
    }
    PyObject* item1, *item2;
    item1 = PySequence_GetItem(pyObj, 0);
    item2 = PySequence_GetItem(pyObj, 1);
    // Did the GetItem work?
    if ((item1 == NULL) || (item2 == NULL)) {
      B2DEBUG(29, "A PyObject pointer was NULL in the sequence");
      return false;
    }
    // Are they longs?
    if (PyLong_Check(item1) && PyLong_Check(item2)) {
      long value1, value2;
      value1 = PyLong_AsLong(item1);
      value2 = PyLong_AsLong(item2);
      if (((value1 == -1) || (value2 == -1)) && PyErr_Occurred()) {
        B2DEBUG(29, "An error occurred while converting the PyLong to long");
        return false;
      }
    } else {
      B2DEBUG(29, "One or more of the PyObjects in the ExpRun wasn't a long");
      return false;
    }
    // Make sure to kill off the reference GetItem gave us responsibility for
    Py_DECREF(item1);
    Py_DECREF(item2);
  } else {
    B2DEBUG(29, "ExpRun was not a Python sequence.");
    return false;
  }
  return true;
}

clearCalibrationData()

void clearCalibrationData ( )

inlineprotectedinherited

Clear calibration data.

Definition at line 324 of file CalibrationAlgorithm.h.

{m_data.clearCalibrationData();}

commit() [1/2]

bool commit ( )

inherited

Submit constants from last calibration into database.

Definition at line 302 of file CalibrationAlgorithm.cc.

{
  if (getPayloads().empty())
    return false;
  list<Database::DBImportQuery> payloads = getPayloads();
  B2INFO("Committing " << payloads.size()  << " payloads to database.");
  return Database::Instance().storeData(payloads);
}

commit() [2/2]

bool commit ( std::list< Database::DBImportQuery >  payloads )

inherited

Submit constants from a (potentially previous) set of payloads.

Definition at line 311 of file CalibrationAlgorithm.cc.

{
  if (payloads.empty())
    return false;
  return Database::Instance().storeData(payloads);
}

convertPyExpRun()

ExpRun convertPyExpRun ( PyObject *  pyObj )

inherited

Performs the conversion of PyObject to ExpRun.

Converts the PyObject to an ExpRun. We've preoviously checked the object so this assumes a lot about the PyObject.

Definition at line 70 of file CalibrationAlgorithm.cc.

{
  ExpRun expRun;
  PyObject* itemExp, *itemRun;
  itemExp = PySequence_GetItem(pyObj, 0);
  itemRun = PySequence_GetItem(pyObj, 1);
  expRun.first = PyLong_AsLong(itemExp);
  Py_DECREF(itemExp);
  expRun.second = PyLong_AsLong(itemRun);
  Py_DECREF(itemRun);
  return expRun;
}

createHisto()

void createHisto ( )

protected

Create histogram for calibration.

Definition at line 38 of file XTCalibrationAlgorithm.cc.

{
 
  B2INFO("create and fill histo");
  /*Create histogram*/
  for (int i = 0; i < 56; ++i) {
    for (int lr = 0; lr < 2; ++lr) {
      for (int al = 0; al < m_nAlphaBins; ++al) {
        for (int th = 0; th < m_nThetaBins; ++th) {
          m_hProf[i][lr][al][th] = new TProfile(Form("m_hProf%d_%d_%d_%d", i, lr, al, th),
                                                Form("(L=%d)-(lr=%d)-(#alpha=%3.0f)-(#theta=%3.0f); Drift time (ns);Drift Length (cm)",
                                                     i, lr, m_iAlpha[al], m_iTheta[th]), 210, -20, 600, 0, 1.2, "i");
          m_hist2d[i][lr][al][th] = new TH2F(Form("h%d_%d_%d_%d", i, lr, al, th),
                                             Form("(L=%d)-(lr=%d)-(#alpha=%3.0f)-(#theta=%3.0f); Drift time (ns);Drift Length (cm)",
                                                  i, lr, m_iAlpha[al], m_iTheta[th]), 210, -20, 600, 110, 0, 1.2);
          if (lr == 1)
            m_hist2dDraw[i][al][th] = new TH2F(Form("h_draw%d_%d_%d", i, al, th),
                                               Form("(L=%d)-(#alpha=%3.0f)-(#theta=%3.0f); Drift time (ns);Drift Length (cm)",
                                                    i, m_iAlpha[al], m_iTheta[th]), 210, -20, 600, 220, -1.2, 1.2);
        }
      }
    }
  }
 
  /* Read data and make histo*/
 
  auto tree = getObjectPtr<TTree>("tree");
 
  UChar_t lay;
  Float_t dt;
  Float_t dx;
  Float_t Pval, alpha, theta;
  Float_t ndf;
 
  tree->SetBranchAddress("lay", &lay);
  tree->SetBranchAddress("t", &dt);
  tree->SetBranchAddress("x_u", &dx);
  tree->SetBranchAddress("alpha", &alpha);
  tree->SetBranchAddress("theta", &theta);
  tree->SetBranchAddress("Pval", &Pval);
  tree->SetBranchAddress("ndf", &ndf);
 
  /* Disable unused branch */
  std::vector<TString> list_vars = {"lay", "t", "x_u", "alpha", "theta", "Pval", "ndf"};
  tree->SetBranchStatus("*", 0);
 
  for (TString brname : list_vars) {
    tree->SetBranchStatus(brname, 1);
  }
 
 
  int al = 0;
  int th = 0;
  TStopwatch time;
  time.Start();
  const Long64_t nEntries = tree->GetEntries();
  B2INFO("Number of entries " << nEntries);
  for (Long64_t i = 0; i < nEntries; ++i) {
    tree->GetEntry(i);
 
    if (Pval < m_minPval || ndf < m_minNdf) continue;
 
    for (int k = 0; k < m_nAlphaBins; ++k) {
      if (alpha < m_upperAlpha[k]) {
        al = k;
        break;
      }
    }
    for (int j = 0; j < m_nThetaBins; ++j) {
      if (theta < m_upperTheta[j]) {
        th = j;
        break;
      }
    }
    int lr = dx > 0 ? c_Right : c_Left;
    if (m_LRseparate) {
      m_hProf[lay][lr][al][th]->Fill(dt, abs(dx));
      m_hist2d[lay][lr][al][th]->Fill(dt, abs(dx));
    } else {
      m_hProf[lay][0][al][th]->Fill(dt, abs(dx));
      m_hist2d[lay][0][al][th]->Fill(dt, abs(dx));
      m_hProf[lay][1][al][th]->Fill(dt, abs(dx));
      m_hist2d[lay][1][al][th]->Fill(dt, abs(dx));
    }
    m_hist2dDraw[lay][al][th]->Fill(dt, dx);
  }
  time.Stop();
  B2INFO("Time to fill histograms: " << time.RealTime() << "s");
  //  time.Print();
}

dumpOutputJson()

const std::string dumpOutputJson ( ) const

inlineinherited

Dump the JSON string of the output JSON object.

Definition at line 223 of file CalibrationAlgorithm.h.

{return m_jsonExecutionOutput.dump();}

enableTextOutput()

void enableTextOutput ( bool  output = true )

inline

Enable text output of calibration result.

Definition at line 78 of file XTCalibrationAlgorithm.h.

{m_textOutput = output;}

execute() [1/2]

CalibrationAlgorithm::EResult execute ( PyObject *  runs, int  iteration = 0, IntervalOfValidity  iov = IntervalOfValidity()  )

inherited

Runs calibration over Python list of runs. Converts to C++ and then calls the other execute() function.

Definition at line 83 of file CalibrationAlgorithm.cc.

{
  B2DEBUG(29, "Running execute() using Python Object as input argument");
  // Reset the execution specific data in case the algorithm was previously called
  m_data.reset();
  m_data.setIteration(iteration);
  vector<ExpRun> vecRuns;
  // Is it a list?
  if (PySequence_Check(runs)) {
    boost::python::handle<> handle(boost::python::borrowed(runs));
    boost::python::list listRuns(handle);
 
    int nList = boost::python::len(listRuns);
    for (int iList = 0; iList < nList; ++iList) {
      boost::python::object pyExpRun(listRuns[iList]);
      if (!checkPyExpRun(pyExpRun.ptr())) {
        B2ERROR("Received Python ExpRuns couldn't be converted to C++");
        m_data.setResult(c_Failure);
        return c_Failure;
      } else {
        vecRuns.push_back(convertPyExpRun(pyExpRun.ptr()));
      }
    }
  } else {
    B2ERROR("Tried to set the input runs but we didn't receive a Python sequence object (list,tuple).");
    m_data.setResult(c_Failure);
    return c_Failure;
  }
  return execute(vecRuns, iteration, iov);
}

execute() [2/2]

CalibrationAlgorithm::EResult execute ( std::vector< Calibration::ExpRun >  runs = {}, int  iteration = 0, IntervalOfValidity  iov = IntervalOfValidity()  )

inherited

Runs calibration over vector of runs for a given iteration.

You can also specify the IoV to save the database payload as. By default the Algorithm will create an IoV from your requested ExpRuns, or from the overall ExpRuns of the input data if you haven't specified ExpRuns in this function.

No checks are performed to make sure that a IoV you specify matches the data you ran over, it simply labels the IoV to commit to the database later.

Definition at line 114 of file CalibrationAlgorithm.cc.

{
  // Check if we are calling this function directly and need to reset, or through Python where it was already done.
  if (m_data.getResult() != c_Undefined) {
    m_data.reset();
    m_data.setIteration(iteration);
  }
 
  if (m_inputFileNames.empty()) {
    B2ERROR("There aren't any input files set. Please use CalibrationAlgorithm::setInputFiles()");
    m_data.setResult(c_Failure);
    return c_Failure;
  }
 
  // Did we receive runs to execute over explicitly?
  if (!(runs.empty())) {
    for (auto expRun : runs) {
      B2DEBUG(29, "ExpRun requested = (" << expRun.first << ", " << expRun.second << ")");
    }
    // We've asked explicitly for certain runs, but we should check if the data granularity is 'run'
    if (strcmp(getGranularity().c_str(), "all") == 0) {
      B2ERROR(("The data is collected with granularity=all (exp=-1,run=-1), but you seem to request calibration for specific runs."
               " We'll continue but using ALL the input data given instead of the specific runs requested."));
    }
  } else {
    // If no runs are provided, infer the runs from all collected data
    runs = getRunListFromAllData();
    // Let's check that we have some now
    if (runs.empty()) {
      B2ERROR("No collected data in input files.");
      m_data.setResult(c_Failure);
      return c_Failure;
    }
    for (auto expRun : runs) {
      B2DEBUG(29, "ExpRun requested = (" << expRun.first << ", " << expRun.second << ")");
    }
  }
 
  m_data.setRequestedRuns(runs);
  if (iov.empty()) {
    // If no user specified IoV we use the IoV from the executed run list
    iov = IntervalOfValidity(runs[0].first, runs[0].second, runs[runs.size() - 1].first, runs[runs.size() - 1].second);
  }
  m_data.setRequestedIov(iov);
  // After here, the getObject<...>(...) helpers start to work
 
  CalibrationAlgorithm::EResult result = calibrate();
  m_data.setResult(result);
  return result;
}

fillRunToInputFilesMap()

void fillRunToInputFilesMap ( )

inherited

Fill the mapping of ExpRun -> Files.

Definition at line 330 of file CalibrationAlgorithm.cc.

{
  m_runsToInputFiles.clear();
  // Save TDirectory to change back at the end
  TDirectory* dir = gDirectory;
  RunRange* runRange;
  // Construct the TDirectory name where we expect our objects to be
  string runRangeObjName(getPrefix() + "/" + RUN_RANGE_OBJ_NAME);
  for (const auto& fileName : m_inputFileNames) {
    //Open TFile to get the objects
    unique_ptr<TFile> f;
    f.reset(TFile::Open(fileName.c_str(), "READ"));
    runRange = dynamic_cast<RunRange*>(f->Get(runRangeObjName.c_str()));
    if (runRange) {
      // Insert or extend the run -> file mapping for this ExpRun
      auto expRuns = runRange->getExpRunSet();
      for (const auto& expRun : expRuns) {
        auto runFiles = m_runsToInputFiles.find(expRun);
        if (runFiles != m_runsToInputFiles.end()) {
          (runFiles->second).push_back(fileName);
        } else {
          m_runsToInputFiles.insert(std::make_pair(expRun, std::vector<std::string> {fileName}));
        }
      }
    } else {
      B2WARNING("Missing a RunRange object for file: " << fileName);
    }
  }
  dir->cd();
}

findPayloadBoundaries()

const std::vector< ExpRun > findPayloadBoundaries ( std::vector< Calibration::ExpRun >  runs, int  iteration = 0  )

inherited

Used to discover the ExpRun boundaries that you want the Python CAF to execute on. This is optional and only used in some.

Definition at line 520 of file CalibrationAlgorithm.cc.

{
  m_boundaries.clear();
  if (m_inputFileNames.empty()) {
    B2ERROR("There aren't any input files set. Please use CalibrationAlgorithm::setInputFiles()");
    return m_boundaries;
  }
  // Reset the internal execution data just in case something is hanging around
  m_data.reset();
  if (runs.empty()) {
    // Want to loop over all runs we could possibly know about
    runs = getRunListFromAllData();
  }
  // Let's check that we have some now
  if (runs.empty()) {
    B2ERROR("No collected data in input files.");
    return m_boundaries;
  }
  // In order to find run boundaries we must have collected with data granularity == 'run'
  if (strcmp(getGranularity().c_str(), "all") == 0) {
    B2ERROR("The data is collected with granularity='all' (exp=-1,run=-1), and we can't use that to find run boundaries.");
    return m_boundaries;
  }
  m_data.setIteration(iteration);
  // User defined setup function
  boundaryFindingSetup(runs, iteration);
  std::vector<ExpRun> runList;
  // Loop over run list and call derived class "isBoundaryRequired" member function
  for (auto currentRun : runs) {
    runList.push_back(currentRun);
    m_data.setRequestedRuns(runList);
    // After here, the getObject<...>(...) helpers start to work
    if (isBoundaryRequired(currentRun)) {
      m_boundaries.push_back(currentRun);
    }
    // Only want run-by-run
    runList.clear();
    // Don't want memory hanging around
    m_data.clearCalibrationData();
  }
  m_data.reset();
  boundaryFindingTearDown();
  return m_boundaries;
}

getAllGranularityExpRun()

Calibration::ExpRun getAllGranularityExpRun ( ) const

inlineprotectedinherited

Returns the Exp,Run pair that means 'Everything'. Currently unused.

Definition at line 327 of file CalibrationAlgorithm.h.

{return m_allExpRun;}

getCollectorName()

std::string getCollectorName ( ) const

inlineinherited

Alias for prefix.

For convenience and less writing, we say developers to set this to default collector module name in constructor of base class. One can however use the dublets of collector+algorithm multiple times with different settings. To bind these together correctly, the prefix has to be set the same for algo and collector. So we call the setter setPrefix rather than setModuleName or whatever. This getter will work out of the box for default cases -> return the name of module you have to add to your path to collect data for this algorithm.

Definition at line 164 of file CalibrationAlgorithm.h.

{return getPrefix();}

getDescription()

const std::string & getDescription ( ) const

inlineinherited

Get the description of the algorithm (set by developers in constructor)

Definition at line 216 of file CalibrationAlgorithm.h.

{return m_description;}

getExpRunString()

string getExpRunString ( Calibration::ExpRun &  expRun ) const

privateinherited

Gets the "exp.run" string repr. of (exp,run)

Definition at line 254 of file CalibrationAlgorithm.cc.

{
  string expRunString;
  expRunString += to_string(expRun.first);
  expRunString += ".";
  expRunString += to_string(expRun.second);
  return expRunString;
}

getFullObjectPath()

string getFullObjectPath ( const std::string &  name, Calibration::ExpRun  expRun  ) const

privateinherited

constructs the full TDirectory + Key name of an object in a TFile based on its name and exprun

Definition at line 263 of file CalibrationAlgorithm.cc.

{
  string dirName = getPrefix() + "/" + name;
  string objName = name + "_" + getExpRunString(expRun);
  return dirName + "/" + objName;
}

getGranularity()

std::string getGranularity ( ) const

inlineinherited

Get the granularity of collected data.

Definition at line 188 of file CalibrationAlgorithm.h.

{return m_granularityOfData;};

getGranularityFromData()

string getGranularityFromData ( ) const

protectedinherited

Get the granularity of collected data.

Definition at line 383 of file CalibrationAlgorithm.cc.

{
  // Save TDirectory to change back at the end
  TDirectory* dir = gDirectory;
  RunRange* runRange;
  string runRangeObjName(getPrefix() + "/" + RUN_RANGE_OBJ_NAME);
  // We only check the first file
  string fileName = m_inputFileNames[0];
  unique_ptr<TFile> f;
  f.reset(TFile::Open(fileName.c_str(), "READ"));
  runRange = dynamic_cast<RunRange*>(f->Get(runRangeObjName.c_str()));
  if (!runRange) {
    B2FATAL("The input file " << fileName << " does not contain a RunRange object at "
            << runRangeObjName << ". Please set your input files to exclude it.");
    return "";
  }
  string granularity = runRange->getGranularity();
  dir->cd();
  return granularity;
}

getInputFileNames()

PyObject * getInputFileNames ( )

inherited

Get the input file names used for this algorithm and pass them out as a Python list of unicode strings.

Definition at line 245 of file CalibrationAlgorithm.cc.

{
  PyObject* objInputFileNames = PyList_New(m_inputFileNames.size());
  for (size_t i = 0; i < m_inputFileNames.size(); ++i) {
    PyList_SetItem(objInputFileNames, i, Py_BuildValue("s", m_inputFileNames[i].c_str()));
  }
  return objInputFileNames;
}

getInputJsonObject()

const nlohmann::json & getInputJsonObject ( ) const

inlineprotectedinherited

Get the entire top level JSON object. We explicitly say this must be of object type so that we might pick.

Definition at line 357 of file CalibrationAlgorithm.h.

{return m_jsonExecutionInput;}

getInputJsonValue()

const T getInputJsonValue ( const std::string &  key ) const

inlineprotectedinherited

Get an input JSON value using a key. The normal exceptions are raised when the key doesn't exist.

Definition at line 350 of file CalibrationAlgorithm.h.

    {
      return m_jsonExecutionInput.at(key);
    }

getIovFromAllData()

IntervalOfValidity getIovFromAllData ( ) const

inherited

Get the complete IoV from inspection of collected data.

Definition at line 325 of file CalibrationAlgorithm.cc.

{
  return getRunRangeFromAllData().getIntervalOfValidity();
}

getIteration()

int getIteration ( ) const

inlineprotectedinherited

Get current iteration.

Definition at line 269 of file CalibrationAlgorithm.h.

{ return m_data.getIteration(); }

getObjectPtr()

std::shared_ptr< T > getObjectPtr ( std::string  name )

inlineprotectedinherited

Get calibration data object (for all runs the calibration is requested for) This function will only work during or after execute() has been called once.

Definition at line 285 of file CalibrationAlgorithm.h.

    {
      if (m_runsToInputFiles.size() == 0)
        fillRunToInputFilesMap();
      return getObjectPtr<T>(name, m_data.getRequestedRuns());
    }

getOutputJsonValue()

const T getOutputJsonValue ( const std::string &  key ) const

inlineprotectedinherited

Get a value using a key from the JSON output object, not sure why you would want to do this.

Definition at line 342 of file CalibrationAlgorithm.h.

    {
      return m_jsonExecutionOutput.at(key);
    }

getPayloads()

std::list< Database::DBImportQuery > & getPayloads ( )

inlineinherited

Get constants (in TObjects) for database update from last execution.

Definition at line 204 of file CalibrationAlgorithm.h.

{return m_data.getPayloads();}

getPayloadValues()

std::list< Database::DBImportQuery > getPayloadValues ( )

inlineinherited

Get constants (in TObjects) for database update from last execution but passed by VALUE.

Definition at line 207 of file CalibrationAlgorithm.h.

{return m_data.getPayloadValues();}

getPrefix()

std::string getPrefix ( ) const

inlineinherited

Get the prefix used for getting calibration data.

Definition at line 146 of file CalibrationAlgorithm.h.

{return m_prefix;}

getRunList()

const std::vector< Calibration::ExpRun > & getRunList ( ) const

inlineprotectedinherited

Get the list of runs for which calibration is called.

Definition at line 266 of file CalibrationAlgorithm.h.

{return m_data.getRequestedRuns();}

getRunListFromAllData()

vector< ExpRun > getRunListFromAllData ( ) const

inherited

Get the complete list of runs from inspection of collected data.

Definition at line 318 of file CalibrationAlgorithm.cc.

{
  RunRange runRange = getRunRangeFromAllData();
  set<ExpRun> expRunSet = runRange.getExpRunSet();
  return vector<ExpRun>(expRunSet.begin(), expRunSet.end());
}

getRunRangeFromAllData()

RunRange getRunRangeFromAllData ( ) const

inherited

Get the complete RunRange from inspection of collected data.

Definition at line 361 of file CalibrationAlgorithm.cc.

{
  // Save TDirectory to change back at the end
  TDirectory* dir = gDirectory;
  RunRange runRange;
  // Construct the TDirectory name where we expect our objects to be
  string runRangeObjName(getPrefix() + "/" + RUN_RANGE_OBJ_NAME);
  for (const auto& fileName : m_inputFileNames) {
    //Open TFile to get the objects
    unique_ptr<TFile> f;
    f.reset(TFile::Open(fileName.c_str(), "READ"));
    RunRange* runRangeOther = dynamic_cast<RunRange*>(f->Get(runRangeObjName.c_str()));
    if (runRangeOther) {
      runRange.merge(runRangeOther);
    } else {
      B2WARNING("Missing a RunRange object for file: " << fileName);
    }
  }
  dir->cd();
  return runRange;
}

getVecInputFileNames()

std::vector< std::string > getVecInputFileNames ( ) const

inlineprotectedinherited

Get the input file names used for this algorithm as a STL vector.

Definition at line 275 of file CalibrationAlgorithm.h.

{return m_inputFileNames;}

inputJsonKeyExists()

bool inputJsonKeyExists ( const std::string &  key ) const

inlineprotectedinherited

Test for a key in the input JSON object.

Definition at line 360 of file CalibrationAlgorithm.h.

{return m_jsonExecutionInput.count(key);}

isBoundaryRequired()

virtual bool isBoundaryRequired ( const Calibration::ExpRun &  )

inlineprotectedvirtualinherited

Given the current collector data, make a decision about whether or not this run should be the start of a payload boundary.

Reimplemented in TestBoundarySettingAlgorithm, PXDAnalyticGainCalibrationAlgorithm, PXDValidationAlgorithm, TestCalibrationAlgorithm, SVD3SampleCoGTimeCalibrationAlgorithm, SVD3SampleELSTimeCalibrationAlgorithm, and SVDCoGTimeCalibrationAlgorithm.

Definition at line 243 of file CalibrationAlgorithm.h.

    {
      B2ERROR("You didn't implement a isBoundaryRequired() member function in your CalibrationAlgorithm but you are calling it!");
      return false;
    }

loadInputJson()

bool loadInputJson ( const std::string &  jsonString )

inherited

Load the m_inputJson variable from a string (useful from Python interface). The return bool indicates success or failure.

Definition at line 502 of file CalibrationAlgorithm.cc.

{
  try {
    auto jsonInput = nlohmann::json::parse(jsonString);
    // Input string has an object (dict) as the top level object?
    if (jsonInput.is_object()) {
      m_jsonExecutionInput = jsonInput;
      return true;
    } else {
      B2ERROR("JSON input string isn't an object type i.e. not a '{}' at the top level.");
      return false;
    }
  } catch (nlohmann::json::parse_error&) {
    B2ERROR("Parsing of JSON input string failed");
    return false;
  }
}

prepare()

void prepare ( )

protected

Prepare the calibration of XT.

Definition at line 309 of file XTCalibrationAlgorithm.cc.

{
  B2INFO("Prepare calibration of XT");
  const double rad2deg = 180 / M_PI;
 
  DBObjPtr<CDCXtRelations> dbXT;
  m_nAlphaBins = dbXT->getNoOfAlphaBins();
  m_nThetaBins = dbXT->getNoOfThetaBins();
  for (unsigned short i = 0; i < m_nAlphaBins; ++i) {
    array3 alpha = dbXT->getAlphaBin(i);
    m_lowerAlpha[i] = alpha[0] * rad2deg;
    m_upperAlpha[i] = alpha[1] * rad2deg;
    m_iAlpha[i] = alpha[2] * rad2deg;
  }
 
  for (unsigned short i = 0; i < m_nThetaBins; ++i) {
    array3 theta = dbXT->getThetaBin(i);
    m_lowerTheta[i] = theta[0] * rad2deg;
    m_upperTheta[i] = theta[1] * rad2deg;
    m_iTheta[i] = theta[2] * rad2deg;
  }
 
  m_xtModePrior = dbXT->getXtParamMode();
  if (!(m_xtModePrior == c_Chebyshev || m_xtModePrior == c_Polynomial)) {
    B2FATAL("Function type before calibration is wrong " << m_xtModePrior);
  }
 
  B2INFO("Number of alpha bins " << m_nAlphaBins);
  B2INFO("Number of theta bins " << m_nThetaBins);
  B2INFO("Function type " << m_xtMode);
 
  for (unsigned short iCL = 0; iCL < 56; ++iCL) {
    for (unsigned short iLR = 0; iLR < 2; ++iLR) {
      for (unsigned short iA = 0; iA < m_nAlphaBins; ++iA) {
        for (unsigned short iT = 0; iT < m_nThetaBins; ++iT) {
          const std::vector<float> params = dbXT->getXtParams(iCL, iLR, iA, iT);
          unsigned short np = params.size();
          for (unsigned short i = 0; i < np; ++i) {
            m_xtPrior[iCL][iLR][iA][iT][i] = params[i];
          }
        }
      }
    }
  }
}

resetInputJson()

void resetInputJson ( )

inlineprotectedinherited

Clears the m_inputJson member variable.

Definition at line 330 of file CalibrationAlgorithm.h.

{m_jsonExecutionInput.clear();}

resetOutputJson()

void resetOutputJson ( )

inlineprotectedinherited

Clears the m_outputJson member variable.

Definition at line 333 of file CalibrationAlgorithm.h.

{m_jsonExecutionOutput.clear();}

sanitaryCheck()

void sanitaryCheck ( )

protected

Check if there are any wrong xt functions.

Definition at line 264 of file XTCalibrationAlgorithm.cc.

{
  const double tMax = 500; // max drift time (nsec)
  for (int l = 0; l < 56; ++l) {
    for (int lr = 0; lr < 2; ++lr) {
      for (int al = 0; al < m_nAlphaBins; ++al) {
        for (int th = 0; th < m_nThetaBins; ++th) {
          if (m_fitStatus[l][lr][al][th] == FitStatus::c_OK) {
            TF1* fun = m_xtFunc[l][lr][al][th];
            double y = fun->Eval(tMax);
            if (y < 0) {
              B2INFO("Strange XT function l " << l << " lr " << lr << " alpha " << al << " theta " << th
                     << ", replaced by initial one");
              fun->SetParameters(m_xtPrior[l][lr][al][th]);
            }
          }
        }
      }
    }
  }
}

saveCalibration() [1/6]

void saveCalibration ( TClonesArray *  data, const std::string &  name  )

protectedinherited

Store DBArray payload with given name with default IOV.

Definition at line 297 of file CalibrationAlgorithm.cc.

{
  saveCalibration(data, name, m_data.getRequestedIov());
}

saveCalibration() [2/6]

void saveCalibration ( TClonesArray *  data, const std::string &  name, const IntervalOfValidity &  iov  )

protectedinherited

Store DBArray with given name and custom IOV.

Definition at line 276 of file CalibrationAlgorithm.cc.

{
  B2DEBUG(29, "Saving calibration TClonesArray '" <<  name << "' to payloads list.");
  getPayloads().emplace_back(name, data, iov);
}

saveCalibration() [3/6]

void saveCalibration ( TObject *  data )

protectedinherited

Store DB payload with default name and default IOV.

Definition at line 287 of file CalibrationAlgorithm.cc.

{
  saveCalibration(data, DataStore::objectName(data->IsA(), ""));
}

saveCalibration() [4/6]

void saveCalibration ( TObject *  data, const IntervalOfValidity &  iov  )

protectedinherited

Store DB payload with default name and custom IOV.

Definition at line 282 of file CalibrationAlgorithm.cc.

{
  saveCalibration(data, DataStore::objectName(data->IsA(), ""), iov);
}

saveCalibration() [5/6]

void saveCalibration ( TObject *  data, const std::string &  name  )

protectedinherited

Store DB payload with given name with default IOV.

Definition at line 292 of file CalibrationAlgorithm.cc.

{
  saveCalibration(data, name, m_data.getRequestedIov());
}

saveCalibration() [6/6]

void saveCalibration ( TObject *  data, const std::string &  name, const IntervalOfValidity &  iov  )

protectedinherited

Store DB payload with given name and custom IOV.

Definition at line 270 of file CalibrationAlgorithm.cc.

{
  B2DEBUG(29, "Saving calibration TObject = '" <<  name << "' to payloads list.");
  getPayloads().emplace_back(name, data, iov);
}

setBField()

void setBField ( bool  bfield )

inline

set to use BField

Definition at line 60 of file XTCalibrationAlgorithm.h.

{m_bField = bfield;}

setDebug()

void setDebug ( bool  debug = false )

inline

Run in debug or silent.

Definition at line 63 of file XTCalibrationAlgorithm.h.

{m_debug = debug; }

setDescription()

void setDescription ( const std::string &  description )

inlineprotectedinherited

Set algorithm description (in constructor)

Definition at line 321 of file CalibrationAlgorithm.h.

{m_description = description;}

setHistFileName()

void setHistFileName ( const std::string &  name )

inline

Set name for histogram output.

Definition at line 84 of file XTCalibrationAlgorithm.h.

{m_histName = "histXT_" + name + ".root";}

setInputFileNames() [1/2]

void setInputFileNames ( PyObject *  inputFileNames )

inherited

Set the input file names used for this algorithm from a Python list.

Set the input file names used for this algorithm and resolve the wildcards.

Definition at line 166 of file CalibrationAlgorithm.cc.

{
  // The reasoning for this very 'manual' approach to extending the Python interface
  // (instead of using boost::python) is down to my fear of putting off final users with
  // complexity on their side.
  //
  // I didn't want users that inherit from this class to be forced to use boost and
  // to have to define a new python module just to use the CAF. A derived class from
  // from a boost exposed class would need to have its own boost python module definition
  // to allow access from a steering file and to the base class functions (I think).
  // I also couldn't be bothered to write a full framework to get around the issue in a similar
  // way to Module()...maybe there's an easy way.
  //
  // But this way we can allow people to continue using their ROOT implemented classes and inherit
  // easily from this one. But add in a few helper functions that work with Python objects
  // created in their steering file i.e. instead of being forced to use STL objects as input
  // to the algorithm.
  if (PyList_Check(inputFileNames)) {
    boost::python::handle<> handle(boost::python::borrowed(inputFileNames));
    boost::python::list listInputFileNames(handle);
    auto vecInputFileNames = PyObjConvUtils::convertPythonObject(listInputFileNames, vector<string>());
    setInputFileNames(vecInputFileNames);
  } else {
    B2ERROR("Tried to set the input files but we didn't receive a Python list.");
  }
}

setInputFileNames() [2/2]

void setInputFileNames ( std::vector< std::string >  inputFileNames )

protectedinherited

Set the input file names used for this algorithm.

Set the input file names used for this algorithm and resolve the wildcards.

Definition at line 194 of file CalibrationAlgorithm.cc.

{
  // A lot of code below is tweaked from RootInputModule::initialize,
  // since we're basically copying the functionality anyway.
  if (inputFileNames.empty()) {
    B2WARNING("You have called setInputFileNames() with an empty list. Did you mean to do that?");
    return;
  }
  auto tmpInputFileNames = RootIOUtilities::expandWordExpansions(inputFileNames);
 
  // We'll use a set to enforce sorted unique file paths as we check them
  set<string> setInputFileNames;
  // Check that files exist and convert to absolute paths
  for (auto path : tmpInputFileNames) {
    string fullPath = fs::absolute(path).string();
    if (fs::exists(fullPath)) {
      setInputFileNames.insert(fs::canonical(fullPath).string());
    } else {
      B2WARNING("Couldn't find the file " << path);
    }
  }
 
  if (setInputFileNames.empty()) {
    B2WARNING("No valid files specified!");
    return;
  } else {
    // Reset the run -> files map as our files are likely different
    m_runsToInputFiles.clear();
  }
 
  // Open TFile to check they can be accessed by ROOT
  TDirectory* dir = gDirectory;
  for (const string& fileName : setInputFileNames) {
    unique_ptr<TFile> f;
    try {
      f.reset(TFile::Open(fileName.c_str(), "READ"));
    } catch (logic_error&) {
      //this might happen for ~invaliduser/foo.root
      //actually undefined behaviour per standard, reported as ROOT-8490 in JIRA
    }
    if (!f || !f->IsOpen()) {
      B2FATAL("Couldn't open input file " + fileName);
    }
  }
  dir->cd();
 
  // Copy the entries of the set to a vector
  m_inputFileNames = vector<string>(setInputFileNames.begin(), setInputFileNames.end());
  m_granularityOfData = getGranularityFromData();
}

setLRSeparate()

void setLRSeparate ( bool  lr = true )

inline

Set LR separate mode (default is true).

Definition at line 87 of file XTCalibrationAlgorithm.h.

{m_LRseparate = lr;}

setMinimumNDF()

void setMinimumNDF ( double  ndf )

inline

set minimum number of degree of freedom requirement

Definition at line 66 of file XTCalibrationAlgorithm.h.

{m_minNdf = ndf;}

setMinimumPval()

void setMinimumPval ( double  pval )

inline

set minimum Prob(Chi2) requirement

Definition at line 69 of file XTCalibrationAlgorithm.h.

{m_minPval = pval;}

setOutputFileName()

void setOutputFileName ( std::string  outputname )

inline

output file name

Definition at line 81 of file XTCalibrationAlgorithm.h.

{m_outputFileName.assign(outputname);}

setOutputJsonValue()

void setOutputJsonValue ( const std::string &  key, const T &  value  )

inlineprotectedinherited

Set a key:value pair for the outputJson object, expected to used internally during calibrate()

Definition at line 337 of file CalibrationAlgorithm.h.

{m_jsonExecutionOutput[key] = value;}

setPrefix()

void setPrefix ( const std::string &  prefix )

inlineinherited

Set the prefix used to identify datastore objects.

Definition at line 167 of file CalibrationAlgorithm.h.

{m_prefix = prefix;}

setStoreHisto()

void setStoreHisto ( bool  storeHist = false )

inline

set to store histogram or not.

Definition at line 75 of file XTCalibrationAlgorithm.h.

{m_storeHisto = storeHist;}

setThreshold()

void setThreshold ( double  th = 0.6 )

inline

Set threshold for the fraction of fitted results.

Definition at line 90 of file XTCalibrationAlgorithm.h.

{m_threshold = th;}

setXtMode()

void setXtMode ( unsigned short  mode = c_Chebyshev )

inline

set xt mode, 0 is polynimial, 1 is Chebshev polynomial

Definition at line 72 of file XTCalibrationAlgorithm.h.

{m_xtMode = mode;}

storeHisto()

void storeHisto ( )

protected

Store histogram to file.

Definition at line 445 of file XTCalibrationAlgorithm.cc.

{
 
  auto hNDF =   getObjectPtr<TH1F>("hNDF");
  auto hPval =   getObjectPtr<TH1F>("hPval");
  auto hEvtT0 =   getObjectPtr<TH1F>("hEventT0");
  B2INFO("saving histograms");
  TFile* fout = new TFile(m_histName.c_str(), "RECREATE");
  TDirectory* top = gDirectory;
  //store NDF, P-val. EventT0 histogram for monitoring during calibration
  if (hNDF && hPval && hEvtT0) {
    hEvtT0->Write();
    hPval->Write();
    hNDF->Write();
  }
  // for each layer
 
  TDirectory* Direct[56];
  int nhisto = 0;
  for (int l = 0; l < 56; ++l) {
    top->cd();
    Direct[l] = gDirectory->mkdir(Form("lay_%d", l));
    Direct[l]->cd();
    for (int th = 0; th < m_nThetaBins; ++th) {
      for (int al = 0; al < m_nAlphaBins; ++al) {
        m_hist2dDraw[l][al][th]->Write();
        for (int lr = 0; lr < 2; ++lr) {
          m_hist2d[l][lr][al][th]->Write();
          if (m_fitStatus[l][lr][al][th] != 1) continue;
          if (m_useSliceFit) {
            if (m_hist2d_1[l][lr][al][th]) {
              m_hist2d_1[l][lr][al][th]->Write();
              nhisto += 1;
            }
          } else {
            m_hProf[l][lr][al][th]->Write();
            nhisto += 1;
          }
        }
      }
    }
  }
  top->cd();
 
  fout->Close();
  B2RESULT("  " << nhisto << " histograms was stored.");
}

updateDBObjPtrs()

void updateDBObjPtrs ( const unsigned int  event = 1, const int  run = 0, const int  experiment = 0  )

protectedinherited

Updates any DBObjPtrs by calling update(event) for DBStore.

Definition at line 404 of file CalibrationAlgorithm.cc.

{
  // Construct an EventMetaData object but NOT in the Datastore
  EventMetaData emd(event, run, experiment);
  // Explicitly update while avoiding registering a Datastore object
  DBStore::Instance().update(emd);
  // Also update the intra-run objects to the event at the same time (maybe unnecessary...)
  DBStore::Instance().updateEvent(event);
}

write()

void write ( )

protected

Store calibrated constand.

Definition at line 355 of file XTCalibrationAlgorithm.cc.

{
  B2INFO("write calibrated XT");
  double par[8];
 
 
  int nfitted = 0;
  int nfailure = 0;
 
  //
  // Save to the localDB
  //
 
  CDCXtRelations* xtRel = new CDCXtRelations();
  const float deg2rad = static_cast<float>(Unit::deg);
 
  for (int i = 0; i < m_nAlphaBins; ++i) {
    std::array<float, 3> alpha3 = {m_lowerAlpha[i]* deg2rad,
                                   m_upperAlpha[i]* deg2rad,
                                   m_iAlpha[i]* deg2rad
                                  };
    xtRel->setAlphaBin(alpha3);
  }
 
  for (int i = 0; i < m_nThetaBins; ++i) {
    std::array<float, 3> theta3 = {m_lowerTheta[i]* deg2rad,
                                   m_upperTheta[i]* deg2rad,
                                   m_iTheta[i]* deg2rad
                                  };
    xtRel->setThetaBin(theta3);
  }
 
  xtRel->setXtParamMode(m_xtMode);
 
  for (int th = 0; th < m_nThetaBins; ++th) {
    for (int al = 0; al < m_nAlphaBins; ++al) {
      for (int l = 0; l < 56; ++l) {
        for (int lr = 0; lr < 2; ++lr) {
          if (m_fitStatus[l][lr][al][th] != FitStatus::c_OK) {
            nfailure += 1;
            B2DEBUG(21, "fit failure status = " <<  m_fitStatus[l][lr][al][th]);
            B2DEBUG(21, "layer " << l << ", r " << lr << ", alpha "  << m_iAlpha[al] << ", theta " <<  m_iTheta[th]);
            B2DEBUG(21, "number of event: " <<  m_hProf[l][lr][al][th]->GetEntries());
            if (m_fitStatus[l][lr][al][th] != FitStatus::c_lowStat) {
              if (m_xtFunc[l][lr][al][th]) {
                B2DEBUG(21, "Probability of fit: " <<  m_xtFunc[l][lr][al][th]->GetProb());
              }
            }
            // If fit is failed
            // and mode of input xt (prior) is same as output, previous xt is used.
            if (m_xtMode == m_xtModePrior) {
              for (int i = 0; i < 8; ++i) {
                par[i] = m_xtPrior[l][lr][al][th][i];
              }
            } else {
              B2FATAL("XT mode before/after calibration is different!");
            }
 
          } else {
            if (par[1] < 0) { // if negative c1, privious xt is kept.
              for (int i = 0; i < 8; ++i) {
                par[i] = m_xtPrior[l][lr][al][th][i];
              }
            } else {
              m_xtFunc[l][lr][al][th]->GetParameters(par);
              nfitted += 1;
            }
          }
          std::vector<float> xtbuff;
          for (int i = 0; i < 8; ++i) {
            xtbuff.push_back(par[i]);
          }
          xtRel->setXtParams(l, lr, al, th, xtbuff);
        }//lr
      }//layer
    }//alpha
  }//theta
 
  if (m_textOutput == true) {
    xtRel->outputToFile(m_outputFileName);
  }
 
  saveCalibration(xtRel, "CDCXtRelations");
 
  B2RESULT("Total number of xt fit: " << m_nAlphaBins * m_nThetaBins * 2 * 56);
  B2RESULT("Successfully Fitted: " << nfitted);
  B2RESULT("Failure Fit: " << nfailure);
 
}

Member Data Documentation

m_allExpRun

const ExpRun m_allExpRun = make_pair(-1, -1)

staticprivateinherited

allExpRun

Definition at line 364 of file CalibrationAlgorithm.h.

m_bField

bool m_bField = true

private

with b field or none

Definition at line 121 of file XTCalibrationAlgorithm.h.

m_boundaries

std::vector<Calibration::ExpRun> m_boundaries

protectedinherited

When using the boundaries functionality from isBoundaryRequired, this is used to store the boundaries. It is cleared when.

Definition at line 261 of file CalibrationAlgorithm.h.

m_cdcGeo

DBObjPtr<CDCGeometry> m_cdcGeo

private

Geometry of CDC.

Definition at line 160 of file XTCalibrationAlgorithm.h.

m_data

ExecutionData m_data

privateinherited

Data specific to a SINGLE execution of the algorithm. Gets reset at the beginning of execution.

Definition at line 382 of file CalibrationAlgorithm.h.

m_debug

bool m_debug = false

private

run in debug or silent

Definition at line 118 of file XTCalibrationAlgorithm.h.

m_description

std::string m_description {""}

privateinherited

Description of the algorithm.

Definition at line 385 of file CalibrationAlgorithm.h.

m_fitStatus

int m_fitStatus[56][2][20][10]

private

Fit flag.

Definition at line 132 of file XTCalibrationAlgorithm.h.

m_granularityOfData

std::string m_granularityOfData

privateinherited

Granularity of input data. This only changes when the input files change so it isn't specific to an execution.

Definition at line 379 of file CalibrationAlgorithm.h.

m_hist2d

TH2F* m_hist2d[56][2][20][10]

private

2D histo of xt

Definition at line 125 of file XTCalibrationAlgorithm.h.

m_hist2d_1

TH1F* m_hist2d_1[56][2][20][10]

private

1D xt histo, results of slice fit

Definition at line 127 of file XTCalibrationAlgorithm.h.

m_hist2dDraw

TH2F* m_hist2dDraw[56][20][10]

private

2d histo for draw

Definition at line 126 of file XTCalibrationAlgorithm.h.

m_histName

std::string m_histName = "histXT.root"

private

root file name

Definition at line 159 of file XTCalibrationAlgorithm.h.

m_hProf

TProfile* m_hProf[56][2][20][10]

private

Profile xt histo.

Definition at line 124 of file XTCalibrationAlgorithm.h.

m_iAlpha

float m_iAlpha[18]

private

Represented alpha in alpha bins.

Definition at line 141 of file XTCalibrationAlgorithm.h.

m_inputFileNames

std::vector<std::string> m_inputFileNames

privateinherited

List of input files to the Algorithm, will initially be user defined but then gets the wildcards expanded during execute()

Definition at line 373 of file CalibrationAlgorithm.h.

m_iTheta

float m_iTheta[7]

private

Represented theta in theta bins.

Definition at line 144 of file XTCalibrationAlgorithm.h.

m_jsonExecutionInput

nlohmann::json m_jsonExecutionInput = nlohmann::json::object()

privateinherited

Optional input JSON object used to make decisions about how to execute the algorithm code.

Definition at line 397 of file CalibrationAlgorithm.h.

m_jsonExecutionOutput

nlohmann::json m_jsonExecutionOutput = nlohmann::json::object()

privateinherited

Optional output JSON object that can be set during the execution by the underlying algorithm code.

Definition at line 403 of file CalibrationAlgorithm.h.

m_lowerAlpha

float m_lowerAlpha[18]

private

Lower boundays of alpha bins.

Definition at line 139 of file XTCalibrationAlgorithm.h.

m_lowerTheta

float m_lowerTheta[7]

private

Lower boundays of theta bins.

Definition at line 142 of file XTCalibrationAlgorithm.h.

m_LRseparate

bool m_LRseparate = true

private

Separate LR in calibration or mix.

Definition at line 120 of file XTCalibrationAlgorithm.h.

m_minEntriesRequired

int m_minEntriesRequired = 5000

private

minimum number of hit per hitosgram.

Definition at line 134 of file XTCalibrationAlgorithm.h.

m_minNdf

double m_minNdf = 5

private

minimum ndf required

Definition at line 116 of file XTCalibrationAlgorithm.h.

m_minPval

double m_minPval = 0.

private

minimum pvalue required

Definition at line 117 of file XTCalibrationAlgorithm.h.

m_nAlphaBins

int m_nAlphaBins

private

number of alpha bins

Definition at line 135 of file XTCalibrationAlgorithm.h.

m_nThetaBins

int m_nThetaBins

private

number of theta bins

Definition at line 136 of file XTCalibrationAlgorithm.h.

m_outputFileName

std::string m_outputFileName = "xt_new.dat"

private

Output xt filename.

Definition at line 158 of file XTCalibrationAlgorithm.h.

m_par6

double m_par6[56]

private

Initial value:

= {89, 91, 94, 99, 104, 107, 110, 117,
                           126, 144, 150, 157, 170, 180,
                           160, 167, 183, 205, 200, 194,
                           177, 189, 192, 206, 224, 234,
                           193, 206, 209, 215, 222, 239,
                           204, 212, 217, 227, 235, 240,
                           215, 222, 230, 239, 246, 253,
                           227, 232, 239, 243, 253, 258,
                           231, 243, 246, 256, 263, 300
                          }

boundary parameter for fitting, semi-experiment number

Definition at line 146 of file XTCalibrationAlgorithm.h.

m_prefix

std::string m_prefix {""}

privateinherited

The name of the TDirectory the collector objects are contained within.

Definition at line 388 of file CalibrationAlgorithm.h.

m_runsToInputFiles

std::map<Calibration::ExpRun, std::vector<std::string> > m_runsToInputFiles

privateinherited

Map of Runs to input files. Gets filled when you call getRunRangeFromAllData, gets cleared when setting input files again.

Definition at line 376 of file CalibrationAlgorithm.h.

m_storeHisto

bool m_storeHisto = true

private

Store histogram or not.

Definition at line 119 of file XTCalibrationAlgorithm.h.

m_textOutput

bool m_textOutput = false

private

output text file if true

Definition at line 157 of file XTCalibrationAlgorithm.h.

m_threshold

double m_threshold = 0.6

private

minimal requirement for the fraction of fitted results

Definition at line 122 of file XTCalibrationAlgorithm.h.

m_upperAlpha

float m_upperAlpha[18]

private

Upper boundays of alpha bins.

Definition at line 140 of file XTCalibrationAlgorithm.h.

m_upperTheta

float m_upperTheta[7]

private

Upper boundays of theta bins.

Definition at line 143 of file XTCalibrationAlgorithm.h.

m_useSliceFit

bool m_useSliceFit = false

private

Use slice fit or profile.

Definition at line 133 of file XTCalibrationAlgorithm.h.

m_xtFunc

TF1* m_xtFunc[56][2][20][10]

private

XTFunction.

Definition at line 128 of file XTCalibrationAlgorithm.h.

m_xtMode

int m_xtMode = c_Chebyshev

private

Mode of xt; 0 is polynomial;1 is Chebyshev.

Definition at line 137 of file XTCalibrationAlgorithm.h.

m_xtModePrior

int m_xtModePrior

private

Mode of xt before calibration; 0 is polynomial;1 is Chebyshev.

Definition at line 138 of file XTCalibrationAlgorithm.h.

m_xtPrior

double m_xtPrior[56][2][18][7][8]

private

paremeters of XT before calibration

Definition at line 130 of file XTCalibrationAlgorithm.h.

---

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

• cdc/calibration/include/XTCalibrationAlgorithm.h
• cdc/calibration/src/XTCalibrationAlgorithm.cc