Belle II Software development
XTCalibrationAlgorithm Class Reference

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

#include <XTCalibrationAlgorithm.h>

Inheritance diagram for XTCalibrationAlgorithm:
CalibrationAlgorithm

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::DBImportQuerygetPayloadValues ()
 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 constant.
 
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]
 parameters 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 boundaries of alpha bins.
 
float m_upperAlpha [18]
 Upper boundaries of alpha bins.
 
float m_iAlpha [18]
 Represented alpha in alpha bins.
 
float m_lowerTheta [7]
 Lower boundaries of theta bins.
 
float m_upperTheta [7]
 Upper boundaries 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< CDCGeometrym_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 52 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.

40 {
41 c_OK,
42 c_Iterate,
43 c_NotEnoughData,
44 c_Failure,
45 c_Undefined
46 };

Constructor & Destructor Documentation

◆ XTCalibrationAlgorithm()

Constructor.

Definition at line 30 of file XTCalibrationAlgorithm.cc.

30 : CalibrationAlgorithm("CDCCalibrationCollector")
31{
33 " -------------------------- XT Calibration Algorithm -------------------------\n"
34 );
35}
void setDescription(const std::string &description)
Set algorithm description (in constructor)
CalibrationAlgorithm(const std::string &collectorModuleName)
Constructor - sets the prefix for collected objects (won't be accesses until execute(....

◆ ~XTCalibrationAlgorithm()

Destructor.

Definition at line 58 of file XTCalibrationAlgorithm.h.

58{}

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

Definition at line 252 of file CalibrationAlgorithm.h.

252{};

◆ 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.

257{};

◆ calibrate()

CalibrationAlgorithm::EResult calibrate ( )
overrideprotectedvirtual

Run algo on data.

Implements CalibrationAlgorithm.

Definition at line 128 of file XTCalibrationAlgorithm.cc.

129{
130 gROOT->SetBatch(1);
131 gPrintViaErrorHandler = true; // Suppress huge log output from TMinuit
132 gErrorIgnoreLevel = 3001;
133 B2INFO("Start calibration");
134
135
136 const auto exprun = getRunList()[0];
137 B2INFO("ExpRun used for DB Geometry : " << exprun.first << " " << exprun.second);
138 updateDBObjPtrs(1, exprun.second, exprun.first);
139 B2INFO("Creating CDCGeometryPar object");
141
142 prepare();
143 createHisto();
144
145 B2INFO("Start Fitting");
146 std::unique_ptr<XTFunction> xt;
147 for (int l = 0; l < 56; ++l) {
148 for (int lr = 0; lr < 2; ++lr) {
149 for (int al = 0; al < m_nAlphaBins; ++al) {
150 for (int th = 0; th < m_nThetaBins; ++th) {
151 if (m_hist2d[l][lr][al][th]->GetEntries() < m_minEntriesRequired) {
152 m_fitStatus[l][lr][al][th] = FitStatus::c_lowStat;
153 continue;
154 }
155 double p0, p1, tmin;
156 TF1* fpol1;
157 if (m_useSliceFit) {
158 m_hist2d[l][lr][al][th]->FitSlicesY(0, 0, -1, 5);
159 m_hist2d_1[l][lr][al][th] = (TH1F*)gDirectory->Get(Form("h%d_%d_%d_%d_1", l, lr, al, th));
160 if (!m_hist2d_1[l][lr][al][th]) {
161 m_fitStatus[l][lr][al][th] = FitStatus::c_lowStat;
162 B2WARNING("Error, not found results of slices fit");
163 continue;
164 }
165 m_hist2d_1[l][lr][al][th]->Fit("pol1", "Q", "", 30, 60);
166 fpol1 = (TF1*)m_hProf[l][lr][al][th]->GetFunction("pol1");
167 } else {
168 /*Set Error for low statistic bin*/
169 for (int n = 0; n < m_hProf[l][lr][al][th]->GetNbinsX(); ++n) {
170 if (m_hProf[l][lr][al][th]->GetBinEntries(n) < 5 && m_hProf[l][lr][al][th]->GetBinEntries(n) > 1) {
171 m_hProf[l][lr][al][th]->SetBinError(n, 0.3 / m_hProf[l][lr][al][th]->GetBinEntries(n));
172 }
173 }
174 m_hProf[l][lr][al][th]->Fit("pol1", "Q", "", 30, 60);
175 fpol1 = (TF1*)m_hProf[l][lr][al][th]->GetFunction("pol1");
176 }
177
178 if (fpol1) {
179 //determine tmin in fitting
180 p0 = fpol1->GetParameter(0);
181 p1 = fpol1->GetParameter(1);
182 tmin = -1 * p0 / p1 + 15;
183 } else {
184 p0 = 0;
185 p1 = 0.005;
186 tmin = 12;
187 }
188
189 // B2INFO("layer " << l << ", lr " << lr << ", alpha " << m_iAlpha[al] << ", theta " << m_iTheta[th]);
190 if (m_useSliceFit) { // if slice fit results exist.
191 xt.reset(new XTFunction(m_hist2d_1[l][lr][al][th], m_xtMode));
192 } else { // from TProfile.
193 xt.reset(new XTFunction(m_hProf[l][lr][al][th], m_xtMode));
194 }
195
196 if (m_bField) {
197 int ial_old = 0;
198 int ith_old = 0;
199 for (int k = 0; k < m_nAlphaBins; ++k) {
200 if (m_iAlpha[al] < m_upperAlpha[k]) {
201 ial_old = k;
202 break;
203 }
204 }
205 for (int j = 0; j < m_nThetaBins; ++j) {
206 if (m_iTheta[th] < m_upperTheta[j]) {
207 ith_old = j;
208 break;
209 }
210 }
211
212 double p6 = m_xtPrior[l][lr][ial_old][ith_old][6];
213 if (p6 > 400) {
214 p6 = 400;
215 }
216
217 if (m_xtMode == m_xtModePrior) {
218 xt->setXTParams(m_xtPrior[l][lr][ial_old][ith_old]);
219 xt->setP6(p6);
220 } else {
221 xt->setXTParams(p0, p1, 0., 0., 0., 0., p6, m_xtPrior[l][lr][ial_old][ith_old][7]);
222 }
223 xt->setFitRange(tmin, p6 + 100);
224 } else {
225 xt->setXTParams(p0, p1, 0., 0., 0., 0., m_par6[l], 0.0001);
226 xt->setFitRange(tmin, m_par6[l] + 100);
227 }
228 xt->setDebug(m_debug);
229 xt->setBField(m_bField);
230 xt->fitXT();
231 if (xt->isValid() == false) {
232 B2WARNING("Empty xt");
233 m_fitStatus[l][lr][al][th] = c_fitFailure;
234 continue;
235 }
236 if (xt->getFitStatus() != 1) {
237 B2WARNING("Fit failed");
238 m_fitStatus[l][lr][al][th] = c_fitFailure;
239 continue;
240 }
241 if (xt->validate() == true) {
242 m_fitStatus[l][lr][al][th] = xt->getFitStatus();
243 m_xtFunc[l][lr][al][th] = (TF1*)xt->getXTFunction();
244
245 if (m_useSliceFit) {
246 m_hist2d_1[l][lr][al][th] = (TH1F*)xt->getFittedHisto();
247 } else {
248 m_hProf[l][lr][al][th] = (TProfile*)xt->getFittedHisto();
249 }
250 } else {
251 m_fitStatus[l][lr][al][th] = c_fitFailure;
252 }
253 }
254 }
255 }
256 }
258 write();
259 storeHisto();
260 return checkConvergence();
261}
static CDCGeometryPar & Instance(const CDCGeometry *=nullptr)
Static method to get a reference to the CDCGeometryPar instance.
void storeHisto()
Store histogram to file.
void prepare()
Prepare the calibration of XT.
void sanitaryCheck()
Check if there are any wrong xt functions.
double m_par6[56]
boundary parameter for fitting, semi-experiment number
double m_xtPrior[56][2][18][7][8]
parameters of XT before calibration
TF1 * m_xtFunc[56][2][20][10]
XTFunction.
void createHisto()
Create histogram for calibration.
int m_minEntriesRequired
minimum number of hit per hitosgram.
TH2F * m_hist2d[56][2][20][10]
2D histo of xt
TProfile * m_hProf[56][2][20][10]
Profile xt histo.
float m_iAlpha[18]
Represented alpha in alpha bins.
DBObjPtr< CDCGeometry > m_cdcGeo
Geometry of CDC.
bool m_useSliceFit
Use slice fit or profile.
void write()
Store calibrated constant.
float m_upperAlpha[18]
Upper boundaries of alpha bins.
EResult checkConvergence()
Check the convergence of XT fit.
int m_xtModePrior
Mode of xt before calibration; 0 is polynomial;1 is Chebyshev.
float m_upperTheta[7]
Upper boundaries of theta bins.
int m_xtMode
Mode of xt; 0 is polynomial;1 is Chebyshev.
TH1F * m_hist2d_1[56][2][20][10]
1D xt histo, results of slice fit
float m_iTheta[7]
Represented theta in theta bins.
void updateDBObjPtrs(const unsigned int event, const int run, const int experiment)
Updates any DBObjPtrs by calling update(event) for DBStore.
const std::vector< Calibration::ExpRun > & getRunList() const
Get the list of runs for which calibration is called.

◆ checkConvergence()

CalibrationAlgorithm::EResult checkConvergence ( )
protected

Check the convergence of XT fit.

Definition at line 284 of file XTCalibrationAlgorithm.cc.

285{
286
287 const int nTotal = 56 * 2 * m_nAlphaBins * m_nThetaBins;
288 int nFitCompleted = 0;
289 for (int l = 0; l < 56; ++l) {
290 for (int lr = 0; lr < 2; ++lr) {
291 for (int al = 0; al < m_nAlphaBins; ++al) {
292 for (int th = 0; th < m_nThetaBins; ++th) {
293 if (m_fitStatus[l][lr][al][th] == FitStatus::c_OK) {
294 nFitCompleted++;
295 }
296 }
297 }
298 }
299 }
300
301 if (static_cast<double>(nFitCompleted) / nTotal < m_threshold) {
302 B2WARNING("Less than " << m_threshold * 100 << " % of XTs were fitted.");
303 return c_NotEnoughData;
304 }
305 return c_OK;
306}
double m_threshold
minimal requirement for the fraction of fitted results
@ c_OK
Finished successfully =0 in Python.
@ c_NotEnoughData
Needs more data =2 in Python.

◆ 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.

29{
30 // Is it a sequence?
31 if (PySequence_Check(pyObj)) {
32 Py_ssize_t nObj = PySequence_Length(pyObj);
33 // Does it have 2 objects in it?
34 if (nObj != 2) {
35 B2DEBUG(29, "ExpRun was a Python sequence which didn't have exactly 2 entries!");
36 return false;
37 }
38 PyObject* item1, *item2;
39 item1 = PySequence_GetItem(pyObj, 0);
40 item2 = PySequence_GetItem(pyObj, 1);
41 // Did the GetItem work?
42 if ((item1 == NULL) || (item2 == NULL)) {
43 B2DEBUG(29, "A PyObject pointer was NULL in the sequence");
44 return false;
45 }
46 // Are they longs?
47 if (PyLong_Check(item1) && PyLong_Check(item2)) {
48 long value1, value2;
49 value1 = PyLong_AsLong(item1);
50 value2 = PyLong_AsLong(item2);
51 if (((value1 == -1) || (value2 == -1)) && PyErr_Occurred()) {
52 B2DEBUG(29, "An error occurred while converting the PyLong to long");
53 return false;
54 }
55 } else {
56 B2DEBUG(29, "One or more of the PyObjects in the ExpRun wasn't a long");
57 return false;
58 }
59 // Make sure to kill off the reference GetItem gave us responsibility for
60 Py_DECREF(item1);
61 Py_DECREF(item2);
62 } else {
63 B2DEBUG(29, "ExpRun was not a Python sequence.");
64 return false;
65 }
66 return true;
67}

◆ clearCalibrationData()

void clearCalibrationData ( )
inlineprotectedinherited

Clear calibration data.

Definition at line 324 of file CalibrationAlgorithm.h.

324{m_data.clearCalibrationData();}

◆ commit() [1/2]

bool commit ( )
inherited

Submit constants from last calibration into database.

Definition at line 302 of file CalibrationAlgorithm.cc.

303{
304 if (getPayloads().empty())
305 return false;
306 list<Database::DBImportQuery> payloads = getPayloads();
307 B2INFO("Committing " << payloads.size() << " payloads to database.");
308 return Database::Instance().storeData(payloads);
309}
std::list< Database::DBImportQuery > & getPayloads()
Get constants (in TObjects) for database update from last execution.
static Database & Instance()
Instance of a singleton Database.
Definition Database.cc:41
bool storeData(const std::string &name, TObject *object, const IntervalOfValidity &iov)
Store an object in the database.
Definition Database.cc:140

◆ 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.

312{
313 if (payloads.empty())
314 return false;
315 return Database::Instance().storeData(payloads);
316}

◆ 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.

71{
72 ExpRun expRun;
73 PyObject* itemExp, *itemRun;
74 itemExp = PySequence_GetItem(pyObj, 0);
75 itemRun = PySequence_GetItem(pyObj, 1);
76 expRun.first = PyLong_AsLong(itemExp);
77 Py_DECREF(itemExp);
78 expRun.second = PyLong_AsLong(itemRun);
79 Py_DECREF(itemRun);
80 return expRun;
81}

◆ createHisto()

void createHisto ( )
protected

Create histogram for calibration.

Definition at line 37 of file XTCalibrationAlgorithm.cc.

38{
39
40 B2INFO("create and fill histo");
41 /*Create histogram*/
42 for (int i = 0; i < 56; ++i) {
43 for (int lr = 0; lr < 2; ++lr) {
44 for (int al = 0; al < m_nAlphaBins; ++al) {
45 for (int th = 0; th < m_nThetaBins; ++th) {
46 m_hProf[i][lr][al][th] = new TProfile(Form("m_hProf%d_%d_%d_%d", i, lr, al, th),
47 Form("(L=%d)-(lr=%d)-(#alpha=%3.0f)-(#theta=%3.0f); Drift time (ns);Drift Length (cm)",
48 i, lr, m_iAlpha[al], m_iTheta[th]), 210, -20, 600, 0, 1.2, "i");
49 m_hist2d[i][lr][al][th] = new TH2F(Form("h%d_%d_%d_%d", i, lr, al, th),
50 Form("(L=%d)-(lr=%d)-(#alpha=%3.0f)-(#theta=%3.0f); Drift time (ns);Drift Length (cm)",
51 i, lr, m_iAlpha[al], m_iTheta[th]), 210, -20, 600, 110, 0, 1.2);
52 if (lr == 1)
53 m_hist2dDraw[i][al][th] = new TH2F(Form("h_draw%d_%d_%d", i, al, th),
54 Form("(L=%d)-(#alpha=%3.0f)-(#theta=%3.0f); Drift time (ns);Drift Length (cm)",
55 i, m_iAlpha[al], m_iTheta[th]), 210, -20, 600, 220, -1.2, 1.2);
56 }
57 }
58 }
59 }
60
61 /* Read data and make histo*/
62
63 auto tree = getObjectPtr<TTree>("tree");
64
65 UChar_t lay;
66 Float_t dt;
67 Float_t dx;
68 Float_t Pval, alpha, theta;
69 Float_t ndf;
70
71 tree->SetBranchAddress("lay", &lay);
72 tree->SetBranchAddress("t", &dt);
73 tree->SetBranchAddress("x_u", &dx);
74 tree->SetBranchAddress("alpha", &alpha);
75 tree->SetBranchAddress("theta", &theta);
76 tree->SetBranchAddress("Pval", &Pval);
77 tree->SetBranchAddress("ndf", &ndf);
78
79 /* Disable unused branch */
80 std::vector<TString> list_vars = {"lay", "t", "x_u", "alpha", "theta", "Pval", "ndf"};
81 tree->SetBranchStatus("*", 0);
82
83 for (TString brname : list_vars) {
84 tree->SetBranchStatus(brname, 1);
85 }
86
87
88 int al = 0;
89 int th = 0;
90 TStopwatch time;
91 time.Start();
92 const Long64_t nEntries = tree->GetEntries();
93 B2INFO("Number of entries " << nEntries);
94 for (Long64_t i = 0; i < nEntries; ++i) {
95 tree->GetEntry(i);
96
97 if (Pval < m_minPval || ndf < m_minNdf) continue;
98
99 for (int k = 0; k < m_nAlphaBins; ++k) {
100 if (alpha < m_upperAlpha[k]) {
101 al = k;
102 break;
103 }
104 }
105 for (int j = 0; j < m_nThetaBins; ++j) {
106 if (theta < m_upperTheta[j]) {
107 th = j;
108 break;
109 }
110 }
111 int lr = dx > 0 ? c_Right : c_Left;
112 if (m_LRseparate) {
113 m_hProf[lay][lr][al][th]->Fill(dt, abs(dx));
114 m_hist2d[lay][lr][al][th]->Fill(dt, abs(dx));
115 } else {
116 m_hProf[lay][0][al][th]->Fill(dt, abs(dx));
117 m_hist2d[lay][0][al][th]->Fill(dt, abs(dx));
118 m_hProf[lay][1][al][th]->Fill(dt, abs(dx));
119 m_hist2d[lay][1][al][th]->Fill(dt, abs(dx));
120 }
121 m_hist2dDraw[lay][al][th]->Fill(dt, dx);
122 }
123 time.Stop();
124 B2INFO("Time to fill histograms: " << time.RealTime() << "s");
125 // time.Print();
126}
bool m_LRseparate
Separate LR in calibration or mix.
double m_minPval
minimum pvalue required
TH2F * m_hist2dDraw[56][20][10]
2d histo for draw
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 t...

◆ dumpOutputJson()

const std::string dumpOutputJson ( ) const
inlineinherited

Dump the JSON string of the output JSON object.

Definition at line 223 of file CalibrationAlgorithm.h.

223{return m_jsonExecutionOutput.dump();}

◆ enableTextOutput()

void enableTextOutput ( bool output = true)
inline

Enable text output of calibration result.

Definition at line 79 of file XTCalibrationAlgorithm.h.

79{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.

84{
85 B2DEBUG(29, "Running execute() using Python Object as input argument");
86 // Reset the execution specific data in case the algorithm was previously called
87 m_data.reset();
88 m_data.setIteration(iteration);
89 vector<ExpRun> vecRuns;
90 // Is it a list?
91 if (PySequence_Check(runs)) {
92 boost::python::handle<> handle(boost::python::borrowed(runs));
93 boost::python::list listRuns(handle);
94
95 int nList = boost::python::len(listRuns);
96 for (int iList = 0; iList < nList; ++iList) {
97 boost::python::object pyExpRun(listRuns[iList]);
98 if (!checkPyExpRun(pyExpRun.ptr())) {
99 B2ERROR("Received Python ExpRuns couldn't be converted to C++");
100 m_data.setResult(c_Failure);
101 return c_Failure;
102 } else {
103 vecRuns.push_back(convertPyExpRun(pyExpRun.ptr()));
104 }
105 }
106 } else {
107 B2ERROR("Tried to set the input runs but we didn't receive a Python sequence object (list,tuple).");
108 m_data.setResult(c_Failure);
109 return c_Failure;
110 }
111 return execute(vecRuns, iteration, iov);
112}
bool checkPyExpRun(PyObject *pyObj)
Checks that a PyObject can be successfully converted to an ExpRun type.
EResult execute(std::vector< Calibration::ExpRun > runs={}, int iteration=0, IntervalOfValidity iov=IntervalOfValidity())
Runs calibration over vector of runs for a given iteration.
Calibration::ExpRun convertPyExpRun(PyObject *pyObj)
Performs the conversion of PyObject to ExpRun.
ExecutionData m_data
Data specific to a SINGLE execution of the algorithm. Gets reset at the beginning of execution.

◆ 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.

115{
116 // Check if we are calling this function directly and need to reset, or through Python where it was already done.
117 if (m_data.getResult() != c_Undefined) {
118 m_data.reset();
119 m_data.setIteration(iteration);
120 }
121
122 if (m_inputFileNames.empty()) {
123 B2ERROR("There aren't any input files set. Please use CalibrationAlgorithm::setInputFiles()");
124 m_data.setResult(c_Failure);
125 return c_Failure;
126 }
127
128 // Did we receive runs to execute over explicitly?
129 if (!(runs.empty())) {
130 for (auto expRun : runs) {
131 B2DEBUG(29, "ExpRun requested = (" << expRun.first << ", " << expRun.second << ")");
132 }
133 // We've asked explicitly for certain runs, but we should check if the data granularity is 'run'
134 if (strcmp(getGranularity().c_str(), "all") == 0) {
135 B2ERROR(("The data is collected with granularity=all (exp=-1,run=-1), but you seem to request calibration for specific runs."
136 " We'll continue but using ALL the input data given instead of the specific runs requested."));
137 }
138 } else {
139 // If no runs are provided, infer the runs from all collected data
140 runs = getRunListFromAllData();
141 // Let's check that we have some now
142 if (runs.empty()) {
143 B2ERROR("No collected data in input files.");
144 m_data.setResult(c_Failure);
145 return c_Failure;
146 }
147 for (auto expRun : runs) {
148 B2DEBUG(29, "ExpRun requested = (" << expRun.first << ", " << expRun.second << ")");
149 }
150 }
151
152 m_data.setRequestedRuns(runs);
153 if (iov.empty()) {
154 // If no user specified IoV we use the IoV from the executed run list
155 iov = IntervalOfValidity(runs[0].first, runs[0].second, runs[runs.size() - 1].first, runs[runs.size() - 1].second);
156 }
157 m_data.setRequestedIov(iov);
158 // After here, the getObject<...>(...) helpers start to work
159
161 m_data.setResult(result);
162 return result;
163}
std::vector< Calibration::ExpRun > getRunListFromAllData() const
Get the complete list of runs from inspection of collected data.
std::vector< std::string > m_inputFileNames
List of input files to the Algorithm, will initially be user defined but then gets the wildcards expa...
EResult
The result of calibration.
@ c_Undefined
Not yet known (before execution) =4 in Python.
virtual EResult calibrate()=0
Run algo on data - pure virtual: needs to be implemented.
std::string getGranularity() const
Get the granularity of collected data.

◆ fillRunToInputFilesMap()

void fillRunToInputFilesMap ( )
inherited

Fill the mapping of ExpRun -> Files.

Definition at line 330 of file CalibrationAlgorithm.cc.

331{
332 m_runsToInputFiles.clear();
333 // Save TDirectory to change back at the end
334 TDirectory* dir = gDirectory;
335 RunRange* runRange;
336 // Construct the TDirectory name where we expect our objects to be
337 string runRangeObjName(getPrefix() + "/" + RUN_RANGE_OBJ_NAME);
338 for (const auto& fileName : m_inputFileNames) {
339 //Open TFile to get the objects
340 unique_ptr<TFile> f;
341 f.reset(TFile::Open(fileName.c_str(), "READ"));
342 runRange = dynamic_cast<RunRange*>(f->Get(runRangeObjName.c_str()));
343 if (runRange) {
344 // Insert or extend the run -> file mapping for this ExpRun
345 auto expRuns = runRange->getExpRunSet();
346 for (const auto& expRun : expRuns) {
347 auto runFiles = m_runsToInputFiles.find(expRun);
348 if (runFiles != m_runsToInputFiles.end()) {
349 (runFiles->second).push_back(fileName);
350 } else {
351 m_runsToInputFiles.insert(std::make_pair(expRun, std::vector<std::string> {fileName}));
352 }
353 }
354 } else {
355 B2WARNING("Missing a RunRange object for file: " << fileName);
356 }
357 }
358 dir->cd();
359}
std::string getPrefix() const
Get the prefix used for getting calibration data.
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 setti...
const std::set< Calibration::ExpRun > & getExpRunSet()
Get access to the stored set.
Definition RunRange.h:64

◆ 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.

521{
522 m_boundaries.clear();
523 if (m_inputFileNames.empty()) {
524 B2ERROR("There aren't any input files set. Please use CalibrationAlgorithm::setInputFiles()");
525 return m_boundaries;
526 }
527 // Reset the internal execution data just in case something is hanging around
528 m_data.reset();
529 if (runs.empty()) {
530 // Want to loop over all runs we could possibly know about
531 runs = getRunListFromAllData();
532 }
533 // Let's check that we have some now
534 if (runs.empty()) {
535 B2ERROR("No collected data in input files.");
536 return m_boundaries;
537 }
538 // In order to find run boundaries we must have collected with data granularity == 'run'
539 if (strcmp(getGranularity().c_str(), "all") == 0) {
540 B2ERROR("The data is collected with granularity='all' (exp=-1,run=-1), and we can't use that to find run boundaries.");
541 return m_boundaries;
542 }
543 m_data.setIteration(iteration);
544 // User defined setup function
545 boundaryFindingSetup(runs, iteration);
546 std::vector<ExpRun> runList;
547 // Loop over run list and call derived class "isBoundaryRequired" member function
548 for (auto currentRun : runs) {
549 runList.push_back(currentRun);
550 m_data.setRequestedRuns(runList);
551 // After here, the getObject<...>(...) helpers start to work
552 if (isBoundaryRequired(currentRun)) {
553 m_boundaries.push_back(currentRun);
554 }
555 // Only want run-by-run
556 runList.clear();
557 // Don't want memory hanging around
558 m_data.clearCalibrationData();
559 }
560 m_data.reset();
562 return m_boundaries;
563}
std::vector< Calibration::ExpRun > m_boundaries
When using the boundaries functionality from isBoundaryRequired, this is used to store the boundaries...
virtual void boundaryFindingTearDown()
Put your algorithm back into a state ready for normal execution if you need to.
virtual void boundaryFindingSetup(std::vector< Calibration::ExpRun >, int)
If you need to make some changes to your algorithm class before 'findPayloadBoundaries' is run,...
virtual bool isBoundaryRequired(const Calibration::ExpRun &)
Given the current collector data, make a decision about whether or not this run should be the start o...

◆ getAllGranularityExpRun()

Calibration::ExpRun getAllGranularityExpRun ( ) const
inlineprotectedinherited

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

Definition at line 327 of file CalibrationAlgorithm.h.

327{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.

164{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.

216{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.

255{
256 string expRunString;
257 expRunString += to_string(expRun.first);
258 expRunString += ".";
259 expRunString += to_string(expRun.second);
260 return expRunString;
261}

◆ 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.

264{
265 string dirName = getPrefix() + "/" + name;
266 string objName = name + "_" + getExpRunString(expRun);
267 return dirName + "/" + objName;
268}
std::string getExpRunString(Calibration::ExpRun &expRun) const
Gets the "exp.run" string repr. of (exp,run)

◆ getGranularity()

std::string getGranularity ( ) const
inlineinherited

Get the granularity of collected data.

Definition at line 188 of file CalibrationAlgorithm.h.

188{return m_granularityOfData;};

◆ getGranularityFromData()

string getGranularityFromData ( ) const
protectedinherited

Get the granularity of collected data.

Definition at line 383 of file CalibrationAlgorithm.cc.

384{
385 // Save TDirectory to change back at the end
386 TDirectory* dir = gDirectory;
387 RunRange* runRange;
388 string runRangeObjName(getPrefix() + "/" + RUN_RANGE_OBJ_NAME);
389 // We only check the first file
390 string fileName = m_inputFileNames[0];
391 unique_ptr<TFile> f;
392 f.reset(TFile::Open(fileName.c_str(), "READ"));
393 runRange = dynamic_cast<RunRange*>(f->Get(runRangeObjName.c_str()));
394 if (!runRange) {
395 B2FATAL("The input file " << fileName << " does not contain a RunRange object at "
396 << runRangeObjName << ". Please set your input files to exclude it.");
397 return "";
398 }
399 string granularity = runRange->getGranularity();
400 dir->cd();
401 return granularity;
402}
std::string getGranularity() const
Gets the m_granularity.
Definition RunRange.h:110

◆ 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.

246{
247 PyObject* objInputFileNames = PyList_New(m_inputFileNames.size());
248 for (size_t i = 0; i < m_inputFileNames.size(); ++i) {
249 PyList_SetItem(objInputFileNames, i, Py_BuildValue("s", m_inputFileNames[i].c_str()));
250 }
251 return objInputFileNames;
252}

◆ 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.

357{return m_jsonExecutionInput;}

◆ getInputJsonValue()

template<class T>
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.

351 {
352 return m_jsonExecutionInput.at(key);
353 }

◆ getIovFromAllData()

IntervalOfValidity getIovFromAllData ( ) const
inherited

Get the complete IoV from inspection of collected data.

Definition at line 325 of file CalibrationAlgorithm.cc.

326{
328}
RunRange getRunRangeFromAllData() const
Get the complete RunRange from inspection of collected data.
IntervalOfValidity getIntervalOfValidity()
Make IntervalOfValidity from the set, spanning all runs. Works because sets are sorted by default.
Definition RunRange.h:70

◆ getIteration()

int getIteration ( ) const
inlineprotectedinherited

Get current iteration.

Definition at line 269 of file CalibrationAlgorithm.h.

269{ return m_data.getIteration(); }

◆ getObjectPtr()

template<class T>
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.

286 {
287 if (m_runsToInputFiles.size() == 0)
288 fillRunToInputFilesMap();
289 return getObjectPtr<T>(name, m_data.getRequestedRuns());
290 }

◆ getOutputJsonValue()

template<class T>
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.

343 {
344 return m_jsonExecutionOutput.at(key);
345 }

◆ 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.

204{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.

207{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.

146{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.

266{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.

319{
320 RunRange runRange = getRunRangeFromAllData();
321 set<ExpRun> expRunSet = runRange.getExpRunSet();
322 return vector<ExpRun>(expRunSet.begin(), expRunSet.end());
323}

◆ getRunRangeFromAllData()

RunRange getRunRangeFromAllData ( ) const
inherited

Get the complete RunRange from inspection of collected data.

Definition at line 361 of file CalibrationAlgorithm.cc.

362{
363 // Save TDirectory to change back at the end
364 TDirectory* dir = gDirectory;
365 RunRange runRange;
366 // Construct the TDirectory name where we expect our objects to be
367 string runRangeObjName(getPrefix() + "/" + RUN_RANGE_OBJ_NAME);
368 for (const auto& fileName : m_inputFileNames) {
369 //Open TFile to get the objects
370 unique_ptr<TFile> f;
371 f.reset(TFile::Open(fileName.c_str(), "READ"));
372 RunRange* runRangeOther = dynamic_cast<RunRange*>(f->Get(runRangeObjName.c_str()));
373 if (runRangeOther) {
374 runRange.merge(runRangeOther);
375 } else {
376 B2WARNING("Missing a RunRange object for file: " << fileName);
377 }
378 }
379 dir->cd();
380 return runRange;
381}
virtual void merge(const RunRange *other)
Implementation of merging - other is added to the set (union)
Definition RunRange.h:52

◆ 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.

275{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.

360{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 PXDAnalyticGainCalibrationAlgorithm, PXDValidationAlgorithm, SVD3SampleCoGTimeCalibrationAlgorithm, SVD3SampleELSTimeCalibrationAlgorithm, SVDCoGTimeCalibrationAlgorithm, TestBoundarySettingAlgorithm, and TestCalibrationAlgorithm.

Definition at line 243 of file CalibrationAlgorithm.h.

244 {
245 B2ERROR("You didn't implement a isBoundaryRequired() member function in your CalibrationAlgorithm but you are calling it!");
246 return false;
247 }

◆ 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.

503{
504 try {
505 auto jsonInput = nlohmann::json::parse(jsonString);
506 // Input string has an object (dict) as the top level object?
507 if (jsonInput.is_object()) {
508 m_jsonExecutionInput = jsonInput;
509 return true;
510 } else {
511 B2ERROR("JSON input string isn't an object type i.e. not a '{}' at the top level.");
512 return false;
513 }
514 } catch (nlohmann::json::parse_error&) {
515 B2ERROR("Parsing of JSON input string failed");
516 return false;
517 }
518}
nlohmann::json m_jsonExecutionInput
Optional input JSON object used to make decisions about how to execute the algorithm code.

◆ prepare()

void prepare ( )
protected

Prepare the calibration of XT.

Definition at line 308 of file XTCalibrationAlgorithm.cc.

309{
310 B2INFO("Prepare calibration of XT");
311 const double rad2deg = 180 / M_PI;
312
313 DBObjPtr<CDCXtRelations> dbXT;
314 m_nAlphaBins = dbXT->getNoOfAlphaBins();
315 m_nThetaBins = dbXT->getNoOfThetaBins();
316 for (unsigned short i = 0; i < m_nAlphaBins; ++i) {
317 array3 alpha = dbXT->getAlphaBin(i);
318 m_lowerAlpha[i] = alpha[0] * rad2deg;
319 m_upperAlpha[i] = alpha[1] * rad2deg;
320 m_iAlpha[i] = alpha[2] * rad2deg;
321 }
322
323 for (unsigned short i = 0; i < m_nThetaBins; ++i) {
324 array3 theta = dbXT->getThetaBin(i);
325 m_lowerTheta[i] = theta[0] * rad2deg;
326 m_upperTheta[i] = theta[1] * rad2deg;
327 m_iTheta[i] = theta[2] * rad2deg;
328 }
329
330 m_xtModePrior = dbXT->getXtParamMode();
331 if (!(m_xtModePrior == c_Chebyshev || m_xtModePrior == c_Polynomial)) {
332 B2FATAL("Function type before calibration is wrong " << m_xtModePrior);
333 }
334
335 B2INFO("Number of alpha bins " << m_nAlphaBins);
336 B2INFO("Number of theta bins " << m_nThetaBins);
337 B2INFO("Function type " << m_xtMode);
338
339 for (unsigned short iCL = 0; iCL < 56; ++iCL) {
340 for (unsigned short iLR = 0; iLR < 2; ++iLR) {
341 for (unsigned short iA = 0; iA < m_nAlphaBins; ++iA) {
342 for (unsigned short iT = 0; iT < m_nThetaBins; ++iT) {
343 const std::vector<float> params = dbXT->getXtParams(iCL, iLR, iA, iT);
344 unsigned short np = params.size();
345 for (unsigned short i = 0; i < np; ++i) {
346 m_xtPrior[iCL][iLR][iA][iT][i] = params[i];
347 }
348 }
349 }
350 }
351 }
352}
float m_lowerTheta[7]
Lower boundaries of theta bins.
float m_lowerAlpha[18]
Lower boundaries of alpha bins.

◆ resetInputJson()

void resetInputJson ( )
inlineprotectedinherited

Clears the m_inputJson member variable.

Definition at line 330 of file CalibrationAlgorithm.h.

330{m_jsonExecutionInput.clear();}

◆ resetOutputJson()

void resetOutputJson ( )
inlineprotectedinherited

Clears the m_outputJson member variable.

Definition at line 333 of file CalibrationAlgorithm.h.

333{m_jsonExecutionOutput.clear();}

◆ sanitaryCheck()

void sanitaryCheck ( )
protected

Check if there are any wrong xt functions.

Definition at line 263 of file XTCalibrationAlgorithm.cc.

264{
265 const double tMax = 500; // max drift time (nsec)
266 for (int l = 0; l < 56; ++l) {
267 for (int lr = 0; lr < 2; ++lr) {
268 for (int al = 0; al < m_nAlphaBins; ++al) {
269 for (int th = 0; th < m_nThetaBins; ++th) {
270 if (m_fitStatus[l][lr][al][th] == FitStatus::c_OK) {
271 TF1* fun = m_xtFunc[l][lr][al][th];
272 double y = fun->Eval(tMax);
273 if (y < 0) {
274 B2INFO("Strange XT function l " << l << " lr " << lr << " alpha " << al << " theta " << th
275 << ", replaced by initial one");
276 fun->SetParameters(m_xtPrior[l][lr][al][th]);
277 }
278 }
279 }
280 }
281 }
282 }
283}

◆ 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.

298{
299 saveCalibration(data, name, m_data.getRequestedIov());
300}
void saveCalibration(TClonesArray *data, const std::string &name)
Store DBArray payload with given name with default IOV.

◆ 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.

277{
278 B2DEBUG(29, "Saving calibration TClonesArray '" << name << "' to payloads list.");
279 getPayloads().emplace_back(name, data, iov);
280}

◆ 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.

288{
289 saveCalibration(data, DataStore::objectName(data->IsA(), ""));
290}
static std::string objectName(const TClass *t, const std::string &name)
Return the storage name for an object of the given TClass and name.
Definition DataStore.cc:150

◆ 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.

283{
284 saveCalibration(data, DataStore::objectName(data->IsA(), ""), iov);
285}

◆ 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.

293{
294 saveCalibration(data, name, m_data.getRequestedIov());
295}

◆ 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.

271{
272 B2DEBUG(29, "Saving calibration TObject = '" << name << "' to payloads list.");
273 getPayloads().emplace_back(name, data, iov);
274}

◆ setBField()

void setBField ( bool bfield)
inline

set to use BField

Definition at line 61 of file XTCalibrationAlgorithm.h.

61{m_bField = bfield;}

◆ setDebug()

void setDebug ( bool debug = false)
inline

Run in debug or silent.

Definition at line 64 of file XTCalibrationAlgorithm.h.

64{m_debug = debug; }

◆ setDescription()

void setDescription ( const std::string & description)
inlineprotectedinherited

Set algorithm description (in constructor)

Definition at line 321 of file CalibrationAlgorithm.h.

321{m_description = description;}

◆ setHistFileName()

void setHistFileName ( const std::string & name)
inline

Set name for histogram output.

Definition at line 85 of file XTCalibrationAlgorithm.h.

85{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.

167{
168 // The reasoning for this very 'manual' approach to extending the Python interface
169 // (instead of using boost::python) is down to my fear of putting off final users with
170 // complexity on their side.
171 //
172 // I didn't want users that inherit from this class to be forced to use boost and
173 // to have to define a new python module just to use the CAF. A derived class from
174 // from a boost exposed class would need to have its own boost python module definition
175 // to allow access from a steering file and to the base class functions (I think).
176 // I also couldn't be bothered to write a full framework to get around the issue in a similar
177 // way to Module()...maybe there's an easy way.
178 //
179 // But this way we can allow people to continue using their ROOT implemented classes and inherit
180 // easily from this one. But add in a few helper functions that work with Python objects
181 // created in their steering file i.e. instead of being forced to use STL objects as input
182 // to the algorithm.
183 if (PyList_Check(inputFileNames)) {
184 boost::python::handle<> handle(boost::python::borrowed(inputFileNames));
185 boost::python::list listInputFileNames(handle);
186 auto vecInputFileNames = PyObjConvUtils::convertPythonObject(listInputFileNames, vector<string>());
187 setInputFileNames(vecInputFileNames);
188 } else {
189 B2ERROR("Tried to set the input files but we didn't receive a Python list.");
190 }
191}
void setInputFileNames(PyObject *inputFileNames)
Set the input file names used for this algorithm from a Python list.
Scalar convertPythonObject(const boost::python::object &pyObject, Scalar)
Convert from Python to given type.

◆ 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.

195{
196 // A lot of code below is tweaked from RootInputModule::initialize,
197 // since we're basically copying the functionality anyway.
198 if (inputFileNames.empty()) {
199 B2WARNING("You have called setInputFileNames() with an empty list. Did you mean to do that?");
200 return;
201 }
202 auto tmpInputFileNames = RootIOUtilities::expandWordExpansions(inputFileNames);
203
204 // We'll use a set to enforce sorted unique file paths as we check them
205 set<string> setInputFileNames;
206 // Check that files exist and convert to absolute paths
207 for (auto path : tmpInputFileNames) {
208 string fullPath = fs::absolute(path).string();
209 if (fs::exists(fullPath)) {
210 setInputFileNames.insert(fs::canonical(fullPath).string());
211 } else {
212 B2WARNING("Couldn't find the file " << path);
213 }
214 }
215
216 if (setInputFileNames.empty()) {
217 B2WARNING("No valid files specified!");
218 return;
219 } else {
220 // Reset the run -> files map as our files are likely different
221 m_runsToInputFiles.clear();
222 }
223
224 // Open TFile to check they can be accessed by ROOT
225 TDirectory* dir = gDirectory;
226 for (const string& fileName : setInputFileNames) {
227 unique_ptr<TFile> f;
228 try {
229 f.reset(TFile::Open(fileName.c_str(), "READ"));
230 } catch (logic_error&) {
231 //this might happen for ~invaliduser/foo.root
232 //actually undefined behaviour per standard, reported as ROOT-8490 in JIRA
233 }
234 if (!f || !f->IsOpen()) {
235 B2FATAL("Couldn't open input file " + fileName);
236 }
237 }
238 dir->cd();
239
240 // Copy the entries of the set to a vector
241 m_inputFileNames = vector<string>(setInputFileNames.begin(), setInputFileNames.end());
243}
std::string m_granularityOfData
Granularity of input data. This only changes when the input files change so it isn't specific to an e...
std::string getGranularityFromData() const
Get the granularity of collected data.
std::vector< std::string > expandWordExpansions(const std::vector< std::string > &filenames)
Performs wildcard expansion using wordexp(), returns matches.

◆ setLRSeparate()

void setLRSeparate ( bool lr = true)
inline

Set LR separate mode (default is true).

Definition at line 88 of file XTCalibrationAlgorithm.h.

88{m_LRseparate = lr;}

◆ setMinimumNDF()

void setMinimumNDF ( double ndf)
inline

set minimum number of degree of freedom requirement

Definition at line 67 of file XTCalibrationAlgorithm.h.

67{m_minNdf = ndf;}

◆ setMinimumPval()

void setMinimumPval ( double pval)
inline

set minimum Prob(Chi2) requirement

Definition at line 70 of file XTCalibrationAlgorithm.h.

70{m_minPval = pval;}

◆ setOutputFileName()

void setOutputFileName ( std::string outputname)
inline

output file name

Definition at line 82 of file XTCalibrationAlgorithm.h.

82{m_outputFileName.assign(outputname);}

◆ setOutputJsonValue()

template<class T>
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.

337{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.

167{m_prefix = prefix;}

◆ setStoreHisto()

void setStoreHisto ( bool storeHist = false)
inline

set to store histogram or not.

Definition at line 76 of file XTCalibrationAlgorithm.h.

76{m_storeHisto = storeHist;}

◆ setThreshold()

void setThreshold ( double th = 0.6)
inline

Set threshold for the fraction of fitted results.

Definition at line 91 of file XTCalibrationAlgorithm.h.

91{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 73 of file XTCalibrationAlgorithm.h.

73{m_xtMode = mode;}

◆ storeHisto()

void storeHisto ( )
protected

Store histogram to file.

Definition at line 444 of file XTCalibrationAlgorithm.cc.

445{
446
447 auto hNDF = getObjectPtr<TH1F>("hNDF");
448 auto hPval = getObjectPtr<TH1F>("hPval");
449 auto hEvtT0 = getObjectPtr<TH1F>("hEventT0");
450 B2INFO("saving histograms");
451 TFile* fout = new TFile(m_histName.c_str(), "RECREATE");
452 TDirectory* top = gDirectory;
453 //store NDF, P-val. EventT0 histogram for monitoring during calibration
454 if (hNDF && hPval && hEvtT0) {
455 hEvtT0->Write();
456 hPval->Write();
457 hNDF->Write();
458 }
459 // for each layer
460
461 TDirectory* Direct[56];
462 int nhisto = 0;
463 for (int l = 0; l < 56; ++l) {
464 top->cd();
465 Direct[l] = gDirectory->mkdir(Form("lay_%d", l));
466 Direct[l]->cd();
467 for (int th = 0; th < m_nThetaBins; ++th) {
468 for (int al = 0; al < m_nAlphaBins; ++al) {
469 m_hist2dDraw[l][al][th]->Write();
470 for (int lr = 0; lr < 2; ++lr) {
471 m_hist2d[l][lr][al][th]->Write();
472 if (m_fitStatus[l][lr][al][th] != 1) continue;
473 if (m_useSliceFit) {
474 if (m_hist2d_1[l][lr][al][th]) {
475 m_hist2d_1[l][lr][al][th]->Write();
476 nhisto += 1;
477 }
478 } else {
479 m_hProf[l][lr][al][th]->Write();
480 nhisto += 1;
481 }
482 }
483 }
484 }
485 }
486 top->cd();
487
488 fout->Close();
489 B2RESULT(" " << nhisto << " histograms was stored.");
490}

◆ 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.

405{
406 // Construct an EventMetaData object but NOT in the Datastore
407 EventMetaData emd(event, run, experiment);
408 // Explicitly update while avoiding registering a Datastore object
410 // Also update the intra-run objects to the event at the same time (maybe unnecessary...)
412}
static DBStore & Instance()
Instance of a singleton DBStore.
Definition DBStore.cc:26
void updateEvent()
Updates all intra-run dependent objects.
Definition DBStore.cc:140
void update()
Updates all objects that are outside their interval of validity.
Definition DBStore.cc:77

◆ write()

void write ( )
protected

Store calibrated constant.

Definition at line 354 of file XTCalibrationAlgorithm.cc.

355{
356 B2INFO("write calibrated XT");
357 double par[8];
358
359
360 int nfitted = 0;
361 int nfailure = 0;
362
363 //
364 // Save to the localDB
365 //
366
367 CDCXtRelations* xtRel = new CDCXtRelations();
368 const float deg2rad = static_cast<float>(Unit::deg);
369
370 for (int i = 0; i < m_nAlphaBins; ++i) {
371 std::array<float, 3> alpha3 = {m_lowerAlpha[i]* deg2rad,
372 m_upperAlpha[i]* deg2rad,
373 m_iAlpha[i]* deg2rad
374 };
375 xtRel->setAlphaBin(alpha3);
376 }
377
378 for (int i = 0; i < m_nThetaBins; ++i) {
379 std::array<float, 3> theta3 = {m_lowerTheta[i]* deg2rad,
380 m_upperTheta[i]* deg2rad,
381 m_iTheta[i]* deg2rad
382 };
383 xtRel->setThetaBin(theta3);
384 }
385
386 xtRel->setXtParamMode(m_xtMode);
387
388 for (int th = 0; th < m_nThetaBins; ++th) {
389 for (int al = 0; al < m_nAlphaBins; ++al) {
390 for (int l = 0; l < 56; ++l) {
391 for (int lr = 0; lr < 2; ++lr) {
392 if (m_fitStatus[l][lr][al][th] != FitStatus::c_OK) {
393 nfailure += 1;
394 B2DEBUG(21, "fit failure status = " << m_fitStatus[l][lr][al][th]);
395 B2DEBUG(21, "layer " << l << ", r " << lr << ", alpha " << m_iAlpha[al] << ", theta " << m_iTheta[th]);
396 B2DEBUG(21, "number of event: " << m_hProf[l][lr][al][th]->GetEntries());
397 if (m_fitStatus[l][lr][al][th] != FitStatus::c_lowStat) {
398 if (m_xtFunc[l][lr][al][th]) {
399 B2DEBUG(21, "Probability of fit: " << m_xtFunc[l][lr][al][th]->GetProb());
400 }
401 }
402 // If fit is failed
403 // and mode of input xt (prior) is same as output, previous xt is used.
404 if (m_xtMode == m_xtModePrior) {
405 for (int i = 0; i < 8; ++i) {
406 par[i] = m_xtPrior[l][lr][al][th][i];
407 }
408 } else {
409 B2FATAL("XT mode before/after calibration is different!");
410 }
411
412 } else {
413 if (par[1] < 0) { // if negative c1, previous xt is kept.
414 for (int i = 0; i < 8; ++i) {
415 par[i] = m_xtPrior[l][lr][al][th][i];
416 }
417 } else {
418 m_xtFunc[l][lr][al][th]->GetParameters(par);
419 nfitted += 1;
420 }
421 }
422 std::vector<float> xtbuff;
423 for (int i = 0; i < 8; ++i) {
424 xtbuff.push_back(par[i]);
425 }
426 xtRel->setXtParams(l, lr, al, th, xtbuff);
427 }//lr
428 }//layer
429 }//alpha
430 }//theta
431
432 if (m_textOutput == true) {
434 }
435
436 saveCalibration(xtRel, "CDCXtRelations");
437
438 B2RESULT("Total number of xt fit: " << m_nAlphaBins * m_nThetaBins * 2 * 56);
439 B2RESULT("Successfully Fitted: " << nfitted);
440 B2RESULT("Failure Fit: " << nfailure);
441
442}
void setThetaBin(const array3 &theta)
Set theta-angle bin (rad)
void outputToFile(std::string fileName) const
Output the contents in test file format.
void setXtParamMode(unsigned short mode)
Set xt parameterization mode.
void setXtParams(const XtID xtID, const std::vector< float > &params)
Set xt parameters for the specified id.
void setAlphaBin(const array3 &alpha)
Set alpha-angle bin (rad)
bool m_textOutput
output text file if true
std::string m_outputFileName
Output xt filename.
static const double deg
degree to radians
Definition Unit.h:109

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 122 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 161 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 119 of file XTCalibrationAlgorithm.h.

◆ m_description

std::string m_description {""}
privateinherited

Description of the algorithm.

Definition at line 385 of file CalibrationAlgorithm.h.

385{""};

◆ m_fitStatus

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

Fit flag.

Definition at line 133 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 126 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 128 of file XTCalibrationAlgorithm.h.

◆ m_hist2dDraw

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

2d histo for draw

Definition at line 127 of file XTCalibrationAlgorithm.h.

◆ m_histName

std::string m_histName = "histXT.root"
private

root file name

Definition at line 160 of file XTCalibrationAlgorithm.h.

◆ m_hProf

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

Profile xt histo.

Definition at line 125 of file XTCalibrationAlgorithm.h.

◆ m_iAlpha

float m_iAlpha[18]
private

Represented alpha in alpha bins.

Definition at line 142 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 145 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 boundaries of alpha bins.

Definition at line 140 of file XTCalibrationAlgorithm.h.

◆ m_lowerTheta

float m_lowerTheta[7]
private

Lower boundaries of theta bins.

Definition at line 143 of file XTCalibrationAlgorithm.h.

◆ m_LRseparate

bool m_LRseparate = true
private

Separate LR in calibration or mix.

Definition at line 121 of file XTCalibrationAlgorithm.h.

◆ m_minEntriesRequired

int m_minEntriesRequired = 5000
private

minimum number of hit per hitosgram.

Definition at line 135 of file XTCalibrationAlgorithm.h.

◆ m_minNdf

double m_minNdf = 5
private

minimum ndf required

Definition at line 117 of file XTCalibrationAlgorithm.h.

◆ m_minPval

double m_minPval = 0.
private

minimum pvalue required

Definition at line 118 of file XTCalibrationAlgorithm.h.

◆ m_nAlphaBins

int m_nAlphaBins
private

number of alpha bins

Definition at line 136 of file XTCalibrationAlgorithm.h.

◆ m_nThetaBins

int m_nThetaBins
private

number of theta bins

Definition at line 137 of file XTCalibrationAlgorithm.h.

◆ m_outputFileName

std::string m_outputFileName = "xt_new.dat"
private

Output xt filename.

Definition at line 159 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 147 of file XTCalibrationAlgorithm.h.

147 {89, 91, 94, 99, 104, 107, 110, 117,
148 126, 144, 150, 157, 170, 180,
149 160, 167, 183, 205, 200, 194,
150 177, 189, 192, 206, 224, 234,
151 193, 206, 209, 215, 222, 239,
152 204, 212, 217, 227, 235, 240,
153 215, 222, 230, 239, 246, 253,
154 227, 232, 239, 243, 253, 258,
155 231, 243, 246, 256, 263, 300
156 };

◆ 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.

388{""};

◆ 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 120 of file XTCalibrationAlgorithm.h.

◆ m_textOutput

bool m_textOutput = false
private

output text file if true

Definition at line 158 of file XTCalibrationAlgorithm.h.

◆ m_threshold

double m_threshold = 0.6
private

minimal requirement for the fraction of fitted results

Definition at line 123 of file XTCalibrationAlgorithm.h.

◆ m_upperAlpha

float m_upperAlpha[18]
private

Upper boundaries of alpha bins.

Definition at line 141 of file XTCalibrationAlgorithm.h.

◆ m_upperTheta

float m_upperTheta[7]
private

Upper boundaries of theta bins.

Definition at line 144 of file XTCalibrationAlgorithm.h.

◆ m_useSliceFit

bool m_useSliceFit = false
private

Use slice fit or profile.

Definition at line 134 of file XTCalibrationAlgorithm.h.

◆ m_xtFunc

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

XTFunction.

Definition at line 129 of file XTCalibrationAlgorithm.h.

◆ m_xtMode

int m_xtMode = c_Chebyshev
private

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

Definition at line 138 of file XTCalibrationAlgorithm.h.

◆ m_xtModePrior

int m_xtModePrior
private

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

Definition at line 139 of file XTCalibrationAlgorithm.h.

◆ m_xtPrior

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

parameters of XT before calibration

Definition at line 131 of file XTCalibrationAlgorithm.h.


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