Belle II Software development
CDCDedxCosineAlgorithm Class Reference

A calibration algorithm for CDC dE/dx electron cos(theta) dependence. More...

#include <CDCDedxCosineAlgorithm.h>

Inheritance diagram for CDCDedxCosineAlgorithm:
CalibrationAlgorithm

Public Types

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

Public Member Functions

 CDCDedxCosineAlgorithm ()
 Constructor: Sets the description, the properties and the parameters of the algorithm.
 
virtual ~CDCDedxCosineAlgorithm ()
 Destructor.
 
void setMethodSep (bool value=true)
 function to make flag active for method of sep
 
void setMergePayload (bool value=true)
 function to decide merge vs relative gains
 
void generateNewPayloads (std::vector< double > cosine)
 function to store new payload after full calibration
 
void setMonitoringPlots (bool value=false)
 function to make flag active for plotting
 
void setFitWidth (double value=2.5)
 set sigma to restrict fir range around mean
 
void FitGaussianWRange (TH1D *&temphist, TString &status)
 function to fit histogram in each cosine bin
 
void setCosineBins (unsigned int value=100)
 function to set number of cosine bins for calibration
 
void setCosineRange (double min=-1.0, double max=1.0)
 function to set number of cosine bins for calibration
 
void setHistBins (int value=600)
 function to set nbins of dedx dist calibration
 
void setHistRange (double min=0.0, double max=3.0)
 function to set min/max range of dedx dist calibration
 
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 algoithm (set by developers in constructor)
 
bool loadInputJson (const std::string &jsonString)
 Load the m_inputJson variable from a string (useful from Python interface). The rturn 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

virtual EResult calibrate () override
 Cosine algorithm.
 
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 interally 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

bool isMethodSep
 if e+e- need to be consider sep
 
bool isMakePlots
 produce plots for status
 
bool isMergePayload
 merge payload at the of calibration
 
double fSigLim
 gaussian fit sigma limit
 
unsigned int fCosbins
 number of bins across cosine range
 
double fCosMin
 min cosine angle for cal
 
double fCosMax
 max cosine angle for cal
 
int fHistbins
 number of bins for dedx histogram
 
double fdEdxMin
 min dedx range for gain cal
 
double fdEdxMax
 max dedx range for gain cal
 
int fStartRun
 boundary start at this run
 
DBObjPtr< CDCDedxCosineCorm_DBCosineCor
 Electron saturation correction DB object.
 
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

A calibration algorithm for CDC dE/dx electron cos(theta) dependence.

Definition at line 25 of file CDCDedxCosineAlgorithm.h.

Member Enumeration Documentation

◆ EResult

enum EResult
inherited

The result of calibration.

Enumerator
c_OK 

Finished successfuly =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,
44 c_Failure,
46 };
@ c_OK
Finished successfuly =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.

Constructor & Destructor Documentation

◆ CDCDedxCosineAlgorithm()

Constructor: Sets the description, the properties and the parameters of the algorithm.

Definition at line 21 of file CDCDedxCosineAlgorithm.cc.

21 :
22 CalibrationAlgorithm("CDCDedxElectronCollector"),
23 isMethodSep(true),
24 isMakePlots(true),
25 isMergePayload(true),
26 fSigLim(2.5),
27 fCosbins(100),
28 fCosMin(-1.0),
29 fCosMax(1.0),
30 fHistbins(600),
31 fdEdxMin(0.0),
32 fdEdxMax(3.0),
33 fStartRun(0)
34
35{
36 // Set module properties
37 setDescription("A calibration algorithm for CDC dE/dx electron cos(theta) dependence");
38
39}
int fStartRun
boundary start at this run
double fdEdxMax
max dedx range for gain cal
bool isMergePayload
merge payload at the of calibration
double fCosMax
max cosine angle for cal
double fCosMin
min cosine angle for cal
double fdEdxMin
min dedx range for gain cal
int fHistbins
number of bins for dedx histogram
bool isMethodSep
if e+e- need to be consider sep
unsigned int fCosbins
number of bins across cosine range
bool isMakePlots
produce plots for status
double fSigLim
gaussian fit sigma limit
Base class for calibration algorithms.
void setDescription(const std::string &description)
Set algorithm description (in constructor)

◆ ~CDCDedxCosineAlgorithm()

virtual ~CDCDedxCosineAlgorithm ( )
inlinevirtual

Destructor.

Definition at line 37 of file CDCDedxCosineAlgorithm.h.

37{}

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.

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

Cosine algorithm.

Implements CalibrationAlgorithm.

Definition at line 44 of file CDCDedxCosineAlgorithm.cc.

45{
46 B2INFO("Preparing dE/dx calibration for CDC dE/dx electron saturation");
47
48 // Get data objects
49 auto ttree = getObjectPtr<TTree>("tree");
50 if (ttree->GetEntries() < 100)return c_NotEnoughData;
51
52 double dedx, costh; int charge;
53 ttree->SetBranchAddress("dedx", &dedx);
54 ttree->SetBranchAddress("costh", &costh);
55 ttree->SetBranchAddress("charge", &charge);
56
57 const auto expRun = getRunList()[0];
58 updateDBObjPtrs(1, expRun.second, expRun.first);
59 fStartRun = expRun.second;
60
61 // make histograms to store dE/dx values in bins of cos(theta)
62 // bin size can be arbitrary, but for now just make uniform bins
63 std::vector<TH1D*> hdEdx_elCosbin(fCosbins), hdEdx_poCosbin(fCosbins), hdEdx_epCosbin(fCosbins);
64
65 const double binW = (fCosMax - fCosMin) / fCosbins;
66
67 for (unsigned int i = 0; i < fCosbins; ++i) {
68
69 double coslow = i * binW + fCosMin, coshigh = coslow + binW;
70
71 hdEdx_elCosbin[i] = new TH1D(Form("hdEdx_elCosbin%d_fRun%d", i, fStartRun), "", fHistbins, fdEdxMin, fdEdxMax);
72 hdEdx_elCosbin[i]->SetTitle(Form("dE/dx dist (e-) in costh (%0.02f, %0.02f), run start: %d", coslow, coshigh, fStartRun));
73 hdEdx_elCosbin[i]->GetXaxis()->SetTitle("dE/dx (no had sat, for e-)");
74 hdEdx_elCosbin[i]->GetYaxis()->SetTitle("Entries");
75
76 hdEdx_poCosbin[i] = new TH1D(Form("hdEdx_poCosbin%d_fRun%d", i, fStartRun), "", fHistbins, fdEdxMin, fdEdxMax);
77 hdEdx_poCosbin[i]->SetTitle(Form("dE/dx dist (e+) in costh (%0.02f, %0.02f), run start: %d", coslow, coshigh, fStartRun));
78 hdEdx_poCosbin[i]->GetXaxis()->SetTitle("dE/dx (no had sat, for e+)");
79 hdEdx_poCosbin[i]->GetYaxis()->SetTitle("Entries");
80
81 hdEdx_epCosbin[i] = new TH1D(Form("hdEdx_epCosbin%d_fRun%d", i, fStartRun), "", fHistbins, fdEdxMin, fdEdxMax);
82 hdEdx_epCosbin[i]->SetTitle(Form("dE/dx dist (e-,e+) in costh (%0.02f, %0.02f), run start: %d", coslow, coshigh, fStartRun));
83 hdEdx_epCosbin[i]->GetXaxis()->SetTitle("dE/dx (no had sat, for e-,e+)");
84 hdEdx_epCosbin[i]->GetYaxis()->SetTitle("Entries");
85 }
86
87 // fill histograms, bin size may be arbitrary
88 TH1D* hCosth_el = new TH1D(Form("hCosth_el_fRun%d", fStartRun),
89 Form("cos(#theta) dist (e- and e+), start run: %d; cos(#theta); Entries", fStartRun), fCosbins, fCosMin, fCosMax);
90 TH1D* hCosth_po = new TH1D(Form("hCosth_po_fRun%d", fStartRun), Form("cos(#theta) dist (e+), start run: %d; cos(#theta); Entries",
92 TH1D* hCosth_ep = new TH1D(Form("hCosth_ep_fRun%d", fStartRun),
93 Form("cos(#theta) dist (e- and e+), start run: %d; cos(#theta); Entries", fStartRun), fCosbins, fCosMin, fCosMax);
94
95 for (int i = 0; i < ttree->GetEntries(); ++i) {
96
97 ttree->GetEvent(i);
98
99 //if track is a junk
100 if (dedx <= 0 || charge == 0) continue;
101
102 //if track is in CDC acceptance (though it is inbuilt in collector module)
103 if (costh < TMath::Cos(150 * TMath::DegToRad()) || costh > TMath::Cos(17 * TMath::DegToRad())) continue;
104
105 int bin = int((costh - fCosMin) / binW);
106 if (bin < 0 || bin >= int(fCosbins)) continue;
107
108 if (isMethodSep) {
109 if (charge < 0) {
110 hCosth_el->Fill(costh);
111 hdEdx_elCosbin[bin]->Fill(dedx);
112 } else if (charge > 0) {
113 hCosth_po->Fill(costh);
114 hdEdx_poCosbin[bin]->Fill(dedx);
115 }
116 } else {
117 hCosth_ep->Fill(costh);
118 hdEdx_epCosbin[bin]->Fill(dedx);
119 }
120 }
121
122 //Plot constants
123 TH1D* hdEdxMeanvsCos_po = new TH1D(Form("hdEdxMeanvsCos_po_fRun%d", fStartRun),
124 Form("dE/dx(e+) rel means, start run: %d; cos(#theta); dE/dx (#mu_{fit})", fStartRun), fCosbins, fCosMin, fCosMax);
125 TH1D* hdEdxSigmavsCos_po = new TH1D(Form("hdEdxSigmavsCos_po_fRun%d", fStartRun),
126 Form("dE/dx(e+) rel means, start run: %d; cos(#theta); dE/dx (#mu_{fit})", fStartRun), fCosbins, fCosMin, fCosMax);
127
128 TH1D* hdEdxMeanvsCos_el = new TH1D(Form("hdEdxMeanvsCos_el_fRun%d", fStartRun),
129 Form("dE/dx(e-) rel means, start run: %d; cos(#theta); dE/dx (#mu_{fit})", fStartRun), fCosbins, fCosMin, fCosMax);
130 TH1D* hdEdxSigmavsCos_el = new TH1D(Form("hdEdxSigmavsCos_el_fRun%d", fStartRun),
131 Form("dE/dx(e-) rel means, start run: %d; cos(#theta); dE/dx (#mu_{fit})", fStartRun), fCosbins, fCosMin, fCosMax);
132
133 TH1D* hdEdxMeanvsCos_ep = new TH1D(Form("hdEdxMeanvsCos_ep_fRun%d", fStartRun),
134 Form("dE/dx(e+, e-) rel means, start run: %d; cos(#theta); dE/dx (#mu_{fit})", fStartRun), fCosbins, fCosMin, fCosMax);
135 TH1D* hdEdxSigmavsCos_ep = new TH1D(Form("hdEdxSigmavsCos_ep_fRun%d", fStartRun),
136 Form("dE/dx(e+, e-) rel means, start run: %d; cos(#theta); dE/dx (#mu_{fit})", fStartRun), fCosbins, fCosMin, fCosMax);
137
138 // more validation plots
139 TCanvas* ctmp_ep = new TCanvas("ctmp_ep", "ctmp_ep", 800, 400);
140 if (isMethodSep)ctmp_ep->Divide(2, 1);
141 else {
142 ctmp_ep->Divide(2, 2);
143 ctmp_ep->SetCanvasSize(800, 800);
144 }
145 std::stringstream psname_ep;
146
147 //validation plots: individual bin dedx dist and fits
148 if (isMakePlots) {
149 psname_ep << Form("cdcdedx_coscal_fits_frun%d.pdf[", fStartRun);
150 ctmp_ep->Print(psname_ep.str().c_str());
151 psname_ep.str("");
152 psname_ep << Form("cdcdedx_coscal_fits_frun%d.pdf", fStartRun);
153 }
154
155 // fit histograms to get gains in bins of cos(theta)
156 std::vector<double> cosine;
157 for (unsigned int i = 0; i < fCosbins; ++i) {
158
159
160 TLine* tl = new TLine();
161 tl->SetLineColor(kBlack);
162
163 double fdEdxMean = 1.0; //This is what we need for calibration
164 double fdEdxMeanErr = 0.0;
165
166 if (!isMethodSep) {
167
168 TString status = "";
169
170 double fdEdxSigma = 0.0, fdEdxSigmaErr = 0.0;
171 FitGaussianWRange(hdEdx_epCosbin[i], status);
172
173 if (status != "FitOK") {
174 fdEdxMean = 1.0;
175 hdEdx_epCosbin[i]->SetTitle(Form("%s, Fit(%s)", hdEdx_epCosbin[i]->GetTitle(), status.Data()));
176 } else {
177 fdEdxMean = hdEdx_epCosbin[i]->GetFunction("gaus")->GetParameter(1);
178 fdEdxMeanErr = hdEdx_epCosbin[i]->GetFunction("gaus")->GetParError(1);
179 fdEdxSigma = hdEdx_epCosbin[i]->GetFunction("gaus")->GetParameter(2);
180 fdEdxSigmaErr = hdEdx_epCosbin[i]->GetFunction("gaus")->GetParError(2);
181 hdEdx_epCosbin[i]->SetTitle(Form("%s, Fit (%s), #mu_{fit}: %0.04f#pm%0.04f,, #sigma_{fit}: %0.04f", hdEdx_epCosbin[i]->GetTitle(),
182 status.Data(), fdEdxMean, fdEdxMeanErr, fdEdxSigma));
183 }
184
185 hdEdxMeanvsCos_ep->SetBinContent(i + 1, fdEdxMean);
186 hdEdxMeanvsCos_ep->SetBinError(i + 1, fdEdxMeanErr);
187 hdEdxSigmavsCos_ep->SetBinContent(i + 1, fdEdxSigma);
188 hdEdxSigmavsCos_ep->SetBinError(i + 1, fdEdxSigmaErr);
189
190 if (isMakePlots) {
191 ctmp_ep->cd(i % 4 + 1); // each canvas is 2x2
192 hdEdx_epCosbin[i]->SetFillColorAlpha(kYellow, 0.25);
193 hdEdx_epCosbin[i]->DrawCopy("hist");
194
195 tl->SetX1(fdEdxMean); tl->SetX2(fdEdxMean);
196 tl->SetY1(0); tl->SetY2(hdEdx_epCosbin[i]->GetMaximum());
197 tl->DrawClone("same");
198 if ((i + 1) % 4 == 0 || (i + 1 == fCosbins))ctmp_ep->Print(psname_ep.str().c_str());
199 }
200 } else {
201
202 double fdEdxMean_el = 1.0, fdEdxMean_elErr = 0.0;
203 double fdEdxSigma_el = 0.0, fdEdxSigma_elErr = 0.0;
204 double fdEdxMean_po = 1.0, fdEdxMean_poErr = 0.0;
205 double fdEdxSigma_po = 0.0, fdEdxSigma_poErr = 0.0;
206 TString status_el = "", status_po = "";
207
208 //Fit _eltrons in cos bins
209 FitGaussianWRange(hdEdx_elCosbin[i], status_el);
210 if (status_el != "FitOK") {
211 fdEdxMean_el = 1.0;
212 hdEdx_elCosbin[i]->SetTitle(Form("%s, Fit(%s)", hdEdx_elCosbin[i]->GetTitle(), status_el.Data()));
213 } else {
214 fdEdxMean_el = hdEdx_elCosbin[i]->GetFunction("gaus")->GetParameter(1);
215 fdEdxMean_elErr = hdEdx_elCosbin[i]->GetFunction("gaus")->GetParError(1);
216 fdEdxSigma_el = hdEdx_elCosbin[i]->GetFunction("gaus")->GetParameter(2);
217 fdEdxSigma_elErr = hdEdx_elCosbin[i]->GetFunction("gaus")->GetParError(2);
218 hdEdx_elCosbin[i]->SetTitle(Form("%s, Fit (%s), #mu_{fit}: %0.04f#pm%0.04f,, #sigma_{fit}: %0.04f", hdEdx_elCosbin[i]->GetTitle(),
219 status_el.Data(), fdEdxMean_el, fdEdxMean_elErr, fdEdxSigma_el));
220 }
221
222 hdEdxMeanvsCos_el->SetBinContent(i + 1, fdEdxMean_el);
223 hdEdxMeanvsCos_el->SetBinError(i + 1, fdEdxMean_elErr);
224 hdEdxSigmavsCos_el->SetBinContent(i + 1, fdEdxSigma_el);
225 hdEdxSigmavsCos_el->SetBinError(i + 1, fdEdxSigma_elErr);
226
227 //Fit _potron in cos bins
228 FitGaussianWRange(hdEdx_poCosbin[i], status_po);
229 if (status_po != "FitOK") {
230 fdEdxMean_po = 1.0;
231 hdEdx_poCosbin[i]->SetTitle(Form("%s, Fit(%s)", hdEdx_poCosbin[i]->GetTitle(), status_po.Data()));
232 } else {
233 fdEdxMean_po = hdEdx_poCosbin[i]->GetFunction("gaus")->GetParameter(1);
234 fdEdxMean_poErr = hdEdx_poCosbin[i]->GetFunction("gaus")->GetParError(1);
235 fdEdxSigma_po = hdEdx_poCosbin[i]->GetFunction("gaus")->GetParameter(2);
236 fdEdxSigma_poErr = hdEdx_poCosbin[i]->GetFunction("gaus")->GetParError(2);
237 hdEdx_poCosbin[i]->SetTitle(Form("%s, Fit (%s), #mu_{fit}: %0.04f#pm%0.04f,, #sigma_{fit}: %0.04f", hdEdx_poCosbin[i]->GetTitle(),
238 status_po.Data(), fdEdxMean_po, fdEdxMean_poErr, fdEdxSigma_po));
239 }
240
241 if (status_po != "FitOK" && status_el == "FitOK") {
242 fdEdxMean_po = fdEdxMean_el;
243 hdEdx_poCosbin[i]->SetTitle(Form("%s, mean (manual) = elec left", hdEdx_poCosbin[i]->GetTitle()));
244 } else if (status_el != "FitOK" && status_po == "FitOK") {
245 fdEdxMean_el = fdEdxMean_po;
246 hdEdx_elCosbin[i]->SetTitle(Form("%s, mean (manual) = posi right", hdEdx_elCosbin[i]->GetTitle()));
247 } else if (status_el != "FitOK" && status_po != "FitOK") {
248 fdEdxMean_po = 1.0; fdEdxMean_el = 1.0;
249 }
250
251 hdEdxMeanvsCos_po->SetBinContent(i + 1, fdEdxMean_po);
252 hdEdxMeanvsCos_po->SetBinError(i + 1, fdEdxMean_poErr);
253 hdEdxSigmavsCos_po->SetBinContent(i + 1, fdEdxSigma_po);
254 hdEdxSigmavsCos_po->SetBinError(i + 1, fdEdxSigma_poErr);
255
256 //for validation purpose
257 if (isMakePlots) {
258
259 ctmp_ep->cd(1); // each canvas is 2x2
260 hdEdx_elCosbin[i]->SetFillColorAlpha(kYellow, 0.25);
261 hdEdx_elCosbin[i]->DrawCopy("");
262 tl->SetX1(fdEdxMean_el); tl->SetX2(fdEdxMean_el);
263 tl->SetY1(0); tl->SetY2(hdEdx_elCosbin[i]->GetMaximum());
264 tl->DrawClone("same");
265
266 ctmp_ep->cd(2); // each canvas is 2x2
267 hdEdx_poCosbin[i]->SetFillColorAlpha(kBlue, 0.25);
268 hdEdx_poCosbin[i]->DrawCopy("");
269 tl->SetX1(fdEdxMean_po); tl->SetX2(fdEdxMean_po);
270 tl->SetY1(0); tl->SetY2(hdEdx_poCosbin[i]->GetMaximum());
271 tl->DrawClone("same");
272 ctmp_ep->Print(psname_ep.str().c_str());
273 }
274
275 //avg of both e+ and e- fdEdxMean
276 fdEdxMean = 0.5 * (fdEdxMean_po + fdEdxMean_el);
277 if (fdEdxMean <= 0)fdEdxMean = 1.0; //protection only
278 fdEdxMeanErr = 0.5 * TMath::Sqrt(fdEdxMean_elErr * fdEdxMean_elErr + fdEdxMean_poErr * fdEdxMean_poErr);
279 hdEdxMeanvsCos_ep->SetBinContent(i + 1, fdEdxMean);
280 hdEdxMeanvsCos_ep->SetBinError(i + 1, fdEdxMeanErr);
281 }
282
283 cosine.push_back(fdEdxMean);
284 delete tl;
285 }
286
287 //more validation plots for debugging
288 if (isMakePlots) {
289
290 psname_ep.str("");
291 psname_ep << Form("cdcdedx_coscal_fits_frun%d.pdf]", fStartRun);
292 ctmp_ep->Print(psname_ep.str().c_str());
293 delete ctmp_ep;
294
295 TCanvas* cstats = new TCanvas("cstats", "cstats", 1000, 500);
296 cstats->SetBatch(kTRUE);
297 cstats->Divide(2, 1);
298 cstats->cd(1);
299 auto hestats = getObjectPtr<TH1I>("hestats");
300 if (hestats) {
301 hestats->SetName(Form("hestats_fRun%d", fStartRun));
302 hestats->SetStats(0);
303 hestats->DrawCopy("");
304 }
305 cstats->cd(2);
306 auto htstats = getObjectPtr<TH1I>("htstats");
307 if (htstats) {
308 hestats->SetName(Form("htstats_fRun%d", fStartRun));
309 htstats->DrawCopy("");
310 hestats->SetStats(0);
311 }
312 cstats->Print(Form("cdcdedx_coscal_stats_frun%d.pdf", fStartRun));
313 delete cstats;
314
315 TCanvas* ctmp_epConst = new TCanvas("ctmp_epConst", "ctmp_epConst", 800, 400);
316 ctmp_epConst->Divide(2, 1);
317
318 TCanvas* ctmp_epCosth = new TCanvas("ctmp_epCosth", "ctmp_epCosth", 600, 500);
319
320 if (isMethodSep) {
321
322 ctmp_epConst->cd(1);
323 gPad->SetGridy(1);
324 hdEdxMeanvsCos_el->SetMarkerStyle(20);
325 hdEdxMeanvsCos_el->SetMarkerSize(0.60);
326 hdEdxMeanvsCos_el->SetMarkerColor(kRed);
327 hdEdxMeanvsCos_el->SetStats(0);
328 hdEdxMeanvsCos_el->SetTitle("comparison of dedx #mu_{fit}^{rel}: (e-=red, e+=blue, avg=black)");
329 hdEdxMeanvsCos_el->GetYaxis()->SetRangeUser(0.96, 1.04);
330 hdEdxMeanvsCos_el->DrawCopy("");
331
332 hdEdxMeanvsCos_po->SetMarkerStyle(20);
333 hdEdxMeanvsCos_po->SetMarkerSize(0.60);
334 hdEdxMeanvsCos_po->SetMarkerColor(kBlue);
335 hdEdxMeanvsCos_po->SetStats(0);
336 hdEdxMeanvsCos_po->DrawCopy("same");
337
338 hdEdxMeanvsCos_ep->SetMarkerStyle(20);
339 hdEdxMeanvsCos_ep->SetMarkerSize(0.60);
340 hdEdxMeanvsCos_ep->SetMarkerColor(kBlack);
341 hdEdxMeanvsCos_ep->SetStats(0);
342 hdEdxMeanvsCos_ep->DrawCopy("same");
343
344 ctmp_epConst->cd(2);
345 gPad->SetGridy(1);
346 hdEdxSigmavsCos_el->SetMarkerStyle(4);
347 hdEdxSigmavsCos_el->SetMarkerColor(kRed);
348 hdEdxSigmavsCos_el->SetMarkerSize(0.90);
349 hdEdxSigmavsCos_el->SetTitle("comparison of dedx #mu_{fit}^{rel}: (e-=open, e+=closed)");
350 hdEdxSigmavsCos_el->GetYaxis()->SetRangeUser(0.4, 0.12);
351 hdEdxSigmavsCos_el->SetStats(0);
352 hdEdxSigmavsCos_el->DrawCopy("");
353
354 hdEdxSigmavsCos_po->SetMarkerStyle(8);
355 hdEdxSigmavsCos_po->SetMarkerSize(0.80);
356 hdEdxSigmavsCos_po->SetMarkerColor(kBlue);
357 hdEdxSigmavsCos_po->SetStats(0);
358 hdEdxSigmavsCos_po->DrawCopy("same");
359
360 ctmp_epCosth->cd();
361 hCosth_el->SetStats(0);
362 hCosth_el->SetLineColor(kRed);
363 hCosth_el->SetFillColorAlpha(kYellow, 0.55);
364 hCosth_el->DrawCopy("");
365 hCosth_po->SetStats(0);
366 hCosth_po->SetLineColor(kBlue);
367 hCosth_po->SetFillColorAlpha(kGray, 0.35);
368 hCosth_po->DrawCopy("same");
369
370 } else {
371
372 ctmp_epConst->cd(1);
373 gPad->SetGridy(1);
374 hdEdxMeanvsCos_ep->SetMarkerStyle(20);
375 hdEdxMeanvsCos_ep->SetMarkerSize(0.60);
376 hdEdxMeanvsCos_ep->SetMarkerColor(kBlack);
377 hdEdxMeanvsCos_ep->SetStats(0);
378 hdEdxMeanvsCos_ep->SetTitle("dedx rel(#mu_{fit}) for e- and e+ combined");
379 hdEdxMeanvsCos_ep->GetYaxis()->SetRangeUser(0.97, 1.04);
380 hdEdxMeanvsCos_ep->DrawCopy("");
381
382 ctmp_epConst->cd(2);
383 gPad->SetGridy(1);
384 hdEdxSigmavsCos_ep->SetMarkerStyle(20);
385 hdEdxSigmavsCos_ep->SetMarkerColor(kRed);
386 hdEdxSigmavsCos_ep->SetMarkerSize(1.1);
387 hdEdxSigmavsCos_ep->SetTitle("dedx rel(#sigma_{fit}) for e- and e+ combined");
388 hdEdxSigmavsCos_ep->GetYaxis()->SetRangeUser(0.4, 0.12);
389 hdEdxSigmavsCos_ep->SetStats(0);
390 hdEdxSigmavsCos_ep->DrawCopy("");
391
392 ctmp_epCosth->cd();
393 hCosth_ep->SetStats(0);
394 hCosth_ep->SetLineColor(kGray);
395 hCosth_ep->SetFillColorAlpha(kGray, 0.25);
396 hCosth_ep->DrawCopy("same");
397 }
398
399 ctmp_epCosth->SaveAs(Form("cdcdedx_coscal_costhdist_frun%d.pdf", fStartRun));
400 delete ctmp_epCosth;
401
402 ctmp_epConst->SaveAs(Form("cdcdedx_coscal_relmeans_frun%d.pdf", fStartRun));
403 ctmp_epConst->SaveAs(Form("cdcdedx_coscal_relmeans_frun%d.root", fStartRun));
404 delete ctmp_epConst;
405 }
406
407 generateNewPayloads(cosine);
408 return c_OK;
409}
void generateNewPayloads(std::vector< double > cosine)
function to store new payload after full calibration
void FitGaussianWRange(TH1D *&temphist, TString &status)
function to fit histogram in each cosine bin
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.
double charge(int pdgCode)
Returns electric charge of a particle with given pdg code.
Definition: EvtPDLUtil.cc:44

◆ 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.

void clearCalibrationData()
Clear calibration data.
ExecutionData m_data
Data specific to a SINGLE execution of the algorithm. Gets reset at the beginning of execution.

◆ 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:42
bool storeData(const std::string &name, TObject *object, const IntervalOfValidity &iov)
Store an object in the database.
Definition: Database.cc:141

◆ 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}
Struct containing exp number and run number.
Definition: Splitter.h:51

◆ 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();}
nlohmann::json m_jsonExecutionOutput
Optional output JSON object that can be set during the execution by the underlying algorithm code.

◆ 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++");
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).");
109 return c_Failure;
110 }
111 return execute(vecRuns, iteration, iov);
112}
void setResult(EResult result)
Setter for current iteration.
void setIteration(int iteration)
Setter for current iteration.
void reset()
Resets this class back to what is needed at the beginning of an execution.
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.

◆ 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()");
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.");
145 return c_Failure;
146 }
147 for (auto expRun : runs) {
148 B2DEBUG(29, "ExpRun requested = (" << expRun.first << ", " << expRun.second << ")");
149 }
150 }
151
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 }
158 // After here, the getObject<...>(...) helpers start to work
159
161 m_data.setResult(result);
162 return result;
163}
void setRequestedIov(const IntervalOfValidity &iov=IntervalOfValidity(0, 0, -1, -1))
Sets the requested IoV for this execution, based on the.
void setRequestedRuns(const std::vector< Calibration::ExpRun > &requestedRuns)
Sets the vector of ExpRuns.
EResult getResult() const
Getter for current result.
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.
virtual EResult calibrate()=0
Run algo on data - pure virtual: needs to be implemented.
std::string getGranularity() const
Get the granularity of collected data.
A class that describes the interval of experiments/runs for which an object in the database is valid.

◆ 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...
Mergeable object holding (unique) set of (exp,run) pairs.
Definition: RunRange.h:25
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
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...

◆ FitGaussianWRange()

void FitGaussianWRange ( TH1D *&  temphist,
TString &  status 
)

function to fit histogram in each cosine bin

Definition at line 469 of file CDCDedxCosineAlgorithm.cc.

470{
471 if (temphist->Integral() < 2000) { //at least 1k bhabha events
472 B2INFO(Form("\tThis hist (%s) have insufficient entries to perform fit (%0.03f)", temphist->GetName(), temphist->Integral()));
473 status = "LowStats";
474 return;
475 } else {
476 temphist->GetXaxis()->SetRange(temphist->FindFirstBinAbove(0, 1), temphist->FindLastBinAbove(0, 1));
477 int fs = temphist->Fit("gaus", "QR");
478 if (fs != 0) {
479 B2INFO(Form("\tFit (round 1) for hist (%s) failed (status = %d)", temphist->GetName(), fs));
480 status = "FitFailed";
481 return;
482 } else {
483 double fdEdxMean = temphist->GetFunction("gaus")->GetParameter(1);
484 double width = temphist->GetFunction("gaus")->GetParameter(2);
485 temphist->GetXaxis()->SetRangeUser(fdEdxMean - 5.0 * width, fdEdxMean + 5.0 * width);
486 fs = temphist->Fit("gaus", "QR", "", fdEdxMean - fSigLim * width, fdEdxMean + fSigLim * width);
487 if (fs != 0) {
488 B2INFO(Form("\tFit (round 2) for hist (%s) failed (status = %d)", temphist->GetName(), fs));
489 status = "FitFailed";
490 return;
491 } else {
492 temphist->GetXaxis()->SetRangeUser(fdEdxMean - 5.0 * width, fdEdxMean + 5.0 * width);
493 B2INFO(Form("\tFit for hist (%s) successful (status = %d)", temphist->GetName(), fs));
494 status = "FitOK";
495 }
496 }
497 }
498}

◆ generateNewPayloads()

void generateNewPayloads ( std::vector< double >  cosine)

function to store new payload after full calibration

Definition at line 411 of file CDCDedxCosineAlgorithm.cc.

412{
413
414 TH1D* hCosCorrOld = new TH1D(Form("hCosCorrOld_fRun%d", fStartRun),
415 Form("cos corr const comparison (red=old, blue=new), start run: %d;cos(#theta);dE/dx #mu_{fit}", fStartRun), fCosbins, fCosMin,
416 fCosMax);
417 TH1D* hCosCorrNew = new TH1D(Form("hCosCorrNew_fRun%d", fStartRun), Form("coss corr, start run: %d;cos(#theta);dE/dx #mu_{fit}",
419 TH1D* hCosCorrRel = new TH1D(Form("hCosCorrRel_fRun%d", fStartRun),
420 Form("new relative cos corr, start run: %d;cos(#theta);dE/dx #mu_{fit}", fStartRun), fCosbins, fCosMin, fCosMax);
421
422 if (isMergePayload) {
423 const auto expRun = getRunList()[0];
424 updateDBObjPtrs(1, expRun.second, expRun.first);
425 // bool refchange = m_DBCosineCor.hasChanged(); //Add this feature for major processing
426 B2INFO("Saving new rung for (Exp, Run) : (" << expRun.first << "," << expRun.second << ")");
427 for (unsigned int ibin = 0; ibin < m_DBCosineCor->getSize(); ibin++) {
428 hCosCorrOld->SetBinContent(ibin + 1, (double)m_DBCosineCor->getMean(ibin));
429 hCosCorrRel->SetBinContent(ibin + 1, cosine.at(ibin));
430 B2INFO("Cosine Corr for Bin # " << ibin << ", Previous = " << m_DBCosineCor->getMean(ibin) << ", Relative = " << cosine.at(
431 ibin) << ", Merged = " << m_DBCosineCor->getMean(ibin)*cosine.at(ibin));
432 cosine.at(ibin) *= (double)m_DBCosineCor->getMean(ibin);
433 hCosCorrNew->SetBinContent(ibin + 1, cosine.at(ibin));
434 }
435 }
436
437 if (isMakePlots) {
438 TCanvas* ctmp_const = new TCanvas("ctmp_const", "ctmp_const", 900, 450);
439 ctmp_const->Divide(2, 1);
440
441 ctmp_const->cd(1);
442 gPad->SetGridy(1);
443 gPad->SetGridx(1);
444 hCosCorrOld->SetStats(0);
445 hCosCorrOld->SetLineColor(kRed);
446 hCosCorrOld->GetYaxis()->SetRangeUser(0.64, 1.20);
447 hCosCorrOld->DrawCopy("");
448 hCosCorrNew->SetStats(0);
449 hCosCorrNew->SetLineColor(kBlue);
450 hCosCorrNew->DrawCopy("same");
451
452 ctmp_const->cd(2);
453 gPad->SetGridy(1);
454 hCosCorrRel->SetStats(0);
455 hCosCorrRel->GetYaxis()->SetRangeUser(0.97, 1.03);
456 hCosCorrRel->SetLineColor(kBlack);
457 hCosCorrRel->DrawCopy("");
458
459 ctmp_const->SaveAs(Form("cdcdedx_coscal_constants_frun%d.pdf", fStartRun));
460 ctmp_const->SaveAs(Form("cdcdedx_coscal_constants_frun%d.root", fStartRun));
461 delete ctmp_const;
462 }
463
464 B2INFO("dE/dx calibration done for CDC dE/dx _eltron saturation");
465 CDCDedxCosineCor* gain = new CDCDedxCosineCor(cosine);
466 saveCalibration(gain, "CDCDedxCosineCor");
467}
DBObjPtr< CDCDedxCosineCor > m_DBCosineCor
Electron saturation correction DB object.
dE/dx wire gain calibration constants
void saveCalibration(TClonesArray *data, const std::string &name)
Store DBArray payload with given name with default IOV.

◆ 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;}
static const Calibration::ExpRun m_allExpRun
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 algorihtm.

Definition at line 164 of file CalibrationAlgorithm.h.

164{return getPrefix();}

◆ getDescription()

const std::string & getDescription ( ) const
inlineinherited

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

Definition at line 216 of file CalibrationAlgorithm.h.

216{return m_description;}
std::string m_description
Description of the algorithm.

◆ 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;};
std::string m_granularityOfData
Granularity of input data. This only changes when the input files change so it isn't specific to an e...

◆ 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;}
nlohmann::json m_jsonExecutionInput
Optional input JSON object used to make decisions about how to execute the algorithm code.

◆ 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.

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(); }
int getIteration() const
Getter for current iteration.

◆ 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.

286 {
287 if (m_runsToInputFiles.size() == 0)
289 return getObjectPtr<T>(name, m_data.getRequestedRuns());
290 }
const std::vector< Calibration::ExpRun > & getRequestedRuns() const
Returns the vector of ExpRuns.
void fillRunToInputFilesMap()
Fill the mapping of ExpRun -> Files.

◆ 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.

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();}
std::list< Database::DBImportQuery > & getPayloads()
Get constants (in TObjects) for database update from last calibration.

◆ 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();}
std::list< Database::DBImportQuery > getPayloadValues()
Get constants (in TObjects) for database update from last calibration but passed by VALUE.

◆ 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;}
std::string m_prefix
The name of the TDirectory the collector objects are contained within.

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

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 rturn 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}

◆ 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();}

◆ 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{
300}
const IntervalOfValidity & getRequestedIov() const
Getter for requested 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:151

◆ 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{
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}

◆ setCosineBins()

void setCosineBins ( unsigned int  value = 100)
inline

function to set number of cosine bins for calibration

Definition at line 72 of file CDCDedxCosineAlgorithm.h.

72{fCosbins = value;}

◆ setCosineRange()

void setCosineRange ( double  min = -1.0,
double  max = 1.0 
)
inline

function to set number of cosine bins for calibration

Definition at line 77 of file CDCDedxCosineAlgorithm.h.

77{fCosMin = min; fCosMax = max;}

◆ 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;}

◆ setFitWidth()

void setFitWidth ( double  value = 2.5)
inline

set sigma to restrict fir range around mean

Definition at line 62 of file CDCDedxCosineAlgorithm.h.

62{fSigLim = value;}

◆ setHistBins()

void setHistBins ( int  value = 600)
inline

function to set nbins of dedx dist calibration

Definition at line 82 of file CDCDedxCosineAlgorithm.h.

82{fHistbins = value;}

◆ setHistRange()

void setHistRange ( double  min = 0.0,
double  max = 3.0 
)
inline

function to set min/max range of dedx dist calibration

Definition at line 87 of file CDCDedxCosineAlgorithm.h.

87{fdEdxMin = min; fdEdxMax = max;}

◆ 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 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.

◆ setMergePayload()

void setMergePayload ( bool  value = true)
inline

function to decide merge vs relative gains

Definition at line 47 of file CDCDedxCosineAlgorithm.h.

47{isMergePayload = value;}

◆ setMethodSep()

void setMethodSep ( bool  value = true)
inline

function to make flag active for method of sep

Definition at line 42 of file CDCDedxCosineAlgorithm.h.

42{isMethodSep = value;}

◆ setMonitoringPlots()

void setMonitoringPlots ( bool  value = false)
inline

function to make flag active for plotting

Definition at line 57 of file CDCDedxCosineAlgorithm.h.

57{isMakePlots = value;}

◆ setOutputJsonValue()

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

Set a key:value pair for the outputJson object, expected to used interally 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;}

◆ 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 unnessary...)
412}
Store event, run, and experiment numbers.
Definition: EventMetaData.h:33
static DBStore & Instance()
Instance of a singleton DBStore.
Definition: DBStore.cc:28
void updateEvent()
Updates all intra-run dependent objects.
Definition: DBStore.cc:142
void update()
Updates all objects that are outside their interval of validity.
Definition: DBStore.cc:79

Member Data Documentation

◆ fCosbins

unsigned int fCosbins
private

number of bins across cosine range

Definition at line 101 of file CDCDedxCosineAlgorithm.h.

◆ fCosMax

double fCosMax
private

max cosine angle for cal

Definition at line 103 of file CDCDedxCosineAlgorithm.h.

◆ fCosMin

double fCosMin
private

min cosine angle for cal

Definition at line 102 of file CDCDedxCosineAlgorithm.h.

◆ fdEdxMax

double fdEdxMax
private

max dedx range for gain cal

Definition at line 106 of file CDCDedxCosineAlgorithm.h.

◆ fdEdxMin

double fdEdxMin
private

min dedx range for gain cal

Definition at line 105 of file CDCDedxCosineAlgorithm.h.

◆ fHistbins

int fHistbins
private

number of bins for dedx histogram

Definition at line 104 of file CDCDedxCosineAlgorithm.h.

◆ fSigLim

double fSigLim
private

gaussian fit sigma limit

Definition at line 100 of file CDCDedxCosineAlgorithm.h.

◆ fStartRun

int fStartRun
private

boundary start at this run

Definition at line 107 of file CDCDedxCosineAlgorithm.h.

◆ isMakePlots

bool isMakePlots
private

produce plots for status

Definition at line 98 of file CDCDedxCosineAlgorithm.h.

◆ isMergePayload

bool isMergePayload
private

merge payload at the of calibration

Definition at line 99 of file CDCDedxCosineAlgorithm.h.

◆ isMethodSep

bool isMethodSep
private

if e+e- need to be consider sep

Definition at line 97 of file CDCDedxCosineAlgorithm.h.

◆ m_allExpRun

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

allExpRun

Definition at line 364 of file CalibrationAlgorithm.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_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_DBCosineCor

DBObjPtr<CDCDedxCosineCor> m_DBCosineCor
private

Electron saturation correction DB object.

Definition at line 108 of file CDCDedxCosineAlgorithm.h.

◆ m_description

std::string m_description {""}
privateinherited

Description of the algorithm.

Definition at line 385 of file CalibrationAlgorithm.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_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_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_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.


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