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DTOccupancyClusterBuilder.cc
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1 
2 /*
3  * See header file for a description of this class.
4  *
5  * \author G. Cerminara - INFN Torino
6  */
7 
10 
11 #include "TCanvas.h"
12 #include "TH2F.h"
13 
14 #include <algorithm>
15 #include <sstream>
16 #include <iostream>
17 
18 using namespace std;
19 using namespace edm;
20 
22 
24 
26  // loop over points already stored
27  for (set<DTOccupancyPoint>::const_iterator pt = thePoints.begin(); pt != thePoints.end(); ++pt) {
28  theDistances[(*pt).distance(point)] = make_pair(*pt, point);
29  }
30  thePoints.insert(point);
31 }
32 
34  while (buildNewCluster()) {
35  if (thePoints.size() <= 1)
36  break;
37  }
38 
39  // build single point clusters with the remaining points
40  for (set<DTOccupancyPoint>::const_iterator pt = thePoints.begin(); pt != thePoints.end(); ++pt) {
41  DTOccupancyCluster clusterCandidate(*pt);
42  theClusters.push_back(clusterCandidate);
43  // store the range for building the histograms later
44  if (clusterCandidate.maxMean() > maxMean)
45  maxMean = clusterCandidate.maxMean();
46  if (clusterCandidate.maxRMS() > maxRMS)
47  maxRMS = clusterCandidate.maxRMS();
48  }
49  LogTrace("DTDQM|DTMonitorClient|DTOccupancyTest|DTOccupancyClusterBuilder")
50  << " # of valid clusters: " << theClusters.size() << endl;
51  sortClusters();
52 }
53 
55  int nBinsX = 100;
56  int nBinsY = 100;
57  int colorMap[12] = {632, 600, 800, 400, 820, 416, 432, 880, 616, 860, 900, 920};
58 
59  TCanvas* canvas = new TCanvas(canvasName.c_str(), canvasName.c_str());
60  canvas->cd();
61  for (vector<DTOccupancyCluster>::const_iterator cluster = theClusters.begin(); cluster != theClusters.end();
62  ++cluster) {
63  stringstream stream;
64  stream << canvasName << "_" << cluster - theClusters.begin();
65  string histoName = stream.str();
66  TH2F* histo = (*cluster).getHisto(histoName,
67  nBinsX,
68  0,
69  maxMean + 3 * maxMean / 100.,
70  nBinsY,
71  0,
72  maxRMS + 3 * maxRMS / 100.,
73  colorMap[cluster - theClusters.begin()]);
74  if (cluster == theClusters.begin())
75  histo->Draw("box");
76  else
77  histo->Draw("box,same");
78  }
79 }
80 
81 std::pair<DTOccupancyPoint, DTOccupancyPoint> DTOccupancyClusterBuilder::getInitialPair() {
82  return theDistances.begin()->second;
83 }
84 
86  theDistances.clear();
87  for (set<DTOccupancyPoint>::const_iterator pt_i = thePoints.begin(); pt_i != thePoints.end(); ++pt_i) { // i loopo
88  for (set<DTOccupancyPoint>::const_iterator pt_j = thePoints.begin(); pt_j != thePoints.end(); ++pt_j) { // j loop
89  if (*pt_i != *pt_j) {
90  theDistances[pt_i->distance(*pt_j)] = make_pair(*pt_i, *pt_j);
91  }
92  }
93  }
94 }
95 
98  for (set<DTOccupancyPoint>::const_iterator pt = thePoints.begin(); pt != thePoints.end(); ++pt) {
100  }
101 }
102 
104  LogTrace("DTDQM|DTMonitorClient|DTOccupancyTest|DTOccupancyClusterBuilder")
105  << "--------- New Cluster Candidate ----------------------" << endl;
106  pair<DTOccupancyPoint, DTOccupancyPoint> initialPair = getInitialPair();
107  LogTrace("DTDQM|DTMonitorClient|DTOccupancyTest|DTOccupancyClusterBuilder")
108  << " Initial Pair: " << endl
109  << " point1: mean " << initialPair.first.mean() << " rms " << initialPair.first.rms() << endl
110  << " point2: mean " << initialPair.second.mean() << " rms " << initialPair.second.rms() << endl;
111  DTOccupancyCluster clusterCandidate(initialPair.first, initialPair.second);
112  if (clusterCandidate.isValid()) {
113  // remove already used pair
114  thePoints.erase(initialPair.first);
115  thePoints.erase(initialPair.second);
116  if (!thePoints.empty()) {
117  computeDistancesToCluster(clusterCandidate);
118  while (clusterCandidate.addPoint(theDistancesFromTheCluster.begin()->second)) {
119  thePoints.erase(theDistancesFromTheCluster.begin()->second);
120  if (thePoints.empty())
121  break;
122  computeDistancesToCluster(clusterCandidate);
123  }
124  }
125  } else {
126  return false;
127  }
128  LogTrace("DTDQM|DTMonitorClient|DTOccupancyTest|DTOccupancyClusterBuilder")
129  << " # of layers: " << clusterCandidate.nPoints() << " avrg. mean: " << clusterCandidate.averageMean()
130  << " avrg. rms: " << clusterCandidate.averageRMS() << endl;
131  theClusters.push_back(clusterCandidate);
132  // store the range for building the histograms later
133  if (clusterCandidate.maxMean() > maxMean)
134  maxMean = clusterCandidate.maxMean();
135  if (clusterCandidate.maxRMS() > maxRMS)
136  maxRMS = clusterCandidate.maxRMS();
138  return true;
139 }
140 
142  LogTrace("DTDQM|DTMonitorClient|DTOccupancyTest|DTOccupancyClusterBuilder") << " sorting" << endl;
143  sort(theClusters.begin(), theClusters.end(), clusterIsLessThan);
144  // we save the detid of the clusters which are not the best one
145  for (vector<DTOccupancyCluster>::const_iterator cluster = ++(theClusters.begin()); cluster != theClusters.end();
146  ++cluster) { // loop over clusters skipping the first
147  set<DTLayerId> clusterLayers = (*cluster).getLayerIDs();
148  LogTrace("DTDQM|DTMonitorClient|DTOccupancyTest|DTOccupancyClusterBuilder")
149  << " # layers in the cluster: " << clusterLayers.size() << endl;
150  theProblematicLayers.insert(clusterLayers.begin(), clusterLayers.end());
151  }
152  LogTrace("DTDQM|DTMonitorClient|DTOccupancyTest|DTOccupancyClusterBuilder")
153  << " # of problematic layers: " << theProblematicLayers.size() << endl;
154 }
155 
157 
159  if (theProblematicLayers.find(layerId) != theProblematicLayers.end()) {
160  return true;
161  }
162  return false;
163 }
svgfig.canvas
def canvas(*sub, **attr)
Definition: svgfig.py:482
DTOccupancyCluster::addPoint
bool addPoint(const DTOccupancyPoint &anotherPoint)
Definition: DTOccupancyCluster.cc:65
MessageLogger.h
clusterIsLessThan
bool clusterIsLessThan(const DTOccupancyCluster &clusterOne, const DTOccupancyCluster &clusterTwo)
for DTOccupancyCluster sorting
Definition: DTOccupancyCluster.cc:174
DTOccupancyCluster::maxMean
double maxMean() const
max average cell occupancy of the layers in the cluster
Definition: DTOccupancyCluster.cc:105
DiDispStaMuonMonitor_cfi.pt
pt
Definition: DiDispStaMuonMonitor_cfi.py:39
DTOccupancyPoint
Definition: DTOccupancyPoint.h:13
edm
HLT enums.
Definition: AlignableModifier.h:19
DTOccupancyClusterBuilder::theDistances
std::map< double, std::pair< DTOccupancyPoint, DTOccupancyPoint > > theDistances
Definition: DTOccupancyClusterBuilder.h:55
DTOccupancyCluster
Definition: DTOccupancyCluster.h:20
cms::cuda::stream
cudaStream_t stream
Definition: HistoContainer.h:57
DTOccupancyClusterBuilder::buildClusters
void buildClusters()
build the clusters
Definition: DTOccupancyClusterBuilder.cc:33
DTOccupancyClusterBuilder::thePoints
std::set< DTOccupancyPoint > thePoints
Definition: DTOccupancyClusterBuilder.h:54
timingPdfMaker.histo
histo
Definition: timingPdfMaker.py:279
DTOccupancyClusterBuilder::DTOccupancyClusterBuilder
DTOccupancyClusterBuilder()
Constructor.
Definition: DTOccupancyClusterBuilder.cc:21
DTOccupancyClusterBuilder::getBestCluster
DTOccupancyCluster getBestCluster() const
get the cluster correspondig to "normal" cell occupancy.
Definition: DTOccupancyClusterBuilder.cc:156
DTOccupancyClusterBuilder::computePointToPointDistances
void computePointToPointDistances()
Definition: DTOccupancyClusterBuilder.cc:85
DTOccupancyClusterBuilder::maxMean
double maxMean
Definition: DTOccupancyClusterBuilder.h:60
DTOccupancyClusterBuilder::isProblematic
bool isProblematic(DTLayerId layerId) const
Definition: DTOccupancyClusterBuilder.cc:158
DTOccupancyClusterBuilder::theProblematicLayers
std::set< DTLayerId > theProblematicLayers
Definition: DTOccupancyClusterBuilder.h:58
DTOccupancyCluster::maxRMS
double maxRMS() const
max RMS of the cell occpuancy distributions of the layers in the cluster
Definition: DTOccupancyCluster.cc:107
DTOccupancyCluster::distance
double distance(const DTOccupancyPoint &point) const
Definition: DTOccupancyCluster.cc:89
DTLayerId
Definition: DTLayerId.h:12
DTOccupancyClusterBuilder::maxRMS
double maxRMS
Definition: DTOccupancyClusterBuilder.h:61
AlCaHLTBitMon_QueryRunRegistry.string
string
Definition: AlCaHLTBitMon_QueryRunRegistry.py:256
DTOccupancyClusterBuilder.h
DTOccupancyClusterBuilder::theDistancesFromTheCluster
std::map< double, DTOccupancyPoint > theDistancesFromTheCluster
Definition: DTOccupancyClusterBuilder.h:56
DTOccupancyClusterBuilder::buildNewCluster
bool buildNewCluster()
Definition: DTOccupancyClusterBuilder.cc:103
DTOccupancyClusterBuilder::drawClusters
void drawClusters(std::string canvasName)
draw a TH2F histograms showing the clusters
Definition: DTOccupancyClusterBuilder.cc:54
DTOccupancyCluster::averageRMS
double averageRMS() const
average RMS of the cell occpuancy distributions of the layers in the cluster
Definition: DTOccupancyCluster.cc:103
DTOccupancyClusterBuilder::sortClusters
void sortClusters()
Definition: DTOccupancyClusterBuilder.cc:141
DTOccupancyCluster::isValid
bool isValid() const
Check if the cluster candidate satisfies the quality requirements.
Definition: DTOccupancyCluster.cc:61
std
Definition: JetResolutionObject.h:76
DTOccupancyClusterBuilder::~DTOccupancyClusterBuilder
virtual ~DTOccupancyClusterBuilder()
Destructor.
Definition: DTOccupancyClusterBuilder.cc:23
DTOccupancyClusterBuilder::computeDistancesToCluster
void computeDistancesToCluster(const DTOccupancyCluster &cluster)
Definition: DTOccupancyClusterBuilder.cc:96
DTOccupancyClusterBuilder::addPoint
void addPoint(const DTOccupancyPoint &point)
Add an occupancy point for a given layer.
Definition: DTOccupancyClusterBuilder.cc:25
HltBtagPostValidation_cff.histoName
histoName
Definition: HltBtagPostValidation_cff.py:17
DTOccupancyClusterBuilder::getInitialPair
std::pair< DTOccupancyPoint, DTOccupancyPoint > getInitialPair()
Definition: DTOccupancyClusterBuilder.cc:81
LogTrace
#define LogTrace(id)
Definition: MessageLogger.h:224
DTOccupancyCluster::nPoints
int nPoints() const
Definition: DTOccupancyCluster.cc:164
point
*vegas h *****************************************************used in the default bin number in original ***version of VEGAS is ***a higher bin number might help to derive a more precise ***grade subtle point
Definition: invegas.h:5
DTOccupancyClusterBuilder::theClusters
std::vector< DTOccupancyCluster > theClusters
Definition: DTOccupancyClusterBuilder.h:57
DTOccupancyCluster::averageMean
double averageMean() const
average cell occupancy of the layers in the cluster
Definition: DTOccupancyCluster.cc:101