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CaloGPUClusterAndCellDataMonitor Class Reference

Places (matched) cluster and cell properties in monitored variables to enable plotting with the Athena THistSvc instead of the custom solution that was being used previously. Its histograms can be configured as in a MonitoringTool. More...

#include <CaloGPUClusterAndCellDataMonitor.h>

Inheritance diagram for CaloGPUClusterAndCellDataMonitor:
Collaboration diagram for CaloGPUClusterAndCellDataMonitor:

Classes

struct  pair_to_plot
 
struct  per_tool_storage
 
struct  sample_comparisons_holder
 

Public Member Functions

 CaloGPUClusterAndCellDataMonitor (const std::string &type, const std::string &name, const IInterface *parent)
 
virtual StatusCode initialize () override
 
virtual ~CaloGPUClusterAndCellDataMonitor ()=default
 
virtual StatusCode update_plots_start (const EventContext &ctx, const CaloRecGPU::ConstantDataHolder &constant_data, const xAOD::CaloClusterContainer *cluster_collection_ptr) const override
 
virtual StatusCode update_plots_end (const EventContext &ctx, const CaloRecGPU::ConstantDataHolder &constant_data, const xAOD::CaloClusterContainer *cluster_collection_ptr) const override
 
virtual StatusCode update_plots (const EventContext &ctx, const CaloRecGPU::ConstantDataHolder &constant_data, const xAOD::CaloClusterContainer *cluster_collection_ptr, const CaloClusterCollectionProcessor *tool) const override
 
virtual StatusCode update_plots (const EventContext &ctx, const CaloRecGPU::ConstantDataHolder &constant_data, const xAOD::CaloClusterContainer *cluster_collection_ptr, const CaloRecGPU::EventDataHolder &event_data, const ICaloClusterGPUInputTransformer *tool) const override
 
virtual StatusCode update_plots (const EventContext &ctx, const CaloRecGPU::ConstantDataHolder &constant_data, const xAOD::CaloClusterContainer *cluster_collection_ptr, const CaloRecGPU::EventDataHolder &event_data, const CaloClusterGPUProcessor *tool) const override
 
virtual StatusCode update_plots (const EventContext &ctx, const CaloRecGPU::ConstantDataHolder &constant_data, const xAOD::CaloClusterContainer *cluster_collection_ptr, const CaloRecGPU::EventDataHolder &event_data, const ICaloClusterGPUOutputTransformer *tool) const override
 
virtual StatusCode finalize_plots () const override
 
ServiceHandle< StoreGateSvc > & evtStore ()
 The standard StoreGateSvc (event store) Returns (kind of) a pointer to the StoreGateSvc. More...
 
const ServiceHandle< StoreGateSvc > & evtStore () const
 The standard StoreGateSvc (event store) Returns (kind of) a pointer to the StoreGateSvc. More...
 
const ServiceHandle< StoreGateSvc > & detStore () const
 The standard StoreGateSvc/DetectorStore Returns (kind of) a pointer to the StoreGateSvc. More...
 
virtual StatusCode sysInitialize () override
 Perform system initialization for an algorithm. More...
 
virtual StatusCode sysStart () override
 Handle START transition. More...
 
virtual std::vector< Gaudi::DataHandle * > inputHandles () const override
 Return this algorithm's input handles. More...
 
virtual std::vector< Gaudi::DataHandle * > outputHandles () const override
 Return this algorithm's output handles. More...
 
Gaudi::Details::PropertyBase & declareProperty (Gaudi::Property< T > &t)
 
Gaudi::Details::PropertyBase * declareProperty (const std::string &name, SG::VarHandleKey &hndl, const std::string &doc, const SG::VarHandleKeyType &)
 Declare a new Gaudi property. More...
 
Gaudi::Details::PropertyBase * declareProperty (const std::string &name, SG::VarHandleBase &hndl, const std::string &doc, const SG::VarHandleType &)
 Declare a new Gaudi property. More...
 
Gaudi::Details::PropertyBase * declareProperty (const std::string &name, SG::VarHandleKeyArray &hndArr, const std::string &doc, const SG::VarHandleKeyArrayType &)
 
Gaudi::Details::PropertyBase * declareProperty (const std::string &name, T &property, const std::string &doc, const SG::NotHandleType &)
 Declare a new Gaudi property. More...
 
Gaudi::Details::PropertyBase * declareProperty (const std::string &name, T &property, const std::string &doc="none")
 Declare a new Gaudi property. More...
 
void updateVHKA (Gaudi::Details::PropertyBase &)
 
MsgStream & msg () const
 
MsgStream & msg (const MSG::Level lvl) const
 
bool msgLvl (const MSG::Level lvl) const
 
 DeclareInterfaceID (ICaloClusterGPUPlotter, 1, 0)
 

Protected Member Functions

void renounceArray (SG::VarHandleKeyArray &handlesArray)
 remove all handles from I/O resolution More...
 
std::enable_if_t< std::is_void_v< std::result_of_t< decltype(&T::renounce)(T)> > &&!std::is_base_of_v< SG::VarHandleKeyArray, T > &&std::is_base_of_v< Gaudi::DataHandle, T >, void > renounce (T &h)
 
void extraDeps_update_handler (Gaudi::Details::PropertyBase &ExtraDeps)
 Add StoreName to extra input/output deps as needed. More...
 

Private Types

typedef ServiceHandle< StoreGateSvc > StoreGateSvc_t
 

Private Member Functions

StatusCode initialize_plotted_variables ()
 
StatusCode add_data (const EventContext &ctx, const CaloRecGPU::ConstantDataHolder &constant_data, const CaloRecGPU::Helpers::CPU_object< CaloRecGPU::CellInfoArr > &cell_info, const CaloRecGPU::Helpers::CPU_object< CaloRecGPU::CellStateArr > &cell_state, const CaloRecGPU::Helpers::CPU_object< CaloRecGPU::ClusterInfoArr > &clusters, const CaloRecGPU::Helpers::CPU_object< CaloRecGPU::ClusterMomentsArr > &moments, const std::string &tool_name) const
 
StatusCode add_combination (const EventContext &ctx, const CaloRecGPU::ConstantDataHolder &constant_data, const int index_1, const int index_2, const std::string &prefix, const bool match_in_energy, const bool match_without_shared, const bool match_perfectly) const
 
bool filter_tool_by_name (const std::string &tool_name) const
 Returns true if this tool should be plotted for. More...
 
StatusCode convert_to_GPU_data_structures (const EventContext &ctx, const CaloRecGPU::ConstantDataHolder &constant_data, const xAOD::CaloClusterContainer *cluster_collection_ptr, CaloRecGPU::Helpers::CPU_object< CaloRecGPU::CellInfoArr > &cell_info, CaloRecGPU::Helpers::CPU_object< CaloRecGPU::CellStateArr > &cell_state, CaloRecGPU::Helpers::CPU_object< CaloRecGPU::ClusterInfoArr > &clusters, CaloRecGPU::Helpers::CPU_object< CaloRecGPU::ClusterMomentsArr > &moments) const
 
StatusCode compactify_clusters (const EventContext &ctx, const CaloRecGPU::ConstantDataHolder &constant_data, const CaloRecGPU::Helpers::CPU_object< CaloRecGPU::CellInfoArr > &cell_info, CaloRecGPU::Helpers::CPU_object< CaloRecGPU::CellStateArr > &cell_state, CaloRecGPU::Helpers::CPU_object< CaloRecGPU::ClusterInfoArr > &clusters, CaloRecGPU::Helpers::CPU_object< CaloRecGPU::ClusterMomentsArr > &moments) const
 Remove invalid clusters, reorder by ET and update the tags accordingly. More...
 
StatusCode match_clusters (sample_comparisons_holder &sch, const CaloRecGPU::ConstantDataHolder &constant_data, const CaloRecGPU::CellInfoArr &cell_info, const CaloRecGPU::CellStateArr &cell_state_1, const CaloRecGPU::CellStateArr &cell_state_2, const CaloRecGPU::ClusterInfoArr &cluster_info_1, const CaloRecGPU::ClusterInfoArr &cluster_info_2, const CaloRecGPU::ClusterMomentsArr &, const CaloRecGPU::ClusterMomentsArr &, const bool match_in_energy, const bool match_without_shared) const
 
StatusCode match_clusters_perfectly (sample_comparisons_holder &sch, const CaloRecGPU::ConstantDataHolder &constant_data, const CaloRecGPU::CellInfoArr &cell_info, const CaloRecGPU::CellStateArr &cell_state_1, const CaloRecGPU::CellStateArr &cell_state_2, const CaloRecGPU::ClusterInfoArr &cluster_info_1, const CaloRecGPU::ClusterInfoArr &cluster_info_2, const CaloRecGPU::ClusterMomentsArr &, const CaloRecGPU::ClusterMomentsArr &, const bool match_without_shared) const
 
Gaudi::Details::PropertyBase & declareGaudiProperty (Gaudi::Property< T > &hndl, const SG::VarHandleKeyType &)
 specialization for handling Gaudi::Property<SG::VarHandleKey> More...
 
Gaudi::Details::PropertyBase & declareGaudiProperty (Gaudi::Property< T > &hndl, const SG::VarHandleKeyArrayType &)
 specialization for handling Gaudi::Property<SG::VarHandleKeyArray> More...
 
Gaudi::Details::PropertyBase & declareGaudiProperty (Gaudi::Property< T > &hndl, const SG::VarHandleType &)
 specialization for handling Gaudi::Property<SG::VarHandleBase> More...
 
Gaudi::Details::PropertyBase & declareGaudiProperty (Gaudi::Property< T > &t, const SG::NotHandleType &)
 specialization for handling everything that's not a Gaudi::Property<SG::VarHandleKey> or a <SG::VarHandleKeyArray> More...
 

Private Attributes

Gaudi::Property< float > m_termThreshold {this, "CellThreshold", 0., "Cell (terminal) threshold (in units of noise Sigma)"}
 Cell (terminal) threshold to use for cluster matching. More...
 
Gaudi::Property< float > m_growThreshold {this, "NeighborThreshold", 2., "Neighbor (grow) threshold (in units of noise Sigma)"}
 Neighbor (growing) threshold to use for cluster matching. More...
 
Gaudi::Property< float > m_seedThreshold {this, "SeedThreshold", 4., "Seed threshold (in units of noise Sigma)"}
 Seed threshold to use for cluster matching. More...
 
SG::ReadHandleKey< CaloCellContainer > m_cellsKey {this, "CellsName", "", "Name(s) of Cell Containers"}
 vector of names of the cell containers to use as input. More...
 
ToolHandle< GenericMonitoringTool > m_moniTool { this, "MonitoringTool", "", "Monitoring tool" }
 Monitoring tool. More...
 
Gaudi::Property< std::vector< SimpleSingleTool > > m_toolsToPlot {this, "ToolsToPlot", {}, "Tools to be plotted individually"}
 Tools to plot individually. More...
 
Gaudi::Property< std::vector< SimpleToolPair > > m_pairsToPlot {this, "PairsToPlot", {}, "Pairs of tools to be compared and plotted"}
 Pairs of tools to compare. More...
 
Gaudi::Property< MatchingOptions > m_matchingOptions {this, "ClusterMatchingParameters", {}, "Parameters for the cluster matching algorithm"}
 Option for adjusting the parameters for the cluster matching algorithm. More...
 
double m_min_similarity = 0.5
 Parameters for the cluster matching algorithm, for easier access. More...
 
double m_seed_weight = 5000.
 
double m_grow_weight = 250.
 
double m_terminal_weight = 10.
 
const CaloCell_ID * m_calo_id {nullptr}
 Pointer to Calo ID Helper. More...
 
std::map< std::string, int > m_toolsToCheckFor
 Map of the strings corresponding to all the tools that will be relevant for plotting (individually or in comparisons) to the index that will be used to identify the tool within the plotter. More...
 
std::map< std::string, std::string > m_toolToIdMap
 Maps tools to their respective identifying prefix for variables. More...
 
int m_numToolsToKeep = 0
 The number of tools that will actually need to be kept in memory for combined plotting. More...
 
std::vector< pair_to_plot > m_toolCombinations
 
std::map< std::string, std::atomic< size_t > > m_numClustersPerTool ATLAS_THREAD_SAFE
 Counts the total number of clusters per tool. More...
 
size_t m_numEvents = 0
 Counts the number of events. More...
 
CaloRecGPU::Helpers::separate_thread_holder< std::vector< per_tool_storage > > m_storageHolder ATLAS_THREAD_SAFE
 Stores the intermediate results needed for tool-level matching. More...
 
std::vector< bool > m_clusterPropertiesToDo
 Control which properties will actually be calculated and stored. More...
 
std::vector< bool > m_comparedClusterPropertiesToDo
 
std::vector< bool > m_extraComparedClusterPropertiesToDo
 
std::vector< bool > m_cellPropertiesToDo
 
std::vector< bool > m_comparedCellPropertiesToDo
 
std::vector< bool > m_cellTypesToDo
 
std::vector< bool > m_comparedCellTypesToDo
 
std::vector< bool > m_extraThingsToDo
 
bool m_doCells = false
 If no properties are asked for, skip the relevant loops entirely... More...
 
bool m_doClusters = false
 
bool m_doCombinedCells = false
 
bool m_doCombinedClusters = false
 
std::atomic< bool > m_plottedVariablesInitialized
 A flag to signal that the variables to be monitored have been detected based on the booked histograms. More...
 
std::mutex m_mutex
 This mutex is locked to ensure only one thread detects the monotired variables. More...
 
StoreGateSvc_t m_evtStore
 Pointer to StoreGate (event store by default) More...
 
StoreGateSvc_t m_detStore
 Pointer to StoreGate (detector store by default) More...
 
std::vector< SG::VarHandleKeyArray * > m_vhka
 
bool m_varHandleArraysDeclared
 

Detailed Description

Places (matched) cluster and cell properties in monitored variables to enable plotting with the Athena THistSvc instead of the custom solution that was being used previously. Its histograms can be configured as in a MonitoringTool.

Author
Nuno Fernandes nuno..nosp@m.dos..nosp@m.santo.nosp@m.s.fe.nosp@m.rnand.nosp@m.es@c.nosp@m.ern.c.nosp@m.h
Date
18 March 2023

Definition at line 40 of file CaloGPUClusterAndCellDataMonitor.h.

Member Typedef Documentation

◆ StoreGateSvc_t

typedef ServiceHandle<StoreGateSvc> AthCommonDataStore< AthCommonMsg< AlgTool > >::StoreGateSvc_t
privateinherited

Definition at line 388 of file AthCommonDataStore.h.

Constructor & Destructor Documentation

◆ CaloGPUClusterAndCellDataMonitor()

CaloGPUClusterAndCellDataMonitor::CaloGPUClusterAndCellDataMonitor ( const std::string &  type,
const std::string &  name,
const IInterface *  parent 
)

Definition at line 25 of file CaloGPUClusterAndCellDataMonitor.cxx.

25  :
26  AthAlgTool(type, name, parent),
27  m_plottedVariablesInitialized(false)
28 {
29  declareInterface<ICaloClusterGPUPlotter> (this);
30 }

◆ ~CaloGPUClusterAndCellDataMonitor()

virtual CaloGPUClusterAndCellDataMonitor::~CaloGPUClusterAndCellDataMonitor ( )
virtualdefault

Member Function Documentation

◆ add_combination()

StatusCode CaloGPUClusterAndCellDataMonitor::add_combination ( const EventContext &  ctx,
const CaloRecGPU::ConstantDataHolder &  constant_data,
const int  index_1,
const int  index_2,
const std::string &  prefix,
const bool  match_in_energy,
const bool  match_without_shared,
const bool  match_perfectly 
) const
private

Definition at line 1843 of file CaloGPUClusterAndCellDataMonitor.cxx.

1851 {
1852 
1853  //Note: Part of the work here is superfluous in the case
1854  // where we are monitoring the tools individually too,
1855  // but in the most generic case that is not guaranteed.
1856  // Partially wasted work, but it's cleaner than the alternative...
1857 
1858  std::vector<per_tool_storage> & store_vec = m_storageHolder.get_for_thread();
1859 
1860  const CaloRecGPU::CellInfoArr & cell_info_1 = store_vec[index_1].cell_info;
1861  const CaloRecGPU::CellStateArr & cell_state_1 = store_vec[index_1].cell_state;
1862  const CaloRecGPU::ClusterInfoArr & clusters_1 = store_vec[index_1].clusters;
1863  const CaloRecGPU::ClusterMomentsArr & moments_1 = store_vec[index_1].moments;
1864 
1865  const CaloRecGPU::CellInfoArr & cell_info_2 = store_vec[index_2].cell_info;
1866  const CaloRecGPU::CellStateArr & cell_state_2 = store_vec[index_2].cell_state;
1867  const CaloRecGPU::ClusterInfoArr & clusters_2 = store_vec[index_2].clusters;
1868  const CaloRecGPU::ClusterMomentsArr & moments_2 = store_vec[index_2].moments;
1869 
1870  sample_comparisons_holder sch;
1871 
1872  if (match_perfectly)
1873  {
1874  ATH_CHECK( match_clusters_perfectly(sch, constant_data, cell_info_1, cell_state_1, cell_state_2,
1875  clusters_1, clusters_2, moments_1, moments_2, match_without_shared) );
1876  }
1877  else
1878  {
1879  ATH_CHECK( match_clusters(sch, constant_data, cell_info_1, cell_state_1, cell_state_2,
1880  clusters_1, clusters_2, moments_1, moments_2, match_in_energy, match_without_shared) );
1881  }
1882 
1883  std::unordered_map<std::string, std::vector<double>> cluster_properties, cell_properties;
1884 
1885  std::unordered_map<std::string, long long int> cell_counts;
1886 
1887  std::vector<double> ref_size_vec(clusters_1.number, 0.), test_size_vec(clusters_2.number, 0.),
1888  ref_weighted_size_vec(clusters_1.number, 0.), test_weighted_size_vec(clusters_2.number, 0.),
1889  ref_diff_cells(clusters_1.number, 0.), test_diff_cells(clusters_2.number, 0.),
1890  ref_diff_cells_weight(clusters_1.number, 0.), test_diff_cells_weight(clusters_2.number, 0.);
1891  //We can store integers up to 2^53 on a double...
1892 
1893  long long int same_energy_1 = 0, same_energy_2 = 0,
1894  same_abs_energy_1 = 0, same_abs_energy_2 = 0,
1895  same_snr_1 = 0, same_snr_2 = 0,
1896  same_abs_snr_1 = 0, same_abs_snr_2 = 0,
1897  same_cluster_cells_count = 0, diff_cluster_cells_count = 0;
1898 
1899  std::set<double> energies_1, energies_2, snrs_1, snrs_2;
1900 
1901  if (m_doCombinedCells)
1902  {
1903  for (int cell = 0; cell < NCaloCells; ++cell)
1904  {
1905  if (!cell_info_1.is_valid(cell) || !cell_info_2.is_valid(cell))
1906  {
1907  continue;
1908  }
1909 
1910  apply_to_multi_class([&](const auto & prop, const size_t i)
1911  {
1912  if (m_comparedCellPropertiesToDo[i])
1913  {
1914  const auto prop_1 = prop.get_property(constant_data, cell_info_1, cell_state_1, clusters_1, moments_1, cell);
1915  const auto prop_2 = prop.get_property(constant_data, cell_info_2, cell_state_2, clusters_2, moments_2, cell);
1916 
1917  cell_properties[prop.name() + "_ref"].push_back(prop_1);
1918  cell_properties[prop.name() + "_test"].push_back(prop_2);
1919 
1920  cell_properties["delta_" + prop.name()].push_back(prop_2 - prop_1);
1921  cell_properties["delta_" + prop.name() + "_rel_ref"].push_back((prop_2 - prop_1) / protect_from_zero(std::abs(prop_1)));
1922  cell_properties["delta_" + prop.name() + "_rel_test"].push_back((prop_2 - prop_1) / protect_from_zero(std::abs(prop_2)));
1923  }
1924  }, BasicCellProperties{});
1925 
1926  apply_to_multi_class([&](const auto & prop, const size_t i)
1927  {
1928  if (m_comparedCellTypesToDo[i])
1929  {
1930  const auto is_1 = prop.is_type(constant_data, cell_info_1, cell_state_1, clusters_1, moments_1, cell);
1931  const auto is_2 = prop.is_type(constant_data, cell_info_2, cell_state_2, clusters_2, moments_2, cell);
1932 
1933  cell_counts["num_" + prop.name() + "_cells_ref"] += is_1;
1934  cell_counts["num_" + prop.name() + "_cells_test"] += is_2;
1935  cell_counts["delta_num_" + prop.name() + "_cells"] += is_2 - is_1;
1936  }
1937  }, BasicCellTypes{});
1938 
1939  const float this_energy_1 = cell_info_1.energy[cell];
1940  const float this_energy_2 = cell_info_2.energy[cell];
1941 
1942  if (m_extraThingsToDo[SameECellsCombined])
1943  {
1944 
1945  if (energies_1.count(this_energy_1))
1946  {
1947  ++same_energy_1;
1948  ++same_abs_energy_1;
1949  }
1950  else if (energies_1.count(-this_energy_1))
1951  {
1952  ++same_abs_energy_1;
1953  }
1954  energies_1.insert(this_energy_1);
1955 
1956  if (energies_2.count(this_energy_2))
1957  {
1958  ++same_energy_2;
1959  ++same_abs_energy_2;
1960  }
1961  else if (energies_2.count(-this_energy_2))
1962  {
1963  ++same_abs_energy_2;
1964  }
1965  energies_2.insert(this_energy_2);
1966  }
1967 
1968  if (m_extraThingsToDo[SameSNRCellsCombined])
1969  {
1970  const float this_snr_1 = this_energy_1 / protect_from_zero(constant_data.m_cell_noise->get_noise(cell, cell_info_1.gain[cell]));
1971 
1972  if (snrs_1.count(this_snr_1))
1973  {
1974  ++same_snr_1;
1975  ++same_abs_snr_1;
1976  }
1977  else if (snrs_1.count(-this_snr_1))
1978  {
1979  ++same_abs_snr_1;
1980  }
1981  snrs_1.insert(this_snr_1);
1982 
1983 
1984  const float this_snr_2 = this_energy_2 / protect_from_zero(constant_data.m_cell_noise->get_noise(cell, cell_info_2.gain[cell]));
1985 
1986  if (snrs_2.count(this_snr_2))
1987  {
1988  ++same_snr_2;
1989  ++same_abs_snr_2;
1990  }
1991  else if (snrs_2.count(-this_snr_2))
1992  {
1993  ++same_abs_snr_2;
1994  }
1995  snrs_2.insert(this_snr_2);
1996  }
1997 
1998  if (m_extraThingsToDo[DiffCells] || m_extraThingsToDo[ClusterComparedSize])
1999  {
2000 
2001  const ClusterTag ref_tag = cell_state_1.clusterTag[cell];
2002  const ClusterTag test_tag = cell_state_2.clusterTag[cell];
2003  int ref_c1 = -3, ref_c2 = -3, test_c1 = -3, test_c2 = -3;
2004  if (ref_tag.is_part_of_cluster())
2005  {
2006  ref_c1 = ref_tag.cluster_index();
2007  ref_c2 = ref_tag.is_shared_between_clusters() ? ref_tag.secondary_cluster_index() : -2;
2008  }
2009 
2010  if (test_tag.is_part_of_cluster())
2011  {
2012  test_c1 = test_tag.cluster_index();
2013  test_c2 = test_tag.is_shared_between_clusters() ? test_tag.secondary_cluster_index() : -2;
2014  }
2015 
2016  const int match_1 = test_c1 < 0 ? -1 : sch.t2r(test_c1);
2017  const int match_2 = test_c2 < 0 ? -1 : sch.t2r(test_c2);
2018 
2019  const float ref_rev_weight = float_unhack(ref_tag.secondary_cluster_weight());
2020  const float test_rev_weight = float_unhack(test_tag.secondary_cluster_weight());
2021 
2022  const float ref_weight = 1.0f - ref_rev_weight;
2023  const float test_weight = 1.0f - test_rev_weight;
2024 
2025  bool cell_is_diff = false;
2026 
2027  if (ref_c1 >= 0)
2028  {
2029  ref_size_vec[ref_c1] += 1;
2030  ref_weighted_size_vec[ref_c1] += ref_weight;
2031 #if CALORECGPU_DISABLE_STRICT_MATCHING
2032  if (!(ref_c1 == match_1 || ref_c1 == match_2 || (match_1 < 0 || match_2 < 0)))
2033 #else
2034  if (!(ref_c1 == match_1 || ref_c1 == match_2))
2035 #endif
2036  {
2037  cell_is_diff = true;
2038  ref_diff_cells[ref_c1] += 1;
2039  ref_diff_cells_weight[ref_c1] += ref_weight;
2040  }
2041  }
2042 
2043  if (ref_c2 >= 0)
2044  {
2045  ref_size_vec[ref_c2] += 1;
2046  ref_weighted_size_vec[ref_c2] += ref_rev_weight;
2047 #if CALORECGPU_DISABLE_STRICT_MATCHING
2048  if (!(ref_c2 == match_1 || ref_c2 == match_2 || (match_1 < 0 || match_2 < 0)))
2049 #else
2050  if (!(ref_c2 == match_1 || ref_c2 == match_2))
2051 #endif
2052  {
2053  cell_is_diff = true;
2054  ref_diff_cells[ref_c2] += 1;
2055  ref_diff_cells_weight[ref_c2] += ref_rev_weight;
2056  }
2057  }
2058 
2059  if (test_c1 >= 0)
2060  {
2061  test_size_vec[test_c1] += 1;
2062  test_weighted_size_vec[test_c1] += test_weight;
2063 #if CALORECGPU_DISABLE_STRICT_MATCHING
2064  if (match_1 >= 0 && !(match_1 == ref_c1 || match_1 == ref_c2 || (ref_c1 < 0 || ref_c2 < 0)))
2065 #else
2066  if (match_1 < 0 || !(match_1 == ref_c1 || match_1 == ref_c2))
2067 #endif
2068  {
2069  cell_is_diff = true;
2070  test_diff_cells[test_c1] += 1;
2071  test_diff_cells_weight[test_c1] += test_weight;
2072  }
2073  }
2074 
2075  if (test_c2 >= 0)
2076  {
2077  test_size_vec[test_c2] += 1;
2078  test_weighted_size_vec[test_c2] += test_rev_weight;
2079 #if CALORECGPU_DISABLE_STRICT_MATCHING
2080  if (match_2 >= 0 && !(match_2 == ref_c1 || match_2 == ref_c2 || (ref_c1 < 0 || ref_c2 < 0)))
2081 #else
2082  if (match_2 < 0 || !(match_2 == ref_c1 || match_2 == ref_c2))
2083 #endif
2084  {
2085  cell_is_diff = true;
2086  test_diff_cells[test_c2] += 1;
2087  test_diff_cells_weight[test_c2] += test_rev_weight;
2088  }
2089  }
2090 
2091  if (!cell_is_diff && (ref_c1 >= 0 || ref_c2 >= 0 || test_c1 >= 0 || test_c2 >= 0))
2092  {
2093  ++same_cluster_cells_count;
2094  }
2095  else if (cell_is_diff)
2096  {
2097  char message_buffer[256];
2098  snprintf(message_buffer, 256,
2099  "%7d | %18f || %6d | %6d | %6d | %6d || %6d | %6d || %016llX | %016llX",
2100  cell, this_energy_1 / protect_from_zero(constant_data.m_cell_noise->get_noise(cell, cell_info_1.gain[cell])),
2101  ref_c1, ref_c2, test_c1, test_c2,
2102  match_1, match_2,
2103  static_cast<tag_type>(ref_tag), static_cast<tag_type>(test_tag));
2104  ATH_MSG_DEBUG(message_buffer);
2105  ++diff_cluster_cells_count;
2106  }
2107 
2108  }
2109  }
2110  }
2111 
2112  if (m_doCombinedClusters)
2113  {
2114 
2115  for (int cluster = 0; cluster < clusters_1.number; ++cluster)
2116  {
2117  const int match = sch.r2t(cluster);
2118  if (match < 0)
2119  //The cluster isn't matched.
2120  {
2121  continue;
2122  }
2123 
2124  apply_to_multi_class([&](const auto & prop, const size_t i)
2125  {
2126  if (m_comparedClusterPropertiesToDo[i])
2127  {
2128  const auto prop_1 = prop.get_property(constant_data, cell_info_1, cell_state_1, clusters_1, moments_1, cluster);
2129  const auto prop_2 = prop.get_property(constant_data, cell_info_2, cell_state_2, clusters_2, moments_2, match);
2130 
2131  cluster_properties[prop.name() + "_ref"].push_back(prop_1);
2132  cluster_properties[prop.name() + "_test"].push_back(prop_2);
2133 
2134  cluster_properties["delta_" + prop.name()].push_back(prop_2 - prop_1);
2135  cluster_properties["delta_" + prop.name() + "_rel_ref"].push_back((prop_2 - prop_1) / protect_from_zero(std::abs(prop_1)));
2136  cluster_properties["delta_" + prop.name() + "_rel_test"].push_back((prop_2 - prop_1) / protect_from_zero(std::abs(prop_2)));
2137  }
2138  }, BasicClusterProperties{});
2139 
2140  apply_to_multi_class([&](const auto & prop, const size_t i)
2141  {
2142  if (m_extraComparedClusterPropertiesToDo[i])
2143  {
2144  cluster_properties[prop.name()].push_back(prop.get_property(constant_data, cell_info_1, cell_state_1, clusters_1, moments_1, cluster,
2145  cell_info_2, cell_state_2, clusters_2, moments_2, match));
2146  }
2147  }, ComparedClusterProperties{});
2148 
2149  if (m_extraThingsToDo[ClusterComparedSize])
2150  {
2151  cluster_properties["size_ref"].push_back(ref_size_vec[cluster]);
2152  cluster_properties["size_test"].push_back(test_size_vec[match]);
2153  cluster_properties["delta_size"].push_back(ref_size_vec[cluster] - test_size_vec[match]);
2154  cluster_properties["delta_size_rel_ref"].push_back((ref_size_vec[cluster] - test_size_vec[match]) / protect_from_zero(ref_size_vec[cluster]));
2155  cluster_properties["delta_size_rel_test"].push_back((ref_size_vec[cluster] - test_size_vec[match]) / protect_from_zero(test_size_vec[match]));
2156 
2157  cluster_properties["weighted_size_ref"].push_back(ref_weighted_size_vec[cluster]);
2158  cluster_properties["weighted_size_test"].push_back(test_weighted_size_vec[match]);
2159  cluster_properties["delta_weighted_size"].push_back(ref_weighted_size_vec[cluster] - test_weighted_size_vec[match]);
2160  cluster_properties["delta_weighted_size_rel_ref"].push_back((ref_weighted_size_vec[cluster] - test_weighted_size_vec[match]) / protect_from_zero(ref_weighted_size_vec[cluster]));
2161  cluster_properties["delta_weighted_size_rel_test"].push_back((ref_weighted_size_vec[cluster] - test_weighted_size_vec[match]) / protect_from_zero(test_weighted_size_vec[match]));
2162  }
2163 
2164  if (m_extraThingsToDo[DiffCells])
2165  {
2166  cluster_properties["diff_cells_ref"].push_back(ref_diff_cells[cluster]);
2167  cluster_properties["diff_cells_ref_rel_size"].push_back(ref_diff_cells[cluster] / protect_from_zero(ref_size_vec[cluster]));
2168  cluster_properties["diff_cells_test"].push_back(test_diff_cells[match]);
2169  cluster_properties["diff_cells_test_rel_size"].push_back(test_diff_cells[match] / protect_from_zero(test_size_vec[match]));
2170  cluster_properties["diff_cells"].push_back(ref_diff_cells[cluster] + test_diff_cells[match]);
2171 
2172  cluster_properties["weighted_diff_cells_ref"].push_back(ref_diff_cells_weight[cluster]);
2173  cluster_properties["weighted_diff_cells_ref_rel_size"].push_back(ref_diff_cells_weight[cluster] / protect_from_zero(ref_weighted_size_vec[cluster]));
2174  cluster_properties["weighted_diff_cells_test"].push_back(test_diff_cells_weight[match]);
2175  cluster_properties["weighted_diff_cells_test_rel_size"].push_back(test_diff_cells_weight[match] / protect_from_zero(test_weighted_size_vec[match]));
2176  cluster_properties["weighted_diff_cells"].push_back(ref_diff_cells_weight[cluster] + test_diff_cells_weight[match]);
2177  }
2178  }
2179  }
2180 
2181  using coll_type = decltype(Monitored::Collection("", std::declval<std::vector<double> &>()));
2182  using scalar_type = decltype(Monitored::Scalar("", std::declval<long long int>()));
2183 
2184  std::vector<coll_type> collections;
2185  std::vector<scalar_type> count_scalars;
2186  std::vector<std::reference_wrapper<Monitored::IMonitoredVariable>> cluster_group, cell_group, counts_group;
2187 
2188  collections.reserve(cluster_properties.size() + cell_properties.size());
2189  count_scalars.reserve(cell_counts.size() + 6 * 3);
2190  cluster_group.reserve(cluster_properties.size());
2191  cell_group.reserve(cell_properties.size());
2192  counts_group.reserve(cell_counts.size() + 3 + 6 * 3);
2193 
2194  auto add_count_vars = [&](const std::string & name, const long long int ref_num, const long long int test_num)
2195  {
2196  count_scalars.emplace_back(Monitored::Scalar(prefix + "_" + name + "_ref", ref_num));
2197  counts_group.push_back(std::ref(count_scalars.back()));
2198 
2199  count_scalars.emplace_back(Monitored::Scalar(prefix + "_" + name + "_test", test_num));
2200  counts_group.push_back(std::ref(count_scalars.back()));
2201 
2202  count_scalars.emplace_back(Monitored::Scalar(prefix + "_delta_" + name, test_num - ref_num));
2203  counts_group.push_back(std::ref(count_scalars.back()));
2204  };
2205 
2206  add_count_vars("num_clusters", clusters_1.number, clusters_2.number);
2207  add_count_vars("num_unmatched_clusters", sch.ref_unmatched(), sch.test_unmatched());
2208 
2209  add_count_vars("num_same_E_cells", same_energy_1, same_energy_2);
2210  add_count_vars("num_same_abs_E_cells", same_abs_energy_1, same_abs_energy_2);
2211  add_count_vars("num_same_SNR_cells", same_snr_1, same_snr_2);
2212  add_count_vars("num_same_abs_SNR_cells", same_abs_snr_1, same_abs_snr_2);
2213 
2214  auto mon_total_unmatched = Monitored::Scalar(prefix + "_num_unmatched_clusters", sch.ref_unmatched() + sch.test_unmatched());
2215  auto mon_same_cluster_cell = Monitored::Scalar(prefix + "_same_cluster_cells", same_cluster_cells_count);
2216  auto mon_diff_cluster_cell = Monitored::Scalar(prefix + "_diff_cluster_cells", diff_cluster_cells_count);
2217 
2218  counts_group.push_back(std::ref(mon_total_unmatched));
2219  counts_group.push_back(std::ref(mon_same_cluster_cell));
2220  counts_group.push_back(std::ref(mon_diff_cluster_cell));
2221 
2222  for (const auto & k_v : cluster_properties)
2223  {
2224  collections.emplace_back(Monitored::Collection(prefix + "_cluster_" + k_v.first, k_v.second));
2225  cluster_group.push_back(std::ref(collections.back()));
2226  }
2227 
2228  for (const auto & k_v : cell_properties)
2229  {
2230  collections.emplace_back(Monitored::Collection(prefix + "_cell_" + k_v.first, k_v.second));
2231  cell_group.push_back(std::ref(collections.back()));
2232  }
2233 
2234  for (const auto & k_v : cell_counts)
2235  {
2236  count_scalars.emplace_back(Monitored::Scalar(prefix + "_" + k_v.first, k_v.second));
2237  counts_group.push_back(std::ref(count_scalars.back()));
2238  }
2239 
2240  auto monitor_clusters = Monitored::Group(m_moniTool, cluster_group);
2241  auto monitor_cells = Monitored::Group(m_moniTool, cell_group);
2242  auto monitor_counts = Monitored::Group(m_moniTool, counts_group);
2243 
2244  return StatusCode::SUCCESS;
2245 }

◆ add_data()

StatusCode CaloGPUClusterAndCellDataMonitor::add_data ( const EventContext &  ctx,
const CaloRecGPU::ConstantDataHolder &  constant_data,
const CaloRecGPU::Helpers::CPU_object< CaloRecGPU::CellInfoArr > &  cell_info,
const CaloRecGPU::Helpers::CPU_object< CaloRecGPU::CellStateArr > &  cell_state,
const CaloRecGPU::Helpers::CPU_object< CaloRecGPU::ClusterInfoArr > &  clusters,
const CaloRecGPU::Helpers::CPU_object< CaloRecGPU::ClusterMomentsArr > &  moments,
const std::string &  tool_name 
) const
private

Definition at line 1657 of file CaloGPUClusterAndCellDataMonitor.cxx.

1664 {
1665  m_numClustersPerTool[tool_name].fetch_add(clusters->number);
1666 
1667  const std::string prefix = m_toolToIdMap.at(tool_name);
1668 
1669  const int index = m_toolsToCheckFor.at(tool_name);
1670 
1671  if (index >= 0 && m_numToolsToKeep > 0)
1672  {
1673  std::vector<per_tool_storage> & store_vec = m_storageHolder.get_for_thread();
1674  store_vec[index].cell_info = *cell_info;
1675  store_vec[index].cell_state = *cell_state;
1676  store_vec[index].clusters = *clusters;
1677  store_vec[index].moments = *moments;
1678  }
1679 
1680  if (prefix != "")
1681  //Tools that are not meant to be plotted individually
1682  //have the empty string as a prefix.
1683  {
1684  std::unordered_map<std::string, std::vector<double>> cluster_properties, cell_properties;
1685 
1686  std::unordered_map<std::string, long long int> cell_counts;
1687 
1688  cluster_properties["size"].resize(clusters->number, 0.);
1689  cluster_properties["weighted_size"].resize(clusters->number, 0.);
1690 
1691  long long int same_energy = 0, same_abs_energy = 0, same_snr = 0, same_abs_snr = 0;
1692 
1693  std::set<double> energies, snrs;
1694 
1695  if (m_doCells)
1696  {
1697 
1698  for (int cell = 0; cell < NCaloCells; ++cell)
1699  {
1700  if (!cell_info->is_valid(cell))
1701  {
1702  continue;
1703  }
1704 
1705  apply_to_multi_class([&](const auto & prop, const size_t i)
1706  {
1707  if (m_cellPropertiesToDo[i])
1708  {
1709  cell_properties[prop.name()].push_back(prop.get_property(constant_data, *cell_info, *cell_state, *clusters, *moments, cell));
1710  }
1711  }, BasicCellProperties{});
1712 
1713  apply_to_multi_class([&](const auto & prop, const size_t i)
1714  {
1715  if (m_cellTypesToDo[i])
1716  {
1717  cell_counts[prop.name()] += prop.is_type(constant_data, *cell_info, *cell_state, *clusters, *moments, cell);
1718  }
1719  }, BasicCellTypes{});
1720 
1721  const float this_energy = cell_info->energy[cell];
1722 
1723  if (m_extraThingsToDo[SameECells])
1724  {
1725 
1726  if (energies.count(this_energy))
1727  {
1728  ++same_energy;
1729  ++same_abs_energy;
1730  }
1731  else if (energies.count(-this_energy))
1732  {
1733  ++same_abs_energy;
1734  }
1735  energies.insert(this_energy);
1736  }
1737 
1738  if (m_extraThingsToDo[SameSNRCells])
1739  {
1740 
1741  const float this_snr = this_energy / protect_from_zero(constant_data.m_cell_noise->get_noise(cell, cell_info->gain[cell]));
1742 
1743  if (snrs.count(this_snr))
1744  {
1745  ++same_snr;
1746  ++same_abs_snr;
1747  }
1748  else if (snrs.count(-this_snr))
1749  {
1750  ++same_abs_snr;
1751  }
1752  snrs.insert(this_snr);
1753  }
1754 
1755  if (m_extraThingsToDo[ClusterSize])
1756  {
1757  const ClusterTag tag = cell_state->clusterTag[cell];
1758  const float weight = float_unhack(tag.secondary_cluster_weight());
1759  if (tag.is_part_of_cluster())
1760  {
1761  cluster_properties["size"][tag.cluster_index()] += 1;
1762  cluster_properties["weighted_size"][tag.cluster_index()] += 1.0f - weight;
1763  if (tag.is_shared_between_clusters())
1764  {
1765  cluster_properties["size"][tag.secondary_cluster_index()] += 1;
1766  cluster_properties["weighted_size"][tag.secondary_cluster_index()] += weight;
1767  }
1768  }
1769  }
1770  }
1771  }
1772 
1773  if (m_doClusters)
1774  {
1775  for (int cluster = 0; cluster < clusters->number; ++cluster)
1776  {
1777  apply_to_multi_class([&](const auto & prop, const size_t i)
1778  {
1779  if (m_clusterPropertiesToDo[i])
1780  {
1781  cluster_properties[prop.name()].push_back(prop.get_property(constant_data, *cell_info, *cell_state, *clusters, *moments, cluster));
1782  }
1783  }, BasicClusterProperties{});
1784  }
1785  }
1786 
1787  using coll_type = decltype(Monitored::Collection("", std::declval<std::vector<double> &>()));
1788  using scalar_type = decltype(Monitored::Scalar("", std::declval<long long int>()));
1789 
1790  std::vector<coll_type> collections;
1791  std::vector<scalar_type> count_scalars;
1792  std::vector<std::reference_wrapper<Monitored::IMonitoredVariable>> cluster_group, cell_group, counts_group;
1793 
1794  collections.reserve(cluster_properties.size() + cell_properties.size());
1795  count_scalars.reserve(cell_counts.size());
1796  cluster_group.reserve(cluster_properties.size());
1797  cell_group.reserve(cell_properties.size());
1798  counts_group.reserve(cell_counts.size() + 5);
1799 
1800  auto mon_clus_num = Monitored::Scalar(prefix + "_num_clusters", clusters->number);
1801  auto mon_same_energy = Monitored::Scalar(prefix + "_num_same_E_cells", same_energy);
1802  auto mon_same_abs_energy = Monitored::Scalar(prefix + "_num_same_abs_E_cells", same_abs_energy);
1803  auto mon_same_snr = Monitored::Scalar(prefix + "_num_same_SNR_cells", same_snr);
1804  auto mon_same_abs_snr = Monitored::Scalar(prefix + "_num_same_abs_SNR_cells", same_abs_snr);
1805 
1806  counts_group.push_back(std::ref(mon_clus_num));
1807  counts_group.push_back(std::ref(mon_same_energy));
1808  counts_group.push_back(std::ref(mon_same_abs_energy));
1809  counts_group.push_back(std::ref(mon_same_snr));
1810  counts_group.push_back(std::ref(mon_same_abs_snr));
1811 
1812  //If we're not doing these plots,
1813  //we're still saving,
1814  //which is slightly inefficient, but.. let's not complicate.
1815 
1816  for (const auto & k_v : cluster_properties)
1817  {
1818  collections.emplace_back(Monitored::Collection(prefix + "_cluster_" + k_v.first, k_v.second));
1819  cluster_group.push_back(std::ref(collections.back()));
1820  }
1821 
1822  for (const auto & k_v : cell_properties)
1823  {
1824  collections.emplace_back(Monitored::Collection(prefix + "_cell_" + k_v.first, k_v.second));
1825  cell_group.push_back(std::ref(collections.back()));
1826  }
1827 
1828  for (const auto & k_v : cell_counts)
1829  {
1830  count_scalars.emplace_back(Monitored::Scalar(prefix + "_num_" + k_v.first + "_cells", k_v.second));
1831  counts_group.push_back(std::ref(count_scalars.back()));
1832  }
1833 
1834  auto monitor_clusters = Monitored::Group(m_moniTool, cluster_group);
1835  auto monitor_cells = Monitored::Group(m_moniTool, cell_group);
1836  auto monitor_counts = Monitored::Group(m_moniTool, counts_group);
1837 
1838  }
1839  return StatusCode::SUCCESS;
1840 }

◆ compactify_clusters()

StatusCode CaloGPUClusterAndCellDataMonitor::compactify_clusters ( const EventContext &  ctx,
const CaloRecGPU::ConstantDataHolder &  constant_data,
const CaloRecGPU::Helpers::CPU_object< CaloRecGPU::CellInfoArr > &  cell_info,
CaloRecGPU::Helpers::CPU_object< CaloRecGPU::CellStateArr > &  cell_state,
CaloRecGPU::Helpers::CPU_object< CaloRecGPU::ClusterInfoArr > &  clusters,
CaloRecGPU::Helpers::CPU_object< CaloRecGPU::ClusterMomentsArr > &  moments 
) const
private

Remove invalid clusters, reorder by ET and update the tags accordingly.

Definition at line 481 of file CaloGPUClusterAndCellDataMonitor.cxx.

487 {
488  std::map<int, int> tag_map;
489 
490  std::vector<int> cluster_order(clusters->number);
491 
492  std::iota(cluster_order.begin(), cluster_order.end(), 0);
493 
494  std::sort(cluster_order.begin(), cluster_order.end(), [&](const int a, const int b)
495  {
496  if (clusters->seedCellID[a] < 0)
497  {
498  return false;
499  //This means that clusters with no cells
500  //(marked as invalid) always compare lower,
501  //so they appear in the end.
502  }
503  else if (clusters->seedCellID[b] < 0)
504  {
505  return true;
506  }
507  return clusters->clusterEt[a] > clusters->clusterEt[b];
508  } );
509 
510  int real_cluster_numbers = clusters->number;
511 
512  for (size_t i = 0; i < cluster_order.size(); ++i)
513  {
514  const int this_id = cluster_order[i];
515  if (clusters->seedCellID[this_id] < 0)
516  {
517  tag_map[this_id] = -1;
518  --real_cluster_numbers;
519  }
520  else
521  {
522  tag_map[this_id] = i;
523  }
524  }
525 
526  const Helpers::CPU_object<ClusterInfoArr> temp_clusters(clusters);
527  const Helpers::CPU_object<ClusterMomentsArr> temp_moments(moments);
528 
529  clusters->number = real_cluster_numbers;
530 
531  for (int i = 0; i < temp_clusters->number; ++i)
532  {
533  clusters->clusterEnergy[i] = temp_clusters->clusterEnergy[cluster_order[i]];
534  clusters->clusterEt[i] = temp_clusters->clusterEt[cluster_order[i]];
535  clusters->clusterEta[i] = temp_clusters->clusterEta[cluster_order[i]];
536  clusters->clusterPhi[i] = temp_clusters->clusterPhi[cluster_order[i]];
537  clusters->seedCellID[i] = temp_clusters->seedCellID[cluster_order[i]];
538  for (int j = 0; j < NumSamplings; ++j)
539  {
540  moments->energyPerSample[j][i] = temp_moments->energyPerSample[j][cluster_order[i]];
541  moments->maxEPerSample[j][i] = temp_moments->maxEPerSample[j][cluster_order[i]];
542  moments->maxPhiPerSample[j][i] = temp_moments->maxPhiPerSample[j][cluster_order[i]];
543  moments->maxEtaPerSample[j][i] = temp_moments->maxEtaPerSample[j][cluster_order[i]];
544  moments->etaPerSample[j][i] = temp_moments->etaPerSample[j][cluster_order[i]];
545  moments->phiPerSample[j][i] = temp_moments->phiPerSample[j][cluster_order[i]];
546  }
547  moments->time[i] = temp_moments->time[cluster_order[i]];
548  moments->firstPhi[i] = temp_moments->firstPhi[cluster_order[i]];
549  moments->firstEta[i] = temp_moments->firstEta[cluster_order[i]];
550  moments->secondR[i] = temp_moments->secondR[cluster_order[i]];
551  moments->secondLambda[i] = temp_moments->secondLambda[cluster_order[i]];
552  moments->deltaPhi[i] = temp_moments->deltaPhi[cluster_order[i]];
553  moments->deltaTheta[i] = temp_moments->deltaTheta[cluster_order[i]];
554  moments->deltaAlpha[i] = temp_moments->deltaAlpha[cluster_order[i]];
555  moments->centerX[i] = temp_moments->centerX[cluster_order[i]];
556  moments->centerY[i] = temp_moments->centerY[cluster_order[i]];
557  moments->centerZ[i] = temp_moments->centerZ[cluster_order[i]];
558  moments->centerMag[i] = temp_moments->centerMag[cluster_order[i]];
559  moments->centerLambda[i] = temp_moments->centerLambda[cluster_order[i]];
560  moments->lateral[i] = temp_moments->lateral[cluster_order[i]];
561  moments->longitudinal[i] = temp_moments->longitudinal[cluster_order[i]];
562  moments->engFracEM[i] = temp_moments->engFracEM[cluster_order[i]];
563  moments->engFracMax[i] = temp_moments->engFracMax[cluster_order[i]];
564  moments->engFracCore[i] = temp_moments->engFracCore[cluster_order[i]];
565  moments->firstEngDens[i] = temp_moments->firstEngDens[cluster_order[i]];
566  moments->secondEngDens[i] = temp_moments->secondEngDens[cluster_order[i]];
567  moments->isolation[i] = temp_moments->isolation[cluster_order[i]];
568  moments->engBadCells[i] = temp_moments->engBadCells[cluster_order[i]];
569  moments->nBadCells[i] = temp_moments->nBadCells[cluster_order[i]];
570  moments->nBadCellsCorr[i] = temp_moments->nBadCellsCorr[cluster_order[i]];
571  moments->badCellsCorrE[i] = temp_moments->badCellsCorrE[cluster_order[i]];
572  moments->badLArQFrac[i] = temp_moments->badLArQFrac[cluster_order[i]];
573  moments->engPos[i] = temp_moments->engPos[cluster_order[i]];
574  moments->significance[i] = temp_moments->significance[cluster_order[i]];
575  moments->cellSignificance[i] = temp_moments->cellSignificance[cluster_order[i]];
576  moments->cellSigSampling[i] = temp_moments->cellSigSampling[cluster_order[i]];
577  moments->avgLArQ[i] = temp_moments->avgLArQ[cluster_order[i]];
578  moments->avgTileQ[i] = temp_moments->avgTileQ[cluster_order[i]];
579  moments->engBadHVCells[i] = temp_moments->engBadHVCells[cluster_order[i]];
580  moments->nBadHVCells[i] = temp_moments->nBadHVCells[cluster_order[i]];
581  moments->PTD[i] = temp_moments->PTD[cluster_order[i]];
582  moments->mass[i] = temp_moments->mass[cluster_order[i]];
583  moments->EMProbability[i] = temp_moments->EMProbability[cluster_order[i]];
584  moments->hadWeight[i] = temp_moments->hadWeight[cluster_order[i]];
585  moments->OOCweight[i] = temp_moments->OOCweight[cluster_order[i]];
586  moments->DMweight[i] = temp_moments->DMweight[cluster_order[i]];
587  moments->tileConfidenceLevel[i] = temp_moments->tileConfidenceLevel[cluster_order[i]];
588  moments->secondTime[i] = temp_moments->secondTime[cluster_order[i]];
589  for (int j = 0; j < NumSamplings; ++j)
590  {
591  moments->nCellSampling[j][i] = temp_moments->nCellSampling[j][cluster_order[i]];
592  }
593  moments->nExtraCellSampling[i] = temp_moments->nExtraCellSampling[cluster_order[i]];
594  moments->numCells[i] = temp_moments->numCells[cluster_order[i]];
595  moments->vertexFraction[i] = temp_moments->vertexFraction[cluster_order[i]];
596  moments->nVertexFraction[i] = temp_moments->nVertexFraction[cluster_order[i]];
597  moments->etaCaloFrame[i] = temp_moments->etaCaloFrame[cluster_order[i]];
598  moments->phiCaloFrame[i] = temp_moments->phiCaloFrame[cluster_order[i]];
599  moments->eta1CaloFrame[i] = temp_moments->eta1CaloFrame[cluster_order[i]];
600  moments->phi1CaloFrame[i] = temp_moments->phi1CaloFrame[cluster_order[i]];
601  moments->eta2CaloFrame[i] = temp_moments->eta2CaloFrame[cluster_order[i]];
602  moments->phi2CaloFrame[i] = temp_moments->phi2CaloFrame[cluster_order[i]];
603  moments->engCalibTot[i] = temp_moments->engCalibTot[cluster_order[i]];
604  moments->engCalibOutL[i] = temp_moments->engCalibOutL[cluster_order[i]];
605  moments->engCalibOutM[i] = temp_moments->engCalibOutM[cluster_order[i]];
606  moments->engCalibOutT[i] = temp_moments->engCalibOutT[cluster_order[i]];
607  moments->engCalibDeadL[i] = temp_moments->engCalibDeadL[cluster_order[i]];
608  moments->engCalibDeadM[i] = temp_moments->engCalibDeadM[cluster_order[i]];
609  moments->engCalibDeadT[i] = temp_moments->engCalibDeadT[cluster_order[i]];
610  moments->engCalibEMB0[i] = temp_moments->engCalibEMB0[cluster_order[i]];
611  moments->engCalibEME0[i] = temp_moments->engCalibEME0[cluster_order[i]];
612  moments->engCalibTileG3[i] = temp_moments->engCalibTileG3[cluster_order[i]];
613  moments->engCalibDeadTot[i] = temp_moments->engCalibDeadTot[cluster_order[i]];
614  moments->engCalibDeadEMB0[i] = temp_moments->engCalibDeadEMB0[cluster_order[i]];
615  moments->engCalibDeadTile0[i] = temp_moments->engCalibDeadTile0[cluster_order[i]];
616  moments->engCalibDeadTileG3[i] = temp_moments->engCalibDeadTileG3[cluster_order[i]];
617  moments->engCalibDeadEME0[i] = temp_moments->engCalibDeadEME0[cluster_order[i]];
618  moments->engCalibDeadHEC0[i] = temp_moments->engCalibDeadHEC0[cluster_order[i]];
619  moments->engCalibDeadFCAL[i] = temp_moments->engCalibDeadFCAL[cluster_order[i]];
620  moments->engCalibDeadLeakage[i] = temp_moments->engCalibDeadLeakage[cluster_order[i]];
621  moments->engCalibDeadUnclass[i] = temp_moments->engCalibDeadUnclass[cluster_order[i]];
622  moments->engCalibFracEM[i] = temp_moments->engCalibFracEM[cluster_order[i]];
623  moments->engCalibFracHad[i] = temp_moments->engCalibFracHad[cluster_order[i]];
624  moments->engCalibFracRest[i] = temp_moments->engCalibFracRest[cluster_order[i]];
625  }
626 
627  for (int i = 0; i < NCaloCells; ++i)
628  {
629  if (!cell_info->is_valid(i))
630  {
631  continue;
632  }
633  const ClusterTag this_tag = cell_state->clusterTag[i];
634  if (!this_tag.is_part_of_cluster())
635  {
636  cell_state->clusterTag[i] = ClusterTag::make_invalid_tag();
637  }
638  else if (this_tag.is_part_of_cluster())
639  {
640  const int old_idx = this_tag.cluster_index();
641  const int new_idx = tag_map[old_idx];
642  const int old_idx2 = this_tag.is_shared_between_clusters() ? this_tag.secondary_cluster_index() : -1;
643  const int new_idx2 = old_idx2 >= 0 ? tag_map[old_idx2] : -1;
644  if (new_idx < 0 && new_idx2 < 0)
645  {
646  cell_state->clusterTag[i] = ClusterTag::make_invalid_tag();
647  }
648  else if (new_idx < 0)
649  {
650  cell_state->clusterTag[i] = ClusterTag::make_tag(new_idx2);
651  }
652  else if (new_idx2 < 0)
653  {
654  cell_state->clusterTag[i] = ClusterTag::make_tag(new_idx);
655  }
656  else
657  {
658  cell_state->clusterTag[i] = ClusterTag::make_tag(new_idx, this_tag.secondary_cluster_weight(), new_idx2);
659  }
660  }
661  }
662 
663  return StatusCode::SUCCESS;
664 }

◆ convert_to_GPU_data_structures()

StatusCode CaloGPUClusterAndCellDataMonitor::convert_to_GPU_data_structures ( const EventContext &  ctx,
const CaloRecGPU::ConstantDataHolder &  constant_data,
const xAOD::CaloClusterContainer *  cluster_collection_ptr,
CaloRecGPU::Helpers::CPU_object< CaloRecGPU::CellInfoArr > &  cell_info,
CaloRecGPU::Helpers::CPU_object< CaloRecGPU::CellStateArr > &  cell_state,
CaloRecGPU::Helpers::CPU_object< CaloRecGPU::ClusterInfoArr > &  clusters,
CaloRecGPU::Helpers::CPU_object< CaloRecGPU::ClusterMomentsArr > &  moments 
) const
private

Definition at line 265 of file CaloGPUClusterAndCellDataMonitor.cxx.

272 {
273  SG::ReadHandle<CaloCellContainer> cell_collection(m_cellsKey, ctx);
274  if ( !cell_collection.isValid() )
275  {
276  ATH_MSG_ERROR( " Cannot retrieve CaloCellContainer: " << cell_collection.name() );
277  return StatusCode::FAILURE;
278  }
279 
280  ret_info.allocate();
281 
282  if (cluster_collection != nullptr)
283  {
284  ret_state.allocate();
285  ret_clusts.allocate();
286  ret_moments.allocate();
287  }
288 
289  for (int i = 0; i < NCaloCells; ++i)
290  {
291  ret_info->energy[i] = 0;
292  ret_info->gain[i] = GainConversion::invalid_gain();
293  ret_info->time[i] = 0;
294  ret_info->qualityProvenance[i] = 0;
295 
296  if (cluster_collection != nullptr)
297  {
298  ret_state->clusterTag[i] = ClusterTag::make_invalid_tag();
299  }
300  }
301 
302  for (CaloCellContainer::const_iterator iCells = cell_collection->begin(); iCells != cell_collection->end(); ++iCells)
303  {
304  const CaloCell * cell = (*iCells);
305 
306  const int index = m_calo_id->calo_cell_hash(cell->ID());
307 
308  const float energy = cell->energy();
309 
310  const unsigned int gain = GainConversion::from_standard_gain(cell->gain());
311 
312  ret_info->energy[index] = energy;
313  ret_info->gain[index] = gain;
314  ret_info->time[index] = cell->time();
315  ret_info->qualityProvenance[index] = QualityProvenance{cell->quality(), cell->provenance()};
316 
317  }
318 
319  if (cluster_collection != nullptr)
320  {
321  const auto cluster_end = cluster_collection->end();
322  auto cluster_iter = cluster_collection->begin();
323 
324  for (int cluster_number = 0; cluster_iter != cluster_end; ++cluster_iter, ++cluster_number )
325  {
326  const xAOD::CaloCluster * cluster = (*cluster_iter);
327  const CaloClusterCellLink * cell_links = cluster->getCellLinks();
328  if (!cell_links)
329  {
330  ATH_MSG_ERROR("Can't get valid links to CaloCells (CaloClusterCellLink)!");
331  return StatusCode::FAILURE;
332  }
333 
334  ret_clusts->clusterEnergy[cluster_number] = cluster->e();
335  ret_clusts->clusterEt[cluster_number] = cluster->et();
336  ret_clusts->clusterEta[cluster_number] = cluster->eta();
337  ret_clusts->clusterPhi[cluster_number] = cluster->phi();
338  ret_clusts->seedCellID[cluster_number] = m_calo_id->calo_cell_hash(cluster->cell_begin()->ID());
339  for (int i = 0; i < NumSamplings; ++i)
340  {
341  ret_moments->energyPerSample[i][cluster_number] = cluster->eSample((CaloSampling::CaloSample) i);
342  ret_moments->maxEPerSample[i][cluster_number] = cluster->energy_max((CaloSampling::CaloSample) i);
343  ret_moments->maxPhiPerSample[i][cluster_number] = cluster->phimax((CaloSampling::CaloSample) i);
344  ret_moments->maxEtaPerSample[i][cluster_number] = cluster->etamax((CaloSampling::CaloSample) i);
345  ret_moments->etaPerSample[i][cluster_number] = cluster->etaSample((CaloSampling::CaloSample) i);
346  ret_moments->phiPerSample[i][cluster_number] = cluster->phiSample((CaloSampling::CaloSample) i);
347  ret_moments->nCellSampling[i][cluster_number] = cluster->numberCellsInSampling((CaloSampling::CaloSample) i);
348  }
349  ret_moments->time[cluster_number] = cluster->time();
350  ret_moments->firstPhi[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::FIRST_PHI);
351  ret_moments->firstEta[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::FIRST_ETA);
352  ret_moments->secondR[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::SECOND_R);
353  ret_moments->secondLambda[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::SECOND_LAMBDA);
354  ret_moments->deltaPhi[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::DELTA_PHI);
355  ret_moments->deltaTheta[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::DELTA_THETA);
356  ret_moments->deltaAlpha[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::DELTA_ALPHA);
357  ret_moments->centerX[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::CENTER_X);
358  ret_moments->centerY[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::CENTER_Y);
359  ret_moments->centerZ[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::CENTER_Z);
360  ret_moments->centerMag[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::CENTER_MAG);
361  ret_moments->centerLambda[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::CENTER_LAMBDA);
362  ret_moments->lateral[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::LATERAL);
363  ret_moments->longitudinal[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::LONGITUDINAL);
364  ret_moments->engFracEM[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::ENG_FRAC_EM);
365  ret_moments->engFracMax[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::ENG_FRAC_MAX);
366  ret_moments->engFracCore[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::ENG_FRAC_CORE);
367  ret_moments->firstEngDens[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::FIRST_ENG_DENS);
368  ret_moments->secondEngDens[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::SECOND_ENG_DENS);
369  ret_moments->isolation[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::ISOLATION);
370  ret_moments->engBadCells[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::ENG_BAD_CELLS);
371  ret_moments->nBadCells[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::N_BAD_CELLS);
372  ret_moments->nBadCellsCorr[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::N_BAD_CELLS_CORR);
373  ret_moments->badCellsCorrE[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::BAD_CELLS_CORR_E);
374  ret_moments->badLArQFrac[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::BADLARQ_FRAC);
375  ret_moments->engPos[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::ENG_POS);
376  ret_moments->significance[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::SIGNIFICANCE);
377  ret_moments->cellSignificance[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::CELL_SIGNIFICANCE);
378  ret_moments->cellSigSampling[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::CELL_SIG_SAMPLING);
379  ret_moments->avgLArQ[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::AVG_LAR_Q);
380  ret_moments->avgTileQ[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::AVG_TILE_Q);
381  ret_moments->engBadHVCells[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::ENG_BAD_HV_CELLS);
382  ret_moments->nBadHVCells[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::N_BAD_HV_CELLS);
383  ret_moments->PTD[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::PTD);
384  ret_moments->mass[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::MASS);
385  ret_moments->EMProbability[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::EM_PROBABILITY);
386  ret_moments->hadWeight[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::HAD_WEIGHT);
387  ret_moments->OOCweight[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::OOC_WEIGHT);
388  ret_moments->DMweight[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::DM_WEIGHT);
389  ret_moments->tileConfidenceLevel[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::TILE_CONFIDENCE_LEVEL);
390  ret_moments->secondTime[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::SECOND_TIME);
391  ret_moments->nExtraCellSampling[cluster_number] = cluster->numberCellsInSampling(CaloSampling::EME2, true);
392  ret_moments->numCells[cluster_number] = cluster->numberCells();
393  ret_moments->vertexFraction[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::VERTEX_FRACTION);
394  ret_moments->nVertexFraction[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::NVERTEX_FRACTION);
395  ret_moments->etaCaloFrame[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::ETACALOFRAME);
396  ret_moments->phiCaloFrame[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::PHICALOFRAME);
397  ret_moments->eta1CaloFrame[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::ETA1CALOFRAME);
398  ret_moments->phi1CaloFrame[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::PHI1CALOFRAME);
399  ret_moments->eta2CaloFrame[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::ETA2CALOFRAME);
400  ret_moments->phi2CaloFrame[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::PHI2CALOFRAME);
401  ret_moments->engCalibTot[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::ENG_CALIB_TOT);
402  ret_moments->engCalibOutL[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::ENG_CALIB_OUT_L);
403  ret_moments->engCalibOutM[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::ENG_CALIB_OUT_M);
404  ret_moments->engCalibOutT[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::ENG_CALIB_OUT_T);
405  ret_moments->engCalibDeadL[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::ENG_CALIB_DEAD_L);
406  ret_moments->engCalibDeadM[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::ENG_CALIB_DEAD_M);
407  ret_moments->engCalibDeadT[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::ENG_CALIB_DEAD_T);
408  ret_moments->engCalibEMB0[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::ENG_CALIB_EMB0);
409  ret_moments->engCalibEME0[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::ENG_CALIB_EME0);
410  ret_moments->engCalibTileG3[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::ENG_CALIB_TILEG3);
411  ret_moments->engCalibDeadTot[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::ENG_CALIB_DEAD_TOT);
412  ret_moments->engCalibDeadEMB0[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::ENG_CALIB_DEAD_EMB0);
413  ret_moments->engCalibDeadTile0[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::ENG_CALIB_DEAD_TILE0);
414  ret_moments->engCalibDeadTileG3[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::ENG_CALIB_DEAD_TILEG3);
415  ret_moments->engCalibDeadEME0[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::ENG_CALIB_DEAD_EME0);
416  ret_moments->engCalibDeadHEC0[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::ENG_CALIB_DEAD_HEC0);
417  ret_moments->engCalibDeadFCAL[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::ENG_CALIB_DEAD_FCAL);
418  ret_moments->engCalibDeadLeakage[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::ENG_CALIB_DEAD_LEAKAGE);
419  ret_moments->engCalibDeadUnclass[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::ENG_CALIB_DEAD_UNCLASS);
420  ret_moments->engCalibFracEM[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::ENG_CALIB_FRAC_EM);
421  ret_moments->engCalibFracHad[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::ENG_CALIB_FRAC_HAD);
422  ret_moments->engCalibFracRest[cluster_number] = cluster->getMomentValue(xAOD::CaloCluster::ENG_CALIB_FRAC_REST);
423  for (auto it = cell_links->begin(); it != cell_links->end(); ++it)
424  {
425  const int cell_ID = m_calo_id->calo_cell_hash(it->ID());
426  const float weight = it.weight();
427 
428  uint32_t weight_as_int = 0;
429  std::memcpy(&weight_as_int, &weight, sizeof(float));
430  //On the platforms we expect to be running this, it should be fine.
431  //Still UB.
432  //With C++20, we could do that bit-cast thing.
433 
434  if (weight_as_int == 0)
435  {
436  weight_as_int = 1;
437  //Subnormal,
438  //but just to distinguish from
439  //a non-shared cluster.
440  }
441 
442  const ClusterTag other_tag = ret_state->clusterTag[cell_ID];
443 
444  const int other_index = other_tag.is_part_of_cluster() ? other_tag.cluster_index() : -1;
445 
446  if (other_index < 0)
447  {
448  if (weight < 0.5f)
449  {
450  ret_state->clusterTag[cell_ID] = ClusterTag::make_tag(cluster_number, weight_as_int, 0);
451  }
452  else
453  {
454  ret_state->clusterTag[cell_ID] = ClusterTag::make_tag(cluster_number);
455  }
456  }
457  else if (weight > 0.5f)
458  {
459  ret_state->clusterTag[cell_ID] = ClusterTag::make_tag(cluster_number, other_tag.secondary_cluster_weight(), other_index);
460  }
461  else if (weight == 0.5f)
462  //Unlikely, but...
463  {
464  const int max_cluster = cluster_number > other_index ? cluster_number : other_index;
465  const int min_cluster = cluster_number > other_index ? other_index : cluster_number;
466  ret_state->clusterTag[cell_ID] = ClusterTag::make_tag(max_cluster, weight_as_int, min_cluster);
467  }
468  else /*if (weight < 0.5f)*/
469  {
470  ret_state->clusterTag[cell_ID] = ClusterTag::make_tag(other_index, weight_as_int, cluster_number);
471  }
472  }
473  }
474 
475  ret_clusts->number = cluster_collection->size();
476  }
477 
478  return StatusCode::SUCCESS;
479 }

◆ declareGaudiProperty() [1/4]

Gaudi::Details::PropertyBase& AthCommonDataStore< AthCommonMsg< AlgTool > >::declareGaudiProperty ( Gaudi::Property< T > &  hndl,
const SG::VarHandleKeyArrayType &   
)
inlineprivateinherited

specialization for handling Gaudi::Property<SG::VarHandleKeyArray>

Definition at line 170 of file AthCommonDataStore.h.

172  {
173  return *AthCommonDataStore<PBASE>::declareProperty(hndl.name(),
174  hndl.value(),
175  hndl.documentation());
176 
177  }

◆ declareGaudiProperty() [2/4]

Gaudi::Details::PropertyBase& AthCommonDataStore< AthCommonMsg< AlgTool > >::declareGaudiProperty ( Gaudi::Property< T > &  hndl,
const SG::VarHandleKeyType &   
)
inlineprivateinherited

specialization for handling Gaudi::Property<SG::VarHandleKey>

Definition at line 156 of file AthCommonDataStore.h.

158  {
159  return *AthCommonDataStore<PBASE>::declareProperty(hndl.name(),
160  hndl.value(),
161  hndl.documentation());
162 
163  }

◆ declareGaudiProperty() [3/4]

Gaudi::Details::PropertyBase& AthCommonDataStore< AthCommonMsg< AlgTool > >::declareGaudiProperty ( Gaudi::Property< T > &  hndl,
const SG::VarHandleType &   
)
inlineprivateinherited

specialization for handling Gaudi::Property<SG::VarHandleBase>

Definition at line 184 of file AthCommonDataStore.h.

186  {
187  return *AthCommonDataStore<PBASE>::declareProperty(hndl.name(),
188  hndl.value(),
189  hndl.documentation());
190  }

◆ declareGaudiProperty() [4/4]

Gaudi::Details::PropertyBase& AthCommonDataStore< AthCommonMsg< AlgTool > >::declareGaudiProperty ( Gaudi::Property< T > &  t,
const SG::NotHandleType &   
)
inlineprivateinherited

specialization for handling everything that's not a Gaudi::Property<SG::VarHandleKey> or a <SG::VarHandleKeyArray>

Definition at line 199 of file AthCommonDataStore.h.

200  {
201  return PBASE::declareProperty(t);
202  }

◆ DeclareInterfaceID()

ICaloClusterGPUPlotter::DeclareInterfaceID ( ICaloClusterGPUPlotter  ,
1  ,
0   
)
inherited

◆ declareProperty() [1/6]

Gaudi::Details::PropertyBase* AthCommonDataStore< AthCommonMsg< AlgTool > >::declareProperty ( const std::string &  name,
SG::VarHandleBase &  hndl,
const std::string &  doc,
const SG::VarHandleType &   
)
inlineinherited

Declare a new Gaudi property.

Parameters
nameName of the property.
hndlObject holding the property value.
docDocumentation string for the property.

This is the version for types that derive from SG::VarHandleBase. The property value object is put on the input and output lists as appropriate; then we forward to the base class.

Definition at line 245 of file AthCommonDataStore.h.

249  {
250  this->declare(hndl.vhKey());
251  hndl.vhKey().setOwner(this);
252 
253  return PBASE::declareProperty(name,hndl,doc);
254  }

◆ declareProperty() [2/6]

Gaudi::Details::PropertyBase* AthCommonDataStore< AthCommonMsg< AlgTool > >::declareProperty ( const std::string &  name,
SG::VarHandleKey &  hndl,
const std::string &  doc,
const SG::VarHandleKeyType &   
)
inlineinherited

Declare a new Gaudi property.

Parameters
nameName of the property.
hndlObject holding the property value.
docDocumentation string for the property.

This is the version for types that derive from SG::VarHandleKey. The property value object is put on the input and output lists as appropriate; then we forward to the base class.

Definition at line 221 of file AthCommonDataStore.h.

225  {
226  this->declare(hndl);
227  hndl.setOwner(this);
228 
229  return PBASE::declareProperty(name,hndl,doc);
230  }

◆ declareProperty() [3/6]

Gaudi::Details::PropertyBase* AthCommonDataStore< AthCommonMsg< AlgTool > >::declareProperty ( const std::string &  name,
SG::VarHandleKeyArray &  hndArr,
const std::string &  doc,
const SG::VarHandleKeyArrayType &   
)
inlineinherited

Definition at line 259 of file AthCommonDataStore.h.

263  {
264 
265  // std::ostringstream ost;
266  // ost << Algorithm::name() << " VHKA declareProp: " << name
267  // << " size: " << hndArr.keys().size()
268  // << " mode: " << hndArr.mode()
269  // << " vhka size: " << m_vhka.size()
270  // << "\n";
271  // debug() << ost.str() << endmsg;
272 
273  hndArr.setOwner(this);
274  m_vhka.push_back(&hndArr);
275 
276  Gaudi::Details::PropertyBase* p = PBASE::declareProperty(name, hndArr, doc);
277  if (p != 0) {
278  p->declareUpdateHandler(&AthCommonDataStore<PBASE>::updateVHKA, this);
279  } else {
280  ATH_MSG_ERROR("unable to call declareProperty on VarHandleKeyArray "
281  << name);
282  }
283 
284  return p;
285 
286  }

◆ declareProperty() [4/6]

Gaudi::Details::PropertyBase* AthCommonDataStore< AthCommonMsg< AlgTool > >::declareProperty ( const std::string &  name,
T &  property,
const std::string &  doc,
const SG::NotHandleType &   
)
inlineinherited

Declare a new Gaudi property.

Parameters
nameName of the property.
propertyObject holding the property value.
docDocumentation string for the property.

This is the generic version, for types that do not derive from SG::VarHandleKey. It just forwards to the base class version of declareProperty.

Definition at line 333 of file AthCommonDataStore.h.

337  {
338  return PBASE::declareProperty(name, property, doc);
339  }

◆ declareProperty() [5/6]

Gaudi::Details::PropertyBase* AthCommonDataStore< AthCommonMsg< AlgTool > >::declareProperty ( const std::string &  name,
T &  property,
const std::string &  doc = "none" 
)
inlineinherited

Declare a new Gaudi property.

Parameters
nameName of the property.
propertyObject holding the property value.
docDocumentation string for the property.

This dispatches to either the generic declareProperty or the one for VarHandle/Key/KeyArray.

Definition at line 352 of file AthCommonDataStore.h.

355  {
356  typedef typename SG::HandleClassifier<T>::type htype;
357  return declareProperty (name, property, doc, htype());
358  }

◆ declareProperty() [6/6]

Gaudi::Details::PropertyBase& AthCommonDataStore< AthCommonMsg< AlgTool > >::declareProperty ( Gaudi::Property< T > &  t)
inlineinherited

Definition at line 145 of file AthCommonDataStore.h.

145  {
146  typedef typename SG::HandleClassifier<T>::type htype;
147  return AthCommonDataStore<PBASE>::declareGaudiProperty(t, htype());
148  }

◆ detStore()

const ServiceHandle<StoreGateSvc>& AthCommonDataStore< AthCommonMsg< AlgTool > >::detStore ( ) const
inlineinherited

The standard StoreGateSvc/DetectorStore Returns (kind of) a pointer to the StoreGateSvc.

Definition at line 95 of file AthCommonDataStore.h.

95 { return m_detStore; }

◆ evtStore() [1/2]

ServiceHandle<StoreGateSvc>& AthCommonDataStore< AthCommonMsg< AlgTool > >::evtStore ( )
inlineinherited

The standard StoreGateSvc (event store) Returns (kind of) a pointer to the StoreGateSvc.

Definition at line 85 of file AthCommonDataStore.h.

85 { return m_evtStore; }

◆ evtStore() [2/2]

const ServiceHandle<StoreGateSvc>& AthCommonDataStore< AthCommonMsg< AlgTool > >::evtStore ( ) const
inlineinherited

The standard StoreGateSvc (event store) Returns (kind of) a pointer to the StoreGateSvc.

Definition at line 90 of file AthCommonDataStore.h.

90 { return m_evtStore; }

◆ extraDeps_update_handler()

void AthCommonDataStore< AthCommonMsg< AlgTool > >::extraDeps_update_handler ( Gaudi::Details::PropertyBase &  ExtraDeps)
protectedinherited

Add StoreName to extra input/output deps as needed.

use the logic of the VarHandleKey to parse the DataObjID keys supplied via the ExtraInputs and ExtraOuputs Properties to add the StoreName if it's not explicitly given

◆ filter_tool_by_name()

bool CaloGPUClusterAndCellDataMonitor::filter_tool_by_name ( const std::string &  tool_name) const
private

Returns true if this tool should be plotted for.

Definition at line 255 of file CaloGPUClusterAndCellDataMonitor.cxx.

257 {
258  ATH_MSG_DEBUG("Checking : '" << tool_name << "': " << m_toolsToCheckFor.count(tool_name));
259  return m_toolsToCheckFor.count(tool_name) > 0;
260 }

◆ finalize_plots()

StatusCode CaloGPUClusterAndCellDataMonitor::finalize_plots ( ) const
overridevirtual

Implements ICaloClusterGPUPlotter.

Definition at line 101 of file CaloGPUClusterAndCellDataMonitor.cxx.

102 {
103  //Well, not do plots, just monitor the number of events and the total number of clusters...
104 
105  auto mon_num_events = Monitored::Scalar("num_events", m_numEvents);
106 
107  for (const auto & k_v : m_toolToIdMap)
108  {
109  auto mon_num_clust = Monitored::Scalar(k_v.second + "_num_total_clusters", m_numClustersPerTool.at(k_v.first).load());
110  }
111 
112  return StatusCode::SUCCESS;
113 }

◆ initialize()

StatusCode CaloGPUClusterAndCellDataMonitor::initialize ( )
overridevirtual

Definition at line 32 of file CaloGPUClusterAndCellDataMonitor.cxx.

33 {
34  ATH_CHECK( m_cellsKey.initialize() );
35 
36  ATH_CHECK( detStore()->retrieve(m_calo_id, "CaloCell_ID") );
37 
38  const std::string this_name = this->name();
39 
40  const std::string algorithm_name_prefix = this_name.substr(0, this_name.rfind('.'));
41  //This is so we take into account the fact that tools
42  //are prefixed with the parent algorithm's name.
43 
44  auto final_string = [& algorithm_name_prefix](const std::string & unpref_str) -> std::string
45  {
46  return algorithm_name_prefix + "." + unpref_str;
47  };
48 
49  const MatchingOptions opts = m_matchingOptions;
50 
51  m_min_similarity = opts.min_similarity;
52  m_seed_weight = opts.seed_w;
53  m_grow_weight = opts.grow_w;
54  m_terminal_weight = opts.term_w;
55 
56  for (const auto & tool : m_toolsToPlot)
57  {
58  const std::string tool_name = final_string(tool.tool);
59  m_toolToIdMap[tool_name] = tool.plot_id;
60  m_toolsToCheckFor[tool_name] = -1;
61  }
62 
63  auto add_tool_from_pair = [this](const std::string & name) -> int
64  {
65  if (!m_toolsToCheckFor.count(name))
66  {
67  m_toolsToCheckFor[name] = m_numToolsToKeep;
68  m_toolToIdMap[name] = "";
69  return m_numToolsToKeep++;
70  }
71  else
72  {
73  const int current = m_toolsToCheckFor[name];
74  if (current >= 0)
75  {
76  return current;
77  }
78  else
79  {
80  m_toolsToCheckFor[name] = m_numToolsToKeep;
81  return m_numToolsToKeep++;
82  }
83  }
84  };
85 
86  for (const auto & pair : m_pairsToPlot)
87  {
88  const int first_index = add_tool_from_pair(final_string(pair.tool_ref));
89  const int second_index = add_tool_from_pair(final_string(pair.tool_test));
90  m_toolCombinations.emplace_back(pair_to_plot{first_index, second_index, pair.plot_id,
91  pair.match_in_energy,
92  pair.match_without_shared,
93  pair.match_perfectly});
94  }
95 
96  ATH_CHECK( m_moniTool.retrieve() );
97 
98  return StatusCode::SUCCESS;
99 }

◆ initialize_plotted_variables()

StatusCode CaloGPUClusterAndCellDataMonitor::initialize_plotted_variables ( )
private

Definition at line 1513 of file CaloGPUClusterAndCellDataMonitor.cxx.

1514 {
1515  const std::vector<std::string> histo_strings = m_moniTool->histogramService()->getHists();
1516  //Small problem: other histograms with matching names.
1517  //Mitigated by the fact that we use cell_<property> and cluster_<property>...
1518 
1519  m_clusterPropertiesToDo.resize(BasicClusterProperties::size(), false);
1520  m_comparedClusterPropertiesToDo.resize(BasicClusterProperties::size(), false);
1521  m_extraComparedClusterPropertiesToDo.resize(ComparedClusterProperties::size(), false);
1522  m_cellPropertiesToDo.resize(BasicCellProperties::size(), false);
1523  m_comparedCellPropertiesToDo.resize(BasicCellProperties::size(), false);
1524  m_cellTypesToDo.resize(BasicCellTypes::size(), false);
1525  m_comparedCellTypesToDo.resize(BasicCellTypes::size(), false);
1526  m_extraThingsToDo.resize(ExtraThingsSize, false);
1527 
1528  auto string_contains = [](const std::string & container, const std::string & contained) -> bool
1529  {
1530  return container.find(contained) != std::string::npos;
1531  };
1532 
1533  auto search_lambda = [&](const auto & prop, const size_t count, bool & check,
1534  const std::string & str, std::vector<bool> & to_do,
1535  const std::string & prefix = "", const std::string & suffix = "")
1536  {
1537  if (string_contains(str, prefix + prop.name() + suffix))
1538  {
1539  to_do[count] = true;
1540  check = true;
1541  }
1542  };
1543 
1544  for (const auto & str : histo_strings)
1545  {
1546  bool found = false;
1547 
1548  apply_to_multi_class(search_lambda, BasicCellProperties{}, found, str, m_cellPropertiesToDo, "_cell_");
1549  apply_to_multi_class(search_lambda, BasicCellTypes{}, found, str, m_cellTypesToDo, "_", "_cells");
1550 
1551  if (found)
1552  {
1553  m_doCells = true;
1554  }
1555 
1556  found = false;
1557 
1558  apply_to_multi_class(search_lambda, BasicClusterProperties{}, found, str, m_clusterPropertiesToDo, "_cluster_");
1559 
1560  if (found)
1561  {
1562  m_doClusters = true;
1563  }
1564 
1565  found = false;
1566 
1567  apply_to_multi_class(search_lambda, BasicCellProperties{}, found, str, m_comparedCellPropertiesToDo, "_cell_delta_");
1568  apply_to_multi_class(search_lambda, BasicCellProperties{}, found, str, m_comparedCellPropertiesToDo, "_cell_", "_ref");
1569  apply_to_multi_class(search_lambda, BasicCellProperties{}, found, str, m_comparedCellPropertiesToDo, "_cell_", "_test");
1570  apply_to_multi_class(search_lambda, BasicCellTypes{}, found, str, m_comparedCellTypesToDo, "num_ref_", "_cells");
1571  apply_to_multi_class(search_lambda, BasicCellTypes{}, found, str, m_comparedCellTypesToDo, "num_test_", "_cells");
1572  apply_to_multi_class(search_lambda, BasicCellTypes{}, found, str, m_comparedCellTypesToDo, "delta_", "_cells");
1573 
1574  if (found)
1575  {
1576  m_doCombinedCells = true;
1577  }
1578 
1579  found = false;
1580 
1581  apply_to_multi_class(search_lambda, BasicClusterProperties{}, found, str, m_comparedClusterPropertiesToDo, "_cluster_delta_", "");
1582  apply_to_multi_class(search_lambda, BasicClusterProperties{}, found, str, m_comparedClusterPropertiesToDo, "_cluster_", "_ref");
1583  apply_to_multi_class(search_lambda, BasicClusterProperties{}, found, str, m_comparedClusterPropertiesToDo, "_cluster_", "_test");
1584  apply_to_multi_class(search_lambda, ComparedClusterProperties{}, found, str, m_extraComparedClusterPropertiesToDo);
1585 
1586  if (found)
1587  {
1588  m_doCombinedClusters = true;
1589  }
1590 
1591  if ( string_contains(str, "cluster_size_ref") ||
1592  string_contains(str, "cluster_size_test") ||
1593  string_contains(str, "cluster_delta_size") ||
1594  string_contains(str, "cluster_weighted_size_ref") ||
1595  string_contains(str, "cluster_weighted_size_test") ||
1596  string_contains(str, "cluster_delta_weighted_size") )
1597  {
1598  m_extraThingsToDo[ClusterComparedSize] = true;
1599  m_doCombinedCells = true;
1600  m_doCombinedClusters = true;
1601  }
1602  else if ( string_contains(str, "cluster_size") ||
1603  string_contains(str, "cluster_weighted_size") )
1604  {
1605  m_extraThingsToDo[ClusterSize] = true;
1606  m_doCells = true;
1607  m_doClusters = true;
1608  }
1609 
1610  if (string_contains(str, "cluster_diff_cells"))
1611  {
1612  m_extraThingsToDo[DiffCells] = true;
1613  m_doCombinedCells = true;
1614  m_doCombinedClusters = true;
1615  }
1616 
1617  if ( string_contains(str, "_num_same_E_cells_ref") ||
1618  string_contains(str, "_num_same_E_cells_test") ||
1619  string_contains(str, "delta_num_same_E_cells") ||
1620  string_contains(str, "_num_same_abs_E_cells_ref") ||
1621  string_contains(str, "_num_same_abs_E_cells_test") ||
1622  string_contains(str, "delta_num_same_abs_E_cells") )
1623  {
1624  m_extraThingsToDo[SameECellsCombined] = true;
1625  m_doCombinedCells = true;
1626  }
1627  else if ( string_contains(str, "_num_same_E_cells") ||
1628  string_contains(str, "_num_same_abs_E_cells") )
1629  {
1630  m_extraThingsToDo[SameECells] = true;
1631  m_doCells = true;
1632  }
1633 
1634  if ( string_contains(str, "_num_same_SNR_cells_ref") ||
1635  string_contains(str, "_num_same_SNR_cells_test") ||
1636  string_contains(str, "delta_num_same_SNR_cells") ||
1637  string_contains(str, "_num_same_abs_SNR_cells_ref") ||
1638  string_contains(str, "_num_same_abs_SNR_cells_test") ||
1639  string_contains(str, "delta_num_same_abs_SNR_cells") )
1640  {
1641  m_extraThingsToDo[SameSNRCellsCombined] = true;
1642  m_doCombinedCells = true;
1643  }
1644  else if ( string_contains(str, "_num_same_SNR_cells") ||
1645  string_contains(str, "_num_same_abs_SNR_cells") )
1646  {
1647  m_extraThingsToDo[SameSNRCells] = true;
1648  m_doCells = true;
1649  }
1650  }
1651 
1652  return StatusCode::SUCCESS;
1653 
1654 }

◆ inputHandles()

virtual std::vector<Gaudi::DataHandle*> AthCommonDataStore< AthCommonMsg< AlgTool > >::inputHandles ( ) const
overridevirtualinherited

Return this algorithm's input handles.

We override this to include handle instances from key arrays if they have not yet been declared. See comments on updateVHKA.

◆ match_clusters()

StatusCode CaloGPUClusterAndCellDataMonitor::match_clusters ( sample_comparisons_holder &  sch,
const CaloRecGPU::ConstantDataHolder &  constant_data,
const CaloRecGPU::CellInfoArr &  cell_info,
const CaloRecGPU::CellStateArr &  cell_state_1,
const CaloRecGPU::CellStateArr &  cell_state_2,
const CaloRecGPU::ClusterInfoArr &  cluster_info_1,
const CaloRecGPU::ClusterInfoArr &  cluster_info_2,
const CaloRecGPU::ClusterMomentsArr &  ,
const CaloRecGPU::ClusterMomentsArr &  ,
const bool  match_in_energy,
const bool  match_without_shared 
) const
private

Definition at line 717 of file CaloGPUClusterAndCellDataMonitor.cxx.

728 {
729  sch.r2t_table.clear();
730  sch.r2t_table.resize(cluster_info_1.number, -1);
731 
732  sch.t2r_table.clear();
733  sch.t2r_table.resize(cluster_info_2.number, -1);
734 
735  std::vector<double> similarity_map(cluster_info_1.number * cluster_info_2.number, 0.);
736 
737  std::vector<double> ref_normalization(cluster_info_1.number, 0.);
738  std::vector<double> test_normalization(cluster_info_2.number, 0.);
739 
740  for (int i = 0; i < NCaloCells; ++i)
741  {
742  const ClusterTag ref_tag = cell_state_1.clusterTag[i];
743  const ClusterTag test_tag = cell_state_2.clusterTag[i];
744 
745  if (!cell_info.is_valid(i))
746  {
747  continue;
748  }
749 
750  double SNR = 0.00001;
751 
752  if (!cell_info.is_bad(*(constant_data.m_geometry), i))
753  {
754  const int gain = cell_info.gain[i];
755 
756  const double cellNoise = constant_data.m_cell_noise->get_noise(i, gain);
757  if (std::isfinite(cellNoise) && cellNoise > 0.0f)
758  {
759  SNR = std::abs(cell_info.energy[i] / cellNoise);
760  }
761  }
762 
763  const double quantity = ( match_in_energy ? std::abs(cell_info.energy[i]) : SNR );
764  const double weight = (quantity + 1e-8) *
765  ( SNR > m_seedThreshold ? (match_in_energy ? 1000 : m_seed_weight) :
766  (
767  SNR > m_growThreshold ? (match_in_energy ? 950 : m_grow_weight) :
768  (
769  SNR > m_termThreshold ? (match_in_energy ? 900 : m_terminal_weight) : (match_in_energy ? 100 : 0)
770  )
771  )
772  );
773  int ref_c1 = -1, ref_c2 = -1, test_c1 = -1, test_c2 = -1;
774 
775  if (ref_tag.is_part_of_cluster())
776  {
777  if (match_without_shared && ref_tag.is_shared_between_clusters())
778  {
779  continue;
780  }
781  ref_c1 = ref_tag.cluster_index();
782  ref_c2 = ref_tag.is_shared_between_clusters() ? ref_tag.secondary_cluster_index() : ref_c1;
783  }
784 
785  if (test_tag.is_part_of_cluster())
786  {
787  if (match_without_shared && test_tag.is_shared_between_clusters())
788  {
789  continue;
790  }
791  test_c1 = test_tag.cluster_index();
792  test_c2 = test_tag.is_shared_between_clusters() ? test_tag.secondary_cluster_index() : test_c1;
793  }
794 
795  float ref_rev_cw = float_unhack(ref_tag.secondary_cluster_weight());
796  float test_rev_cw = float_unhack(test_tag.secondary_cluster_weight());
797 
798  float ref_cw = 1.0f - ref_rev_cw;
799  float test_cw = 1.0f - test_rev_cw;
800 
801  if (ref_c1 >= int(cluster_info_1.number) || ref_c2 >= int(cluster_info_1.number) ||
802  test_c1 >= int(cluster_info_2.number) || test_c2 >= int(cluster_info_2.number) )
803  {
804  ATH_MSG_DEBUG( "Error in matches: " << i << " " << ref_c1 << " " << ref_c2 << " "
805  << test_c1 << " " << test_c2 << " ("
806  << cluster_info_1.number << " | " << cluster_info_2.number << ")" );
807  continue;
808  }
809 
810  if (ref_c1 >= 0 && test_c1 >= 0)
811  {
812  similarity_map[test_c1 * cluster_info_1.number + ref_c1] += weight * ref_cw * test_cw;
813  similarity_map[test_c1 * cluster_info_1.number + ref_c2] += weight * ref_rev_cw * test_cw;
814  similarity_map[test_c2 * cluster_info_1.number + ref_c1] += weight * ref_cw * test_rev_cw;
815  similarity_map[test_c2 * cluster_info_1.number + ref_c2] += weight * ref_rev_cw * test_rev_cw;
816  }
817  if (ref_c1 >= 0)
818  {
819  ref_normalization[ref_c1] += weight * ref_cw * ref_cw;
820  ref_normalization[ref_c2] += weight * ref_rev_cw * ref_rev_cw;
821  }
822  if (test_c1 >= 0)
823  {
824  test_normalization[test_c1] += weight * test_cw * test_cw;
825  test_normalization[test_c2] += weight * test_rev_cw * test_rev_cw;
826  }
827  }
828 
829  for (int testc = 0; testc < cluster_info_2.number; ++testc)
830  {
831  const double test_norm = test_normalization[testc] + double(test_normalization[testc] == 0.);
832  for (int refc = 0; refc < cluster_info_1.number; ++refc)
833  {
834  const double ref_norm = ref_normalization[refc] + double(ref_normalization[refc] == 0.);
835  similarity_map[testc * cluster_info_1.number + refc] /= std::sqrt(ref_norm * test_norm);
836  }
837  }
838 
839  //In essence, the Gale-Shapley Algorithm
840 
841  std::vector<std::vector<int>> sorted_GPU_matches;
842 
843  sorted_GPU_matches.reserve(cluster_info_2.number);
844 
845  for (int testc = 0; testc < cluster_info_2.number; ++testc)
846  {
847  std::vector<int> sorter(cluster_info_1.number);
848  std::iota(sorter.begin(), sorter.end(), 0);
849 
850  std::sort(sorter.begin(), sorter.end(),
851  [&](const int a, const int b)
852  {
853  const double a_weight = similarity_map[testc * cluster_info_1.number + a];
854  const double b_weight = similarity_map[testc * cluster_info_1.number + b];
855  return a_weight > b_weight;
856  }
857  );
858 
859  size_t wanted_size = 0;
860 
861  for (; wanted_size < sorter.size(); ++wanted_size)
862  {
863  const double match_weight = similarity_map[testc * cluster_info_1.number + sorter[wanted_size]];
864  if (match_weight < m_min_similarity)
865  {
866  break;
867  }
868  }
869 
870  //Yeah, we could do a binary search for best worst-case complexity,
871  //but we are expecting 1~2 similar clusters and the rest garbage,
872  //so we're expecting only 1~2 iterations.
873  //This actually means all that sorting is way way overkill,
874  //but we must make sure in the most general case that this works...
875 
876  sorter.resize(wanted_size);
877 
878  sorted_GPU_matches.push_back(sorter);
879  }
880 
881  int num_iter = 0;
882 
883  constexpr int max_iter = 32;
884 
885  std::vector<double> matched_weights(cluster_info_1.number, -1.);
886 
887  std::vector<size_t> skipped_matching(cluster_info_2.number, 0);
888 
889  for (int stop_counter = 0; stop_counter < cluster_info_2.number && num_iter < max_iter; ++num_iter)
890  {
891  stop_counter = 0;
892  for (int testc = 0; testc < int(sorted_GPU_matches.size()); ++testc)
893  {
894  if (skipped_matching[testc] < sorted_GPU_matches[testc].size())
895  {
896  const int match_c = sorted_GPU_matches[testc][skipped_matching[testc]];
897  const double match_weight = similarity_map[testc * cluster_info_1.number + match_c];
898  if (match_weight >= m_min_similarity && match_weight > matched_weights[match_c])
899  {
900  const int prev_match = sch.r2t_table[match_c];
901  if (prev_match >= 0)
902  {
903  ++skipped_matching[prev_match];
904  --stop_counter;
905  }
906  sch.r2t_table[match_c] = testc;
907  matched_weights[match_c] = match_weight;
908  ++stop_counter;
909  }
910  else
911  {
912  ++skipped_matching[testc];
913  }
914  }
915  else
916  {
917  ++stop_counter;
918  }
919  }
920  }
921 
922  sch.unmatched_ref_list.clear();
923  sch.unmatched_test_list.clear();
924 
925  for (size_t i = 0; i < sch.r2t_table.size(); ++i)
926  {
927  const int match = sch.r2t_table[i];
928  if (match < 0)
929  {
930  sch.unmatched_ref_list.push_back(i);
931  }
932  else
933  {
934  sch.t2r_table[match] = i;
935  }
936  }
937 
938  for (size_t i = 0; i < sch.t2r_table.size(); ++i)
939  {
940  if (sch.t2r_table[i] < 0)
941  {
942  sch.unmatched_test_list.push_back(i);
943  }
944  }
945 
946  {
947  char message_buffer[256];
948  snprintf(message_buffer, 256,
949  "%2d: %5d / %5d || %5d / %5d || %3d || %5d | %5d || %5d",
950  num_iter,
951  int(sch.r2t_table.size()) - int(sch.unmatched_ref_list.size()), int(sch.r2t_table.size()),
952  int(sch.t2r_table.size()) - int(sch.unmatched_test_list.size()), int(sch.t2r_table.size()),
953  int(sch.r2t_table.size()) - int(sch.t2r_table.size()),
954  int(sch.unmatched_ref_list.size()),
955  int(sch.unmatched_test_list.size()),
956  int(sch.unmatched_ref_list.size()) - int(sch.unmatched_test_list.size())
957  );
958  ATH_MSG_INFO(message_buffer);
959  }
960 
961  return StatusCode::SUCCESS;
962 
963 }

◆ match_clusters_perfectly()

StatusCode CaloGPUClusterAndCellDataMonitor::match_clusters_perfectly ( sample_comparisons_holder &  sch,
const CaloRecGPU::ConstantDataHolder &  constant_data,
const CaloRecGPU::CellInfoArr &  cell_info,
const CaloRecGPU::CellStateArr &  cell_state_1,
const CaloRecGPU::CellStateArr &  cell_state_2,
const CaloRecGPU::ClusterInfoArr &  cluster_info_1,
const CaloRecGPU::ClusterInfoArr &  cluster_info_2,
const CaloRecGPU::ClusterMomentsArr &  ,
const CaloRecGPU::ClusterMomentsArr &  ,
const bool  match_without_shared 
) const
private

Definition at line 965 of file CaloGPUClusterAndCellDataMonitor.cxx.

975 {
976  sch.r2t_table.clear();
977  sch.r2t_table.resize(cluster_info_1.number, -1);
978 
979  sch.t2r_table.clear();
980  sch.t2r_table.resize(cluster_info_2.number, -1);
981 
982  std::vector<char> match_possibilities(cluster_info_1.number * cluster_info_2.number, 1);
983 
984  for (int i = 0; i < NCaloCells; ++i)
985  {
986  const ClusterTag ref_tag = cell_state_1.clusterTag[i];
987  const ClusterTag test_tag = cell_state_2.clusterTag[i];
988 
989  if (!cell_info.is_valid(i))
990  {
991  continue;
992  }
993 
994  int ref_c1 = -1, ref_c2 = -1, test_c1 = -1, test_c2 = -1;
995 
996  if (ref_tag.is_part_of_cluster())
997  {
998  if (match_without_shared && ref_tag.is_shared_between_clusters())
999  {
1000  continue;
1001  }
1002  ref_c1 = ref_tag.cluster_index();
1003  ref_c2 = ref_tag.is_shared_between_clusters() ? ref_tag.secondary_cluster_index() : -1;
1004  }
1005 
1006  if (test_tag.is_part_of_cluster())
1007  {
1008  if (match_without_shared && test_tag.is_shared_between_clusters())
1009  {
1010  continue;
1011  }
1012  test_c1 = test_tag.cluster_index();
1013  test_c2 = test_tag.is_shared_between_clusters() ? test_tag.secondary_cluster_index() : -1;
1014  }
1015 
1016  for (int refc = 0; refc < cluster_info_1.number; ++refc)
1017  {
1018  if (refc == ref_c1 || refc == ref_c2)
1019  {
1020  continue;
1021  }
1022 
1023  if (test_c1 >= 0)
1024  {
1025  match_possibilities[test_c1 * cluster_info_1.number + refc] = 0;
1026  }
1027  if (test_c2 >= 0)
1028  {
1029  match_possibilities[test_c2 * cluster_info_1.number + refc] = 0;
1030  }
1031  }
1032 
1033  for (int testc = 0; testc < cluster_info_2.number; ++testc)
1034  {
1035  if (testc == test_c1 || testc == test_c2)
1036  {
1037  continue;
1038  }
1039 
1040  if (ref_c1 >= 0)
1041  {
1042  match_possibilities[testc * cluster_info_1.number + ref_c1] = 0;
1043  }
1044  if (ref_c2 >= 0)
1045  {
1046  match_possibilities[testc * cluster_info_1.number + ref_c2] = 0;
1047  }
1048  }
1049 
1050  }
1051 
1052  for (int testc = 0; testc < cluster_info_2.number; ++testc)
1053  {
1054  for (int refc = 0; refc < cluster_info_1.number; ++refc)
1055  {
1056  if (match_possibilities[testc * cluster_info_1.number + refc] > 0)
1057  {
1058  sch.r2t_table[refc] = testc;
1059  sch.t2r_table[testc] = refc;
1060  }
1061  }
1062  }
1063 
1064  for (int refc = 0; refc < cluster_info_1.number; ++refc)
1065  {
1066  if (sch.r2t_table[refc] < 0)
1067  {
1068  sch.unmatched_ref_list.push_back(refc);
1069  }
1070  }
1071 
1072  for (int testc = 0; testc < cluster_info_2.number; ++testc)
1073  {
1074  if (sch.t2r_table[testc] < 0)
1075  {
1076  sch.unmatched_test_list.push_back(testc);
1077  }
1078  }
1079 
1080  {
1081  char message_buffer[256];
1082  snprintf(message_buffer, 256,
1083  "%2d: %5d / %5d || %5d / %5d || %3d || %5d | %5d || %5d",
1084  0,
1085  int(sch.r2t_table.size()) - int(sch.unmatched_ref_list.size()), int(sch.r2t_table.size()),
1086  int(sch.t2r_table.size()) - int(sch.unmatched_test_list.size()), int(sch.t2r_table.size()),
1087  int(sch.r2t_table.size()) - int(sch.t2r_table.size()),
1088  int(sch.unmatched_ref_list.size()),
1089  int(sch.unmatched_test_list.size()),
1090  int(sch.unmatched_ref_list.size()) - int(sch.unmatched_test_list.size())
1091  );
1092  ATH_MSG_INFO(message_buffer);
1093  }
1094 
1095  return StatusCode::SUCCESS;
1096 
1097 }

◆ msg() [1/2]

MsgStream& AthCommonMsg< AlgTool >::msg ( ) const
inlineinherited

Definition at line 24 of file AthCommonMsg.h.

24  {
25  return this->msgStream();
26  }

◆ msg() [2/2]

MsgStream& AthCommonMsg< AlgTool >::msg ( const MSG::Level  lvl) const
inlineinherited

Definition at line 27 of file AthCommonMsg.h.

27  {
28  return this->msgStream(lvl);
29  }

◆ msgLvl()

bool AthCommonMsg< AlgTool >::msgLvl ( const MSG::Level  lvl) const
inlineinherited

Definition at line 30 of file AthCommonMsg.h.

30  {
31  return this->msgLevel(lvl);
32  }

◆ outputHandles()

virtual std::vector<Gaudi::DataHandle*> AthCommonDataStore< AthCommonMsg< AlgTool > >::outputHandles ( ) const
overridevirtualinherited

Return this algorithm's output handles.

We override this to include handle instances from key arrays if they have not yet been declared. See comments on updateVHKA.

◆ renounce()

std::enable_if_t<std::is_void_v<std::result_of_t<decltype(&T::renounce)(T)> > && !std::is_base_of_v<SG::VarHandleKeyArray, T> && std::is_base_of_v<Gaudi::DataHandle, T>, void> AthCommonDataStore< AthCommonMsg< AlgTool > >::renounce ( T &  h)
inlineprotectedinherited

Definition at line 380 of file AthCommonDataStore.h.

381  {
382  h.renounce();
383  PBASE::renounce (h);
384  }

◆ renounceArray()

void AthCommonDataStore< AthCommonMsg< AlgTool > >::renounceArray ( SG::VarHandleKeyArray &  handlesArray)
inlineprotectedinherited

remove all handles from I/O resolution

Definition at line 364 of file AthCommonDataStore.h.

364  {
365  handlesArray.renounce();
366  }

◆ sysInitialize()

virtual StatusCode AthCommonDataStore< AthCommonMsg< AlgTool > >::sysInitialize ( )
overridevirtualinherited

Perform system initialization for an algorithm.

We override this to declare all the elements of handle key arrays at the end of initialization. See comments on updateVHKA.

Reimplemented in DerivationFramework::CfAthAlgTool, AthCheckedComponent< AthAlgTool >, AthCheckedComponent<::AthAlgTool >, and asg::AsgMetadataTool.

◆ sysStart()

virtual StatusCode AthCommonDataStore< AthCommonMsg< AlgTool > >::sysStart ( )
overridevirtualinherited

Handle START transition.

We override this in order to make sure that conditions handle keys can cache a pointer to the conditions container.

◆ update_plots() [1/4]

StatusCode CaloGPUClusterAndCellDataMonitor::update_plots ( const EventContext &  ctx,
const CaloRecGPU::ConstantDataHolder &  constant_data,
const xAOD::CaloClusterContainer *  cluster_collection_ptr,
const CaloClusterCollectionProcessor *  tool 
) const
overridevirtual

Implements ICaloClusterGPUPlotter.

Definition at line 168 of file CaloGPUClusterAndCellDataMonitor.cxx.

172 {
173  if (filter_tool_by_name(tool->name()))
174  {
175  Helpers::CPU_object<CellInfoArr> cell_info;
176  Helpers::CPU_object<CellStateArr> cell_state;
177  Helpers::CPU_object<ClusterInfoArr> clusters;
178  Helpers::CPU_object<ClusterMomentsArr> moments;
179 
180  ATH_CHECK( convert_to_GPU_data_structures(ctx, constant_data, cluster_collection_ptr,
181  cell_info, cell_state, clusters, moments ) );
182 
183  return add_data(ctx, constant_data, cell_info, cell_state, clusters, moments, tool->name());
184  }
185  else
186  {
187  return StatusCode::SUCCESS;
188  }
189 }

◆ update_plots() [2/4]

StatusCode CaloGPUClusterAndCellDataMonitor::update_plots ( const EventContext &  ctx,
const CaloRecGPU::ConstantDataHolder &  constant_data,
const xAOD::CaloClusterContainer *  cluster_collection_ptr,
const CaloRecGPU::EventDataHolder &  event_data,
const CaloClusterGPUProcessor *  tool 
) const
overridevirtual

Implements ICaloClusterGPUPlotter.

Definition at line 208 of file CaloGPUClusterAndCellDataMonitor.cxx.

213 {
214  if (filter_tool_by_name(tool->name()))
215  {
216  Helpers::CPU_object<CellInfoArr> cell_info = event_data.m_cell_info_dev;
217  Helpers::CPU_object<CellStateArr> cell_state = event_data.m_cell_state_dev;
218  Helpers::CPU_object<ClusterInfoArr> clusters = event_data.m_clusters_dev;
219  Helpers::CPU_object<CaloRecGPU::ClusterMomentsArr> moments = event_data.m_moments_dev;
220 
221  ATH_CHECK( compactify_clusters(ctx, constant_data, cell_info, cell_state, clusters, moments) );
222 
223  return add_data(ctx, constant_data, cell_info, cell_state, clusters, moments, tool->name());
224  }
225  else
226  {
227  return StatusCode::SUCCESS;
228  }
229 }

◆ update_plots() [3/4]

StatusCode CaloGPUClusterAndCellDataMonitor::update_plots ( const EventContext &  ctx,
const CaloRecGPU::ConstantDataHolder &  constant_data,
const xAOD::CaloClusterContainer *  cluster_collection_ptr,
const CaloRecGPU::EventDataHolder &  event_data,
const ICaloClusterGPUInputTransformer *  tool 
) const
overridevirtual

Implements ICaloClusterGPUPlotter.

Definition at line 191 of file CaloGPUClusterAndCellDataMonitor.cxx.

196 {
197  if (filter_tool_by_name(tool->name()))
198  {
199  return add_data(ctx, constant_data, event_data.m_cell_info_dev, event_data.m_cell_state_dev,
200  event_data.m_clusters_dev, event_data.m_moments_dev, tool->name());
201  }
202  else
203  {
204  return StatusCode::SUCCESS;
205  }
206 }

◆ update_plots() [4/4]

StatusCode CaloGPUClusterAndCellDataMonitor::update_plots ( const EventContext &  ctx,
const CaloRecGPU::ConstantDataHolder &  constant_data,
const xAOD::CaloClusterContainer *  cluster_collection_ptr,
const CaloRecGPU::EventDataHolder &  event_data,
const ICaloClusterGPUOutputTransformer *  tool 
) const
overridevirtual

Implements ICaloClusterGPUPlotter.

Definition at line 231 of file CaloGPUClusterAndCellDataMonitor.cxx.

236 {
237  if (filter_tool_by_name(tool->name()))
238  {
239  Helpers::CPU_object<CellInfoArr> cell_info;
240  Helpers::CPU_object<CellStateArr> cell_state;
241  Helpers::CPU_object<ClusterInfoArr> clusters;
242  Helpers::CPU_object<CaloRecGPU::ClusterMomentsArr> moments;
243 
244  ATH_CHECK( convert_to_GPU_data_structures(ctx, constant_data, cluster_collection_ptr,
245  cell_info, cell_state, clusters, moments ) );
246 
247  return add_data(ctx, constant_data, cell_info, cell_state, clusters, moments, tool->name());
248  }
249  else
250  {
251  return StatusCode::SUCCESS;
252  }
253 }

◆ update_plots_end()

StatusCode CaloGPUClusterAndCellDataMonitor::update_plots_end ( const EventContext &  ctx,
const CaloRecGPU::ConstantDataHolder &  constant_data,
const xAOD::CaloClusterContainer *  cluster_collection_ptr 
) const
overridevirtual

Implements ICaloClusterGPUPlotter.

Definition at line 140 of file CaloGPUClusterAndCellDataMonitor.cxx.

143 {
144  ATH_MSG_INFO("");
145 
146  for (const auto & combination : m_toolCombinations)
147  {
148  if (combination.index_ref < 0 || combination.index_test < 0)
149  {
150  ATH_MSG_WARNING("Invalid tool combination, please check your configuration! " << combination.prefix);
151  continue;
152  }
153  ATH_CHECK( add_combination(ctx, constant_data, combination.index_ref, combination.index_test, combination.prefix,
154  combination.match_in_energy, combination.match_without_shared, combination.match_perfectly) );
155  }
156 
157  ATH_MSG_INFO("");
158 
159  if (m_numToolsToKeep > 0)
160  {
161  m_storageHolder.release_one();
162  //Release the tool storage.
163  }
164 
165  return StatusCode::SUCCESS;
166 }

◆ update_plots_start()

StatusCode CaloGPUClusterAndCellDataMonitor::update_plots_start ( const EventContext &  ctx,
const CaloRecGPU::ConstantDataHolder &  constant_data,
const xAOD::CaloClusterContainer *  cluster_collection_ptr 
) const
overridevirtual

Implements ICaloClusterGPUPlotter.

Definition at line 115 of file CaloGPUClusterAndCellDataMonitor.cxx.

118 {
119  if (!m_plottedVariablesInitialized.load())
120  {
121  std::lock_guard<std::mutex> lock_guard(m_mutex);
122  if (!m_plottedVariablesInitialized.load())
123  {
124  CaloGPUClusterAndCellDataMonitor * dhis ATLAS_THREAD_SAFE = const_cast<CaloGPUClusterAndCellDataMonitor *>(this);
125  //We have the mutex.
126  //It's safe.
127  ATH_CHECK( dhis->initialize_plotted_variables() );
128  m_plottedVariablesInitialized.store(true);
129  }
130  }
131  if (m_numToolsToKeep > 0)
132  {
133  m_storageHolder.get_one().resize(m_numToolsToKeep);
134  }
135  //Allocate a vector of data holders for this thread and resize it to the necessary size.
136 
137  return StatusCode::SUCCESS;
138 }

◆ updateVHKA()

void AthCommonDataStore< AthCommonMsg< AlgTool > >::updateVHKA ( Gaudi::Details::PropertyBase &  )
inlineinherited

Definition at line 308 of file AthCommonDataStore.h.

308  {
309  // debug() << "updateVHKA for property " << p.name() << " " << p.toString()
310  // << " size: " << m_vhka.size() << endmsg;
311  for (auto &a : m_vhka) {
312  std::vector<SG::VarHandleKey*> keys = a->keys();
313  for (auto k : keys) {
314  k->setOwner(this);
315  }
316  }
317  }

Member Data Documentation

◆ ATLAS_THREAD_SAFE [1/2]

std::map<std::string, std::atomic<size_t> > m_numClustersPerTool CaloGPUClusterAndCellDataMonitor::ATLAS_THREAD_SAFE
mutableprivate

Counts the total number of clusters per tool.

Definition at line 275 of file CaloGPUClusterAndCellDataMonitor.h.

◆ ATLAS_THREAD_SAFE [2/2]

CaloRecGPU::Helpers::separate_thread_holder<std::vector<per_tool_storage> > m_storageHolder CaloGPUClusterAndCellDataMonitor::ATLAS_THREAD_SAFE
mutableprivate

Stores the intermediate results needed for tool-level matching.

Definition at line 290 of file CaloGPUClusterAndCellDataMonitor.h.

◆ m_calo_id

const CaloCell_ID* CaloGPUClusterAndCellDataMonitor::m_calo_id {nullptr}
private

Pointer to Calo ID Helper.

Definition at line 247 of file CaloGPUClusterAndCellDataMonitor.h.

◆ m_cellPropertiesToDo

std::vector<bool> CaloGPUClusterAndCellDataMonitor::m_cellPropertiesToDo
private

Definition at line 296 of file CaloGPUClusterAndCellDataMonitor.h.

◆ m_cellsKey

SG::ReadHandleKey<CaloCellContainer> CaloGPUClusterAndCellDataMonitor::m_cellsKey {this, "CellsName", "", "Name(s) of Cell Containers"}
private

vector of names of the cell containers to use as input.

Definition at line 204 of file CaloGPUClusterAndCellDataMonitor.h.

◆ m_cellTypesToDo

std::vector<bool> CaloGPUClusterAndCellDataMonitor::m_cellTypesToDo
private

Definition at line 297 of file CaloGPUClusterAndCellDataMonitor.h.

◆ m_clusterPropertiesToDo

std::vector<bool> CaloGPUClusterAndCellDataMonitor::m_clusterPropertiesToDo
private

Control which properties will actually be calculated and stored.

In principle, should be automagically filled based on the booked histograms.

Definition at line 295 of file CaloGPUClusterAndCellDataMonitor.h.

◆ m_comparedCellPropertiesToDo

std::vector<bool> CaloGPUClusterAndCellDataMonitor::m_comparedCellPropertiesToDo
private

Definition at line 297 of file CaloGPUClusterAndCellDataMonitor.h.

◆ m_comparedCellTypesToDo

std::vector<bool> CaloGPUClusterAndCellDataMonitor::m_comparedCellTypesToDo
private

Definition at line 298 of file CaloGPUClusterAndCellDataMonitor.h.

◆ m_comparedClusterPropertiesToDo

std::vector<bool> CaloGPUClusterAndCellDataMonitor::m_comparedClusterPropertiesToDo
private

Definition at line 295 of file CaloGPUClusterAndCellDataMonitor.h.

◆ m_detStore

StoreGateSvc_t AthCommonDataStore< AthCommonMsg< AlgTool > >::m_detStore
privateinherited

Pointer to StoreGate (detector store by default)

Definition at line 393 of file AthCommonDataStore.h.

◆ m_doCells

bool CaloGPUClusterAndCellDataMonitor::m_doCells = false
private

If no properties are asked for, skip the relevant loops entirely...

Definition at line 302 of file CaloGPUClusterAndCellDataMonitor.h.

◆ m_doClusters

bool CaloGPUClusterAndCellDataMonitor::m_doClusters = false
private

Definition at line 302 of file CaloGPUClusterAndCellDataMonitor.h.

◆ m_doCombinedCells

bool CaloGPUClusterAndCellDataMonitor::m_doCombinedCells = false
private

Definition at line 302 of file CaloGPUClusterAndCellDataMonitor.h.

◆ m_doCombinedClusters

bool CaloGPUClusterAndCellDataMonitor::m_doCombinedClusters = false
private

Definition at line 302 of file CaloGPUClusterAndCellDataMonitor.h.

◆ m_evtStore

StoreGateSvc_t AthCommonDataStore< AthCommonMsg< AlgTool > >::m_evtStore
privateinherited

Pointer to StoreGate (event store by default)

Definition at line 390 of file AthCommonDataStore.h.

◆ m_extraComparedClusterPropertiesToDo

std::vector<bool> CaloGPUClusterAndCellDataMonitor::m_extraComparedClusterPropertiesToDo
private

Definition at line 296 of file CaloGPUClusterAndCellDataMonitor.h.

◆ m_extraThingsToDo

std::vector<bool> CaloGPUClusterAndCellDataMonitor::m_extraThingsToDo
private

Definition at line 298 of file CaloGPUClusterAndCellDataMonitor.h.

◆ m_grow_weight

double CaloGPUClusterAndCellDataMonitor::m_grow_weight = 250.
private

Definition at line 242 of file CaloGPUClusterAndCellDataMonitor.h.

◆ m_growThreshold

Gaudi::Property<float> CaloGPUClusterAndCellDataMonitor::m_growThreshold {this, "NeighborThreshold", 2., "Neighbor (grow) threshold (in units of noise Sigma)"}
private

Neighbor (growing) threshold to use for cluster matching.

Definition at line 194 of file CaloGPUClusterAndCellDataMonitor.h.

◆ m_matchingOptions

Gaudi::Property<MatchingOptions> CaloGPUClusterAndCellDataMonitor::m_matchingOptions {this, "ClusterMatchingParameters", {}, "Parameters for the cluster matching algorithm"}
private

Option for adjusting the parameters for the cluster matching algorithm.

Definition at line 230 of file CaloGPUClusterAndCellDataMonitor.h.

◆ m_min_similarity

double CaloGPUClusterAndCellDataMonitor::m_min_similarity = 0.5
private

Parameters for the cluster matching algorithm, for easier access.

Definition at line 242 of file CaloGPUClusterAndCellDataMonitor.h.

◆ m_moniTool

ToolHandle< GenericMonitoringTool > CaloGPUClusterAndCellDataMonitor::m_moniTool { this, "MonitoringTool", "", "Monitoring tool" }
private

Monitoring tool.

Definition at line 208 of file CaloGPUClusterAndCellDataMonitor.h.

◆ m_mutex

std::mutex CaloGPUClusterAndCellDataMonitor::m_mutex
mutableprivate

This mutex is locked to ensure only one thread detects the monotired variables.

Definition at line 313 of file CaloGPUClusterAndCellDataMonitor.h.

◆ m_numEvents

size_t CaloGPUClusterAndCellDataMonitor::m_numEvents = 0
private

Counts the number of events.

Definition at line 278 of file CaloGPUClusterAndCellDataMonitor.h.

◆ m_numToolsToKeep

int CaloGPUClusterAndCellDataMonitor::m_numToolsToKeep = 0
private

The number of tools that will actually need to be kept in memory for combined plotting.

Definition at line 261 of file CaloGPUClusterAndCellDataMonitor.h.

◆ m_pairsToPlot

Gaudi::Property< std::vector<SimpleToolPair> > CaloGPUClusterAndCellDataMonitor::m_pairsToPlot {this, "PairsToPlot", {}, "Pairs of tools to be compared and plotted"}
private

Pairs of tools to compare.

Definition at line 225 of file CaloGPUClusterAndCellDataMonitor.h.

◆ m_plottedVariablesInitialized

std::atomic<bool> CaloGPUClusterAndCellDataMonitor::m_plottedVariablesInitialized
mutableprivate

A flag to signal that the variables to be monitored have been detected based on the booked histograms.

Definition at line 308 of file CaloGPUClusterAndCellDataMonitor.h.

◆ m_seed_weight

double CaloGPUClusterAndCellDataMonitor::m_seed_weight = 5000.
private

Definition at line 242 of file CaloGPUClusterAndCellDataMonitor.h.

◆ m_seedThreshold

Gaudi::Property<float> CaloGPUClusterAndCellDataMonitor::m_seedThreshold {this, "SeedThreshold", 4., "Seed threshold (in units of noise Sigma)"}
private

Seed threshold to use for cluster matching.

Definition at line 199 of file CaloGPUClusterAndCellDataMonitor.h.

◆ m_terminal_weight

double CaloGPUClusterAndCellDataMonitor::m_terminal_weight = 10.
private

Definition at line 242 of file CaloGPUClusterAndCellDataMonitor.h.

◆ m_termThreshold

Gaudi::Property<float> CaloGPUClusterAndCellDataMonitor::m_termThreshold {this, "CellThreshold", 0., "Cell (terminal) threshold (in units of noise Sigma)"}
private

Cell (terminal) threshold to use for cluster matching.

Definition at line 189 of file CaloGPUClusterAndCellDataMonitor.h.

◆ m_toolCombinations

std::vector<pair_to_plot> CaloGPUClusterAndCellDataMonitor::m_toolCombinations
private

Definition at line 272 of file CaloGPUClusterAndCellDataMonitor.h.

◆ m_toolsToCheckFor

std::map<std::string, int> CaloGPUClusterAndCellDataMonitor::m_toolsToCheckFor
private

Map of the strings corresponding to all the tools that will be relevant for plotting (individually or in comparisons) to the index that will be used to identify the tool within the plotter.

(Indices of -1 signal tools that are only plotted individually, no need to keep them.)

Definition at line 255 of file CaloGPUClusterAndCellDataMonitor.h.

◆ m_toolsToPlot

Gaudi::Property<std::vector<SimpleSingleTool> > CaloGPUClusterAndCellDataMonitor::m_toolsToPlot {this, "ToolsToPlot", {}, "Tools to be plotted individually"}
private

Tools to plot individually.

Warning
If a tool appears more than once with different identifiers, the last one is used.

Definition at line 220 of file CaloGPUClusterAndCellDataMonitor.h.

◆ m_toolToIdMap

std::map<std::string, std::string> CaloGPUClusterAndCellDataMonitor::m_toolToIdMap
private

Maps tools to their respective identifying prefix for variables.

Definition at line 258 of file CaloGPUClusterAndCellDataMonitor.h.

◆ m_varHandleArraysDeclared

bool AthCommonDataStore< AthCommonMsg< AlgTool > >::m_varHandleArraysDeclared
privateinherited

Definition at line 399 of file AthCommonDataStore.h.

◆ m_vhka

std::vector<SG::VarHandleKeyArray*> AthCommonDataStore< AthCommonMsg< AlgTool > >::m_vhka
privateinherited

Definition at line 398 of file AthCommonDataStore.h.

The documentation for this class was generated from the following files:
CaloGPUClusterAndCellDataMonitor::m_cellPropertiesToDo
std::vector< bool > m_cellPropertiesToDo
Definition: CaloGPUClusterAndCellDataMonitor.h:296
xAOD::CaloCluster_v1::CENTER_MAG
@ CENTER_MAG
Cluster Centroid ( )
Definition: CaloCluster_v1.h:135
xAOD::CaloCluster_v1::SECOND_R
@ SECOND_R
Second Moment in .
Definition: CaloCluster_v1.h:123
python.PyKernel.retrieve
def retrieve(aClass, aKey=None)
Definition: PyKernel.py:110
xAOD::CaloCluster_v1::phimax
float phimax(const CaloSample sampling) const
Retrieve of cell with maximum energy in given sampling.
Definition: CaloCluster_v1.cxx:589
xAOD::CaloCluster_v1::phi
virtual double phi() const
The azimuthal angle ( ) of the particle.
Definition: CaloCluster_v1.cxx:256
xAOD::CaloCluster_v1::time
flt_t time() const
Access cluster time.
fillPileUpNoiseLumi.current
current
Definition: fillPileUpNoiseLumi.py:52
CaloRecGPU::CellInfoArr::gain
unsigned char gain[NCaloCells]
Definition: EventInfoDefinitions.h:190
xAOD::CaloCluster_v1::ENG_CALIB_DEAD_UNCLASS
@ ENG_CALIB_DEAD_UNCLASS
Attached Calibration Hit energy in dead material in unclassified areas of the detector.
Definition: CaloCluster_v1.h:246
xAOD::CaloCluster_v1::FIRST_PHI
@ FIRST_PHI
First Moment in .
Definition: CaloCluster_v1.h:121
python.CaloRecoConfig.f
f
Definition: CaloRecoConfig.py:127
xAOD::CaloCluster_v1::OOC_WEIGHT
@ OOC_WEIGHT
Out-of-cluster weight (E_ooc/E_w)
Definition: CaloCluster_v1.h:175
xAOD::CaloCluster_v1::ENG_FRAC_CORE
@ ENG_FRAC_CORE
Energy fraction of the sum of the hottest cells in each sampling.
Definition: CaloCluster_v1.h:142
xAOD::CaloCluster_v1::cell_begin
const_cell_iterator cell_begin() const
Iterator of the underlying CaloClusterCellLink (const version)
Definition: CaloCluster_v1.h:812
CaloRecGPU::ClusterInfoArr::number
int number
Definition: EventInfoDefinitions.h:329
DataModel_detail::const_iterator
Const iterator class for DataVector/DataList.
Definition: DVLIterator.h:82
TrigDefs::Group
Group
Properties of a chain group.
Definition: GroupProperties.h:13
hotSpotInTAG.suffix
string suffix
Definition: hotSpotInTAG.py:186
ReadCellNoiseFromCool.cell
cell
Definition: ReadCellNoiseFromCool.py:53
python.PerfMonSerializer.p
def p
Definition: PerfMonSerializer.py:743
xAOD::CaloCluster_v1::numberCells
int numberCells() const
Return total number of cells in cluster.
Definition: CaloCluster_v1.cxx:818
xAOD::CaloCluster_v1::VERTEX_FRACTION
@ VERTEX_FRACTION
Vertex fraction of this cluster wrt.
Definition: CaloCluster_v1.h:184
CaloRecGPU::ClusterTag::secondary_cluster_index
constexpr int32_t secondary_cluster_index() const
Definition: TagDefinitions.h:253
ATH_MSG_INFO
#define ATH_MSG_INFO(x)
Definition: AthMsgStreamMacros.h:31
xAOD::CaloCluster_v1::getMomentValue
double getMomentValue(MomentType type) const
Retrieve individual moment - no check for existance! Returns -999 on error.
Definition: CaloCluster_v1.h:906
xAOD::CaloCluster_v1::MASS
@ MASS
cell based mass i.e. the mass of the 4-vector sum of all massless positive energetic cells
Definition: CaloCluster_v1.h:172
xAOD::CaloCluster_v1::EM_PROBABILITY
@ EM_PROBABILITY
Classification probability to be em-like.
Definition: CaloCluster_v1.h:173
CaloGPUClusterAndCellDataMonitor::m_extraThingsToDo
std::vector< bool > m_extraThingsToDo
Definition: CaloGPUClusterAndCellDataMonitor.h:298
CaloCellPos2Ntuple.int
int
Definition: CaloCellPos2Ntuple.py:24
CaloRecGPU::ClusterTag::is_shared_between_clusters
constexpr bool is_shared_between_clusters() const
Definition: TagDefinitions.h:273
xAOD::CaloCluster_v1::CENTER_X
@ CENTER_X
Cluster Centroid ( )
Definition: CaloCluster_v1.h:131
xAOD::CaloCluster_v1::ENG_BAD_HV_CELLS
@ ENG_BAD_HV_CELLS
Total em-scale energy of cells with bad HV in this cluster.
Definition: CaloCluster_v1.h:167
xAOD::uint32_t
setEventNumber uint32_t
Definition: EventInfo_v1.cxx:127
CaloRecGPU::EventDataHolder::m_moments_dev
CaloRecGPU::Helpers::CUDA_object< CaloRecGPU::ClusterMomentsArr > m_moments_dev
Definition: DataHolders.h:91
SG::ReadHandle
Definition: StoreGate/StoreGate/ReadHandle.h:70
index
Definition: index.py:1
CaloGPUClusterAndCellDataMonitor::m_min_similarity
double m_min_similarity
Parameters for the cluster matching algorithm, for easier access.
Definition: CaloGPUClusterAndCellDataMonitor.h:242
AthCommonDataStore::declareProperty
Gaudi::Details::PropertyBase & declareProperty(Gaudi::Property< T > &t)
Definition: AthCommonDataStore.h:145
xAOD::CaloCluster_v1::ENG_CALIB_DEAD_LEAKAGE
@ ENG_CALIB_DEAD_LEAKAGE
Attached Calibration Hit energy in dead material behind calorimeters.
Definition: CaloCluster_v1.h:243
xAOD::CaloCluster_v1::ETA2CALOFRAME
@ ETA2CALOFRAME
Eta of sampling 2 in the calo frame (for egamma)
Definition: CaloCluster_v1.h:191
xAOD::CaloCluster_v1::AVG_LAR_Q
@ AVG_LAR_Q
Sum(E_cell_LAr^2 Q_cell_LAr)/Sum(E_cell_LAr^2)
Definition: CaloCluster_v1.h:163
xAOD::CaloCluster_v1::ETA1CALOFRAME
@ ETA1CALOFRAME
Eta of sampling 1 in the calo frame (for egamma)
Definition: CaloCluster_v1.h:189
CaloCondBlobAlgs_fillNoiseFromASCII.gain
gain
Definition: CaloCondBlobAlgs_fillNoiseFromASCII.py:110
CaloRecGPU::Helpers::SimpleHolder
Holds one objects of type \T in memory context Context.
Definition: Calorimeter/CaloRecGPU/CaloRecGPU/Helpers.h:1069
CaloRecGPU::EventDataHolder::m_cell_state_dev
CaloRecGPU::Helpers::CUDA_object< CaloRecGPU::CellStateArr > m_cell_state_dev
Definition: DataHolders.h:89
CaloGPUClusterAndCellDataMonitor::m_comparedClusterPropertiesToDo
std::vector< bool > m_comparedClusterPropertiesToDo
Definition: CaloGPUClusterAndCellDataMonitor.h:295
skel.it
it
Definition: skel.GENtoEVGEN.py:423
CaloGPUClusterAndCellDataMonitor::m_plottedVariablesInitialized
std::atomic< bool > m_plottedVariablesInitialized
A flag to signal that the variables to be monitored have been detected based on the booked histograms...
Definition: CaloGPUClusterAndCellDataMonitor.h:308
CaloGPUClusterAndCellDataMonitor::m_cellTypesToDo
std::vector< bool > m_cellTypesToDo
Definition: CaloGPUClusterAndCellDataMonitor.h:297
CaloRecGPU::EventDataHolder::m_clusters_dev
CaloRecGPU::Helpers::CUDA_object< CaloRecGPU::ClusterInfoArr > m_clusters_dev
Definition: DataHolders.h:90
xAOD::CaloCluster_v1::ENG_CALIB_TILEG3
@ ENG_CALIB_TILEG3
Calibration Hit energy inside the cluster scintillator.
Definition: CaloCluster_v1.h:222
AthCommonDataStore< AthCommonMsg< AlgTool > >::m_evtStore
StoreGateSvc_t m_evtStore
Pointer to StoreGate (event store by default)
Definition: AthCommonDataStore.h:390
AthCommonDataStore< AthCommonMsg< AlgTool > >::m_vhka
std::vector< SG::VarHandleKeyArray * > m_vhka
Definition: AthCommonDataStore.h:398
xAOD::CaloCluster_v1::ENG_CALIB_DEAD_T
@ ENG_CALIB_DEAD_T
Attached Calibration Hit energy in dead material with tight matching (Angle < 0.3).
Definition: CaloCluster_v1.h:214
CaloGPUClusterAndCellDataMonitor::match_clusters
StatusCode match_clusters(sample_comparisons_holder &sch, const CaloRecGPU::ConstantDataHolder &constant_data, const CaloRecGPU::CellInfoArr &cell_info, const CaloRecGPU::CellStateArr &cell_state_1, const CaloRecGPU::CellStateArr &cell_state_2, const CaloRecGPU::ClusterInfoArr &cluster_info_1, const CaloRecGPU::ClusterInfoArr &cluster_info_2, const CaloRecGPU::ClusterMomentsArr &, const CaloRecGPU::ClusterMomentsArr &, const bool match_in_energy, const bool match_without_shared) const
Definition: CaloGPUClusterAndCellDataMonitor.cxx:717
xAOD::CaloCluster_v1::ENG_CALIB_OUT_M
@ ENG_CALIB_OUT_M
Attached Calibration Hit energy outside clusters but inside the calorimeter with medium matching (Ang...
Definition: CaloCluster_v1.h:200
xAOD::CaloCluster_v1::et
double et() const
Definition: CaloCluster_v1.h:856
xAOD::CaloCluster_v1::CENTER_LAMBDA
@ CENTER_LAMBDA
Shower depth at Cluster Centroid.
Definition: CaloCluster_v1.h:136
CaloRecGPU::CellInfoArr::energy
float energy[NCaloCells]
Definition: EventInfoDefinitions.h:189
xAOD::CaloCluster_v1::ENG_CALIB_EMB0
@ ENG_CALIB_EMB0
Calibration Hit energy inside the cluster barrel presampler.
Definition: CaloCluster_v1.h:218
postInclude.sorter
sorter
Definition: postInclude.SortInput.py:23
read_hist_ntuple.t
t
Definition: read_hist_ntuple.py:5
xAOD::CaloCluster_v1::ENG_CALIB_DEAD_TILE0
@ ENG_CALIB_DEAD_TILE0
Attached Calibration Hit energy in dead material between EMB3 and TILE0.
Definition: CaloCluster_v1.h:230
CaloRecGPU::CellStateArr::clusterTag
tag_type clusterTag[NCaloCells]
Definition: EventInfoDefinitions.h:324
CaloRecGPU::NumSamplings
constexpr int NumSamplings
Definition: BaseDefinitions.h:44
xAOD::CaloCluster_v1::ENG_FRAC_MAX
@ ENG_FRAC_MAX
Energy fraction of hottest cell.
Definition: CaloCluster_v1.h:140
CaloRecGPU::ConstantDataHolder::m_geometry
CaloRecGPU::Helpers::CPU_object< CaloRecGPU::GeometryArr > m_geometry
Definition: DataHolders.h:24
CaloGPUClusterAndCellDataMonitor::add_data
StatusCode add_data(const EventContext &ctx, const CaloRecGPU::ConstantDataHolder &constant_data, const CaloRecGPU::Helpers::CPU_object< CaloRecGPU::CellInfoArr > &cell_info, const CaloRecGPU::Helpers::CPU_object< CaloRecGPU::CellStateArr > &cell_state, const CaloRecGPU::Helpers::CPU_object< CaloRecGPU::ClusterInfoArr > &clusters, const CaloRecGPU::Helpers::CPU_object< CaloRecGPU::ClusterMomentsArr > &moments, const std::string &tool_name) const
Definition: CaloGPUClusterAndCellDataMonitor.cxx:1657
xAOD::CaloCluster_v1::etamax
float etamax(const CaloSample sampling) const
Retrieve of cell with maximum energy in given sampling.
Definition: CaloCluster_v1.cxx:576
xAOD::CaloCluster_v1::PHI1CALOFRAME
@ PHI1CALOFRAME
Phi of sampling 1 in the calo frame (for egamma)
Definition: CaloCluster_v1.h:190
CaloGPUClusterAndCellDataMonitor::m_numEvents
size_t m_numEvents
Counts the number of events.
Definition: CaloGPUClusterAndCellDataMonitor.h:278
CaloGPUClusterAndCellDataMonitor::m_terminal_weight
double m_terminal_weight
Definition: CaloGPUClusterAndCellDataMonitor.h:242
XMLtoHeader.count
count
Definition: XMLtoHeader.py:85
CaloGPUClusterAndCellDataMonitor::m_seedThreshold
Gaudi::Property< float > m_seedThreshold
Seed threshold to use for cluster matching.
Definition: CaloGPUClusterAndCellDataMonitor.h:199
CaloRecGPU::ClusterTag
Definition: TagDefinitions.h:222
CaloRecGPU::EventDataHolder::m_cell_info_dev
CaloRecGPU::Helpers::CUDA_object< CaloRecGPU::CellInfoArr > m_cell_info_dev
Definition: DataHolders.h:88
AthCommonDataStore< AthCommonMsg< AlgTool > >::detStore
const ServiceHandle< StoreGateSvc > & detStore() const
The standard StoreGateSvc/DetectorStore Returns (kind of) a pointer to the StoreGateSvc.
Definition: AthCommonDataStore.h:95
Monitored::Collection
ValuesCollection< T > Collection(std::string name, const T &collection)
Declare a monitored (double-convertible) collection.
Definition: MonitoredCollection.h:38
CaloGPUClusterAndCellDataMonitor::m_toolsToCheckFor
std::map< std::string, int > m_toolsToCheckFor
Map of the strings corresponding to all the tools that will be relevant for plotting (individually or...
Definition: CaloGPUClusterAndCellDataMonitor.h:255
SG::VarHandleKeyArray::setOwner
virtual void setOwner(IDataHandleHolder *o)=0
xAOD::CaloCluster_v1::SECOND_LAMBDA
@ SECOND_LAMBDA
Second Moment in .
Definition: CaloCluster_v1.h:124
dqt_zlumi_pandas.weight
int weight
Definition: dqt_zlumi_pandas.py:200
xAOD::CaloCluster_v1::PTD
@ PTD
relative spread of pT of constiuent cells = sqrt(n)*RMS/Mean
Definition: CaloCluster_v1.h:170
xAOD::CaloCluster_v1::etaSample
float etaSample(const CaloSample sampling) const
Retrieve barycenter in a given sample.
Definition: CaloCluster_v1.cxx:532
xAOD::CaloCluster_v1::CENTER_Z
@ CENTER_Z
Cluster Centroid ( )
Definition: CaloCluster_v1.h:133
CaloGPUClusterAndCellDataMonitor::m_doCombinedCells
bool m_doCombinedCells
Definition: CaloGPUClusterAndCellDataMonitor.h:302
python.setupRTTAlg.size
int size
Definition: setupRTTAlg.py:39
CaloRecGPU::ClusterTag::cluster_index
constexpr int32_t cluster_index() const
Definition: TagDefinitions.h:243
xAOD::CaloCluster_v1::SECOND_ENG_DENS
@ SECOND_ENG_DENS
Second Moment in E/V.
Definition: CaloCluster_v1.h:144
CaloGPUClusterAndCellDataMonitor::m_grow_weight
double m_grow_weight
Definition: CaloGPUClusterAndCellDataMonitor.h:242
CaloRecGPU::CellStateArr
Definition: EventInfoDefinitions.h:323
xAOD::CaloCluster_v1
Description of a calorimeter cluster.
Definition: CaloCluster_v1.h:59
xAOD::CaloCluster_v1::DM_WEIGHT
@ DM_WEIGHT
Dead-material weight (E_dm/E_ooc)
Definition: CaloCluster_v1.h:176
CaloGPUClusterAndCellDataMonitor::m_growThreshold
Gaudi::Property< float > m_growThreshold
Neighbor (growing) threshold to use for cluster matching.
Definition: CaloGPUClusterAndCellDataMonitor.h:194
CaloGPUClusterAndCellDataMonitor::m_toolToIdMap
std::map< std::string, std::string > m_toolToIdMap
Maps tools to their respective identifying prefix for variables.
Definition: CaloGPUClusterAndCellDataMonitor.h:258
CaloRecGPU::tag_type
TagBase::carrier tag_type
Definition: TagDefinitions.h:325
AthCommonDataStore
Definition: AthCommonDataStore.h:52
xAOD::CaloCluster_v1::HAD_WEIGHT
@ HAD_WEIGHT
Hadronic weight (E_w/E_em)
Definition: CaloCluster_v1.h:174
ATH_MSG_ERROR
#define ATH_MSG_ERROR(x)
Definition: AthMsgStreamMacros.h:33
CaloGPUClusterAndCellDataMonitor::m_moniTool
ToolHandle< GenericMonitoringTool > m_moniTool
Monitoring tool.
Definition: CaloGPUClusterAndCellDataMonitor.h:208
ParticleGun_FastCalo_ChargeFlip_Config.energy
energy
Definition: ParticleGun_FastCalo_ChargeFlip_Config.py:78
CaloGPUClusterAndCellDataMonitor::m_calo_id
const CaloCell_ID * m_calo_id
Pointer to Calo ID Helper.
Definition: CaloGPUClusterAndCellDataMonitor.h:247
xAOD::CaloCluster_v1::eta
virtual double eta() const
The pseudorapidity ( ) of the particle.
Definition: CaloCluster_v1.cxx:251
lumiFormat.i
int i
Definition: lumiFormat.py:92
CaloSampling::CaloSample
CaloSample
Definition: Calorimeter/CaloGeoHelpers/CaloGeoHelpers/CaloSampling.h:22
xAOD::CaloCluster_v1::energy_max
float energy_max(const CaloSample sampling) const
Retrieve maximum cell energy in given sampling.
Definition: CaloCluster_v1.cxx:563
ATH_MSG_DEBUG
#define ATH_MSG_DEBUG(x)
Definition: AthMsgStreamMacros.h:29
xAOD::CaloCluster_v1::CELL_SIG_SAMPLING
@ CELL_SIG_SAMPLING
CaloSample of the cell with the largest |E|/sig.
Definition: CaloCluster_v1.h:161
xAOD::CaloCluster_v1::ENG_CALIB_TOT
@ ENG_CALIB_TOT
Calibration Hit energy inside the cluster.
Definition: CaloCluster_v1.h:195
CaloGPUClusterAndCellDataMonitor::m_cellsKey
SG::ReadHandleKey< CaloCellContainer > m_cellsKey
vector of names of the cell containers to use as input.
Definition: CaloGPUClusterAndCellDataMonitor.h:204
CaloGPUClusterAndCellDataMonitor::m_clusterPropertiesToDo
std::vector< bool > m_clusterPropertiesToDo
Control which properties will actually be calculated and stored.
Definition: CaloGPUClusterAndCellDataMonitor.h:295
xAOD::CaloCluster_v1::ENG_CALIB_FRAC_EM
@ ENG_CALIB_FRAC_EM
Calibration Hit energy inside the cluster caused by e/gamma/pi0.
Definition: CaloCluster_v1.h:248
xAOD::CaloCluster_v1::ISOLATION
@ ISOLATION
Energy weighted fraction of non-clustered perimeter cells.
Definition: CaloCluster_v1.h:146
xAOD::CaloCluster_v1::ENG_CALIB_FRAC_REST
@ ENG_CALIB_FRAC_REST
Calibration Hit energy inside the cluster caused by other particles.
Definition: CaloCluster_v1.h:253
checkCorrelInHIST.prefix
dictionary prefix
Definition: checkCorrelInHIST.py:391
CaloRecGPU::ClusterInfoArr
Definition: EventInfoDefinitions.h:328
CaloGPUClusterAndCellDataMonitor::m_mutex
std::mutex m_mutex
This mutex is locked to ensure only one thread detects the monotired variables.
Definition: CaloGPUClusterAndCellDataMonitor.h:313
test_pyathena.parent
parent
Definition: test_pyathena.py:15
CaloRecGPU::ConstantDataHolder::m_cell_noise
CaloRecGPU::Helpers::CPU_object< CaloRecGPU::CellNoiseArr > m_cell_noise
Definition: DataHolders.h:26
CaloGPUClusterAndCellDataMonitor::m_matchingOptions
Gaudi::Property< MatchingOptions > m_matchingOptions
Option for adjusting the parameters for the cluster matching algorithm.
Definition: CaloGPUClusterAndCellDataMonitor.h:231
xAOD::CaloCluster_v1::DELTA_PHI
@ DELTA_PHI
Angular shower axis deviation ( ) from IP-to-Center.
Definition: CaloCluster_v1.h:126
xAOD::CaloCluster_v1::ENG_CALIB_DEAD_FCAL
@ ENG_CALIB_DEAD_FCAL
Attached Calibration Hit energy in dead material before FCAL, between FCAL and HEC.
Definition: CaloCluster_v1.h:241
ATH_CHECK
#define ATH_CHECK
Definition: AthCheckMacros.h:40
CaloGPUClusterAndCellDataMonitor::m_doClusters
bool m_doClusters
Definition: CaloGPUClusterAndCellDataMonitor.h:302
xAOD::CaloCluster_v1::phiSample
float phiSample(const CaloSample sampling) const
Retrieve barycenter in a given sample.
Definition: CaloCluster_v1.cxx:547
CaloRecGPU::NCaloCells
constexpr int NCaloCells
Definition: BaseDefinitions.h:13
AthCommonDataStore< AthCommonMsg< AlgTool > >::m_detStore
StoreGateSvc_t m_detStore
Pointer to StoreGate (detector store by default)
Definition: AthCommonDataStore.h:393
SG::VarHandleKey::initialize
StatusCode initialize(bool used=true)
If this object is used as a property, then this should be called during the initialize phase.
Definition: AthToolSupport/AsgDataHandles/Root/VarHandleKey.cxx:103
xAOD::double
double
Definition: CompositeParticle_v1.cxx:159
xAOD::CaloCluster_v1::FIRST_ENG_DENS
@ FIRST_ENG_DENS
First Moment in E/V.
Definition: CaloCluster_v1.h:143
CaloGPUClusterAndCellDataMonitor::m_extraComparedClusterPropertiesToDo
std::vector< bool > m_extraComparedClusterPropertiesToDo
Definition: CaloGPUClusterAndCellDataMonitor.h:296
xAOD::CaloCluster_v1::getCellLinks
const CaloClusterCellLink * getCellLinks() const
Get a pointer to the CaloClusterCellLink object (const version)
Definition: CaloCluster_v1.cxx:905
AthAlgTool::AthAlgTool
AthAlgTool()
Default constructor:
xAOD::CaloCluster_v1::ENG_BAD_CELLS
@ ENG_BAD_CELLS
Total em-scale energy of bad cells in this cluster.
Definition: CaloCluster_v1.h:148
CaloRecGPU::CellInfoArr
Definition: EventInfoDefinitions.h:188
SG::VarHandleKeyArray::renounce
virtual void renounce()=0
SG::HandleClassifier::type
std::conditional< std::is_base_of< SG::VarHandleKeyArray, T >::value, VarHandleKeyArrayType, type2 >::type type
Definition: HandleClassifier.h:54
CaloGPUClusterAndCellDataMonitor::m_comparedCellTypesToDo
std::vector< bool > m_comparedCellTypesToDo
Definition: CaloGPUClusterAndCellDataMonitor.h:298
xAOD::CaloCluster_v1::TILE_CONFIDENCE_LEVEL
@ TILE_CONFIDENCE_LEVEL
Confidence Level of a tile calorimeter cluster to be noise.
Definition: CaloCluster_v1.h:178
xAOD::CaloCluster_v1::ENG_CALIB_EME0
@ ENG_CALIB_EME0
Calibration Hit energy inside the cluster endcap presampler.
Definition: CaloCluster_v1.h:220
xAOD::CaloCluster_v1::ENG_FRAC_EM
@ ENG_FRAC_EM
Energy fraction in EM calorimeters.
Definition: CaloCluster_v1.h:139
CaloGPUClusterAndCellDataMonitor::filter_tool_by_name
bool filter_tool_by_name(const std::string &tool_name) const
Returns true if this tool should be plotted for.
Definition: CaloGPUClusterAndCellDataMonitor.cxx:255
xAOD::CaloCluster_v1::ENG_CALIB_DEAD_M
@ ENG_CALIB_DEAD_M
Attached Calibration Hit energy in dead material with medium matching (Angle < 0.5).
Definition: CaloCluster_v1.h:211
merge_scale_histograms.doc
string doc
Definition: merge_scale_histograms.py:9
name
std::string name
Definition: Control/AthContainers/Root/debug.cxx:192
CaloGPUClusterAndCellDataMonitor::compactify_clusters
StatusCode compactify_clusters(const EventContext &ctx, const CaloRecGPU::ConstantDataHolder &constant_data, const CaloRecGPU::Helpers::CPU_object< CaloRecGPU::CellInfoArr > &cell_info, CaloRecGPU::Helpers::CPU_object< CaloRecGPU::CellStateArr > &cell_state, CaloRecGPU::Helpers::CPU_object< CaloRecGPU::ClusterInfoArr > &clusters, CaloRecGPU::Helpers::CPU_object< CaloRecGPU::ClusterMomentsArr > &moments) const
Remove invalid clusters, reorder by ET and update the tags accordingly.
Definition: CaloGPUClusterAndCellDataMonitor.cxx:481
plotBeamSpotMon.b
b
Definition: plotBeamSpotMon.py:77
xAOD::CaloCluster_v1::ENG_CALIB_DEAD_HEC0
@ ENG_CALIB_DEAD_HEC0
Attached Calibration Hit energy in dead material between EME3 and HEC0.
Definition: CaloCluster_v1.h:238
CaloGPUClusterAndCellDataMonitor::m_doCells
bool m_doCells
If no properties are asked for, skip the relevant loops entirely...
Definition: CaloGPUClusterAndCellDataMonitor.h:302
AtlCoolConsole.tool
tool
Definition: AtlCoolConsole.py:453
CaloCell::ID
Identifier ID() const
get ID (from cached data member) non-virtual and inline for fast access
Definition: CaloCell.h:279
CaloRecGPU::ClusterMomentsArr
Definition: EventInfoDefinitions.h:342
xAOD::CaloCluster_v1::AVG_TILE_Q
@ AVG_TILE_Q
Sum(E_cell_Tile^2 Q_cell_Tile)/Sum(E_cell_Tile^2)
Definition: CaloCluster_v1.h:165
LArNewCalib_Delay_OFC_Cali.check
check
Definition: LArNewCalib_Delay_OFC_Cali.py:208
xAOD::CaloCluster_v1::PHICALOFRAME
@ PHICALOFRAME
Phi in the calo frame (for egamma)
Definition: CaloCluster_v1.h:188
CaloRecGPU::ClusterTag::is_part_of_cluster
constexpr bool is_part_of_cluster() const
Definition: TagDefinitions.h:233
CaloGPUClusterAndCellDataMonitor::m_termThreshold
Gaudi::Property< float > m_termThreshold
Cell (terminal) threshold to use for cluster matching.
Definition: CaloGPUClusterAndCellDataMonitor.h:189
xAOD::CaloCluster_v1::ENG_CALIB_DEAD_TILEG3
@ ENG_CALIB_DEAD_TILEG3
Attached Calibration Hit energy in dead material before scintillator.
Definition: CaloCluster_v1.h:232
CaloGPUClusterAndCellDataMonitor::match_clusters_perfectly
StatusCode match_clusters_perfectly(sample_comparisons_holder &sch, const CaloRecGPU::ConstantDataHolder &constant_data, const CaloRecGPU::CellInfoArr &cell_info, const CaloRecGPU::CellStateArr &cell_state_1, const CaloRecGPU::CellStateArr &cell_state_2, const CaloRecGPU::ClusterInfoArr &cluster_info_1, const CaloRecGPU::ClusterInfoArr &cluster_info_2, const CaloRecGPU::ClusterMomentsArr &, const CaloRecGPU::ClusterMomentsArr &, const bool match_without_shared) const
Definition: CaloGPUClusterAndCellDataMonitor.cxx:965
xAOD::CaloCluster_v1::FIRST_ETA
@ FIRST_ETA
First Moment in .
Definition: CaloCluster_v1.h:122
MatchingOptions
Definition: CaloGPUClusterAndCellDataMonitorOptions.h:355
xAOD::CaloCluster_v1::DELTA_THETA
@ DELTA_THETA
Angular shower axis deviation ( ) from IP-to-Center.
Definition: CaloCluster_v1.h:128
DeMoScan.index
string index
Definition: DeMoScan.py:362
xAOD::CaloCluster_v1::eSample
float eSample(const CaloSample sampling) const
Definition: CaloCluster_v1.cxx:521
DiTauMassTools::MaxHistStrategyV2::e
e
Definition: PhysicsAnalysis/TauID/DiTauMassTools/DiTauMassTools/HelperFunctions.h:26
CaloGPUClusterAndCellDataMonitor::m_numToolsToKeep
int m_numToolsToKeep
The number of tools that will actually need to be kept in memory for combined plotting.
Definition: CaloGPUClusterAndCellDataMonitor.h:261
a
TList * a
Definition: liststreamerinfos.cxx:10
xAOD::CaloCluster_v1::ENG_CALIB_DEAD_TOT
@ ENG_CALIB_DEAD_TOT
Attached Calibration Hit energy in dead material.
Definition: CaloCluster_v1.h:224
h
CaloCell
Data object for each calorimeter readout cell.
Definition: CaloCell.h:57
CaloGPUClusterAndCellDataMonitor::add_combination
StatusCode add_combination(const EventContext &ctx, const CaloRecGPU::ConstantDataHolder &constant_data, const int index_1, const int index_2, const std::string &prefix, const bool match_in_energy, const bool match_without_shared, const bool match_perfectly) const
Definition: CaloGPUClusterAndCellDataMonitor.cxx:1843
CondAlgsOpts.found
int found
Definition: CondAlgsOpts.py:101
python.CaloScaleNoiseConfig.str
str
Definition: CaloScaleNoiseConfig.py:78
xAOD::CaloCluster_v1::SIGNIFICANCE
@ SIGNIFICANCE
Cluster significance.
Definition: CaloCluster_v1.h:157
std::sort
void sort(typename std::reverse_iterator< DataModel_detail::iterator< DVL > > beg, typename std::reverse_iterator< DataModel_detail::iterator< DVL > > end, const Compare &comp)
Specialization of sort for DataVector/List.
Definition: DVL_algorithms.h:623
ATH_MSG_WARNING
#define ATH_MSG_WARNING(x)
Definition: AthMsgStreamMacros.h:32
ref
const boost::regex ref(r_ef)
xAOD::CaloCluster_v1::PHI2CALOFRAME
@ PHI2CALOFRAME
Phi of sampling 2 in the calo frame (for egamma)
Definition: CaloCluster_v1.h:192
xAOD::CaloCluster_v1::N_BAD_HV_CELLS
@ N_BAD_HV_CELLS
number of cells with bad HV
Definition: CaloCluster_v1.h:168
python.CaloScaleNoiseConfig.type
type
Definition: CaloScaleNoiseConfig.py:78
CaloRecGPU::QualityProvenance
Definition: EventInfoDefinitions.h:116
RunTileMonitoring.clusters
clusters
Definition: RunTileMonitoring.py:133
if
if(febId1==febId2)
Definition: LArRodBlockPhysicsV0.cxx:569
SG::VarHandleBase::vhKey
SG::VarHandleKey & vhKey()
Return a non-const reference to the HandleKey.
Definition: StoreGate/src/VarHandleBase.cxx:616
xAOD::CaloCluster_v1::ENG_CALIB_DEAD_L
@ ENG_CALIB_DEAD_L
Attached Calibration Hit energy in dead material with loose matching (Angle < 1.0).
Definition: CaloCluster_v1.h:208
declareProperty
#define declareProperty(n, p, h)
Definition: BaseFakeBkgTool.cxx:15
CaloRecGPU::CellInfoArr::is_valid
constexpr bool is_valid(const int cell) const
Definition: EventInfoDefinitions.h:316
xAOD::CaloCluster_v1::LATERAL
@ LATERAL
Normalized lateral moment.
Definition: CaloCluster_v1.h:137
CaloGPUClusterAndCellDataMonitor::m_seed_weight
double m_seed_weight
Definition: CaloGPUClusterAndCellDataMonitor.h:242
CaloGPUClusterAndCellDataMonitor
Places (matched) cluster and cell properties in monitored variables to enable plotting with the Athen...
Definition: CaloGPUClusterAndCellDataMonitor.h:42
xAOD::CaloCluster_v1::SECOND_TIME
@ SECOND_TIME
Second moment of cell time distribution in cluster.
Definition: CaloCluster_v1.h:180
str
Definition: BTagTrackIpAccessor.cxx:11
python.Bindings.keys
keys
Definition: Control/AthenaPython/python/Bindings.py:790
xAOD::CaloCluster_v1::DELTA_ALPHA
@ DELTA_ALPHA
Angular shower axis deviation ( ) from IP-to-Center.
Definition: CaloCluster_v1.h:130
xAOD::CaloCluster_v1::ENG_CALIB_FRAC_HAD
@ ENG_CALIB_FRAC_HAD
Calibration Hit energy inside the cluster caused by charged pi+ and pi-.
Definition: CaloCluster_v1.h:251
xAOD::CaloCluster_v1::CELL_SIGNIFICANCE
@ CELL_SIGNIFICANCE
Cell significance = E/sig of the cell with the largest |E|/sig.
Definition: CaloCluster_v1.h:159
xAOD::CaloCluster_v1::ENG_CALIB_OUT_L
@ ENG_CALIB_OUT_L
Attached Calibration Hit energy outside clusters but inside the calorimeter with loose matching (Angl...
Definition: CaloCluster_v1.h:196
xAOD::CaloCluster_v1::ENG_CALIB_DEAD_EME0
@ ENG_CALIB_DEAD_EME0
Attached Calibration Hit energy in dead material before EME0, between EME0 and EME1.
Definition: CaloCluster_v1.h:235
CaloCondBlobAlgs_fillNoiseFromASCII.tag
string tag
Definition: CaloCondBlobAlgs_fillNoiseFromASCII.py:24
xAOD::CaloCluster_v1::ENG_CALIB_OUT_T
@ ENG_CALIB_OUT_T
Attached Calibration Hit energy outside clusters but inside the calorimeter with tight matching (Angl...
Definition: CaloCluster_v1.h:204
CaloGPUClusterAndCellDataMonitor::m_toolCombinations
std::vector< pair_to_plot > m_toolCombinations
Definition: CaloGPUClusterAndCellDataMonitor.h:272
xAOD::CaloCluster_v1::BAD_CELLS_CORR_E
@ BAD_CELLS_CORR_E
Energy of bad cells with energy density average correction applied.
Definition: CaloCluster_v1.h:153
Monitored::Scalar
Declare a monitored scalar variable.
Definition: MonitoredScalar.h:34
CaloRecGPU::CellInfoArr::is_bad
static constexpr bool is_bad(const bool is_tile, const QualityProvenance qp, const bool treat_L1_predicted_as_good=false)
GPU version of CaloBadCellHelper::isBad.
Definition: EventInfoDefinitions.h:199
athena.opts
opts
Definition: athena.py:86
xAOD::CaloCluster_v1::ETACALOFRAME
@ ETACALOFRAME
Eta in the calo frame (for egamma)
Definition: CaloCluster_v1.h:187
xAOD::CaloCluster_v1::N_BAD_CELLS_CORR
@ N_BAD_CELLS_CORR
Number of bad cells with energy density average correction applied.
Definition: CaloCluster_v1.h:151
xAOD::CaloCluster_v1::LONGITUDINAL
@ LONGITUDINAL
Normalized longitudinal moment.
Definition: CaloCluster_v1.h:138
CaloGPUClusterAndCellDataMonitor::ATLAS_THREAD_SAFE
std::map< std::string, std::atomic< size_t > > m_numClustersPerTool ATLAS_THREAD_SAFE
Counts the total number of clusters per tool.
Definition: CaloGPUClusterAndCellDataMonitor.h:275
xAOD::CaloCluster_v1::NVERTEX_FRACTION
@ NVERTEX_FRACTION
slightly updated vertex fraction more pile up independent (similar to nJVF)
Definition: CaloCluster_v1.h:185
xAOD::CaloCluster_v1::N_BAD_CELLS
@ N_BAD_CELLS
number of bad cells
Definition: CaloCluster_v1.h:149
AthCommonDataStore::declareGaudiProperty
Gaudi::Details::PropertyBase & declareGaudiProperty(Gaudi::Property< T > &hndl, const SG::VarHandleKeyType &)
specialization for handling Gaudi::Property<SG::VarHandleKey>
Definition: AthCommonDataStore.h:156
CaloGPUClusterAndCellDataMonitor::convert_to_GPU_data_structures
StatusCode convert_to_GPU_data_structures(const EventContext &ctx, const CaloRecGPU::ConstantDataHolder &constant_data, const xAOD::CaloClusterContainer *cluster_collection_ptr, CaloRecGPU::Helpers::CPU_object< CaloRecGPU::CellInfoArr > &cell_info, CaloRecGPU::Helpers::CPU_object< CaloRecGPU::CellStateArr > &cell_state, CaloRecGPU::Helpers::CPU_object< CaloRecGPU::ClusterInfoArr > &clusters, CaloRecGPU::Helpers::CPU_object< CaloRecGPU::ClusterMomentsArr > &moments) const
Definition: CaloGPUClusterAndCellDataMonitor.cxx:265
xAOD::CaloCluster_v1::e
virtual double e() const
The total energy of the particle.
Definition: CaloCluster_v1.cxx:265
xAOD::CaloCluster_v1::CENTER_Y
@ CENTER_Y
Cluster Centroid ( )
Definition: CaloCluster_v1.h:132
xAOD::CaloCluster_v1::ENG_CALIB_DEAD_EMB0
@ ENG_CALIB_DEAD_EMB0
Attached Calibration Hit energy in dead material before EMB0, between EMB0 and EMB1.
Definition: CaloCluster_v1.h:227
constants.EME2
int EME2
Definition: Calorimeter/CaloClusterCorrection/python/constants.py:56
CaloRecGPU::ClusterTag::secondary_cluster_weight
constexpr int32_t secondary_cluster_weight() const
Definition: TagDefinitions.h:263
CaloGPUClusterAndCellDataMonitor::m_toolsToPlot
Gaudi::Property< std::vector< SimpleSingleTool > > m_toolsToPlot
Tools to plot individually.
Definition: CaloGPUClusterAndCellDataMonitor.h:221
CaloGPUClusterAndCellDataMonitor::m_doCombinedClusters
bool m_doCombinedClusters
Definition: CaloGPUClusterAndCellDataMonitor.h:302
match
bool match(std::string s1, std::string s2)
match the individual directories of two strings
Definition: hcg.cxx:356
fitman.k
k
Definition: fitman.py:528
xAOD::CaloCluster_v1::ENG_POS
@ ENG_POS
Total positive Energy of this cluster.
Definition: CaloCluster_v1.h:156
CaloGPUClusterAndCellDataMonitor::m_comparedCellPropertiesToDo
std::vector< bool > m_comparedCellPropertiesToDo
Definition: CaloGPUClusterAndCellDataMonitor.h:297
CaloGPUClusterAndCellDataMonitor::m_pairsToPlot
Gaudi::Property< std::vector< SimpleToolPair > > m_pairsToPlot
Pairs of tools to compare.
Definition: CaloGPUClusterAndCellDataMonitor.h:226
xAOD::CaloCluster_v1::numberCellsInSampling
int numberCellsInSampling(const CaloSample samp, bool isInnerWheel=false) const
Returns number of cells in given sampling.
Definition: CaloCluster_v1.cxx:802
xAOD::CaloCluster_v1::BADLARQ_FRAC
@ BADLARQ_FRAC
Energy fraction of LAr cells with quality larger than a given cut.
Definition: CaloCluster_v1.h:155
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