EIC code displayed by LXR master/​include/​Rivet/​Tools/​Cutflow.hh	Source navigation Diff markup Identifier search General search
	Version: master test Revert   Change

File indexing completed on 2025-09-17 09:13:39

 #ifndef RIVET_Cutflow_HH
 #define RIVET_Cutflow_HH
 
 #include "Rivet/Tools/RivetYODA.hh"
 #include "Rivet/Tools/Utils.hh"
 
 #include <iomanip>
 #include <iostream>
 #include <vector>
 #include <sstream>
 #include <string>
 
 namespace Rivet {
 
   namespace {
     template<typename T>
     std::vector<T> operator+(std::vector<T>&& res, const std::vector<T>& vadd) {
       res.insert(std::end(res), std::begin(vadd), std::end(vadd));
       return std::move(res);
     }
   }
 
   /// A tracker of numbers & fractions of events passing sequential cuts
   class Cutflow : public YODA::BinnedHisto<std::string> {
   public:
 
     using BaseT = YODA::BinnedHisto<std::string>;
     using BinningT = BaseT::BinningT;
     using FillType = BaseT::FillType;
     using BinType = BaseT::BinT;
     using Ptr = std::shared_ptr<Cutflow>;
     using AnalysisObject::operator =;
 
     /// @brief Nullary constructor
     Cutflow() : BaseT(), icurr(0) {}
 
     /// @brief Constructor using binning object
     Cutflow(const BinningT& binning) : BaseT(binning), icurr(0) { }
 
     /// @brief Constructor using rvalue binning object
     Cutflow(BinningT&& binning) : BaseT(std::move(binning)), icurr(0) { }
 
     /// Proper constructor using a cutflow name and a list of edges
     ///
     /// @note the constructor will preprend the empty string as a pre-cut step.
     Cutflow(const std::vector<std::string>& edges, const std::string& path = "")
       : BaseT(std::vector<std::string>{""} + edges, path), icurr(0) { }
 
     /// @brief Fill function with FillType
     ///
     /// @note This method will set the current fill position icurr.
     virtual int fill(FillType&& coords, const double weight = 1.0, const double fraction = 1.0) {
       int pos = BaseT::fill(std::move(coords), weight, fraction);
       icurr = (size_t)pos; // cannot be negative for discrete AOs
       return pos;
     }
 
     /// @brief Fill function using an explicit coordinate
     //
     /// @note This method will set the current fill position icurr.
     virtual int fill(std::string val, const double weight = 1.0, const double fraction = 1.0) {
       int pos = BaseT::fill({val}, weight, fraction);
       icurr = (size_t)pos; // cannot be negative for discrete AOs
       return pos;
     }
 
     /// @brief Convenience method to fill the pre-cut step
     virtual int fillinit(const double weight=1.0, const double fraction=1.0) {
       return fill(""s, weight, fraction);
     }
 
     /// @brief Convenience method to fill the next cut step if @a cutresult is true
     virtual int fillnext(const bool cutresult, const double weight = 1.0, const double fraction = 1.0) {
       if (!cutresult)  return 0;
       const std::string edge = BaseT::bin(++icurr).xEdge();
       return fill(edge, weight, fraction);
     }
 
     /// @brief Convenience method to fill the next cut step
     virtual int fillnext(const double weight = 1.0, const double fraction = 1.0) {
       return fillnext(true, weight, fraction);
     }
 
     /// @brief Convenience method to fill the next cut steps from an n-element results vector @a cutresult
     virtual int fillnext(const std::vector<bool>& cutresults, const double weight = 1.0, const double fraction = 1.0) {
       if (icurr+cutresults.size() > BaseT::numBins()+1) {
         throw RangeError("Number of filled cut results needs to match the Cutflow construction (in cutflow '"+BaseT::path()+"')");
       }
       for (size_t i = 0; i < cutresults.size(); ++i) {
         if (!cutresults[i])  return 0;
         fillnext(weight, fraction); // also incremenrs icurr
       }
       return (int)icurr;
     }
 
     /// Returns current cutflow index for debugging
     size_t currentIndex() const {  return icurr; }
 
     /// Scale the cutflow weights by the given factor
     void scale(const double factor) {
       BaseT::scaleW(factor);
     }
 
     /// Scale the cutflow weights so that the weight count after cut @a edge is @a norm
     void normalizeStep(const std::string& edge, const double norm) {
       const auto& b = BaseT::binAt(edge);
       if (b.sumW() == 0) {
         MSG_WARNING("Failed to scale Cutflow " << BaseT::path() << " as bin " << edge << " is empty");
         return;
       }
       scale(norm/b.sumW());
     }
 
     /// Alias to scale the cutflow weights so that the weight after the pre-init cut is @a norm
     void normalizeFirst(const double norm) {
       normalizeStep(""s, norm);
     }
 
     /// Create a string representation
     string str() const {
       using namespace std;
       stringstream ss;
       ss << fixed << std::setprecision(1) << BaseT::bin(1).sumW();
       const size_t weight0len = ss.str().length();
       ss << fixed << std::setprecision(1) << BaseT::bin(1).effNumEntries();
       const size_t count0len = ss.str().length();
       ss.str("");
       ss << BaseT::path() << " cut-flow:\n";
       size_t maxnamelen = 0;
       for (const string& edge : BaseT::xEdges()) {
         maxnamelen = std::max(edge.length(), maxnamelen);
       }
       ss << setw(maxnamelen+5) << "" << "   "
          << setw(weight0len) << right << "Weight" << "   "
          << setw(count0len) << right << "Count" << "    "
          << setw(6) << right << "A_cumu" << "    "
          << setw(6) << right << "A_incr";
       //for (size_t i = 0; i <= ncuts; ++i) {
       const double wtot = BaseT::bin(1).sumW();
       double wlast = wtot;
       for (const auto& bin : BaseT::bins()) {
         const size_t i = bin.index();
         const int pcttot = (wtot == 0) ? -1 : round(100*bin.sumW()/wtot);
         const int pctinc = (i == 1 || wlast == 0) ? -1 : round(100*bin.sumW()/wlast);
         wlast = bin.sumW();
         stringstream ss2;
         ss2 << fixed << setprecision(1) << bin.sumW();
         const string weightstr = ss2.str(); ss2.str("");
         ss2 << fixed << setprecision(1) << bin.effNumEntries();
         const string countstr = ss2.str(); ss2.str("");
         ss2 << fixed << setprecision(3) << pcttot << "%";
         const string pcttotstr = ss2.str(); ss2.str("");
         ss2 << fixed << setprecision(3) << pctinc << "%";
         const string pctincstr = ss2.str();
         ss << "\n"
            << setw(maxnamelen+5) << left << (i == 1 ? "" : "Pass "+BaseT::bin(i).xEdge()) << "   "
            << setw(weight0len) << right << weightstr << "    "
            << setw(count0len) << right << countstr << "    "
            << setw(6) << right << (pcttot < 0 ? "- " : pcttotstr) << "    "
            << setw(6) << right << (pctinc < 0 ? "- " : pctincstr);
       }
       return ss.str();
     }
 
     /// Print string representation to a stream
     void print(std::ostream& os) const {
       os << str() << std::flush;
     }
 
   protected:
 
     /// Get a logger object.
     Log& getLog() const {
       return Rivet::Log::getLog("Rivet.Cutflow");
     }
 
     size_t icurr;
 
   };
 
 
   /// FillCollector specialisation for all Cutflow-like AO
   template <>
   class FillCollector<Cutflow> : public Cutflow {
   public:
 
     using YAO = Cutflow;
     using Ptr = shared_ptr<FillCollector<YAO>>;
     using YAO::operator =;
 
     FillCollector() : YAO() { }
 
     /// Constructor
     ///
     /// We call the cheaper constructor based on the
     /// binning to avoid copying of the bin content.
     /// The underlying binning object is still used
     /// in analize() by many routines, e.g. to query
     /// numBins() or to loop over bins() with
     /// subsequent calls to bin xEdge() etc.
     FillCollector(typename YAO::Ptr yao) : YAO(yao->binning()) {
       YAO::setPath(yao->path());
     }
 
     /// Overloaded fill method, which stores Fill info
     /// until Multiplexer<T>::collapseEventGroup() is called.
     ///
     /// @todo Do we need to deal with users using fractions directly?
     int fill(typename YAO::FillType&& fillCoords,
              const double weight=1.0, const double fraction=1.0) {
       (void)fraction; // suppress unused variable warning
       YAO::icurr = YAO::_binning.globalIndexAt(fillCoords);
       _fills.insert(_fills.end(), { std::move(fillCoords), weight } );
       return (int)YAO::icurr;
     }
 
     int fill(const std::string val, const double weight = 1.0, const double fraction = 1.0) {
       return fill(typename YAO::FillType{val}, weight, fraction);
     }
 
     int fillnext(const bool cutresult, const double weight = 1.0, const double fraction = 1.0) {
       if (!cutresult)  return 0;
       return fill(YAO::bin(++YAO::icurr).xEdge(), weight, fraction);
     }
 
     int fillnext(const double weight = 1.0, const double fraction = 1.0) {
       return fillnext(true, weight, fraction);
     }
 
     int fillnext(const std::vector<bool>& cutresults, const double weight = 1.0, const double fraction = 1.0) {
       if (YAO::icurr+cutresults.size() > YAO::numBins()+1) {
         throw RangeError("Number of filled cut results needs to match the Cutflow construction (in cutflow '"+YAO::path()+"')");
       }
       for (size_t i = 0; i < cutresults.size(); ++i) {
         if (!cutresults[i])  return 0;
         fillnext(weight, fraction);
       }
       return (int)YAO::icurr;
     }
 
     int fillinit(const double weight=1.0, const double fraction=1.0) {
       return fill(""s, weight, fraction);
     }
 
     /// Empty the subevent stack (for start of new event group).
     void reset() noexcept { _fills.clear(); }
 
     /// Access the fill info subevent stack.
     const Fills<YAO>& fills() const { return _fills; }
 
   private:
 
     Fills<YAO> _fills;
 
   };
 
 
   /// @name Cutflow utilities
   /// @{
 
   /// Convenience alias
   using CutflowPtr = MultiplexPtr<Multiplexer<Cutflow>>;
 
   /// Print a Cutflow to a stream
   inline std::ostream& operator << (std::ostream& os, const Cutflow& cf) {
     return os << cf.str();
   }
 
   inline std::ostream& operator << (std::ostream& os, const CutflowPtr& cf) {
     return os << cf->str();
   }
 
   /// @}
 
 
   /// A container for several Cutflow objects, with some convenient batch access
   class Cutflows : public YODA::FillableStorage<2, CutflowPtr, std::string>,
                      public YODA::Fillable {
   public:
 
     using BaseT = YODA::FillableStorage<2, CutflowPtr, std::string>;
     using BinContentT = CutflowPtr;
     using BinT = YODA::Bin<1, BinContentT, BaseT::BinningT>;
     using FillDim = std::integral_constant<size_t, 2>;
 
     /// @name Constructors
     /// @{
 
     /// Nullary constructor
     Cutflows() : BaseT(groupAdapter<FillDim{}, BinContentT, std::string>) { }
 
     /// Constructor using a vector of (outer) edges
     Cutflows(const std::vector<std::string>& edges)
          : BaseT(YODA::Axis<std::string>(edges), groupAdapter<FillDim{}, BinContentT, std::string>) { }
 
     /// Constructor using an initializer_set of (outer) edges
     Cutflows(std::initializer_list<std::string>&& edges)
          : BaseT(YODA::Axis<std::string>(std::move(edges)), groupAdapter<FillDim{}, BinContentT, std::string>) { }
 
     /// @}
 
     /// @name Fill methods
     /// @{
 
     /// Fill method using the FillType of the underlying FIllableStorage
     int fill(const std::string& grpCoord, const std::string& edge, const double weight = 1.0, const double fraction = 1.0) {
       auto& cfl = BaseT::binAt({grpCoord});
       if (!cfl.raw())  return -1; // nullptr if bin not booked
       return cfl->fill({edge}, weight, fraction);
     }
 
     /// Method to fill the pre-cut steps
     int groupfillinit(const double weight=1.0, const double fraction=1.0) {
       bool pass = true;
       for (auto& cfl : BaseT::bins()) {
         if (!cfl.get())  continue;
         pass &= cfl->fillinit(weight, fraction);
       }
       return (int)pass;
     }
 
     /// Method to fill the next step if @a cutresult is true
     int groupfillnext(const bool cutresult, const double weight = 1.0, const double fraction = 1.0) {
       if (!cutresult)  return 0;
       bool pass = true;
       for (auto& cfl : BaseT::bins()) {
         if (!cfl.get())  continue;
         pass &= cfl->fillnext(cutresult, weight, fraction);
       }
       return (int)pass;
     }
 
     /// Short-hand method that assumes the cut result is true
     int groupfillnext(const double weight = 1.0, const double fraction = 1.0) {
       return groupfillnext(true, weight, fraction);
     }
 
     /// Method using a vector of @a cutresults
     int groupfillnext(const std::vector<bool>& cutresults, const double weight = 1.0, const double fraction = 1.0) {
       bool pass = true;
       for (auto& cfl : BaseT::bins()) {
         if (!cfl.get())  continue;
         pass &= cfl->fillnext(cutresults, weight, fraction);
       }
       return (int)pass;
     }
 
     /// Method that only fills the next step at coordinate @a grpCoord
     int fillnext(const std::string& grpCoord, const double weight=1.0, const double fraction=1.0) {
       return BaseT::binAt(grpCoord)->fillnext(weight, fraction);
     }
 
     /// Method that only fills the next step at coordinate @a grpCoord if @a cutresult is true
     int fillnext(const std::string& grpCoord, const bool cutresult, const double weight=1.0, const double fraction=1.0) {
       return BaseT::binAt(grpCoord)->fillnext(cutresult, weight, fraction);
     }
 
     /// Method that only fills the next step at coordinate @a grpCoord using a vector of @a cutresults
     int fillnext(const std::string& grpCoord, const std::vector<bool>& cutresults,
                  const double weight = 1.0, const double fraction = 1.0) {
       return BaseT::binAt(grpCoord)->fillnext(cutresults, weight, fraction);
     }
 
     /// @}
 
     /// @name Reset methods
     /// @{
 
     /// @brief Reset the histogram.
     ///
     /// Keep the binning but set all bin contents and related quantities to zero
     void reset() noexcept { BaseT::reset(); }
 
     /// @}
 
     /// @name Whole histo data
     /// @{
 
     /// @brief Fill dimension of the object (number of conent axes + temprary axis)
     size_t fillDim() const noexcept { return FillDim{}; }
 
     /// @brief Total dimension of the object (number of fill axes + filled value)
     size_t dim() const noexcept { return fillDim()+1; }
 
     /// @brief Get the number of fills (fractional fills are possible).
     double numEntries(const bool includeOverflows=true) const noexcept {
       double n = 0;
       for (const auto& cfl : BaseT::bins(includeOverflows)) {
         if (!cfl.get())  continue;
         n += cfl->numEntries(includeOverflows);
       }
       return n;
     }
 
     /// @brief Get the effective number of fills.
     double effNumEntries(const bool includeOverflows=true) const noexcept {
       double n = 0;
       for (const auto& cfl : BaseT::bins(includeOverflows)) {
         if (!cfl.get())  continue;
         n += cfl->effNumEntries(includeOverflows);
       }
       return n;
     }
 
     /// @brief Calculates sum of weights in histo group.
     double sumW(const bool includeOverflows=true) const noexcept {
       double sumw = 0;
       for (const auto& cfl : BaseT::bins(includeOverflows)) {
         if (!cfl.get())  continue;
         sumw += cfl->sumW(includeOverflows);
       }
       return sumw;
     }
 
     /// @brief Calculates sum of squared weights in histo group.
     double sumW2(const bool includeOverflows=true) const noexcept {
       double sumw2 = 0;
       for (const auto& cfl : BaseT::bins(includeOverflows)) {
         if (!cfl.get())  continue;
         sumw2 += cfl->sumW2(includeOverflows);
       }
       return sumw2;
     }
 
     /// @brief Get the total volume of the histogram group.
     double integral(const bool includeOverflows=true) const noexcept {
       return sumW(includeOverflows);
     }
 
     /// @brief Get the total volume error of the histogram group.
     double integralError(const bool includeOverflows=true) const noexcept {
       return sqrt(sumW2(includeOverflows));
     }
 
     /// @}
 
     /// @name Transformations
     /// @{
 
     /// @brief Rescale as if all fill weights had been different by factor @a scalefactor.
     void scaleW(const double scalefactor) noexcept {
       for (auto& cfl : BaseT::bins(true, true)) {
         if (!cfl.get())  continue;
         cfl->scaleW(scalefactor);
       }
     }
 
     /// @brief Rescale as if all fill weights had been different by factor @a scalefactor along dimension @a i.
     void scale(const double scalefactor) noexcept {
       for (auto& cfl : BaseT::bins(true, true)) {
         if (!cfl.get())  continue;
         cfl->scale(scalefactor);
       }
     }
 
     /// Scale the cutflow weights so that the weight count after cut @a edge is @a norm
     ///
     /// @note Consider each sub-histogram separately when calculating the integral.
     void normalizeStep(const std::string& edge, const double norm) {
       for (auto& cfl : BaseT::bins(true, true)) {
         if (!cfl.get())  continue;
         if (cfl->binAt(edge).sumW() != 0.)  cfl->normalizeStep(edge, norm);
       }
     }
 
     /// Alias to scale the cutflow weights so that the weight after the pre-init cut is @a norm
     void normalizeFirst(const double norm) {
       normalizeStep(""s, norm);
     }
 
     /// @}
 
     /// @name Streaming utilities
     /// @{
 
     /// Create a string representation
     string str() const {
       std::stringstream ss;
       for (auto& cf : BaseT::bins(true, true)) {
         if (!cf.get())  continue;
         ss << cf << "\n\n";
       }
       return ss.str();
     }
 
     /// Print string representation to a stream
     void print(std::ostream& os) const {
       os << str() << std::flush;
     }
 
     /// @}
 
   };
 
   /// @name Cutflows utilities
   /// @{
 
   /// Convenience alias
   using CutflowsPtr = std::shared_ptr<Cutflows>;
 
   /// Print a Cutflows to a stream
   inline std::ostream& operator << (std::ostream& os, const Cutflows& cfs) {
     return os << cfs.str();
   }
 
   /// Print a Cutflows to a stream
   inline std::ostream& operator << (std::ostream& os, const CutflowsPtr& cfs) {
     return os << cfs->str();
   }
 
   /// @}
 
 }
 
 #endif

This page was automatically generated by the 2.3.7 LXR engine. The LXR team