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Histogram.h
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// -*- C++ -*-
//
// Histogram.h is a part of Herwig++ - A multi-purpose Monte Carlo event generator
// Copyright (C) 2002-2007 The Herwig Collaboration
//
// Herwig++ is licenced under version 2 of the GPL, see COPYING for details.
// Please respect the MCnet academic guidelines, see GUIDELINES for details.
//
#ifndef HERWIG_Histogram_H
#define HERWIG_Histogram_H
//
// This is the declaration of the Histogram class.
//
#include "Histogram.fh"
#include "ThePEG/Interface/Interfaced.h"
#include "Statistic.h"
#include <string>
// workaround for OS X bug where isnan() and isinf() are hidden
// when <iostream> is included
extern "C" int isnan(double) throw();
namespace Herwig {
using namespace ThePEG;
/**
* Options for histogram output.
* They can be combined using the '|' operator, e.g. 'Frame | Ylog'
*/
namespace HistogramOptions {
const unsigned int None = 0; /**< No options */
const unsigned int Frame = 1; /**< Plot on new frame */
const unsigned int Errorbars = 1 << 1; /**< Plot error bars */
const unsigned int Xlog = 1 << 2; /**< log scale for x-axis */
const unsigned int Ylog = 1 << 3; /**< log scale for y-axis */
const unsigned int Smooth = 1 << 4; /**< smooth the line */
const unsigned int Rawcount = 1 << 5; /**< don't normalize to unit area */
}
/**
* The Histogram class is a simple histogram for the Analysis handlers.
*
* @see \ref HistogramInterfaces "The interfaces"
* defined for Histogram.
*/
class Histogram: public Interfaced {
public:
/** @name Standard constructors and destructors. */
//@{
/**
* The default constructor.
* @param lower The lower limit of the histogram
* @param upper The upper limit of the histogram
* @param nbin Number of bins
*/
inline Histogram(double lower=0., double upper=0., unsigned int nbin=0);
/**
* Constructor for variable width bins
* @param limits The lower limits for the bins followed by the upper limit of the last bin
*/
inline Histogram(vector<double> limits);
/**
* Constructor with data included
* @param limits The lower limits for the bins followed by the upper limit of the last bin
* @param data The data
* @param dataerror The errors on the data
*/
inline Histogram(vector<double> limits, vector<double> data, vector<double> dataerror);
//@}
public:
/**
* Operator to add a point to the histogrma with unit weight
*/
inline void operator+=(double);
/**
* Function to add a weighted point to the histogram
*/
inline void addWeighted(double data, double weight);
/**
* Number of bins (not counting the overflow)
*/
inline unsigned int numberOfBins() const;
/**
* Get the prefactor
*/
inline double prefactor() const;
/**
* Set the prefactor
*/
inline void prefactor(double );
/**
* Access to the statistics on the total entry of the histogram
*/
inline const Statistic & globalStatistics() const;
/**
* Normalise the distributions to the data
*/
void normaliseToData();
/**
* Normalise the distributions to the total cross section
*/
void normaliseToCrossSection();
/**
* Return the chi squared
* @param chisq The chi squared
* @param ndegrees The number of points
* @param minfrac The minimum fractional error on the data point
*/
void chiSquared(double & chisq,
unsigned int & ndegrees, double minfrac=0.) const;
/**
* Output as a topdrawer file. The histogram is normalised to unit area
* @param out The output stream
* @param flags A bitmask of flags from HistogramOptions, e.g. Frame|Ylog
* @param colour The colour for the line
* @param title The title for the top of the plot
* @param titlecase topdraw format for the title
* @param left Left axis lable
* @param leftcase topdraw format for left axis label
* @param bottom Bottom axis lable
* @param bottomcase Bottom axis lable ofr topdraw
* N.B. in td smoothing only works for histograms with uniform binning.
*/
void topdrawOutput(ostream & out,
unsigned int flags = 0,
string colour = string("BLACK"),
string title = string(),
string titlecase = string(),
string left = string(),
string leftcase = string(),
string bottom = string(),
string bottomcase = string()
) const;
/**
* get the number of visible entries (all entries without those in the
* under- and overflow bins) in the histogram. This assumes integer
* entries, ie it gives wrong results for weighted histograms.
*/
unsigned int visibleEntries() const;
/**
* Compute the normalisation of the data.
*/
double dataNorm() const;
/**
* Output into a simple ascii file, easily readable by gnuplot.
*/
void simpleOutput(ostream & out, bool errorbars, bool normdata=false);
/**
* Dump bin data into a vector
*/
vector<double> dumpBins() const;
/**
* Returns a new histogram containing bin-by-bin ratios of two histograms
*/
Histogram ratioWith(const Histogram & h2) const;
public:
/**
* The standard Init function used to initialize the interfaces.
* Called exactly once for each class by the class description system
* before the main function starts or
* when this class is dynamically loaded.
*/
static void Init();
protected:
/** @name Clone Methods. */
//@{
/**
* Make a simple clone of this object.
* @return a pointer to the new object.
*/
inline virtual IBPtr clone() const;
/** Make a clone of this object, possibly modifying the cloned object
* to make it sane.
* @return a pointer to the new object.
*/
inline virtual IBPtr fullclone() const;
//@}
private:
/**
* The static object used to initialize the description of this class.
* Indicates that this is a concrete class with persistent data.
*/
static NoPIOClassDescription<Histogram> initHistogram;
/**
* The assignment operator is private and must never be called.
* In fact, it should not even be implemented.
*/
Histogram & operator=(const Histogram &);
private:
/**
* Global statistics of all data that went into the histogram.
*/
Statistic _globalStats;
/**
* Set to true if there is experimental data available
*/
bool _havedata;
/**
* One bin of the histogram. limit is the _lower_ bound of the bin.
*/
struct Bin {
/**
* Default constructor
*/
Bin() : contents(0.0), contentsSq(0.0),
limit(0.0), data(0.0), dataerror(0.0) {}
/**
* Contents of the bin
*/
double contents;
/**
* Contents squared for the error
*/
double contentsSq;
/**
* The limit for the bin
*/
double limit;
/**
* The experimental value for the bin
*/
double data;
/**
* The error on the experimental value for the bin
*/
double dataerror;
};
/**
* The histogram bins. _bins[0] is the underflow, _bins.back() the overflow
*/
vector<Bin> _bins;
/**
* Prefactors to multiply the output by
*/
double _prefactor;
};
}
#include "ThePEG/Utilities/ClassTraits.h"
namespace ThePEG {
/** @cond TRAITSPECIALIZATIONS */
/** This template specialization informs ThePEG about the
* base classes of Histogram. */
template <>
struct BaseClassTrait<Herwig::Histogram,1> {
/** Typedef of the first base class of Histogram. */
typedef Herwig::Statistic NthBase;
};
/** This template specialization informs ThePEG about the name of
* the Histogram class and the shared object where it is defined. */
template <>
struct ClassTraits<Herwig::Histogram>
: public ClassTraitsBase<Herwig::Histogram> {
/** Return a platform-independent class name */
static string className() { return "Herwig::Histogram"; }
};
/** @endcond */
}
#include "Histogram.icc"
#ifndef ThePEG_TEMPLATES_IN_CC_FILE
// #include "Histogram.tcc"
#endif
// void SampleHistogram::printMoments(char* name, double Nmax, double dN,
// double x0, double x1) {
// ofstream out(name);
// if (!out) {
// cerr << "SampleHistoGram::printMoments: ERROR! Can't open file" << endl;
// }
// time_t now_t;
// now_t = time(0);
// out << "# created " << ctime(&now_t)
// << "# by SampleHistogram::printMoments(..., "
// << Nmax << ", " << dN << ")" << endl
// << "# " << this->samples() << " entries, mean +/- sigma = "
// << this->mean() << " +/- " << this->stdDev() << endl;
// double x0N, x1N, delta, hi;
// for (double N=dN; N < Nmax; N += dN) {
// double fN = 0.0;
// for(int i = 0; i < howManyBuckets-1; i++) {
// x0N = pow(bucketLimit[i], N);
// x1N = pow(bucketLimit[i+1], N);
// delta = (bucketLimit[i+1] - bucketLimit[i]);
// if (delta > 0 && this->samples() > 0
// && bucketLimit[i] >= x0 && bucketLimit[i] <= x1
// && bucketLimit[i+1] >= x0 && bucketLimit[i+1] <= x1) {
// hi = double(bucketCount[i+1]/(delta*(this->samples())));
// fN += hi*(x1N-x0N)/N;
// }
// }
// out << N
// << " "
// << fN << endl;
// }
// out.close();
// }
#endif /* HERWIG_Histogram_H */

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