htl - histogram template library

25th May, 1999

HTL - Histogram Template Library

Pavel Binko , LHCb / CERN 1

LHCb Computing Meeting


Pavel Binko

LHCb / CERN

25th May, 1999




What is HTL ?

C++ class library– Provides powerful histogramming functionality– It only deals with histograms - binned data

(not with n-tuples - unbinned data)

– Exploits the template facility of C++– Designed to be compact, extensible, modular and performant– Uses “the same” basic signature as HBOOK subroutines

Histogram name, number of bins, lower and upper bounds of the histogram axis are enough to create a 1D histogram

Transient and Persistent Histograms are de-coupled– Uses Objectivity/DB for persistency– Light weight Persistent Object Manager available (pre-alpha version)

25th May, 1999




Histogram Classes

User works with these predefined types– Histo1D - 1D histogram with Gravity_Bin_1D and fixed binning– Histo1DVar - 1D histogram with Gravity_Bin_1D and variable binning– ProfileHisto - 1D histogram with Profile_Bin and fixed binning– ProfileHistoVar - 1D histogram with Profile_Bin and variable binning– Histo2D - 2D histogram with Weighted_Bin and fixed binning– Histo2DF - 2D histogram with Float_Weighted_Bin and fixed binning– Histo2DVar - 2D histogram with Weighted_Bin and variable binning

Persistent version of all of them available– PHisto1D etc.

25th May, 1999




Partitions and Bins

Partitions describe– One dimension of the problem space– How it is divided into intervals

Bins contain information about– The content, the error and possibly the center of the bin– Fix and variable binning available

Weighted_Bin represents bins with weighted data points– By default the gravity centers are the middle or center of the bin

Gravity_Bin_1D represents bins with weighted data points– They know how to determine the gravity center of the bins

Profile_Bin represents bins that can average another quantity

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I_Histo Interface

– virtual const char* name( ) – Title attached to current histogram.

– virtual I_Bin& i_bin( I_Bin_Location &a_location ) – virtual I_Bin& i_extra_bin( I_Extra_Bin_Location &a_location )

– In-range and extra bin associated with extra location a_location

– virtual Size bin_count( ) – virtual Size extra_bin_count( )

– Number of in-range and extra bins

– virtual Size dim( )– Dimension of the histo, i.e., of the problem space

– virtual I_Partition& i_partition( Index p = 0 ) – Partition interface of this histogram

– virtual I_Bin& i_bin( Index i )– Any bin (in-range or extra) with index "i" (note that this is a linear access)

25th May, 1999




I_Partition Interface

– virtual double i_bin_width( Index i ) – Width of in-range bin "i".

– virtual double i_lower_point( ) – Leftmost point of the partition.

– virtual double i_lower_point( Index i ) – Leftmost point of bin indexed by "i".

– virtual double i_upper_point( ) – Rightmost point of the partition.

– virtual double i_upper_point( Index i ) – Rightmost point of bin indexed by "i".

25th May, 1999




I_Bin Interface

– virtual double value( Index i = 0) and virtual double error( Index i = 0) – Value and error associated with this bin

– virtual Size count( ) – Count associated with this bin = Number of entries

– virtual void set_value( double other, Index i = 0 )– Set the value associated with this bin to "other"

– virtual void set_error( double other, Index i = 0 ) – Change/set the error of the bin to "other"

– virtual void set_count( Size other ) – Change/set the count of the bin to "other"

– virtual double center( Index i = 0) – Absolute or relative center of this bin on axis "i"

– virtual int offset( Index i = 0) – Relative or absolute position for the center of the bin

25th May, 1999




Create and fill a histogram

#include "HTL/Histograms.h" // Transient histograms

Histo1D *histo = new Histo1D( "Transient Histo_1D", 20, 0.0, 20.0 );

// Let's fill the histogram with 50000 points

long i;

double x, w;

for( i=0; i<50000; i++ ) {

x = (i % 22) - 1;

w = (x-9.5)*(x-9.5)/100;

histo->fill(x,w);

}

delete histo;

25th May, 1999




Helper Classes

I_Histo, I_Partition and I_Bin interfaces not sufficient– Helper classes introduced do add missing functionality

H_2D_Helper ( make slices, 2D projections ) H_Bin_Helper ( mins, maxs, in_range_error( ), bin_center() ) H_HistoTable1D and 2D ( write( ) - ASCII table output ) H_Printout ( print( ) - line printer output ) H_Statistics ( mean( ), rms( ), entries counts )

– Shortcuts for mean( ) and rms( ) provided Syntax: histo->mean( )

25th May, 1999




Output of a histogram

#include "HTL/Histograms.h" // Transient histograms

#include "HTL/PHistograms.h" // Persistent histograms

Histo1D *histoT = new Histo1D("Transient Histo_1D", 20, 0.0, 20.0 );

HepRef(PHisto2D) histoP =

new PHisto2D("Persistent Histo_2D", 20, 0.0, 20.0, 20, 0.0, 20.0 );

// Line printer representation of a histogram

HPrinter hp( cout ); // Into any output stream

hp.print( *histoT );

// ASCII table with a histogram contents

HistoTable1D ht1( "histo.txt” ); // Only into a text file

ht1.write( *histoP );

delete histoT;

delete histoP;

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What is missing

Fill( ) is not part of any interface– Implemented as non-virtual inline functions

Output the histogram contents as an array (not ASCII)

Open for any input ...

25th May, 1999




Interface to PAW (1)

Provide set of new (similar to old) PAW commands To access HTL histograms the same way as the HBOOK histograms are accessed now

Two new menus created– OODB - interface to the Objectivity/DB

OPEN - Open a data base and a container HTLIN - Put in memory the HTL histogram indexed by ID LIST - List the HTL histograms in the currently opened data base

– T_HTL - to manipulate HTL transient histograms 1DHISTO - Create an HTL histogram PRINT - Print a HTL histogram LIST - List HTL histograms DELETE - Delete HTL histograms identified by ID PLOT - Plot a HTL histogram FRHBOOK - Convert the HBOOK histogram ID into an HTL histogram

25th May, 1999




Interface to PAW (2)

Proof of concept done– Integration of C++ in a FORTRAN application possible– Integration of HTL in well known PAW framework possible

Missing– 1D histograms with non-equidistant binning– Profile histograms– 2D histograms– Interface to KUIP vectors (PUT/CONTENT, GET/CONTENT etc ...)– HTL histograms filling– Fitting– etc.

25th May, 1999




Integration in GAUDI

Neither HTL code, nor HTL libraries compatible with our strategy– Changes done by Dino Ferrero Merlino and me– Library compiled in our environment with new created project file

Integration started last week - not part of this GAUDI release Required changes

– Slight modifications into HistogramSvc– Decisive changes in IHistogram interface

Merging of HTL interfaces into single consistent IHistogram interface

htl - histogram template library

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