Abstract
The analysis category was introduced in Geant4 release 9.5 to help users capture statistical data in the form of histograms and ntuples and store these in files in various formats. Up to release 10.3 the following formats had been introduced: csv, AIDA/XML and the binary ROOT file format. We present here the work done to handle, in Geant4 10.4, the binary HDF5 file format, a format/library widely used in other domains of science but quite ignored in HEP for the moment. Work has been done also to support the management of a single file in a multi-thread or MPI parallel environment for the ROOT format; we present the introduction of a row-wise way to manage paginated ntuples in order to restore an “event view” lost by our today column-wise implementation for this format.
Highlights
We remind the reader that the Geant4 [1] analysis category is organized in two layers; first the g4tools "basic layer” that provides histograms, profiles, ntuples along with the mechanisms to store these in file in various formats by bringing only what is needed to do that; and second the Geant4 analysis “upper layer” to help users manage collections of these, putting the accent on a uniform, user-friendly interface integrated in the Geant4 user API, by offering, for example, interactive commands, units andactivation of selected objects
As Geant4 is related to domains of science other than HEP, where the HDF5 [8] library is used, it seemed interesting to us to add this file format to the ones already handled
The ROOT file format has the TTree/TBranch/TLeaf which implement this kind of paginated table and the g4tools ntuple writter for the ROOT file format arranges to map this structure in files
Summary
We remind the reader that the Geant4 [1] analysis category is organized in two layers; first the g4tools "basic layer” (agnostic of Geant core) that provides histograms, profiles, ntuples (and plots since Geant4 10.3) along with the mechanisms to store these in file in various formats by bringing only what is needed to do that; and second the Geant analysis “upper layer” to help users manage collections of these, putting the accent on a uniform, user-friendly interface integrated in the Geant user API, by offering, for example, interactive commands, units and (in)activation of selected objects. About HDF5 itself and for a breakdown of users, we refer to [8] but quote the short presentation in the support section: HDF5 is a data model, library, and binary file format for storing and managing data. It supports an unlimited variety of datatypes, and is designed for flexible and efficient I/O and for high volume and complex data. The HDF5 Technology suite includes tools and applications for managing, manipulating, viewing, and analysing data in the HDF5 format
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