Anaphe - OO Libraries and Tools for Data Analysis

The Anaphe project is an ongoing effort to provide an Object Oriented software environment for data analysis in HENP experiments. A range of commercial and public domain libraries is used to cover basic functionalities; on top of these libraries a set of HENP-specific C++ class libraries for histogram management, fitting, plotting and ntuple-like data analysis has been developed. In order to comply with the user requirements for a command-line driven tool, we have chosen to use a scripting language (Python) as the front-end for a data analysis tool. The loose coupling provided by the consequent use of (AIDA compliant) Abstract Interfaces for each component in combination with the use of shared libraries for their implementation provides an easy integration of existing libraries into modern scripting languages thus allowing for rapid application development. This integration is simplified even further using a specialised toolkit (SWIG) to create "shadow classes" for the Python language, which map the definitions of the Abstract Interfaces almost at a one-to-one level. This paper will give an overview of the architecture and design choices and will present the current status and future developments of the project

Architecture of collaborating frameworks: simulation, visualisation, user interface and analysis

The Anaphe project is an ongoing effort to provide an Object Oriented software environment for data analysis in HENP experiments. A range of commercial and public domain libraries is used to cover basic functionalities; on top of these libraries a set of HENP-specific C++ class libraries for histogram management, fitting, plotting and ntuple-like data analysis has been developed. In order to comply with the user requirements for a command-line driven tool, we have chosen to use a scripting language (Python) as the front-end for a data analysis tool. The loose coupling provided by the consequent use of (AIDA compliant) Abstract Interfaces for each component in combination with the use of shared libraries for their implementation provides an easy integration of existing libraries into modern scripting languages thus allowing for rapid application development. This integration is simplified even further using a specialised toolkit (SWIG) to create "shadow classes" for the Python language, which map the definitions of the Abstract Interfaces almost at a one-to-one level. This paper will give an overview of the architecture and design choices and will present the current status and future developments of the project

A Persistent Object Manager for HEP

% RD45 \\ \\ RD45 is currently investigating solutions to the problem of storing, managing and accessing the extremely large volumes of data that will be created at the LHC where, given the anticipated lifetime and data rates, a system capable of scaling to approximately 100~PB is required. The project places strong emphasis on the use of industry standard solutions wherever possible, and is currently focussing on the potential use of commercial standards-conforming Object Database Management Systems transparently coupled to Mass Storage Systems. Production use of components of what could eventually become the solution for LHC has already been made by existing experiments at CERN, and it is planned to gradually increase the amount of physics data handled by the system into the multi-TB range and beyond over the next years