Scientific Data Analysis using Jython Scripting and Java - Chekanov, Sergei V.
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Scientific Data Analysis using Jython Scripting and Java presents practical approaches for data analysis using Java scripting based on Jython, a Java implementation of the Python language. The chapters essentially cover all aspects of data analysis, from arrays and histograms to clustering analysis, curve fitting, metadata and neural networks. A comprehensive coverage of data visualisation tools implemented in Java is also included.
Written by the primary developer of the jHepWork data-analysis framework, the book provides a reliable and complete reference source laying the foundation for…mehr

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Produktbeschreibung
Scientific Data Analysis using Jython Scripting and Java presents practical approaches for data analysis using Java scripting based on Jython, a Java implementation of the Python language. The chapters essentially cover all aspects of data analysis, from arrays and histograms to clustering analysis, curve fitting, metadata and neural networks. A comprehensive coverage of data visualisation tools implemented in Java is also included.

Written by the primary developer of the jHepWork data-analysis framework, the book provides a reliable and complete reference source laying the foundation for data-analysis applications using Java scripting. More than 250 code snippets (of around 10-20 lines each) written in Jython and Java, plus several real-life examples help the reader develop a genuine feeling for data analysis techniques and their programming implementation.

This is the first data-analysis and data-mining book which is completely based on the Jython language, and opens doors to scripting using a fully multi-platform and multi-threaded approach. Graduate students and researchers will benefit from the information presented in this book.
Autorenporträt
S. Chekanov was born in Minsk (Belarus) and received his Ph.D. in experimental physics at Radboud University Nijmegen, The Netherlands. He has more than twenty five years of experience in high-energy particle physics including advanced programming and analysis of large data volumes collected by high-energy experiments operated by major international collaborations. He has written a book and over a hundred professional articles, many of them based on analysis of experimental data from large-scale international experiments, such as LEP (CERN, European Organization for Nuclear Research), HERA (DESY, German Electron Synchrotron) and LHC, the Large Hadron Collider experiment at CERN. Over the past decade he has divided his time between data analysis, developing analysis tools and providing software support for the Midwest data-analysis centre (USA) of the LHC experiment. He is founder of the jWork.ORG community portal for promoting scientific computing for science and education.In 2005 he created a data-analysis software environment, which is presently known as DMelt. Currently, this software is the world's leading open-source program for data analysis, statistics and scientific visualization, incorporating Java packages from more than 100 developers around the world and with thousands of users. Presently, he works at the Argonne National Laboratory (Chicago, USA).