Scientific Data Analysis Using Jython Scripting and Java

2010. Auflage 2010
ISBN: 978-1-84996-286-5
Verlag: Springer

Buch, Englisch, 440 Seiten, Format (B × H): 163 mm x 240 mm, Gewicht: 1820 g

Reihe: Advanced Information and Knowledge Processing

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.

Zielgruppe

Graduate

Autoren/Hrsg.

Chekanov, Sergei V

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Automatische Datenerfassung, Datenanalyse
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Programmier- und Skriptsprachen
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining

Inhaltsverzeichnis

Jython, Java and jHepWork.- to Jython.- Mathematical Functions.- One-dimensional Data.- Two-dimensional Data.- Multi-dimensional Data.- Arrays, Matrices and Linear Algebra.- Histograms.- Random Numbers and Statistical Samples.- Graphical Canvases.- Input and Output.- Miscellaneous Analysis Issues Using jHepWork.- Data Clustering.- Linear Regression and Curve Fitting.- Neural Networks.- Steps in Data Analysis.- Real-life Examples.

Über Autor(innen)

S.V.Chekanov was born in Minsk (USSR) and received his Ph.D. in experimental physics (University of Nijmegen, The Netherlands). He has more than twenty years of experience in high-energy fields including advanced programming and analysis of large data volumes collected by high-energy experiments operated by major international collaborations. He has written over a hundred physics articles, many of them are based on analysis of experimental data from large-scale international experiments, 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 physics analysis, developing analysis tools and providing software support for the Midwest data analysis center (USA) of the LHC experiment. In 2005 he began the creation of the jHepWork data analysis framework which is now the world's leading open-source Java software for scientists. Presently, he works at the Argonne National Laboratory (Chicago, USA).