Scientific Data Analysis using Jython Scripting and Java

  • Sergei V.┬áChekanov

Part of the Advanced Information and Knowledge Processing book series (AI&KP)

Table of contents

  1. Front Matter
    Pages I-XXIV
  2. Sergei V. Chekanov
    Pages 1-2
  3. Sergei V. Chekanov
    Pages 3-26
  4. Sergei V. Chekanov
    Pages 27-84
  5. Sergei V. Chekanov
    Pages 85-120
  6. Sergei V. Chekanov
    Pages 121-134
  7. Sergei V. Chekanov
    Pages 135-159
  8. Sergei V. Chekanov
    Pages 161-169
  9. Sergei V. Chekanov
    Pages 171-192
  10. Sergei V. Chekanov
    Pages 193-221
  11. Sergei V. Chekanov
    Pages 223-233
  12. Sergei V. Chekanov
    Pages 235-271
  13. Sergei V. Chekanov
    Pages 273-312
  14. Sergei V. Chekanov
    Pages 313-334
  15. Sergei V. Chekanov
    Pages 335-342
  16. Sergei V. Chekanov
    Pages 343-365
  17. Sergei V. Chekanov
    Pages 367-382
  18. Sergei V. Chekanov
    Pages 383-405
  19. Sergei V. Chekanov
    Pages 407-433
  20. Back Matter
    Pages 435-440

About this book

Introduction

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.

Keywords

Cluster Clustering Data Analysis Data Mining Java Jython Python

Authors and affiliations

  • Sergei V.┬áChekanov
    • 1
  1. 1.HEP Division, ANLArgonne National LaboratoryArgonneUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-84996-287-2
  • Copyright Information Springer-Verlag London Limited 2010
  • Publisher Name Springer, London
  • eBook Packages Computer Science
  • Print ISBN 978-1-84996-286-5
  • Online ISBN 978-1-84996-287-2
  • Series Print ISSN 1610-3947
  • About this book