Scientific data analysis using Jython Scripting and Java

Scientific data analysis using Jython Scripting and Java

Chekanov, Sergei V.

83,15 €(IVA inc.)

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. The only book which describes Java scripting for science and engineering. Lays the foundation for data analysis using Java and Python using a truly multi-threaded and multiplatform approach. Contains examples, about 250 in total, all are very short (10-20 lines of the code). Contains real-life examples derived from the author's experience as a data analyser for the last 20 years of work in physics. INDICE: Introduction.- 1 Jython, Java and jHepWork.- 2 Introduction to Jython.- 3 Mathematical Functions.- 4 One-dimensional Data.- 5 Two-dimensional Data.- 6 Multi-dimensional Data.- 7 Arrays, Matrices and Linear Algebra.- 8 Histograms.- 9 Random Numbers and Statistical Samples.- 10 Graphical Canvases.- 11Input and Output.- 12 Miscellaneous Analysis Issues Using jHepWork.- 13 Data Clustering.- 14 Linear Regression and Curve Fitting.- 15 Neural Networks.- 16 Steps in Data Analysis.- 17 Real-life Examples.- Index of Examples.- Index

  • ISBN: 978-1-84996-286-5
  • Editorial: Springer
  • Encuadernacion: Cartoné
  • Páginas: 497
  • Fecha Publicación: 29/07/2010
  • Nº Volúmenes: 1
  • Idioma: Inglés