Book preview
"The art of scientific computation: Introduction to data analysis using Jython scripting and Java"
by S.V.Chekanov
This is a book preview (PDF)
517 pages. The book will be published by
Springer-Verlag Gmbh.
This book material is protected under international treaties and copyright laws.
The PDF file is provided to preview
the original book, not for redistribution.
All code snippets in this preview version have been removed and
available only in the original book.
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About this book:This book presents practical approaches for data analysis using Java scripting based Jython - the 100% pure Java implementation of the Python language. Each chapter describes the conceptual and methodological aspects of modern data-analysis tools and their implementations in Java/Jython, covering essentially all aspects of data analysis from simple multidimensional arrays and histograms to clustering analysis, curve fitting, metadata and neural networks. This book includes a comprehensive coverage of various numerical and graphical packages implemented in Java and included to the jHepWork project.
The book was written by the primary developer of the software, and presents a reliable and complete source of reference which lays the foundation for data-analysis applications using Java scripting. The book includes more than 200 code snippets (usually 10-20 lines each) written in Jython and Java and several real-life data-analysis examples which 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, thus it opens doors to scripting using fully multi-platform and multi-threaded approach. |
Downloading book examples and exercises
The book contains about 260 Python, Jython and Java code snippets. If you have the original printed book, you can download the code examples organized by chapters from this download page.
Chapters
- Introduction
- Jython, Java and jHepWork
- Introduction 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
- Index of examples
- Index
This book is protected under international treaties and copyright laws of the United States of America and International copyright laws. No part of this book may be reproduced, without the express written consent of S.V.Chekanov. Permission is granted to the purchaser of this product to reproduce sections of this book for personal use only. Sale or trade of such reproductions is strictly prohibited.