Scientific Data Analysis using Jython Scripting and Java (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. Front Matter....Pages I-XXIV Introduction....Pages 1-2 Jython, Java and jHepWork....Pages 3-26 Introduction to Jython....Pages 27-84 Mathematical Functions....Pages 85-120 One-dimensional Data....Pages 121-134 Two-dimensional Data....Pages 135-159 Multi-dimensional Data....Pages 161-169 Arrays, Matrices and Linear Algebra....Pages 171-192 Histograms....Pages 193-221 Random Numbers and Statistical Samples....Pages 223-233 Graphical Canvases....Pages 235-271 Input and Output....Pages 273-312 Miscellaneous Analysis Issues Using jHepWork....Pages 313-334 Data Clustering....Pages 335-342 Linear Regression and Curve Fitting....Pages 343-365 Neural Networks....Pages 367-382 Steps in Data Analysis....Pages 383-405 Real-life Examples....Pages 407-433 Back Matter....Pages 435-440