DMelt:Start

DataMelt Online Manual
S.Chekanov (editor)

This manual describes DataMelt (DMelt) (former jHepWork, 2005-2013, SCaVis 2013-2015), an environment for numeric computation, statistical analysis and graphical visualization on the Java platform. How to use Java scripting for scientific data analysis, data mining, statistics and numeric computations can be found in these books published by Springer Verlag, 2010, 2016. DataMelt (or, in short, DMelt) is a successor of the popular SCaVis and jHepWork packages that have been under intensive development since 2005. DMelt is fully backward compatible with jHepWork 3.9.

General topics

• 1 Installation
• 2 Running DMelt
• 3 DMelt IDE
• 4 Small Screen Devices
• 5 Using Scripts
• 6 Netbean
• 7 Working with text
• 8 Using Other Languages
• 9 Advanced Usage
• Android
• Help
• Scientific Tools
• Useful Utilities
• WikiForWiki

Programming

• 1 Introduction
• 2 BeanShell
• 3 Jython
• 4 Java
• 5 Groovy
• 6 JRuby
• 7 Matlab and Octave
• 8 Algorithms
• 9 External libraries
• Benchmarks

Mathematics

• 1 Functions
• 2 Parametric Functions
• 3 Non Parametric Functions
• 4 Special Functions
• 5 Polynomials
• 6 Equations
• 7 Graphs

Data Visualization in 2D and 3D

• 1 Canvases
• 2 Plots in 2D
• 3 Custom Plots
• 4 Showing 2D Shapes
• 5 Plots in 3D
• 6 Math Exhibits
• 7 Charts
• 8 Plot Annotations
• 9 Plot Styles by Example
• Diagrams
• Export to Vector Graphics
• Interactive Geometry
• JavaView
• OFF Files
• Real-Time Data
• Spreadsheets
• Technical Drawings
• VisAd

Numeric Calculations

• 1 Linear Algebra
• 2 Random Numbers
• 3 Random Matrices
• 4 Linear Equations
• 5 Integration
• 6 Minimization
• 7 PCA Analysis
• 8 Numeric Python

Data Analysis

• 1 Data Structures
• 2 Data Collections
• 3 Histograms
• 4 Data Mining
• 5 Fitting Data
• 6 Advanced Data Fitting
• 7 Fitting Shapes
• 8 Metadata
• 9 Peak Finders
• Anomaly Detection
• Using Weka

Input and Output

• 1 File Input and Output
• 2 Java and Python IO
• 3 Java Serialization
• 4 CSV File Format
• 5 DIF File Format
• 6 EDN File Format
• 7 YAML File Format
• 8 Cross Paltform IO
• 9 Other file formats
• Advanced IO
• Databases
• Excel Tables
• Performance
• ROOT IO
• Saving Arrays

Statistics

• 1 General Topics
• 2 Distribution Functions
• 3 Statistical Tests
• 4 Statistical Limits
• 5 Statistical classification
• 6 Dimensionality reduction

Symbolic Calculations using Java and Python

• 1 Introduction
• 2 Jasymca
• 3 JScl
• 4 Symja
• 5 SimPy
• Computer Algebra

Symbolic Calculations using JMathlab

• 1 Introduction
• 2 Numbers
• 3 Symbolic Variables
• 4 Commands
• 5 Calculus
• 6 Functions
• 7 Programming
• 8 Symbolic Transformations
• 9 Vectors and Matrices
• Equations
• Plotting
• Polynomials

Measurements and Units

• 1 Unit conversions
• 2 Measurements with Units
• 3 Error Propagation
• 4 Calculations with Units

Artificial Intelligence and Machine Learning

• 1 Backpropagation Neural Net
• 2 Bayesian Neural Net
• 3 Kohonen Maps
• 4 Recurrent NN and LSTM
• 5 Convolutional NN
• 6 Classification problem
• Cellular Automaton
• Data Clustering
• Decision Tree
• Machine Learning algorithms
• Symbolic Regression

Digital Signal Processing

• 1 Fast Fourier Transforms
• 2 Discrete Fourier Transform
• 4 Wavelets
• 5 Fast Wavelet Transform
• 6 Kalman Filter

Image Processing

• 1 Image Manipulation
• 2 Image Manipulation with ImageJ
• 3 Image Identificantion
• 4 Image Analysis

Text Processing

• 1 Working with text in IDE
• 2 Searching in text using Lucene

Programming in Physics

• HEP

Finance and market analysis

• Financial Charts
• Financial Computations
• Market Prediction
• Time Series
• Trade Derivatives

External guides

• BeanShell
• Medusa
• VisAd

For Developers

• Contributions
• Current Tasks
• Getting Source Code
• How to contribute
• License Information
• Sponsorship
• Usage And Popularity

Reading this manual

If you see the yellow warning message shown above, and red box on top-right, than this indicates that you have a limited access to this manual. Such yellow boxes protect text and code examples from guests. The current access privileges are sufficient to view about 30% of this online manual, which is usually sufficient to get started with DataMelt. You cannot access URL to most of code snippets and references to documentation API for Java third-party classes is disabled.

If you are new to DataMelt, use the member area to become DMelt member. If you are already DMelt member and have made one-time contribution to this project, simply login to the member area and come back to this manual.

How to run the code snippets

In case of short code snippets, use the interactive JythonShell of the DataMelt IDE.

In case if a code snippet is too long, you may wish to execute it directly inside the DataMelt IDE. Start the IDE and open the URL dialog as [File]-[Open from URL]. You will see a window where you can insert the URL link to a Jython code example. One can obtain URL location of code snippets given in this manual as: navigate the mouse under the "Download snipped" link (located above the shown code) and select "Copy link location". Then paste the URL link to the DataMelt URL window and press "run".

Additional resources

You are free to look at additional resources to help get started with DMelt:

• Interactive Python/Jython and Matlab/Octave tutorials (Java powered)
• Movies with DataMelt tutorials
• FAQ (Frequently Asked Questions) on numerical recipes using using Jython, Java and DataMelt
• DataMelt Java API (limited access for non-members)
• DataMelt Topic API (limited access for non-members)
• DataMelt online examples

License of the Manual

Copyright © 2005-2019 jWork.ORG, S.Chekanov and contributors. All rights reserved.

This online documentation are provided under a license agreement containing restrictions on use and disclosure and are protected by intellectual property laws. Except as expressly permitted in your license agreement or allowed by law, you may not use, copy, reproduce, translate, broadcast, modify, license, transmit, distribute, exhibit, perform, publish, or display any part, in any form, or by any means.

The information contained herein is subject to change without notice and is not warranted to be error-free. If you find any errors, please report them to us in writing. This documentation is NOT distributed under a GPL license. Use of this documentation is subject to the following terms:

• You may create a printed copy of this documentation solely for your own personal use.
• Conversion to other formats is allowed as long as the actual content is not altered or edited in any way.
• You shall not publish or distribute this documentation in any form or on any media.
• Any other use, such as any dissemination of printed copies or use of this documentation, in whole or in part, in another publication, requires the prior written consent from an authorized representative of the DataMelt team and/or its affiliates reserve any and all rights to this documentation not expressly granted above.