DataMelt is a scientific computing and data analysis environment aimed at researchers, engineers and students. Previously known as jHepWork and SCaVis, it combines numerical libraries, scripting facilities and visualisation tools within a single application.
The software is designed for exploratory scientific analysis, where researchers need to manipulate datasets, perform calculations and examine results through graphs and statistical summaries. It provides an interface for integrating mathematical and scientific libraries without requiring users to build a complete analysis environment from separate components.
DataMelt is particularly suited to work involving numerical methods, statistical modelling, histograms and visualisation. Its scripting approach allows calculations to be repeated and adapted for different datasets, while graphical tools help users inspect the results.
The project has an extensive collection of functionality, although its published stable release history is relatively old. Users considering it for new scientific work should verify compatibility with their current software environment.
This is free and open source software.
Key Features
- Two-dimensional and three-dimensional plotting of scientific data and mathematical functions.
- Interactive charts with configurable labels, annotations and axes.
- Histogram creation, statistical distributions and profile histograms.
- Numerical analysis using integrated mathematical and statistical libraries.
- Linear regression, curve fitting and parameter estimation.
- Matrix algebra and mathematical function evaluation.
- Random number generation and statistical sampling.
- Clustering methods including k-means, fuzzy clustering and hierarchical clustering.
- Support for selected neural network and other data analysis methods.
- Interactive scripting environment for constructing repeatable analyses.
- Integrated editor with syntax highlighting and code-completion facilities.
- Interactive shells for executing scripts and inspecting results.
- Integration with FreeHEP and other scientific libraries.
- Data input and output facilities for supported numerical and scientific formats.
- Export of visualisations to vector and raster graphics formats.
- Cross-platform support – runs on Linux, macOS, and Windows.
Website: datamelt.org
Support:
Developer: S. Chekanov
License: GNU General Public License v2.0
DataMelt is written in Java. Learn Java with our recommended free books and free tutorials.
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I very recommend DataMelt for scientific data analysis and visualization. It supports Groovy, the fastest dynamically-typed language. It also has a massive number of example to get started