RANGA

RANGA

RANGA is an open-source software used for numerical simulation and data analysis. It provides a programming language and development environment for numerical computations and data visualization.
RANGA image
opensource numerical-simulation data-visualization programming-language

Ranga: Open-Source Numerical Simulation Software

Ranga is an open-source software used for numerical simulation and data analysis. It provides a programming language and development environment for numerical computations and data visualization.

What is RANGA?

RANGA is an open-source software application developed by SciComp Inc. for numerical simulation, data analysis, and visualization. It features an intuitive programming language and integrated development environment (IDE) designed specifically for numerical computing.

Some key features and capabilities of RANGA include:

  • Array-oriented language optimized for vector/matrix operations
  • Extensive math and statistics libraries for linear algebra, differential equations, Monte Carlo simulations, etc.
  • 2D and 3D plotting for data visualization
  • Built-in parallel computing for accelerated simulations
  • Scripting interface for automation and batch processing
  • Interoperability with Python, C/C++, Fortran, and other languages
  • Cross-platform support for Windows, Mac, and Linux

RANGA makes it easy for scientists, engineers, analysts, and other domain experts to rapidly develop numerical models, perform simulations, analyze data, and generate insight without having to master a lower-level programming language like C++ or Fortran. Its specialized language constructs and libraries provide high productivity.

The software is offered both as a free community edition for personal/academic use as well as paid professional editions that add technical support, additional toolkits, and other capabilities suited for commercial use.

RANGA Features

Features

  1. Programming language and environment for data analysis
  2. Numerical computation and simulation
  3. Data visualization
  4. Statistical analysis
  5. Machine learning

Pricing

  • Open Source

Pros

Open source and free

Large community support

Extensive libraries and packages

Flexible and customizable

Runs on multiple platforms

Cons

Steep learning curve

Less user friendly than GUI programs

Not as fast as compiled languages

Version inconsistencies


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