A highly-customizable environment for working with tabular data. Easy to learn, fast to use.
|18 Jan 2011||matt dash||
Rave is an open source MATLAB toolbox that provides point-and-click access to a wide variety of visualization, data analysis, optimization, and modeling capabilities. Rave was created by Professor Brian German's research group at Georgia Tech's School of Aerospace Engineering to support engineering design decision making research, but its capabilities are general enough to be used in many other fields.
Rave is built to be easy to learn, easy to use, and easy for users to extend with new visualization, optimization, and other capabilities. Using Rave's existing capabilities requires no coding or prior experience with MATLAB, while new capabilities can be added by using a template-based interface that gives coders the maximum amount of flexibility in creating new functions.
Rave can be used with any "flat file" data set, or it can link directly to data-generating MATLAB functions to enable interactive visualization and data mining, design steering, and user-in-the-loop optimization.
Rave is built on an easy-to-learn m-code interface that also lets you write your own visualization, exploration, optimization, and surrogate modeling functions and plug them in to Rave without modifying any of Rave's source code. This enables researchers working in these areas to leverage Rave's existing capabilities while developing code that can easily be shared with a broad user community.