This document gives a brief introduction into the source code the the Databionic ESOM Tools for interested developers. More information can be found in the Javadoc and the source itself. If you have any questions or ideas for new features please contact us on the mailing lists.
| databionics.esom | |
| databionics.esom.cooling | Definition of cooling strategies. Add you own versions by implementing the interface Cooling. |
| databionics.esom.grid | ESOM grid. A grid holds the prototype vector and defines the map space topology by the function findNeighbors. We implemented 1D and 2D grids with various topologies. Possible extensions of this package include hexagonal grids, spherical grids, and 3D grids. Feel free to ask for assistance if you are interested in implementing these grids. |
| databionics.esom.gui | The basic GUI components of the ESOM analyzer |
| databionics.esom.neighborhood | Definition of neighborhood kernels. Add you own versions by implementing the interface Neighborhood. |
| databionics.esom.renderer | Global classes for visualization. The Renderer glues all visualization components together and creates the actual image. |
| databionics.esom.renderer.background | Background visualization methods that all inherit from BackgroundRenderer. Most backgrounds create a matrix of height values based on the collection of prototype vectors in a grid. Feel free to ask for assistance if you are interested in implementing new background. |
| databionics.esom.renderer.foreground | Foreground visualization methods that all inherit from ForegroundRenderer. Most foregrounds simply decide on a color for the bestmatches. Feel free to ask for assistance if you are interested in implementing new background. |
| databionics.esom.tool.* | |
| databionics.esom.train | Implementation of training algorithms. All algorithms should inherit from SOM. The SOM class contains the basic algorithm broken down in elementary steps and methods for bestmatch search and neuron update. OnlineSOM and BatchSOM implement these steps in the corresponding order. Possible extensions of this package include algorithms for temporal SOM training or fast approximate training methods. Feel free to ask for assistance if you are interested in implementing new training methods. |
| databionics.esom.util | Some utility classes mainly for the GUI. |
| databionics | Base classes for all applications handling command line parsing and configuration file loading. |
| databionics.cli | Extension of commons-cli with loading default values from config file. |
| databionics.gui | Useful GUI classes like a panel displaying log4j messages and a dialog for running programs based on an XML description of the parameters. |
| databionics.io | Loading and saving of all file formats. Classes also act as data containers within the code. |
| databionics.math | Pairwise distance calculation and Pareto Density Estimation. |
| databionics.modules | Description of program parameters loadable from XML files. Running these programs as a job and watching the result. |
| databionics.project | Managing a collection of file types. |
| databionics.runner | Helper class to run external tools (non-Java). |
| databionics.text | Some simple string routines including n-gram similarity. |
| databionics.util | Some utilities including searching for classes in a jar and reading an environment variable. |