Comparison with other free data-analysis packages
Main differences with JAS (unsupported)
- full-featured IDE (JAS has a primitive text editor, which does not have even syntax highlighting)
- Powerful plotting package for data visualization. Using JAS, it is impossible (or very difficult) to produce plots of good quality (i.e. good enough to include into scientific papers). jHepWork includes the jHPlot program to display graphics in 2D and 3D. Look at the snapshots. With jHepWork you can even use Greek symbols and subscripts for labels!
- Programs written using the jHepWork classes are short due to several enhancements. For example, to read a file and plot points with statistical and systematical errors, one needs only 2 statements. The syntax is very similar to ROOT (using python), see snapshots. At the same time, one can still use the JAIDA classes.
- All objects (data containers, histograms, arrays) can be serialized in external files (including XML).
Main differences with ROOT
- jHepWork is a multi-platform framework.
- Native Java serialization for all data containers and histograms (including XML)
- does not require compilation and installation.
- better suited for distributed analysis environment via the Internet (applets, Java web starts). Can leverage the power of the server.
- scripts can be compiled to jar libraries without any modification (unlike ROOT or PAW). In ROOT, in order to compile a script, you should write a proper C++ code which is usually by a factor 3 longer than the equivalent Jython scripts.
- has a build-in help for accessible methods using JAVA reflection technology
- Powerful multithread support
- Any java IDEs (Netbean, Eclipse) can be used for development.
- Auto-update