Interactive Data Language, IDL: Does anybody care?
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Published on 2008-11-04T04:09:09Z
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Anyone use a language called Interactive Data Language, IDL? It is popular with scientists. I think it is a poor language because it is proprietary (every terminal running it has to have an expensive license purchased) and it has minimal support (try searching for IDL, the language, right now on stack) . I am trying to convince my colleagues to stop using it and learn C/C++/Python/Fortran/Java/Ruby. Does anybody know about or even care about IDL enough to have opinions on it? What do you think of it? Should I tell my colleagues to stop wasting their time on it now? How can I convince them?
Edit: People are getting the impression that I don't know or use IDL. Also, I said IDL has minimal support which is true in one sense, so I must clarify that the scientific libraries are indeed large. I use IDL all the time, but this is exactly the problem: I am only using IDL because colleagues use it. There is a file format IDL uses, the .sav, which can only be opened in IDL. So I must use IDL to work with this data and transfer the data back to colleagues, but I know I would be more efficient in another language. This is like someone sending you a microsoft word file in an email attachment and if you don't understand how wrong that is then you probably write too many words not enough code and you bought microsoft word.
Edit: As an alternative to IDL Python is popular. Here is a list of The Pros of IDL (and the cons) from AstroBetter:
Pros of IDL
- Mature many numerical and astronomical libraries available
- Wide astronomical user base
- Numerical aspect well integrated with language itself
- Many local users with deep experience
- Faster for small arrays
- Easier installation
- Good, unified documentation
- Standard GUI run/debug tool (IDLDE)
- Single widget system (no angst about which to choose or learn)
- SAVE/RESTORE capability
- Use of keyword arguments as flags more convenient
Cons of IDL
- Narrow applicability, not well suited to general programming
- Slower for large arrays
- Array functionality less powerful
- Table support poor
- Limited ability to extend using C or Fortran, such extensions hard to distribute and support
- Expensive, sometimes problem collaborating with others that don’t have or can’t afford licenses.
- Closed source (only RSI can fix bugs)
- Very awkward to integrate with IRAF tasks
- Memory management more awkward
- Single widget system (useless if working within another framework)
- Plotting:
- Awkward support for symbols and math text
- Many font systems, portability issues (v5.1 alleviates somewhat)
- not as flexible or as extensible
- plot windows not intrinsically interactive (e.g., pan & zoom)
Pros of Python
- Very general and powerful programming language, yet easy to learn. Strong, but optional, Object Oriented programming support
- Very large user and developer community, very extensive and broad library base
- Very extensible with C, C++, or Fortran, portable distribution mechanisms available
- Free; non-restrictive license; Open Source
- Becoming the standard scripting language for astronomy
- Easy to use with IRAF tasks
- Basis of STScI application efforts
- More general array capabilities
- Faster for large arrays, better support for memory mapping
- Many books and on-line documentation resources available (for the language and its libraries)
- Better support for table structures
- Plotting
- framework (matplotlib) more extensible and general
- Better font support and portability (only one way to do it too)
- Usable within many windowing frameworks (GTK, Tk, WX, Qt…)
- Standard plotting functionality independent of framework used
- plots are embeddable within other GUIs
- more powerful image handling (multiple simultaneous LUTS, optional resampling/rescaling, alpha blending, etc)
- Support for many widget systems
- Strong local influence over capabilities being developed for Python
Cons of Python
- More items to install separately
- Not as well accepted in astronomical community (but support clearly growing)
- Scientific libraries not as mature:
- Documentation not as complete, not as unified
- Not as deep in astronomical libraries and utilities
- Not all IDL numerical library functions have corresponding functionality in Python
- Some numeric constructs not quite as consistent with language (or slightly less convenient than IDL)
- Array indexing convention “backwards”
- Small array performance slower
- No standard GUI run/debug tool
- Support for many widget systems (angst regarding which to choose)
- Current lack of function equivalent to SAVE/RESTORE in IDL
- matplotlib does not yet have equivalents for all IDL 2-D plotting capability (e.g., surface plots)
- Use of keyword arguments used as flags less convenient
- Plotting:
- comparatively immature, still much development going on
- missing some plot type (e.g., surface)
- 3-d capability requires VTK (though matplotlib has some basic 3-d capability)
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