MATLAB, Python and R are commonly used in bioacoustics. Whilst all three languages are excellent choices, it is difficult to ask entrants into bioacoustics to learn all three. I have tried to put together a table with a summary of what each language is good/bad at - any thoughts on the scores/ additional rows to add?
| MATLAB | Python | R | |
|---|---|---|---|
| How easy/intuitive is it to get started | Excellent (totally integrated code and IDE) | Good (Spyder IDE is great) | Good (R Studio) |
| Open source | No | Yes | Yes |
| Price | Very expensive (but often paid for in academia) | Free | Free |
| Documentation | Excellent (consistently comprehensive help files) | Good (help depends on package) | Good (help depends on package) |
| Speed | Slow | Slow | Slow |
| Audio functions e.g. opening files etc. | Excellent (includes X3 libraries) | Excellent | Excellent |
| Signal processing functions | Excellent (includes GUI toolbox) | Excellent (scipy.signal) | Good |
| Deep learning tools | Good | Excellent (the default language for Deep Learning) | Medium? |
| Statistics | Medium (patchy at best) | Medium? | Excellent (designed for stats) |
| Package Management | Less choice but easy and integrated | Lots of packages - can be confusing | Easy in R studio but lots of competing packages |
| Building UIs (graphical programs) | Easy and integrated | More complex (and perhaps powerful) with lots of different packages e.g. Tkinter, wxPython, and PyQt. | Easy with R shiny |
| Use with PAMGuard | Well developed library to read PAMGuard output | Library planned for 2023 | Well developed library to read PAMGuard output |
