Tag Archives: CLI

Add geometry values to vector layer in GRASS GIS

In my previous post I explained how to add geometry values to the attribute table of a vector map in QGIS. You can do the same in GRASS GIS. It is slightly more complicated (don’t worry, it is still easy enough), but also more powerful. Below I will briefly explain how to use this tool using the GUI or command line. Continue reading

Creating a map using the command line

Although I like to carry out GIS analyses using the command line interface (CLI), creating maps is something I still tend to do using the graphical interface (GUI). And most of the time that makes perfect sense to me, creating something visual (the map), using visual tools (GRASS GUI gis.m or QGIS).

But things change when e.g., you have to create many maps of the same area changing one variable only, Continue reading

Which text editor to use with R?

Although some users would prefer a graphical user interface for R, the arguably best way to work with R is through the command line. This can be done directly in the R console, but often it is more convenient to write scripts in a separate file, instead of typing them directly in the console. This requires a text editor, and you can of course use the default one that comes with your OS. However, there are text editors that offer different levels of integration with R. Below are the ones I tried. Continue reading

Why a GUI for R isn’t always a bad idea

The arguably best way to work with R is through the command line. Some even argue that the use of a graphical user interface (GUI) should be completely discouraged. And that is where I disagree. The command line can be quit intimidating for the new or occasional users, who may therefore benefit from a GUI. There are a number of different GUI available, for example R commander, JGR, Deducer (which includes a very nice plot builder), RKward, Rattle (geared towards data mining) and BiodiversityR (focuses on biodiversity analysis). None of them offer the same sophisticated graphical interface as e.g., S plus or SPSS, but they are in general easy to use and quit suitable for the more common type of analyzes. What they have in common is that while providing you with an graphical interface, they also show you the commands generated via the point and click dialogs. This helps in getting to know the R syntax and thus simplifies the learning curve of R. Continue reading