encountered an issue with laGP and BLAS and added a small section to the install instructions

Author: nevrome

docs/install.md

@@ -11,7 +11,7 @@ remotes::install_github('nevrome/mobest')
 
 You can also install specific/older versions of mobest with the following syntax: `nevrome/mobest[@ref|#pull|@*release]`. For example to install the publication release version you can run `remotes::install_github('nevrome/[email protected]')`.
 
-For any of this to work a number of **system libraries** (mostly for processing geospatial data) have to be installed on your system, primarily for one particular dependency of mobest: the **`sf` R package**. The following table includes the libraries and the names of the relevant packages in the package management systems of various Linux distributions and MacOS.
+For this to work a number of **system libraries** (mostly for processing geospatial data) have to be installed on your system, primarily for one particular dependency of mobest: the [**`sf` R package**](https://r-spatial.github.io/sf). The following table includes the libraries and the names of the relevant packages in the package management systems of various Linux distributions and MacOS.
 
 | System library                                                        | deb package<br>(Ubuntu/Debian) | rpm package<br>(Fedora/CentOS) | pkgbuild package<br>(Arch) | brew package<br>(MacOS) |
 |-----------------------------------------------------------------------|----------------------------------|---------------------------------|-------------------------|----------------------|
@@ -22,6 +22,15 @@ For any of this to work a number of **system libraries** (mostly for processing
 
 The `sf` package maintainers provide a good explanation how to install these: <https://r-spatial.github.io/sf/#installing>
 
+Finally, mobest uses the [**`laGP` R package**](https://doi.org/10.32614/CRAN.package.laGP) for its core interpolation mechanism. `laGP` gets automatically installed together with mobest (with the code above). It uses the [BLAS](https://www.netlib.org/blas/) system library for fast matrix computations. If `mobest::locate()` runs only single-threaded, so not multi-threaded, and consequently very slowly, then your BLAS installation may be borked. You can use the following simple test to confirm the issue in R:
+
+```r
+A <- matrix(rnorm(6000^2), 6000, 6000)
+system.time(A %*% A)
+```
+
+If this does not run in parallel, then you should probably switch to another BLAS implementation. Run `extSoftVersion()` to see which BLAS library you're currently using in R.
+
 ## Create an apptainer image to run mobest
 
 If installing system libraries is not possible (for example because you don't have root access) or desirable, then mobest can also be run through a virtualization layer. One option is the high performance computing container system [**apptainer**](https://apptainer.org) (formerly ["singularity"](https://apptainer.org/news/community-announcement-20211130)). To do this you can follow these steps: