Prerequisites
MiDAR requires R version 4.2.0 or higher, available from CRAN. Using an R IDE such as RStudio, Positron, or Visual Studio Code is also recommended.
While MiDAR’s core functionality requires no R coding
skills, basic familiarity with R and an IDE is needed. New to R? Try
online tutorials such a An
opinionated tour of RStudio and the RStudio User
Guide. Additionally, having a colleague who is familiar with RStudio
can be helpful to get started smoothly and stay motivated.
Installing MiDAR
To install, or to update, MiDAR, run the following code
in the R console:
if (!require("pak")) install.packages("pak")
pak::pkg_install("SLINGhub/midar")Learning MiDAR
If you are new to MiDAR, please explore the tutorials available via the top menu bar. These resources will help you become familiar with the package’s concepts and functionalities. In particular, the tutorials on Preparing and importing data and A basic MiDAR workflow offer essential information to get you started smoothly.
Some MiDAR functions, particularly those for plotting, have many
arguments to allow detailed customizations. To get started, use the
default settings (i.e., without defining them), and then adjust them to
suit your needs. Use ?functionname or search the
[References(reference/index.html) page for detailed descriptions, or
check the ‘Manual’ section for tips and tricks. A common error is
omitting required arguments. If unclear errors occur, consult the Help
to ensure correct arguments and data types. Robustness will improve in
future package versions.
MiDAR Recipes
To build your own data processing workflows, the ‘Recipes’ provide a good starting point. Choose one or more recipes that match your application, copy-paste into your R script/notebook, and start from there to adapt to your specific data and process. The recipes also introduce you to some function names and argument options that may typically be used in the recipes’ context.
For more detailed information, refer to the ‘Manual’ section for details on data structures and the use of MiDAR functions, and the ‘Reference’ section for comprehensive documentation on all functions, their arguments, data classes, and test datasets.