The goal of angstroms was to provide easy access to Regional Ocean Modeling System (ROMS) but now it provides easy access and control over any complex gridded output available to the raster package in R.
The key features are:
This approach aligns with the plotting and interpretation tools in the quadmesh package, particularly the mesh_plot() and quadmesh() functions.
angstroms first reached CRAN in 2017. The five ideas above have since been taken up, more generally, by other packages and writing:
So angstroms is not being rewritten in place. It is the ROMS front end: it keeps what is specific to ROMS, and over time hands the general jobs to packages that each do one thing.
What stays in angstroms:
romscoords());romshcoords());romsangle(), romsrotate());create_transport()).What moves out, one small release at a time:
| Job | Now | Later |
|---|---|---|
| read slices | raster and ncdf4 | tidync or vapour |
| index arithmetic | raster extents in index space | vaster |
| coordinate transformation | reproj | reproj (already) |
| geometry into grid space | nearest grid node (romsmap()) |
controlledburn, with edges cut into short pieces before mapping |
| grid as mesh, plotting | quadmesh | quadmesh |
romsmap() moves only the vertices of a geometry, each to its nearest grid node. That is fine for a quick look, as its help page says, but a long edge on a curvilinear grid can then cross cells it never touches. Cutting edges into short pieces first, and mapping to fractional column and row rather than the nearest node, is the fix that the controlledburn route will bring.
The scope is ROMS for now. Other model grids with the same structure may follow.
Install the released version from CRAN with:
install.packages("angstroms")You can install the development version of angstroms from github with:
# install.packages("remotes")
remotes::install_github("AustralianAntarcticDivision/angstroms")Angstroms aims to make working with gridded output as easy as possible in R. Rather than re-map explicitly the complex curvilinear grid in ROMS or ACCESS (or many others), the approach simplifies this by:
In combination these allow extraction and query from the complex grids output very easily.
The ability to deal with time series across multiple files is still in development, though can be used simply now with standard loops.
Here are some notes on lessons learned, all is work in progress.
romsdata(), to ensure that ncdf = TRUE is consistent, and to reduce the amount of extent-setting and orienting codeset_indextent on a brick/raster to ensure it is in index-extent, again to reduce code duplicationsncdf=TRUE is required, because on some systems we might fall back to rgdal which won’t support NetCDF properly (can be done with SDS strings or VRT but that’s a hassle)Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.