vortexRdata is the auxiliary data package for vortexR.

vortexRdata provides data from two publications, Campbell et al (2016) and Pacioni et al. (2017) both as original output from the population viability analysis software Vortex and as R objects.

The R package vortexR uses the raw data provided here to illustrate its functionality of parsing raw Vortex output into R objects.

The stable versions of vortexRdata and vortexR can be installed with:

install.packages("vortexR", dependencies = TRUE)

The latest development versions of vortexRdata and vortexR can be installed with:

# install.packages("devtools")
devtools::install_github("carlopacioni/vortexRdata")
devtools::install_github("carlopacioni/vortexR")

See the vortexR README for detailed help with the installation of Java-based packages.

You can use the data provided by vortexRdata as binary R objects as follows:

require(vortexRdata)
data("pac.clas")
head(pac.clas)

The full list of provided compiled data can be found in the package's documentation: help(package = "vortexRdata").

If you wish to test vortexR's data handling functions on actual Vortex output files, you can use the raw data here as a starting point that is guaranteed to work.

pac.dir <- system.file("extdata", "pacioni", package="vortexRdata")
cam.dir <- system.file("extdata", "campbell", package="vortexRdata")
f <- file.path(pac.dir, "Pacioni_et_al_ST_Classic(Base).stdat")
require(vortexR)
one.st.classic <- collate_one_dat(f, 3)
head(one.st.classic)

The two folders of raw data are named "campbell" and "pacioni", respectively.

Using example data allows users of vortexR to trouble-shoot and validate their workflow before using their own Vortex output.

If you use data provided by vortexRdata, please use the citation generated from citation("vortexRdata").

We are happy to receive feedback and contributions through bug reports and pull requests through the main package vortexR.

Stable version of vortexR and vortexRdata are available on CRAN. A paper describing vortexR is available here.