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Virtual (Google Meets Link to come), 11am - 2pm Pacific Standard Time, each day
We have organized a set of sessions, back to back, starting from the most “general”, and ending with the most “detailed”. The hope is to attract non-modelers (e.g., managers, scientists, practitioners) to the first session, people who think they might want to see more how models work (e.g., scientists, students, technicians), and those who want to build and use models for research and operational purposes (e.g., scientists, technicians, programmers).
(in progress – but likely stable enough to follow for installations – updated Jan 19, 2021)
Introduction to SpaDES
- Sections 1-3
Sections 1-2 - ~2+ hours – This is a high level intro for scientists, managers, policy makers, decision makers, coupled with examples of ongoing projects in SpaDES
that will showcase the utility of the framework.
Section 3 - ~2+ hours – This section will take you through high-level examples of how to run pre-made SpaDES
modules, run modules from other people, and change model parameters.
Learning SpaDES
- Sections 4-6
Section 4 - 2+ hours – we will take you through basic SpaDES
concepts, while using the previous day’s examples to get you started with understanding the packages and framework.
Sections 5-6 - 2+ hours – This is intended to dive a little bit into the code, learn how to create relatively simple modules and establish links between modules. WE will also touch upon essential aspects of programming with SpaDES
, such as caching and debugging.
This is a high level intro for scientists, managers, policy makers, decision makers, coupled with examples of ongoing projects in SpaDES
that will showcase the utility of the framework.
My first project in SpaDES
- Section 7
You will need to do a few things:
Each of these steps is described in furthre detail below.
If you are using Ubuntu Linux, please see section below for installing binary package files
All the steps below can be found in a single R file, which may be easier to use
If you are feeling lucky, you can try this to do it all:
# source("https://raw.githubusercontent.com/PredictiveEcology/SpaDES.Workshops/master/README.R")
For more information, see here.
xcode-select --install
.r-base-dev
is installed.To confirm everything is installed correctly, run this next line in your R console/Rstudio session. If it shows a “non-empty” path, then you have what you need for the workshop.
Sys.which("make")
If it shows something like this:
make
""
Then you will have to debug your Rtools
installation using the internet as your friend.
workshopPath = "~/SpaDESWorkshop"
modulePath = file.path(workshopPath, "modules")
Get a few helper functions (installGitHubPackage
, getModule
)
## Restart your R session so it is clear
## Ctrl-shift-F10 if you are in Rstudio
source("https://raw.githubusercontent.com/PredictiveEcology/SpaDES-modules/master/R/SpaDES_Helpers.R")
Install latest Require to help with package installation (check that you have one already – you need one already installed; then update, if required)
installedPkgs <- installed.packages(.libPaths()[1])
if (!"Require" %in% rownames(installedPkgs))
install.packages("Require") # to make sure you have 2 dependencies (data.table, remotes)
if (!identical(as.character(packageVersion("Require")), "0.0.11"))
installGitHubPackage("PredictiveEcology/Require@development") # install latest version of Require
Decide whether you want to install packages (and versions) in an isolated folder
{r for-isolated-package-folder} # This isn't perfect as it will not be totally isolated # .libPaths(file.path(workshopPath, "R")) # if you want it fully isolated, you will have to run this file in 2 steps: # Run this next line, then restart session # Require::setup(file.path(workshopPath, "R")) # Then restart your session and run it all again
Install (or update) SpaDES and around 130 package dependencies (if needed)
(note igraph
needs to be installed from source on Linux-alikes)
installSpaDES()
if (dir.exists(modulePath)) unlink(modulePath, recursive = TRUE)
# LandR Biomass modules (simulation modules)
getModule("PredictiveEcology/Biomass_core", modulePath = modulePath)
getModule("PredictiveEcology/Biomass_regeneration", modulePath = modulePath)
# LandR Biomass modules (data preparation modules)
getModule("PredictiveEcology/Biomass_borealDataPrep", modulePath = modulePath)
getModule("PredictiveEcology/Biomass_speciesData", modulePath = modulePath)
# https://github.com/PredictiveEcology/scfm/blob/development/scfm.Rmd fire modules
getModule("PredictiveEcology/scfm@development", modulePath = modulePath, overwrite = TRUE)
# If you have been using the binary package manager for Ubuntu, you have to turn it off
if (isTRUE(grepl("packagemanager", getOption("repos")[["CRAN"]])))
options("repos" = c(CRAN = "https://cran.rstudio.com/"))
modulesInstalled <- dir(modulePath)
dependencies <- SpaDES.core::reqdPkgs(module = modulesInstalled, modulePath = modulePath)
# scfm is actually a collection of modules... the modules are nested in folders
scfmModulePath <- file.path(modulePath, "scfm", "modules")
scfmModulesInstalled = dir(scfmModulePath)
dependencies <- append(dependencies,
SpaDES.core::reqdPkgs(module = scfmModulesInstalled,
modulePath = scfmModulePath) )
needed <- unique(unlist(dependencies, recursive = FALSE))
Require::Require(needed, require = FALSE, upgrade = "never")
error 403
It can happen that if you try downloading from GitHub
many times, you exceed the API rate limit:
install_github('PredictiveEcology/SpaDES')
Downloading GitHub repo PredictiveEcology/SpaDES@master
Error: HTTP error 403.
API rate limit exceeded for ###.###.##.###.
(...)
The error should provide the solution to fixing this problem, but if for some reason you don’t find these instructions, here they are:
usethis::browse_github_pat()
to create a GitHub tokenusethis::edit_r_environ()
and add the environment variable with GITHUB_PAT = 'your_github_token'
. Restart R (so that the GITHUB_PAT is read) and try to reinstall: devtools::install_github(...)
Because there are a lot of packages, it may be faster to install binaries from the Rstudio CRAN mirror. To use this CRAN mirror, you can run this code to set up the correct CRAN repository. If you put this in your .Rprofile
file, then your R sessions will always use this binary repository:
options("repos" = c(CRAN = "https://cran.rstudio.com"))
if (Sys.info()["sysname"] == "Linux" && grepl("Ubuntu", utils::osVersion)) {
.os.version <- strsplit(system("lsb_release -c", intern = TRUE), ":\t")[[1]][[2]]
.user.agent <- paste0(
"R/", getRversion(), " R (",
paste(getRversion(), R.version["platform"], R.version["arch"], R.version["os"]),
")"
)
options(repos = c(CRAN = paste0("https://packagemanager.rstudio.com/all/__linux__/",
.os.version, "/latest")))
options(HTTPUserAgent = .user.agent)
}
If you are comfortable with GitHub.com
, you can clone the entire SpaDES.Workshops
repository and thus have all the *.Rmd
files used in this workshop:
https://github.com/PredictiveEcology/SpaDES.Workshops
For a direct link to the workshops, click on the top navigation bar or go here