SpaDES modulesSpaDESOur Getting Started Guide is available from the wiki.
The modules vignette contains much more detail.
SpaDES modulemodule.path <- file.path(dirname(tempdir()), "modules")
downloadModule('wolfAlps', module.path, data = TRUE)
list.files(file.path(module.path, 'wolfAlps'), all.files = TRUE)
/moduleRepository
|_ moduleName/
|_ data/ # directory for all included data
|_ CHECKSUMS.txt # contains checksums for data files
|_ citation.bib # bibtex citation for the module
|_ LICENSE.txt # describes module's legal usage
|_ README.txt # provide overview of key aspects
|_ moduleName.R # module code file (incl. metadata)
|_ moduleName.Rmd # documentation, usage info, etc.
|_ moduleName_x.y.z.zip # zip archive of previous versions
SpaDES moduleadvanced: not included (yet) in the main module repo are examples of modules that include unit tests and code coverage.
These are encouraged and can be built using
# when creating a new module
newModule(..., unitTests = TRUE) # default
# or after-the-fact with
newModuleTests(...)
SpaDES modulesamplePath <- system.file('sampleModules', package = 'SpaDES')
openModules('randomLandscapes', samplePath)
A module code file (.R) consists of the following key sections:
module metatadata (defineModule block)
definitions of each module event type (doEvent.moduleName block)
additional functions used in the events above
(optional) block of code that is run during module initialization, used to perform additional data processing/transformation steps (.inputObjects block)
The newModule function creates a module template for you to edit to suit your needs:
newModule('moduleName', file.path('path/to/my/module/directory'))
Alternatively, use the RStudio addin which is simply a GUI wrapper for this function:
Each module requires a collection of metadata describing the module, its dependencies, and linking to documentation, etc.
These metatadata are defined in the defineModule code block at the start of the file, and are intended to be both human and machine readable.
# see section 'Required metadata elements'
?defineModule
Parameters defined in the module’s defineParameter block are module-specific.
This is where default parameter values are specified (which can be overridden by the user during simInit()).
The inputObjects and outputObjects metadata fields specify a module’s inputs and outputs respectively.
These refer to R objects, rather than raw data files.
sourceURL field in module metadata is used for URLs of external data, which are downloaded using downloadData()Each event consists of two parts:
scheduleEvent())To keep this section as easy to read as possible, use additional module functions (defined in the section below).
envir), rather than pass them as function arguments.envir is similar to accessing items in a list, i.e., sim[["object"]] or sim$object can be used.modulenameEventtype()..inputObjects block (optional)See ?defineModule for details.
SpaDES builds on R’s exceptional graphics capabilities, and the standard R visualization packages etc. can be used with SpaDES.
However, for fast prototyping and on-the-fly graphics useful for module debugging and development you should use Plot().
- much faster than base graphics, ggplot, etc.
- modular plotting (automatic multipanel layouts)
WARNING: The built-in RStudio plotting device is heinously slow!
dev()
PlottingSee the plotting vignette and ?Plot for more detailed examples.
Plot(...)
clearPlot()
Plot(..., new = TRUE)
Plot(..., addTo = objectName)
rePlot()
Module-specific plot parameters can be used to control plotting for your event: .plotInitialTime and .plotInterval.
E.g., schedule a recurring plot event within a module:
nextPlot <- time(mySim) + SpaDES::p(mySim)$.plotInterval
mySim <- scheduleEvent(mySim, nextPlot, "moduleName", "plot")
See http://spades.predictiveecology.org/vignettes/iii-plotting.html#interacting-with-plots
clickValues()clickExtent()http://spades.predictiveecology.org/vignettes/ii-modules.html#load-and-.save-modules
.saveObjectssaveFiles()E.g., schedule a recurring save event within a module:
nextSave <- time(mySim) + SpaDES::p(mySim)$.saveInterval
sim <- scheduleEvent(mySim, nextSave, "moduleName", "save")
Checkpointing is build into SpaDES automatically and can be turned on at the simulation level (not the module level).
parameters <- list(
.checkpoint = list(interval = 10, file = "chkpnt.RData")
)
mySim <- simInit(..., params = parameters)
See vignette for more details.
NOTE don’t checkpoint too often, or your simulation will slow down too much (disk writes are slow).
using spades(sim, debug = TRUE)
adding browser() calls to your module code
using the Rstudio debugger
SpaDES toolsSpaDES package?SpaDES
SpaDES)See this wiki entry.
Add a new module parameter and output to the module metadata.
Add a ‘summarize’ event.
Add an new event function that calculates the statistic(s) of interest.
Update your module’s reqdPkgs metadata field if you are using additional packages.
*Adapted from the one on the wiki.
moduleDiagram and objectDiagram to confirm how data objects are passed among modules.*Adapted from the one on the wiki.
sim$function(sim) to access event functionsuse sim$object to access simulation data objectssim[[globals(sim)$objectName]] to access variable-named objectsmoduleNameFunction() instead of function().sim$function notation is not required for the definition of event functions*Adapted from the one on the wiki.
.Rmd file and README?.Rmd file to generate a .pdf or .html version?*Adapted from the one on the wiki.
data/sourceURL metadata field.inputObjects are correctCHECKSUMS.txt file for all data using checksums(..., write = TRUE)*Adapted from the one on the wiki.
downloadModule and downloadData from a temp dir to ensure your module can be downloaded correctly by others