Finding other modules

Eliot McIntire

Source: vignettes/v-finding-other-modules.Rmd 
if (!require("SpaDES.project")) {
  {install.packages("SpaDES.project", repos = c("predictiveecology.r-universe.dev", getOption("repos")))
   require("SpaDES.project")}
}
#> Loading required package: SpaDES.project

Find other’s modules

One powerful aspect of SpaDES is the ability to connect to other people’s modules. It can be challenging to know where other modules are and what they do. Using the listModules function.

The command sequence we will use is:

  • listModule to identify which modules exist on cloud storage systems,
  • getModules to bring them (or a subset) to your local machine,
  • moduleDependencies to do the metadata analysis,
  • moduleDependenciesToGraph converts them to a graph,
  • moduleDependenciesToGraph to visualize that graph.

A user can use only some of these steps if they do not want to produce the visuals.

A small selection of SpaDES modules

Some Biomass_* modules

This will search the PredictiveEcology github.com repository for any SpaDES module whose name has Biomass_species, Biomass_core, Biomass_regen in it. The search will find any module that contains those keywords, i.e., Biomass_regen will find Biomass_regeneration

Account <- "PredictiveEcology"
grepListShort <- "Biomass_species|Biomass_core|Biomass_regen"
mods <- listModules(grepListShort, accounts = Account)

modPath <- normPath(tempdir2())
getModule(mods, modulePath = modPath)
#> $success
#> [1] "PredictiveEcology/Biomass_core"             
#> [2] "PredictiveEcology/Biomass_regeneration"     
#> [3] "PredictiveEcology/Biomass_regenerationPM"   
#> [4] "PredictiveEcology/Biomass_speciesData"      
#> [5] "PredictiveEcology/Biomass_speciesFactorial" 
#> [6] "PredictiveEcology/Biomass_speciesParameters"
#> 
#> $failed
#> character(0)

DT <- moduleDependencies(mods, modulePath = modPath)
graph <- moduleDependenciesToGraph(DT)
(vn <- PlotModuleGraph(graph))

FireSense modules 

Account <- "PredictiveEcology"
grepListShort <- "fireSense"
mods <- listModules(grepListShort, accounts = Account)

getModule(mods, modulePath = modPath)
#> $success
#>  [1] "PredictiveEcology/fireSense"                
#>  [2] "PredictiveEcology/fireSense_dataPrepFit"    
#>  [3] "PredictiveEcology/fireSense_dataPrepPredict"
#>  [4] "PredictiveEcology/fireSense_EscapeFit"      
#>  [5] "PredictiveEcology/fireSense_EscapePredict"  
#>  [6] "PredictiveEcology/fireSense_IgnitionFit"    
#>  [7] "PredictiveEcology/fireSense_IgnitionPredict"
#>  [8] "PredictiveEcology/fireSense_SpreadFit"      
#>  [9] "PredictiveEcology/fireSense_SpreadPredict"  
#> [10] "PredictiveEcology/fireSense_summary"        
#> 
#> $failed
#> character(0)

DT <- moduleDependencies(mods, modulePath = modPath)
graph <- moduleDependenciesToGraph(DT)
(vn <- PlotModuleGraph(graph))

LandR modules 

Account <- "PredictiveEcology"
grepListShort <- "Biomass_|LandR"
mods <- listModules(grepListShort, accounts = Account)

getModule(mods, modulePath = modPath)
#> $success
#>  [1] "PredictiveEcology/Biomass_borealDataPrep"   
#>  [2] "PredictiveEcology/Biomass_summary"          
#>  [3] "PredictiveEcology/Biomass_validationKNN"    
#>  [4] "PredictiveEcology/Biomass_yieldTables"      
#>  [5] "PredictiveEcology/LandRCBM_split3pools"     
#>  [6] "PredictiveEcology/Biomass_core"             
#>  [7] "PredictiveEcology/Biomass_regeneration"     
#>  [8] "PredictiveEcology/Biomass_regenerationPM"   
#>  [9] "PredictiveEcology/Biomass_speciesData"      
#> [10] "PredictiveEcology/Biomass_speciesFactorial" 
#> [11] "PredictiveEcology/Biomass_speciesParameters"
#> 
#> $failed
#> character(0)

DT <- moduleDependencies(mods, modulePath = modPath)
graph <- moduleDependenciesToGraph(DT)
(vn <- PlotModuleGraph(graph))

A larger selection of “known” SpaDES modules 

# Can do same, but with long list -- not done here -- can try
accountsListLong <- c("PredictiveEcology", "ianmseddy", "achubaty",
                       "FOR-CAST", "eliotmcintire", "tati-micheletti", "CeresBarros")
grepListLong <- c("Biomass", "WBI", "LandR", "fireSense", "CBM",
                  "LandMine", "LandWeb", "NRV", #"scfm",
                  "priority", "fire",
                  "dataPrep", "DataPrep", "RoF", "Ontario", "ROF")
modsLong <- listModules(grepListLong, accounts = accountsListLong)

# pass to listModules for much larger figure
getModule(modsLong, modulePath = modPath)
#> $success
#>  [1] "PredictiveEcology/Biomass_borealDataPrep"     
#>  [2] "PredictiveEcology/Biomass_core"               
#>  [3] "PredictiveEcology/Biomass_regeneration"       
#>  [4] "PredictiveEcology/Biomass_regenerationPM"     
#>  [5] "PredictiveEcology/Biomass_speciesData"        
#>  [6] "PredictiveEcology/Biomass_speciesFactorial"   
#>  [7] "PredictiveEcology/Biomass_speciesParameters"  
#>  [8] "PredictiveEcology/Biomass_summary"            
#>  [9] "PredictiveEcology/Biomass_validationKNN"      
#> [10] "PredictiveEcology/Biomass_yieldTables"        
#> [11] "PredictiveEcology/LandRCBM_split3pools"       
#> [12] "PredictiveEcology/fireSense"                  
#> [13] "PredictiveEcology/fireSense_dataPrepFit"      
#> [14] "PredictiveEcology/fireSense_dataPrepPredict"  
#> [15] "PredictiveEcology/fireSense_EscapeFit"        
#> [16] "PredictiveEcology/fireSense_EscapePredict"    
#> [17] "PredictiveEcology/fireSense_IgnitionFit"      
#> [18] "PredictiveEcology/fireSense_IgnitionPredict"  
#> [19] "PredictiveEcology/fireSense_SpreadFit"        
#> [20] "PredictiveEcology/fireSense_SpreadPredict"    
#> [21] "PredictiveEcology/fireSense_summary"          
#> [22] "PredictiveEcology/CBM_core"                   
#> [23] "PredictiveEcology/CBM_dataPrep_SK"            
#> [24] "PredictiveEcology/CBM_defaults"               
#> [25] "PredictiveEcology/CBM_vol2biomass"            
#> [26] "PredictiveEcology/LandMine"                   
#> [27] "PredictiveEcology/LandWeb_summary"            
#> [28] "PredictiveEcology/priorityPlaces"             
#> [29] "ianmseddy/Quebec_fires_preamble"              
#> [30] "ianmseddy/gmcsDataPrep"                       
#> [31] "achubaty/LandR_MPB_studyArea"                 
#> [32] "FOR-CAST/NRV_summary"                         
#> [33] "FOR-CAST/Ontario_preamble"                    
#> [34] "tati-micheletti/fitBirdBiomassModel"          
#> [35] "tati-micheletti/anthroDisturbance_DataPrep"   
#> [36] "tati-micheletti/potentialResourcesNT_DataPrep"
#> 
#> $failed
#> character(0)

DT <- moduleDependencies(modsLong, modulePath = modPath)
graph <- moduleDependenciesToGraph(DT)
(vn <- PlotModuleGraph(graph))

All SpaDES modules in a set of known accounts

This takes much longer to run as it scans all (open) repositories for each element of accounts. It will search for a relatively “lightweight” indicator of a SpaDES module, namely, a file at the top level that has the same name as the repository, but whose file extension is .R.

# Can do same, but with long list -- not done here -- can try
accountsListLong <- c("PredictiveEcology", "ianmseddy", "achubaty",
                       "FOR-CAST", "eliotmcintire", "tati-micheletti", "CeresBarros")
modsLong <- listModules(accounts = accountsListLong)

# pass to listModules for much larger figure
getModule(modsLong, modulePath = modPath)
#> $success
#>  [1] "PredictiveEcology/BGC"                        
#>  [2] "PredictiveEcology/burnSummaries"              
#>  [3] "PredictiveEcology/canClimateData"             
#>  [4] "PredictiveEcology/canFireRegimeZones"         
#>  [5] "achubaty/mpbClimateData"                      
#>  [6] "achubaty/mpbPine"                             
#>  [7] "achubaty/mpbRedTopSpread"                     
#>  [8] "FOR-CAST/HSI_Caribou_MB"                      
#>  [9] "tati-micheletti/anthroDisturbance_Generator"  
#> [10] "tati-micheletti/birdsNWT"                     
#> [11] "tati-micheletti/caribouCIP"                   
#> [12] "tati-micheletti/caribouPopGrowthModel"        
#> [13] "tati-micheletti/caribouRSF_NT"                
#> [14] "tati-micheletti/disturbanceGenerator_NT"      
#> [15] "CeresBarros/FavierFireSpread"                 
#> [16] "PredictiveEcology/Biomass_borealDataPrep"     
#> [17] "PredictiveEcology/Biomass_core"               
#> [18] "PredictiveEcology/Biomass_regeneration"       
#> [19] "PredictiveEcology/Biomass_regenerationPM"     
#> [20] "PredictiveEcology/Biomass_speciesData"        
#> [21] "PredictiveEcology/Biomass_speciesFactorial"   
#> [22] "PredictiveEcology/Biomass_speciesParameters"  
#> [23] "PredictiveEcology/Biomass_summary"            
#> [24] "PredictiveEcology/Biomass_validationKNN"      
#> [25] "PredictiveEcology/Biomass_yieldTables"        
#> [26] "PredictiveEcology/CBM_core"                   
#> [27] "PredictiveEcology/CBM_dataPrep_SK"            
#> [28] "PredictiveEcology/CBM_defaults"               
#> [29] "PredictiveEcology/CBM_vol2biomass"            
#> [30] "PredictiveEcology/fireSense"                  
#> [31] "PredictiveEcology/fireSense_dataPrepFit"      
#> [32] "PredictiveEcology/fireSense_dataPrepPredict"  
#> [33] "PredictiveEcology/fireSense_EscapeFit"        
#> [34] "PredictiveEcology/fireSense_EscapePredict"    
#> [35] "PredictiveEcology/fireSense_IgnitionFit"      
#> [36] "PredictiveEcology/fireSense_IgnitionPredict"  
#> [37] "PredictiveEcology/fireSense_SpreadFit"        
#> [38] "PredictiveEcology/fireSense_SpreadPredict"    
#> [39] "PredictiveEcology/fireSense_summary"          
#> [40] "PredictiveEcology/LandMine"                   
#> [41] "PredictiveEcology/LandRCBM_split3pools"       
#> [42] "PredictiveEcology/LandWeb_summary"            
#> [43] "PredictiveEcology/priorityPlaces"             
#> [44] "ianmseddy/gmcsDataPrep"                       
#> [45] "ianmseddy/Quebec_fires_preamble"              
#> [46] "achubaty/LandR_MPB_studyArea"                 
#> [47] "FOR-CAST/NRV_summary"                         
#> [48] "FOR-CAST/Ontario_preamble"                    
#> [49] "tati-micheletti/anthroDisturbance_DataPrep"   
#> [50] "tati-micheletti/fitBirdBiomassModel"          
#> [51] "tati-micheletti/potentialResourcesNT_DataPrep"
#> 
#> $failed
#> [1] "ianmseddy/gmcsPredict"

DT <- moduleDependencies(modsLong, modulePath = modPath)
#> Error in h(simpleError(msg, call)) : 
#>   error in evaluating the argument 'x' in selecting a method for function 'defineModule': argument "max" is missing, with no default
#> Error in h(simpleError(msg, call)) : 
#>   error in evaluating the argument 'x' in selecting a method for function 'defineModule': argument "max" is missing, with no default
#> Error in .local(module = module, path = path, defineModuleListItems = defineModuleListItems) : 
#>   C:/Users/emcintir/AppData/Local/Temp/RtmpMZzbJB/reproducible/KXkLY6kJ/gmcsPredict/gmcsPredict.R does not exist. This was created by putting modulePath with the module name as a folder and filename. Please correct the modulePath or module name in the simInit() call.
#> Error in .local(module = module, path = path, defineModuleListItems = defineModuleListItems) : 
#>   C:/Users/emcintir/AppData/Local/Temp/RtmpMZzbJB/reproducible/KXkLY6kJ/gmcsPredict/gmcsPredict.R does not exist. This was created by putting modulePath with the module name as a folder and filename. Please correct the modulePath or module name in the simInit() call.
graph <- moduleDependenciesToGraph(DT)
(vn <- PlotModuleGraph(graph))