R Under development (unstable) (2025-03-09 r87914 ucrt) -- "Unsuffered Consequences"
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> ## This test will build from simple to more complex sensitivity analysis
> 
> require(apsimx)
Loading required package: apsimx
APSIM(X) not found.
                        If APSIM(X) is installed in an alternative location,
                        set paths manually using 'apsimx_options' or 'apsim_options'.
                        You can still try as the package will look into the registry (under Windows)
> packageVersion("apsimx")
[1] '2.8.235'
> require(ggplot2)
Loading required package: ggplot2
> apsimx_options(warn.versions = FALSE)
> 
> run.sens.apsimx <- FALSE
> 
> tmp.dir <- tempdir()
> setwd(tmp.dir)
> 
> ## WheatRye example
> if(run.sens.apsimx){
+   
+   ## Test the effect of changing RUE
+   extd.dir <- "~/Dropbox/apsimx/inst/extdata"
+   file.copy(file.path(extd.dir, "WheatRye.apsimx"), ".")
+   file.copy(file.path(extd.dir, "Ames.met"), ".")
+   
+   inspect_apsimx("WheatRye.apsimx", node = "Report")
+   
+   edit_apsimx("WheatRye.apsimx", node = "Report",
+               parm = "VariableNames",
+               value = "[Wheat].Leaf.Transpiration",
+               overwrite = TRUE)
+   
+   
+   sim0 <- apsimx("WheatRye.apsimx")
+   
+   ggplot(data = sim0, aes(x = Date, y = Wheat.AboveGround.Wt)) + 
+     geom_point()
+   
+   ggplot(data = sim0, aes(x = Date, y = Wheat.Leaf.Transpiration)) + 
+     geom_point()
+   
+   inspect_apsimx_replacement("WheatRye.apsimx",
+                              node = "Wheat", node.child = "Leaf",
+                              node.subchild = "Photosynthesis",
+                              node.subsubchild = "RUE")
+   
+   pp <- "Wheat.Leaf.Photosynthesis.RUE"
+   
+   start <- Sys.time()
+   rues <- seq(0, 3, 0.25)
+   res.dat <- NULL
+   
+   for(i in seq_along(rues)){
+     
+     edit_apsimx_replacement("WheatRye.apsimx",
+                             node.string = pp,
+                             parm = "FixedValue",
+                             value = rues[i],
+                             overwrite = TRUE,
+                             verbose = FALSE)
+     
+     sim1 <- apsimx("WheatRye.apsimx")
+     
+     res.dat <- rbind(res.dat, data.frame(rue = rues[i], 
+                                          wheat.aboveground.wt = mean(sim1$Wheat.AboveGround.Wt),
+                                          wheat.leaf.lai = mean(sim1$Wheat.Leaf.LAI),
+                                          wheat.leaf.transpiration = mean(sim1$Wheat.Leaf.Transpiration)))
+   }
+   end <- Sys.time()
+   
+   elapsed.time <- end - start
+   
+   ggplot(data = res.dat, aes(x = rue, y = wheat.aboveground.wt)) + 
+     geom_point() + 
+     geom_smooth(se = FALSE)
+   
+   ggplot(data = res.dat, aes(x = rue, y = wheat.leaf.lai)) + 
+     geom_point() + 
+     geom_smooth(se = FALSE)
+ 
+   ggplot(data = res.dat, aes(x = rue, y = wheat.leaf.transpiration)) + 
+     geom_point() + 
+     geom_smooth(se = FALSE)
+   
+   ggplot(data = sim1, aes(x = Date, y = Wheat.AboveGround.Wt)) + 
+     geom_point()
+  
+   ggplot(data = sim1, aes(x = Date, y = Wheat.Leaf.LAI)) + 
+     geom_point()
+   
+   file.remove("WheatRye.apsimx")
+   file.remove("Ames.met")
+   file.remove("WheatRye.db")
+   file.remove("WheatRye.db-shm")
+   file.remove("WheatRye.db-wal")
+ }
> 
> ## MaizeSoybean example
> if(run.sens.apsimx){
+   
+   ## Test the effect of changing RUE
+   extd.dir <- "~/Dropbox/apsimx/inst/extdata"
+   file.copy(file.path(extd.dir, "MaizeSoybean.apsimx"), ".")
+   file.copy(file.path(extd.dir, "Ames.met"), ".")
+   
+   inspect_apsimx("MaizeSoybean.apsimx", node = "Report",
+                  root = "SimulationMaize")
+   
+   edit_apsimx("MaizeSoybean.apsimx",
+               root = "SimulationMaize",
+               node = "Report",
+               parm = "VariableNames",
+               value = c("[Maize].AboveGround.Wt", "[Maize].Leaf.LAI", "[Maize].Leaf.Transpiration"),
+               overwrite = TRUE)
+   
+   sim0 <- apsimx("MaizeSoybean.apsimx")
+   
+   ggplot(data = sim0, aes(x = Date, y = Maize.AboveGround.Wt)) + 
+     geom_point()
+   
+   ggplot(data = sim0, aes(x = Date, y = Maize.Leaf.LAI)) + 
+     geom_point()
+ 
+   ggplot(data = sim0, aes(x = Date, y = Maize.Leaf.Transpiration)) + 
+     geom_point()
+ 
+   pp <- "Maize.Leaf.Photosynthesis.RUE"
+   
+   start <- Sys.time()
+   rues <- seq(0, 3, 0.25)
+   res.dat <- NULL
+   
+   for(i in seq_along(rues)){
+     
+     edit_apsimx_replacement("MaizeSoybean.apsimx",
+                             node.string = pp,
+                             parm = "FixedValue",
+                             value = rues[i],
+                             overwrite = TRUE,
+                             verbose = FALSE)
+     
+     sim1 <- apsimx("MaizeSoybean.apsimx")
+     
+     res.dat <- rbind(res.dat, data.frame(rue = rues[i], 
+                                          maize.aboveground.wt = mean(sim1$Maize.AboveGround.Wt, na.rm = TRUE),
+                                          maize.leaf.lai = mean(sim1$Maize.Leaf.LAI, na.rm = TRUE),
+                                          maize.leaf.transpiration = mean(sim1$Maize.Leaf.Transpiration, na.rm = TRUE)))
+   }
+   end <- Sys.time()
+   elapsed.time <- end - start
+   
+   ggplot(data = res.dat, aes(x = rue, y = maize.aboveground.wt)) + 
+     geom_point() + 
+     geom_smooth(se = FALSE)
+   
+   ggplot(data = res.dat, aes(x = rue, y = maize.leaf.lai)) + 
+     geom_point() + 
+     geom_smooth(se = FALSE)
+   
+   ggplot(data = res.dat, aes(x = rue, y = maize.leaf.transpiration)) + 
+     geom_point() + 
+     geom_smooth(se = FALSE) 
+   
+   ## For the specific simulation
+   ggplot(data = sim1, aes(x = Date, y = Maize.AboveGround.Wt)) + 
+     geom_point()
+   
+   ggplot(data = sim1, aes(x = Date, y = Maize.Leaf.LAI)) + 
+     geom_point()
+ 
+   ggplot(data = sim1, aes(x = Date, y = Maize.Leaf.Transpiration)) + 
+     geom_point()
+   
+   ### Clean up
+   file.remove(dir(pattern = "MaizeSoybean"))
+   file.remove("Ames.met")
+ }
> 
> if(run.sens.apsimx){
+   
+   extd.dir <- system.file("extdata", package = "apsimx")
+   file.copy(file.path(extd.dir, "Wheat.apsimx"), tmp.dir)
+   file.copy(file.path(extd.dir, "Ames.met"), ".")
+   ## Identify a parameter of interest
+   ## In this case we want to know the impact of varying the fertilizer amount
+   pp <- inspect_apsimx("Wheat.apsimx", src.dir = tmp.dir, 
+                        node = "Manager", parm = list("SowingFertiliser", 1))
+   pp <- paste0(pp, ".Amount")
+   ## Do we need to edit the Report?
+   edit_apsimx("Wheat.apsimx", src.dir = tmp.dir, node = "Report",
+               parm = "VariableNames", value = c("max of [Wheat].Leaf.LAI from 1-Jan to 31-Dec as MaximumLAI", 
+                                                 "sum of [Wheat].Leaf.Transpiration from 1-Jan to 31-Dec as AnnualLeafTranspiration"),
+               overwrite = TRUE)
+   ## Before the analysis
+   sim0 <- apsimx("Wheat.apsimx", src.dir = tmp.dir)
+   
+   head(sim0)
+   
+   ggplot(data = sim0, aes(x = Date, y = MaximumLAI)) + 
+     geom_point()
+   
+   ggplot(data = sim0, aes(x = MaximumLAI, y = Yield)) + 
+     geom_point()
+   
+   ## For simplicity, we create a vector of fertilizer amounts (instead of sampling)
+   start <- Sys.time()
+   ferts <- seq(5, 300, length.out = 10)
+   col.res <- NULL
+   for(i in 1:10){
+     
+     edit_apsimx("Wheat.apsimx", src.dir = tmp.dir,
+                 node = "Other", parm.path = pp,
+                 value = ferts[i],
+                 overwrite = TRUE)
+     
+     sim <- apsimx("Wheat.apsimx", src.dir = tmp.dir)
+     col.res <- rbind(col.res, data.frame(fertilizer.amount = ferts[i], 
+                                          wheat.aboveground.wt = mean(sim$Wheat.AboveGround.Wt, na.rm = TRUE),
+                                          wheat.yield = mean(sim$Yield, na.rm = TRUE),
+                                          wheat.maximum.lai = mean(sim$MaximumLAI, na.rm = TRUE),
+                                          wheat.annual.leaf.transpiration = mean(sim$AnnualLeafTranspiration, na.rm = TRUE)))
+   }
+   end <- Sys.time()
+   elapsed.time <- end - start
+   
+   ggplot(col.res, aes(x = fertilizer.amount, y = wheat.aboveground.wt)) + 
+     geom_point()
+   
+   ggplot(col.res, aes(x = fertilizer.amount, y = wheat.yield)) + 
+     geom_point()
+ 
+   ggplot(col.res, aes(x = fertilizer.amount, y = wheat.maximum.lai)) + 
+     geom_point()
+ 
+   ggplot(col.res, aes(x = fertilizer.amount, y = wheat.annual.leaf.transpiration)) + 
+     geom_point()
+   
+   ### Clean up
+   file.remove(dir(pattern = "Wheat"))
+   file.remove("Ames.met")
+ 
+ }
> 
> if(run.sens.apsimx){
+   
+   extd.dir <- system.file("extdata", package = "apsimx")
+   file.copy(file.path(extd.dir, "Wheat.apsimx"), ".")
+   file.copy(file.path(extd.dir, "Ames.met"), ".")
+   ## Identify a parameter of interest
+   ## In this case we want to know the impact of varying the fertilizer amount
+   ## and the plant population
+   pp1 <- inspect_apsimx("Wheat.apsimx", src.dir = ".", 
+                        node = "Manager", parm = list("SowingFertiliser", 1))
+   pp1 <- paste0(pp1, ".Amount")
+   
+   pp2 <- inspect_apsimx("Wheat.apsimx", src.dir = tmp.dir, 
+                        node = "Manager", parm = list("SowingRule1", 9))
+   pp2 <- paste0(pp2, ".Population")
+   
+   grd <- expand.grid(parm1 = c(50, 100, 150), parm2 = c(100, 200, 300))
+   names(grd) <- c("Fertiliser", "Population")
+   
+   start <- Sys.time()
+   sns <- sens_apsimx("Wheat.apsimx", src.dir = tmp.dir,
+                      parm.paths = c(pp1, pp2),
+                      grid = grd,
+                      cores = 2L)
+   end <- Sys.time()
+   ### Time elapsed with 2 cores (Mac 2017): 1.158267 (minutes)
+   ### Time elapsed with 1 core (Mac 2017): 1.921198 (minutes)
+   ### Time elapsed with 2 cores (Mac 2021): 55.6 (seconds)
+   
+   summary(sns)
+   summary(sns, select = "Wheat.AboveGround.Wt")
+   summary(sns, select = "AboveGround")
+   ## summary(sns, select = "AboveGround", formula = 2L)
+ 
+   sns.nn <- sens_apsimx("Wheat.apsimx", src.dir = tmp.dir,
+                         parm.paths = c(pp1, pp2),
+                         grid = grd, summary = "none",
+                         cores = 2L)
+   
+   summary(sns.nn, select = "Wheat.AboveGround.Wt")
+   
+   ## it is possible to use the package sensitivity to design an experiment
+   library(sensitivity)
+   X.mrrs <- morris(factors = c("Fertiliser", "Population"), r = 3, 
+                      design = list(type = "oat", levels = 3, grid.jump = 1), 
+                      binf = c(5, 50), bsup = c(200, 300))
+   
+   sns2 <- sens_apsimx("Wheat.apsimx", src.dir = tmp.dir,
+                       parm.paths = c(pp1, pp2),
+                       grid = X.mrrs$X,
+                       cores = 2L)
+   ## These are the sensitivity results for AboveGround.Wt only
+   sns.res.ag <- tell(X.mrrs, sns2$grid.sims$Wheat.AboveGround.Wt)
+   sns.res.ag
+   plot(sns.res.ag)
+   
+   ### Clean up
+   file.remove(dir(pattern = "Wheat"))
+   file.remove(dir(pattern = "Ames.met"))
+   
+ }
> 
> #### Create Classic example ####
> if(run.sens.apsimx){
+   
+   apsim_options(warn.versions = FALSE)
+   ex.dir <- auto_detect_apsim_examples()
+   extd.dir <- system.file("extdata", package = "apsimx")
+   file.copy(file.path(extd.dir, "Millet.apsim"), ".")  
+   file.copy(file.path(ex.dir, "MetFiles", "Goond.met"), ".")
+ 
+   pp1 <- inspect_apsim("Millet.apsim", src.dir = tmp.dir, 
+                         node = "Manager", 
+                        parm = list("Sow", 2),
+                        print.path = TRUE)
+   
+   pp2 <- inspect_apsim("Millet.apsim", src.dir = tmp.dir, 
+                        node = "Manager", 
+                        parm = list("Sow", 5), 
+                        print.path = TRUE)
+ 
+   grd <- expand.grid(parm1 = c("15-nov", "1-dec", "15-dec"), parm2 = c(5, 7, 9))
+   names(grd) <- c("date", "density")    
+   
+   edit_apsim("Millet.apsim", node = "Clock",
+              parm = "start_date", value = "01/01/1980",
+              overwrite = TRUE)
+   
+   sim0 <- apsim("Millet.apsim")
+   
+   sns <- sens_apsim("Millet.apsim",
+                      parm.paths = c(pp1, pp2),
+                      grid = grd)
+   
+   summary(sns)
+   summary(sns, select = "millet_biomass")
+   
+   sns2 <- sens_apsim("Millet.apsim",
+                     parm.paths = c(pp1, pp2),
+                     grid = grd,
+                     summary = "none")
+   
+   sns2$grid.sims[1:5, 1:5]  
+   
+ }
> 
> #### Testing the cores argument ####
> 
> run.sens.apsimx.cores <- FALSE
> 
> if(run.sens.apsimx.cores){
+   
+   extd.dir <- system.file("extdata", package = "apsimx")
+   file.copy(file.path(extd.dir, "Wheat.apsimx"), ".")
+   file.copy(file.path(extd.dir, "Ames.met"), ".")
+   ## Identify a parameter of interest
+   ## In this case we want to know the impact of varying the fertilizer amount
+   ## and the plant population
+   pp1 <- inspect_apsimx("Wheat.apsimx", src.dir = ".", 
+                         node = "Manager", parm = list("SowingFertiliser", 1))
+   pp1 <- paste0(pp1, ".Amount")
+   
+   pp2 <- inspect_apsimx("Wheat.apsimx", src.dir = tmp.dir, 
+                         node = "Manager", parm = list("SowingRule1", 9))
+   pp2 <- paste0(pp2, ".Population")
+   
+   grd <- expand.grid(parm1 = c(50, 100, 150), parm2 = c(100, 200, 300))
+   names(grd) <- c("Fertiliser", "Population")
+   
+   ## dim(grd) ## 9 simulations
+   start <- Sys.time()
+   sns <- sens_apsimx("Wheat.apsimx", src.dir = tmp.dir,
+                      parm.paths = c(pp1, pp2),
+                      grid = grd)
+   (Sys.time() - start)
+   ## This takes 1.55 minutes (Mac)
+   ## This now (Jan 2024) takes 2.14 minutes (Mac)
+   ## Mac 2017 (Aug 2024): 1.800195
+   ## Mac 2021 (Mar 2025): 1.5 minutes
+   summary(sns)
+   summary(sns, select = "Wheat.AboveGround.Wt", scale = TRUE)
+   summary(sns, select = "AboveGround", scale = TRUE)
+   
+   start <- Sys.time()
+   sns.c2 <- sens_apsimx("Wheat.apsimx", src.dir = tmp.dir,
+                         parm.paths = c(pp1, pp2),
+                         grid = grd, cores = 2L)
+   (Sys.time() - start)
+   ## This takes 1.29 minutes (Jan 2024)
+   ## Windows: NA
+   ## Mac 2017 (Aug 2024): 1.319598
+   ## Mac 2021 (Mar 2025): 54 seconds 
+   ## Are they the same?
+   (diff.sns.vs.sns.c2 <- sum(colSums(sns$grid.sims - sns.c2$grid.sims)))
+   
+   if(abs(diff.sns.vs.sns.c2) > 0.001)
+     stop("Simulations with 2 cores do not match")
+   
+   start <- Sys.time()
+   sns.c4 <- sens_apsimx("Wheat.apsimx", src.dir = tmp.dir,
+                         parm.paths = c(pp1, pp2),
+                         grid = grd, cores = 4)
+   (Sys.time() - start)
+   ## Mac 2017 (Aug 2024) takes: 1.161401 minutes
+   ## Mac 2021 (Mar 2025) takes: 33.9 seconds
+   (diff.sns.vs.sns.c4 <- sum(colSums(sns$grid.sims - sns.c4$grid.sims)))
+   
+   if(abs(diff.sns.vs.sns.c4) > 0.001)
+     stop("Simulations with 4 cores do not match")
+ 
+   #### Summary = 'none' and 1L core
+   start <- Sys.time()
+   sns.s0 <- sens_apsimx("Wheat.apsimx", src.dir = tmp.dir,
+                         parm.paths = c(pp1, pp2),
+                         summary = "none",
+                         grid = grd)
+   (Sys.time() - start)
+   
+   start <- Sys.time()
+   sns.s0.c2 <- sens_apsimx("Wheat.apsimx", src.dir = tmp.dir,
+                            parm.paths = c(pp1, pp2),
+                            summary = "none",
+                            grid = grd,
+                            cores = 2L)
+   (Sys.time() - start)
+   ### The difference in times here are: Mac 2017 (1 core) - 1.63 vs. (2 cores) - 1.1
+   ### The difference in times here are: Mac 2021 (1 core) - 1.52 vs. (2 cores) - 54.4 seconds
+   ## library(arsenal) 
+   
+   ## Data.frames are not identical, but summary results are
+   ## cm1 <- arsenal::comparedf(sns.s0$grid.sims, sns.s0.c2$grid.sims)
+   sns.s0$grid.sims[78, "Fertiliser"]
+   sns.s0.c2$grid.sims[78, "Fertiliser"]
+   ## The results are the same, but in different order
+   
+   summary(sns.s0, select = "AboveGround.Wt", scale = TRUE)
+   summary(sns.s0.c2, select = "AboveGround.Wt", scale = TRUE)
+   
+   summary(sns.s0, select = "AboveGround.N", scale = TRUE)
+   summary(sns.s0.c2, select = "AboveGround.N", scale = TRUE)
+   
+   summary(sns.s0, select = "Yield", scale = TRUE)
+   summary(sns.s0.c2, select = "Yield", scale = TRUE)
+   
+   ### What if I reorder the simulations?
+   snsd1 <- sns.s0$grid.sims
+   snsd2 <- sns.s0.c2$grid.sims
+ 
+   snsd1.o <- snsd1[order(snsd1$Fertiliser, snsd1$Population, snsd1$Date), ]
+   snsd2.o <- snsd2[order(snsd2$Fertiliser, snsd2$Population, snsd2$Date), ]
+   ##cmpd12 <- arsenal::comparedf(snsd2.o, snsd2.o)   
+   
+   ### Clean up
+   file.remove(dir(pattern = "Wheat"))
+   file.remove(dir(pattern = "Ames.met"))
+ 
+ }
> 
> #### Testing passing of soil profiles -----
> 
> run.sens.apsimx.soils <- FALSE
> 
> if(run.sens.apsimx.soils){
+   
+   extd.dir <- system.file("extdata", package = "apsimx")
+   file.copy(file.path(extd.dir, "Wheat.apsimx"), ".")
+   file.copy(file.path(extd.dir, "Ames.met"), ".")
+   ## Identify a parameter of interest
+   ## In this case we want to know the impact of varying the fertilizer amount
+   ## and the plant population
+   pp1 <- inspect_apsimx("Wheat.apsimx", src.dir = ".", 
+                         node = "Manager", parm = list("SowingFertiliser", 1))
+   pp1 <- paste0(pp1, ".Amount")
+   
+   pp2 <- inspect_apsimx("Wheat.apsimx", src.dir = tmp.dir, 
+                         node = "Manager", parm = list("SowingRule1", 9))
+   pp2 <- paste0(pp2, ".Population")
+   
+   grd <- expand.grid(parm1 = c(50, 100, 150), parm2 = c(100, 200, 300), parm3 = c(1, 2))
+   names(grd) <- c("Fertiliser", "Population", "soil.profile")
+   
+   inspect_apsimx("Wheat.apsimx", node = "Other", parm = list(1, 1, 5, 0), print.path = TRUE)
+ 
+   ### Getting soils
+   sps <- get_ssurgo_soil_profile(lonlat = c(-93, 42), nsoil = 2, fix = TRUE)
+   
+   plot(sps[[1]], property = "water")
+   plot(sps[[1]], property = "Carbon")
+   
+   plot(sps[[2]], property = "water")
+   plot(sps[[2]], property = "Carbon")
+ 
+   ## Base simulation
+   sim0 <- apsimx("Wheat.apsimx", src.dir = tmp.dir)
+   
+   start <- Sys.time()
+   sns <- sens_apsimx("Wheat.apsimx", src.dir = tmp.dir,
+                      parm.paths = c(pp1, pp2, 'soil.profile'),
+                      soil.profiles = sps,
+                      grid = grd)
+   (Sys.time() - start) 
+   ## Taking 3.32 minutes (Mac 2017 - Aug 2024)
+   ## Taking 3.1 minutes (Mac 2021 - Mar 2025)
+   
+   snsd <- sns$grid.sims
+   
+   ggplot(data = snsd, aes(x = Fertiliser, y = Yield, color = as.factor(soil.profile))) + 
+     facet_wrap(~ Population) + 
+     geom_line()
+ 
+   ggplot(data = snsd, aes(x = Fertiliser, y = Wheat.AboveGround.Wt, color = as.factor(soil.profile))) + 
+     facet_wrap(~ Population) + 
+     geom_line()
+   
+   ### Compare soil profiles
+   cmps <- compare_apsim_soil_profile(sps[[1]], sps[[2]])
+   
+   plot(cmps, plot.type = "depth", soil.var = c("DUL"))
+   plot(cmps, plot.type = "depth", soil.var = c("LL15")) ## Should implement 'water'
+   plot(cmps, plot.type = "depth", soil.var = "Carbon")
+ 
+   ### Clean up
+   file.remove("Wheat.apsimx")
+   file.remove("Ames.met")
+ }
> 
> #### Multiple soils simulation ----
> ### I need to think more about the additional tests that I need to 
> ### to ensure that the feature of cycling through soils works
> ### Why did I think that there can be more than one column of soils that
> ### Need to be replaced? I think it is because of multiple simulations
> ### In one simulation run I could need to replace the soil of several 'roots'
> ### How do I do this?
> 
> run.multiple.soils.sens.apsimx <- FALSE
> 
> if(run.multiple.soils.sens.apsimx){
+   
+   ### Is AgPasture the best example of a multiple simulation file?
+   extd.dir <- system.file("extdata", package = "apsimx")  
+   file.copy(file.path(extd.dir, "MaizeSoybean.apsimx"), ".")
+   file.copy(file.path(extd.dir, "Ames.met"), ".")
+   
+   inspect_apsimx("MaizeSoybean.apsimx", ".", node = "Other",
+                  parm = 2)
+   
+   inspect_apsimx("MaizeSoybean.apsimx", ".", node = "Other",
+                  parm = list(1, 2, 5, 0))
+   
+   check_apsimx("MaizeSoybean.apsimx", root = "SimulationSoybean")
+   check_apsimx("MaizeSoybean.apsimx", root = "SimulationMaize")
+   
+   sim0 <- apsimx("MaizeSoybean.apsimx")
+ 
+   dir()
+   dim(sim0)
+   
+   ggplot(data = sim0[sim0$SimulationName == "SimulationMaize", ], 
+          aes(x = Date, y = Maize.Total.Wt)) + 
+     geom_line()
+   
+   ggplot(data = sim0[sim0$SimulationName == "SimulationSoybean", ], 
+          aes(x = Date, y = Soybean.Total.Wt)) + 
+     geom_line()
+   
+   ### Inspecting the soil
+   inspect_apsimx("MaizeSoybean.apsimx", node = "Soil",
+                  root = "SimulationSoybean",
+                  soil.child = "Physical")
+   
+   inspect_apsimx("MaizeSoybean.apsimx", node = "Soil",
+                  root = "SimulationMaize",
+                  soil.child = "Physical")
+ 
+   inspect_apsimx("MaizeSoybean.apsimx", node = "Soil",
+                  root = "SimulationMaize") ### Nicollet
+   inspect_apsimx("MaizeSoybean.apsimx", node = "Soil",
+                  root = "SimulationSoybean") ### Nicollet
+   
+   #### Extracting alternative soils for this location?
+   sps <- get_ssurgo_soil_profile(c(-93.76911, 42.02204), nsoil = 2, fix = TRUE)
+ 
+   #### Which soils are these?
+   sps[[1]]$metadata$SoilType
+   sps[[2]]$metadata$SoilType
+   
+   plot(sps[[1]], property = "water")
+   plot(sps[[2]], property = "water")
+   
+   #### Now I want to edit these soils for each simulation... Will it work?
+   #### What if I ONLY change the soils? It does not work
+   soil.paths <- c("SimulationSoybean.Soil", "SimulationMaize.Soil")
+   grd <- expand.grid(soil1 = 1:2, soil2 = 1:2)
+   names(grd) <- soil.paths
+   
+   start <- Sys.time()
+   sns.soil0 <- sens_apsimx("MaizeSoybean.apsimx", 
+                            parm.paths = soil.paths,
+                            convert = rep(FALSE, 2),
+                            replacement = rep(FALSE, 2),
+                            grid = grd,
+                            summary = "none",
+                            soil.profiles = sps)
+   (Sys.time() - start)
+   
+   head(sns.soil0$grid.sims[, c(1, 2, 3, 9)])
+ 
+   snsM <- subset(sns.soil0$grid.sims, SimulationName == "SimulationMaize") 
+   ggplot(data = snsM, 
+          aes(x = Date, y = Maize.Total.Wt, color = as.factor(SimulationMaize.Soil))) + 
+     geom_line() + 
+     ylim(c(1000, 2000))
+   
+   snsS <- subset(sns.soil0$grid.sims, SimulationName == "SimulationSoybean") 
+   ggplot(data = snsS, 
+          aes(x = Date, y = Soybean.Total.Wt, color = as.factor(SimulationSoybean.Soil))) + 
+     geom_line()
+   
+   ### Can I use more than one core?
+   start <- Sys.time()
+   sns.soil0.c2 <- sens_apsimx("MaizeSoybean.apsimx", 
+                               parm.paths = soil.paths,
+                               convert = rep(FALSE, 2),
+                               replacement = rep(FALSE, 2),
+                               grid = grd,
+                               summary = "none",
+                               soil.profiles = sps,
+                               cores = 2L)
+   (Sys.time() - start)
+   #### There appears to be no benefit with such a small number of simulations,
+   #### but it runs...
+   
+   
+ }
> 
> proc.time()
   user  system elapsed 
   0.89    0.20    1.01