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Several functions are designed to modify the apsimx file, including *
replace
an existing model * remove
an existing
model * append
a new model as sibling node *
insert
a new model as child
read_apsimx
is used to read files with apsimx json
format, i.e. *.apsimx
for simulations and
*.json
for model under resource.
The existing model can be replaced
and
removed
. The example below shows to update the critical
thermal and then remove it.
# Find the ThermalTime model
a <- search_path(wheat, '[Wheat].Phenology.ThermalTime')
a$node$Children[[1]]$X[[2]]
#> [1] 26
# Update the optimum temperature
a$node$Children[[1]]$X[[2]] <- 27
# Replace with new value
wheat_new <- replace_model(wheat, a$path, a$node)
b <- search_path(wheat_new, '[Wheat].Phenology.ThermalTime')
# The optimum temperature should be updated now
b$node$Children[[1]]$X[[2]]
#> [1] 27
# The ThermalTime model can also be removed
a <- search_path(wheat, '[Wheat].Phenology.ThermalTime')
wheat_new <- remove_model(wheat, a$path)
b <- search_path(wheat_new, '[Wheat].Phenology.ThermalTime')
# The ThermalTime model should not be found now (i.e. Empty list)
b
#> list()
Function new_model
is used to generate the required
elements for a new model, e.g. createing a new cultivar
Hartog
new_cultivar <- new_model("PMF.Cultivar", name = "Hartog")
new_cultivar
#> $`$type`
#> [1] "Models.PMF.Cultivar, Models"
#>
#> $Name
#> [1] "Hartog"
#>
#> $Children
#> list()
#>
#> $IncludeInDocumentation
#> [1] TRUE
#>
#> $Enabled
#> [1] TRUE
#>
#> $ReadOnly
#> [1] FALSE
#>
#> $Alias
#> list()
#>
#> $Command
#> list()
Then the Command
can be updated to specify new parameter
values.
new_cultivar$Command <- list(
"[Phenology].MinimumLeafNumber.FixedValue = 6",
"[Phenology].VrnSensitivity.FixedValue = 0")
Finally the new cultivar can be inserted into apsimx file.
# Read the apsimx file
wheat <- read_apsimx(system.file("extdata/wheat.apsimx", package = "rapsimng"))
# Create a new Replacements
replacements <- new_model("Core.Replacements")
# Insert the replacements into root folder
wheat_new <- insert_model(wheat, 1, replacements)
replacements_node <- search_path(wheat_new, ".Simulations.Replacements")
replacements_node$path
#> [1] 1 3
# Insert the new cultivar
wheat_new <- insert_model(wheat_new, replacements_node$path, new_cultivar)
# Check the new cultivar
cultivar_node <- search_path(wheat_new,
".Simulations.Replacements.Hartog")
cultivar_node$path
#> [1] 1 3 1
cultivar_node$node$Command
#> [[1]]
#> [1] "[Phenology].MinimumLeafNumber.FixedValue = 6"
#>
#> [[2]]
#> [1] "[Phenology].VrnSensitivity.FixedValue = 0"
A new model can be generated in R according to Models assemble in
APSIM Next Generation. The rapsimng package stores a copy of
Models.xml
from APSIM Next Generation on
1st August, 2020
.
The available models can be listed using function
available_models
.
Function update_cultivar
is a short way to update
parameter values for cultivars.
wheat <- read_apsimx(system.file("extdata/wheat.apsimx", package = "rapsimng"))
# Update cultivars
df <- data.frame(name = rep("Hartog", 3),
parameter = c("[Phenology].MinimumLeafNumber.FixedValue",
"[Phenology].VrnSensitivity.FixedValue",
"[Phenology].PpSensitivity.FixedValue"),
value = c(9, 7, 3))
wheat_cultivar <- update_cultivar(wheat, df)
# Check update cultivar paramters
hartog <- search_path(wheat_cultivar, "[Replacements].Hartog")
hartog$path
#> NULL
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.