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09: Troubleshooting / caveats
Fallert, S. and Cabral, J.S.
Source:vignettes/A09_troubleshooting_and_caveats.Rmd
A09_troubleshooting_and_caveats.Rmd
When creating your own simulation, you may encounter issues / errors to which the solution may not be immediately obvious. Here we will cover a basic strategy on how to debug with the example of a simple typo in one of the species traits.
Debugging
The following code will result in an error:
library(metaRange)
library(terra)
set_verbosity(0)
raster_file <- system.file("ex/elev.tif", package = "terra")
r <- rast(raster_file)
r <- scale(r, center = FALSE, scale = TRUE)
r <- rep(r, 10)
landscape <- sds(r)
names(landscape) <- c("habitat_quality")
sim <- create_simulation(
source_environment = landscape,
ID = "example_simulation",
seed = 1
)
sim$add_species(name = "species_1")
sim$add_traits(
species = "species_1",
population_level = TRUE,
abundance = 100,
reproduction_rtae = 0.5,
carrying_capacity = 1000
)
sim$add_process(
species = "species_1",
process_name = "reproduction",
process_fun = function() {
ricker_reproduction_model(
self$traits$abundance,
self$traits$reproduction_rate,
self$traits$carrying_capacity * self$sim$environment$current$habitat_quality
)
},
execution_priority = 1
)
sim$begin()
#> Warning: package 'metaRange' was built under R version 4.3.3
#> metaRange version: 1.1.4
#> terra 1.7.55
#> Error: Not compatible with requested type: [type=NULL; target=double].
And it may not immediately be obvious what the problem is. The first
step to narrow down the problem is to enable extensive verbosity. So, if
we run the code again, but this time with set_verbosity(2)
,
we get the following output:
set_verbosity(2)
sim <- create_simulation(
source_environment = landscape,
ID = "example_simulation",
seed = 1
)
#> number of time steps: 10
#> time step layer mapping: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
#> added environment
#> class : SpatRasterDataset
#> subdatasets : 1
#> dimensions : 90, 95 (nrow, ncol)
#> nlyr : 10
#> resolution : 0.008333333, 0.008333333 (x, y)
#> extent : 5.741667, 6.533333, 49.44167, 50.19167 (xmin, xmax, ymin, ymax)
#> coord. ref. : lon/lat WGS 84 (EPSG:4326)
#> source(s) : memory
#> names : habitat_quality
#>
#> created simulation: example_simulation
sim$add_species(name = "species_1")
#> adding species
#> name: species_1
sim$add_traits(
species = "species_1",
population_level = TRUE,
abundance = 100,
reproduction_rtae = 0.5,
carrying_capacity = 1000
)
#> adding traits:
#> [1] "abundance" "reproduction_rtae" "carrying_capacity"
#>
#> to species:
#> [1] "species_1"
#>
sim$add_process(
species = "species_1",
process_name = "reproduction",
process_fun = function() {
ricker_reproduction_model(
self$traits$abundance,
self$traits$reproduction_rate,
self$traits$carrying_capacity * self$sim$environment$current$habitat_quality
)
},
execution_priority = 1
)
#> adding process: reproduction
#> to species:
#> [1] "species_1"
#>
The setup look ok so far. Now we start the simulation.
sim$begin()
#>
#> Starting simualtion.
#>
#> passed initial sanity checks.
#>
#> start of time step: 1
#> |- species_1 : reproduction
#> Error: Not compatible with requested type: [type=NULL; target=double].
We can see that the error occurs in the first time step, in the
reproduction
process of “species_1”. With this information,
we can now insert a browser()
function, which stops the
code execution once it is called and lets us inspect the process and the
variables of the function / environment it has been called from.
set_verbosity(2)
sim <- create_simulation(
source_environment = landscape,
ID = "example_simulation",
seed = 1
)
sim$add_species(name = "species_1")
sim$add_traits(
species = "species_1",
population_level = TRUE,
abundance = 100,
reproduction_rtae = 0.5,
carrying_capacity = 1000
)
sim$add_process(
species = "species_1",
process_name = "reproduction",
process_fun = function() {
browser()
ricker_reproduction_model(
self$traits$abundance,
self$traits$reproduction_rate,
self$traits$carrying_capacity * self$sim$environment$current$habitat_quality
)
},
execution_priority = 1
)
sim$begin()
In the browser, we are conceptually inside the
reproduction
process of “species_1”. This means we can make
use of the self
keyword to inspect the state of the
species.
As a first step, we might want to call ls()
to see which
objects we can inspect.
# type this in the console,
# once the browser has halted the code execution
ls()
#> [1] "initialize" "name" "print" "processes" "sim"
#> [6] "traits"
Since the error was about an wrong type being passed to the
reproduction function, we can inspect the traits
of the
species to see if they are as we would expect them to be. This means we
can just type self$traits
in the console to see them and we
may notice that the reproduction_rate
is misspelled as
reproduction_rtae
.
# type this in the console,
# once the browser has halted the code execution
self$traits
#> abundance : num [1:90, 1:95] 100 100 100 100 100 100 100 100 100 100 ...
#> carrying_capacity : num [1:90, 1:95] 1000 1000 1000 1000 1000 1000 1000 1000 1000 1000 ...
#> reproduction_rtae : num [1:90, 1:95] 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 ...
We can quit the browser by typing Q
and then
Enter
in the console. Now we can remove the
browser()
call from the code again and proceed to fix the
typo.
General caveats
While metaRange can be used to simulate a wide range of scenarios, there are some caveats to keep in mind.
-
Different scales of the environment and the species
Since the size and resolution of the environment also describes the spatial size of each population (i.e. one grid cell = one population), it is important to choose scales that are appropriate for the species. This is especially important to keep in mind when simulating multiple species, since they may have different spatial requirements.
-
Gene flow
While it is planned for future versions, metaRange does (currently) not support gene flow during dispersal.
-
Spatial distortion
Since metaRange uses raster data to represent the environment, it is important to keep in mind that the raster is a 2D representation of a 3D world. The larger the geographic extent of the environment, the more distorted the raster will be (also depending on the map projection and the resolution).