diff --git a/docs/src/developing.md b/docs/src/developing.md
index 89ca256aa8135967573ce1e499c23af173f3ff96..7e2c3c63ceb2fb1037ba9022ef6293ee2a5ed8aa 100644
--- a/docs/src/developing.md
+++ b/docs/src/developing.md
@@ -129,3 +129,25 @@ To build the documentation, run `make docs`, or `cd docs; julia builddocs.jl`
Persefone uses [Makie](https://makie.org/) as a plotting library to generate its
output graphics. Additionally, Persefone Desktop uses
[QML.jl](https://github.com/JuliaGraphics/QML.jl) to create its graphical user interface.
+
+### Unitful.jl
+
+Throughout the source code, variables can be tagged with their appropriate units using
+the [Unitful.jl](https://painterqubits.github.io/Unitful.jl/stable/) library. This makes
+the code easier to understand, and also allows automatic unit conversion:
+
+```julia
+julia> 1ha == 10000m²
+true
+
+julia> 2km |> m
+2000 m
+
+julia> 2km / 10m
+200.0
+```
+
+Within Persefone, the following units and dimensions have been imported for direct usage:
+`cm`, `m`, `km`, `m²`, `ha`, `km²`, `Length`, `Area`. For a full list of supported units,
+see [here](https://github.com/PainterQubits/Unitful.jl/blob/master/src/pkgdefaults.jl).
+To define new units, see [the documentation](https://painterqubits.github.io/Unitful.jl/stable/newunits/).
diff --git a/src/nature/species/skylark.jl b/src/nature/species/skylark.jl
index b639630b22f5a3b891308e1f04b69a7286a5e21d..9f4e2e7ce5e300db45e441552c74fc2e8e70a7a4 100644
--- a/src/nature/species/skylark.jl
+++ b/src/nature/species/skylark.jl
@@ -3,11 +3,10 @@
### This file holds the code for the Eurasian Skylark (Alauda arvensis).
###
-#XXX global variable
+#XXX global variable/function
skylarkhabitat = @habitat((@landcover() == grass ||
- # settle on grass or arable land (but not maize)
(@landcover() == agriculture && @cropname() != "maize")) &&
- @distancetoedge() > 50m) # at least 50m from other habitats
+ @distancetoedge() > 50m)
#XXX this ought to check for distance to forest and builtup,
# but that's very expensive (see below)
# @distanceto(forest) > 5 && # at least 50m from forest edges
diff --git a/test/landscape_tests.jl b/test/landscape_tests.jl
index 10bd212907286e3ffd36330eaf4b77595ce5dbcc..b82576512052685ee743d91ff42a5f3dfdfcfeb4 100644
--- a/test/landscape_tests.jl
+++ b/test/landscape_tests.jl
@@ -47,14 +47,14 @@ end
@test Ps.directionto((2,3), model, Ps.grass) == (1,2)
@test Ps.directionto((2,3), model, Ps.water) == (4,1)
@test Ps.directionto((2,3), model, Ps.soil) == nothing
- @test Ps.distanceto((2,3), model, Ps.agriculture) == 0
- @test Ps.distanceto((2,3), model, Ps.forest) == 2
- @test Ps.distanceto((2,3), model, Ps.grass) == 2
- @test Ps.distanceto((2,3), model, Ps.water) == 4
+ @test Ps.distanceto((2,3), model, Ps.agriculture) == 0m
+ @test Ps.distanceto((2,3), model, Ps.forest) == 20m
+ @test Ps.distanceto((2,3), model, Ps.grass) == 20m
+ @test Ps.distanceto((2,3), model, Ps.water) == 40m
@test Ps.distanceto((2,3), model, Ps.soil) == Inf
- @test Ps.distancetoedge((1,1), model) == 4
- @test Ps.distancetoedge((4,4), model) == 1
- @test Ps.distancetoedge((6,6), model) == 2
+ @test Ps.distancetoedge((1,1), model) == 40m
+ @test Ps.distancetoedge((4,4), model) == 10m
+ @test Ps.distancetoedge((6,6), model) == 20m
end
@testset "Weather initialisation" begin
diff --git a/test/nature_tests.jl b/test/nature_tests.jl
index da1c81cbfc8ddc03fdb7e220188aaae7d800cfc8..5d84ac9400fb894ed5d2fff4778763a5d34f15df 100644
--- a/test/nature_tests.jl
+++ b/test/nature_tests.jl
@@ -57,11 +57,11 @@ end) # end eval
# create a set of habitat descriptors
h1 = @habitat(@landcover() == Ps.water)
h2 = @habitat(@cropname() == "winter wheat" &&
- @cropheight() < 2)
- h3 = @habitat(@distanceto(Ps.water) > 2 &&
- @distancetoedge() <= 2)
+ @cropheight() < 2) #XXX randomly chosen value
+ h3 = @habitat(@distanceto(Ps.water) > 20m &&
+ @distancetoedge() <= 20m)
#FIXME nested macros don't work properly, counting seems wrong
- h4 = @habitat(@countanimals(radius=1) == 1)
+ h4 = @habitat(@countanimals(radius=10m) == 1)
# test the descriptors
@test h1((6,4), model) == true
@test h1((5,4), model) == false
@@ -94,12 +94,12 @@ end
# initialisation parameters, set 3
initparams3 = Ps.PopInitParams(birthphase = Ps.life, initphase = Ps.life, pairs = true,
habitat = @habitat(@landcover() == Ps.grass))
- @test_logs((:warn, "initpopulation!() called with popsize and popdensity both <= 0"),
+ @test_logs((:warn, "initpopulation!() called with popsize and indarea both <= 0"),
(:info, "Initialised 36 Mermaids."),
Ps.initpopulation!(Ps.Mermaid, initparams3, model))
- @test Ps.countanimals((2,2), model, radius=2) == Ps.countanimals((5,3), model, radius=1) == 0
+ @test Ps.countanimals((2,2), model, radius=20m) == Ps.countanimals((5,3), model, radius=10m) == 0
@test Ps.countanimals((5,5), model) == Ps.countanimals((6,6), model) == 2
- a1, a2 = Ps.nearby_animals((6,6), model, radius=0)
+ a1, a2 = Ps.nearby_animals((6,6), model, radius=0m)
@test a1.sex != a2.sex
Ps.killallanimals!(model)
# initialisation parameters, set 4
@@ -109,7 +109,7 @@ end
@test_logs((:warn, "There are not enough suitable locations for Mermaid in the landscape."),
(:info, "Initialised 5 Mermaids."),
Ps.initpopulation!(Ps.Mermaid, initparams4, model))
- @test Ps.countanimals((1,1), model, radius=4) == 0
+ @test Ps.countanimals((1,1), model, radius=40m) == 0
@test Ps.countanimals((6,4), model) == 5
end
@@ -124,11 +124,11 @@ end
@test_logs((:debug, "Created Mermaid 1."), min_level=Logging.Debug,
Ps.create!(mermaid, Ps.withtestlogger(model)))
# test population initialisation
- @test_logs((:warn, "initpopulation!() called with popsize and popdensity both <= 0"),
+ @test_logs((:warn, "initpopulation!() called with popsize and indarea both <= 0"),
(:info, "Initialised 2 Mermaids."),
Ps.initpopulation!("Mermaid", model))
@test Ps.nagents(model) == 2
- @test Ps.countanimals((1,1), model, radius=4) == 0
+ @test Ps.countanimals((1,1), model, radius=40m) == 0
@test Ps.countanimals(pond, model) == 2
@test model.animals[1].age == 0
# test event handling
@@ -226,6 +226,8 @@ end
@testset "Skylark submodel" begin
# set up a modified test landscape
model = inittestmodel()
+ #FIXME the tests here fail if @distancetoedge >= 50m in `skylarkhabitat`,
+ # as no individuals are initialised
for x in 1:6
for y in 5:6
model.landscape[x,y] = Pixel(Ps.agriculture, missing, [], [])
diff --git a/test/runtests.jl b/test/runtests.jl
index 8540f05b24689f69b43ef6a28169b1e4a2b68e34..6bf31e2bf18b1c8bfb4e10cc0fd00a755f347461 100644
--- a/test/runtests.jl
+++ b/test/runtests.jl
@@ -20,6 +20,10 @@ const Ps = Persefone
const TESTPARAMETERS = joinpath(pkgdir(Persefone), "test/test_parameters.toml")
const TESTSETTINGS = Ps.getsettings(TESTPARAMETERS)
+import Unitful: cm, m, km, ha, Length, Area
+const m² = m^2
+const km² = km^2
+
"""
inittestmodel(smallmap=true)
diff --git a/test/test_parameters.toml b/test/test_parameters.toml
index 33413f85989fe7c08935a3c87020d09cb005167b..4d88eb3bf0deeee889c106ce4ff90329e1706a89 100644
--- a/test/test_parameters.toml
+++ b/test/test_parameters.toml
@@ -21,7 +21,8 @@ startdate = 2022-02-01
enddate = 2022-03-31
[world]
-mapdirectory = "."
+mapdirectory = "." # the directory in which all geographic data are stored
+mapresolution = 10 # map resolution in meters
landcovermap = "landcover_jena.tif" # location of the landcover map
farmfieldsmap = "fields_jena.tif" # location of the field geometry map
weatherfile = "weather_jena.csv" # location of the weather data file
@@ -30,7 +31,8 @@ weatherfile = "weather_jena.csv" # location of the weather data file
farmmodel = "FieldManager" # which version of the farm model to use (not yet implemented)
[nature]
-targetspecies = ["Wolpertinger", "Wyvern"] # list of target species to simulate
+targetspecies = ["Wolpertinger", "Wyvern"] # list of target species to simulate - example species
+#targetspecies = ["Skylark"] # list of target species to simulate
popoutfreq = "daily" # output frequency population-level data, daily/monthly/yearly/end/never
indoutfreq = "daily" # output frequency individual-level data, daily/monthly/yearly/end/never
insectmodel = ["season", "habitat", "pesticides"] # which factors affect insect growth ("weather" is not yet implemented)