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Added line to rabbit_fox_hawk.jl to make animation run and fix #1118 #1126

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Jan 18, 2025
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Added line to rabbit_fox_hawk.jl to make animation run and fix #1118 #1126

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207c37c
Added line to rabbit_fox_hawk.jl to make animation run and fix #1118
fieldofnodes Jan 18, 2025
dd04e98
Update Project.toml
Datseris Jan 18, 2025
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2 changes: 1 addition & 1 deletion Project.toml
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Original file line number Diff line number Diff line change
@@ -1,7 +1,7 @@
name = "Agents"
uuid = "46ada45e-f475-11e8-01d0-f70cc89e6671"
authors = ["George Datseris", "Tim DuBois", "Aayush Sabharwal", "Ali Vahdati", "Adriano Meligrana"]
version = "6.2.1"
version = "6.2.2"

[deps]
CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
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108 changes: 54 additions & 54 deletions examples/rabbit_fox_hawk.jl
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Expand Up @@ -61,29 +61,29 @@ const v0 = (0.0, 0.0, 0.0) # we don't use the velocity field here
# with the specified heightmap and containing the specified number of rabbits, foxes and hawks.

function initialize_model(
heightmap_url =
heightmap_url=
"https://raw.githubusercontent.com/JuliaDynamics/" *
"JuliaDynamics/master/videos/agents/rabbit_fox_hawk_heightmap.png",
water_level = 8,
grass_level = 20,
mountain_level = 35;
n_rabbits = 160, ## initial number of rabbits
n_foxes = 30, ## initial number of foxes
n_hawks = 30, ## initial number of hawks
Δe_grass = 25, ## energy gained from eating grass
Δe_rabbit = 30, ## energy gained from eating one rabbit
rabbit_repr = 0.06, ## probability for a rabbit to (asexually) reproduce at any step
fox_repr = 0.03, ## probability for a fox to (asexually) reproduce at any step
hawk_repr = 0.02, ## probability for a hawk to (asexually) reproduce at any step
rabbit_vision = 6, ## how far rabbits can see grass and spot predators
fox_vision = 10, ## how far foxes can see rabbits to hunt
hawk_vision = 15, ## how far hawks can see rabbits to hunt
rabbit_speed = 1.3, ## movement speed of rabbits
fox_speed = 1.1, ## movement speed of foxes
hawk_speed = 1.2, ## movement speed of hawks
regrowth_chance = 0.03, ## probability that a patch of grass regrows at any step
dt = 0.1, ## discrete timestep each iteration of the model
seed = 42, ## seed for random number generator
water_level=8,
grass_level=20,
mountain_level=35;
n_rabbits=160, ## initial number of rabbits
n_foxes=30, ## initial number of foxes
n_hawks=30, ## initial number of hawks
Δe_grass=25, ## energy gained from eating grass
Δe_rabbit=30, ## energy gained from eating one rabbit
rabbit_repr=0.06, ## probability for a rabbit to (asexually) reproduce at any step
fox_repr=0.03, ## probability for a fox to (asexually) reproduce at any step
hawk_repr=0.02, ## probability for a hawk to (asexually) reproduce at any step
rabbit_vision=6, ## how far rabbits can see grass and spot predators
fox_vision=10, ## how far foxes can see rabbits to hunt
hawk_vision=15, ## how far hawks can see rabbits to hunt
rabbit_speed=1.3, ## movement speed of rabbits
fox_speed=1.1, ## movement speed of foxes
hawk_speed=1.2, ## movement speed of hawks
regrowth_chance=0.03, ## probability that a patch of grass regrows at any step
dt=0.1, ## discrete timestep each iteration of the model
seed=42, ## seed for random number generator
)

## Download and load the heightmap. The grayscale value is converted to `Float64` and
Expand Down Expand Up @@ -111,7 +111,7 @@ function initialize_model(

## Note that the dimensions of the space do not have to correspond to the dimensions
## of the pathfinder. Discretisation is handled by the pathfinding methods
space = ContinuousSpace((100., 100., 50.); periodic = false)
space = ContinuousSpace((100.0, 100.0, 50.0); periodic=false)

## Generate an array of random numbers, and threshold it by the probability of grass growing
## at that location. Although this causes grass to grow below `water_level`, it is
Expand All @@ -121,30 +121,30 @@ function initialize_model(
)
properties = (
## The pathfinder for rabbits and foxes
landfinder = AStar(space; walkmap = land_walkmap),
landfinder=AStar(space; walkmap=land_walkmap),
## The pathfinder for hawks
airfinder = AStar(space; walkmap = air_walkmap, cost_metric = MaxDistance{3}()),
Δe_grass = Δe_grass,
Δe_rabbit = Δe_rabbit,
rabbit_repr = rabbit_repr,
fox_repr = fox_repr,
hawk_repr = hawk_repr,
rabbit_vision = rabbit_vision,
fox_vision = fox_vision,
hawk_vision = hawk_vision,
rabbit_speed = rabbit_speed,
fox_speed = fox_speed,
hawk_speed = hawk_speed,
heightmap = heightmap,
grass = grass,
regrowth_chance = regrowth_chance,
water_level = water_level,
grass_level = grass_level,
dt = dt,
airfinder=AStar(space; walkmap=air_walkmap, cost_metric=MaxDistance{3}()),
Δe_grass=Δe_grass,
Δe_rabbit=Δe_rabbit,
rabbit_repr=rabbit_repr,
fox_repr=fox_repr,
hawk_repr=hawk_repr,
rabbit_vision=rabbit_vision,
fox_vision=fox_vision,
hawk_vision=hawk_vision,
rabbit_speed=rabbit_speed,
fox_speed=fox_speed,
hawk_speed=hawk_speed,
heightmap=heightmap,
grass=grass,
regrowth_chance=regrowth_chance,
water_level=water_level,
grass_level=grass_level,
dt=dt,
)

model = StandardABM(Animal, space; agent_step! = animal_step!,
model_step! = model_step!, rng, properties)
model = StandardABM(Animal, space; (agent_step!)=animal_step!,
(model_step!)=model_step!, rng, properties)

## spawn each animal at a random walkable position according to its pathfinder
for _ in 1:n_rabbits
Expand Down Expand Up @@ -199,32 +199,32 @@ function animal_step!(rabbit, model, ::Rabbit)
## Get a list of positions of all nearby predators
predators = [
x.pos for x in nearby_agents(rabbit, model, model.rabbit_vision) if
variant(x) isa Fox || variant(x) isa Hawk
]
variant(x) isa Fox || variant(x) isa Hawk
]
## If the rabbit sees a predator and isn't already moving somewhere
if !isempty(predators) && is_stationary(rabbit, model.landfinder)
## Try and get an ideal direction away from predators
direction = (0., 0., 0.)
direction = (0.0, 0.0, 0.0)
for predator in predators
## Get the direction away from the predator
away_direction = (rabbit.pos .- predator)
## In case there is already a predator at our location, moving anywhere is
## moving away from it, so it doesn't contribute to `direction`
all(away_direction .≈ 0.) && continue
all(away_direction .≈ 0.0) && continue
## Add this to the overall direction, scaling inversely with distance.
## As a result, closer predators contribute more to the direction to move in
direction = direction .+ away_direction ./ eunorm(away_direction) ^ 2
direction = direction .+ away_direction ./ eunorm(away_direction)^2
end
## If the only predator is right on top of the rabbit
if all(direction .≈ 0.)
if all(direction .≈ 0.0)
## Move anywhere
chosen_position = random_walkable(rabbit.pos, model, model.landfinder, model.rabbit_vision)
else
## Normalize the resultant direction, and get the ideal position to move it
direction = direction ./ eunorm(direction)
## Move to a random position in the general direction of away from predators
position = rabbit.pos .+ direction .* (model.rabbit_vision / 2.)
chosen_position = random_walkable(position, model, model.landfinder, model.rabbit_vision / 2.)
position = rabbit.pos .+ direction .* (model.rabbit_vision / 2.0)
chosen_position = random_walkable(position, model, model.landfinder, model.rabbit_vision / 2.0)
end
plan_route!(rabbit, chosen_position, model.landfinder)
end
Expand Down Expand Up @@ -300,7 +300,7 @@ function animal_step!(hawk, model, ::Hawk)
remove_agent!(rand(abmrng(model), food), model, model.airfinder)
hawk.energy += model.Δe_rabbit
## Fly back up
plan_route!(hawk, hawk.pos .+ (0., 0., 7.), model.airfinder)
plan_route!(hawk, hawk.pos .+ (0.0, 0.0, 7.0), model.airfinder)
end

## The rest of the stepping function is similar to that of foxes, except hawks use a
Expand Down Expand Up @@ -366,7 +366,7 @@ model = initialize_model()
#
# using GLMakie # CairoMakie doesn't do 3D plots well
# ```

animalcolor(animal) = animalcolor(animal, variant(animal))
animalcolor(a::Rabbit) = :brown
animalcolor(a::Fox) = :orange
animalcolor(a::Hawk) = :blue
Expand All @@ -381,7 +381,7 @@ function Agents.static_preplot!(ax::Axis3, p::ABMPlot)
(100/205):(100/205):100,
(100/205):(100/205):100,
p.abmobs[].model[].heightmap;
colormap = :terrain
colormap=:terrain
)
end

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