69 lines
2.0 KiB
Julia
69 lines
2.0 KiB
Julia
import Pkg
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Pkg.activate("./env")
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Pkg.instantiate()
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include("./predator_prey_generic.jl")
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using GLMakie
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GLMakie.activate!()
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# To view our starting population, we can build an overview plot using [`abmplot`](@ref).
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# We define the plotting details for the wolves and sheep:
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ashape(a) = a.def.symbol
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acolor(a) = a.def.color
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# and instruct [`abmplot`](@ref) how to plot grass as a heatmap:
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grasscolor(model) = model.growth ./ model.regrowth_time
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# and finally define a colormap for the grass:
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heatkwargs = (colormap = [:brown, :green], colorrange = (0, 1))
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# and put everything together and give it to [`abmplot`](@ref)
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return plotkwargs = (;
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agent_color = acolor,
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agent_size = 25,
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agent_marker = ashape,
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agentsplotkwargs = (strokewidth = 1.0, strokecolor = :black),
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heatarray = grasscolor,
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heatkwargs = heatkwargs,
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)
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events = []
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animal_defs = [
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AnimalDefinition(30,'●',RGBAf(1.0, 1.0, 1.0, 1),20, 20, 1, 0.3, 20, 3, "Sheep", ["Wolf","Bear"], ["Grass"])
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AnimalDefinition(3,'▲',RGBAf(0.2, 0.2, 0.3, 1),20, 20, 1, 0.07, 20, 1, "Wolf", [], ["Sheep"])
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]
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stable_params = (;
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events = events,
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animal_defs = animal_defs,
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dims = (30, 30),
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regrowth_time = 30,
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Δenergy_grass = 6,
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seed = 71758,
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)
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# GLMakie Parameters
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model_params_ranges = Dict(
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:regrowth_time => 0:1:100,
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:Δenergy_grass => 0:1:50,
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)
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animal_params_ranges = generate_animal_parameter_ranges(animal_defs)
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params = merge(model_params_ranges,animal_params_ranges)
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# Data Collection
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sheep(a) = a.def.type == "Sheep"
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wolf(a) = a.def.type == "Wolf"
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eaten(a) = a.def.type == "Sheep" && a.death_cause == Predation
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starved(a) = a.def.type == "Sheep" && a.death_cause == Starvation
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count_grass(model) = count(model.fully_grown)
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adata = [(sheep, count), (wolf, count), (eaten, count), (starved, count)]
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mdata = [count_grass]
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# initialize and run
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model = initialize_model(;stable_params...)
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fig, abmobs = abmexploration(
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model;
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params,
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plotkwargs...,
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adata,
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alabels = ["Sheep", "Wolf", "Eaten", "Starved"],
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mdata, mlabels = ["Grass"]
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)
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wait(display(fig)) |