195 lines
6.3 KiB
Plaintext
195 lines
6.3 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"import Pkg\n",
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"Pkg.activate(\"./env\")\n",
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"Pkg.instantiate()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"(agent_color = acolor, agent_size = 25, agent_marker = ashape, offset = offset, agentsplotkwargs = (strokewidth = 1.0, strokecolor = :black), heatarray = grasscolor, heatkwargs = (colormap = [:brown, :green], colorrange = (0, 1)))"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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"# To view our starting population, we can build an overview plot using [`abmplot`](@ref).\n",
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"# We define the plotting details for the wolves and sheep:\n",
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"offset(a) = a isa Sheep ? (-0.1, -0.1*rand()) : (+0.1, +0.1*rand())\n",
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"ashape(a) = a isa Sheep ? :circle : :utriangle\n",
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"acolor(a) = a isa Sheep ? RGBAf(1.0, 1.0, 1.0, 0.8) : RGBAf(0.2, 0.2, 0.3, 0.8)\n",
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"\n",
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"# and instruct [`abmplot`](@ref) how to plot grass as a heatmap:\n",
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"grasscolor(model) = model.countdown ./ model.regrowth_time\n",
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"# and finally define a colormap for the grass:\n",
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"heatkwargs = (colormap = [:brown, :green], colorrange = (0, 1))\n",
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"\n",
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"# and put everything together and give it to [`abmplot`](@ref)\n",
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"plotkwargs = (;\n",
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" agent_color = acolor,\n",
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" agent_size = 25,\n",
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" agent_marker = ashape,\n",
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" offset,\n",
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" agentsplotkwargs = (strokewidth = 1.0, strokecolor = :black),\n",
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" heatarray = grasscolor,\n",
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" heatkwargs = heatkwargs,\n",
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")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {},
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"outputs": [],
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"source": [
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"include(\"./predator_prey.jl\")\n",
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"Pkg.status([\"Agents\",\"GLMakie\"]; mode = Pkg.Types.PKGMODE_MANIFEST, io=stdout)\n",
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"using GLMakie\n",
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"GLMakie.activate!()\n",
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"\n",
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"# Event(name, value, pre_value, t_start, t_end, t_cycle, timerstart)\n",
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"events = RecurringEvent[]\n",
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"#push!(events, RecurringEvent(\"Drought\", 80, 30, 30, 50, 120, 1))\n",
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"#push!(events, RecurringEvent(\"Flood\", 50, 30, 70, 80, 120, 1))\n",
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"push!(events, RecurringEvent(\"PreyReproduceSeasonal\", 0.5, 0.1, 1, 4, 12, 1))\n",
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"push!(events, RecurringEvent(\"PredatorReproduceSeasonal\", 0.1, 0.07, 4, 6, 12, 1))\n",
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"\n",
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"stable_params = (;\n",
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" events = events,\n",
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" n_sheep = 30,\n",
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" n_wolves = 3,\n",
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" dims = (30, 30),\n",
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" regrowth_time = 30,\n",
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" Δenergy_sheep = 6,\n",
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" sheep_reproduce = 0.3,\n",
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" sheep_perception = 0,\n",
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" wolf_reproduce = 0.07,\n",
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" Δenergy_wolf = 20,\n",
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" wolf_perception = 0,\n",
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" seed = 71758,\n",
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")\n",
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"\n",
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"params = Dict(\n",
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" :regrowth_time => 0:1:100,\n",
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" :Δenergy_sheep => 0:1:50,\n",
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" :sheep_reproduce => 0:0.01:1,\n",
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" :sheep_perception => 0:1:8,\n",
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" :Δenergy_wolf => 0:1:50, \n",
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" :wolf_reproduce => 0:0.01:1, \n",
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" :wolf_perception => 0:1:8,\n",
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")\n",
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"\n",
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"sheep(a) = a isa Sheep\n",
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"wolf(a) = a isa Wolf\n",
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"count_grass(model) = count(model.fully_grown)\n",
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"adata = [(sheep, count), (wolf, count)]\n",
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"mdata = [count_grass]\n",
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"model = initialize_model(;stable_params...)\n",
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"fig, abmobs = abmexploration(\n",
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" model;\n",
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" params,\n",
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" plotkwargs...,\n",
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" adata,\n",
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" alabels = [\"Sheep\", \"Wolf\"],\n",
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" mdata, mlabels = [\"Grass\"]\n",
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")\n",
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"#, step! = (model) -> begin event_handler!(model, \"Dürre\") model.wolf_reproduce = 0.1 Agents.step!() end\n",
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"#fig, ax, abmobs = abmplot(model; add_controls=true, plotkwargs...)\n",
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"\n",
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"fig"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 143,
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"metadata": {},
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"outputs": [],
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"source": [
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"include(\"./predator_prey.jl\")\n",
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"\n",
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"using CairoMakie\n",
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"CairoMakie.activate!() # hide\n",
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"sheepwolfgrass = initialize_model(;stable_params...)\n",
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"\n",
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"abmvideo(\n",
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" \"sheepwolf.mp4\",\n",
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" sheepwolfgrass;\n",
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" frames = 2000,\n",
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" framerate = 8,\n",
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" title = \"Sheep Wolf Grass\",\n",
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" plotkwargs...,\n",
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")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 37,
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"metadata": {},
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"outputs": [],
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"source": [
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"\n",
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"sheepwolfgrass = initialize_model()\n",
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"\n",
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"fig, ax, abmobs = abmplot(sheepwolfgrass; plotkwargs...)\n",
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"fig\n",
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"\n",
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"# Now, lets run the simulation and collect some data. Define datacollection:\n",
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"sheep(a) = a isa Sheep\n",
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"wolf(a) = a isa Wolf\n",
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"count_grass(model) = count(model.fully_grown)\n",
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"# Run simulation:\n",
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"sheepwolfgrass = initialize_model()\n",
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"steps = 1000\n",
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"adata = [(sheep, count), (wolf, count)]\n",
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"mdata = [count_grass]\n",
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"adf, mdf = run!(sheepwolfgrass, steps; adata, mdata)\n",
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"\n",
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"# The following plot shows the population dynamics over time.\n",
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"# Initially, wolves become extinct because they consume the sheep too quickly.\n",
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"# The few remaining sheep reproduce and gradually reach an\n",
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"# equilibrium that can be supported by the amount of available grass.\n",
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"function plot_population_timeseries(adf, mdf)\n",
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" figure = Figure(size = (600, 400))\n",
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" ax = figure[1, 1] = Axis(figure; xlabel = \"Step\", ylabel = \"Population\")\n",
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" sheepl = lines!(ax, adf.time, adf.count_sheep, color = :cornsilk4)\n",
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" wolfl = lines!(ax, adf.time, adf.count_wolf, color = RGBAf(0.2, 0.2, 0.3))\n",
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" grassl = lines!(ax, mdf.time, mdf.count_grass, color = :green)\n",
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" figure[1, 2] = Legend(figure, [sheepl, wolfl, grassl], [\"Sheep\", \"Wolves\", \"Grass\"])\n",
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" figure\n",
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"end\n",
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"\n",
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"plot_population_timeseries(adf, mdf)\n"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Julia 1.10.2",
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"language": "julia",
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"name": "julia-1.10"
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},
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"language_info": {
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"file_extension": ".jl",
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"mimetype": "application/julia",
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"name": "julia",
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"version": "1.10.2"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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