SCJ-PredatorPrey/main.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Install and use environment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import Pkg\n",
    "Pkg.activate(\"./env\")\n",
    "Pkg.instantiate()\n",
    "include(\"./predator_prey_generic.jl\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Setup for GLMakie"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "using GLMakie\n",
    "GLMakie.activate!()\n",
    "# To view our starting population, we can build an overview plot using [`abmplot`](@ref).\n",
    "# We define the plotting details for the wolves and sheep:\n",
    "ashape(a) = a.def.symbol\n",
    "acolor(a) = a.def.color\n",
    "\n",
    "# and instruct [`abmplot`](@ref) how to plot grass as a heatmap:\n",
    "grasscolor(model) = model.growth ./ model.regrowth_time\n",
    "# and finally define a colormap for the grass:\n",
    "heatkwargs = (colormap = [:brown, :green], colorrange = (0, 1))\n",
    "\n",
    "# and put everything together and give it to [`abmplot`](@ref)\n",
    "return plotkwargs = (;\n",
    "    agent_color = acolor,\n",
    "    agent_size = 25,\n",
    "    agent_marker = ashape,\n",
    "    agentsplotkwargs = (strokewidth = 1.0, strokecolor = :black),\n",
    "    heatarray = grasscolor,\n",
    "    heatkwargs = heatkwargs,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Select scenario by executing the corresponding cell. Then run the model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Scenario 1\n",
    "This has similar functionality to the original model, where animals walk randomly and reproduce by chance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "events = []\n",
    "animal_defs = [\n",
    "AnimalDefinition(30,'●',RGBAf(1.0, 1.0, 1.0, 1),0, 0, 1, 0.3, 20, 0, \"Sheep\", [\"Wolf\",\"Bear\"], [\"Grass\"])\n",
    "AnimalDefinition(3,'▲',RGBAf(0.2, 0.2, 0.3, 1),0, 0, 1, 0.07, 20, 0, \"Wolf\", [], [\"Sheep\"])\n",
    "]\n",
    "stable_params = (;\n",
    "    events = events,\n",
    "    animal_defs = animal_defs,\n",
    "    dims = (30, 30),\n",
    "    regrowth_time = 30,\n",
    "    Δenergy_grass = 6,\n",
    "    seed = 71758,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Scenario 2\n",
    "This uses score based movement logic and animals only reproduce when they have enough energy.\n",
    "This model is more stable. Less prey starves and a similar oscillation to the Lotka-Voltera equations emerges."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "events = []\n",
    "animal_defs = [\n",
    "AnimalDefinition(30,'●',RGBAf(1.0, 1.0, 1.0, 1),20, 20, 1, 0.3, 20, 3, \"Sheep\", [\"Wolf\",\"Bear\"], [\"Grass\"])\n",
    "AnimalDefinition(3,'▲',RGBAf(0.2, 0.2, 0.3, 1),20, 20, 1, 0.07, 20, 1, \"Wolf\", [], [\"Sheep\"])\n",
    "]\n",
    "stable_params = (;\n",
    "    events = events,\n",
    "    animal_defs = animal_defs,\n",
    "    dims = (30, 30),\n",
    "    regrowth_time = 30,\n",
    "    Δenergy_grass = 6,\n",
    "    seed = 71758,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Scenario 3\n",
    "This tries to simulate the effects of droughts and floods"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "events = RecurringEvent[\n",
    "RecurringEvent(\"Drought\", 30, 40, 100, 124, 240, 0)\n",
    "RecurringEvent(\"Flood\", 0.4, 0, 20, 20, 120, 0)\n",
    "] # -> extreme Populationsschwankungen, Räuber stirbt aus (t=433) und System kollabiert\n",
    "animal_defs = [\n",
    "AnimalDefinition(30,'●',RGBAf(1.0, 1.0, 1.0, 1),20, 20, 1, 0.3, 20, 3, \"Sheep\", [\"Wolf\",\"Bear\"], [\"Grass\"])\n",
    "AnimalDefinition(3,'▲',RGBAf(0.2, 0.2, 0.3, 1),20, 20, 1, 0.07, 20, 1, \"Wolf\", [], [\"Sheep\"])\n",
    "]\n",
    "stable_params = (;\n",
    "    events = events,\n",
    "    animal_defs = animal_defs,\n",
    "    dims = (30, 30),\n",
    "    regrowth_time = 30,\n",
    "    Δenergy_grass = 6,\n",
    "    seed = 71758,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Scenario 4\n",
    "This tries to simulate winter seasons."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "events = RecurringEvent[\n",
    "RecurringEvent(\"Winter\", 0, 0, 18, 24, 24, 0)\n",
    "RecurringEvent(\"PreyReproduceSeasonal\", 0.5, 0.1, 1, 7, 24, 0)\n",
    "RecurringEvent(\"PredatorReproduceSeasonal\", 0.1, 0.04, 6, 12, 24, 0)\n",
    "] # -> geringere max. Population, dafür weniger starke Schwankung.\n",
    "animal_defs = [\n",
    "AnimalDefinition(30,'●',RGBAf(1.0, 1.0, 1.0, 1),20, 20, 1, 0.3, 20, 3, \"Sheep\", [\"Wolf\",\"Bear\"], [\"Grass\"])\n",
    "AnimalDefinition(3,'▲',RGBAf(0.2, 0.2, 0.3, 1),20, 20, 1, 0.07, 20, 1, \"Wolf\", [], [\"Sheep\"])\n",
    "]\n",
    "stable_params = (;\n",
    "    events = events,\n",
    "    animal_defs = animal_defs,\n",
    "    dims = (30, 30),\n",
    "    regrowth_time = 30,\n",
    "    Δenergy_grass = 6,\n",
    "    seed = 71758,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Scenario 5\n",
    "This tries to simulate droughts and floods with winter seasons"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "events = RecurringEvent[\n",
    "RecurringEvent(\"Drought\", 30, 40, 100, 124, 240, 0)\n",
    "RecurringEvent(\"Flood\", 0.4, 0, 25, 25, 120, 0)\n",
    "RecurringEvent(\"Winter\", 0, 0, 18, 24, 24, 0)\n",
    "RecurringEvent(\"PreyReproduceSeasonal\", 0.5, 0.1, 1, 7, 24, 0)\n",
    "RecurringEvent(\"PredatorReproduceSeasonal\", 0.1, 0.05, 6, 12, 24, 0)\n",
    "] # -> starke Schwankung durch, allerdings bleibt das System stabil\n",
    "animal_defs = [\n",
    "AnimalDefinition(30,'●',RGBAf(1.0, 1.0, 1.0, 1),20, 2000, 1, 0.3, 20, 3, \"Sheep\", [\"Wolf\",\"Bear\"], [\"Grass\"])\n",
    "AnimalDefinition(3,'▲',RGBAf(0.2, 0.2, 0.3, 1),20, 2000, 1, 0.07, 20, 1, \"Wolf\", [], [\"Sheep\"])\n",
    "]\n",
    "stable_params = (;\n",
    "    events = events,\n",
    "    animal_defs = animal_defs,\n",
    "    dims = (30, 30),\n",
    "    regrowth_time = 30,\n",
    "    Δenergy_grass = 6,\n",
    "    seed = 71758,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Run the Model interactive"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [],
   "source": [
    "# GLMakie Parameters\n",
    "model_params_ranges = Dict(\n",
    "    :regrowth_time => 0:1:100,\n",
    "    :Δenergy_grass => 0:1:50,\n",
    ")\n",
    "animal_params_ranges = generate_animal_parameter_ranges(animal_defs)\n",
    "params = merge(model_params_ranges,animal_params_ranges)\n",
    "\n",
    "# Data Collection\n",
    "sheep(a) = a.def.type == \"Sheep\"\n",
    "wolf(a) = a.def.type == \"Wolf\"\n",
    "eaten(a) = a.def.type == \"Sheep\" && a.death_cause == Predation\n",
    "starved(a) = a.def.type == \"Sheep\" && a.death_cause == Starvation\n",
    "count_grass(model) = count(model.fully_grown)\n",
    "adata = [(sheep, count), (wolf, count), (eaten, count), (starved, count)]\n",
    "mdata = [count_grass]\n",
    "\n",
    "# initialize and run\n",
    "model = initialize_model(;stable_params...)\n",
    "fig, abmobs = abmexploration(\n",
    "    model;\n",
    "    params,\n",
    "    plotkwargs...,\n",
    "    adata,\n",
    "    alabels = [\"Sheep\", \"Wolf\", \"Eaten\", \"Starved\"],\n",
    "    mdata, mlabels = [\"Grass\"]\n",
    ")\n",
    "fig"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Just run and plot the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "steps = 2000\n",
    "\n",
    "# GLMakie Parameters\n",
    "model_params_ranges = Dict(\n",
    "    :regrowth_time => 0:1:100,\n",
    "    :Δenergy_grass => 0:1:50,\n",
    ")\n",
    "animal_params_ranges = generate_animal_parameter_ranges(animal_defs)\n",
    "params = merge(model_params_ranges,animal_params_ranges)\n",
    "\n",
    "# Data Collection\n",
    "sheep(a) = a.def.type == \"Sheep\"\n",
    "wolf(a) = a.def.type == \"Wolf\"\n",
    "eaten(a) = a.def.type == \"Sheep\" && a.death_cause == Predation\n",
    "starved(a) = a.def.type == \"Sheep\" && a.death_cause == Starvation\n",
    "count_grass(model) = count(model.fully_grown)\n",
    "adata = [(sheep, count), (wolf, count), (eaten, count), (starved, count)]\n",
    "mdata = [count_grass]\n",
    "\n",
    "# initialize and run\n",
    "model = initialize_model(;stable_params...)\n",
    "df1,df2 = run!(model, steps; adata, mdata)\n",
    "\n",
    "using DataFrames, Plots\n",
    "\n",
    "fig = Plots.plot(layout = (2, 1), size = (800, 600), legend = true)\n",
    "Plots.plot!(fig[1], df1.time, df1.count_sheep, label = \"Sheep\", linewidth = 1)\n",
    "Plots.plot!(fig[1], df1.time, df1.count_wolf, label = \"Wolf\", linewidth = 1)\n",
    "Plots.plot!(fig[1], df2.time, df2.count_grass, label = \"Grass\", linewidth = 1)\n",
    "Plots.plot!(fig[2], df1.time, df1.count_eaten, label = \"Eaten\", linewidth = 1)\n",
    "Plots.plot!(fig[2], df1.time, df1.count_starved, label = \"Starved\", linewidth = 1)\n",
    "\n",
    "Plots.title!(fig[1], \"Population Dynamics\")\n",
    "Plots.xlabel!(fig[1], \"Time\")\n",
    "Plots.ylabel!(fig[1], \"Count\")\n",
    "Plots.title!(fig[2], \"Death Cause\")\n",
    "Plots.xlabel!(fig[2], \"Time\")\n",
    "Plots.ylabel!(fig[2], \"Count\")\n",
    "display(fig)"
   ]
  }
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