103 lines
4.5 KiB
Julia
103 lines
4.5 KiB
Julia
import Pkg
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Pkg.activate("./env")
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using Distributed
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@everywhere include("./predator_prey_generic.jl")
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using BlackBoxOptim, Random
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using Statistics: mean, median
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using Serialization
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function load(file)
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fh = open(file, "r")
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optctrlb, res = deserialize(fh);
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close(fh)
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return (optctrlb, res)
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end
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function generator(x,n)
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models = []
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rng = MersenneTwister(71758)
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for i in 1:n
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animal_defs = [
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#AnimalDefinition(trunc(Int,x[8]),'●',RGBAf(1.0, 1.0, 1.0, 1),x[3], x[3], 1, x[1], x[3], trunc(Int,x[6]), "Sheep", ["Wolf","Bear"], ["Grass"])
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#AnimalDefinition(trunc(Int,x[9]),'▲',RGBAf(0.2, 0.2, 0.3, 1),x[4], x[4], 1, x[2], x[4], trunc(Int,x[7]), "Wolf", [], ["Sheep"])
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AnimalDefinition(trunc(Int,x[6]),'●',RGBAf(1.0, 1.0, 1.0, 1),0, 0, 1, x[1], x[3], 0, "Sheep", ["Wolf","Bear"], ["Grass"])
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AnimalDefinition(trunc(Int,x[7]),'▲',RGBAf(0.2, 0.2, 0.3, 1),0, 0, 1, x[2], x[4], 0, "Wolf", [], ["Sheep"])
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]
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stable_params = (;
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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 = x[5],
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#seed = 71758,
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)
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seed = rand(rng,1000:100000)
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push!(models,initialize_model(;seed,stable_params...))
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end
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return models
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end
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function cost(x)
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steps = 2000
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iterations = 10
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models = generator(x,iterations)
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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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df1,df2 = ensemblerun!(models, steps; adata, mdata, parallel=true, showprogress=true)
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println(x)
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fitness_scores = []
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for i in 1:iterations
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df = df1[df1.ensemble .== i,:]
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println(string(count(!iszero,df.count_sheep))*" "*string(count(!iszero,df.count_wolf)))
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score = count(iszero,df.count_sheep) + 2*count(iszero,df.count_wolf)
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push!(fitness_scores,score)
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end
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fitness = float(sum(fitness_scores))
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println(fitness)
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return fitness
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end
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#result = bboptimize(cost,SearchRange = [(0.0, 1.0),(0.0, 1.0),(0.0, 30.0),(0.0, 30.0),],NumDimensions = 4,MaxTime = 20,)
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SearchRange = [
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(0.01, 0.4),
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(0.01, 0.4),
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(5.0, 30.0),
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(5.0, 30.0),
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(5.0, 30.0),
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#(1, 3),
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#(1, 3),
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(3, 30),
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(3, 30),
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]
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optctrl = bbsetup(cost;SearchRange, MaxTime = 300, Method = :generating_set_search)#, TraceInterval=1.0, TraceMode=:verbose);
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#optctrl, res = load("SimpleModellOptimization900.tmp");
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res = bboptimize(optctrl)
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tempfilename = "./temp" * string(rand(1:Int(1e8))) * ".tmp"
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fh = open(tempfilename, "w")
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serialize(fh, (optctrl, res))
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close(fh)
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#Repro_Schaf, Repro_Wolf, Delta_Energie_Schaf, Delta_Energy_Wolf, Delta_Energy_Gras, n_Schafe, n_Wölfe
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#[0.26817737483789245, 0.027182763696826588, 14.440470034137558, 27.81279288508929, 15.785601397364756, 28.644469239080397, 13.471462703569484]
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#[0.11524114234251756, 0.07378121226251827, 29.31006871020899, 20.47494251025892, 5.915473514486612, 9.568612576389182, 22.299369669891565]
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# Schaf stirbt aus obwohl es mehr energy bekommt???
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#[0.11524114234251756, 0.07378121226251827, 29.31006871020899, 20.47494251025892, 12.155473514486612, 9.568612576389182, 22.299369669891565]
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#Wolf stirbt aus weil Schaf sich zu wenig reproduziert
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#[0.016950722103029812, 0.07378121226251827, 29.31006871020899, 20.47494251025892, 5.915473514486612, 9.568612576389182, 22.299369669891565]
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#Wolf stirbt aus, da er sich viel zu stark reproduziert
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#[0.11524114234251756, 0.25901432860274654, 29.31006871020899, 20.47494251025892, 5.915473514486612, 9.568612576389182, 22.299369669891565]
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#Aber hier plötzlich wieder einigermaßen stabil
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#[0.11524114234251756, 0.2477989358947258, 29.31006871020899, 20.47494251025892, 5.915473514486612, 9.568612576389182, 22.299369669891565]
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#Wolf stirbt weil zu wenig Schafe am Anfang
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#[0.11524114234251756, 0.07378121226251827, 29.31006871020899, 20.47494251025892, 5.915473514486612, 3.3286125763891814, 22.299369669891565]
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#Einigermaßen stabil, aber Schaf stirbt oft aus, weil zu hohe reproduktion
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#[0.39570778081524405, 0.07378121226251827, 29.31006871020899, 20.47494251025892, 5.915473514486612, 9.568612576389182, 22.299369669891565] |