def run(fitness_fn_key, rep="bubble_down"):
fitness_fn = fitness.benchmarks(fitness_fn_key)
gp.set_fns_leaves(fitness_fn.arity)
variga.MINLEN = 100
variga.MAXLEN = 100
variga.PHENOTYPE_DISTANCE = gp.tree_distance
variga.FITNESS = fitness_fn
if rep == "bubble_down":
variga.GENERATE = generate_bubble_down_tree_and_fn
elif rep == "grow":
variga.GENERATE = generate_grow_tree_and_fn
else:
raise ValueError
variga.MAXIMISE = False
variga.SUCCESS = success
variga.POPSIZE = 1000
variga.GENERATIONS = 100
variga.PMUT = 0.01
variga.CROSSOVER_PROB = 0.7
variga.ELITE = 1
variga.TOURNAMENT_SIZE = 3
variga.WRAPS = 1
variga.main()
variga.MAXLEN = 100
variga.PHENOTYPE_DISTANCE = gp.tree_distance
# run the fitness function as normal to get individuals' semantics
variga.FITNESS = fitness_fn
# but overwrite the individuals' fitness values
variga.COEVOLUTIONARY_FITNESS = lambda pop: LCCB_coevo(fitness_fn, pop)
if rep == "bubble_down":
variga.GENERATE = lambda rng: generate_bubble_down_tree_and_fn_minn_maxn(10, 20, rng)
elif rep == "grow":
variga.GENERATE = generate_grow_tree_and_fn_maxd
else:
raise ValueError
variga.MAXIMISE = False
variga.SUCCESS = lambda x: False # FIXME
variga.POPSIZE = 50
variga.GENERATIONS = 20
variga.PMUT = 0.01
variga.CROSSOVER_PROB = 0.7
variga.ELITE = 1
variga.TOURNAMENT_SIZE = 3
variga.WRAPS = 1
variga.main()
if __name__ == "__main__":
srff = fitness.benchmarks("pagie-2d")
gp.set_fns_leaves(srff.arity)
# run(srff)
LCEB(srff, 10, 5, 2)
