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Description
~/pypi_local/pygad/pygad.py in run(self)
1261 self.last_generation_fitness = self.cal_pop_fitness()
1262
-> 1263 best_solution, best_solution_fitness, best_match_idx = self.best_solution(pop_fitness=self.last_generation_fitness)
1264
1265 # Appending the best solution in the current generation to the best_solutions list.
~/pypi_local/pygad/pygad.py in best_solution(self, pop_fitness)
3115 pop_fitness = self.cal_pop_fitness()
3116 # Then return the index of that solution corresponding to the best fitness.
-> 3117 best_match_idx = numpy.where(pop_fitness == numpy.max(pop_fitness))[0][0]
3118
3119 best_solution = self.population[best_match_idx, :].copy()
IndexError: index 0 is out of bounds for axis 0 with size 0
This is how I have created my GA instance before run:
num_generations = 1500num_parents_mating = 20sol_per_pop = 50num_genes = num_customersgene_type = intinit_range_low = 0init_range_high = 6gene_space= np.arange(6)parent_selection_type = "sss"keep_parents = 20crossover_type = "single_point"mutation_type = "random"mutation_num_genes= [3, 1]mutation_probability = [0.25, 0.1]mutation_percent_genes = [20,10]# create an instance of the pygad.GA class global ga_instancega_instance = pygad.GA(num_generations=num_generations, fitness_func=fitness_func, num_parents_mating=4, gene_space = gene_space, sol_per_pop=50, num_genes=num_genes, gene_type = gene_type, mutation_type="adaptive", mutation_num_genes=(3, 1), save_solutions= True)ga_instance.run()