from lordran import platform_selector as ps from lordran import sliding_puzzle_parallel as spp def random_pop_size( context , how_many , max_size_chromossome ): print '[random list generator]' return spp.RandomNumberList( context ).execute( ps.Execution.ASYNC , how_many , max_size_chromossome ) exit( 0 ) if __name__ == '__main__' : import time context = ps.get_intel_context() a = time.time() random_list = random_pop_size( context , 10 , 10 ) a = time.time() - a print '-->[ Finish at : ' , ( a / 60 ) , ']' print random_list
from lordran import platform_selector as ps from lordran import sliding_puzzle_parallel as spp def init_pop( context , random_list , puzzle ): return spp.InitialPopulationGeneratorEnhanced( context ).execute( ps.Execution.ASYNC , random_list , [ -1 , puzzle.move_top , 1 , puzzle.move_bot ] ) if __name__ == '__main__' : #~ puzzle = spp.Puzzle( range( 9 ) ) puzzle = spp.Puzzle( [1,0,2,3,4,5,6,7,8] ) context = ps.get_intel_context() import time # --- INITIAL POPULATION --- population , offset_list , max_chromossome_size = init_pop( context , range(1,10) , puzzle ) # --- FITNESS --- a = time.time() fitness_result_list , chromossome_list , chromossome_offset_list = spp.FitnessEnhanced( context ).execute( ps.Execution.ASYNC , population , offset_list , max_chromossome_size , puzzle ) # --- CROSSOVER --- print 'fitness_result_list:' , type( fitness_result_list ) print 'chromossome_list:' , type( chromossome_list )