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 )