def set_bad_names(self):
self.bad_names = [""]
if config.data_config is not None:
data_col = config.get_datafile().get_data_header()
labels, _ = config.get_labels_info()
functions = config.get_functions()
self.bad_names += data_col + labels + functions
def update_functions(self):
self.remove_function.clear()
for i, func in enumerate(config.get_functions()):
func_entry = self.remove_function.addAction(func)
func_entry.triggered.connect(
make_caller(self.open_function_removal, i))
def get_function_columns(self):
functions = config.get_functions()
func_col = []
for i, key in enumerate(self.df):
if key in functions:
func_col.append(i)
return func_col
def get_original_columns(self):
functions = config.get_functions()
orig_col = []
for i, key in enumerate(self.df):
if key not in functions:
orig_col.append(i)
return orig_col
print("gene{0}: {1}".format(i, node.getData()))
def write_result(self, path):
wd = open(path, 'w')
for ind in self.p:
wd.write("fitness: {0}\n".format(ind.getFitness()))
wd.write("registers: {0}\n".format(ind.getRegisters()))
for i, node in enumerate(ind.getGene()):
wd.write("gene{0}: {1}\n".format(i, node.getData()))
if __name__ == "__main__":
from config import get_functions, get_registers, get_constants
print("..set up functions")
inputs = [[0, 0], [0, 1], [1, 0], [1, 1]]
func = get_functions()
print("..Done!")
print("..create Population")
ppl = Population()
ppl.show()
print("..Done!")
print("..create Population")
constants = get_constants(bit=True)
n_register = 10
ppl.createPopulation(functions=func,
constants=constants,
n_ind=5,
n_gene=5,
n_register=n_register)
# config
gc.enable()
inputs = [[0, 0], [0, 1], [1, 0], [1, 1]]
revolution = 300
n_register = 3
n_ind = 50
n_gene = 10
elite_size = 3
tourn_size = 3
cross_rate = 0.7
mutate_rate = 0.5
path = "./result/result.txt"
# init
ppl = Population()
functions = get_functions()
constants = get_constants(lower=-10, upper=10, bit=True)
ppl.createPopulation(functions=functions,
constants=constants,
n_ind=n_ind,
n_gene=n_gene,
n_register=n_register)
eval_function = lambda x: x[0] ^ x[1] # xor
ppl.excute_all(inputs, eval_function)
# revolution
p = ProgressBar(0, revolution)
for i in range(revolution):
#print("revolution: ", i)
p.update(i + 1)
elite = Selection.elite(ppl, elite_size)
