def fitness_function(bin_string):
from expression import eval_bin_string
val = eval_bin_string(bin_string)
if val == required_int:
ret = float("inf")
else:
ret = 1 / abs(float(val - required_int))
return ret
def fitness_function(bin_string):
from expression import eval_bin_string
val = eval_bin_string(bin_string)
if val == required_int:
ret = float("inf")
else:
ret = 1 / abs(float(val - required_int))
return ret
#! /usr/bin/env python
def fitness_function(bin_string):
from expression import eval_bin_string
val = eval_bin_string(bin_string)
if val == required_int:
ret = float("inf")
else:
ret = 1 / abs(float(val - required_int))
return ret
if __name__ == '__main__':
import genetic
from expression import eval_bin_string, conv_to_expression
global required_int
required_int = int(raw_input('Input integer: '))
genetic.initialize(50, 4, 100, fitness_function, 0.7, 0.001)
while True:
fittest = genetic.get_fittest(5)
print "Most fittest:",
for v in fittest:
print eval_bin_string(v),
print
if eval_bin_string(fittest[0]) == required_int:
break
genetic.next_generation()
print "Found expression: %s" % conv_to_expression(genetic.get_fittest(1)[0])
#! /usr/bin/env python
def fitness_function(bin_string):
from expression import eval_bin_string
val = eval_bin_string(bin_string)
if val == required_int:
ret = float("inf")
else:
ret = 1 / abs(float(val - required_int))
return ret
if __name__ == '__main__':
import genetic
from expression import eval_bin_string, conv_to_expression
global required_int
required_int = int(raw_input('Input integer: '))
genetic.initialize(50, 4, 100, fitness_function, 0.7, 0.001)
while True:
fittest = genetic.get_fittest(5)
print "Most fittest:",
for v in fittest:
print eval_bin_string(v),
print
if eval_bin_string(fittest[0]) == required_int:
break
genetic.next_generation()
print "Found expression: %s" % conv_to_expression(
genetic.get_fittest(1)[0])
