from attribute import Attribute
from dataset import Dataset
from genetic import Population
attributes = [Attribute("score", list(range(-5,6))),]
data = [
[5],
[4],
[3],
[2],
[1],
[0],
[-1],
[-2],
[-3],
[-4],
[-5],
]
data = data * 10
scores = Population(Dataset(attributes, data), lambda i: 5 - abs(i[0]), rseed=1)
print(scores)
for i in range(100):
scores.generation()
print(scores)
print(scores.frequency())
from attribute import Attribute
from dataset import Dataset
from genetic import Population
attributes = [Attribute("score", [x/10 for x in range(-50, 50)]),]
data = [[x/10] for x in range(-50, 50)] * 5
scores = Population(Dataset(attributes, data), lambda i: -i[0]**4 + i[0]**3 + 20*i[0]**2 + i[0]-2)
print("using -x^4+x^3+20x^2+x-2\n")
print("initial",scores)
for i in range(1000):
scores.generation()
print("final",scores)
print("frequency", scores.frequency())
print("mode",scores.mode())
print("fittest",scores.fittest())