[英]Genetic Programming pyeasyGA and Zelle graphics on Python
我想制作一個簡單的程序來提高我對這類編程的了解。 我發現了一個非常有用的庫,pyeasyGA,並且我嘗試使用graphics.py創建一個簡單的程序,從隨機生成的“pass”序列創建一個收斂到一個點的序列。
這就是它的工作原理:
def create_individual(data):
a = [(randint(0,5),randint(0,5)) for n in range(len(data))]
print(a)
return a
此函數創建一系列傳遞,因為graphics.py庫允許您通過為對象移動它想要移動它來移動對象。 那是我的“個人”。
為了計算健身,我使用了這個:
def fitness(individual, data):
totX=0
totY=0
for elem in individual:
totX+=elem[0]
totY+=elem[1]
tot = (totX,totY)
return distEuclidea(arrivo, tot)
def distEuclidea(p1,p2):
x1 = p1[0]
y1 = p1[1]
x2 = p2[0]
y2 = p2[1]
return ((x2-x1)**2+(y2-y1)**2)**(1/2)
此功能計算距所需到達點的距離。
在這些過程之后,程序會產生很多代,並且會使個體具有最低的適應度,但它不起作用。
它沒有發展。 每個傳遞序列似乎都是隨機生成的。
有人能幫助我嗎?
編輯:
該計划似乎有效。 唯一的問題是幾代人。
我發現你的健身功能最難理解。 而不是平均角落或找到中心,它將角落相加然后找到距離。 什么是幾何解釋?
此外,您的代碼是指ga.logGenerations,它不是當前pyeasyga 0.3.1版本的一部分。
以下是我對你的要求的近似。 如果它沒有標記,那么請用示例和/或圖表來擴充您的解釋:
from time import sleep
from random import randint
from itertools import cycle
from graphics import *
from pyeasyga import pyeasyga
NUMBER_OF_RECTANGLES = 4 # make one more than what you want to see
NUMBER_OF_POINTS = 2
arrivo = (90, 90)
colori = ["red", "green", "blue", "cyan", "magenta", "yellow"]
X, Y = 0, 1
def distEuclidea(p1, p2):
x1, y1 = p1
x2, y2 = p2
return ((x2 - x1) ** 2 + (y2 - y1) ** 2) ** 0.5
def create_individual(colors):
color = next(colors)
while color in rectangles and rectangles[color] is None: # skip over deleted rectangle
color = next(colors)
if color in rectangles:
rectangle = rectangles[color]
p1, p2 = rectangle.getP1(), rectangle.getP2()
points = [[p1.getX(), p1.getY()], [p2.getX(), p2.getY()]]
else:
points = [[randint(0, 20), randint(0, 20)] for _ in range(NUMBER_OF_POINTS)]
rectangle = Rectangle(*[Point(x, y) for x, y in points])
rectangle.setOutline(color)
rectangle.draw(win)
rectangles[color] = rectangle
return [color, points]
def fitness(individual, colors):
_, points = individual
rectangle = Rectangle(*[Point(x, y) for x, y in points])
center = rectangle.getCenter()
return distEuclidea(arrivo, (center.getX(), center.getY()))
def mutate(individual):
_, points = individual
mutate_index = randint(0, NUMBER_OF_POINTS - 1)
points[mutate_index][X] += randint(-1, 1)
points[mutate_index][Y] += randint(-1, 1)
def is_point_inside_rectangle(point, rectangle):
p1, p2 = rectangle.getP1(), rectangle.getP2()
return min(p1.getX(), p2.getX()) < point.getX() < max(p1.getX(), p2.getX()) and \
min(p1.getY(), p2.getY()) < point.getY() < max(p1.getY(), p2.getY())
win = GraphWin("Genetic Graphics", 500, 500)
win.setCoords(0, 0, 100, 100)
rectangles = {}
color_generator = cycle(colori[0:NUMBER_OF_RECTANGLES])
arrivoC = Circle(Point(*arrivo), 1)
arrivoC.setFill("orange")
arrivoC.draw(win)
number_of_rectangles = NUMBER_OF_RECTANGLES
while True:
ga = pyeasyga.GeneticAlgorithm(color_generator, \
elitism=False, \
maximise_fitness=False, \
crossover_probability=0.0, \
population_size=number_of_rectangles)
ga.create_individual = create_individual
ga.fitness_function = fitness
ga.mutate_function = mutate
ga.run()
for member in ga.last_generation():
my_fitness, (my_color, my_points) = member
if rectangles[my_color] is None:
continue # skip over deleted rectangle
rectangle = Rectangle(*[Point(x, y) for x, y in my_points])
rectangle.setOutline(my_color)
rectangle.draw(win)
rectangles[my_color] = rectangle
if is_point_inside_rectangle(arrivoC.getCenter(), rectangle):
rectangles[my_color] = None # delete finished rectangle
number_of_rectangles -= 1
if number_of_rectangles < 2:
break
sleep(0.1)
for value in rectangles.values():
if value is not None:
value.undraw() # delete unfinished rectangle
win.getMouse()
win.close()
以上是粗略的代碼(例如,它並不總是保持通用域點和矩形獨立於graphics.py點和矩形。)但它應該給你一些實驗:
它在窗口的左下角創建矩形,遺傳算法在右上角向目標突變,當它們到達目標時丟棄矩形。
我的代碼的一部分復雜性是pyeasyga沒有提供一個功能鈎子來可視化每一代發生的事情。 更好的方法可能是將pyeasyga子類化為添加這樣的鈎子以簡化代碼的邏輯。
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