parse_doc_string(MMGA.__init__)
if __name__ == '__main__':
problem = MultiModalSimple2()
algorithm = MMGA(pop_size=20, eliminate_duplicates=True)
ret = minimize(problem,
algorithm,
termination=('n_gen', 100),
seed=1,
save_history=True,
verbose=False)
def plot(algorithm):
pop = algorithm.pop
sc = Scatter(title=algorithm.n_gen)
sc.add(curve(algorithm.problem), plot_type="line", color="black")
sc.add(np.column_stack([pop.get("X"), pop.get("F")]), color="red")
sc.do()
plot(ret.algorithm)
plt.show()
with Video(File("mm.mp4")) as vid:
for entry in ret.history:
plot(entry)
vid.record()
def __init__(self):
super().__init__()
self.vid = Video(File("tsp.mp4"))
import numpy as np
from matplotlib import pyplot as plt
from pyrecorder.recorders.file import File
from pyrecorder.video import Video
with Video(File("wave.mp4", fps=15)) as vid:
for t in range(200):
x = np.linspace(0, 4, 1000)
y = np.sin(2 * np.pi * (x - 0.01 * t))
plt.plot(x, y)
vid.record()
import matplotlib.pyplot as plt
import numpy as np
from pyrecorder.recorders.file import File
from pyrecorder.video import Video
plt.style.use('dark_background')
with Video(File("coil.mp4", fps=15)) as vid:
for t in range(500):
a = np.arange(t) * 0.1
plt.plot(a * np.sin(a), a * np.cos(a))
plt.xlim(-50, 50)
plt.ylim(-50, 50)
plt.axis('off')
vid.record()
# START example
import numpy as np
from pyrecorder.recorders.file import File
from pyrecorder.video import Video
from pymoo.algorithms.nsga2 import NSGA2
from pymoo.visualization.scatter import Scatter
vid = Video(File("example.mp4"))
for k in range(10):
X = np.random.random((100, 2))
Scatter(title=str(k)).add(X).do()
vid.record()
vid.close()
# END example
# START ga
from pymoo.factory import get_problem
from pymoo.optimize import minimize
problem = get_problem("zdt1")
algorithm = NSGA2(pop_size=100, eliminate_duplicates=True)
ret = minimize(problem,
algorithm,
termination=('n_gen', 100),
seed=1,
save_history=True,
