suggested points lie outside of domain
This happens because of some numerical precision issues.
import adaptive
adaptive.notebook_extension()
def f(xy):
import random
import time
time.sleep(4 + random.random()/10)
return random.randint(1, 10)
learner = adaptive.Learner2D(
f,
bounds=[
(0.16, 0.2),
(0.6, 2.4)
]
)
runner = adaptive.Runner(learner, goal=lambda l: l.npoints > 1000, ntasks=10, log=True)
runner.live_info()
Will fail after ~20 points.