我已经实现scipy.optimize.minimize来最小化具有128个值的一维数组的熊猫数据帧的增量值的平均值。
它似乎可以运行并且可以完成工作,但是它并不会在最大迭代次数或从此处另一个stackoverflow问题获取的回调函数处停止。
我的代码是:
import numpy as np
from scipy.optimize import minimize, rosen
import time
import warnings
class TookTooLong(Warning):
pass
class MinimizeStopper(object):
def __init__(self, max_sec=60*60*5):
self.max_sec = max_sec
self.start = time.time()
def __call__(self, xk=None):
elapsed = time.time() - self.start
if elapsed > self.max_sec:
warnings.warn("Terminating optimization: time limit reached",
TookTooLong)
else:
# you might want to report other stuff here
print("Elapsed: %.3f sec" % elapsed)
import scipy.optimize
res = scipy.optimize.minimize(minFunct,oned,options=
{"disp":True,"maxiter":100},tol=0.01,
method ="BFGS",callback=MinimizeStopper(1E-3))
一段时间后显示的消息告诉我已达到maxiter且已达到比开始时小的函数值,但并没有停止。自从它在jupyter中运行以来,我无法在没有单元完成的情况下获得res。
答案 0 :(得分:1)
根据docs回调,应为可调用的返回True
以终止并具有以下格式callback(xk)
。而在您的代码中,您将其定义为类的初始化。相反,您应该定义您的类的实例,然后将其__call__()
函数分配给callback
,如下所示:
import time
import warnings
import numpy as np
from scipy.optimize import minimize, rosen
class TookTooLong(Warning):
pass
class MinimizeStopper(object):
def __init__(self, max_sec=10):
self.max_sec = max_sec
self.start = time.time()
def __call__(self, xk):
# callback to terminate if max_sec exceeded
elapsed = time.time() - self.start
if elapsed > self.max_sec:
warnings.warn("Terminating optimization: time limit reached",
TookTooLong)
else:
# you might want to report other stuff here
print("Elapsed: %.3f sec" % elapsed)
# init stopper
minimize_stopper = MinimizeStopper()
# minimze
res = minimize(rosen,
x0 = np.random.randint(5, size=128),
method ="BFGS",
tol = 0.01,
options = {"maxiter":10, "disp":True},
callback = minimize_stopper.__call__)
或者,您可以为最小化器定义一个类,并在其中构建一个回调函数以在一定时间后终止最小化。可以这样完成:
import time
import warnings
import numpy as np
from scipy.optimize import minimize, rosen
class TookTooLong(Warning):
pass
class Minimizer:
def __init__(self, timeout, maxiter):
self.timeout = timeout
self.maxiter = maxiter
def minimize(self):
self.start_time = time.time()
# minimize
res = minimize(rosen,
x0 = np.random.randint(5, size=128),
method ="BFGS",
tol = 0.01,
options = {"maxiter":self.maxiter, "disp":True},
callback = self.callback)
return res
def callback(self, x):
# callback to terminate if max_sec exceeded
elapsed = time.time() - self.start_time
if elapsed > self.timeout:
warnings.warn("Terminating optimization: time limit reached",
TookTooLong)
return True
else:
print("Elapsed: %.3f sec" % elapsed)
# init minimizer and minimize
minimizer = Minimizer(0.1, 100)
result = minimizer.minimize()
先用timeout=0.1 & maxiter=100
然后用timeout=10 & maxiter=10
测试这些代码,以观察两种终止类型。