scipy.optimize.minimize 不会在 maxiter 或回调处停止

Question

我已经实现了 scipy.optimize.minimize 以最小化具有 128 个值的一维数组的 pandas 数据帧的增量值的平均值。

它似乎在运行并做一些事情，但它并没有停止在 maxiter 或从此处的另一个 Stack Overflow 问题获取的回调函数处。

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，并且已达到比开始时更小的函数值，但它并没有停止。由于它是在 jupyter 中运行的，因此如果没有完成单元格，我无法到达 res。

Answer 1

根据docs 回调应该是一个可调用的返回True 用于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，您应该定义一个类的实例，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，您可以为您的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您的最小化。这可以像这样完成：

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()

测试这些代码：timeout=0.1 & maxiter=100 然后timeout=10 & maxiter=10 观察这两种终止类型。