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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，但它并没有停在maxiter或停在从此处的另一个 Stack Overflow 问题中获取的回调函数处。

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maxiter已经达到并且已经达到了比开始时更小的函数值，但它并没有停止。由于它在 jupyter 中运行，因此如果没有完成单元格，我将无法到达res。

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1 回答 1

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根据文档回调应该是一个可调用的返回True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。这可以这样做：

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=100thentimeout=10 & maxiter=10观察这两种类型的终止。

于 2019-05-22T09:11:14.910 回答