带有__init__错误的PyGMO自定义类

Question

我正在PyGMO处理并行优化问题。不幸的是，文档不是很有帮助。根据{{​​3}}，我正在讨论我的问题

import PyGMO as pygmo
class my_problem(pygmo.base):
    def __init__(self,model,config,pars,**kwargs):
        # Does some parameter definition according to input arguments model, config etc...
        ...

        # Invoke base class as required by PyGMO
        super(my_problem,self).__init__(self.__dim)

    def _objfun_impl(self,x):
        ...
        f = ...  # Cost function to optimize
        return (f,)

# Main
model = 'ei'
config = 'x1'
args = (...)
prob = my_problem(model,config,args)
algo = pygmo.algorithm.de(gen=20)
isl = pygmo.island(algo,prob,20)
print isl.population.champion.f
isl.evolve(10)
print isl.population.champion.f

这不起作用并产生以下错误：

File     "/home/maurizio/Dropbox/Stability_Analysis_network/mymain.py", line 643, in main_routine
isl = pygmo.island(algo,prob,20)
File "/usr/lib/python2.7/site-packages/PyGMO/core/__init__.py", line 239, in island
return _generic_island_ctor(None, *args, **kwargs)
File "/usr/lib/python2.7/site-packages/PyGMO/core/__init__.py", line 132, in _generic_island_ctor
return py_island(*args, **kwargs)
File "/usr/lib/python2.7/site-packages/PyGMO/core/__init__.py", line 119, in _generic_island_ctor
super(type(self), self).__init__(*ctor_args)
File "/usr/lib/python2.7/site-packages/PyGMO/core/__init__.py", line 48, in __init__
_core._base_island.__init__(self, *args)
File "/usr/lib/python2.7/site-packages/PyGMO/problem/_base.py", line 36, in __get_deepcopy__
return deepcopy(self)
File "/usr/lib64/python2.7/copy.py", line 190, in deepcopy
y = _reconstruct(x, rv, 1, memo)
File "/usr/lib64/python2.7/copy.py", line 329, in _reconstruct
y = callable(*args)
TypeError: __init__() takes exactly 4 arguments (1 given)

对__init__指的是什么以及缺少哪些参数有任何想法？我怀疑这是我班级定义的问题。

Answer 1

问题是由my_problem.__init__(...)（即Child类）和base.__init__（即Parent类）的输入参数之间的不匹配引起的。如果未提供这些参数的默认值，则__init__从super(my_problem,self)继承base会产生冲突。在实践中，更正的工作版本是：

import PyGMO as pygmo
class my_problem(pygmo.base):
    def __init__(self,model='ei',config='conf1',pars=[1]*20):
        # Does some parameter definition according to input arguments model, config etc...
    ...

    self.__dim = 3
    ...

    # Invoke base class as required by PyGMO
    super(my_problem,self).__init__(self.__dim)

    def _objfun_impl(self,x):
        ...
        f = ...  # Cost function to optimize
        return (f,)

# Main
...

如果**kwargs是硬编码的，则无法将base传递给子类，因此应相应地更改为this post。