PyGMO custom class with __init__ error - python-2.7

Question

I am working on a parallelized optimization problem in PyGMO. Unfortunately the docs are not very helpful. According to these guidelines, I am riting my problem as
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
This does not work and produce the following error:
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)
Any idea to what __init__ is referring to and what parameters are missing? I suspect that it is a problem with my class definition.

Answer 1

The issue is caused by the mismatch between input arguments of my_problem.__init__(...) (i.e. the Child class) and the base.__init__ (i.e. the Parent class). If defaults for these parameters are not provided then a conflict results by the inheritance of __init__ by super(my_problem,self) from base. In practice, a corrected working version is:
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
...
It is not possible instead to pass **kwargs to the child class insofar as base is hard coded and should be changed accordingly to this post.