Re: [Numpy-discussion] random.RandomState and deepcopy
On Fri, Mar 13, 2015 at 5:59 PM, Neal Becker ndbeck...@gmail.com wrote: Robert Kern wrote: On Fri, Mar 13, 2015 at 5:34 PM, Neal Becker ndbeck...@gmail.com wrote: It is common that to guarantee good statistical independence between various random generators, a singleton instance of an RNG is shared between them. So I typically have various random generator objects, which (sometimes several levels objects deep) embed an instance of RandomState. Now I have a requirement to copy a generator object (without knowing exactly what that generator object is). Or rather, you want the generator object to *avoid* copies by returning itself when a copy is requested of it. My solution is to use deepcopy on the top-level object. But I need to overload __deepcopy__ on the singleton RandomState object. Unfortunately, RandomState doesn't allow customization of __deepcopy__ (or anything else). And it has no __dict__. You can always subclass RandomState to override its __deepcopy__. -- Robert Kern Yes, I think I prefer this: from numpy.random import RandomState class shared_random_state (RandomState): def __init__ (self, rs): RandomState.__init__(self, rs) def __deepcopy__ (self, memo): return self Although, that means I have to use it like this: rs = shared_random_state (0) where I really would prefer (for aesthetic reasons): rs = shared_random_state (RandomState(0)) but I don't know how to do that if shared_random_state inherits from RandomState. shrug If you insist: class shared_random_state(RandomState): def __init__(self, rs): self.__setstate__(rs.__getstate__()) def __deepcopy__(self, memo): return self -- Robert Kern ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] random.RandomState and deepcopy
On Fri, Mar 13, 2015 at 5:34 PM, Neal Becker ndbeck...@gmail.com wrote: It is common that to guarantee good statistical independence between various random generators, a singleton instance of an RNG is shared between them. So I typically have various random generator objects, which (sometimes several levels objects deep) embed an instance of RandomState. Now I have a requirement to copy a generator object (without knowing exactly what that generator object is). Or rather, you want the generator object to *avoid* copies by returning itself when a copy is requested of it. My solution is to use deepcopy on the top-level object. But I need to overload __deepcopy__ on the singleton RandomState object. Unfortunately, RandomState doesn't allow customization of __deepcopy__ (or anything else). And it has no __dict__. You can always subclass RandomState to override its __deepcopy__. -- Robert Kern ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] random.RandomState and deepcopy
Robert Kern wrote: On Fri, Mar 13, 2015 at 5:34 PM, Neal Becker ndbeck...@gmail.com wrote: It is common that to guarantee good statistical independence between various random generators, a singleton instance of an RNG is shared between them. So I typically have various random generator objects, which (sometimes several levels objects deep) embed an instance of RandomState. Now I have a requirement to copy a generator object (without knowing exactly what that generator object is). Or rather, you want the generator object to *avoid* copies by returning itself when a copy is requested of it. My solution is to use deepcopy on the top-level object. But I need to overload __deepcopy__ on the singleton RandomState object. Unfortunately, RandomState doesn't allow customization of __deepcopy__ (or anything else). And it has no __dict__. You can always subclass RandomState to override its __deepcopy__. -- Robert Kern Yes, I think I prefer this: from numpy.random import RandomState class shared_random_state (RandomState): def __init__ (self, rs): RandomState.__init__(self, rs) def __deepcopy__ (self, memo): return self Although, that means I have to use it like this: rs = shared_random_state (0) where I really would prefer (for aesthetic reasons): rs = shared_random_state (RandomState(0)) but I don't know how to do that if shared_random_state inherits from RandomState. -- Those who fail to understand recursion are doomed to repeat it ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
