On Mo, 2016-02-15 at 17:06 +0000, Gutenkunst, Ryan N - (rgutenk) wrote: > Thank Jonathan, > > Good to confirm this isn't something inappropriate I'm doing. I give > up transparency here in my application, so I'll just work around it. > I leave it up to wiser numpy heads as to whether it's worth altering > these numpy.ma functions to enable subclassing. >
Frankly, when it comes to masked array stuff, at least I am puzzled
most of the time, so input is very welcome.
Most of the people currently contributing, barely use masked arrays as
far as I know, and sometimes it is hard to make good calls. It is a not
the easiest code base and any feedback or nudging is important. A new
release is about to come out, and if you feel it there is a serious
regression, we may want to push for fixing it (or even better, you may
have time to suggest a fix yourself).
- Sebastian
> Best,
> Ryan
>
> On Feb 13, 2016, at 11:48 AM, Jonathan Helmus <jjhel...@gmail.com>
> wrote:
>
> >
> >
> > On 2/12/16 6:06 PM, Gutenkunst, Ryan N - (rgutenk) wrote:
> > > Hello all,
> > >
> > > In 2009 I developed an application that uses a subclass of masked
> > > arrays as a central data object. My subclass Spectrum possesses
> > > additional attributes along with many custom methods. It was very
> > > convenient to be able to use standard numpy functions for doing
> > > arithmetic on these objects. However, my code broke with numpy
> > > 1.10. I've finally had a chance to track down the problem, and I
> > > am hoping someone can suggest a workaround.
> > >
> > > See below for an example, which is as minimal as I could concoct.
> > > In this case, I have a Spectrum object that I'd like to take the
> > > logarithm of using numpy.ma.log, while preserving the value of
> > > the "folded" attribute. Up to numpy 1.9, this worked as expected,
> > > but in numpy 1.10 and 1.11 the attribute is not preserved.
> > >
> > > The change in behavior appears to be driven by a commit made on
> > > Jun 16th, 2015 by Marten van Kerkwijk. In particular, the commit
> > > changed _MaskedUnaryOperation.__call__ so that the result array's
> > > update_from method is no longer called with the input array as
> > > the argument, but rather the result of the numpy UnaryOperation
> > > (old line 889, new line 885). Because that UnaryOperation doesn't
> > > carry my new attribute, it's not present for update_from to
> > > access. I notice that similar changes were made to
> > > MaskedBinaryOperation, although I haven't tested those. It's not
> > > clear to me from the commit message why this particular change
> > > was made, so I don't know whether this new behavior is
> > > intentional.
> > >
> > > I know that subclassing arrays isn't widely encouraged, but it
> > > has been very convenient in my code. Is it still possible to
> > > subclass masked_array in such a way that functions like
> > > numpy.ma.log preserve additional attributes? If so, can someone
> > > point me in the right direction?
> > >
> > > Thanks!
> > > Ryan
> > >
> > > *** Begin example
> > >
> > > import numpy
> > > print 'Working with numpy {0}'.format(numpy.__version__)
> > >
> > > class Spectrum(numpy.ma.masked_array):
> > > def __new__(cls, data, mask=numpy.ma.nomask,
> > > data_folded=None):
> > > subarr = numpy.ma.masked_array(data, mask=mask,
> > > keep_mask=True,
> > > shrink=True)
> > > subarr = subarr.view(cls)
> > > subarr.folded = data_folded
> > >
> > > return subarr
> > >
> > > def __array_finalize__(self, obj):
> > > if obj is None:
> > > return
> > > numpy.ma.masked_array.__array_finalize__(self, obj)
> > > self.folded = getattr(obj, 'folded', 'unspecified')
> > >
> > > def _update_from(self, obj):
> > > print('Input to update_from: {0}'.format(repr(obj)))
> > > numpy.ma.masked_array._update_from(self, obj)
> > > self.folded = getattr(obj, 'folded', 'unspecified')
> > >
> > > def __repr__(self):
> > > return 'Spectrum(%s, folded=%s)'\
> > > % (str(self), str(self.folded))
> > >
> > > fs1 = Spectrum([2,3,4.], data_folded=True)
> > > fs2 = numpy.ma.log(fs1)
> > > print('fs2.folded status: {0}'.format(fs2.folded))
> > > print('Expectation is True, achieved with numpy 1.9')
> > >
> > > *** End example
> > >
> > > --
> > > Ryan Gutenkunst
> > > Assistant Professor
> > > Molecular and Cellular Biology
> > > University of Arizona
> > > phone: (520) 626-0569, office LSS 325
> > > http://gutengroup.mcb.arizona.edu
> > > Latest paper: "Computationally efficient composite likelihood
> > > statistics for demographic inference"
> > > Molecular Biology and Evolution;
> > > http://dx.doi.org/10.1093/molbev/msv255
> > Ryan,
> >
> > I'm not sure if you will be able to get this to work as in NumPy
> > 1.9, but the __array_wrap__ method is intended to be the mechanism
> > for subclasses to set their return type, adjust metadata, etc [1].
> > Unfortunately, the numpy.ma.log function does not seem to make a
> > call to __array_wrap__ (at least in NumPy 1.10.2) although
> > numpy.log does:
> >
> > from __future__ import print_function
> > import numpy
> > print('Working with numpy {0}'.format(numpy.__version__))
> >
> >
> > class Spectrum(numpy.ma.masked_array):
> > def __new__(cls, data, mask=numpy.ma.nomask, data_folded=None):
> > subarr = numpy.ma.masked_array(data, mask=mask,
> > keep_mask=True,
> > shrink=True)
> > subarr = subarr.view(cls)
> > subarr.folded = data_folded
> >
> > return subarr
> >
> > def __array_finalize__(self, obj):
> > if obj is None:
> > return
> > numpy.ma.masked_array.__array_finalize__(self, obj)
> > self.folded = getattr(obj, 'folded', 'unspecified')
> >
> > def __array_wrap__(self, out_arr, context=None):
> > print('__array_wrap__ called')
> > return numpy.ndarray.__array_wrap__(self, out_arr, context)
> >
> > def __repr__(self):
> > return 'Spectrum(%s, folded=%s)'\
> > % (str(self), str(self.folded))
> >
> > fs1 = Spectrum([2,3,4.], data_folded=True)
> >
> > print('numpy.ma.log:')
> > fs2 = numpy.ma.log(fs1)
> > print('fs2 type:', type(fs2))
> > print('fs2.folded status: {0}'.format(fs2.folded))
> >
> > print('numpy.log:')
> > fs3 = numpy.log(fs1)
> > print('fs3 type:', type(fs3))
> > print('fs3.folded status: {0}'.format(fs3.folded))
> >
> > ----
> > $ python example.py
> > Working with numpy 1.10.2
> > numpy.ma.log:
> > fs2 type: <class '__main__.Spectrum'>
> > fs2.folded status: unspecified
> > numpy.log:
> > __array_wrap__ called
> > fs3 type: <class '__main__.Spectrum'>
> > fs3.folded status: True
> >
> >
> > The change mentioned in the original message was made in pull
> > request 3907 [2] in case anyone wants to have a look.
> >
> > Cheers,
> >
> > - Jonathan Helmus
> >
> > [1] http://docs.scipy.org/doc/numpy-1.10.1/user/basics.subclassing.
> > html#array-wrap-for-ufuncs
> > [2] https://github.com/numpy/numpy/pull/3907
> > _______________________________________________
> > NumPy-Discussion mailing list
> > NumPy-Discussion@scipy.org
> > https://mail.scipy.org/mailman/listinfo/numpy-discussion
>
> --
> Ryan Gutenkunst
> Assistant Professor
> Molecular and Cellular Biology
> University of Arizona
> phone: (520) 626-0569, office LSS 325
> http://gutengroup.mcb.arizona.edu
> Latest paper: "Computationally efficient composite likelihood
> statistics for demographic inference"
> Molecular Biology and Evolution;
> http://dx.doi.org/10.1093/molbev/msv255
>
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion@scipy.org
> https://mail.scipy.org/mailman/listinfo/numpy-discussion
>
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