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 <jjhelmus@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

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 <jjhelmus@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