On Sun, Mar 8, 2009 at 3:27 PM, Darren Dale <dsdal...@gmail.com> wrote:
> On Sun, Mar 8, 2009 at 5:02 PM, Darren Dale <dsdal...@gmail.com> wrote: > >> On Sun, Mar 8, 2009 at 4:54 PM, Charles R Harris < >> charlesr.har...@gmail.com> wrote: >> >>> >>> >>> On Sun, Mar 8, 2009 at 2:48 PM, Charles R Harris < >>> charlesr.har...@gmail.com> wrote: >>> >>>> >>>> >>>> On Sun, Mar 8, 2009 at 1:04 PM, Darren Dale <dsdal...@gmail.com> wrote: >>>> >>>>> On Sat, Mar 7, 2009 at 1:23 PM, Darren Dale <dsdal...@gmail.com>wrote: >>>>> >>>>>> On Sun, Feb 22, 2009 at 7:01 PM, Darren Dale <dsdal...@gmail.com>wrote: >>>>>> >>>>>>> On Sun, Feb 22, 2009 at 6:35 PM, Darren Dale <dsdal...@gmail.com>wrote: >>>>>>> >>>>>>>> On Sun, Feb 22, 2009 at 6:28 PM, Pierre GM <pgmdevl...@gmail.com>wrote: >>>>>>>> >>>>>>>>> >>>>>>>>> On Feb 22, 2009, at 6:21 PM, Eric Firing wrote: >>>>>>>>> >>>>>>>>> > Darren Dale wrote: >>>>>>>>> >> Does anyone know why __array_wrap__ is not called for subclasses >>>>>>>>> >> during >>>>>>>>> >> arithmetic operations where an iterable like a list or tuple >>>>>>>>> >> appears to >>>>>>>>> >> the right of the subclass? When I do "mine*[1,2,3]", array_wrap >>>>>>>>> is >>>>>>>>> >> not >>>>>>>>> >> called and I get an ndarray instead of a MyArray. "[1,2,3]*mine" >>>>>>>>> is >>>>>>>>> >> fine, as is "mine*array([1,2,3])". I see the same issue with >>>>>>>>> >> division, >>>>>>>>> > >>>>>>>>> > The masked array subclass does not show this behavior: >>>>>>>>> >>>>>>>>> Because MaskedArray.__mul__ and others are redefined. >>>>>>>>> >>>>>>>>> Darren, you can fix your problem by redefining MyArray.__mul__ as: >>>>>>>>> >>>>>>>>> def __mul__(self, other): >>>>>>>>> return np.ndarray.__mul__(self, np.asanyarray(other)) >>>>>>>>> >>>>>>>>> forcing the second term to be a ndarray (or a subclass of). You can >>>>>>>>> do >>>>>>>>> the same thing for the other functions (__add__, __radd__, ...) >>>>>>>> >>>>>>>> >>>>>>>> Thanks for the suggestion. I know this can be done, but ufuncs like >>>>>>>> np.multiply(mine,[1,2,3]) will still not work. Plus, if I reimplement >>>>>>>> these >>>>>>>> methods, I take some small performance hit. I've been putting a lot of >>>>>>>> work >>>>>>>> in lately to get quantities to work with numpy's stock ufuncs. >>>>>>>> >>>>>>> >>>>>>> I should point out: >>>>>>> >>>>>>> import numpy as np >>>>>>> >>>>>>> a=np.array([1,2,3,4]) >>>>>>> b=np.ma.masked_where(a>2,a) >>>>>>> np.multiply([1,2,3,4],b) # yields a masked array >>>>>>> np.multiply(b,[1,2,3,4]) # yields an ndarray >>>>>>> >>>>>>> >>>>>> I'm not familiar with the numpy codebase, could anyone help me figure >>>>>> out where I should look to try to fix this bug? I've got a nice set of >>>>>> generators that work with nosetools to test all combinations of numerical >>>>>> dtypes, including combinations of scalars, arrays, and iterables of each >>>>>> type. In my quantities package, just testing multiplication yields 1031 >>>>>> failures, all of which appear to be caused by this bug (#1026 on trak) or >>>>>> bug #826. >>>>> >>>>> >>>>> >>>>> I finally managed to track done the source of this problem. >>>>> _find_array_wrap steps through the inputs, asking each of them for their >>>>> __array_wrap__ and binding it to wrap. If more than one input defines >>>>> __array_wrap__, you enter a block that selects one based on array >>>>> priority, >>>>> and binds it back to wrap. The problem was when the first input defines >>>>> array_wrap but the second one does not. In that case, _find_array_wrap >>>>> never >>>>> bothered to rebind the desired wraps[0] to wrap, so wrap remains Null or >>>>> None, and wrap is what is returned to the calling function. >>>>> >>>>> I've tested numpy with this patch applied, and didn't see any >>>>> regressions. Would someone please consider committing it? >>>>> >>>>> Thanks, >>>>> Darren >>>>> >>>>> $ svn diff numpy/core/src/umath_ufunc_object.inc >>>>> Index: numpy/core/src/umath_ufunc_object.inc >>>>> =================================================================== >>>>> --- numpy/core/src/umath_ufunc_object.inc (revision 6569) >>>>> +++ numpy/core/src/umath_ufunc_object.inc (working copy) >>>>> @@ -3173,8 +3173,10 @@ >>>>> PyErr_Clear(); >>>>> } >>>>> } >>>>> + if (np >= 1) { >>>>> + wrap = wraps[0]; >>>>> + } >>>>> if (np >= 2) { >>>>> - wrap = wraps[0]; >>>>> maxpriority = PyArray_GetPriority(with_wrap[0], >>>>> PyArray_SUBTYPE_PRIORITY); >>>>> for (i = 1; i < np; ++i) { >>>>> >>>> >>>> Applied in r6573. Thanks. >>>> >>> >>> Oh, and can you provide a test for this fix? >>> >> >> Yes, I'll send a patch for a test as soon as its ready. 6573 closes two >> tickets, 1026 and 1022. Did you see the patch I sent for issue #826? It is >> also posted at the bug report. > > > > Index: numpy/core/tests/test_umath.py > =================================================================== > --- numpy/core/tests/test_umath.py (revision 6573) > +++ numpy/core/tests/test_umath.py (working copy) > @@ -240,6 +240,19 @@ > assert_equal(args[1], a) > self.failUnlessEqual(i, 0) > > + def test_wrap_with_iterable(self): > + # test fix for bug #1026: > + class with_wrap(np.ndarray): > + __array_priority = 10 > + def __new__(cls): > + return np.asarray(1).view(cls).copy() > + def __array_wrap__(self, arr, context): > + return arr.view(type(self)) > + a = with_wrap() > + x = ncu.multiply(a, (1, 2, 3)) > + self.failUnless(isinstance(x, with_wrap)) > + assert_array_equal(x, np.array((1, 2, 3))) > + > def test_old_wrap(self): > class with_wrap(object): > def __array__(self): > Thanks. This was applied in r6575. Chuck > >
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