[Numpy-discussion] Plans for Numpy 1.4.0 and scipy 0.8.0
Mon Jun 22 09:30:27 CDT 2009
On Mon, Jun 22, 2009 at 7:27 AM, Darren Dale <email@example.com> wrote:
> On Mon, Jun 22, 2009 at 3:04 AM, Charles R Harris <
> firstname.lastname@example.org> wrote:
>> On Mon, Jun 22, 2009 at 12:18 AM, Pierre GM<email@example.com> wrote:
>> > On Jun 21, 2009, at 5:01 AM, David Cournapeau wrote:
>> >> (Continuing the discussion initiated in the neighborhood iterator
>> >> thread)
>> >> Hi,
>> >> I would like to gather people's opinion on what to target for numpy
>> >> 1.4.0.
>> > Is this a wish list ?
>> > * As Darren mentioned, some __array_prepare__ method called when a
>> > ufunc is called on a subclass of ndarray, before any computation takes
>> > place. Think of it as a parallel to __array_wrap__
>> This is an interesting idea but it need some fleshing out. Working out
>> a few example applications would firm things up I think. Things like
>> what parameters would be passed need to be specified.
> I posted an explanation of what parameters would be passed and a simple
> example of how the implementation might look and behave. I gave two
> application examples, MaskedArray and Quantities.
>> For instance, if
>> units are involved there would be a difference between binary and
>> unary functions. And what of things like log and exp which should have
>> unitless arguments? There looks to be a lot of preliminary work there.
> These considerations are already addressed and many of the ufuncs
> (arithmetic, inverse, etc) are already implemented in Quantities-0.5b2 (I'll
> post a 0.5b3 that implements log and exp this morning at PyPI). The identity
> of the ufunc itself is used as the context for operating on the units or
> raising an error if the units are incompatible with the operation.
I just posted sources and installers for quantities-0.5b5 at
http://pypi.python.org/pypi . Part of the code that allows quantities to
work with standard numpy ufuncs is in quantity.py (Quantity.__array_wrap__)
and the rest is at the end of dimensionality.py. So for example, you can do:
import numpy as np
import quantities as pq
np.log(pq.m) # raises an error
np.log(pq.m/pq.m) # yields: array(0.0) * dimensionless
unrecognized ufuncs return a dimensionless quantity by default, but
quantities could raise an error instead:
ufunc <ufunc 'logical_and'> not implemented, please file a bug report
array(True, dtype=bool) * dimensionless
Unit handling is all implemented in __array_wrap__, but this occurs too late
in the ufunc to catch errors before the ufunc can modify data in-place. For
np.add(q1,q2) # raises an ValueError
np.add(q1,q2, q1) # also raises a ValueError, but too late:
print q1 # yields array(2.0) * m
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