[Numpy-discussion] Assigning complex values to a real array

Ryan May rmay31@gmail....
Wed Dec 9 08:46:41 CST 2009


On Wed, Dec 9, 2009 at 3:51 AM, David Warde-Farley <dwf@cs.toronto.edu> wrote:
> On 9-Dec-09, at 1:26 AM, Dr. Phillip M. Feldman wrote:
>> Unfortunately, NumPy seems to be a sort of step-child of Python,
>> tolerated,
>> but not fully accepted. There are a number of people who continue to
>> use Matlab,
>> despite all of its deficiencies, because it can at least be counted
>> on to
>> produce correct answers most of the time.
>
> Except that you could never fully verify that it produces correct
> results, even if that was your desire.
>
> There are legitimate reasons for wanting to use Matlab (e.g.
> familiarity, because collaborators do, and for certain things it's
> still faster than the alternatives) but correctness of results isn't
> one of them. That said, people routinely let price tags influence
> their perceptions of worth.

While I'm not going to argue in favor of Matlab, and think it's
benefits are being over-stated, let's call a spade a spade.  Silent
downcasting of complex types to float is a *wart*.  It's not sensible
behavior, it's an implementation detail that smacks new users in the
face.  It's completely insensible to consider converting from complex
to float in the same vein as a simple loss of precision from 64-bit to
32-bit.  The following doesn't work:

a = np.array(['bob', 'sarah'])
b = np.arange(2.)
b[:] = a
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)

/home/rmay/<ipython console> in <module>()

ValueError: invalid literal for float(): bob

Why doesn't that silently downcast the strings to 0.0 or something
silly?  Because that would be *stupid*.  So why doesn't trying to
stuff 3+4j into the array get the same error, because 3+4j is
definitely not a float value either.

Ryan

-- 
Ryan May
Graduate Research Assistant
School of Meteorology
University of Oklahoma


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