numpy migration (also posted to numpy-discussion)

[Duncan Smith]

Travis E. Oliphant wrote:
> Duncan Smith wrote:
> 
>> Hello,
>>      Since moving to numpy I've had a few problems with my existing
>> code.  It basically revolves around the numpy scalar types. e.g.
>>
> 
> You will probably get more help on the numpy discussion list:
> 
> numpy-discussion at scipy.org
> 
> 
> You are encountering problems because numpy scalar types don't raise
> errors (unless you have set the appropriate hardware flag using
> numpy.seterr).
> 

Aha!

> You can get Python scalars out of NumPy arrays if you really want them
> using (for example...)
> 
> a.item(0,0)
> 
> 
>>
>> An additional problem involves classes that have e.g. __rmul__ methods
>> defined and are sufficiently similar to numpy arrays that my classes'
>> __rmul__ methods are not invoked when using numpy scalars.
>>
> 
> Could you please post an example showing the problem?
> 

I'll try to post a minimal example tomorrow.  But they are classes that
have an ndarray as an attribute, and with __getitem__ and __setitem__
methods which simply call the corresponding array methods.  Maybe that's
enough to account for the behaviour?  I'll check tomorrow.

>>
>> I might (I hope) be missing something obvious; but it seems like, to be
>> safe, I'm going to have to do a lot of explicit conversions to Python
>> types (or abandon catching zero division errors, and documenting some of
>> my classes to highlight that whether scalar * a equals a * scalar
>> depends on whether a.__rmul__ is called, which depends on the type of
>> scalar).
>>
> 
> numpy scalars are try a lot more things before giving up on
> multiplication and letting the other class have a stab at it.
> 
> Post your problems to the numpy discussion list for better help and more
> discussion.
> 

Yes, I have done.  But it's awaiting moderation; presumably because I
posted using a different e-mail address than the one I registered with
(I wasn't thinking).  Thanks for the reply.

Duncan