Re: [Numpy-discussion] dtype=object behavior change from 0.9.6 to beta 1

[Tom D. <tom...@al...>]

Yes one can take a toy example and hack it to work but I don't necessarily
have control over the input as to whether it is a list of object arrays,
list of 1d heterogenous arrays, etc.  Before I didn't need to worry about
the input because numpy understood that a list of 1d arrays is a 2d piece of
data.  Now it understands this for all dtypes except object.  My question
was is this new set of semantics preferable to the old.

I think your example kind of proves my point.  Does it really make any sense
for the following two ways of specifying an array give such different
results?  They strike me as _meaning_ the same thing.  Doesn't it seem
inconsistent to you?


In [13]: array([array([1,'A', None], dtype=object),array([2,2,'Some
string'],dtype=object)], dtype=object).shape
Out[13]: (2,)

and

In [14]: array([array([1,'A', None], dtype=object),array([2,2,'Some
string'],dtype=object)]).shape
Out[14]: (2, 3)
So my question is what is the _advantage_ of the new semantics?  The two
examples above used to give the same results.  In what cases is it
preferable for them to give different results?  How does it make life
simpler?


On 8/31/06, Charles R Harris <cha...@gm...> wrote:

> On 8/31/06, Tom Denniston <tom...@al...> wrote:
>
> > But i have hetergenious arrays that have numbers and strings and
> > NoneType, etc.
> >
> > Take for instance:
> >
> > In [11]: numpy.array([numpy.array([1,'A', None]),
> > numpy.array([2,2,'Some string'])], dtype=object)
> > Out[11]:
> > array([[1, A, None],
> >        [2, 2, Some string]], dtype=object)
> >
> > In [12]: numpy.array([numpy.array([1,'A', None]),
> > numpy.array([2,2,'Some string'])], dtype=object).shape
> > Out[12]: (2, 3)
> >
> > Works fine in Numeric and pre beta numpy but in beta numpy versions i
> > get:
>
>
> I think you want:
>
> In [59]: a = array([array([1,'A', None],dtype=object),array([2,2,'Some
> string'],dtype=object)])
>
> In [60]: a.shape
> Out[60]: (2, 3)
>
>
> Which makes good sense to me.
>
> Chuck
>
>
>
>
>
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