[Numpy-discussion] reciprocal(0)

[Ralf Gommers]

You're right, that's a little inconsistent. I would also prefer to get an
overflow for divide by 0 rather than casting to zero.

- ralf


On Sun, Jun 7, 2009 at 12:22 AM, <josef.pktd at gmail.com> wrote:

> On Sat, Jun 6, 2009 at 11:49 PM, Ralf Gommers
> <ralf.gommers at googlemail.com> wrote:
> > Hi,
> >
> > I expect `reciprocal(x)` to calculate 1/x, and for input 0 to either
> follow
> > the python rules or give the np.divide(1, 0) result. However the result
> > returned (with numpy trunk) is:
> >
> >>>> np.reciprocal(0)
> > -2147483648
> >
> >>>> np.divide(1, 0)
> > 0
> >>>> 1/0
> > Traceback (most recent call last):
> >   File "<stdin>", line 1, in <module>
> > ZeroDivisionError: integer division or modulo by zero
> >
> > The result for a zero float argument is inf as expected. I want to
> document
> > the correct behavior for integers, what should it be?
> >
> > Cheers,
> > Ralf
>
> Add a warning not to use integers, if a nan or inf is possible in the
> code, because the behavior in numpy is not very predictable.
> overflow looks ok, but I really don't like the casting of nans to zero.
>
> Josef
>
> >>> x = np.array([0,1],dtype=int)
>
> >>> x[1] = np.nan
> >>> x
> array([0, 0])
>
> >>> x[1]= np.inf
> Traceback (most recent call last):
> OverflowError: cannot convert float infinity to long
>
> >>> np.array([np.nan, 1],dtype=int)
> array([0, 1])
>
> >>> np.array([0, np.inf],dtype=int)
> Traceback (most recent call last):
> ValueError: setting an array element with a sequence.
>
> >>> np.array([np.nan, np.inf]).astype(int)
> array([-2147483648, -2147483648])
>
>
> and now yours looks like an inf cast to zero
>
> >>> x = np.array([0,1],dtype=int)
> >>> x/x[0]
> array([0, 0])
>
> Masked Arrays look good for this
>
> >>> x = np.ma.array([0,1],dtype=int)
> >>> x
> masked_array(data = [0 1],
>             mask = False,
>       fill_value = 999999)
>
> >>> x/x[0]
> masked_array(data = [-- --],
>             mask = [ True  True],
>       fill_value = 999999)
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