On Tue, Feb 23, 2016 at 3:30 PM, Nathaniel Smith wrote:
> What should this do?
>
> np.zeros((12, 0)).reshape((10, -1, 2))
>
It should error out, I already covered that. 12 != 20.
Ben Root
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On Tue, Feb 23, 2016 at 12:23 PM, Benjamin Root wrote:
>
> On Tue, Feb 23, 2016 at 3:14 PM, Nathaniel Smith wrote:
>>
>> Sure, it's totally ambiguous. These are all legal:
>
>
>
> I would argue that except for the first reshape, all of those should be an
> error, and that the current algorithm is
On Tue, Feb 23, 2016 at 3:14 PM, Nathaniel Smith wrote:
> Sure, it's totally ambiguous. These are all legal:
I would argue that except for the first reshape, all of those should be an
error, and that the current algorithm is buggy.
This isn't a heuristic. It isn't guessing. It is making the s
On Tue, Feb 23, 2016 at 8:45 AM, Benjamin Root wrote:
> but, it isn't really ambiguous, is it? The -1 can only refer to a single
> dimension, and if you ignore the zeros in the original and new shape, the -1
> is easily solvable, right?
Sure, it's totally ambiguous. These are all legal:
In [1]:
On Di, 2016-02-23 at 21:06 +0100, Sebastian Berg wrote:
> On Di, 2016-02-23 at 14:57 -0500, Benjamin Root wrote:
> > I'd be more than happy to write up the patch. I don't think it
> > would
> > be quite like make zeros be ones, but it would be along those
> > lines.
> > One case I need to wrap my h
On Di, 2016-02-23 at 14:57 -0500, Benjamin Root wrote:
> I'd be more than happy to write up the patch. I don't think it would
> be quite like make zeros be ones, but it would be along those lines.
> One case I need to wrap my head around is to make sure that a 0 would
> happen if the following was
I'd be more than happy to write up the patch. I don't think it would be
quite like make zeros be ones, but it would be along those lines. One case
I need to wrap my head around is to make sure that a 0 would happen if the
following was true:
>>> a = np.ones((0, 5*64))
>>> a.shape = (-1, 5, 64)
ED
On Di, 2016-02-23 at 11:45 -0500, Benjamin Root wrote:
> but, it isn't really ambiguous, is it? The -1 can only refer to a
> single dimension, and if you ignore the zeros in the original and new
> shape, the -1 is easily solvable, right?
I think if there is a simple logic (like using 1 for all zer
but, it isn't really ambiguous, is it? The -1 can only refer to a single
dimension, and if you ignore the zeros in the original and new shape, the
-1 is easily solvable, right?
Ben Root
On Tue, Feb 23, 2016 at 11:41 AM, Warren Weckesser <
warren.weckes...@gmail.com> wrote:
>
>
> On Tue, Feb 23,
On Tue, Feb 23, 2016 at 11:32 AM, Benjamin Root
wrote:
> Not exactly sure if this should be a bug or not. This came up in a fairly
> general function of mine to process satellite data. Unexpectedly, one of
> the satellite files had no scans in it, triggering an exception when I
> tried to reshape
Not exactly sure if this should be a bug or not. This came up in a fairly
general function of mine to process satellite data. Unexpectedly, one of
the satellite files had no scans in it, triggering an exception when I
tried to reshape the data from it.
>>> import numpy as np
>>> a = np.zeros((0, 5
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