[Numpy-discussion] when did column_stack become C-contiguous?

[josef.pktd at gmail.com]

On Mon, Oct 19, 2015 at 9:00 AM, <josef.pktd at gmail.com> wrote:

>
>
> On Mon, Oct 19, 2015 at 5:16 AM, Sebastian Berg <
> sebastian at sipsolutions.net> wrote:
>
>> On Mo, 2015-10-19 at 01:34 -0400, josef.pktd at gmail.com wrote:
>> >
>>
>> <snip>
>>
>>
>> >
>> > It looks like in 1.9 it depends on the order of the 2-d arrays, which
>> > it didn't do in 1.6
>> >
>>
>> Yes, it uses concatenate, and concatenate probably changed in 1.7 to use
>> "K" (since "K" did not really exists before 1.7 IIRC).
>> Not sure what we can do about it, the order is not something that is
>> easily fixed unless explicitly given. It might be optimized (as in this
>> case I would guess).
>> Whether or not doing the fastest route for these kind of functions is
>> faster for the user is of course impossible to know, we can only hope
>> that in most cases it is better.
>> If someone has an idea how to decide I am all ears, but I think all we
>> can do is put in asserts/tests in the downstream code if it relies
>> heavily on the order (or just copy, if the order is wrong) :(, another
>> example is change of the output order in advanced indexing in some
>> cases, it makes it faster sometimes, and probably slower in others, what
>> is right seems very much non-trivial.
>>
>
> To understand the reason:
>
> Is this to have more efficient memory access during copying?
>
> AFAIU, column_stack needs to create a new array which has to be either F
> or C contiguous, so we always have to pick one of the two. With a large
> number of 1d arrays it seemed more "intuitive" to me to copy them by
> columns.
>


just as background

I was mainly surprised last night about having my long held beliefs
shattered. I skipped numpy 1.7 and 1.8 in my development environment and
still need to catch up now that I use 1.9 as my main numpy version.

I might have to update a bit my "folk wisdom", which is not codified
anywhere and doesn't have unit tests.

For example, the improvement iteration for Fortran contiguous or not C or F
contiguous arrays sounded very useful, but I never checked if it would
affect us.

Josef



>
> Josef
>
>
>
>>
>> - Sebastian
>>
>>
>> >
>> > >>> np.column_stack((np.ones(10), np.ones((10, 2), order='F'))).flags
>> >   C_CONTIGUOUS : False
>> >   F_CONTIGUOUS : True
>> >   OWNDATA : True
>> >   WRITEABLE : True
>> >   ALIGNED : True
>> >   UPDATEIFCOPY : False
>> >
>> >
>> >
>> >
>> > which means the default order looks more like "K" now, not "C", IIUC
>> >
>> >
>> > Josef
>> >
>> >
>> >
>> >
>> >
>> >         Josef
>> >
>> >
>> >
>> >
>> >
>> >                 Stephan
>> >
>> >                 _______________________________________________
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>> >                 NumPy-Discussion at scipy.org
>> >
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>> >
>> >
>> >
>> >
>> >
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