[Numpy-discussion] code review/build & test for datetime business day API

Mark Wiebe mwwiebe@gmail....
Thu Jun 16 19:02:41 CDT 2011


On Thu, Jun 16, 2011 at 5:52 PM, Derek Homeier <
derek@astro.physik.uni-goettingen.de> wrote:

> Hi Mark,
>
> On 16.06.2011, at 5:40PM, Mark Wiebe wrote:
>
> >> >>> np.datetime64('2011-06-16 02:03:04Z', 'D')
> >> np.datetime64('0000-06-16','D')
> >>
> >> I've tried to track this down in datetime.c, but unsuccessfully so (i.e.
> I could not connect it
> >> to any of the dts->year assignments therein).
> >>
> > This is definitely perplexing. Probably the first thing to check is
> whether it's breaking during parsing or printing. This should always produce
> the same result:
> >
> > >>> np.datetime64('1970-03-23 20:00:00Z').astype('i8')
> > 7070400
> >
> > But maybe the test_days_creation is already checking that thoroughly
> enough.
> >
> > Then, maybe printf-ing the year value at various stages of the printing,
> like in set_datetimestruct_days, after convert_datetime_to_datetimestruct,
> and in make_iso_8601_date. This would at least isolate where the year is
> getting lost.
> >
> ok, that was a lengthy hunt, but it's in printing the string in
> make_iso_8601_date:
>
>    tmplen = snprintf(substr, sublen, "%04" NPY_INT64_FMT, dts->year);
>    fprintf(stderr, "printed %d[%d]: dts->year=%lld: %s\n", tmplen, sublen,
> dts->year, substr);
>
> produces
>
> >>> np.datetime64('1970-03-23 20:00:00Z', 'D')
> printed 4[62]: dts->year=1970: 0000
> numpy.datetime64('0000-03-23','D')
>
> It seems snprintf is not using the correct format for INT64 (as I happened
> to do in fprintf before
> realising I had to use "%lld" ;-) - could it be this is a general issue,
> which just does not show up
> on little-endian machines because they happen to pass the right half of the
> int64 to printf?
> BTW, how is this supposed to be handled (in 4 digits) if the year is indeed
> beyond the 32bit range
> (i.e. >~ 0.3 Hubble times...)? Just wondering if one could simply cast it
> to int32 before print.
>

I'd prefer to fix the NPY_INT64_FMT macro. There's no point in having it if
it doesn't work... What is NumPy setting it to for that platform?

-Mark


> Cheers,
>                                                         Derek
>
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion@scipy.org
> http://mail.scipy.org/mailman/listinfo/numpy-discussion
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: http://mail.scipy.org/pipermail/numpy-discussion/attachments/20110616/b7610706/attachment.html 


More information about the NumPy-Discussion mailing list