On Tue, Aug 4, 2015 at 4:39 AM, Sebastian Berg <sebast...@sipsolutions.net> wrote:
> On Mo, 2015-08-03 at 21:32 +0200, Sturla Molden wrote: > > On 03/08/15 20:51, Chris Barker wrote: > > > > > well, IIUC, np.int <http://np.int> is the python integer type, which > is > > > a C long in all the implemtations of cPython that I know about -- but > is > > > that a guarantee?in the future as well? > > > > It is a Python int on Python 2. > > > > On Python 3 dtype=np.int means the dtype will be C long, because a > > Python int has no size limit. But np.int aliases Python int. And > > creating an array with dype=int therefore does not create an array of > > Python int, it creates an array of C long. To actually get dtype=int we > > have to write dtype=object, which is just crazy. > > > > Since it seemes there may be a few half truths flying around in this > thread. See http://docs.scipy.org/doc/numpy/user/basics.types.html Quote: "Note that, above, we use the *Python* float object as a dtype. NumPy knows that int refers to np.int_, bool meansnp.bool_, that float is np.float_ and complex is np.complex_. The other data-types do not have Python equivalents." Is there a conflict with the current thread? Josef (I'm not a C person, so most of this is outside my scope, except for watching bugfixes to make older code work for larger datasets. Use `intp`, Luke.) > > > and also note the sentence below the table (maybe the table should also > note these): > > Additionally to intc the platform dependent C integer types short, long, > longlong and their unsigned versions are defined. > > - Sebastian > > > > > Sturla > > > > > > > > _______________________________________________ > > NumPy-Discussion mailing list > > NumPy-Discussion@scipy.org > > http://mail.scipy.org/mailman/listinfo/numpy-discussion > > > > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion > >
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