On Di, 2015-08-04 at 05:57 -0400, josef.pktd@gmail.com wrote:
On Tue, Aug 4, 2015 at 4:39 AM, Sebastian Berg
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?
No, but I had the impression that the C compatible type names "short", "cint", "long", etc. where forgotten.
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 >
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