hi,
it recently came to my attention that the default integer type in numpy
on windows 64 bit is a 32 bit integers [0].
This seems like a quite serious problem as it means you can't use any
integers created from python integers 32 bit to index arrays larger
than 2GB.
For example
On 15.07.2014 20:06, Julian Taylor wrote:
hi,
as you may know we want to release numpy 1.9 soon. We should have solved
most indexing regressions the first beta showed.
The remaining blockers are finishing the new __numpy_ufunc__ feature.
This feature should allow for alternative method to
On Wed, Jul 23, 2014 at 6:19 PM, Julian Taylor
jtaylor.deb...@googlemail.com wrote:
hi,
it recently came to my attention that the default integer type in numpy
on windows 64 bit is a 32 bit integers [0].
This seems like a quite serious problem as it means you can't use any
integers created
On 23.07.2014 20:54, Robert Kern wrote:
On Wed, Jul 23, 2014 at 6:19 PM, Julian Taylor
jtaylor.deb...@googlemail.com wrote:
hi,
it recently came to my attention that the default integer type in numpy
on windows 64 bit is a 32 bit integers [0].
This seems like a quite serious problem as it
On Wed, Jul 23, 2014 at 8:50 PM, Julian Taylor
jtaylor.deb...@googlemail.com wrote:
On 23.07.2014 20:54, Robert Kern wrote:
On Wed, Jul 23, 2014 at 6:19 PM, Julian Taylor
jtaylor.deb...@googlemail.com wrote:
hi,
it recently came to my attention that the default integer type in numpy
on
On Wed, 2014-07-23 at 21:50 +0200, Julian Taylor wrote:
On 23.07.2014 20:54, Robert Kern wrote:
On Wed, Jul 23, 2014 at 6:19 PM, Julian Taylor
jtaylor.deb...@googlemail.com wrote:
hi,
it recently came to my attention that the default integer type in numpy
on windows 64 bit is a 32 bit
On Wed, 2014-07-23 at 22:06 +0200, Sebastian Berg wrote:
On Wed, 2014-07-23 at 21:50 +0200, Julian Taylor wrote:
On 23.07.2014 20:54, Robert Kern wrote:
On Wed, Jul 23, 2014 at 6:19 PM, Julian Taylor
jtaylor.deb...@googlemail.com wrote:
hi,
it recently came to my attention that the
On 23.07.2014 22:04, Robert Kern wrote:
On Wed, Jul 23, 2014 at 8:50 PM, Julian Taylor
jtaylor.deb...@googlemail.com wrote:
On 23.07.2014 20:54, Robert Kern wrote:
On Wed, Jul 23, 2014 at 6:19 PM, Julian Taylor
jtaylor.deb...@googlemail.com wrote:
hi,
it recently came to my attention that
On Wed, Jul 23, 2014 at 9:34 PM, Julian Taylor
jtaylor.deb...@googlemail.com wrote:
On 23.07.2014 22:04, Robert Kern wrote:
On Wed, Jul 23, 2014 at 8:50 PM, Julian Taylor
jtaylor.deb...@googlemail.com wrote:
On 23.07.2014 20:54, Robert Kern wrote:
On Wed, Jul 23, 2014 at 6:19 PM, Julian
On Wed, Jul 23, 2014 at 9:57 PM, Robert Kern robert.k...@gmail.com wrote:
That's what I'm suggesting that we change: make
`type(ndarray.shape[i])` be `np.intp` instead of `long`.
However, I'm not sure that this is an issue with numpy 1.8.0 at least.
I can't reproduce the reported problem on
On Wed, Jul 23, 2014 at 9:57 PM, Robert Kern robert.k...@gmail.com wrote:
That's perhaps what you want, but numpy has never claimed to do this.
The numpy project deliberately chose (and is so documented) to make
its default integer type a C long, not a C size_t, to match Python's
default.
23.07.2014, 20:37, Julian Taylor kirjoitti:
[clip: __numpy_ufunc__]
So its been a week and we got a few answers and new issues. To
summarize: - to my knowledge no progress was made on the issues -
scipy already has a released version using the current
implementation - no very loud objections
Julian Taylor jtaylor.deb...@googlemail.com wrote:
The default integer dtype should be sufficiently large to index into any
numpy array, thats what I call an API here. win64 behaves different, you
have to explicitly upcast your index to be able to index all memory.
No, you don't have to
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