I was just about to submit some pull requests for fixes to the
_gufuncs_linalg module and discovered that it no longer exists. It looks
like it was removed in this
commithttps://github.com/numpy/numpy/commit/0f516827dd081625b8b2262297be57ac855a9bb5.
Is there any reason why it was removed without
answers my question.
-Jay
On Tue, Mar 18, 2014 at 12:36 PM, Nathaniel Smith n...@pobox.com wrote:
On Tue, Mar 18, 2014 at 5:26 PM, Jay Bourque jay.bour...@continuum.io
wrote:
I was just about to submit some pull requests for fixes to the
_gufuncs_linalg module and discovered
I would love to get the following pull requests of mine merged in:
https://github.com/numpy/numpy/pull/2822
https://github.com/numpy/numpy/pull/462
https://github.com/numpy/numpy/pull/359
https://github.com/numpy/numpy/pull/2821
The last one probably requires a bit more work, but I'm still
, Oct 1, 2012 at 10:36 AM, Jay Bourque jay.bour...@continuum.iowrote:
All,
I've submitted the following pull request for NumPy:
https://github.com/numpy/numpy/pull/462
This change allows ufuncs to be registered for structured arrays by using
a new API method PyUFunc_RegisterLoopForStructType
All,
I've submitted the following pull request for NumPy:
https://github.com/numpy/numpy/pull/462
This change allows ufuncs to be registered for structured arrays by using a
new API method PyUFunc_RegisterLoopForStructType. For example, a ufunc
could be registered to take two arrays of type
...@gmail.com
wrote:
On Wed, Jul 25, 2012 at 10:29 AM, Jay Bourque jay.bour...@continuum.io
wrote:
I'm actively looking at this issue since it was my pull request that
broke
this (https://github.com/numpy/numpy/pull/350). We definitely don't
want to
break this functionality for 1.7. The problem
Ondrej,
Just submitted the following pull request for this:
https://github.com/numpy/numpy/pull/401
-Jay
On Fri, Aug 31, 2012 at 12:09 PM, Ondřej Čertík ondrej.cer...@gmail.comwrote:
On Fri, Aug 31, 2012 at 6:15 AM, Jay Bourque jay.bour...@continuum.io
wrote:
Ondrej,
Sorry
I'm actively looking at this issue since it was my pull request that broke
this (https://github.com/numpy/numpy/pull/350). We definitely don't want to
break this functionality for 1.7. The problem is that even though indexing
with a subset of fields still returns a copy (for now), it now returns a
Just added PR #359. The purpose is to allow the nditer object operand and
iter flags to be set for a ufunc to provide better control over how an
array is iterated over by a ufunc and how the ufunc uses the operands
passed to it. One specific motivation for this is to be able to specify an
input
Travis can better speak to specific use cases, but one example where this
might be useful is an in place ufunc, or a ufunc operand that's
broadcasted and can hold a reduce value.
On Sun, Jul 15, 2012 at 2:23 PM, Nathaniel Smith n...@pobox.com wrote:
On Sun, Jul 15, 2012 at 6:18 PM, jay bourque
mapping of text files?
7. Eventually reduce memory usage even more by using same object for
duplicate values in array (depends on implementing enum dtype?)
Anything else?
-Jay Bourque
continuum.io
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be available to help you with
porting/testing your code with numpy, or I can take what you have and build on
it in my numpy fork on github.
-Jay Bourque
Continuum IO
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