Is this with 1.7? There see a few memory leak fixes in 1.7, so if you
aren't using that you should try it to be sure. And if you are using it,
then there is one known memory leak bug in 1.7 that you might want to check
whether you're hitting:
https://github.com/numpy/numpy/issues/2969
-n
On 25 Feb
On Mon, Feb 25, 2013 at 9:58 PM, wrote:
> On Mon, Feb 25, 2013 at 9:20 PM, Sebastian Berg
> wrote:
>> On Mon, 2013-02-25 at 10:50 -0500, Skipper Seabold wrote:
>>> On Mon, Feb 25, 2013 at 10:43 AM, Till Stensitzki
>>> wrote:
>>> >
>>> > First, sorry that i didnt search for an old thread, but be
On Mon, Feb 25, 2013 at 9:20 PM, Sebastian Berg
wrote:
> On Mon, 2013-02-25 at 10:50 -0500, Skipper Seabold wrote:
>> On Mon, Feb 25, 2013 at 10:43 AM, Till Stensitzki
>> wrote:
>> >
>> > First, sorry that i didnt search for an old thread, but because i
>> disagree with
>> > conclusion i would at
On Mon, 2013-02-25 at 10:50 -0500, Skipper Seabold wrote:
> On Mon, Feb 25, 2013 at 10:43 AM, Till Stensitzki
> wrote:
> >
> > First, sorry that i didnt search for an old thread, but because i
> disagree with
> > conclusion i would at least address my reason:
> >
> >> I don't like
> >> np.abs(arr)
I'm hoping this discussion will return to the drawing the line question.
http://stackoverflow.com/questions/8108688/in-python-when-should-i-use-a-function-instead-of-a-method
Alan Isaac
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On Mon, Feb 25, 2013 at 7:49 PM, wrote:
> On Mon, Feb 25, 2013 at 7:11 PM, Charles R Harris
> wrote:
>>
>>
>> On Sat, Feb 23, 2013 at 1:33 PM, Robert Kern wrote:
>>>
>>> On Sat, Feb 23, 2013 at 7:25 PM, Nathaniel Smith wrote:
>>> > On Sat, Feb 23, 2013 at 3:38 PM, Till Stensitzki
>>> > wrote:
On Mon, Feb 25, 2013 at 7:11 PM, Charles R Harris
wrote:
>
>
> On Sat, Feb 23, 2013 at 1:33 PM, Robert Kern wrote:
>>
>> On Sat, Feb 23, 2013 at 7:25 PM, Nathaniel Smith wrote:
>> > On Sat, Feb 23, 2013 at 3:38 PM, Till Stensitzki
>> > wrote:
>> >> Hello,
>> >> i know that the array object is a
On Sat, Feb 23, 2013 at 1:33 PM, Robert Kern wrote:
> On Sat, Feb 23, 2013 at 7:25 PM, Nathaniel Smith wrote:
> > On Sat, Feb 23, 2013 at 3:38 PM, Till Stensitzki
> wrote:
> >> Hello,
> >> i know that the array object is already crowded, but i would like
> >> to see the abs method added, especi
Josef's suggestion is the first thing I'd try.
Are you doing any of this in C ? It is easy to end up duplicating memory
that you need to Py_DECREF .
In the C debugger you should be able to monitor the ref count of your
python objects.
btw, for manual tracking of reference counts you can do,
sy
On Mon, 2013-02-25 at 18:01 +0100, Todd wrote:
> The problem with b is that it breaks down if the two status have the
> same dimensionality.
>
> I think a better approach would be for
>
> a in b
>
> With a having n dimensions, it returns true if there is any subarray
> of b that matches a alon
On Mon, 2013-02-25 at 16:33 +, Nathaniel Smith wrote:
> On Mon, Feb 25, 2013 at 3:10 PM, Sebastian Berg
> wrote:
> > Hello all,
> >
> > currently the `__contains__` method or the `in` operator on arrays, does
> > not return what the user would expect when in the operation `a in b` the
> > `a`
On Mon, Feb 25, 2013 at 8:50 AM, Skipper Seabold wrote:
> On Mon, Feb 25, 2013 at 10:43 AM, Till Stensitzki
> wrote:
> >
> > First, sorry that i didnt search for an old thread, but because i
> disagree with
> > conclusion i would at least address my reason:
> >
> >> I don't like
> >> np.abs(arr).
The problem with b is that it breaks down if the two status have the same
dimensionality.
I think a better approach would be for
a in b
With a having n dimensions, it returns true if there is any subarray of b
that matches a along the last n dimensions.
So if a has 3 dimensions and b has 6, a i
On Mon, Feb 25, 2013 at 3:10 PM, Sebastian Berg
wrote:
> Hello all,
>
> currently the `__contains__` method or the `in` operator on arrays, does
> not return what the user would expect when in the operation `a in b` the
> `a` is not a single element (see "In [3]-[4]" below).
True, I did not expec
On Mon, Feb 25, 2013 at 8:41 AM, Jaakko Luttinen
wrote:
> Hi!
>
> I was wondering if anyone could help me in finding a memory leak problem
> with NumPy. My project is quite massive and I haven't been able to
> construct a simple example which would reproduce the problem..
>
> I have an iterative a
On Mon, Feb 25, 2013 at 10:43 AM, Till Stensitzki wrote:
>
> First, sorry that i didnt search for an old thread, but because i
disagree with
> conclusion i would at least address my reason:
>
>> I don't like
>> np.abs(arr).max()
>> because I have to concentrate to much on the braces, especially if
I added allocation tracking tools to numpy for exactly this reason.
They are not very well documented, but you can see how to use them
here:
https://github.com/numpy/numpy/tree/master/tools/allocation_tracking
Ray
On Mon, Feb 25, 2013 at 8:41 AM, Jaakko Luttinen
wrote:
> Hi!
>
> I was wonderi
On Sat, Feb 23, 2013 at 9:34 PM, Benjamin Root wrote:
>
> My issue is having to remember which ones are methods and which ones are
> functions. There doesn't seem to be a rhyme or reason for the choices, and
> I would rather like to see that a line is drawn, but I am not picky as to
> where it is
First, sorry that i didnt search for an old thread, but because i disagree with
conclusion i would at least address my reason:
> I don't like
> np.abs(arr).max()
> because I have to concentrate to much on the braces, especially if arr
> is a calculation
This exactly, adding an abs into an old e
Hello all,
currently the `__contains__` method or the `in` operator on arrays, does
not return what the user would expect when in the operation `a in b` the
`a` is not a single element (see "In [3]-[4]" below).
The first solution coming to mind might be checking `all()` for all
dimensions given i
Hi!
I was wondering if anyone could help me in finding a memory leak problem
with NumPy. My project is quite massive and I haven't been able to
construct a simple example which would reproduce the problem..
I have an iterative algorithm which should not increase the memory usage
as the iteration
I submitted a bug report (and patch) to cx_freeze. You can follow up with
them at http://sourceforge.net/p/cx-freeze/bugs/36/.
-Brad
On Mon, Feb 25, 2013 at 12:06 AM, Gelin Yan wrote:
>
>
> On Mon, Feb 25, 2013 at 3:53 PM, Bradley M. Froehle <
> brad.froe...@gmail.com> wrote:
>
>> I can repro
On Mon, Feb 25, 2013 at 3:53 PM, Bradley M. Froehle
wrote:
> I can reproduce with NumPy 1.7.0, but I'm not convinced the bug lies
> within NumPy.
>
> The exception is not being raised on the `del sys` line. Rather it is
> being raised in numpy.__init__:
>
> File
> "/home/bfroehle/.local/lib/pyt
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