The attached program leaks about 24 bytes per loop. The comments give a
bit more detail as to when the leak occurs and doesn't. How can I track
down where this leak is actually coming from?
Here is a sample run on my machine:
$ python simple.py
Python Version: 2.7.3 (default, Apr 20 2012, 22:
On Fri, Jul 20, 2012 at 10:11 AM, Andreas Hilboll wrote:
> Hi,
>
> I have a problem using histogram2d:
>
>from numpy import linspace, histogram2d
>bins_x = linspace(-180., 180., 360)
>bins_y = linspace(-90., 90., 180)
>data_x = linspace(-179.96875, 179.96875, 5760)
>data_y = li
Hi,
On Fri, Jul 20, 2012 at 6:42 PM, yogesh karpate wrote:
> I think since its a joint histogram, you need to have equal no. of data
> points and bins
> in both x and y.
Makes sense that number of elements of data points (x, y) is equal. Perhaps
the documentation like
http://docs.scipy.org/doc/n
20.07.2012 22:17, OC kirjoitti:
> The syntax "numpy.complex(A)" seems to be the most natural and obvious
> thing a user would want for casting an array A to complex values.
I think I disagree here -- that something like that works at all is
rather surprising. Remember that
numpy.complex,
==
Announcing PyTables 2.4.0
==
We are happy to announce PyTables 2.4.0.
This is an incremental release which includes many changes to prepare
for future Python 3 support.
What's new
==
This release includes support for the float16 data t
On Fri, Jul 20, 2012 at 1:17 PM, OC wrote:
>> numpy.complex is just a reference to the built in complex, so only works
>> on scalars:
> What is the use of storing the "complex()" built-in function in the
> numpy namespace, when it is already accessible from everywhere?
for consitancy with teh r
The syntax "numpy.complex(A)" seems to be the most natural and obvious
thing a user would want for casting an array A to complex values.
Expressions like "A.astype(complex)", "array(A, dtype=complex)",
"numpy.complex128(A)" are less obvious, especially the last two ones,
which look a bit far-fe
On Thu, Jul 19, 2012 at 4:58 PM, Ondřej Čertík wrote:
>
> So I have tried the MinGW-5.0.3.exe in Wine, but it tries to install
> from some wrong url and it fails to install.
> I have unpacked the tarballs by hand into "~/.wine/drive_c/MinGW":
>
> binutils-2.17.50-20070129-1.tar.gz
> w32api-3.7.ta
On Fri, Jul 20, 2012 at 12:24 PM, Ondřej Čertík wrote:
>>> So I have tried the MinGW-5.0.3.exe in Wine, but it tries to install
>>> from some wrong url and it fails to install.
>>> I have unpacked the tarballs by hand into "~/.wine/drive_c/MinGW":
>>>
>> Not surprising, that MinGW is really gettin
I think since its a joint histogram, you need to have equal no. of data
points and bins
in both x and y.
On Fri, Jul 20, 2012 at 5:11 PM, Andreas Hilboll wrote:
> Hi,
>
> I have a problem using histogram2d:
>
>from numpy import linspace, histogram2d
>bins_x = linspace(-180., 180., 360)
>
Hi,
I have a problem using histogram2d:
from numpy import linspace, histogram2d
bins_x = linspace(-180., 180., 360)
bins_y = linspace(-90., 90., 180)
data_x = linspace(-179.96875, 179.96875, 5760)
data_y = linspace(-89.96875, 89.96875, 2880)
histogram2d(data_x, data_y, (bins_x,
On Fri, Jul 20, 2012 at 1:50 PM, Ondřej Čertík wrote:
> On Wed, Jul 18, 2012 at 8:09 AM, Travis Oliphant wrote:
>>
>> Hey all,
>>
>> We are going to work on a beta release on the 1.7.x branch.The master is
>> open again for changes for 1.8.x. There will be some work on the 1.7.x
>> branch
On Wed, Jul 18, 2012 at 8:09 AM, Travis Oliphant wrote:
>
> Hey all,
>
> We are going to work on a beta release on the 1.7.x branch.The master is
> open again for changes for 1.8.x. There will be some work on the 1.7.x
> branch to fix bugs including bugs that are already reported but have
>> So I have tried the MinGW-5.0.3.exe in Wine, but it tries to install
>> from some wrong url and it fails to install.
>> I have unpacked the tarballs by hand into "~/.wine/drive_c/MinGW":
>>
> Not surprising, that MinGW is really getting old. It's still the last
> available one with gcc 3.x as II
On 20-Jul-2012 11:34, Andreas Hilboll wrote:
>> Hi,
>>
>> I am pleased to announce the availability of the first release candidate
>> of
>> SciPy 0.11.0. For this release many new features have been added, and over
>> 120 tickets and pull requests have been closed. Also noteworthy is that
>> the
>>
On Thu, Jul 19, 2012 at 5:52 AM, Cheng Li wrote:
> Hi All,
>
> ** **
>
> I have spot a strange behavior of numpy.fromfunction(). The sample codes
> are as follows:
>
> >>> import numpy as np
>
> >>> def myOnes(i,j):
>
> return 1.0
>
> >>> a = np.fromfunction(myO
> Hi,
>
> I am pleased to announce the availability of the first release candidate
> of
> SciPy 0.11.0. For this release many new features have been added, and over
> 120 tickets and pull requests have been closed. Also noteworthy is that
> the
> number of contributors for this release has risen to
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