I'm seeing about a factor of 50 difference in performance between
sorting a random integer array versus sorting that same array viewed
as a structured array. Am I doing anything wrong here?
In [2]: x = np.random.randint(1, size=1)
In [3]: xarr = x.view(dtype=[('a', np.int)])
In [4]: tim
For library compatibility testing I'm trying to use numpy 1.4.1 with Python
2.7.3 on a 64-bit CentOS-5 platform. I installed a clean Python from
source (basically "./configure --prefix=$prefix ; make install") and then
installed numpy 1.4.1 with "python setup.py install".
The crash message begins
When comparing rows of a structured masked array I'm getting an
exception. A similar operation on an structured ndarray gives the
expected True/False result. Note that this exception only occurs if
one or more of the mask values are True, since otherwise both row
objects are np.void and the ndarr
There was a thread in January discussing the non-obvious behavior of
numpy.mean() for large arrays of float32 values [1]. This issue is
nicely discussed at the end of the numpy.mean() documentation [2] with
an example:
>>> a = np.zeros((2, 512*512), dtype=np.float32)
>>> a[0, :] = 1.0
>>> a[1, :]
On Sun, Jul 22, 2012 at 8:54 AM, Dr.Leo wrote:
> Hi,
>
> I am a seasoned numpy/pandas user mainly interested in financial
> applications. These and other applications would greatly benefit from a
> decimal data type with flexible rounding rules, precision etc.
>
> Yes, there is cdecimal, the tradi
On Mon, Jul 16, 2012 at 3:06 PM, Paul Natsuo Kishimoto
wrote:
> I've implemented this feature with skip_header=-1 as suggested by
> Pierre, and in doing so removed the regression. TravisBot seems to like
> it: https://github.com/numpy/numpy/pull/351
>
> On Mon, 2012-07-16 at 16:12 +0200, Pierre GM
On Fri, Jul 13, 2012 at 11:15 AM, Paul Natsuo Kishimoto
wrote:
> Hello everyone,
>
> I am a longtime NumPy user, and I just filed my first contribution to
> the code as pull request to fix what I felt was a bug in the behaviour
> of genfromtxt() https://github.com/numpy/numpy/pull/351
> It
On Tue, May 22, 2012 at 4:07 PM, Dan Goodman wrote:
> On 22/05/2012 18:20, Nathaniel Smith wrote:
>> I don't know of anything that the docs are lacking in particular. It's
>> just that subclassing in general is basically a special form of
>> monkey-patching: you have this ecosystem of cooperating
I came across this problem which appears to be new in numpy 1.6.2 (vs. 1.6.1):
In [17]: a = np.array([(1, )], dtype=[('a', 'i4')])
In [18]: ra = a.view(np.recarray)
In [19]: '{}'.format(ra[0])
---
RuntimeError
Over on the scipy-user mailing list there was a question about
subclassing ndarray and I was interested to see two responses that
seemed to imply that subclassing should be avoided.
>From Dag and Nathaniel, respectively:
"Subclassing ndarray is a very tricky business -- I did it once and
regrette
On Mon, May 7, 2012 at 3:30 PM, Charles R Harris
wrote:
>
>
> On Mon, May 7, 2012 at 7:28 AM, Tom Aldcroft
> wrote:
>>
>> Sorry to bother again, but I am running into an issue with the numpy
>> quaternion dtype on numpy 1.6.1 :
>>
>> $ python
>>
Sorry to bother again, but I am running into an issue with the numpy
quaternion dtype on numpy 1.6.1 :
$ python
ActivePython 2.7.1.4 (ActiveState Software Inc.) based on
Python 2.7.1 (r271:86832, Feb 7 2011, 11:30:54)
[GCC 4.0.2 20051125 (Red Hat 4.0.2-8)] on linux2
Type "help", "copyright", "cre
I ran into a problem trying to build and import the numpy_quaternion
extension on CentOS-5 x86_64:
$ python setup.py build
C compiler: gcc -pthread -fno-strict-aliasing -fPIC -g -O2 -DNDEBUG -g
-fwrapv -O3 -Wall -Wstrict-prototypes -fPIC
compile options:
'-I/data/cosmos2/ska/arch/x86_64-linux_Ce
;>>
>>>> On Sat, May 5, 2012 at 11:55 AM, Charles R Harris
>>>> wrote:
>>>>>
>>>>> On Sat, May 5, 2012 at 5:27 AM, Tom Aldcroft
>>>>> wrote:
>>>>>>
>>>>>> On Fri, May 4, 2012 at 11:44 PM, Ila
On Sat, May 5, 2012 at 12:55 PM, Charles R Harris
wrote:
>
>
> On Sat, May 5, 2012 at 5:27 AM, Tom Aldcroft
> wrote:
>>
>> On Fri, May 4, 2012 at 11:44 PM, Ilan Schnell
>> wrote:
>> > Hi Chuck,
>> >
>> > thanks for the prompt reply. I
On Fri, May 4, 2012 at 11:44 PM, Ilan Schnell wrote:
> Hi Chuck,
>
> thanks for the prompt reply. I as curious because because
> someone was interested in adding http://pypi.python.org/pypi/Quaternion
> to EPD, but Martin and Mark's implementation of quaternions
> looks much better.
Hi -
I'm a
On Sat, Mar 31, 2012 at 2:25 AM, Prashant Saxena wrote:
> Hi,
>
> I am sub-classing numpy.ndarry for vector array representation. The append
> function is like this:
>
> def append(self, other):
> self = numpy.append(self, [other], axis=0)
>
> Example:
> vary = VectorArray([v1, v2])
> #
This is not yet released (but will be in the near future):
http://readthedocs.org/docs/astropy/en/latest/table/index.html
https://github.com/astropy/astropy/blob/master/astropy/table/table.py
You can at least use this as an example of how to add rows and columns
to a structured array. Or be an e
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