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]:
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
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, :] = 0.1
On Sun, Jul 22, 2012 at 8:54 AM, Dr.Leo fhaxbo...@googlemail.com 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
On Mon, Jul 16, 2012 at 3:06 PM, Paul Natsuo Kishimoto
m...@paul.kishimoto.name 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
On Fri, Jul 13, 2012 at 11:15 AM, Paul Natsuo Kishimoto
m...@paul.kishimoto.name 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()
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
On Tue, May 22, 2012 at 4:07 PM, Dan Goodman dg.gm...@thesamovar.net 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
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
regretted
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, credits
On Mon, May 7, 2012 at 3:30 PM, Charles R Harris
charlesr.har...@gmail.com wrote:
On Mon, May 7, 2012 at 7:28 AM, Tom Aldcroft aldcr...@head.cfa.harvard.edu
wrote:
Sorry to bother again, but I am running into an issue with the numpy
quaternion dtype on numpy 1.6.1 :
$ python
ActivePython
wrote:
On Sat, May 5, 2012 at 11:55 AM, Charles R Harris
charlesr.har...@gmail.com wrote:
On Sat, May 5, 2012 at 5:27 AM, Tom Aldcroft
aldcr...@head.cfa.harvard.edu wrote:
On Fri, May 4, 2012 at 11:44 PM, Ilan Schnell ischn...@enthought.com
wrote:
Hi Chuck,
thanks for the prompt reply
I ran into a problem trying to build and import the numpy_quaternion
extension on CentOS-5 x86_64:
$ python setup.py build
SNIP
C compiler: gcc -pthread -fno-strict-aliasing -fPIC -g -O2 -DNDEBUG -g
-fwrapv -O3 -Wall -Wstrict-prototypes -fPIC
compile options:
On Fri, May 4, 2012 at 11:44 PM, Ilan Schnell ischn...@enthought.com 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
On Sat, May 5, 2012 at 12:55 PM, Charles R Harris
charlesr.har...@gmail.com wrote:
On Sat, May 5, 2012 at 5:27 AM, Tom Aldcroft aldcr...@head.cfa.harvard.edu
wrote:
On Fri, May 4, 2012 at 11:44 PM, Ilan Schnell ischn...@enthought.com
wrote:
Hi Chuck,
thanks for the prompt reply. I
On Sat, Mar 31, 2012 at 2:25 AM, Prashant Saxena animator...@yahoo.com 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 =
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
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