> On May 26th, I sent an email titled "curious about how people would
> feel about moving to github."
Should we really be supporting Ruby like that ;)
Personally I am an idiot when to comes to SVN, so a move to GitHub might
make it easier for me to contribute.
Sturla
_
On 07/13/2010 04:05 PM, Christopher Barker wrote:
> Robert Kern wrote:
>
>>> I don't believe that there are any such options, but is there a particular
>>> reason why you *don't* want to use such external libs if you have them? I
>>> don't think anyone has considered a use-case where one would
On Tue, Jul 13, 2010 at 8:15 PM, Charles R Harris
wrote:
> How should we handle commits during the next week or two? I have a few
> things I want to get in before 1.5 is tagged.
Just keep committing as normal using svn for now. Once we are ready
to make the transition (which includes having docu
On Tue, Jul 13, 2010 at 8:20 PM, Jarrod Millman wrote:
> Hello all,
>
> On May 26th, I sent an email titled "curious about how people would
> feel about moving to github." While there were a few concerns raised,
> everyone was generally positive and were mainly concerned that this
> transition wo
This is awesome! I love github. I really wanted to champion for its
use at the BoF but unfortunately missed it.
--Josh
On Tue, Jul 13, 2010 at 6:20 PM, Jarrod Millman wrote:
> Hello all,
>
> On May 26th, I sent an email titled "curious about how people would
> feel about moving to github." Whil
Hello all,
On May 26th, I sent an email titled "curious about how people would
feel about moving to github." While there were a few concerns raised,
everyone was generally positive and were mainly concerned that this
transition would need to be done carefully with clear workflow
instructions and
On Tue, Jul 13, 2010 at 12:45 PM, Kurt Smith wrote:
> On Tue, Jul 13, 2010 at 11:54 AM, John Reid
> wrote:
> > Hi,
> >
> > I have some arrays of various shapes in which I need to set any NaNs to
> > 0. I have been doing the following:
> >
> > a[numpy.where(numpy.isnan(a)] = 0.
> >
> >
> >
> > as
On Tue, Jul 13, 2010 at 3:05 PM, Christopher Barker
wrote:
> Robert Kern wrote:
> >> I don't believe that there are any such options, but is there a
> particular
> >> reason why you *don't* want to use such external libs if you have them?
> I
> >> don't think anyone has considered a use-case wher
Robert Kern wrote:
>> I don't believe that there are any such options, but is there a particular
>> reason why you *don't* want to use such external libs if you have them? I
>> don't think anyone has considered a use-case where one would want to ignore
>> such libraries.
>
> Building redistributa
On Tue, Jul 13, 2010 at 14:39, Benjamin Root wrote:
> Stefan,
>
> I don't believe that there are any such options, but is there a particular
> reason why you *don't* want to use such external libs if you have them? I
> don't think anyone has considered a use-case where one would want to ignore
>
Stefan,
I don't believe that there are any such options, but is there a particular
reason why you *don't* want to use such external libs if you have them? I
don't think anyone has considered a use-case where one would want to ignore
such libraries.
Ben Root
On Sat, Jul 10, 2010 at 11:15 AM, S
On Tue, Jul 13, 2010 at 10:36 AM, Pauli Virtanen wrote:
> ti, 2010-07-13 kello 10:06 -0700, Keith Goodman kirjoitti:
>> No need to use where. You can just do a[np.isnan(a)] = 0. But you do
>> have to watch out for 0d arrays, can't index into those.
>
> You can, but the index must be appropriate:
>
On Tue, Jul 13, 2010 at 10:45 AM, Kurt Smith wrote:
> You could make use of np.atleast_1d, and then everything would be
> canonicalized:
>
> In [33]: a = np.array(np.nan)
>
> In [34]: a
> Out[34]: array(nan)
>
> In [35]: a1d = np.atleast_1d(a)
>
> In [36]: a1d
> Out[36]: array([ NaN])
>
> In [37
On Tue, Jul 13, 2010 at 11:54 AM, John Reid wrote:
> Hi,
>
> I have some arrays of various shapes in which I need to set any NaNs to
> 0. I have been doing the following:
>
> a[numpy.where(numpy.isnan(a)] = 0.
>
>
>
> as you can see here:
>
> In [20]: a=numpy.ones(2)
>
> In [21]: a[1]=numpy.log(-1
ti, 2010-07-13 kello 10:06 -0700, Keith Goodman kirjoitti:
> No need to use where. You can just do a[np.isnan(a)] = 0. But you do
> have to watch out for 0d arrays, can't index into those.
You can, but the index must be appropriate:
>>> x = np.array(4)
>>> x[()] = 3
>>> x
array(3)
_
On Tue, Jul 13, 2010 at 9:54 AM, John Reid wrote:
> Hi,
>
> I have some arrays of various shapes in which I need to set any NaNs to
> 0. I have been doing the following:
>
> a[numpy.where(numpy.isnan(a)] = 0.
>
> as you can see here:
>
> In [20]: a=numpy.ones(2)
>
> In [21]: a[1]=numpy.log(-1)
>
>
Hi,
I have some arrays of various shapes in which I need to set any NaNs to
0. I have been doing the following:
a[numpy.where(numpy.isnan(a)] = 0.
as you can see here:
In [20]: a=numpy.ones(2)
In [21]: a[1]=numpy.log(-1)
In [22]: a
Out[22]: array([ 1., NaN])
In [23]: a[numpy.where(numpy
On Tue, Jul 13, 2010 at 4:31 AM, Wes McKinney wrote:
> On Tue, Jul 13, 2010 at 8:26 AM, Sebastian Haase wrote:
>> On Tue, Jul 13, 2010 at 2:20 PM, William Johnston
>> wrote:
>>> Hello,
>>>
>>> I simply installed numpy in my Python26 installation, and then copied the
>>> numpy directory to my si
On Sat, Jul 10, 2010 at 7:51 PM, Peter <
numpy-discuss...@maubp.freeserve.co.uk> wrote:
> On Fri, Jul 9, 2010 at 4:27 PM, Christoph Gohlke wrote:
> > On 7/9/2010 7:11 AM, Peter wrote:
> >> I was going to ask if someone could build Windows installers for
> >> NumPy 1.4.1 on Python 2.7 (to facilita
On Mon, Jul 12, 2010 at 6:44 PM, Nathaniel Peterson
wrote:
> Wes McKinney writes:
>
>> Did you mean to post a different link? That's the ticket I just created :)
>
> How silly of me! I meant http://projects.scipy.org/numpy/ticket/1427
> ___
> NumPy-Disc
Ryan May writes:
> On Mon, Jul 12, 2010 at 8:04 AM, Neil Crighton wrote:
>> Gael Varoquaux normalesup.org> writes:
>>> I do such manipulation all the time, and keeping track of which axis is
>>> what is fairly tedious and error prone. It would be much nicer to be able
>>> to write:
>>>
>>>
On Tue, Jul 13, 2010 at 8:26 AM, Sebastian Haase wrote:
> On Tue, Jul 13, 2010 at 2:20 PM, William Johnston
> wrote:
>> Hello,
>>
>> I simply installed numpy in my Python26 installation, and then copied the
>> numpy directory to my site-packages folder of my IronPython installation.
>>
>> Did I
On Tue, Jul 13, 2010 at 2:20 PM, William Johnston wrote:
> Hello,
>
> I simply installed numpy in my Python26 installation, and then copied the
> numpy directory to my site-packages folder of my IronPython installation.
>
> Did I miss any installation steps in doing so? The multiarray module coul
Hello,
I simply installed numpy in my Python26 installation, and then copied the
numpy directory to my site-packages folder of my IronPython installation.
Did I miss any installation steps in doing so? The multiarray module could
not be found using IronPython.
Thanks.
___
> Not really. 1-D structured arrays can and do work well for the very
> common case where one has unlabeled rows and labeled columns. They are
> also a little bit more flexible in that the columns can be
> heterogeneous in dtype, as columns are wont to do.
>
> May I politely suggest that, just as s
25 matches
Mail list logo
