Charles R Harris wrote:
>
>
> On Tue, Dec 16, 2008 at 8:59 PM, David Cournapeau
> mailto:da...@ar.media.kyoto-u.ac.jp>>
> wrote:
>
> Hi,
>
>There have been some changes recently in the umath code, which
> breaks windows 64 compilation - and I don't understand their rationale
> e
On Tue, Dec 16, 2008 at 8:59 PM, David Cournapeau <
da...@ar.media.kyoto-u.ac.jp> wrote:
> Hi,
>
>There have been some changes recently in the umath code, which
> breaks windows 64 compilation - and I don't understand their rationale
> either. I have myself spent quite a good deal of time to m
Hi,
There have been some changes recently in the umath code, which
breaks windows 64 compilation - and I don't understand their rationale
either. I have myself spent quite a good deal of time to make sure this
works on many platforms/toolchains, by fixing the config distutils
command and that
On Wed, Dec 17, 2008 at 5:09 AM, Lin Shao wrote:
> Hi,
>
> I found this earlier dialog about refactoring umathmodule.c (see
> bottom) where David mentioned it wasn't tested on 64-bit Windows.
>
> I tried compiling numpy 1.3.0.dev6118 on both a 32-bit and 64-bit
> Windows for Python 2.6.1 with VS 9
On Dec 16, 2008, at 1:57 PM, Ryan May wrote:
> I just noticed the following and I was kind of surprised:
>
a = ma.MaskedArray([1,2,3,4,5], mask=[False,True,True,False,False])
b = a*5
b
> masked_array(data = [5 -- -- 20 25],
> mask = [False True True False False],
> fi
Ryan,
OK, I'll look into that. I won't have time to address it before this
next week, however. Option #2 looks like the best.
In other news, I was considering renaming genloadtxt to genfromtxt,
and using ndfromtxt, mafromtxt, recfromtxt, recfromcsv for the
function names. That way, loadtxt i
Pierre GM wrote:
> All,
> Here's the latest version of genloadtxt, with some recent corrections.
> With just a couple of tweaking, we end up with some decent speed: it's
> still slower than np.loadtxt, but only 15% so according to the test at
> the end of the package.
I have one more use issue
Hi,
I found this earlier dialog about refactoring umathmodule.c (see
bottom) where David mentioned it wasn't tested on 64-bit Windows.
I tried compiling numpy 1.3.0.dev6118 on both a 32-bit and 64-bit
Windows for Python 2.6.1 with VS 9.0, and not surprisingly, it worked
on 32-bit but not on 64-bi
Hi,
I just noticed the following and I was kind of surprised:
>>>a = ma.MaskedArray([1,2,3,4,5], mask=[False,True,True,False,False])
>>>b = a*5
>>>b
masked_array(data = [5 -- -- 20 25],
mask = [False True True False False],
fill_value=99)
>>>b.data
array([ 5, 10, 15, 20,
On 12/16/2008 1:29 AM Jarrod Millman apparently wrote:
> Yes. Please don't start new moin wiki documentation. We have a good
> solution for documentation that didn't exist when the moin
> documentation was started. Either put new docs in the docstrings or
> in the scipy tutorial.
OK, in this c
There was an discussion about this on the c.l.p a while ago. Using a sort
will scale like O(n log n) or worse, whereas using a set (hash table) will
scale like amortized O(n). How to use a Python set to get a unique
collection of objects I'll leave to your imagination.
Sturla Molden
> On Mon, De
Thanks Daran,
that works like a charm!
Hanno
On Tue, Dec 16, 2008, Daran Rife said:
> Whoops! A hasty cut-and-paste from my IDLE session.
> This should read:
>
> import numpy as np
>
> a = [(x0,y0), (x1,y1), ...] # A numpy array, but could be a list
> l = a.tolist()
> l.sort()
> unique = [x
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