> On 16 Oct 2016, at 03:21, Allan Haldane wrote:
>
>> On 10/14/2016 07:49 PM, Juan Nunez-Iglesias wrote:
>> +1 for propagate_mask. That is the only proposal that immediately makes
>> sense to me. "contagious" may be cute but I think approximately 0% of
>> users would guess its purpose on first
> On 03 Apr 2015, at 00:04, Colin J. Williams wrote:
>
>
>
> On 02-Apr-15 4:35 PM, Eric Firing wrote:
>> On 2015/04/02 10:22 AM, josef.p...@gmail.com wrote:
>>> Swapping the axis when slices are mixed with fancy indexing was a
>>> design mistake, IMO. But not fancy indexing itself.
>> I'm not
> On 17 Mar 2015, at 09:11, Dieter Van Eessen
> wrote:
>
> Hello,
>
> Sorry to disturb again, but the topic still bugs me somehow...
> I'll try to rephrase the question:
>
> - What's the influence of the type of N-array representation with respect to
> TENSOR-calculus?
> - Are multiple repre
> On 14.03.2015, at 10:57, Danny Kramer wrote:
>
> Hi,
> I am getting the following error message:
>
> C:\Python27\lib\site-packages\numpy\lib\npyio.py:819: UserWarning: loadtxt:
> Empty input file: "[]"
> warnings.warn('loadtxt: Empty input file: "%s"' % fname)
> main loop list assignment
On 18.10.2013 12:33, Pooja Gupta wrote:
> I have generated random point around a object and then evaluate each
> random point on certain criteria. But problem is that every time I am
> getting new point. How i can resolve this problem so that my result
> should be uniform. Is any way to evaluate th
Hi Stefan,
I would be happy to file a pull request against the docs if you (or
somebody) could point me to a document on how and where to do that.
Hanno
On 24.07.2013 12:31, Stéfan van der Walt wrote:
> Hi Hanno
>
> On Wed, Jul 24, 2013 at 11:46 AM, Hanno Klemm
> wrote:
&g
Hi,
I found the following inconsistency between the advertised and the
actual behviour of structured arrays:
on http://docs.scipy.org/doc/numpy/user/basics.rec.html it says in the
section
"Accessing multiple fields at once"
Notice that the fields are always returned in the same order regardle
Skipper,
this looks like a problem that I had in the bad old days with ATLAS, as well.
Try compiling openblas with the -fPIC flag that used to help.
Best of luck,
Hanno
hanno.kl...@me.com
Sent from my mobile device, please excuse my brevity.
On 23.03.2013, at 19:19, Skipper Seabold wrote:
ue-in-pythons-numpy
>
> ___
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Am 28.06.2012 um 23:07 schrieb Matthew Brett:
> Hi,
>
> On Thu, Jun 28, 2012 at 1:42 PM, srean wrote:
>> In case this changes your mind (or assuages fears) just wanted to
>> point out that many open source projects do this. It is not about
>> claiming that one is more important than the other, n
Hi,
have a look at scipy optimize. For a solution with only positive values you
could consider using scipy.optimize.nnls, if you want more general (linear)
constraints, have a look at the linear programming functions.
Another possibility would be looking at openOpt, which has probably more
g
Hi,
this should work:
import numpy as np
ndim = 20
cube = np.random.rand(32,ndim, ndim)
result = np.zeros([ndim, ndim], np.float32)
def combine(cube, result):
for ii in range(ndim):
for jj in range(ndim):
result[ii, jj] = np.sqrt((cube[:,ii, jj])).sum()
return
Am 27.01.2011 um 00:29 schrieb Mark Wiebe:
On Wed, Jan 26, 2011 at 3:18 PM, Hanno Klemm
wrote:
Mark,
interesting idea. Given the fact that in 2-d euclidean metric, the
Einstein summation conventions are only a way to write out
conventional matrix multiplications, do you consider at some
Mark,
interesting idea. Given the fact that in 2-d euclidean metric, the
Einstein summation conventions are only a way to write out
conventional matrix multiplications, do you consider at some point to
include a non-euclidean metric in this thing? (As you have in special
relativity, for e
Hi,
I have the following question, that I could not find an answer to in the
example list, or by googling:
I have a record array with dtype such as:
dtype([('times', 'http://projects.scipy.org/mailman/listinfo/numpy-discussion
; prevents the Delaunay triangulation algorithm from completing its
>> task.
>>
>> Question, is there an efficent way, of getting rid of the duplicate
>> entries?
>> All I can think of involves loops.
>>
>> Thanks and regards,
>> Hanno
>
> __
?
All I can think of involves loops.
Thanks and regards,
Hanno
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N.array([1.,0,0,0,0,0,0])
>>> N.correlate(x,y2, mode='full')
array([ 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0.])
>>> N.__version__
'1.1.1'
>>>
Best regards,
Hanno
Stéfan van der Walt <[EMAIL PROTECTED]> said:
> Hi Hanno
>
>
-Type: text/plain; charset=ISO-8859-1
> Content-Transfer-Encoding: quoted-printable
> Content-Disposition: inline
>
> 2008/8/20 Hanno Klemm <[EMAIL PROTECTED]>:
> > In [29]: x =3D array([0.,0.,1, 0, 0])
> > In [35]: y1 =3D array([1,0,0,0,0])
> >
> > In [36]: cor
y help would be appreciated, the numpy
version is 1.0.4.
Best regards,
Hanno
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that with
ndarrays, or is there?
Cheers,
Hanno
Francesc Alted <[EMAIL PROTECTED]> said:
> A Friday 30 May 2008, Hanno Klemm escrigué:
> > Hi,
> >
> > I try to save the contents of a numpy recarray with PyTables into a
> > file. That works well, however, if I
escription := {
"id": Int32Col(shape=(), dflt=0, pos=0),
"x": Float64Col(shape=(), dflt=0.0, pos=1),
"y": Float64Col(shape=(), dflt=0.0, pos=2)}
byteorder := 'little'
chunkshape := (409,)
>>> f.close()
>>> f = t.openFile('test.h5',
e=1e+20)
>>> a+=b
>>> a
array([[ 1., 2., 3.],
[ 0., 3., 0.],
[ 4., 5., 6.]])
>>> N.__version__
'1.0.4'
>>>
Best regards,
Hanno
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.88353492
+4.13682075e-08j,
5.3595916
-2.06841037e-08j], [
> 3.8064764 +1.03420519e-08j, 5.3595916
-2.06841037e-08j,
6.9127068 +1.03420519e-08j]])>>>
sqrtm(a)*sqrtm(a)array([[ 25.08487289 +1.03595922e-07j,
19.42586452
-1.82329475e-07j,
> 14.48926259
+7.87335527e-08j
Didrik,
thanks, I'll definitely will have a look at this.
Hanno
Didrik Pinte <[EMAIL PROTECTED]> said:
>
> --=-aUNlfGW7wc8MzGzdSDGo
> Content-Type: text/plain
> Content-Transfer-Encoding: quoted-printable
>
> On Mon, 2007-06-25 at 23:09 +0200, Hanno Klemm wr
I will try and dig a bit more in the literature, maybe I find something.
Hanno
On Jun 25, 2007, at 4:59 PM, Timothy Hochberg wrote:
>
>
>
> On 6/25/07, Hanno Klemm < [EMAIL PROTECTED]> wrote:
>> Tim,
>>
>> Thank you very much, the code does what's it e
max(i*binsize, 1)
> j1 = min(j0+binsize, n)
> denominator = 0
> for j in range(j0, j1):
> d2 = (data[...,j:] - data[...,:-j])**2
> result[i] += d2.sum()
> denominator += N.prod(d2.shape)
> resu
hberg <[EMAIL PROTECTED]> said:
> --=_Part_157389_1558912.1182523880067
> Content-Type: text/plain; charset=ISO-8859-1; format=flowed
> Content-Transfer-Encoding: 7bit
> Content-Disposition: inline
>
> On 6/22/07, Hanno Klemm <[EMAIL PROTECTED]> wrote:
> >
> >
> > Hi,
> >
>
Hi,
I have an array which represents regularly spaced spatial data. I now
would like to compute the (semi-)variogram, i.e.
gamma(h) = 1/N(h) \sum_{i,j\in N(h)} (z_i - z_j)**2,
where h is the (approximate) spatial difference between the
measurements z_i, and z_j, and N(h) is the number of measur
changes are in
> the svn. So, I don't think this is an issue that has arisen due to the
> changes unless you have checked numpy out recently and compiled it
> yourself.
>
> MJ
>
> -Original Message-
> From: [EMAIL PROTECTED]
> [mailto:[EMAIL PROTECTED] On Be
/proj/yot04/apps/python2.5/lib/python2.5/site-packages/numpy/core/__init__.py",
line 5, in
import multiarray
ImportError: No module named multiarray
Am I doing something wrong? Or does freeze.py not work with numpy?
Hanno
--
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[EMAIL PROTECTED]
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rom
[0,1,...,n/2-1,-n/2,...-1]
Is this inconsistent or am I missing something here?
Hanno
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