On Sat, May 4, 2013 at 12:43 AM, Pauli Virtanen wrote:
> 26.04.2013 18:51, Robert Kern kirjoitti:
> [clip]
>> Right now, the recurring cost is kicking the www.scipy.org wiki every
>> once in a while under the deluge of spam.
>
> It's dying a slow death again.
>
On Thu, May 2, 2013 at 3:57 PM, Charles R Harris
wrote:
>
> On Thu, May 2, 2013 at 8:40 AM, Robert Kern wrote:
>>
>> On Thu, May 2, 2013 at 3:28 PM, Charles R Harris
>> wrote:
>> >
>> >
>> > On Thu, May 2, 2013 at 7:47 AM, Robert Kern
>
On Thu, May 2, 2013 at 3:28 PM, Charles R Harris
wrote:
>
>
> On Thu, May 2, 2013 at 7:47 AM, Robert Kern wrote:
>>
>> On Thu, May 2, 2013 at 2:38 PM, Charles R Harris
>> wrote:
>> >
>> > On Thu, May 2, 2013 at 7:28 AM, Robert Kern
>> &
On Thu, May 2, 2013 at 2:38 PM, Charles R Harris
wrote:
>
> On Thu, May 2, 2013 at 7:28 AM, Robert Kern wrote:
>>
>> On Thu, May 2, 2013 at 12:03 PM, Nathaniel Smith wrote:
>> > On 1 May 2013 23:12, "Charles R Harris"
>> > wrote:
>> >>
;t checked, but I assume that what multiple output argument ufuncs do
> is to return a tuple. You can't use a single array in the general case,
> because the multiple output types might not be homogenous.
Correct.
[~]
|19> np.modf.nout
2
[~]
|20> np.modf(np.linspace(0, 1, 5))
(array([
Different optimization flags
and compiler versions will probably also affect this, not just the
target architecture. It's possible that those are actually the source
of this observation.
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component will reduce a temporary.
> The same goes for constructing a complex, real + imag * 1j
Similarly, we can eliminate two temporaries here.
Both of the cases are probably best addressed by a single function.
The syntactic sugar of an np.i object is unnecessary, IMO.
imag = np.tocomplex
ilable in the Cephes library.
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to stop that is
to help finish the migration of content to the new static site:
https://github.com/scipy/scipy.org-new
I think the major TODO items there are the conversion of the Topical
Software and Cookbook pages. I can give dumps of the current wiki
pages to anyone who wants to help with that.
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orrectly, you'll need to point the numpy.scipy.org
> CNAME to a non-github IP, and install a HTTP redirect **or** a HTTPD
> rewrite on that IP. So we need to find a server to do that. Probably
> easiest to ask numfocus, right?
There's no need. We'll j
not clear exactly what it is referring to. Having an HTTP server
with an A record for numpy.scipy.org that just issues HTTP 301
redirects for everything? I can look into getting that set up.
https://help.github.com/articles/my-custom-domain-isn-t-working#multiple-domains-in-cname-file
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s no problem with including
the example that I wrote in the rollaxis() docstring.
In any case, whether you put the documentation in the rollaxis()
docstring or in one of the indexing/iteration sections, or
(preferably) both, I strongly encourage you to do that first and see
how it goes before addi
(3, 4, 6)
(3, 4, 6)
(3, 4, 6)
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lly left out of any tutorials or guides.
Then let's add it.
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On Thu, Apr 25, 2013 at 6:54 PM, Matthew Brett wrote:
> Hi,
>
> On Thu, Apr 25, 2013 at 10:42 AM, Robert Kern wrote:
>> On Thu, Apr 25, 2013 at 6:30 PM, Matthew Brett
>> wrote:
>>> So the decision has to be based on some estimate of:
>>>
>>> 1)
On Thu, Apr 25, 2013 at 6:30 PM, Matthew Brett wrote:
> Hi,
>
> On Thu, Apr 25, 2013 at 10:14 AM, Robert Kern wrote:
>> On Wed, Apr 24, 2013 at 10:37 PM, andrew giessel
>> wrote:
>>> Hello all-
>>>
>>> A while back I emailed the list about functio
makes this more visible for
> users, new and old, and I hope members of this list will agree it is worth
> adding to the namespace.
I'm afraid I don't. It's a just a reduced-functionality version of
rollaxis(). I don't think the additional name adds anything
substantial.
ays -- we developed savez for a reason...
> but maybe I just need to give it a shot and see how it works.
The rationale behind .npy format are laid out here:
https://github.com/numpy/numpy/blob/master/doc/neps/npy-format.txt
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s
array[()]gives a rank-3 view of the last 3 axes (i.e. all of them)
The rank-N-general rules look like so: For a rank-N array, an N-tuple
gives a scalar. Subsequent (N-M)-tuples gives appropriate rank-M views
picked out by the tuple.
I can't explain the scalar[()] behavior, though. :-)
ed by
those limitations, you should start using more full-fledged and
standard file formats.
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"""
>
> I also see:
>
> For a description of the ``.npy`` format, see `format`.
>
> but no idea where to find 'format' -- it looks like it should be a
> link in the Sphinx docs, but it's not.
It does seem to be missing from the docs.
https://github.com/numpy/numpy/blob/master/numpy/lib/format.py
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mpy.ndarray)
>
>
> This has been annoying, particular as rank-zero scalars are kind of a pain.
np.save() and company (and the NPY format itself) are for arrays, not
for scalars. np.save() uses an np.asanyarray() to coerce its input
which is why your scalar gets converted to a rank-zero arra
flow on
the 32-bit platform but won't on a 32-bit platform, but those are
usually indicative of bugs to be fixed.
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ask
general "numpy ecosystem" questions here as a starting point, one must
expect to be pointed to better resources when they exist and to follow
up there.
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e products, especially questions about their development
roadmaps. Whether or not it is "reasonable" or on-topic to ask here,
one won't get good answers here.
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On Wed, Apr 10, 2013 at 1:06 PM, Nathaniel Smith wrote:
> This kind of personal attack is never appropriate for this list. Please
> stop.
My apologies. I will stop.
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On Wed, Apr 10, 2013 at 12:30 PM, Dmitrey wrote:
>
>
> --- Исходное сообщение ---
> От кого: "Robert Kern"
> Дата: 9 апреля 2013, 14:29:43
>> Well, it's your software. You are free to make it as buggy as you wish, I
>> guess.
>
> Yes, and that
On Tue, Apr 9, 2013 at 4:15 PM, Dmitrey wrote:
>
>
> --- Исходное сообщение ---
> От кого: "Robert Kern"
> Дата: 16 марта 2013, 22:15:07
>
> On Sat, Mar 16, 2013 at 6:19 PM, Dmitrey wrote:
>>
>>
>> --- Исходное сообщение ---
>> От кого: &
just `PyArray` to my knowledge. Do you mean direct access to the
`data` member of the PyArrayObject struct? Yes, that is deprecated.
Use the PyArray_DATA() macro to get a `void*` pointer to the start of
the data.
http://docs.scipy.org/doc/numpy/reference/c-
On Sat, Mar 16, 2013 at 6:19 PM, Dmitrey wrote:
>
>
> --- Исходное сообщение ---
> От кого: "Robert Kern"
> Дата: 16 марта 2013, 19:54:51
>
> On Sat, Mar 16, 2013 at 10:39 AM, Matthieu Brucher
> wrote:
>> Even if they have different hashes, they can
to be used in the code snippet that Dmitrey showed.
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On Thu, Mar 14, 2013 at 11:00 AM, Neal Becker wrote:
> Robert Kern wrote:
>
>> On Wed, Mar 13, 2013 at 12:16 AM, Neal Becker wrote:
>>> I guess I talked to you about 100 years ago about sharing state between
>>> numpy
>>> rng and code I have in c++ that wr
struct and
export a pointer to it via a PyCapsule.
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On Wed, Mar 13, 2013 at 7:20 PM, Neal Becker wrote:
> Robert Kern wrote:
>
>> On Wed, Mar 13, 2013 at 6:40 PM, Neal Becker wrote:
>>> Grabbed numpy-1.7.0 source.
>>> Cython is 0.18
>>>
>>> cython mtrand.pyx produces lots of errors.
>>
>&g
On Wed, Mar 13, 2013 at 6:40 PM, Neal Becker wrote:
> Grabbed numpy-1.7.0 source.
> Cython is 0.18
>
> cython mtrand.pyx produces lots of errors.
It helps to copy-and-paste the errors that you are seeing.
In any case, Cython 0.18 works okay on master's mtrand.pyx sources.
On Tue, Mar 12, 2013 at 10:38 PM, Neal Becker wrote:
> Nathaniel Smith wrote:
>
>> On Tue, Mar 12, 2013 at 9:25 PM, Nathaniel Smith wrote:
>>> On Mon, Mar 11, 2013 at 9:46 AM, Robert Kern wrote:
>>>> On Sun, Mar 10, 2013 at 6:12 PM, Siu Kwan Lam wrote:
>&g
e is some low-level C work that needs to be done to allow the
non-uniform distributions to be shared between implementations of the
core uniform PRNG, but that's the same no matter how you organize the
upper layer.
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On Wed, Mar 6, 2013 at 10:56 PM, Nathaniel Smith wrote:
> On Wed, Mar 6, 2013 at 10:53 PM, Robert Kern wrote:
>> On Wed, Mar 6, 2013 at 10:45 PM, Nathaniel Smith wrote:
>>> On Wed, Mar 6, 2013 at 10:33 PM, Robert Kern wrote:
>>>> On Wed, Mar 6, 2013 at 8:09 PM, N
On Wed, Mar 6, 2013 at 10:45 PM, Nathaniel Smith wrote:
> On Wed, Mar 6, 2013 at 10:33 PM, Robert Kern wrote:
>> On Wed, Mar 6, 2013 at 8:09 PM, Nathaniel Smith wrote:
>>> A number of items on the 1.8 todo list are reminders to remove things
>>> that we deprecate
n to heart, though. We shouldn't remove stuff
faster than 12 months or so. I just think that it should modify our
release process, not our "marking for deprecation" process.
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1_opts] [cmd2 [cmd2_opts] ...]
or: setup.py --help [cmd1 cmd2 ...]
or: setup.py --help-commands
or: setup.py cmd --help
error: no commands supplied
Anyone who was expecting the interactive setup will probably complain here.
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On Tue, Feb 26, 2013 at 12:11 AM, Charles R Harris
wrote:
>
> On Sat, Feb 23, 2013 at 1:33 PM, Robert Kern wrote:
>>
>> On Sat, Feb 23, 2013 at 7:25 PM, Nathaniel Smith wrote:
>> > On Sat, Feb 23, 2013 at 3:38 PM, Till Stensitzki
>> > wrote:
>> >&
why
> np.abs(a) is so much harder than a.abs(), and why this function and
> not other unary functions?
Or even abs(a).
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m/numpy/numpy
> http://sourceforge.net/projects/numpy/files/
>
> Is there some misleading documentation still around that gave
> you a different impression?
Todd is responding to a message about PyDSTool, which is developed on
Sourceforge, not numpy.
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6e-01+7.071067811865431318e-01j)
> ...
What were you expecting? A single row? savetxt() always writes out
len(arr) rows. Reshape your vector into a (1,N) array if you want a
single row.
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numpy-discussion is for both development discussions and support
questions. The set of people interested in the developer discussions
is mostly the same as the set of people giving support, so there has
never been too much impetus for breaking the list into two
ne? (I didn't find them, only a similar package
> https://github.com/schmir/pypiserver, but that doesn't seem to be it.)
http://wiki.python.org/moin/CheeseShopDev
You can get help with PyPI on Catalog-SIG:
http://mail.python.org/mailman/listinfo/catalog-sig
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o the docstrings via sphinx, like in scipy?
Click on the "Edit Page" link on the left. Follow the instructions on
the front page of the numpy Docstring Editor site to sign up:
http://docs.scipy.org/numpy/Front%20Page/
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not public, I guess. I suppose anyone
> who uses the image would have to have their own licenses for the Intel
> stuff? Does anyone have experience of this?
You need to purchase one license per developer:
http://software.intel.com/en-us/articles/intel-math-kernel-libra
the community and we want
>> to share the work done.
>
> It certainly does look useful. My question is -- why do we need two
> complete copies of the linear algebra routine interfaces? Can we just
> replace the existing linalg functions with these new implementations?
> Or if not, wh
ion and avoid the
inv() by using solve().
viy0 = np.linalg.solve(v, y0)
for i, t in enumerate(tlist):
# And no need to dot() the first part. Broadcasting works just fine.
sol_t = (v * np.exp(-w*t)).dot(viy0)
...
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> equal, so I can remove them. So for example, the 1st and last row.
all_equal_mask = np.logical_and.reduce(arr[:,1:] == arr[:,:-1], axis=1)
some_unequal = arr[~all_equal_mask]
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idx0
array([[0],
[1],
[2],
[3],
[4]])
[~]
|7> v[idx0, idx]
array([[ 3, 4],
[ 1, 12],
[ 7, 23],
[ 6, 11],
[ 8, 9]])
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,1]]
http://docs.scipy.org/doc/numpy/user/basics.indexing.html#indexing-multi-dimensional-arrays
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fferent, so the result
of the multiplication will be different, so fill can not be used.
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On Mon, Jan 14, 2013 at 1:04 AM, Nathaniel Smith wrote:
> On Sun, Jan 13, 2013 at 11:48 PM, Skipper Seabold wrote:
>> On Sun, Jan 13, 2013 at 6:39 PM, Nathaniel Smith wrote:
>>>
>>> On Sun, Jan 13, 2013 at 11:24 PM, Robert Kern
>>> wrote:
>>> >
alternative that does not expand the API with two-liners is to let
the ndarray.fill() method return self:
a = np.empty(...).fill(20.0)
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a good to overwrite
> the error setting.
Precisely.
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ly
desirable since many of the masked values will be trip these errors
spuriously even though they will be masked out in the result.
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on framework again. Just don't mv it from where it
gets installed. Then the numpy-1.6.2-py2.7-python.org-macosx10.3.dmg
will recognize it.
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it make sense if pylab.power were the frequently used power
> function rather than a means for sampling from the power distribution?
Matplotlib may be discussed over here:
https://lists.sourceforge.net/lists/listinfo/matplotlib-users
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cumulate(reset_idx)
cumsum = np.cumsum(x)
cumsum = cumsum - cumsum[reset_idx]
return cumsum
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it, but it
>> did just bite me and a student a few times.
>
> The trail leads to here:
> http://projects.scipy.org/numpy/attachment/ticket/36/numpy-6-norm-change-
> default.diff
>
> Seems like the chances of learning the reason why this change was done
> are pretty sli
ink flags for
the language, often because they are more variable with respect to
specific compiler versions.
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ls, so you may want to do some digging of your own.
> 2) Is there a better way to build Cython files than this weird
> monkey-patching thing they propose? (It's still better than the horror
> that setuptools/distribute require, but I guess I have higher
> expectations...)
Sadly,
How do I do that?
C, dummy = numpy.broadcast_arrays(A[:,newaxis,:], numpy.empty([1,state,1]))
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On Wed, Aug 8, 2012 at 10:34 AM, David Cournapeau wrote:
> On Wed, Aug 8, 2012 at 12:55 AM, Nathaniel Smith wrote:
>> On Mon, Aug 6, 2012 at 8:31 PM, Robert Kern wrote:
>>> Those are not the original Fortran sources. The original Fortran sources are
>>> in the public
matics Institute
> >> University of Warwick
> >> Coventry
> >> West Midlands
> >> CV4 7AL
> >> United Kingdom
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On Thu, Aug 2, 2012 at 11:41 PM, Geoffrey Irving wrote:
> On Thu, Aug 2, 2012 at 1:26 PM, Robert Kern wrote:
>> On Thu, Aug 2, 2012 at 8:46 PM, Geoffrey Irving wrote:
>>> Hello,
>>>
>>> The attached .npy file was written from custom C++ code. It loads
>
format standard was that
it would accept what numpy spits out for the descr, not that it would
accept absolutely anything that numpy.dtype() can consume, even
deprecated aliases (though I will admit that that is almost what the
NEP says). In particular, endianness really should be included or else
y
;> Values from which to choose. `x` and `y` need to have the same
>> shape as `condition`
>>
>> In the example you gave, x was a scalar.
>
> net.max() returns an array:
>
> >>> print type(net.max())
>
>
> I would prefer not to use: from xxx import *,
>
> because of the name pollution.
>
> The name convention that I copied above facilitates avoiding the pollution.
>
> In the same spirit, I've used:
> import pylab as plb
But in that same spirit, using np and plt separately is preferred.
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m?
"python setup.py bdist_egg" should never work, but "python setupegg.py
bdist_egg" should.
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7;1:3,:,4') for a[1:3,:,4] ect.
> I am very close now.
[~]
|1> from numpy import index_exp
[~]
|2> index_exp[1:3,:,2:4]
(slice(1, 3, None), slice(None, None, None), slice(2, 4, None))
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NumP
8, 9, 10])
>
> In [26]: b[slice(1)]
> Out[26]: array([1])
>
> In [27]: b[slice(4)]
> Out[27]: array([1, 2, 3, 4])
>
> In [28]: b[slice(None,4)]
> Out[28]: array([1, 2, 3, 4])
>
> so slice(4) is actually slice(None,4), how can I exactly want retrieve a[4]
&
4?
You need special handling for NaTs to be consistent with how we deal
with NaNs in floats.
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s would impact projects like ipython that does
> tab-completion support, but I know that that would drive me nuts in my basic
> tab-completion setup I have for my regular python terminal. Of course, in
> the grand scheme of things, that really isn't all that imp
ok before you leap.
> I had explicit check for
> myarray.base==None, which it is not when I get the ndarray from a pickle.
That is not the way to check if an ndarray owns its data. Instead,
check a.flags['OWNDATA']
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On Thu, Jun 21, 2012 at 7:33 PM, eat wrote:
> Heh,
>
> On Thu, Jun 21, 2012 at 6:03 PM, Robert Kern wrote:
>>
>> On Thu, Jun 21, 2012 at 3:59 PM, bob tnur wrote:
>> > Hi all numpy fun;)
>> > This question is already posted in stackoverflow by some people,
on is herein:
> http://stackoverflow.com/questions/10074270/how-can-i-find-the-minimum-number-of-lines-needed-to-cover-all-the-zeros-in-a-2
My "numpy solution" for this is just
$ pip install munkres
http://pypi.python.org/pypi/munkres
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On Wed, Jun 20, 2012 at 3:58 PM, Neal Becker wrote:
> Maybe I'm being slow, but is there any convenient function to calculate,
> for 2 vectors:
>
> \sum_i \sum_j x_i y_j
>
> (I had a matrix once, but it vanished without a trace)
np.multiply.outer(x, y)
onsistency it would be desirable for this to return
>
> [8, 9, 0, 1]
Unfortunately, this would be inconsistent with Python semantics:
[~]
|1> u = range(10)
[~]
|2> u[-2:2]
[]
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useful behavior
> needs to be documented.
Suggestions for improving the standard Python documentation (which
documents these functions) can be sent here:
http://docs.python.org/bugs.html#documentation-bugs
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nyway, my point was that a having a function with the "adding" semantics in
> NumPy would be handy.
x += numpy.bincount(idx, vals, minlength=len(x))
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apply_binary (np.logical_or, u/5 == 3, u/5 == 8, u/5 ==
> 13))
reduce(np.logical_and, args)
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= np.delete(M, bad_rows, axis=0)
P = np.delete(P, bad_cols, axis=1)
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ITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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On Fri, May 25, 2012 at 3:55 PM, Nathaniel Smith wrote:
> On May 25, 2012 2:21 PM, "Robert Kern" wrote:
>>
>> On Thu, May 24, 2012 at 5:52 PM, Robert Kern wrote:
>>
>> > (Hmm, now that I think about it, the edge cases are when the strides
>> &g
On Fri, May 25, 2012 at 3:55 PM, Nathaniel Smith wrote:
> On May 25, 2012 2:21 PM, "Robert Kern" wrote:
>>
>> On Thu, May 24, 2012 at 5:52 PM, Robert Kern wrote:
>>
>> > (Hmm, now that I think about it, the edge cases are when the strides
>> &g
On Thu, May 24, 2012 at 5:52 PM, Robert Kern wrote:
> (Hmm, now that I think about it, the edge cases are when the strides
> are 0 or negative. 0-stride axes can simply be removed, and I think we
> should be able to work back to a first item and flip the sign on the
> negative
r negative. 0-stride axes can simply be removed, and I think we
should be able to work back to a first item and flip the sign on the
negative strides. The typical positive-stride solution can be found in
an open source C++ global array code, IIRC. Double-hmmm...)
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Robert Kern
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er data.flat, if you must iterate manually.
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sufficient for
> me.
BLAS has the xAXPY functions, which will do this for float and complex.
import numpy as np
from scipy.linalg import fblas
def add_scaled_inplace(a, scale, b):
if np.issubdtype(a.dtype, complex):
fblas.zaxpy(b, a, a=scale)
else:
fblas.daxpy(b, a, a
On Tue, May 22, 2012 at 2:45 PM, Nathaniel Smith wrote:
> On Tue, May 22, 2012 at 11:06 AM, Robert Kern wrote:
>> On Tue, May 22, 2012 at 9:27 AM, Nathaniel Smith wrote:
>>> So starting in Python 2.7 and 3.2, the Python developers have made
>>> DeprecationWa
On Tue, May 22, 2012 at 11:14 AM, Dag Sverre Seljebotn
wrote:
> On 05/22/2012 12:06 PM, Robert Kern wrote:
>> On Tue, May 22, 2012 at 9:27 AM, Nathaniel Smith wrote:
>>> So maybe we should change all our DeprecationWarnings into
>>> FutureWarnings (or at least the on
r DeprecationWarnings
possibly should be FutureWarnings, but most shouldn't I don't think.
I can see a case being made for using a custom non-silenced exception
for some cases that really probably show up mostly in true end-user
scenarios, e.g. genfromtxt(). But
even sure if such a thing exists, in which case NumPy would
> indeed be a special case.
numpy *is* pretty unique in this regard. The need for this style of
polymorphism at this level is even rarer.
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On Wed, May 16, 2012 at 4:35 PM, Nathaniel Smith wrote:
> On Wed, May 16, 2012 at 4:24 PM, Robert Kern wrote:
>> On Wed, May 16, 2012 at 4:21 PM, Nathaniel Smith wrote:
>>
>>> I built some pristine python 2.7 installs from scratch (no virtualenv,
>>> no distr
ms fine - it finds atlas in /usr/lib64/atlas.
>
> With current numpy master (3d416a0a), numpy itself builds fine,
> but scipy's setup.py can't find atlas (even though it's looking in the
> right places). Log attached.
The log says it's looking in /usr/lib64/atl
xecutable that
runs the setup.py manages to import. So if you are using virtualenv,
just make sure that the virtualenv is activated and "python" refers to
the virtualenv's python executable.
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Robert Kern
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