Dear all-
Structured arrays are great, but I am having problems filtering them
efficiently. Reading through the mailing list, it seems like boolean
arrays are the recommended approach to filtering arrays for arbitrary
conditions, but my testing shows that a combination of take and where
can be muc
On Tue, Dec 21, 2010 at 5:53 PM, Mark Wiebe wrote:
> Hello NumPy-ers,
>
> After some performance analysis, I've designed and implemented a new
> iterator designed to speed up ufuncs and allow for easier multi-dimensional
> iteration. The new code is fairly large, but works quite well already. I
On Tue, Dec 21, 2010 at 6:06 PM, David wrote:
>
>
This looks pretty cool. I hope to be able to take a look at it during
> the christmas holidays.
>
Thanks!
>
> I cannot comment in details yet, but it seems to address several issues
> I encountered myself while implementing the neighborhood iter
That's a good suggestion - added. Unfortunately, it looks like the github
rst converter doesn't make a table of contents with working links.
Cheers,
Mark
On Tue, Dec 21, 2010 at 6:00 PM, John Salvatier
wrote:
> I applaud you on your vision. I only have one small suggestion: I suggest
> you put
Hi Mark,
On 12/22/2010 09:53 AM, Mark Wiebe wrote:
> Hello NumPy-ers,
>
> After some performance analysis, I've designed and implemented a new
> iterator designed to speed up ufuncs and allow for easier
> multi-dimensional iteration. The new code is fairly large, but works
> quite well already.
I applaud you on your vision. I only have one small suggestion: I suggest
you put a table of contents at the beginning of your NEP so people may skip
to the part that most interests them.
On Tue, Dec 21, 2010 at 4:59 PM, John Salvatier
wrote:
> That is an amazing christmas present.
>
> On Tue, De
On Mon, Dec 20, 2010 at 1:42 PM, John Salvatier
wrote:
> A while ago, I asked a whether it was possible to multi-iterate over
> several ndarrays but exclude a certain axis(
> http://www.mail-archive.com/numpy-discussion@scipy.org/msg29204.html),
> sort of a combination of PyArray_IterAllButAxis an
That is an amazing christmas present.
On Tue, Dec 21, 2010 at 4:53 PM, Mark Wiebe wrote:
> Hello NumPy-ers,
>
> After some performance analysis, I've designed and implemented a new
> iterator designed to speed up ufuncs and allow for easier multi-dimensional
> iteration. The new code is fairly
Hello NumPy-ers,
After some performance analysis, I've designed and implemented a new
iterator designed to speed up ufuncs and allow for easier multi-dimensional
iteration. The new code is fairly large, but works quite well already. If
some people could read the NEP and give some feedback, that
On Mon, Dec 20, 2010 at 10:28, Alan G Isaac wrote:
> I want to sample *without* replacement from a vector
> (as with Python's random.sample). I don't see a direct
> replacement for this, and I don't want to carry two
> PRNG's around. Is the best way something like this?
>
> permutation(m
Chuck wrote:
> The reversed matrix is a view, no copyihg is done. It is even faster than
> an inplace reversal.
This is why I love NumPy. In C, Fortran or Matlab most programmers would
probably form the reversed array. In NumPy we just change some
metainformation (data pointer and strides) behin
We often need to generate more than one such sample from an array, e.g.
for permutation tests. If we shuffle an array x of size N and use x[:M] as
a random sample "without replacement", we just need to put them back
randomly to get the next sample (cf. Fisher-Yates shuffle). That way we
get O(M) a
bincount does not currently allow a generator as an argument.
I'm wondering if it is considered too costly to extend it to allow this.
(Motivation: I'm counting based on an attribute of a large number of objects,
and I don't need a list of the data.)
Thanks,
Alan Isaac
___
::
>>> np.bincount([])
Traceback (most recent call last):
File "", line 1, in
ValueError: The first argument cannot be empty.
Why not?
(I.e., why isn't an empty array the right answer?)
Thanks,
Alan Isaac
___
NumPy-Discussion ma
I know this question came up on the mailing list some time ago
(19/09/2008), and the conclusion was that yes, you can do it more or
less efficiently in pure python; the trick is to use two different
methods. If your sample is more than, say, a quarter the size of the
set you're drawing from, you pe
On 12/20/2010 10:49 PM, josef.p...@gmail.com wrote:
> What's the difference between a numpy Random and a python
> random.Random instance of separate states of the random number
> generators?
Sorry, I don't understand the question. The difference
for my use is that a np.RandomState instance provi
16 matches
Mail list logo
