Re: [Numpy-discussion] Oops - maybe post3 numpy file?

On Thu, Oct 8, 2015 at 8:39 PM, Charles R Harris wrote: > > > On Thu, Oct 8, 2015 at 6:30 PM, Matthew Brett > wrote: > >> Hi, >> >> I'm afraid I made a mistake uploading OSX wheels for numpy 1.10.0. >> Using twine to do the upload generated a

Re: [Numpy-discussion] Comments on governance proposal (was: Notes from the numpy dev meeting at scipy 2015)

On Thu, Aug 27, 2015 at 8:57 AM, Matthew Brett matthew.br...@gmail.com wrote: Hi, On Thu, Aug 27, 2015 at 12:11 PM, Sebastian Berg sebast...@sipsolutions.net wrote: On Do, 2015-08-27 at 10:45 +0100, Matthew Brett wrote: Hi, On Thu, Aug 27, 2015 at 10:35 AM, Bryan Van de Ven

Re: [Numpy-discussion] Comments on governance proposal (was: Notes from the numpy dev meeting at scipy 2015)

On Thu, Aug 27, 2015 at 12:22 PM, Matthew Brett matthew.br...@gmail.com wrote: Hi On Thu, Aug 27, 2015 at 5:11 PM, josef.p...@gmail.com wrote: On Thu, Aug 27, 2015 at 11:04 AM, Matthew Brett matthew.br...@gmail.com wrote: Hi, On Thu, Aug 27, 2015 at 3:34 PM,

Re: [Numpy-discussion] Notes from the numpy dev meeting at scipy 2015

On Wed, Aug 26, 2015 at 10:06 AM, Travis Oliphant tra...@continuum.io wrote: On Wed, Aug 26, 2015 at 1:41 AM, Nathaniel Smith n...@pobox.com wrote: Hi Travis, Thanks for taking the time to write up your thoughts! I have many thoughts in return, but I will try to restrict myself to two

Re: [Numpy-discussion] Comments on governance proposal (was: Notes from the numpy dev meeting at scipy 2015)

On Thu, Aug 27, 2015 at 11:04 AM, Matthew Brett matthew.br...@gmail.com wrote: Hi, On Thu, Aug 27, 2015 at 3:34 PM, josef.p...@gmail.com wrote: [snip] I don't really see a problem with codifying the status quo. That's an excellent point.If we believe that the current situation is

Re: [Numpy-discussion] Comments on governance proposal (was: Notes from the numpy dev meeting at scipy 2015)

On Thu, Aug 27, 2015 at 2:06 PM, Matthew Brett matthew.br...@gmail.com wrote: Hi, On Thu, Aug 27, 2015 at 6:23 PM, josef.p...@gmail.com wrote: On Thu, Aug 27, 2015 at 12:22 PM, Matthew Brett matthew.br...@gmail.com wrote: Hi On Thu, Aug 27, 2015 at 5:11 PM,

[Numpy-discussion] meshgrid dtype casting

I'm trying to build a meshgrid with small nonnegative integers default is int32 >>> np.meshgrid([0,1,2], [0,1])[0].dtype dtype('int32') If I use uint, then the arrays are upcast to int64 - Why? >>> np.meshgrid(np.array([0,1,2], np.uint), np.array([0,1], np.uint))[0].dtype dtype('int64')

Re: [Numpy-discussion] Comments on governance proposal (was: Notes from the numpy dev meeting at scipy 2015)

On Fri, Sep 4, 2015 at 7:19 PM, Matthew Brett wrote: > On Sat, Sep 5, 2015 at 12:04 AM, wrote: > > > > > > On Fri, Sep 4, 2015 at 5:55 PM, Matthew Brett > > wrote: > >> > >> Hi, > >> > >> On Fri, Sep 4, 2015 at 10:22 PM,

Re: [Numpy-discussion] Comments on governance proposal (was: Notes from the numpy dev meeting at scipy 2015)

On Fri, Sep 4, 2015 at 5:55 PM, Matthew Brett wrote: > Hi, > > On Fri, Sep 4, 2015 at 10:22 PM, Eric Firing wrote: > > On 2015/09/04 10:53 AM, Matthew Brett wrote: > >> On Fri, Sep 4, 2015 at 2:33 AM, Matthew Brett > wrote:

Re: [Numpy-discussion] Sign of NaN

On Tue, Sep 29, 2015 at 11:25 AM, Anne Archibald wrote: > IEEE 754 has signum(NaN)->NaN. So does np.sign on floating-point arrays. > Why should it be different for object arrays? > > Anne > > P.S. If you want exceptions when NaNs appear, that's what np.seterr is > for. -A >

Re: [Numpy-discussion] Sign of NaN

On Tue, Sep 29, 2015 at 2:16 PM, Nathaniel Smith wrote: > On Sep 29, 2015 8:25 AM, "Anne Archibald" wrote: > > > > IEEE 754 has signum(NaN)->NaN. So does np.sign on floating-point arrays. > Why should it be different for object arrays? > > The argument for

Re: [Numpy-discussion] Governance model request

On Tue, Sep 22, 2015 at 10:55 PM, Bryan Van de Ven wrote: > > > On Sep 22, 2015, at 1:48 PM, Matthew Brett > wrote: > > > > The point is, that a sensible organization and a sensible leader has > > to take the possibility of conflict of interest into

Re: [Numpy-discussion] Fast vectorized arithmetic with ~32 significant digits under Numpy

On Fri, Dec 11, 2015 at 11:22 AM, Anne Archibald wrote: > Actually, GCC implements 128-bit floats in software and provides them as > __float128; there are also quad-precision versions of the usual functions. > The Intel compiler provides this as well, I think, but I don't

Re: [Numpy-discussion] Numpy 1.10.3 release.

On Sat, Jan 2, 2016 at 4:47 PM, Charles R Harris wrote: > Hi All, > > A significant segfault problem has been reported against Numpy 1.10.2 and I > want to make a quick 1.10.3 release to get it fixed. Two questions > > What exactly is the release process that has been

Re: [Numpy-discussion] Numpy 1.10.3 release.

On Sun, Jan 3, 2016 at 12:05 AM, wrote: > On Sat, Jan 2, 2016 at 4:47 PM, Charles R Harris > wrote: >> Hi All, >> >> A significant segfault problem has been reported against Numpy 1.10.2 and I >> want to make a quick 1.10.3 release to get it

Re: [Numpy-discussion] ENH: Add the function 'expand_view'

On Tue, Nov 24, 2015 at 7:13 PM, Nathaniel Smith wrote: > On Nov 24, 2015 11:57 AM, "John Kirkham" wrote: > > > > Takes an array and tacks on arbitrary dimensions on either side, which > is returned as a view always. Here are the relevant features: > > > > *

[Numpy-discussion] asarray(sparse) -> object

Is this intentional? >>> exog <50x5 sparse matrix of type '' with 50 stored elements in Compressed Sparse Column format> >>> np.asarray(exog) array(<50x5 sparse matrix of type '' with 50 stored elements in Compressed Sparse Column format>, dtype=object) I'm just a newbie who thought to use

Re: [Numpy-discussion] asarray(sparse) -> object

On Fri, Nov 20, 2015 at 6:29 PM, CJ Carey wrote: > The short answer is: "kind of". > > These two Github issues explain what's going on more in-depth: > https://github.com/scipy/scipy/issues/3995 > https://github.com/scipy/scipy/issues/4239 > Thanks, I didn't pay

Re: [Numpy-discussion] Numpy 1.11.0b2 released

On Fri, Feb 5, 2016 at 3:24 PM, wrote: > > > On Fri, Feb 5, 2016 at 1:14 PM, Pauli Virtanen wrote: > >> 05.02.2016, 19:55, Nathaniel Smith kirjoitti: >> > On Feb 5, 2016 8:28 AM, "Chris Barker - NOAA Federal" < >> chris.bar...@noaa.gov> >> > wrote: >> >> >>

Re: [Numpy-discussion] [Suggestion] Labelled Array

On Sat, Feb 13, 2016 at 1:01 PM, Allan Haldane wrote: > Sorry, to reply to myself here, but looking at it with fresh eyes maybe > the performance of the naive version isn't too bad. Here's a comparison of > the naive vs a better implementation: > > def

Re: [Numpy-discussion] [Suggestion] Labelled Array

On Sat, Feb 13, 2016 at 1:42 PM, Jeff Reback wrote: > These operations get slower as the number of groups increase, but with a > faster function (e.g. the standard ones which are cythonized), the > constant on > the increase is pretty low. > > In [23]: c =

Re: [Numpy-discussion] ANN: numpydoc 0.6.0 released

On Sat, Feb 13, 2016 at 10:03 AM, Ralf Gommers wrote: > Hi all, > > I'm pleased to announce the release of numpydoc 0.6.0. The main new > feature is support for the Yields section in numpy-style docstrings. This > is described in >

Re: [Numpy-discussion] Behavior of np.random.uniform

On Tue, Jan 19, 2016 at 12:43 PM, Charles R Harris < charlesr.har...@gmail.com> wrote: > > > On Tue, Jan 19, 2016 at 10:42 AM, Robert Kern > wrote: > >> On Tue, Jan 19, 2016 at 5:40 PM, Charles R Harris < >> charlesr.har...@gmail.com> wrote: >> > >> > On Tue, Jan 19, 2016

Re: [Numpy-discussion] NumPy 1.11.0b3 released.

On Mon, Feb 15, 2016 at 10:46 PM, wrote: > > > On Fri, Feb 12, 2016 at 4:19 PM, Nathan Goldbaum > wrote: > >> https://github.com/numpy/numpy/blob/master/doc/release/1.11.0-notes.rst >> >> On Fri, Feb 12, 2016 at 3:17 PM, Andreas Mueller

Re: [Numpy-discussion] NumPy 1.11.0b3 released.

On Mon, Feb 15, 2016 at 11:31 PM, Charles R Harris < charlesr.har...@gmail.com> wrote: > > > On Mon, Feb 15, 2016 at 9:15 PM, wrote: > >> >> >> On Mon, Feb 15, 2016 at 11:05 PM, Charles R Harris < >> charlesr.har...@gmail.com> wrote: >> >>> >>> >>> On Mon, Feb 15, 2016 at

Re: [Numpy-discussion] NumPy 1.11.0b3 released.

On Tue, Feb 16, 2016 at 12:09 AM, wrote: > > > On Mon, Feb 15, 2016 at 11:31 PM, Charles R Harris < > charlesr.har...@gmail.com> wrote: > >> >> >> On Mon, Feb 15, 2016 at 9:15 PM, wrote: >> >>> >>> >>> On Mon, Feb 15, 2016 at 11:05 PM, Charles R

Re: [Numpy-discussion] Proposal to add `weights` to `np.percentile` and `np.median`

On Tue, Feb 16, 2016 at 1:41 PM, Joseph Fox-Rabinovitz < jfoxrabinov...@gmail.com> wrote: > Thanks for pointing me to that. I had something a bit different in > mind but that definitely looks like a good start. > > On Tue, Feb 16, 2016 at 1:32 PM, Antony Lee > wrote: > >

Re: [Numpy-discussion] Proposal to add `weights` to `np.percentile` and `np.median`

On Tue, Feb 16, 2016 at 2:48 PM, Joseph Fox-Rabinovitz < jfoxrabinov...@gmail.com> wrote: > Please correct me if I misunderstood, but the code in that commit is > doing a full sort, somewhat similar to what > `scipy.stats.scoreatpercentile`. If that is correct, I will run some > benchmarks first,

Re: [Numpy-discussion] making "low" optional in numpy.randint

On Wed, Feb 17, 2016 at 10:01 AM, G Young wrote: > Hello all, > > I have a PR open here that > makes "low" an optional parameter in numpy.randint and introduces new > behavior into the API as follows: > > 1) `low == None` and `high

Re: [Numpy-discussion] making "low" optional in numpy.randint

On Wed, Feb 17, 2016 at 2:09 PM, G Young wrote: > Yes, you are correct in explaining my intentions. However, as I also > mentioned in the PR discussion, I did not quite understand how your wrapper > idea would make things any more comprehensive at the cost of additional >

Re: [Numpy-discussion] making "low" optional in numpy.randint

On Wed, Feb 17, 2016 at 2:20 PM, wrote: > > > On Wed, Feb 17, 2016 at 2:09 PM, G Young wrote: > >> Yes, you are correct in explaining my intentions. However, as I also >> mentioned in the PR discussion, I did not quite understand how your wrapper >>

Re: [Numpy-discussion] making "low" optional in numpy.randint

On Wed, Feb 17, 2016 at 3:58 PM, G Young wrote: > I sense that this issue is now becoming more of "randint has become too > complicated" I suppose we could always "add" more functions that present > simpler interfaces, though if you really do want simple, there's always >

Re: [Numpy-discussion] making "low" optional in numpy.randint

On Wed, Feb 17, 2016 at 7:17 PM, Juan Nunez-Iglesias wrote: > Ah! Touché! =) My last and admittedly weak defense is that I've been > writing numpy since before 1.7. =) > > On Thu, Feb 18, 2016 at 11:08 AM, Alan Isaac wrote: > >> On 2/17/2016 7:01 PM,

Re: [Numpy-discussion] Suggestion: special-case np.array(range(...)) to be faster

On Thu, Feb 18, 2016 at 1:15 PM, Antony Lee wrote: > Mostly so that there is no performance lost when someone passes range(...) > instead of np.arange(...). At least I had never realized that one is much > faster than the other and always just passed range() as a

Re: [Numpy-discussion] [Suggestion] Labelled Array

On Fri, Feb 19, 2016 at 12:08 PM, Allan Haldane wrote: > I also want to add a historical note here, that 'groupby' has been > discussed a couple times before. > > Travis Oliphant even made an NEP for it, and Wes McKinney lightly hinted > at adding it to numpy. > >

Re: [Numpy-discussion] Suggestion: special-case np.array(range(...)) to be faster

On Sat, Feb 13, 2016 at 9:43 PM, wrote: > > > On Sat, Feb 13, 2016 at 8:57 PM, Antony Lee > wrote: > >> Compare (on Python3 -- for Python2, read "xrange" instead of "range"): >> >> In [2]: %timeit np.array(range(100), np.int64) >> 10 loops,

Re: [Numpy-discussion] Suggestion: special-case np.array(range(...)) to be faster

On Sat, Feb 13, 2016 at 8:57 PM, Antony Lee wrote: > Compare (on Python3 -- for Python2, read "xrange" instead of "range"): > > In [2]: %timeit np.array(range(100), np.int64) > 10 loops, best of 3: 156 ms per loop > > In [3]: %timeit np.arange(100,

Re: [Numpy-discussion] Suggestion: special-case np.array(range(...)) to be faster

On Sun, Feb 14, 2016 at 3:21 AM, Antony Lee wrote: > re: no reason why... > This has nothing to do with Python2/Python3 (I personally stopped using > Python2 at least 3 years ago.) Let me put it this way instead: if > Python3's "range" (or Python2's "xrange") was not a

Re: [Numpy-discussion] NumPy 1.11.0b3 released.

On Wed, Feb 10, 2016 at 5:36 PM, Charles R Harris wrote: > > > On Wed, Feb 10, 2016 at 2:58 PM, Pauli Virtanen wrote: > >> 10.02.2016, 04:09, Charles R Harris kirjoitti: >> > I'm pleased to announce the release of NumPy 1.11.0b3. This beta >> contains >>

Re: [Numpy-discussion] Changes to generalized ufunc core dimension checking

On Thu, Mar 17, 2016 at 1:08 AM, Steve Waterbury wrote: > On 03/16/2016 10:32 PM, Fernando Perez wrote: > >> On Wed, Mar 16, 2016 at 3:45 PM, Steve Waterbury >> > wrote: >> >> On 03/16/2016 06:28 PM, Nathaniel

Re: [Numpy-discussion] ndarray.T2 for 2D transpose

On Thu, Apr 7, 2016 at 11:13 AM, Todd wrote: > On Wed, Apr 6, 2016 at 5:20 PM, Nathaniel Smith wrote: >> >> On Wed, Apr 6, 2016 at 10:43 AM, Todd wrote: >> > >> > My intention was to make linear algebra operations easier in numpy. >> >

Re: [Numpy-discussion] ndarray.T2 for 2D transpose

On Thu, Apr 7, 2016 at 11:42 AM, Todd wrote: > On Thu, Apr 7, 2016 at 11:35 AM, wrote: >> >> On Thu, Apr 7, 2016 at 11:13 AM, Todd wrote: >> > On Wed, Apr 6, 2016 at 5:20 PM, Nathaniel Smith wrote: >> >> >> >> On

Re: [Numpy-discussion] ndarray.T2 for 2D transpose

On Thu, Apr 7, 2016 at 1:35 PM, Sebastian Berg wrote: > On Do, 2016-04-07 at 13:29 -0400, josef.p...@gmail.com wrote: > > > > > > On Thu, Apr 7, 2016 at 1:20 PM, Sebastian Berg < > > sebast...@sipsolutions.net> wrote: > > > On Do, 2016-04-07 at 11:56 -0400,

Re: [Numpy-discussion] ndarray.T2 for 2D transpose

On Thu, Apr 7, 2016 at 2:17 PM, Chris Barker wrote: > On Thu, Apr 7, 2016 at 10:00 AM, Ian Henriksen < > insertinterestingnameh...@gmail.com> wrote: > >> Here's another example that I've seen catch people now and again. >> >> A = np.random.rand(100, 100) >> b =

Re: [Numpy-discussion] ndarray.T2 for 2D transpose

On Thu, Apr 7, 2016 at 1:20 PM, Sebastian Berg wrote: > On Do, 2016-04-07 at 11:56 -0400, josef.p...@gmail.com wrote: > > > > > > > > > > > I don't think numpy treats 1d arrays as row vectors. numpy has C > > -order for axis preference which coincides in many cases

Re: [Numpy-discussion] ndarray.T2 for 2D transpose

On Thu, Apr 7, 2016 at 3:26 PM, Ian Henriksen < insertinterestingnameh...@gmail.com> wrote: > On Thu, Apr 7, 2016 at 12:31 PM wrote: > >> write unit tests with non square 2d arrays and the exception / test error >> shows up fast. >> >> Josef >> >> > Absolutely, but good

Re: [Numpy-discussion] ndarray.T2 for 2D transpose

On Thu, Apr 7, 2016 at 4:07 PM, Ian Henriksen < insertinterestingnameh...@gmail.com> wrote: > On Thu, Apr 7, 2016 at 1:53 PM wrote: > >> On Thu, Apr 7, 2016 at 3:26 PM, Ian Henriksen < >> insertinterestingnameh...@gmail.com> wrote: >> >>> On Thu, Apr 7, 2016 at 12:31 PM

Re: [Numpy-discussion] ndarray.T2 for 2D transpose

On Fri, Apr 8, 2016 at 5:11 PM, Charles R Harris wrote: > > > On Fri, Apr 8, 2016 at 2:52 PM, wrote: > >> >> >> On Fri, Apr 8, 2016 at 3:55 PM, Charles R Harris < >> charlesr.har...@gmail.com> wrote: >> >>> >>> >>> On Fri, Apr 8, 2016 at 12:17

Re: [Numpy-discussion] ndarray.T2 for 2D transpose

On Fri, Apr 8, 2016 at 3:55 PM, Charles R Harris wrote: > > > On Fri, Apr 8, 2016 at 12:17 PM, Chris Barker > wrote: > >> On Fri, Apr 8, 2016 at 9:59 AM, Charles R Harris < >> charlesr.har...@gmail.com> wrote: >> >>> Apropos column/row vectors,

Re: [Numpy-discussion] Make np.bincount output same dtype as weights

On Sat, Mar 26, 2016 at 9:54 PM, Joseph Fox-Rabinovitz wrote: > Would it make sense to just make the output type large enough to hold the > cumulative sum of the weights? > > > - Joseph Fox-Rabinovitz > > -- Original message-- > > From: Jaime Fernández del Río >

Re: [Numpy-discussion] Windows wheels, built, but should we deploy?

On Fri, Mar 4, 2016 at 1:38 PM, Matthew Brett wrote: > On Fri, Mar 4, 2016 at 12:29 AM, David Cournapeau > wrote: > > > > > > On Fri, Mar 4, 2016 at 4:42 AM, Matthew Brett > > wrote: > >> > >> Hi, > >> > >> Summary: > >> >

Re: [Numpy-discussion] Changing the behavior of (builtins.)round (via the __round__ dunder) to return an integer

On Wed, Apr 13, 2016 at 4:31 AM, Stephan Hoyer wrote: > On Wed, Apr 13, 2016 at 12:42 AM, Antony Lee > wrote: > >> (Note that I am suggesting to switch to the new behavior regardless of >> the version of Python.) >> > > I would lean towards making this

Re: [Numpy-discussion] Integers to integer powers

On Thu, May 19, 2016 at 10:16 PM, wrote: > > > On Thu, May 19, 2016 at 5:37 PM, Charles R Harris < > charlesr.har...@gmail.com> wrote: > >> Hi All, >> >> There are currently several pull requests apropos integer arrays/scalars >> to integer powers and, because the area is

Re: [Numpy-discussion] Integers to integer powers

On Thu, May 19, 2016 at 5:37 PM, Charles R Harris wrote: > Hi All, > > There are currently several pull requests apropos integer arrays/scalars > to integer powers and, because the area is messy and involves tradeoffs, > I'd like to see some discussion here on the

Re: [Numpy-discussion] Integers to integer powers

On Fri, May 20, 2016 at 3:23 PM, Charles R Harris wrote: > > > On Fri, May 20, 2016 at 1:15 PM, Nathaniel Smith wrote: > >> On Fri, May 20, 2016 at 11:35 AM, Charles R Harris >> wrote: >> > >> > >> > On Thu, May 19, 2016 at

Re: [Numpy-discussion] Integers to integer powers

On Fri, May 20, 2016 at 6:54 PM, Nathaniel Smith wrote: > On May 20, 2016 12:44 PM, wrote: > [...] > > > > can numpy cast to float by default for power or **? > > Maybe? The question is whether there are any valid use cases for getting > ints back: > > >>>

Re: [Numpy-discussion] Integers to integer powers

On Fri, May 20, 2016 at 4:27 PM, Warren Weckesser < warren.weckes...@gmail.com> wrote: > > > On Fri, May 20, 2016 at 4:22 PM, Alan Isaac wrote: > >> On 5/19/2016 11:30 PM, Nathaniel Smith wrote: >> >>> the last bad >>> option IMHO would be that we make int ** (negative int)

Re: [Numpy-discussion] Proposal: numpy.random.random_seed

On Tue, May 17, 2016 at 4:49 AM, Robert Kern wrote: > On Tue, May 17, 2016 at 9:09 AM, Stephan Hoyer wrote: > > > > On Tue, May 17, 2016 at 12:18 AM, Robert Kern > wrote: > >> > >> On Tue, May 17, 2016 at 4:54 AM, Stephan Hoyer

Re: [Numpy-discussion] Remove a random sample from array

On Mon, May 16, 2016 at 12:24 PM, Elliot Hallmark wrote: > Use `random.shuffle(range(len(arr))` to make a list of indices. Use a > slices to get your 20/80. Convert to integer arrays and index your > original array with them. Use sorted on the 80% list if you need to >

Re: [Numpy-discussion] three-way comparisons

On Sat, May 14, 2016 at 3:23 AM, Phillip Feldman < phillip.m.feld...@gmail.com> wrote: > I often find a need to do the type of comparison done by function shown > below. I suspect that this would be more efficient for large arrays if > implemented direction in C. Is there any possibility of

Re: [Numpy-discussion] Proposal: numpy.random.random_seed

On Wed, May 18, 2016 at 12:01 PM, Robert Kern wrote: > On Wed, May 18, 2016 at 4:50 PM, Chris Barker > wrote: > >> > >> > ...anyway, the real reason I'm a bit grumpy is because there are solid > >> > engineering reasons why users *want* this API, >

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