Re: [Numpy-discussion] Added atleast_nd, request for clarification/cleanup of atleast_3d

On 2016/07/06 8:25 AM, Benjamin Root wrote: I wouldn't have the keyword be "where", as that collides with the notion of "where" elsewhere in numpy. Agreed. Maybe "side"? (I find atleast_1d and atleast_2d to be very helpful for handling inputs, as Ben noted; I'm skeptical as to the value of a

Re: [Numpy-discussion] Floor divison on int returns float

On 2016/04/04 9:23 AM, T J wrote: I'm on NumPy 1.10.4 (mkl). >>> np.uint(3) // 2 # 1.0 >>> 3 // 2 # 1 Is this behavior expected? It's certainly not desired from my perspective. If this is not a bug, could someone explain the rationale to me. Thanks. I agree that it's almost always unde

Re: [Numpy-discussion] Question about nump.ma.polyfit

On 2015/12/14 6:39 PM, Samuel Dupree wrote: I'm running Python 2.7.11 from the Anaconda distribution (version 2.4.1) on a MacBook Pro running Mac OS X version 10.11.2 (El Capitan) I'm attempting to use numpy.ma.polyfit to perform a linear least square fit on some data I have. I'm running NumPy v

Re: [Numpy-discussion] When to stop supporting Python 2.6?

On 2015/12/03 12:47 PM, Charles R Harris wrote: Hi All, Thought I would raise the topic apropos this post . There is not a great advantage to dropping 2.6, OTOH, 2.7 has more features (memoryview) and we could clean u

Re: [Numpy-discussion] future of f2py and Fortran90+

, Sturla Molden wrote: Eric Firing wrote: I'm curious: has anyone been looking into what it would take to enable f2py to handle modern Fortran in general? And into prospects for getting such an effort funded? No need. Use Cython and Fortran 2003 ISO C bindings. That is the only portable w

Re: [Numpy-discussion] Recognizing a cycle in a vector

On 2015/12/02 10:45 PM, Manolo Martínez wrote: 1) this func sorts the absolute value of the amplitudes to find the two most important components, and this seems overkill for large vectors. Try inds = np.argpartition(-np.abs(ft), 2)[:2] Now inds holds the indices of the two largest components

Re: [Numpy-discussion] Feedback on new argument positions for ma.dot and MaskedArray.dot

On 2015/11/08 3:46 PM, Charles R Harris wrote: Hi All, I'd like some feedback for the position of the `strict` and `out` arguments for masked arrays. See gh-6653 for the PR in question. Current status without #6652 1. ma.dot(a, b, strict=False) -- es

Re: [Numpy-discussion] Problem while writing array with np.savetxt

On 2015/09/23 9:17 PM, Andrew Nelson wrote: Dear list, whilst trying to write an array to disk I am coming across the following. What am I doing wrong? Surely f is a file handle? (python 3.4.3, numpy 1.9.2) import numpy as np a = np.arange(10.) with open('test.dat', 'w') as f: np.savetxt(

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

On 2015/09/04 10:53 AM, Matthew Brett wrote: > On Fri, Sep 4, 2015 at 2:33 AM, Matthew Brett wrote: >> Hi, >> >> On Wed, Sep 2, 2015 at 5:41 PM, Chris Barker wrote: >>> 1) I very much agree that governance can make or break a project. However, >>> the actual governance approach often ends up maki

Re: [Numpy-discussion] Numpy FFT.FFT slow with certain samples

On 2015/08/28 10:36 AM, Sebastian Berg wrote: > If you don't mind the extra dependency or licensing and this is an issue > for you, you can try pyfftw (there are likely other similar projects) > which wraps fftw and does not have this problem as far as I know. It > exposes a numpy-like interface.

Re: [Numpy-discussion] Problems using add_npy_pkg_config

I used to use scons, but I've been pretty happy with switching to waf. (Very limited use in both cases: two relatively simple packages.) One of the nicest things is how light it is--no external dependencies, everything can be included in the package itself.

[Numpy-discussion] future of f2py and Fortran90+

F2py is a great tool, but my impression is that it is being left behind by the evolution of Fortran from F90 onward. This is unfortunate; it would be nice to be able to easily wrap new Fortran libraries. I'm curious: has anyone been looking into what it would take to enable f2py to handle mode

Re: [Numpy-discussion] On responding to dubious ideas (was: Re: Advanced indexing: "fancy" vs. orthogonal)

On 2015/04/08 10:02 AM, Alan G Isaac wrote: > 3. I admit, my students are NOT using non-boolen fancy indexing on > multidimensional arrays. (As far as I know.) Are yours? Yes, one attempted to, essentially by accident. That was in my original message. Please refer back to that. The earlier p

Re: [Numpy-discussion] On responding to dubious ideas (was: Re: Advanced indexing: "fancy" vs. orthogonal)

On 2015/04/08 9:40 AM, Ralf Gommers wrote: > Their proposal is not being discussed; instead that potentially useful > discussion is being completely derailed by insisting on wanting to talk > about changes to numpy's indexing behavior. Good point. That was an unintended consequence of my message.

Re: [Numpy-discussion] On responding to dubious ideas (was: Re: Advanced indexing: "fancy" vs. orthogonal)

On 2015/04/08 8:09 AM, Alan G Isaac wrote: > That analogy fails because it suggests a private conversation. This list is > extremely public. > For example, I am just a user, and I am on it. I can tell you that as a > long-time numpy user > my reaction to the proposal to change indexing semantics

Re: [Numpy-discussion] Advanced indexing: "fancy" vs. orthogonal

On 2015/04/03 7:59 AM, Jaime Fernández del Río wrote: > I have an all-Pyhton implementation of an OrthogonalIndexer class, > loosely based on Stephan's code plus some axis remapping, that provides > all the needed functionality for getting and setting with orthogonal > indices. Excellent! > > Wou

Re: [Numpy-discussion] Advanced indexing: "fancy" vs. orthogonal

On 2015/04/02 1:14 PM, Hanno Klemm wrote: > Well, I have written quite a bit of code that relies on fancy > indexing, and I think the question, if the behaviour of the [] > operator should be changed has sailed with numpy now at version 1.9. > Given the amount packages that rely on numpy, changing

Re: [Numpy-discussion] Advanced indexing: "fancy" vs. orthogonal

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 saying there should be no fancy indexing capability; I am saying that it should be available through a function or

Re: [Numpy-discussion] Advanced indexing: "fancy" vs. orthogonal

On 2015/04/02 4:15 AM, Jaime Fernández del Río wrote: > We probably need more traction on the "should this be done?" discussion > than on the "can this be done?" one, the need for a reordering of the > axes swings me slightly in favor, but I mostly don't see it yet. As a long-time user of numpy, a

Re: [Numpy-discussion] Rewrite np.histogram in c?

On 2015/03/23 7:36 AM, Ralf Gommers wrote: > > > On Mon, Mar 23, 2015 at 2:59 PM, Daniel da Silva > mailto:var.mail.dan...@gmail.com>> wrote: > > Hope this isn't too off-topic: but it would be very nice if > np.histogram and np.histogram2d supported masked arrays. Is this out > of scope

Re: [Numpy-discussion] Fix masked arrays to properly edit views

On 2015/03/14 1:02 PM, John Kirkham wrote: > The sample case of the issue ( > https://github.com/numpy/numpy/issues/5558 ) is shown below. A proposal > to address this behavior can be found here ( > https://github.com/numpy/numpy/pull/5580 ). Please give me your feedback. > > > I tried to change th

Re: [Numpy-discussion] numpy pickling problem - python 2 vs. python 3

On 2015/03/06 1:29 PM, Julian Taylor wrote: > I think the ship for a warning has long sailed. At this point its > probably more an annoyance for python3 users and will not prevent many > more python2 users from saving files that can't be loaded into python3. The point of a warning is that anything

Re: [Numpy-discussion] numpy pickling problem - python 2 vs. python 3

On 2015/03/06 10:23 AM, Pauli Virtanen wrote: > 06.03.2015, 20:00, Benjamin Root kirjoitti: >> A slightly different way to look at this is one of sharing data. If I am >> working on a system with 3.4 and I want to share data with others who may >> be using a mix of 2.7 and 3.3 systems, this problem

Re: [Numpy-discussion] Silent Broadcasting considered harmful

On 2015/02/08 12:43 PM, josef.p...@gmail.com wrote: > > For me the main behavior I had to adjust to was loosing a dimension in > any reduce operation, mean, sum, ... > > if x is 2d > x - x.mean(1) > we loose a dimension, and it doesn't broadcast in the right direction Though you can use: x_demea

Re: [Numpy-discussion] Datetime again

On 2015/01/28 6:29 PM, Charles R Harris wrote: > > > And as for "The 64 bits of long long really isn't enough and leads > to all sorts of compromises". not long enough for what? I've always > thought that what we need is the ability to set the epoch. Does > anyone ever need picoseco

Re: [Numpy-discussion] EDF+ specification

Nathaniel, I don't know what sequence of wrong button pushes led to this, but the message was intended for Io Flament. Sorry for the puzzling disruption! Eric On 2015/01/20 1:17 PM, Nathaniel Smith wrote: > On Tue, Jan 20, 2015 at 10:51 PM, Eric Firing wrote: >> http://www.edfp

[Numpy-discussion] EDF+ specification

http://www.edfplus.info/specs/edfplus.html#additionalspecs Io, Is this the file format you have? Eric ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion

Re: [Numpy-discussion] Detect if array has been transposed

On 2014/10/12, 8:29 AM, Pauli Virtanen wrote: > 12.10.2014, 20:19, Mads Ipsen kirjoitti: >> Is there any way for me to detect (on the Python side) that transpose() >> has been invoked on the matrix, and thereby only do the copy operation >> when it really is needed? > > The correct way to do this i

Re: [Numpy-discussion] Numpy 'None' comparison FutureWarning

On 2014/09/21, 11:10 AM, Demitri Muna wrote: > Hi, > > I just encountered the following in my code: > > FutureWarning: comparison to `None` will result in an elementwise object > comparison in the future. > > I'm very concerned about this. This is a very common programming pattern > (lazy loading):

Re: [Numpy-discussion] Short-hand array creation in `numpy.mat` style

On 2014/07/06, 4:27 PM, Alexander Belopolsky wrote: > > On Sun, Jul 6, 2014 at 6:06 PM, Eric Firing <mailto:efir...@hawaii.edu>> wrote: > > (I'm not entirely convinced > np.arr() is a good idea at all; but if it is, it must be kept simple.) > > &

Re: [Numpy-discussion] Short-hand array creation in `numpy.mat` style

On 2014/07/06, 11:43 AM, Nathaniel Smith wrote: > On Sun, Jul 6, 2014 at 9:35 PM, Daniel da Silva > wrote: >> The idea is that there be a short-hand for creating arrays as there is for >> matrices: >> >>np.mat('.2 .7 .1; .3 .5 .2; .1 .1 .9') >> >> It was suggested in GitHub issue #4817 in ligh

Re: [Numpy-discussion] segfault from scipy.io.netcdf with scipy-0.14 numpy-0.18

On 2014/05/07 11:26 PM, Robert McGibbon wrote: > Hey all, > > The travis tests for a library I work on just stopped working, and I > tracked down the bug to the following test case. The file > "MDTraj/testing/reference/mdcrd.nc " is a netcdf3 file > in our repository > (https://git

Re: [Numpy-discussion] List of arrays failing index(), remove() etc

On 2014/05/07 2:14 PM, mfm24 wrote: > I'm having a problem I haven't seen elsewhere (and apologies if it has > been answered before). > > I see the following behavior (copied verbatim from a python session): > > Python 2.7.4 (default, Apr 6 2013, 19:55:15) [MSC v.1500 64 bit (AMD64)] on > win32 >

Re: [Numpy-discussion] Resolving the associativity/precedence debate for @

On 2014/03/22 8:13 AM, Nathaniel Smith wrote: > Hi all, > > After 88 emails we don't have a conclusion in the other thread (see > [1] for background). But we have to come to some conclusion or another > if we want @ to exist:-). So I'll summarize where the discussion > stands and let's see if we ca

Re: [Numpy-discussion] python array

On 2014/03/13 9:09 PM, Sudheer Joseph wrote: > Dear Oslen, > > I had a detailed look at the example you send and points I got were below > > a = np.arange(-8, 8).reshape((4, 4)) > b = ma.masked_array(a, mask=a < 0) > > > Out[33]: b[b<4] > masked_array(data = [-- -- -- -- -- -- -- -- 0 1 2 3], >

Re: [Numpy-discussion] surprising behavior of np.asarray on masked arrays

On 2013/12/05 5:14 PM, Faraz Mirzaei wrote: > Hi, > > If I pass a masked array through np.asarray, I get original unmasked array. > > Example: > > test = np.array([[1, 0], [-1, 3]]) > > testMasked = ma.masked_less_equal(test, 0) > > > print testMasked > > [[1 --] > > [-- 3]] > > > print testMaske

Re: [Numpy-discussion] Masked arrays: Rationale for "False convention"

On 2013/09/30 4:57 PM, Ondřej Čertík wrote: > On Mon, Sep 30, 2013 at 8:29 PM, Eric Firing wrote: >> On 2013/09/30 4:05 PM, josef.p...@gmail.com wrote: >>> On Mon, Sep 30, 2013 at 9:38 PM, Charles R Harris >>> wrote: >>>> >>>> >>>>

Re: [Numpy-discussion] Masked arrays: Rationale for "False convention"

On 2013/09/30 4:05 PM, josef.p...@gmail.com wrote: > On Mon, Sep 30, 2013 at 9:38 PM, Charles R Harris > wrote: >> >> >> >> On Mon, Sep 30, 2013 at 7:05 PM, Ondřej Čertík >> wrote: >>> >>> Hi, >>> >>> What is the rationale for using False in 'mask' for elements that >>> should be included? >>> >>

Re: [Numpy-discussion] Strange behavior with boolean slices...

On 2013/08/25 2:30 PM, Cera, Tim wrote: > I have done this before, but am now really confused. > > Created an array 'day' specifying the 'f' type > > In [29]: day > Out[29]: array([ 5., 5.], dtype=float32) > > # Have a mask... > In [30]: mask > Out[30]: array([ True, False], dtype=bool) > > # So f

Re: [Numpy-discussion] Strange behavior with boolean slices...

On 2013/08/25 2:30 PM, Cera, Tim wrote: > I have done this before, but am now really confused. > > Created an array 'day' specifying the 'f' type > > In [29]: day > Out[29]: array([ 5., 5.], dtype=float32) > > # Have a mask... > In [30]: mask > Out[30]: array([ True, False], dtype=bool) > > # So f

Re: [Numpy-discussion] strange behavior of variable

On 2013/08/17 9:49 PM, Sudheer Joseph wrote: > Hi, > I have defined a small function to find the n maximum values > of an array as below. With in it I assign the input array to a second > array and temporarily make the array location after first iteration as > nan. I expected this tempora

[Numpy-discussion] please close 611, 629, 2490, 2264

Github issues 611, 629, and 2490 are duplicates. 611 included patches with a test and a fix, both of which were committed long ago, so all three issues should be closed. Please see my comment on 2264 as to why that should be closed. On 1417, please remove the "component:numpy.ma" label and add

[Numpy-discussion] bug fixes: which branch?

What is the preferred strategy for handling bug fix PRs? Initial fix on master, and then a separate PR to backport to v1.7.x? Or the reverse? It doesn't look like v1.7.x is being merged into master regularly, so the matplotlib pattern (fix on maintenance, merge maintenance into master) seems

Re: [Numpy-discussion] saving 3d array

On 2013/06/15 6:06 AM, Pierre GM wrote: > > On Jun 15, 2013, at 17:35 , Matthew Brett wrote: > >> Hi, >> >> On Sat, Jun 15, 2013 at 2:51 PM, Sudheer Joseph >> wrote: >>> >>> Thank you very much for this tip. >>> Is there a typical way to save masked and the rest separately?. Not much >>> familia

[Numpy-discussion] time to revisit NA/ma ideas

A nice summary of the discussions from a year ago is here: http://www.numpy.org/NA-overview.html It provides food for thought. Eric ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion

[Numpy-discussion] NA, and replacement or reimplimentation of np.ma

On 2013/06/14 7:22 AM, Nathaniel Smith wrote: > On Wed, Jun 12, 2013 at 7:43 PM, Eric Firing wrote: >> On 2013/06/12 2:10 AM, Nathaniel Smith wrote: >>> Personally I think that overloading np.empty is horribly ugly, will >>> continue confusing newbies and everyone

Re: [Numpy-discussion] numpy.filled, again

On 2013/06/14 5:15 AM, Alan G Isaac wrote: > On 6/14/2013 9:27 AM, Aldcroft, Thomas wrote: >> If I just saw np.values(..) in some code I would never guess what it is >> doing from the name > > That suggests np.fromvalues. > But more important than the name I think > is allowing broadcasting of the

Re: [Numpy-discussion] numpy.filled, again

On 2013/06/13 10:36 AM, Benjamin Root wrote: > > On Thu, Jun 13, 2013 at 9:36 AM, Aldcroft, Thomas > mailto:aldcr...@head.cfa.harvard.edu>> > wrote: > > > > > On Wed, Jun 12, 2013 at 2:55 PM, Eric Firing <mailto:efir...@hawaii.edu>> wrote:

Re: [Numpy-discussion] numpy.filled, again

On 2013/06/12 8:13 AM, Warren Weckesser wrote: > That's why I suggested 'filledwith' (add the underscore if you like). > This also allows a corresponding masked implementation, 'ma.filledwith', > without clobbering the existing 'ma.filled'. Consensus on np.filled? absolutely not, you do not have a

Re: [Numpy-discussion] numpy.filled, again

On 2013/06/12 4:18 AM, Nathaniel Smith wrote: > Now imagine a different new version of this page, if we overload > 'empty' to add a fill= option. I don't even know how we document that > on this page. The list will remain: >empty >ones >zeros Opposite of "empty": "full". So that is an

Re: [Numpy-discussion] numpy.filled, again

On 2013/06/12 2:10 AM, Nathaniel Smith wrote: > Hi all, > > It looks like we've gotten a bit confused and need to untangle > something. There's a PR to add new functions 'np.filled' and > 'np.filled_like': >https://github.com/numpy/numpy/pull/2875 > And there was a discussion about this on the

Re: [Numpy-discussion] empty_like for masked arrays

On 2013/06/10 10:17 AM, Aldcroft, Thomas wrote: > I use np.ma , and for me the most intuitive would be the > second option where the new array matches the original array in shape > and dtype, but always has an empty mask. I always think of the *_like() > functions as just copying sha

Re: [Numpy-discussion] suggested change of behavior for interp

case that I think might reasonably be an option but that should not be required. Eric > > I have been bitten by this problem too. > > Cheers! > Ben Root > > On Jun 4, 2013 9:08 PM, "Eric Firing" <mailto:efir...@hawaii.edu>> wrote: >

Re: [Numpy-discussion] suggested change of behavior for interp

On 2013/06/04 2:05 PM, Charles R Harris wrote: > > > On Tue, Jun 4, 2013 at 12:07 PM, Slavin, Jonathan > mailto:jsla...@cfa.harvard.edu>> wrote: > > Hi, > > I would like to suggest that the behavior of numpy.interp be changed > regarding treatment of situations in which the x-coordinate

Re: [Numpy-discussion] GSOC 2013

On 2013/03/05 8:14 AM, Kurt Smith wrote: > On Tue, Mar 5, 2013 at 1:45 AM, Eric Firing wrote: >> On 2013/03/04 9:01 PM, Nicolas Rougier wrote: >>>>> This made me think of a serious performance limitation of structured >>>>> dtypes: a >>>>>

Re: [Numpy-discussion] GSOC 2013

On 2013/03/04 9:01 PM, Nicolas Rougier wrote: >> >This made me think of a serious performance limitation of structured >> >dtypes: a >> >structured dtype is always "packed", which may lead to terrible byte >> >alignment >> >for common types. For instance, `dtype([('a', 'u1'), ('b', >> >'u8')]).i

Re: [Numpy-discussion] New numpy functions: filled, filled_like

On 2013/01/17 4:13 AM, Pierre Haessig wrote: > Hi, > > Le 14/01/2013 20:05, Benjamin Root a écrit : >> I do like the way you are thinking in terms of the broadcasting >> semantics, but I wonder if that is a bit awkward. What I mean is, if >> one were to use broadcasting semantics for creating an a

Re: [Numpy-discussion] New numpy functions: filled, filled_like

On 2013/01/14 6:15 AM, Olivier Delalleau wrote: > - I agree the name collision with np.ma.filled is a problem. I have no > better suggestion though at this point. How about "initialized()"? ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org htt

Re: [Numpy-discussion] New numpy functions: filled, filled_like

On 2013/01/13 7:27 AM, Nathaniel Smith wrote: > Hi all, > > PR 2875 adds two new functions, that generalize zeros(), ones(), > zeros_like(), ones_like(), by simply taking an arbitrary fill value: >https://github.com/numpy/numpy/pull/2875 > So >np.ones((10, 10)) > is the same as >np.fill

Re: [Numpy-discussion] Regression: in-place operations (possibly intentional)

On 2012/09/21 12:20 PM, Nathaniel Smith wrote: > On Fri, Sep 21, 2012 at 10:04 PM, Chris Barker wrote: >> On Fri, Sep 21, 2012 at 10:03 AM, Nathaniel Smith wrote: >> >>> You're right of course. What I meant is that >>>a += b >>> should produce the same result as >>>a[...] = a + b >>> >>>

Re: [Numpy-discussion] Regression: in-place operations (possibly intentional)

On 2012/09/18 9:25 AM, Charles R Harris wrote: > > > On Tue, Sep 18, 2012 at 1:13 PM, Benjamin Root > wrote: > > > > On Tue, Sep 18, 2012 at 2:47 PM, Charles R Harris > mailto:charlesr.har...@gmail.com>> wrote: > > > > On Tue, Sep 18, 2012 at 11:39 AM, Benja

Re: [Numpy-discussion] numpy.ma.MaskedArray.min() makes a copy?

On 2012/09/18 7:40 AM, Benjamin Root wrote: > > > On Fri, Sep 7, 2012 at 12:05 PM, Nathaniel Smith > wrote: > > On 7 Sep 2012 14:38, "Benjamin Root" > wrote: > > > > An issue just reported on the matplotlib-users list involved a >

Re: [Numpy-discussion] Fancy-indexing reorders output in corner cases?

On 05/14/2012 06:03 PM, Travis Oliphant wrote: > What happens, though when you have > > a[:, in1 :, in2]? > > in1 and in2 are broadcasted together to create a two-dimensional > "sub-space" that must fit somewhere. Where should it go? Should > it replace in1 or in2?I.e. should the output be

Re: [Numpy-discussion] Removing masked arrays for 1.7? (Was 1.7 blockers)

On 04/17/2012 08:40 AM, Matthew Brett wrote: > Hi, > > On Tue, Apr 17, 2012 at 7:24 AM, Nathaniel Smith wrote: >> On Tue, Apr 17, 2012 at 5:59 AM, Matthew Brett >> wrote: >>> Hi, >>> >>> On Mon, Apr 16, 2012 at 8:40 PM, Travis Oliphant >>> wrote: Mark and I will have conversations about N

Re: [Numpy-discussion] Masked Arrays in NumPy 1.x

On 04/09/2012 06:52 PM, Travis Oliphant wrote: > Hey all, > > I've been waiting for Mark Wiebe to arrive in Austin where he will > spend several weeks, but I also know that masked arrays will be only > one of the things he and I are hoping to make head-way on while he is > in Austin.Nevertheles

Re: [Numpy-discussion] Using logical function on more than 2 arrays, availability of a "between" function ?

On 03/25/2012 12:22 PM, Pierre Haessig wrote: > Hi Eric, > > Thanks for the hints ! > > Le 25/03/2012 20:33, Eric Firing a écrit : >> Using the bitwise operators in place of logical operators is a hack to >> get around limitations of the language; but, if done caref

Re: [Numpy-discussion] Using logical function on more than 2 arrays, availability of a "between" function ?

On 03/25/2012 06:55 AM, Pierre Haessig wrote: > Hi, > > I have an off topic but somehow related question : > > Le 19/03/2012 12:04, Matthieu Rigal a écrit : >> array = numpy.logical_and(numpy.logical_and(aBlueChannel< 1.0, aNirChannel> >> (aBlueChannel * 1.0)), aNirChannel< (aBlueChannel * 1.8))

Re: [Numpy-discussion] Missing data again

On 03/07/2012 11:15 AM, Pierre Haessig wrote: > Hi, > Le 07/03/2012 20:57, Eric Firing a écrit : >> In other words, good low-level support for numpy.ma functionality? > Coming back to *existing* ma support, I was just wondering whether it > was now possible to "np.save&

Re: [Numpy-discussion] Missing data again

On 03/07/2012 09:26 AM, Nathaniel Smith wrote: > On Wed, Mar 7, 2012 at 5:17 PM, Charles R Harris > wrote: >> On Wed, Mar 7, 2012 at 9:35 AM, Pierre Haessig >>> Coming back to Travis proposition "bit-pattern approaches to missing >>> data (*at least* for float64 and int32) need to be implemented.

Re: [Numpy-discussion] change the mask state of one element in a masked array

On 02/18/2012 05:52 AM, Chao YUE wrote: > Dear all, > > I built a new empty masked array: > > In [91]: a=np.ma.empty((2,5)) Of course this only makes sense if you are going to immediately populate the array. > > In [92]: a > Out[92]: > masked_array(data = > [[ 1.20569155e-312 3.34730819e-31

Re: [Numpy-discussion] Proposed Roadmap Overview

On 02/17/2012 09:55 PM, David Cournapeau wrote: > I may not have explained it very well: my whole point is that we don't > recruite people, where I understand recruit as hiring full time, > profesional programmers.We need more people who can casually spend a few > hours - typically grad students, s

Re: [Numpy-discussion] Proposed Roadmap Overview

On 02/17/2012 05:39 AM, Charles R Harris wrote: > > > On Fri, Feb 17, 2012 at 8:01 AM, David Cournapeau > wrote: > > Hi Travis, > > On Thu, Feb 16, 2012 at 10:39 PM, Travis Oliphant > mailto:tra...@continuum.io>> wrote: > > Mark Wiebe and I have been dis

Re: [Numpy-discussion] Numpy governance update

On 02/15/2012 08:50 AM, Matthew Brett wrote: > Hi, > > On Wed, Feb 15, 2012 at 5:51 AM, Alan G Isaac wrote: >> On 2/14/2012 10:07 PM, Bruce Southey wrote: >>> The one thing that gets over looked here is that there is a huge >>> diversity of users with very different skill levels. But very few >>>

Re: [Numpy-discussion] Change in scalar upcasting rules for 1.6.x?

On 02/13/2012 08:07 PM, Charles R Harris wrote: > > > Let it go, Travis. It's a waste of time. (Off-list) Chuck, I really appreciate your consistent good sense; this is just one of many examples. Thank you for all your numpy work. Eric ___ NumPy-Disc

Re: [Numpy-discussion] Migrating issues to GitHub

On 02/11/2012 10:44 AM, Travis Oliphant wrote: > This is good feedback. > > It looks like there are 2 concerns: > > 1) no way to add attachments --- it would seem that gists and indeed > other github repos solves that problem. Not really, in practice. Yes one can use these mechanisms, but they ar

Re: [Numpy-discussion] numpy.arange() error?

On 02/09/2012 09:20 AM, Drew Frank wrote: > Eric Firing hawaii.edu> writes: > >> >> On 02/08/2012 09:31 PM, teomat wrote: >>> >>> Hi, >>> >>> Am I wrong or the numpy.arange() function is not correct 100%? >>> >>> T

Re: [Numpy-discussion] numpy.arange() error?

On 02/08/2012 09:31 PM, teomat wrote: > > Hi, > > Am I wrong or the numpy.arange() function is not correct 100%? > > Try to do this: > > In [7]: len(np.arange(3.1, 4.9, 0.1)) > Out[7]: 18 > > In [8]: len(np.arange(8.1, 9.9, 0.1)) > Out[8]: 19 > > I would expect the same result for each command. No

Re: [Numpy-discussion] NetCDF4/numpy question

On 01/27/2012 11:18 AM, Howard wrote: > Hi all > > I am a fairly recent convert to python and I have got a question that's > got me stumped. I hope this is the right mailing list: here goes :) > > I am reading some time series data out of a netcdf file a single > timestep at a time. If the data is

Re: [Numpy-discussion] consensus (was: NA masks in the next numpy release?)

On 10/29/2011 12:57 PM, Charles R Harris wrote: > > > On Sat, Oct 29, 2011 at 4:47 PM, Eric Firing <mailto:efir...@hawaii.edu>> wrote: > > On 10/29/2011 12:02 PM, Olivier Delalleau wrote: > > > > > I haven't been following the discussi

Re: [Numpy-discussion] consensus (was: NA masks in the next numpy release?)

On 10/29/2011 12:02 PM, Olivier Delalleau wrote: > > I haven't been following the discussion closely, but wouldn't it be instead: > a.mask[0:2] = True? That would be consistent with numpy.ma and the opposite of Mark's implementation. I can live with either, but I much prefer the numpy.ma versio

Re: [Numpy-discussion] consensus (was: NA masks in the next numpy release?)

On 10/29/2011 12:26 AM, Ralf Gommers wrote: > The history of this discussion doesn't suggest it straightforward to get > a design right first time. It's a complex subject. > > The second part of your statement, "and then implement", sounds so > simple. The reality is that there are only a handful o

Re: [Numpy-discussion] NA masks in the next numpy release?

On 10/25/2011 04:56 PM, Travis Oliphant wrote: > So, I am very interested in making sure I remember the details of the > counterproposal.What I recall is that you wanted to be able to > differentiate between a "bit-pattern" mask and a boolean-array mask > in the API. I believe currently even

Re: [Numpy-discussion] NA masks in the next numpy release?

On 10/23/2011 12:34 PM, Nathaniel Smith wrote: > like. And in this case I do think we can come up with an API that will > make everyone happy, but that Mark's current API probably can't be > incrementally evolved to become that API.) > No one could object to coming up with an API that makes every

Re: [Numpy-discussion] NA masks in the next numpy release?

On 10/23/2011 10:49 AM, Nathaniel Smith wrote: > But I (and presumably others) were unaware of the pull request, > because it turns out that actually Mark did*not* point to the pull > request, at least in email to either me or numpy-discussion. As far as > I can tell, the first time that pull requ

Re: [Numpy-discussion] anyway to check a ndarray is a mased array or not?

On 10/18/2011 03:13 AM, Olivier Delalleau wrote: > if hasattr(a, 'mask'): # or if isinstance(a, numpy.ma.core.MaskedArray.) or if numpy.ma.isMA(a): or if numpy.ma.isMaskedArray(a): Eric > code 1 > else > code 2 > > -=- Olivier > > 2011/10/18 Chao YUE mailto:chaoyue...@gmail.com>>

Re: [Numpy-discussion] wanted: decent matplotlib alternative

On 10/13/2011 12:22 PM, Gökhan Sever wrote: > > > On Thu, Oct 13, 2011 at 4:15 PM, Benjamin Root > wrote: > > Myself and other developers would greatly appreciate help from the > community to point out which examples are too confusing or out of > date. We > > >

Re: [Numpy-discussion] numpy.interp running time

On 08/16/2011 04:22 AM, Timo Kluck wrote: > 2011/8/1 Timo Kluck: >> I just submitted a patch at >> http://projects.scipy.org/numpy/ticket/1920 . It implements Eric's >> suggestion. Please review, I'll be happy to adapt it to any of your >> feedback. >> > I submitted a minor patch a while ago. It ha

Re: [Numpy-discussion] Reading a big netcdf file

On 08/03/2011 11:24 AM, Gökhan Sever wrote: > I[1]: timeit a = np.fromfile('temp.npa', dtype=np.uint16) > 1 loops, best of 3: 263 ms per loop You need to clear your cache and then run timeit with options "-n1 -r1". Eric ___ NumPy-Discussion mailing lis

Re: [Numpy-discussion] numpy.interp running time

On 07/29/2011 11:18 AM, Timo Kluck wrote: > Dear numpy developers, > > The current implementation of numpy.interp(x,xp,fp) comes down to: first > calculating all the slopes of the linear interpolant (these are > len(xp)-1), then use a binary search to find where x is in xp (running > time log(len(x

Re: [Numpy-discussion] code review request: masked dtype transfers

On 07/08/2011 01:31 PM, Mark Wiebe wrote: > I've just made pull request 105: > > https://github.com/numpy/numpy/pull/105 > It's merged, which is good, but I have a suggestion relevant to that pull and I suspect to many others to come: use defines and macros to consolidate some of the implementat

Re: [Numpy-discussion] code review request: masked dtype transfers

On 07/08/2011 01:31 PM, Mark Wiebe wrote: > I've just made pull request 105: > > https://github.com/numpy/numpy/pull/105 > > This adds public API PyArray_MaskedCopyInto and PyArray_MaskedMoveInto, > which behave analogously to the corresponding unmasked functions. To > expose this with a reasonable

Re: [Numpy-discussion] code review request: masked dtype transfers

On 07/08/2011 01:31 PM, Mark Wiebe wrote: > I've just made pull request 105: > > https://github.com/numpy/numpy/pull/105 > > This adds public API PyArray_MaskedCopyInto and PyArray_MaskedMoveInto, > which behave analogously to the corresponding unmasked functions. To > expose this with a reasonable

Re: [Numpy-discussion] using the same vocabulary for missing value ideas

On 07/06/2011 07:51 PM, Chris Barker wrote: > On 7/6/11 11:57 AM, Mark Wiebe wrote: >> On Wed, Jul 6, 2011 at 1:25 PM, Christopher Barker > >> Is this really true? if you use a bitpattern for IGNORE, haven't you >> just lost the ability to get the original value back if you want to stop >

Re: [Numpy-discussion] alterNEP - was: missing data discussion round 2

On 07/01/2011 06:40 PM, Nathaniel Smith wrote: > On Fri, Jul 1, 2011 at 9:29 AM, Christopher Jordan-Squire > BTW, you can't access the memory of a masked value by taking a view, > at least if I'm reading this version of the NEP correctly, and it > seems to be the latest: > > https://github.com

Re: [Numpy-discussion] Missing/accumulating data

On 07/01/2011 10:27 AM, Charles R Harris wrote: > > > On Fri, Jul 1, 2011 at 1:39 PM, Christopher Barker > mailto:chris.bar...@noaa.gov>> wrote: > > Joe Harrington wrote: > > All > > that has to happen is to allow the sense of the mask to be FALSE > = the > > data are bad, T

Re: [Numpy-discussion] missing data discussion round 2

On 06/30/2011 08:53 AM, Nathaniel Smith wrote: > On Wed, Jun 29, 2011 at 2:21 PM, Eric Firing wrote: >> In addition, for new code, the full-blown masked array module may not be >> needed. A convenience it adds, however, is the automatic masking of >> invalid values: >&

Re: [Numpy-discussion] missing data discussion round 2

On 06/29/2011 09:32 AM, Matthew Brett wrote: > Hi, > [...] > > Clearly there are some overlaps between what masked arrays are trying > to achieve and what Rs NA mechanisms are trying to achieve. Are they > really similar enough that they should function using the same API? > And if so, won't that

Re: [Numpy-discussion] missing data discussion round 2

On 06/28/2011 07:26 AM, Nathaniel Smith wrote: > On Tue, Jun 28, 2011 at 9:38 AM, Charles R Harris > wrote: >> Nathaniel, an implementation using masks will look *exactly* like an >> implementation using na-dtypes from the user's point of view. Except that >> taking a masked view of an unmasked a

Re: [Numpy-discussion] Concepts for masked/missing data

On 06/25/2011 09:09 AM, Benjamin Root wrote: > > > On Sat, Jun 25, 2011 at 1:57 PM, Nathaniel Smith <mailto:n...@pobox.com>> wrote: > > On Sat, Jun 25, 2011 at 11:50 AM, Eric Firing <mailto:efir...@hawaii.edu>> wrote: > > On 06/25/2011 07:05

Re: [Numpy-discussion] Concepts for masked/missing data

On 06/25/2011 07:05 AM, Nathaniel Smith wrote: > On Sat, Jun 25, 2011 at 9:26 AM, Matthew Brett > wrote: >> So far I see the difference between 1) and 2) being that you cannot >> unmask. So, if you didn't even know you could unmask data, then it >> would not matter that 1) was being implemented

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