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

On Fri, Sep 21, 2012 at 5:51 PM, Eric Firing wrote: > 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 +=

Re: [Numpy-discussion] specifying numpy as dependency in your project, install_requires

On Fri, Sep 21, 2012 at 5:39 PM, Nathaniel Smith wrote: > On Fri, Sep 21, 2012 at 9:42 PM, Ralf Gommers wrote: >> Eh, just installing numpy with "python setup.py install" uses plain >> distutils, not setuptools. So there indeed isn't an entry in >> easy-install.pth. Which some consider a feature

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 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 >> >> If we change the casting rule for the first one but not the

Re: [Numpy-discussion] specifying numpy as dependency in your project, install_requires

On Fri, Sep 21, 2012 at 9:42 PM, Ralf Gommers wrote: > Eh, just installing numpy with "python setup.py install" uses plain > distutils, not setuptools. So there indeed isn't an entry in > easy-install.pth. Which some consider a feature:) I don't think this is correct. To be clear on the technica

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

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 > > If we change the casting rule for the first one but not the second, though, > then these will produce different results if

Re: [Numpy-discussion] specifying numpy as dependency in your project, install_requires

On Fri, Sep 21, 2012 at 4:37 PM, Benjamin Root wrote: > > > On Fri, Sep 21, 2012 at 4:19 PM, Travis Oliphant > wrote: >> >> >> On Sep 21, 2012, at 3:13 PM, Ralf Gommers wrote: >> >> Hi, >> >> An issue I keep running into is that packages use: >> install_requires = ["numpy"] >> or >> insta

Re: [Numpy-discussion] specifying numpy as dependency in your project, install_requires

On Fri, Sep 21, 2012 at 10:37 PM, Benjamin Root wrote: > > > On Fri, Sep 21, 2012 at 4:19 PM, Travis Oliphant wrote: > >> >> On Sep 21, 2012, at 3:13 PM, Ralf Gommers wrote: >> >> Hi, >> >> An issue I keep running into is that packages use: >> install_requires = ["numpy"] >> or >> install

Re: [Numpy-discussion] specifying numpy as dependency in your project, install_requires

Am Fr 21 Sep 2012 22:37:13 CEST schrieb Benjamin Root: > > > On Fri, Sep 21, 2012 at 4:19 PM, Travis Oliphant > wrote: > > > On Sep 21, 2012, at 3:13 PM, Ralf Gommers wrote: > >> Hi, >> >> An issue I keep running into is that packages use: >> install

Re: [Numpy-discussion] specifying numpy as dependency in your project, install_requires

On Fri, Sep 21, 2012 at 4:19 PM, Travis Oliphant wrote: > > On Sep 21, 2012, at 3:13 PM, Ralf Gommers wrote: > > Hi, > > An issue I keep running into is that packages use: > install_requires = ["numpy"] > or > install_requires = ['numpy >= 1.6'] > > in their setup.py. This simply doesn't w

Re: [Numpy-discussion] specifying numpy as dependency in your project, install_requires

On Sep 21, 2012, at 3:13 PM, Ralf Gommers wrote: > Hi, > > An issue I keep running into is that packages use: > install_requires = ["numpy"] > or > install_requires = ['numpy >= 1.6'] > > in their setup.py. This simply doesn't work a lot of the time. I actually > filed a bug against pa

[Numpy-discussion] specifying numpy as dependency in your project, install_requires

Hi, An issue I keep running into is that packages use: install_requires = ["numpy"] or install_requires = ['numpy >= 1.6'] in their setup.py. This simply doesn't work a lot of the time. I actually filed a bug against patsy for that (https://github.com/pydata/patsy/issues/5), but Nathaniel

Re: [Numpy-discussion] Fwd: Package: scipy-0.11.0-0.1.rc2.fc18 Tag: f18-updates-candidate Status: failed Built by: orion

Hi Orion, On Thu, Sep 20, 2012 at 2:56 PM, Orion Poplawski wrote: > This is a plea for some help. We've been having trouble getting scipy to > pass all of the tests in the Fedora 18 build with python 3.3 (although it > seems to build okay in Fedora 19). Below are the logs of the build. There >

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

On 21 Sep 2012 17:31, "Chris Barker" wrote: > > On Thu, Sep 20, 2012 at 2:48 PM, Nathaniel Smith wrote: > > because a += b > > really should be the same as a = a + b. > > I don't think that's the case - the inplace operator should be (and > are) more than syntactic sugar -- they have a different

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

On Thu, Sep 20, 2012 at 2:48 PM, Nathaniel Smith wrote: > because a += b > really should be the same as a = a + b. I don't think that's the case - the inplace operator should be (and are) more than syntactic sugar -- they have a different meaning and use (in fact, I think they should't work at al

Re: [Numpy-discussion] ZeroRank memmap behavior?

Hey, this is indirectly related (I think it might fix many of these memmap oddities though?)... Why does the memmap object not implement: def __array_wrap__(self, obj): if self is obj: return obj return np.array(obj, copy=False, subok=False) By doing so if we hav

[Numpy-discussion] ZeroRank memmap behavior?

I'm deeply puzzled by the recently changed behavior of zero-rank memmaps. I think this change happened from version 1.6.0 to 1.6.1, which I'm currently using. >>> import numpy as np Create a zero-rank memmap. >>> x = np.memmap(filename='/tmp/m', dtype=float, mode='w+', shape=()) Give it a value