Mailman 3 November 2016 - NumPy-Discussion

Re: [Numpy-discussion] array comprehension
by Nathaniel Smith 04 Nov '16

04 Nov '16

Are you sure fromiter doesn't make an intermediate list or equivalent? It has to collect all the values before it can know the shape or dtype of the array to put them in. On Nov 4, 2016 5:26 AM, "Francesc Alted" <faltet(a)gmail.com> wrote: 2016-11-04 13:06 GMT+01:00 Neal Becker <ndbecker2(a)gmail.com>: > I find I often write: > np.array ([some list comprehension]) > > mainly because list comprehensions are just so sweet. > > But I imagine this isn't particularly efficient. > Right. Using a generator and np.fromiter() will avoid the creation of the intermediate list. Something like: np.fromiter((i for i in range(x))) # use xrange for Python 2 > > I wonder if numpy has a "better" way, and if not, maybe it would be a nice > addition? > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion(a)scipy.org > https://mail.scipy.org/mailman/listinfo/numpy-discussion > -- Francesc Alted _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion(a)scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion

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ANN: pandas v0.19.1 released!
by Joris Van den Bossche 04 Nov '16

04 Nov '16

Hi all, I'm pleased to announce the release of pandas 0.19.1. This is a bug-fix release from 0.19.0 and includes some small regression fixes, bug fixes and performance improvements. We recommend that all users upgrade to this version. See the v0.19.1 Whatsnew page <http://pandas.pydata.org/pandas-docs/version/0.19.1/whatsnew.html> for an overview of all bugs that have been fixed in 0.19.1. Thanks to all contributors! Joris --- *How to get it:* Source tarballs and windows/mac/linux wheels are available on PyPI (thanks to Christoph Gohlke for the windows wheels, and to Matthew Brett for setting up the mac/linux wheels). Conda packages are already available via the conda-forge channel (conda install pandas -c conda-forge). It will be available on the main channel shortly. *Issues:* Please report any issues on our issue tracker: https://github.com/pydata/ pandas/issues *Thanks to all the contributors of the 0.19.1 release:* - Adam Chainz - Anthonios Partheniou - Arash Rouhani - Ben Kandel - Brandon M. Burroughs - Chris - chris-b1 - Chris Warth - David Krych - dubourg - gfyoung - Iván Vallés Pérez - Jeff Reback - Joe Jevnik - Jon M. Mease - Joris Van den Bossche - Josh Owen - Keshav Ramaswamy - Larry Ren - mattrijk - Michael Felt - paul-mannino - Piotr Chromiec - Robert Bradshaw - Sinhrks - Thiago Serafim - Tom Bird

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array comprehension
by Neal Becker 04 Nov '16

04 Nov '16

I find I often write: np.array ([some list comprehension]) mainly because list comprehensions are just so sweet. But I imagine this isn't particularly efficient. I wonder if numpy has a "better" way, and if not, maybe it would be a nice addition?

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Branching NumPy 1.12.x
by Charles R Harris 04 Nov '16

04 Nov '16

Hi All, I'm thinking that it is time to branch NumPy 1.12.x. I haven't got everything in it that I would have liked, in particular __numpy_ufunc__, but I think there is plenty of material and not branching is holding up some of the more risky stuff. My current thoughts on __numpy_ufunc__ is that it would be best to work it out over the 1.13.0 release cycle, starting with enabling it again right after the branch. Julian's work on avoiding temporary copies and Pauli's overlap handling PR are two other changes I've been putting off but don't want to delay further. There are some other smaller things that I had scheduled for 1.12.0, but would like to spend more time looking at. If there are some things that you think just have to be in 1.12.0, please mention them, but I'd rather aim at getting 1.13.0 out in a timely manner. Thoughts? Chuck

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Useless but tricky exercise
by Nicolas P. Rougier 03 Nov '16

03 Nov '16

Hi all, Given an array V that is a view of a base B, I was wondering if it is possible to find a (string) index such that `V = B[index]` For example: ``` B = np.arange(8*8).reshape(8,8) V = B[::2,::2] index = find_view(B,V) print(index) "::2,::2" print(np.allclose(V, eval("B[%s]" % index))) True ``` I wrote a solution at https://gist.github.com/rougier/b8c2256434b3a4a4271260cd4cc6cbc7 (not very thoroughly tested) but maybe there are better ways to do that (like a magic numpy call ?) (no use-case at all, only for teaching) Nicolas

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Using numpy.rint() with scalars
by Yuri Sukhov 03 Nov '16

03 Nov '16

Hi all, According to the documentation for numpy.rint() (https://docs.scipy.org/doc/ numpy/reference/generated/numpy.rint.html), it's a ufunc that accepts an array-like object as an input. But it also works with scalar inputs. Could anyone clarify if such use case is considered to be common and acceptable? It it just the documentation that does not cover one of the possible scenarios, or is it a side effect and such use case should be avoided? I want to use rint() with scalars as I have not found an alternative with the same behavior in cPython, but if it's not how it should be used, I don't want to rewrite the app when that behavior will change. Thanks! Yuri.

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missing from contributor list?
by Sturla Molden 03 Nov '16

03 Nov '16

Why am I missing from the contributor hist here? https://github.com/numpy/numpy/blob/master/numpy/_build_utils/src/apple_sge… Sturla

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