Mailman 3 December 2015 - NumPy-Discussion

random integers
by Charles R Harris Dec. 31, 2015

Dec. 31, 2015

Hi All, I've implemented several new random integer functions in #6910 <https://github.com/numpy/numpy/pull/6910>, to wit - np.random.random_int32 - np.random.random_int64 - np.random.random_intp These are the minimum functions that I think we need for the numpy 1.11.0 release, most especially the random_intp function for fuzz testing the mem_overlap functions. However, there is the question of the best way to expose the functions. Currently, they are all separately exposed, … [View More]

2 1

How to find indices of values in an array (indirect in1d) ?
by Nicolas P. Rougier Dec. 30, 2015

Dec. 30, 2015

I’m scratching my head around a small problem but I can’t find a vectorized solution. I have 2 arrays A and B and I would like to get the indices (relative to B) of elements of A that are in B: >>> A = np.array([2,0,1,4]) >>> B = np.array([1,2,0]) >>> print (some_function(A,B)) [1,2,0] # A[0] == 2 is in B and 2 == B[1] -> 1 # A[1] == 0 is in B and 0 == B[2] -> 2 # A[2] == 1 is in B and 1 == B[0] -> 0 Any idea ? I tried numpy.in1d with no luck. Nicolas

5 11

Re: [Numpy-discussion] How to find indices of values in an array (indirect in1d) ?
by Peter Creasey Dec. 30, 2015

Dec. 30, 2015

> > In the end, I?ve only the list comprehension to work as expected > > A = [0,0,1,3] > B = np.arange(8) > np.random.shuffle(B) > I = [list(B).index(item) for item in A if item in B] > > > But Mark's and Sebastian's methods do not seem to work... > The function you want is also in the open source astronomy package iccpy ( https://github.com/Lowingbn/iccpy ), which essentially does a variant of Sebastian’s code (which I also couldn’t quite get working), and … [View More]

1 0

Support of @= in numpy?
by Hans Larsen Dec. 27, 2015

Dec. 27, 2015

I have a Python3.5.1 64bits on Windows 10 same bit-length! I want to knowing when and what version of numpy, that support @= ? I have a functional numpy-1-10-1!=-O -- Hans Larsen Galgebakken Sønder 4-11A 2620 Albertslund Danmark/Danio

3 3

Problem writing array with savetxt (python3.5)
by Maxim Mayzel Dec. 26, 2015

Dec. 26, 2015

Dear all, I’m having a problem writing an array with np.savetxt, see below. (python3.5, numpy 1.10.1) import numpy as np a=np.ones(5,dtype=int) np.savetxt('t.txt',a) Works fine, but the content of ’t.txt’ is overwritten. But, passing file handle gives an error, while it works fine on python2.7 ! with open('t.txt','w') as t: np.savetxt(t,a,fmt='%i') ...: --------------------------------------------------------------------------- TypeError Traceback (… [View More]

2 1

Re: [Numpy-discussion] [SciPy-Dev] ANN: first release candidate for scipy 0.17.0
by Matthew Brett Dec. 24, 2015

Dec. 24, 2015

Hi, On Wed, Dec 23, 2015 at 12:34 PM, Evgeni Burovski <evgeny.burovskiy(a)gmail.com> wrote: > Hi, > > I'm pleased to announce the availability of the first release > candidate for Scipy 0.17.0. Please try this rc and report any issues > on Github tracker or scipy-dev mailing list. > Source tarballs and full release notes are available from Github > Releases: https://github.com/scipy/scipy/releases/tag/v0.17.0rc1 > > Please note that this is a source-only … [View More]

1 0

packaging of numpy for windows
by jo Dec. 23, 2015

Dec. 23, 2015

Hi I would like to package python + numpy and our app for windows using pynsist in such a way that the user does not need to compile anything. Although pynsist made a package numpy did not start after installation due to some missing libraries. Obviously including the numpy directory is not enough. Is there an nsi script or filelist for numpy what I should deliver ? Do I need msft redistributables? tx

1 0

numpy-1.11.0.dev0 windows wheels compiled with mingwpy available
by Carl Kleffner Dec. 23, 2015

Dec. 23, 2015

I made numpy master (numpy-1.11.0.dev0 , https://github.com/numpy/numpy/commit/0243bce23383ff5e894b99e40df2f8fd806ad…) windows binary wheels available for testing. Install it with pip: > pip install -i https://pypi.anaconda.org/carlkl/simple numpy These builds are compiled with OPENBLAS trunk for BLAS/LAPACK support and the mingwpy compiler toolchain. OpenBLAS is deployed within the numpy wheels. To be performant on all usual CPU architectures OpenBLAS is configured with it's 'dynamic … [View More]

6 7

Re: [Numpy-discussion] PR for complex np.interp, question about assert_almost_equal
by Peter Creasey Dec. 22, 2015

Dec. 22, 2015

>>> The tests pass on my machine, but I see that the TravisCI builds are >>> giving assertion fails (on my own test) with python 3.3 and 3.5 of the >>> form: >>> > assert_almost_equal >>> > TypeError: Cannot cast array data from dtype('complex128') to >>> dtype('float64') according to the rule 'safe' >>> > > The problem then is probably here > <https://github.com/numpy/numpy/pull/6872/files#diff-… [View More]

1 0

Proposal: stop providing official win32 downloads (for now)
by Nathaniel Smith Dec. 22, 2015

Dec. 22, 2015

Hi all, I'm wondering what people think of the idea of us (= numpy) stopping providing our "official" win32 builds (the "superpack installers" distributed on sourceforge) starting with the next release. These builds are: - low quality: they're linked to an old & untuned build of ATLAS, so linear algebra will be dramatically slower than builds using MKL or OpenBLAS. They're win32 only and will never support win64. They're using an ancient version of gcc. They will never support python 3.5 … [View More]

11 20