<div dir="ltr"><br><div class="gmail_extra"><br><div class="gmail_quote">On Thu, Aug 24, 2017 at 6:56 PM, Pauli Virtanen <span dir="ltr"><<a href="mailto:pav@iki.fi" target="_blank">pav@iki.fi</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">-----BEGIN PGP SIGNED MESSAGE-----<br>
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Dear all,<br>
<br>
Prerelease binary wheels for Scipy on Windows 32-bit & 64-bit are now<br>
available in case you would like to test them.<br>
<br>
Currently, the plans are that binary wheels will also be provided for<br>
future releases on PyPi, so that you will be able to do simply "pip<br>
install scipy" also on Windows. At least, assuming we manage to test<br>
these wheels well enough for which help would be useful.<br>
<br>
You can install the scipy prerelease packages as shown below. Note that<br>
they are meant for testing only, and correspond to the current Scipy<br>
development version. Please report issues found on the Scipy issue<br>
tracker on github (be sure to mention how you installed scipy and<br>
python).<br>
<br>
The wheels are meant to be used with the Python obtained from <a href="https://p" rel="noreferrer" target="_blank">https://p</a><br>
<a href="http://ython.org" rel="noreferrer" target="_blank">ython.org</a> --- these are not meant to be used with e.g. Conda, although<br>
it may be they work.<br></blockquote><div><br></div><div>What's the numpy requirement?</div><div>I assume the scipy version should not be used with a currently installed numpy unless it is Fortran compatible.</div><div>For example, Winpython distributes Gohlke's binaries build with MKL.</div><div>Is there an automatic check when not installing into an empty virtual environment?</div><div><br></div><div>Josef</div><div><br></div><div><br></div><div><br></div><div> </div><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">
<br>
The work leading to a viable automatized compilation approach was done<br>
in<br>
<a href="https://github.com/scipy/scipy/pull/7616" rel="noreferrer" target="_blank">https://github.com/scipy/<wbr>scipy/pull/7616</a><br>
<a href="https://github.com/numpy/numpy/pull/9431" rel="noreferrer" target="_blank">https://github.com/numpy/<wbr>numpy/pull/9431</a><br>
<br>
Example:<br>
<br>
C:\Users\pauli\src\env2\<wbr>Scripts>pip install -f <a href="https://7933911d6844c6c53a7d-47bd50c35cd79bd838daf386af554a83.ssl.cf2.rackcdn.com/" rel="noreferrer" target="_blank">https://7933911d6844c6c53a7d-<wbr>47bd50c35cd79bd838daf386af554a<wbr>83.ssl.cf2.rackcdn.com/</a> --pre scipy<br>
Collecting scipy<br>
Downloading <a href="https://7933911d6844c6c53a7d-47bd50c35cd79bd838daf386af554a83.ssl.cf2.rackcdn.com/scipy-1.0.0.dev0+20170824221943_2a1fdcf-cp36-none-win32.whl" rel="noreferrer" target="_blank">https://7933911d6844c6c53a7d-<wbr>47bd50c35cd79bd838daf386af554a<wbr>83.ssl.cf2.rackcdn.com/scipy-<wbr>1.0.0.dev0+20170824221943_<wbr>2a1fdcf-cp36-none-win32.whl</a> (26.0MB)<br>
100% |█████████████████████████████<wbr>███| 26.0MB 47kB/s<br>
Collecting numpy>=1.8.2 (from scipy)<br>
Downloading <a href="https://7933911d6844c6c53a7d-47bd50c35cd79bd838daf386af554a83.ssl.cf2.rackcdn.com/numpy-1.14.0.dev0+20170824081646_707f33f-cp36-none-win32.whl" rel="noreferrer" target="_blank">https://7933911d6844c6c53a7d-<wbr>47bd50c35cd79bd838daf386af554a<wbr>83.ssl.cf2.rackcdn.com/numpy-<wbr>1.14.0.dev0+20170824081646_<wbr>707f33f-cp36-none-win32.whl</a> (6.8MB)<br>
100% |█████████████████████████████<wbr>███| 6.9MB 168kB/s<br>
Installing collected packages: numpy, scipy<br>
Successfully installed numpy-1.14.0.dev0+707f33f scipy-1.0.0.dev0+2a1fdcf<br>
<br>
C:\Users\pauli\src\env2\<wbr>Scripts>python<br>
Python 3.6.2 (v3.6.2:5fd33b5, Jul 8 2017, 04:14:34) [MSC v.1900 32 bit (Intel)] on win32<br>
Type "help", "copyright", "credits" or "license" for more information.<br>
>>> import scipy.integrate, scipy.linalg, numpy as np<br>
>>> scipy.integrate.quad(lambda x: 1/(1 + x**2), -np.inf, np.inf)<br>
(3.141592653589793, 5.155583041103855e-10)<br>
>>> scipy.linalg.eigvals([[1,0],[<wbr>0,2]])<br>
array([ 1.+0.j, 2.+0.j])<br>
>>> exit()<br>
<br>
- --<br>
Pauli Virtanen<br>
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</blockquote></div><br></div></div>