Mailman 3 October 2010 - NumPy-Discussion

Matlab IO Warning in mio5.py
by Ben Longstaff 22 Nov '10

22 Nov '10

Is the warning message produced by the test script below an issue I need to address if I am to use the numpy and scipy libraries? The script below gives me the warning below on both windows 7 and vista Thanks for your time Ben Python Script #!/path/to/python import re, string, sys from numpy import * import scipy.weave print "Hello, World!" Warning Message C:\Python26\lib\site-packages\scipy\io\matlab\mio5.py:90: RuntimeWarning: __builtin__.file size changed, may indicate binary incompatibility from mio5_utils import VarReader5 Hello, World!

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Test failures on 2.6
by T J 18 Nov '10

18 Nov '10

Hi, I'm getting a couple of test failures with Python 2.6, Numpy 1.2.0, Nose 0.10.4: nose version 0.10.4 ..........................................................................................................................................................................................................................................................................................................................................................................................................................................F................K........................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................./share/home/me/usr/lib/python2.6/site-packages/numpy/lib/tests/test_io.py:68: SyntaxWarning: assertion is always true, perhaps remove parentheses? assert(c.readlines(), ........................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................./share/home/me/usr/lib/python2.6/site-packages/numpy/ma/tests/test_core.py:1315: SyntaxWarning: assertion is always true, perhaps remove parentheses? assert(store._mask, True) /home/me/usr/lib/python2.6/site-packages/numpy/ma/tests/test_core.py:1322: SyntaxWarning: assertion is always true, perhaps remove parentheses? assert(store._mask, True) /home/me/usr/lib/python2.6/site-packages/numpy/ma/tests/test_core.py:1989: SyntaxWarning: assertion is always true, perhaps remove parentheses? assert(test.mask, [0,1,0,0,0,0,0,0,0,0]) ...............................................E................................................................................................................................................................................ ====================================================================== ERROR: Tests the min/max functions with explicit outputs ---------------------------------------------------------------------- Traceback (most recent call last): File "/home/me/usr/lib/python2.6/site-packages/numpy/ma/tests/test_core.py", line 653, in test_minmax_funcs_with_output result = npfunc(xm,axis=0,out=nout) File "/home/me/usr/lib/python2.6/site-packages/numpy/core/fromnumeric.py", line 1525, in amin return amin(axis, out) File "/home/me/usr/lib/python2.6/site-packages/numpy/ma/core.py", line 2978, in min np.putmask(out, newmask, np.nan) ValueError: cannot convert float NaN to integer ====================================================================== FAIL: test_umath.TestComplexFunctions.test_against_cmath ---------------------------------------------------------------------- Traceback (most recent call last): File "/home/me/usr/lib/python2.6/site-packages/nose-0.10.4-py2.6.egg/nose/case.py", line 182, in runTest self.test(*self.arg) File "/home/me/usr/lib/python2.6/site-packages/numpy/core/tests/test_umath.py", line 268, in test_against_cmath assert abs(a - b) < atol, "%s %s: %s; cmath: %s"%(fname,p,a,b) AssertionError: arcsin 2: (1.57079632679-1.31695789692j); cmath: (1.57079632679+1.31695789692j) ---------------------------------------------------------------------- Ran 1726 tests in 8.856s FAILED (KNOWNFAIL=1, errors=1, failures=1) <nose.result.TextTestResult run=1726 errors=1 failures=1>

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Trouble cloning numpy Github repo over HTTP
by Scott Sinclair 09 Nov '10

09 Nov '10

Hi, I'm behind a firewall that doesn't allow me to use the git protocol so I can't use the git:// URL. I see the following problem: $ git clone http://github.com/numpy/numpy.git numpy Initialized empty Git repository in /home/scott/external_repos/numpy/.git/ error: RPC failed; result=22, HTTP code = 417 I never have trouble cloning other repos off of Github over HTTP. See http://support.github.com/discussions/repos/4323-error-rpc-failed-result22-… Does anyone else see this problem? Thanks, Scott

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Error in API docs?
by Henry Gomersall 04 Nov '10

04 Nov '10

There is an inconsistency in the documentation for NPY_INOUT_ARRAY. cf. http://docs.scipy.org/doc/numpy/user/c-info.how-to-extend.html#NPY_INOUT_AR… http://docs.scipy.org/doc/numpy/reference/c-api.array.html#NPY_INOUT_ARRAY The first link includes the flag NPY_UPDATEIFCOPY. Checking the code seems to confirm that the correct version is that in the first link, and also that NPY_OUT_ARRAY is wrong in the API docs. I haven't checked NPY_INOUT_FARRAY or NPY_OUT_FARRAY. Cheers, Henry

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List with numpy semantics
by Nikolaus Rath 03 Nov '10

03 Nov '10

Hello, I have a couple of numpy arrays which belong together. Unfortunately they have different dimensions, so I can't bundle them into a higher dimensional array. My solution was to put them into a Python list instead. But unfortunately this makes it impossible to use any ufuncs. Has someone else encountered a similar problem and found a nice solution? Something like a numpy list maybe? Best, -Nikolaus -- »Time flies like an arrow, fruit flies like a Banana.« PGP fingerprint: 5B93 61F8 4EA2 E279 ABF6 02CF A9AD B7F8 AE4E 425C

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ANN: NumPy 1.5.1 release candidate 1
by Ralf Gommers 02 Nov '10

02 Nov '10

Hi, I am pleased to announce the availability of the first release candidate of NumPy 1.5.1. This is a bug-fix release with no new features compared to 1.5.0. Binaries, sources and release notes can be found at https://sourceforge.net/projects/numpy/files/. A note on the available binaries for OS X: these are known to not work on Intel-based OS X 10.5. We hope to have that problem fixed within a week. On Windows there are still two known test failures: - #1610, in fromfile (under Python 2.x) - #1633, a failing test for ldexp (under Python 2.5 only) Please report any other issues on the Numpy-discussion mailing list. Enjoy, Ralf

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np.ma.masked_invalid and precision
by bevan jenkins 01 Nov '10

01 Nov '10

Hello, I am not sure if the following is a bug or not. I recently tried to set the print precision in numpy but it didn't seem to make a difference. It seems that the use of np.ma.masked_invalid results in arrays printing precision of 12 regardless of the default setting or any subsequent setting. Generating masked arrays does not seem to have this behaviour. Is this a bug or am I doing it wrong? Thanks, Bevan In [1]: eg = np.random.random(1) In [2]: eg_mask = np.ma.masked_array(eg) In [3]: eg_mask_invalid = np.ma.masked_invalid(eg) In [4]: eg Out[4]: array([ 0.78592569]) In [5]: eg_mask Out[5]: masked_array(data = [ 0.78592569], mask = False, fill_value = 1e+20) In [6]: eg_mask_invalid Out[6]: masked_array(data = [0.785925693305], mask = [False], fill_value = 1e+20) In [7]: np.set_printoptions(precision=3) In [8]: eg Out[8]: array([ 0.786]) In [9]: eg_mask Out[9]: masked_array(data = [ 0.786], mask = False, fill_value = 1e+20) In [10]: eg_mask_invalid Out[10]: masked_array(data = [0.785925693305], mask = [False], fill_value = 1e+20)

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Including fix for #1637 in 1.5.1 ?
by David Cournapeau 01 Nov '10

01 Nov '10

Hi, I just committed a quick fix for http://projects.scipy.org/numpy/ticket/1637. I did want to include it for 1.5.x branch as it is already in RC stage, but it may still be useful to do so if the release managers think it is appropriate (there is a test for it): http://github.com/numpy/numpy/commit/cdcbaa4ce4b47a7bfd8905222124fd22460252… cheers, David

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IPython on python3, for the adventurous...
by Fernando Perez 31 Oct '10

31 Oct '10

Hi all, thanks to the great work done by Thomas Kluyver, for those of you starting to use Numpy (or other projects) on Python 3 and who wanted to have IPython as your working environment, things are getting off the ground: (py3k)amirbar[py3k]> python3 ipython.py Python 3.1.2 (release31-maint, Sep 17 2010, 20:34:23) Type "copyright", "credits" or "license" for more information. IPython 0.11.alpha1.git -- An enhanced Interactive Python. ? -> Introduction and overview of IPython's features. %quickref -> Quick reference. help -> Python's own help system. object? -> Details about 'object', use 'object??' for extra details. In [1]: import io In [2]: import sys In [3]: sys.ver sys.version sys.version_info In [3]: sys.version Out[3]: '3.1.2 (release31-maint, Sep 17 2010, 20:34:23) \n[GCC 4.4.5]' etc... This is still very much a work in progress, and we haven't made any official release. But there's a github repo up and running with a proper bug tracker, so by all means let us know what works and what doesnt' (and even better, join in with help!): http://github.com/ipython/ipython-py3k Our hope is to eventually merge this work into ipython proper at some point in the future, but since the history of this branch is likely to be messy (with many merges from trunk, auto-generated code and possible rebases down the road) we're keeping it in a separate repo for now. Cheers, f

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whitespace in git repo
by Darren Dale 30 Oct '10

30 Oct '10

We have been discussing whitespace and line endings at the following pull request: http://github.com/numpy/numpy/pull/4 . Chuck suggested we discuss it here on the list. I have the following set in my ~/.gitconfig file: [apply] whitespace = fix [core] autocrlf = input which is attempting to correct some changes in: branding/icons/numpylogo.svg branding/icons/numpylogoicon.svg tools/win32build/nsis_scripts/numpy-superinstaller.nsi.in David C. suggested that the nsi.in file should not be changed. I suggested adding a .gitattributes file along with the existing .gitignore file in the numpy repo. This would enforce windows line endings for the nsi.in file: tools/win32build/nsis_scripts/numpy-superinstaller.nsi.in eol=crlf alternatively this would disable any attempt to convert line endings: tools/win32build/nsis_scripts/numpy-superinstaller.nsi.in -text I think the former is preferable. But it seems like a good idea to include some git config files in the repo to ensure trailing whitespace is stripped and line endings are appropriate to the numpy project, regardless of what people may have in their ~/.gitconfig file. Comments? Darren

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