Mailman 3 December 2009 - NumPy-Discussion

Py3 merge
by Pauli Virtanen 08 Dec '09

08 Dec '09

Hi, I'd like to commit my Py3 Numpy branch to SVN trunk soon: http://github.com/pv/numpy-work/commits/py3k For an overview, check the notes: http://github.com/pv/numpy-work/blob/py3k/doc/Py3K.txt None of the changes should affect behavior on Py2. The test status currently is: Python 3.1: Ran 1964 tests in 10.294s FAILED (KNOWNFAIL=5, errors=435, failures=74) Python 2.4: Ran 2480 tests in 18.209s OK (KNOWNFAIL=4, SKIP=2) Python 2.5: Ran 2483 tests in 18.552s OK (KNOWNFAIL=4) Python 2.6: Ran 2484 tests in 20.359s OK (KNOWNFAIL=5) The next TODOs are: - Map 'S' scalartype to 'U' on Py3, and add a new scalartype for bytes - Finish the rest of the PyString transition - Fix I/O - Hammer out causes for test failures More TODOs are listed in Py3K.txt. Pauli

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Zero Division not handled correctly?
by Skipper Seabold 08 Dec '09

08 Dec '09

I believe this is known, but I am surprised that division by "integer" zero results in the following. In [1]: import numpy as np In [2]: np.__version__ Out[2]: '1.4.0.dev7539' In [3]: 0**-1 # or 0**-1/-1 --------------------------------------------------------------------------- ZeroDivisionError Traceback (most recent call last) /home/skipper/school/Data/ascii/numpy/<ipython console> in <module>() ZeroDivisionError: 0.0 cannot be raised to a negative power In [4]: np.array([0.])**-1 Out[4]: array([ Inf]) In [5]: np.array([0.])**-1/-1 Out[5]: array([-Inf]) In [6]: np.array([0])**-1. Out[6]: array([ Inf]) In [7]: np.array([0])**-1./-1 Out[7]: array([-Inf]) In [8]: np.array([0])**-1 Out[8]: array([-9223372036854775808]) In [9]: np.array([0])**-1/-1 Floating point exception This last command crashes the interpreter. There have been some threads about similar issues over the years, but I'm wondering if this is still intended/known or if this should raise an exception or return inf or -inf. I expected a -inf, though maybe this is incorrect on my part. Skipper

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Build error
by Gael Varoquaux 08 Dec '09

08 Dec '09

I just did an SVN up, and I am getting a build error: $ python setup.py build_ext --inplace ... building extension "numpy.linalg.lapack_lite" sources adding 'numpy/linalg/lapack_litemodule.c' to sources. adding 'numpy/linalg/python_xerbla.c' to sources. building extension "numpy.random.mtrand" sources error: _numpyconfig.h not found in numpy include dirs ['numpy/core/include', 'numpy/core/include/numpy'] It's probably something minor, and I will figure it out, but I wanted to make sure the devs were aware of the potential hitch. Gaël

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Py3k: including npy_config.h outside numpy.core
by David Cournapeau 08 Dec '09

08 Dec '09

Hi, I have noticed that now some code outside numpy/core uses npy_config.h. As suggested by its location (numpy/core/src/private), it is specific to numpy/core, and should not be used outside. What's the rationale to use npy_config.h in numpy/core ? cheers, David

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re cfunctions help with concatenating (vstack, hstack, etc.)
by John [H2O] 08 Dec '09

08 Dec '09

Hello (Pierre?), I'm trying to work more with structured arrays, which at times seems great, and at others (due to my lack of familiarity) very frustrating. Anyway, right now I'm writing a bit of code to read a series of files with x,y,z data. I'm creating record arrays for each file a read. Once I have them all read, I just want to load them into one big array. But it doesn't seem as straight forward as concatenation: In [102]: type(D); D.shape; D.dtype.names Out[102]: <class 'numpy.core.records.recarray'> Out[102]: (3025,) Out[102]: ('datetime', 'lon', 'lat', 'elv', 'co') In [103]: type(D2); D2.shape; D2.dtype.names Out[103]: <class 'numpy.core.records.recarray'> Out[103]: (3445,) Out[103]: ('datetime', 'lon', 'lat', 'elv', 'co') In [104]: C = rf.stack_arrays((D,D2)) In [105]: type(C); C.shape; C.dtype.names Out[105]: <class 'numpy.ma.core.MaskedArray'> Out[105]: (6470,) Out[105]: ('datetime', 'lon', 'lat', 'elv', 'co') In [106]: C.datetime --------------------------------------------------------------------------- AttributeError Traceback (most recent call last) /xnilu_wrk/flex_wrk/jfb/RESEARCH_ARCTIC/Arctic_CO/<ipython console> in <module>() AttributeError: 'MaskedArray' object has no attribute 'datetime' In [107]: C[0] Out[107]: (datetime.datetime(2008, 6, 29, 14, 50, tzinfo=<UTC>), 248.83900164808117, 53.949661856137709, -0.31834712473582627, 112.91218844292422) In [108]: So it seems I end up with a masked array of the correct length, but it is an array of tuples and no longer a record array. Am I missing a step? Thanks, john -- View this message in context: http://old.nabble.com/recfunctions-help-with-concatenating-%28vstack%2C-hst… Sent from the Numpy-discussion mailing list archive at Nabble.com.

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numpy.test() failures
by Nils Wagner 08 Dec '09

08 Dec '09

>>> numpy.__version__ '1.5.0.dev7980' FAIL: test_buffer_hashlib (test_regression.TestRegression) ---------------------------------------------------------------------- Traceback (most recent call last): File "/home/nwagner/local/lib64/python2.6/site-packages/numpy/core/tests/test_regression.py", line 1246, in test_buffer_hashlib assert_equal(md5(x).hexdigest(), '2a1dd1e1e59d0a384c26951e316cd7e6') File "/home/nwagner/local/lib64/python2.6/site-packages/numpy/testing/utils.py", line 307, in assert_equal raise AssertionError(msg) AssertionError: Items are not equal: ACTUAL: 'aa341a15f5ade44faafbe190f98c2587' DESIRED: '2a1dd1e1e59d0a384c26951e316cd7e6' ---------------------------------------------------------------------- Ran 2485 tests in 14.328s FAILED (KNOWNFAIL=5, failures=1) <nose.result.TextTestResult run=2485 errors=0 failures=1>

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1.4.0rc: Failing regression test on Solaris/SPARC
by Michael Droettboom 08 Dec '09

08 Dec '09

We've got 2 failing regression tests left on Solaris/SPARC, with the same apparent root cause (a difference in out-of-domain handling in asin and friends). Would anyone (particularly someone familiar with masked arrays) be able to look at #1173 to confirm that my suggested fix is correct? http://projects.scipy.org/numpy/ticket/1173 http://projects.scipy.org/numpy/ticket/1174 Mike -- Michael Droettboom Science Software Branch Operations and Engineering Division Space Telescope Science Institute Operated by AURA for NASA

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np.equal
by josef.pktd＠gmail.com 07 Dec '09

07 Dec '09

what's the difference in the implementation between np.equal and == ? np.equal raises NotImplemented for strings, while == works. >>> aa array(['a', 'b', 'a', 'aa', 'a'], dtype='|S2') >>> aa == 'a' array([ True, False, True, False, True], dtype=bool) >>> np.equal(aa,'a') NotImplemented >>> np.equal(np.arange(5),1) array([False, True, False, False, False], dtype=bool) >>> np.equal(np.arange(5),'a') NotImplemented >>> np.arange(5) == 'a' False Josef

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Test of numpy/py3k
by Nadav Horesh 07 Dec '09

07 Dec '09

I would like to test and prepare for migration of numpy/python3.1 on a linux box. Can anyone provide an installation recipe (and maybe some more tips)? Nadav.

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Chararray depreciated?
by Gael Varoquaux 07 Dec '09

07 Dec '09

http://docs.scipy.org/doc/numpy/reference/generated/numpy.chararray.html says that chararray are depreciated. I think I saw a discussion on the mailing list that hinted otherwise. Which one is true? Should I correct the docs? Cheers, Gaël

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