On Tue, 03 Jul 2012, Olivier Grisel wrote: > 2012/7/2 Yaroslav Halchenko <[email protected]>: > > Just now spotted that sklearn hasn't migrated to wheezy yet because of
> > Tail of log for scikit-learn on armel: > > Traceback (most recent call last): > > File "/usr/lib/python2.7/dist-packages/nose/case.py", line 197, in runTest > > self.test(*self.arg) > > File > > "/build/buildd-scikit-learn_0.11.0-1-armel-QM4IQa/scikit-learn-0.11.0/debian/python-sklearn/usr/lib/python2.7/dist-packages/sklearn/feature_extraction/tests/test_text.py", > > line 265, in test_tfidf_no_smoothing > > assert_equal(len(w), 1) > > AssertionError: 0 != 1 > No idea for that one. this one is funny -- apparently on armel it (numpy) doesn't care to spit out warning about division by 0: (Pdb) print df [ 3. 2. 0.] (Pdb) n > /home/yoh/sklearn/scikit-learn-0.11.0/sklearn/feature_extraction/text.py(581)fit() -> self.idf_ = np.log(float(n_samples) / df) + 1.0 (Pdb) n > /home/yoh/sklearn/scikit-learn-0.11.0/sklearn/feature_extraction/text.py(583)fit() -> return self apparently warnings are not that reliable altogether across numpy versions / architectures: $> python -c 'import numpy as np; from platform import platform; print np.__version__, platform(); 1.0 / np.array([0.])' 1.6.2 Linux-3.1.0-1-amd64-x86_64-with-debian-wheezy-sid -c:1: RuntimeWarning: divide by zero encountered in divide $> python -c 'import numpy as np; from platform import platform; print np.__version__, platform(); 1.0 / np.array([0.])' 1.4.1 Linux-2.6.32-5-amd64-x86_64-with-debian-6.0.4 (sid)yoh@abel:~$ python -c 'import numpy as np; from platform import platform; print np.__version__, platform(); 1.0 / np.array([0.])' 1.6.2 Linux-2.6.32-armv5tel-with-debian-wheezy-sid So IMHO it would be the best to condition that test on numpy reporting the warnings. Please review/accept/adopt https://github.com/scikit-learn/scikit-learn/pull/928 > > Tail of log for scikit-learn on mipsel: > > self.test(*self.arg) > > File > > "/build/buildd-scikit-learn_0.11.0-1-mipsel-ZOiuQA/scikit-learn-0.11.0/debian/python-sklearn/usr/lib/python2.6/dist-packages/sklearn/covariance/tests/test_robust_covariance.py", > > line 28, in test_mcd > > launch_mcd_on_dataset(100, 5, 20, 0.01, 0.01, 70) > > File > > "/build/buildd-scikit-learn_0.11.0-1-mipsel-ZOiuQA/scikit-learn-0.11.0/debian/python-sklearn/usr/lib/python2.6/dist-packages/sklearn/covariance/tests/test_robust_covariance.py", > > line 67, in launch_mcd_on_dataset > > assert(error_cov < tol_cov) > > AssertionError > Fixed in: > https://github.com/scikit-learn/scikit-learn/commit/071cdb0982e1356552fc07b9cdd5d2ec2625add5 Thanks -- I will pick up this "lucky to succeed once" fix ;) -- Yaroslav O. Halchenko Postdoctoral Fellow, Department of Psychological and Brain Sciences Dartmouth College, 419 Moore Hall, Hinman Box 6207, Hanover, NH 03755 Phone: +1 (603) 646-9834 Fax: +1 (603) 646-1419 WWW: http://www.linkedin.com/in/yarik ------------------------------------------------------------------------------ Live Security Virtual Conference Exclusive live event will cover all the ways today's security and threat landscape has changed and how IT managers can respond. Discussions will include endpoint security, mobile security and the latest in malware threats. http://www.accelacomm.com/jaw/sfrnl04242012/114/50122263/ _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
