> > 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
ok -- that one reliably replicates on current master
0.11-branching-379-g898d953 with
SKLEARN_SEED=113 PYTHONPATH=$PWD nosetests -s -v
sklearn/covariance/tests/test_robust_covariance.py
if you could seed it with this seed prior the tests
> actually this one can fail on my laptop ... since no seeding facility is
> available ( ;-) ), here is the line I ran
> ( set -e; for s in {1..1000}; do echo seed=$s; SKLEARN_SEED=$s
> PYTHONPATH=$PWD nosetests -s -v
> sklearn/covariance/tests/test_robust_covariance.py; done; )
> and here is the cut out of the failing output:
> ======================================================================
> FAIL: Tests the FastMCD algorithm implementation
> ----------------------------------------------------------------------
> Traceback (most recent call last):
> File "/usr/lib/python2.7/dist-packages/nose/case.py", line 197, in runTest
> self.test(*self.arg)
> File
> "/home/yoh/deb/gits/scikit-learn/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
> "/home/yoh/deb/gits/scikit-learn/sklearn/covariance/tests/test_robust_covariance.py",
> line 67, in launch_mcd_on_dataset
> assert(error_cov < tol_cov)
> AssertionError:
> 0.0049211381236789111 = <module 'numpy' from
> '/usr/lib/pymodules/python2.7/numpy/__init__.pyc'>.mean((array([[ 1.76405235,
> 0.40015721, 0.97873798, 2.2408932 , 1.86755799],
> [-0.97727788, 0.95008842, -0.15135721, -0.10321885, 0.4105985 ],
> ...
> [ 0.16505432, 0.11554982, -0.01784241, 0.14433467,
> 0.61933516]])) ** 2)
> assert(0.010874013902418312 < 0.01)
> assert(<module 'numpy' from
> '/usr/lib/pymodules/python2.7/numpy/__init__.pyc'>.sum(array([ True, True,
> True, True, False, True, True, True, True,
> ....
> True, True, False, True, False, True, False, False, False,
> True], dtype=bool)) >= 70)
> I will try now on master
--
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
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