On Tue, Mar 10, 2015 at 1:20 PM, Charles R Harris

wrote:

On Tue, Mar 10, 2015 at 10:33 AM, wrote:

...

I got a illegal value message using MKL on Windows 64 while running the statsmodels test suite.

Kevin is getting the same with more information, which indicates that it might be numpy.linalg.svd

https://github.com/statsmodels/statsmodels/issues/2308#issuecomment-78086656

Is this serious?

I'm just setting up a new computer and haven't investigated yet. Given the name of the test class, this might be a warning for an inf or nan, then it would be our problem in statsmodels

What version of Numpy? Does this also happen if you aren't using MKL? The dlascl reference http://www.netlib.org/lapack/explore-html/de/d3c/dlascl_8f.html is here. It is possible that the problem being solved is numerically sensitive and that the treatment of underflow/overflow due to compiler flags might be producing zeros or infs.

nosetests says NumPy version 1.9.2rc1 Version is from winpython which I guess uses Gohlke binaries. It didn't show up with official numpy in 32bit python, and it doesn't show up on TravisCI. In contrast to Kevin, I don't get any info or test failure M:\Notes>nosetests --pdb --pdb-failures -v statsmodels.base.tests.test_data.Test MissingArray statsmodels.base.tests.test_data.TestMissingArray.test_raise_no_missing ... ok statsmodels.base.tests.test_data.TestMissingArray.test_raise ... ok statsmodels.base.tests.test_data.TestMissingArray.test_drop ... ok statsmodels.base.tests.test_data.TestMissingArray.test_none ... Intel MKL ERROR: Parameter 4 was incorrect on entry to DLASCL. Intel MKL ERROR: Parameter 5 was incorrect on entry to DLASCL. Intel MKL ERROR: Parameter 4 was incorrect on entry to DLASCL. Intel MKL ERROR: Parameter 5 was incorrect on entry to DLASCL. ok statsmodels.base.tests.test_data.TestMissingArray.test_endog_only_raise ... ok statsmodels.base.tests.test_data.TestMissingArray.test_endog_only_drop ... ok statsmodels.base.tests.test_data.TestMissingArray.test_mv_endog ... ok statsmodels.base.tests.test_data.TestMissingArray.test_extra_kwargs_2d ... ok statsmodels.base.tests.test_data.TestMissingArray.test_extra_kwargs_1d ... ok ---------------------------------------------------------------------- Ran 9 tests in 0.049s OK However based on the testcase, it looks like we call np.linalg.svd with an array that contains nans, DLASCL might then be used internally in the svd calculations Josef

Chuck

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