I should have added: $ lsb_release -a LSB Version: :core-4.0-amd64:core-4.0-noarch:graphics-4.0-amd64:graphics-4.0-noarch:printing-4.0-amd64:printing-4.0-noarch Distributor ID: RedHatEnterpriseServer Description: Red Hat Enterprise Linux Server release 6.2 (Santiago) Release: 6.2 Codename: Santiago $ python -c "import numpy; numpy.test('full')" Running unit tests for numpy NumPy version 1.6.2 NumPy is installed in /opt/numpy/1.6.2/intel/13.0.1/lib/python2.7/site-packages/numpy Python version 2.7.3 (default, Feb 9 2013, 16:14:16) [GCC 4.7.2] nose version 1.2.1 So nobody knows why the number of tests run are different among different runs of the same binary/library on different nodes? https://github.com/numpy/numpy/blob/master/doc/TESTS.rst.txt implies they shouldn't... Regards, Davide Del Vento, On 02/11/2013 08:54 PM, Davide Del Vento wrote:

I compiled numpy 1.6.2 (right before 1.7 came out) with the intel compiler and MKL library. I'm trying to assess whether or not everything has been build fine. Since my machine is actually a cluster, I'm running the tests in different configurations (login node and batch script). However, I'm confused by the number of tests which ran. On the login nodes (either interactively or without tty) I get:

Ran 3587 tests in 22.211s FAILED (KNOWNFAIL=5, SKIP=11, failures=2)

Whereas in a remote batch node (with a script) I get:

Ran 3229 tests in 15.642s OK (KNOWNFAIL=5, SKIP=19)

Where did the 358 "missing" tests go in the batch run? The handful difference in SKIPped and FAILed (which I am investigating) cannot be the reason.

What is it happening?

PS: a similar thing happened with scipy, which I'm asking on the scipy mailing list.

Thanks and Regards, Davide