Dear Terri, I have slides available [1], which may give a useful introduction (see slides 16 to 58 approximately) - it’s mostly generic and then very specific for Python and py.test. It was used as teaching material for Masters and PhD students without a computer science background.
Best wishes, Hans http://www.southampton.ac.uk/~fangohr/training/Software-Engineering-for-Computational-Science-and-Engineering-Hans-Fangohr.pdf Prof Hans Fangohr Senior Data Analysis Scientist European XFEL GmbH Germany [email protected]<mailto:[email protected]> http://www.xfel.eu/organization/staff/fangohr_hans/ Professor of Computational Modelling University of Southampton United Kingdom [email protected] http://www.soton.ac.uk/~fangohr @ProfCompMod On 14 Jul 2017, at 22:21, Olav Vahtras <[email protected]<mailto:[email protected]>> wrote: Dear Terri In addition I can recommend the following resource: pythontesting.net<http://pythontesting.net> has a podcast series on testing and more, check out the new book on pytest by the site maintainer Brian Okken Regards Olav Olav 14 juli 2017 kl. 21:36 skrev Ashwin Srinath <[email protected]<mailto:[email protected]>>: If you're using Python, numpy.testing has the tools you'll need: https://docs.scipy.org/doc/numpy/reference/routines.testing.html There's also pandas.testing for testing code that uses Pandas. Thanks, Ashwin On Fri, Jul 14, 2017 at 3:27 PM, Terri Yu <[email protected]> wrote: Hi everyone, Are there any resources that explain how to write unit tests for scientific software? I'm writing some software that processes audio signals and there are many parameters. I'm wondering what's the best way to test floating point numeric results. Do I need to test every single parameter? How can I verify accuracy of numeric results... use a different language / library? I would like to do a good job of testing, but I also don't want to write a bunch of semi-useless tests that take a long time to run. I would appreciate any thoughts you have. Thank you, Terri _______________________________________________ Discuss mailing list [email protected] http://lists.software-carpentry.org/listinfo/discuss _______________________________________________ Discuss mailing list [email protected] http://lists.software-carpentry.org/listinfo/discuss _______________________________________________ Discuss mailing list [email protected]<mailto:[email protected]> http://lists.software-carpentry.org/listinfo/discuss _______________________________________________ Discuss mailing list [email protected] http://lists.software-carpentry.org/listinfo/discuss
