On Thu, Sep 26, 2013 at 10:27 PM, John Chilton <chil...@msi.umn.edu> wrote: > My recommendation would be make the tool dependency install work on as > many platforms as you can and not try to optimize in such a way that > it is not going to work - i.e. favor reproduciblity over performance.
Reproducibility versus speed is a particular issue with floating point libraries - NumPy using ATLAS vs OpenBLAST vs Intel MKL vs just plain NumPy will probably all give slightly different answers (on some tasks), and at different speed. In this case, for simplicity I would advocate plain NumPy, without worrying about needing ATLAS. For packages needing NumPy with ALTAS, perhaps a new Tool Shed entry could be created, package_numpy_1_7_with_atlas or similar (based on the current configuration)? Peter ___________________________________________________________ Please keep all replies on the list by using "reply all" in your mail client. To manage your subscriptions to this and other Galaxy lists, please use the interface at: http://lists.bx.psu.edu/ To search Galaxy mailing lists use the unified search at: http://galaxyproject.org/search/mailinglists/
