Hi, I'm starting to (slowly) replace numarray by NumPy at the core of PyTables, specially at those places where the speed of NumPy is *much* better, that is, in the creation of arrays (there are places in PyTables where this is critical, most specially in indexation) and in copying arrays. In both cases, NumPy performs between 8x to 40x than numarray and this is, well..., excellent :-)
Also, the big unification between numerical homogeneous arrays, string homogeneous arrays (with unicode support added) and heterogeneous arrays (recarrays, with nested records support there also!) is simplyfying very much the code in PyTables where there are many places where one have to distinguish between those different objects in numarray. Fortunately, this distinction is not necessary anymore in many of this places. Furthermore, I'm seeing that most of the corner cases where numarray do well (this was the main reason I was conservative about migrating anyway), are also very well resolved in NumPy (in some cases better, as for one, NumPy has chosen NULL terminated strings for internal representation, instead of space padding in numarray that gave me lots of headaches). Of course, there are some glitches that I'll report appropriately, but overall, NumPy is behaving better than expected (and I already had *great* expectations). Well, I just wanted to report these experiences just in case other people is pondering about migrating as well to NumPy. But also wanted to thanks (once more), the excellent work of the NumPy crew, and specially Travis for their first-class work. Thanks! -- >0,0< Francesc Altet http://www.carabos.com/ V V Cárabos Coop. V. Enjoy Data "-" ------------------------------------------------------------------------- Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnk&kid=120709&bid=263057&dat=121642 _______________________________________________ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion