A Thursday 01 November 2007, Timothy Hochberg escrigué:
On Nov 1, 2007 7:14 AM, David M. Cooke <cookedm@physics.mcmaster.ca> > Another issue is that numexpr is still in the scipy sandbox, so
only those who enable it will use it (or use it through PyTables). One problem with moving it out is that Tim reports the compile times on Windows are ridiculous (20 mins!).
While this is true at the default optimization (O2), it compiles reasonably quickly at O1 and I've never been able to detect a speed difference between versions compiled with O1 versus O2. It would probably be sufficient to crank back the optimization on Windows.
Yes. This has been my experience too on Windows/MSVC boxes.
Maybe numexpr should become a scikit? It certainly doesn't need the rest of scipy.
Call me intrepid, but I've always felt that numexpr belongs more to numpy itself than scipy. However, I agree that perhaps it should be a bit more polished (but not much; perhaps just adding some functions like, exp, log, log10... would be enough) before being integrated. At any rate, Numexpr would be a extremely useful complement to NumPy. My two cents, --
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