Sebastian Haase wrote: > On Wednesday 23 August 2006 18:37, Travis Oliphant wrote: > >> David M. Cooke wrote: >> >>> On Wed, 23 Aug 2006 16:22:52 -0700 >>> >>> Sebastian Haase <[EMAIL PROTECTED]> wrote: >>> >>>> On Wednesday 23 August 2006 16:12, Bill Baxter wrote: >>>> >>>>> The thing that I find I keep forgetting is that abs() is a built-in, >>>>> but other simple functions are not. So it's abs(foo), but >>>>> numpy.floor(foo) and numpy.ceil(foo). And then there's round() which >>>>> is a built-in but can't be used with arrays, so numpy.round_(foo). >>>>> Seems like it would be more consistent to just add a numpy.abs() and >>>>> numpy.round(). >>>>> >>>> Regarding the original subject: >>>> a) "absolute" is impractically too much typing and >>>> b) I just thought some (module-) functions might be "forgotten" to be >>>> put in as (object-) methods ... !? >>>> >>> Four-line change, so I added a.abs() (three lines for array, one >>> for MaskedArray). >>> >> While I appreciate it's proactive nature, I don't like this change >> because it adds another "ufunc" as a method. Right now, I think conj is >> the only other method like that. >> >> Instead, I like better the idea of adding abs, round, max, and min to >> the "non-import-*" namespace of numpy. >> >> > How does this compare with > mean, min, max, average > ? >
I'm not sure what this question is asking, so I'll answer what I think it is asking. The mean, min, max, and average functions are *not* ufuncs. They are methods of particular ufuncs. The abs() should not be slow (because it calls the __abs__ method which for arrays is mapped to the ufunc absolute). Thus, there is one more layer of indirection which will only matter for small arrays. -Travis ------------------------------------------------------------------------- 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
