Christopher Barker wrote: > I'm a bit confused, because I thought that when you extracted a scalar > from an array, you got regular python scalar for the datatypes that are > supported. This made it clear that you always get a numpy Scalar, which, > in a few situations, behaves differently than a seemingly equivalent > Python scalar.
Part of the point of adding scalar types was to ensure that a[0], for example, always exposes the array interface (.shape, .dtype, etc.) whether a.shape is (10,) or (10, 10). This uniformity aids generic programming. -- Robert Kern "I have come to believe that the whole world is an enigma, a harmless enigma that is made terrible by our own mad attempt to interpret it as though it had an underlying truth." -- Umberto Eco ------------------------------------------------------------------------- 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
