On 7/18/06, Alan G Isaac <[EMAIL PROTECTED]> wrote: > it cannot upcast, as the '+=' operation will use only the > memory initially allocated for a.
Not true: >>> x = [2,3] >>> x += array(2) >>> type(x) <type 'numpy.ndarray'> This is just the design choice made by numpy. I don't see the need for an error. Augmented assignment is a sufficiently advanced feature that those who use it can be expected to know what it does. Loosing imaginary part maybe a more compelling reason for an error than loosing precision, but it would be clearly wrong to have different types behave differently. Silent downcasting from float to int is actually a useful feature. ------------------------------------------------------------------------- Take Surveys. Earn Cash. Influence the Future of IT Join SourceForge.net's Techsay panel and you'll get the chance to share your opinions on IT & business topics through brief surveys -- and earn cash http://www.techsay.com/default.php?page=join.php&p=sourceforge&CID=DEVDEV _______________________________________________ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion