For the non-destructive+propagating case, do I understand correctly that this would mean I (as a user) could temporarily decide to IGNORE certain portions of my data, perform a series of computation on that data, and the IGNORED flag (or however it is implemented) would be propagated from computation to computation? If that's the case, I suspect I'd use it all the time ... to effectively perform data subsetting without generating (partial) copies of large datasets. But maybe I misunderstand the intended notion of propagation ...
Gary > Or put another way, do you think that the MISSING and IGNORED concepts > are adequate to cover practical use cases, or do you have an example > where what's really wanted is say non-destructive + propagating? I can > see how it would work, but I don't think I'd ever use it, so I'm > curious... > > -- Nathaniel > _______________________________________________ > NumPy-Discussion mailing list > [email protected] > http://mail.scipy.org/mailman/listinfo/numpy-discussion > > > The information in this e-mail is intended only for the person to whom it is addressed. If you believe this e-mail was sent to you in error and the e-mail contains patient information, please contact the Partners Compliance HelpLine at http://www.partners.org/complianceline . If the e-mail was sent to you in error but does not contain patient information, please contact the sender and properly dispose of the e-mail. _______________________________________________ NumPy-Discussion mailing list [email protected] http://mail.scipy.org/mailman/listinfo/numpy-discussion
