Pierre GM wrote: > but you can use integers/dates/strings as indices and get your > result.
cool! I like that. >>>> print example > [Jul-2008 Aug-2008 Sep-2008 Oct-2008 Nov-2008 Dec-2008] I like this -- seeing the integers for the times makes me wonder what that point is -- we've all been using numbers for time for years already -- what would a datetime array give us other than auto-conversion from datetime objects, if it doesn't include nicer display, timedelta, etc. >>>> print example.tovalue() > [24091 24092 24093 24094 24095 24096] And is that a regular array of integers? >>>> print example.tolist() > [datetime.datetime(2008, 7, 31, 0, 0), datetime.datetime(2008, 8, 31, 0, 0), nice, too. > Now that I think about this, wouldn't be better if, after the eventual > introduction of the new datetime types in NumPy, the matplotlib would > use any of these three and throw away their current datetime class? yes, that would be better, but what to do during the transition? > [Unless they have good reasons for keeping their epoch and/or scale] If they do, they those should be taken into account when designing numpy's datetime types. > That's nice! But it would be even nicer if that could be integrated in > general NumPy arrays after the introduction of the datetime types (just > thinking aloud ;-) what would using dates/strings as indices mean for general numpy arrays? > That's ok. But my point is that this forces you to represent absolute > dates, and that's what I was trying to avoid. The proposed date/time > types could work either as absolute or relative, depending on the needs > of the user. Only when converting them to the Python > ``datetime.datetime`` containers a time origin will be set, and hence, > they represents an absolute date then. However, if you convert the > NumPy datetimes into a ``datetime.timedelta``, your times will continue > to be relative. That would be utterly important so as not to clutter > NumPy too much with another set of 'timedelta' types, IMO. hmm -- I see the tradeoff, but I like the timedelta concept too. I'm ambivalent now... I'm also imaging some extra utility functions/method that would be nice: aDateTimeArray.hours(dtype=float) to convert to hours (and days, and seconds, etc). And maybe some that would create a DateTimeArray from various time units. I often have to read/write data files that have time in various units like that -- it would be nice to use array operations to work with them. -Chris -- Christopher Barker, Ph.D. Oceanographer Emergency Response Division NOAA/NOS/OR&R (206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception [EMAIL PROTECTED] _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion