[Numpy-discussion] fixing up datetime

Pierre GM pgmdevlist at gmail.com
Tue Jun 7 16:56:13 EDT 2011


On Jun 7, 2011, at 5:54 PM, Robert Kern wrote:

> On Tue, Jun 7, 2011 at 07:34, Dave Hirschfeld <dave.hirschfeld at gmail.com> wrote:
> 
>> I'm not convinced about the events concept - it seems to add complexity
>> for something which could be accomplished better in other ways. A [Y]//4
>> dtype is better specified as [3M] dtype, a [D]//100 is an [864S]. There
>> may well be a good reason for it however I can't see the need for it in my
>> own applications.
> 
> Well, [D/100] doesn't represent [864s]. It represents something that
> happens 100 times a day, but not necessarily at precise regular
> intervals. For example, suppose that I am representing payments that
> happen twice a month, say on the 1st and 15th of every month, or the
> 5th and 20th. I would use [M/2] to represent that. It's not [2W], and
> it's not [15D]. It's twice a month.

I understand that, that was how the concept was developed in the first place. I still wonder it's that necessary. I would imagine that a structured type could do the same job, without to much hassle (I'm thinking of a ('D',100), like you can have a (np.float,100), for example...)

> The default conversions may seem to imply that [D/100] is equivalent
> to [864s], but they are not intended to.

Well, like Chris suggested (I think), we could prevent type conversion when the denominator is not 1...


> They are just a starting
> point for one to write one's own, more specific conversions.
> Similarly, we have default conversions from low frequencies to high
> frequencies defaulting to representing the higher precision event at
> the beginning of the low frequency interval. E.g. for days->seconds,
> we assume that the day is representing the initial second at midnight
> of that day. We then use offsets to allow the user to add more
> information to specify it more precisely.

As Dave H. summarized, we used a basic keyword to do the same thing in scikits.timeseries, with the addition of some subfrequencies like A-SEP to represent a year starting in September, for example. It works, but it's really not elegant a solution.



On Jun 7, 2011, at 6:53 PM, Christopher Barker wrote:

> Pierre GM wrote:
>> Using the ISO as reference, you have a good definition of months.
> 
> Yes, but only one. there are others. For instance, the climate modelers 
> like to use a calendar that has 360 days a year: 12 30 day months. That 
> way they get something with the same timescale as months and years, but 
> have nice, linear, easy to use units (differentiable, and all that).


Ah Chris... That's easy for climate models, but when you have to deal with actual station data ;) More seriously, that's the kind of specific case that could be achieved by subclassing an array with a standard unit (like, days). I do understand your arguments for not recognizing a standard Gregorian calendar month as a universal unit. Nevertheless, it can be converted to days without ambiguity in the ISO8601 system.




More information about the NumPy-Discussion mailing list