I am doing it slightly differently. My data structure is a similar compound 
type depending upon the instrument data being saved. I however chose to put the 
time data into a second time axis (dimension scale) which is also a Packet 
Table. I chose this because having a smaller dataset should speed the effort to 
find the appropriate data index.

Initially that axis was just a timestamp, but this got pushback, and I am now 
also storing a date time string in the scale.


Scott

> -----Original Message-----
> From: [email protected] [mailto:[email protected]]
> On Behalf Of Steve Bissell
> Sent: Friday, December 17, 2010 6:43 AM
> To: [email protected]
> Subject: Re: [Hdf-forum] Best practice for timeseries and storing timestamps
> in Packet Table API
>
>
> Hey karl - not sure about "best practices" but what I've done, which seems to
> work pretty well so far, is indeed to use compound types, with the first
> element of the struct being time. This works well for our application, where
> we may be recording several thousand distinct channels that can be regarded
> as asynchronous, and hence each of the packet tables storing the channel
> data carries its own timestamp in the table entries.
> Only thing to watch out for is that you cannot store bit-sized parameters
> inside a compound type, see my post
> http://hdf-forum.184993.n3.nabble.com/Possible-to-pack-bit-types-into-
> compound-data-types-td1131024.html#a1168717
> for an example of the problem (and a very basic example of a compound type).
> For our application, it's hard to see how we'd store time any other way,
> since each record in the packet table arrives unpredictably, so referencing
> some "other table" would just add complication storage - arrival time is an
> essential property of the data itself.
> Cheers
> Steve
> --
> View this message in context: http://hdf-forum.184993.n3.nabble.com/Best-
> practice-for-timeseries-and-storing-timestamps-in-Packet-Table-API-
> tp2104069p2104301.html
> Sent from the hdf-forum mailing list archive at Nabble.com.
>
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