Jonathan,
>> Typical producers of this kind of data are numerical particle tracking
>> models. ?These codes step through time, following the (x,y,t) or
>> (x,y,z,t) trajectories of individual particles. ?At each time step,
>> more particles may be introduced to be tracked, while other particles
>> stop being tracked because they leave the domain, hit the boundary, or
>> whatever.
>
> This kind of data could be described by the trajectory feature type, but each
> trajectory would be entirely independent, so they'd all have separate times,
> whereas as you describe it the time coord is common to all trajectories (that
> exist at a particular time). To arrange this, an indirection could be used on
> the time dimension:
> ?data(i,o) ? ? x(i,o) y(i,o) z(i,o) t(tindex(i,o))
> where i is the instance (which of the trajectories), o is the point along that
> trajectory, t is the coordinate vector of common times, and tindex is an index
> to t. For example, we might have these two trajectories (x,t) (omitting y and
> z for simplicity)
> ?(0,10) (1,11) (2,12)
> ? ? ? ? (3,11) (2,12) (1,13) (0,14)
> Then t would be [10,11,12,13,14] (all the times). For the first trajectory
> ?x=[0,1,2] tindex=[0,1,2]
> and for the second
> ?x=[3,2,1,0] tindex=[1,2,3,4]
> Is that right? Perhaps/probably there's a neater or more natural way to do it.
Yes, that's exactly right.
With the approach you suggest, if you wanted to obtain all the
particle positions at a particular time step, would you need to read
all tindex for all particles? (I'm a little fuzzy on what the CDL
would look like...)
Thanks,
Rich
--
Dr. Richard P. Signell?? (508) 457-2229
USGS, 384 Woods Hole Rd.
Woods Hole, MA 02543-1598
Received on Wed Oct 13 2010 - 06:13:28 BST
