Re: [h5md-user] proposal 100 - update

[Pierre de Buyl]

Hi all,

On Mon, Jun 01, 2015 at 10:01:06PM +0200, Pierre de Buyl wrote:
> On Mon, Jun 01, 2015 at 03:54:16PM -0400, Peter Colberg wrote:
> > On Fri, May 29, 2015 at 08:46:56AM +0200, Pierre de Buyl wrote:
> > > But, in another likely usage, imagine that step is not linear and that
> > > time[i]=step[i]*DT for all values of i.
> > > 
> > > My "new" extension is that if you have a non-scalar dataset for "step" 
> > > and a
> > > scalar dataset for "time", you can compute the value in time as
> > > time[i]=step[i]*time
> > 
> > If time depends on step, I would suggest this scheme:
> > 
> >   \-- step[Inf]
> >   |    +-- timestep: Float[]
> >   \-- value[Inf, …]
> > 
> > However, to keep things simple, I would not favour this extension. If
> > one already goes through the trouble of writing the variable-length
> > step dataset, it is not much more work to write the time dataset using
> > the same datatype and dataspace.
> 
> It is more about writing less data than convenience per se. I don't see this 
> as
> a "must have" though.

Any other opinion on this?

As a reminder, I propose that step[Inf] and time[] (that is, a scalar dataset)
allows one to evaluate the time at index i as (step[i]+step.offset*time[]).

P