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Re: [h5md-user] proposal 100 - update
From: |
Pierre de Buyl |
Subject: |
Re: [h5md-user] proposal 100 - update |
Date: |
Tue, 9 Jun 2015 14:36:18 +0200 |
User-agent: |
Mutt/1.5.23 (2014-03-12) |
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