have you looked at the sander output file to see if it completed without
errors?
On Mon, Nov 19, 2018 at 12:23 PM Charu Sharma (JRF) <
charu.sharma.lnmiit.ac.in> wrote:
> SIR WHY MY AMBPDB FILE NOT CREATING ? WHY ONLY MY polyAT_vac_init_min.rst
> <
> http://ambermd.org/tutorials/basic/tutorial1/files/output_files/polyAT_vac_init_min.rst
> >.
> SHOWING ERROR ?
>
> On Mon, Nov 19, 2018 at 7:32 PM Daniel Roe <daniel.r.roe.gmail.com> wrote:
>
> > Hi,
> >
> > Your issue is here:
> >
> > On Mon, Nov 19, 2018 at 7:59 AM Rajbinder Kaur Virk
> > <rajbinderkaurvirk.gmail.com> wrote:
> > > No clusters found.
> >
> > This isn't a cpptraj error per se. Based on the parameters you gave
> > the 'cluster' command, no clusters were found. You'll need to try to
> > adjust the parameters you're giving the DBSCAN algorithm, or try
> > another algorithm. Clustering is much more of an art form than a
> > science, so plan on a fair amount of trial and error here. It's good
> > that you're starting off with a relatively small trajectory; this will
> > allow you to become familiar with the results without waiting around
> > too much. I highly recommend reading the entire 'cluster' command
> > entry in the Amber 18 manual if you haven't already (section 29.11.4,
> > starting on page 694), and in particular the 'Hints for setting DBSCAN
> > parameters' subsection if you want to continue using DBSCAN. I also
> > recommend reading this excellent paper on clustering MD trajectories
> > from Shao, Cheatham et al.:
> > https://pubs.acs.org/doi/abs/10.1021/ct700119m
> >
> > Some general clustering tips:
> >
> > 1) In my experience I've obtained better results with 'sieve <#>
> > random' as opposed to plain 'sieve <#>'.
> > 2) If you're not going to change your distance metric (including
> > sieve) you way want to use 'savepairdist'/'loadpairdist' to avoid
> > recalculating the pairwise distances every time. This is useful e.g.
> > when doing hierarchical aggolmerative with varying epsilon, etc.
> > 3) The OpenMP version of cpptraj (cpptraj.OMP) can accelerate the
> > pairwise distance calculation, but don't use more threads than you
> > have physical cores.
> >
> > Also, there is a very basic clustering tutorial you may find useful
> > here: http://www.amber.utah.edu/AMBER-workshop/London-2015/Cluster/
> >
> > Hope this helps,
> >
> > -Dan
> >
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Received on Mon Nov 19 2018 - 09:30:04 PST
