Re: [AMBER] cpptraj error

From: Daniel Roe <>
Date: Mon, 19 Nov 2018 13:04:59 -0500


1) In general it is considered bad etiquette to use an existing email
thread for an unrelated problem, not to mention confusing and
unhelpful for other users who may encounter your issues in the future.

2) While posting screenshots can sometimes help in diagnosing your
problem, there is no substitute for listing the exact commands you
used, your exact input file, the actual output/error messages you
received, etc. In your case I can't even see the complete 'ambpdb'
command you used that generated the error message you see, so I can't
really help. And I guess the second picture is supposed to show that
the restart file was never generated?

3) Be patient. Most of the people on this list who answer Amber mail
are volunteers, meaning they often have other pressing obligations.

On Mon, Nov 19, 2018 at 12:22 PM Charu Sharma (JRF)
<> wrote:
> On Mon, Nov 19, 2018 at 7:32 PM Daniel Roe <> wrote:
>> Hi,
>> Your issue is here:
>> On Mon, Nov 19, 2018 at 7:59 AM Rajbinder Kaur Virk
>> <> 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.:
>> 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:
>> Hope this helps,
>> -Dan
>> _______________________________________________
>> AMBER mailing list

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Received on Mon Nov 19 2018 - 10:30:03 PST
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