From: Jérôme Hénin (jhenin_at_ifr88.cnrs-mrs.fr)
Date: Thu Sep 29 2011 - 05:04:42 CDT
Yes: a bug was introduced, that's what happened. Then it was fixed in
the next version.
On 29 September 2011 08:05, JC Gumbart <gumbart_at_ks.uiuc.edu> wrote:
> Something changed between NAMD versions 2.8b2 and 2.8b3 that causes this error, although I can't figure out what it is. Hopefully Jerome can enlighten us?
>
>
> On Sep 28, 2011, at 3:38 PM, Yun Luo wrote:
>
>>
>> Dear NAMD developers,
>>
>> I want to use ABF with colvar "alpha" for a ten-alanine peptide. It seems work when I tested my script on linux cluster. But when I use NAMD2.8 on Blue Gene/P supercomputer, the output gives error message as below:
>> colvars: ----------------------------------------------------------------------
>> colvars: Initializing a new collective variable.
>> colvars: # name = alpha
>> colvars: Initializing a new "alpha" component.
>> colvars: # componentCoeff = 1 [default]
>> colvars: # componentExp = 1 [default]
>> colvars: # period = 0 [default]
>> colvars: # wrapAround = 0 [default]
>> colvars: # psfSegID = HLX
>> colvars: # hBondCoeff = 0.5
>> colvars: # hBondCutoff = 3.3
>> colvars: # hBondExpNumer = 6
>> colvars: # hBondExpDenom = 8
>> colvars: Error: cannot add atoms to a dummy group.
>> colvars: If this error message is unclear, try recompiling with -DCOLVARS_DEBUG.
>> FATAL ERROR: Error in the collective variables module: exiting.
>> -----------------------------------------------------------------------------------------
>>
>> Is this a bug related to supercomputer version?
>> My colvar and abf input file is shown as below:
>> colvarsTrajFrequency 100
>> colvarsRestartFrequency 100
>>
>> colvar {
>> name alpha
>> width 0.1
>> lowerboundary 0.0
>> upperboundary 1.0
>> lowerwallconstant 10.0
>> upperwallconstant 10.0
>> extendedLagrangian on
>>
>> alpha {
>> residuerange 1-10
>> psfSegID HLX
>> hbondcoeff 0.5
>> angleref 88
>> angletol 15
>> hbondcutoff 3.3
>> hbondexpnumer 6
>> hbondexpdenom 8
>> }
>> }
>>
>> abf {
>> colvars alpha
>> fullSamples 10000
>> applyBias yes
>> outputFreq 100
>> hideJacobian no
>> }
>>
>> Thanks !
>>
>> Lyna
>
>
>
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