Hello Till--
> pcsPots = {} # store in a dict so I can access the values during calculation
This will be easier if you instead make pcsPots a PotList:
pcsPots = PotList('pcs')
then:
for (name, pcs_list, tensor) in pcsSpecs:
pcsPot = rdcPotTools.create_RDCPot(name, pcs_list, oTensor=tensor)
pcsPot.setUseDistance(True)
pcsPot.setScale(1)
pcsPot.setShowAllRestraints(True)
pcsPot.setVerbose(True)
tensors[name] = tensor
pcsPots.append( pcsPot )
potList.append( pcsPots )
for pot in pcsPots:
calcXTensor(pot.oTensor)
pcsPots_target_scale = 40.0
def scalepcs_for_time(t):
s = min(pcsPots_target_scale * t / expramp_duration, pcsPots_target_scale)
for p in pcsPots:
p.setScale(s)
return s
>
> Now, first of all, calcXTensor only really works for the Thulium-induced set
> of PCSs, for the others I get a few "mayDisplacement" messages and the
> parameters stay unchanged after the calculation.
Please try increasing the value of maxDisplacement in the call to
calcXTensor. It is possible that the default of 15 Angstroms is too
small for your case. I'm not certain that the call to
calcTensorOrientation is useful.
> Secondly, I the simulation
> will only ever start as long as I only have a single PCS-set in my potList.
> However, I wish to have a list of PCS-sets, each associated with a unique
> tensor, and base the refinement on that data.
What happens when you used more than one set of PCS data? This should
certainly be possible.
best regards--
Charles
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