[Chimera-users] representative fits in chimera fitmap search
kosinski at embl.de
Fri Mar 18 10:19:59 PDT 2016
In the fitmap command global search, how the unique fit is selected from
the cluster of similar fits?
Ideally, from each cluster, I would like to obtain the fit the gave the
best cross-correlation. But, I think, based on the fit_search code in
FitMap/search.py, what is happening is that the first unique fit ever
encountered is added to the fit list:
close = b.close_transforms(ptf)
if len(close) == 0:
transforms = [M.multiply_matrices(ptf, mtv) for mtv in
stats['hits'] = 1
f = Fit(models, transforms, volume, stats)
f.ptf = ptf
fo[id(ptf)] = f
s = fo[id(close)].stats
s['hits'] += 1
and any subsequent fit that is close to the first, would be discarded,
even if it gives better cross-correlation.
Do I understand correctly that the unique fit is not necessarily the
best scoring fit from the cluster?
Thanks in advance for clarification,
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