def test_TrajCluster(self):
"""TrajCluster test"""
from biskit.md import traj2ensemble
traj = T.load( T.testRoot()+'/lig_pcr_00/traj.dat')
traj = traj2ensemble( traj )
aMask = traj.ref.mask( lambda a: a['name'] in ['CA','CB','CG'] )
traj = traj.thin( 1 )
traj.fit( aMask, verbose=self.local )
self.tc = TrajCluster( traj, verbose=self.local )
## check how many clusters that are needed with the given criteria
n_clusters = self.tc.calcClusterNumber( min_clst=3, max_clst=15,
rmsLimit=0.7, aMask=aMask )
## cluster
self.tc.cluster( n_clusters, aMask=aMask )
if self.local:
member_frames = self.tc.memberFrames()
print('There are %i clusters where the members are:'%n_clusters)
for i in range(n_clusters):
print('Cluster %i (%i members): %s'%( i+1,
len(member_frames[i]),
member_frames[i] ))
#!/usr/bin/env python
## re-generate binary test data in this folder
import biskit as B
import biskit.tools as T
from biskit.md import AmberCrdParser, EnsembleTraj, traj2ensemble
p = AmberCrdParser('raw/traj.crd', 'raw/traj_ref.pdb' )
## create standard trajectory object
t = p.crd2traj()
t.frameNames = T.load('raw/traj_framenames.list')
te = traj2ensemble(t, members=10)
te.fit(fit=0) ## re-calculate profile 'rms' (all-atom fit to average structure)
T.dump(te, 'traj.dat')
#!/usr/bin/env python
## re-generate binary test data in this folder
import biskit as B
import biskit.tools as T
from biskit.md import AmberCrdParser, EnsembleTraj, traj2ensemble
p = AmberCrdParser('raw/traj.crd', 'raw/traj_ref.pdb')
## create standard trajectory object
t = p.crd2traj()
t.frameNames = T.load('raw/traj_framenames.list')
te = traj2ensemble(t, members=10)
te.fit(
fit=0) ## re-calculate profile 'rms' (all-atom fit to average structure)
T.dump(te, 'traj.dat')