/usr/share/RDKit/Contrib/LEF/ClusterFps.py is in rdkit-data 201503-3.
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# Copyright (c) 2009, Novartis Institutes for BioMedical Research Inc.
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met:
#
# * Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above
# copyright notice, this list of conditions and the following
# disclaimer in the documentation and/or other materials provided
# with the distribution.
# * Neither the name of Novartis Institutes for BioMedical Research Inc.
# nor the names of its contributors may be used to endorse or promote
# products derived from this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
# A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
# OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
# SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
# LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
# DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
# THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#
# Created by Greg Landrum and Anna Vulpetti, March 2009
from __future__ import print_function
from rdkit.ML.Cluster import Butina
from rdkit import DataStructs
import sys,cPickle
# sims is the list of similarity thresholds used to generate clusters
sims=[.9,.8,.7,.6]
smis=[]
uniq=[]
uFps=[]
for fileN in sys.argv[1:]:
inF = file(sys.argv[1],'r')
cols = cPickle.load(inF)
fps = cPickle.load(inF)
for row in fps:
nm,smi,fp = row[:3]
if smi not in smis:
try:
fpIdx = uFps.index(fp)
except ValueError:
fpIdx=len(uFps)
uFps.append(fp)
uniq.append([fp,nm,smi,'FP_%d'%fpIdx]+row[3:])
smis.append(smi)
def distFunc(a,b):
return 1.-DataStructs.DiceSimilarity(a[0],b[0])
for sim in sims:
clusters=Butina.ClusterData(uniq,len(uniq),1.-sim,False,distFunc)
print('Sim: %.2f, nClusters: %d'%(sim,len(clusters)), file=sys.stderr)
for i,cluster in enumerate(clusters):
for pt in cluster:
uniq[pt].append(str(i+1))
cols.append('cluster_thresh_%d'%(int(100*sim)))
print(' '.join(cols))
for row in uniq:
print(' '.join(row[1:]))
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