# # 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:]))