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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 import Chem
from rdkit.Chem import AllChem
from rdkit.Chem.AtomPairs import Pairs,Torsions
import sys,cPickle

# maxPathLength is the maximum path length in atoms
# maxPathLength=6 corresponds to F-FP-5
# maxPathLength=7 corresponds to F-FP-6
# maxPathLength=8 corresponds to F-FP-7
maxPathLength=8

# nameField is the name of the property (from the SD file) that has molecule
# names... If the molecules have names in the first row of the file, use "_Name"
nameField = 'Compound_orig'
#nameField = '_Name'

extraQueries=(
              ('SCF3?',Chem.MolFromSmarts('SC(F)(F)F')),
              ('COCF3?',Chem.MolFromSmarts('C(=O)C(F)(F)F')),
              ('OCF3?',Chem.MolFromSmarts('OC(F)(F)F')),
              ('NCF3?',Chem.MolFromSmarts('NC(F)(F)F')),
              ('CF3?',Chem.MolFromSmarts('C(F)(F)F')),
    )

def GetMolFingerprint(mol,maxPathLength):
    FQuery = Chem.MolFromSmarts('F')
    CF3Query= Chem.MolFromSmarts('[$(C(F)(F)F)]')
    CF3Rxn = AllChem.ReactionFromSmarts('[*:1]-C(F)(F)F>>[*:1]-F')
    hasCF3 = mol.HasSubstructMatch(CF3Query)
    if hasCF3:
        p = CF3Rxn.RunReactants((mol,))[0][0]
        Chem.SanitizeMol(p)
        for nm in mol.GetPropNames():
            p.SetProp(nm,mol.GetProp(nm))
        mol = p
    match = mol.GetSubstructMatch(FQuery)
    fp = Torsions.GetHashedTopologicalTorsionFingerprint(mol,nBits=9192,targetSize=maxPathLength,fromAtoms=match)
    for i in range(2,maxPathLength):
        nfp = Torsions.GetHashedTopologicalTorsionFingerprint(mol,nBits=9192,targetSize=i,fromAtoms=match)
        for bit,v in nfp.GetNonzeroElements().iteritems():
            fp[bit] = fp[bit]+v
    return fp

if __name__=='__main__':
    suppl = Chem.SDMolSupplier(sys.argv[1])
    outF = file(sys.argv[2],'w+')
    fps = []

    for i,mol in enumerate(suppl):
        if not mol:
            continue
        smi = Chem.MolToSmiles(mol,True)
        queryMatches = [str(mol.HasSubstructMatch(y)) for x,y in extraQueries]

        fp = GetMolFingerprint(mol,maxPathLength)

        nm = mol.GetProp(nameField)
        fps.append([nm,smi,fp]+queryMatches)
    colNames = ['name','smiles','fp']+[x for x,y in extraQueries]
    cPickle.dump(colNames,outF)
    cPickle.dump(fps,outF)

    print('name1 smiles1 name2 smiles2 name12 smiles12 environment_id '+' '.join([x for x,y in extraQueries]))
    if 1:
        seen = []
        smis=[]
        data=[]
        for row in fps:
            nm = row[0]
            smi = row[1]
            fp = row[2]
            if fp in seen and smi not in smis:
                id = seen.index(fp)
                onm,osmi=data[id]
                print(nm,smi,onm,osmi,nm+'.'+onm,smi+'.'+osmi,id+1,' '.join(row[3:]))
            else:
                seen.append(fp)
                smis.append(smi)
                data.append((nm,smi))
    else:
        smis=[]
        for nm,smi,fp in fps:
            if smi not in smis:
                pass