#
#  Copyright (c) 2009, Novartis Institutes for BioMedical Research Inc.
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# Created by Greg Landrum and Anna Vulpetti, March 2009


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

# 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]
  pickle.dump(colNames, outF)
  pickle.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
