#
#  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 import DataStructs
from CreateFps import GetMolFingerprint
from rdkit.RDLogger import logger
logger=logger()
import sys

# 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'

# propField is the name of the property (from the SD file) you want to use
# as the "activity"
propField='chemical_shift_1'

# similarity threshold for a pair to be considered interesting.
# (i.e. pairs with a similiarity below this value will not be
# added to the output.
similarityThreshold=0.5

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

    data=[]
    logger.info('reading molecules and generating fingeprints')
    for i,mol in enumerate(suppl):
        if not mol:
            continue
        smi = Chem.MolToSmiles(mol,True)
        nm = mol.GetProp(nameField)
        property = float(mol.GetProp(propField))
        fp = GetMolFingerprint(mol,maxPathLength)
        data.append((nm,smi,property,fp))
        
    logger.info('  got %d molecules'%len(data))

    logger.info('calculating pairs')
    pairs = []
    for i in range(len(data)):
        for j in range(i+1,len(data)):
            if DataStructs.DiceSimilarity(data[i][-1],data[j][-1])>similarityThreshold:
                pairs.append((i,j))
        if not (i+1)%100:
            logger.info('Done %d molecules'%(i+1))
    
    logger.info('  got %d reasonable pairs'%len(pairs))

    logger.info('creating output file')
    print >>outF,'nameA|nameB|nameAB|smilesA|smilesB|smilesAB|actA|actB|dAct|dist|disparity'
    for i,j in pairs:
        if data[i][2]<data[j][2]:
            i,j=j,i
        nmi,smii,propi,fpi=data[i]
        nmj,smij,propj,fpj=data[j]
        dAct = propi-propj
        dist = 1.-DataStructs.DiceSimilarity(fpi,fpj)
        if dist!=0:
            disparity=dAct/dist
        else:
            disparity=1000
        print >>outF,'%s|%s|%s_%s|%s|%s|%s.%s|%f|%f|%f|%f|%f'%(nmi,nmj,nmi,nmj,smii,smij,smii,smij,
                                                               propi,propj,dAct,dist,disparity)