def test_InsertData(self):
newTblName = 'NEW_TABLE'
conn = DbConnect(self.tempDbName)
try:
conn.GetCursor().execute('drop table %s' % (newTblName))
except Exception:
pass
conn.Commit()
conn.AddTable(newTblName, 'id int,val1 int, val2 int')
for i in range(10):
conn.InsertData(newTblName, (i, i + 1, 2 * i))
conn.Commit()
d = conn.GetData(table=newTblName)
assert len(d) == 10
self.assertEqual(len(conn.GetColumnNames(table=newTblName)), 3)
conn.AddColumn(newTblName, 'val3', 'int')
conn.Commit()
self.assertEqual(len(conn.GetColumnNames(table=newTblName)), 4)
d = conn.GetColumns('id,val3', table=newTblName)
self.assertEqual(len(d), 10)
self.assertTrue(all(r[1] is None for r in d))
for r in d:
conn.InsertColumnData(newTblName, 'val3', r[0],
'id={0}'.format(r[0]))
conn.Commit()
d = conn.GetColumns('id,val3', table=newTblName)
self.assertTrue(all(r[0] == r[1] for r in d))
d = None
try:
conn.GetCursor().execute('drop table %s' % (newTblName))
except Exception:
assert 0, 'drop table failed'
def DBToData(dbName, tableName, user='******', password='******', dupCol=-1, what='*', where='',
join='', pickleCol=-1, pickleClass=None, ensembleIds=None):
""" constructs an _MLData.MLDataSet_ from a database
**Arguments**
- dbName: the name of the database to be opened
- tableName: the table name containing the data in the database
- user: the user name to be used to connect to the database
- password: the password to be used to connect to the database
- dupCol: if nonzero specifies which column should be used to recognize
duplicates.
**Returns**
an _MLData.MLDataSet_
**Notes**
- this uses Dbase.DataUtils functionality
"""
conn = DbConnect(dbName, tableName, user, password)
res = conn.GetData(fields=what, where=where, join=join, removeDups=dupCol, forceList=1)
nPts = len(res)
vals = [None] * nPts
ptNames = [None] * nPts
classWorks = True
for i in range(nPts):
tmp = list(res[i])
ptNames[i] = tmp.pop(0)
if pickleCol >= 0:
if not pickleClass or not classWorks:
tmp[pickleCol] = cPickle.loads(str(tmp[pickleCol]))
else:
try:
tmp[pickleCol] = pickleClass(str(tmp[pickleCol]))
except Exception:
tmp[pickleCol] = cPickle.loads(str(tmp[pickleCol]))
classWorks = False
if ensembleIds:
tmp[pickleCol] = BitUtils.ConstructEnsembleBV(tmp[pickleCol], ensembleIds)
else:
if ensembleIds:
tmp = TakeEnsemble(tmp, ensembleIds, isDataVect=True)
vals[i] = tmp
varNames = conn.GetColumnNames(join=join, what=what)
data = MLData.MLDataSet(vals, varNames=varNames, ptNames=ptNames)
return data
def testAddTable(self):
""" tests AddTable and GetTableNames functionalities """
newTblName = 'NEW_TABLE'
conn = DbConnect(self.tempDbName)
try:
conn.GetCursor().execute('drop table %s' % (newTblName))
except Exception:
pass
conn.Commit()
self.assertNotIn(newTblName, [x.strip() for x in conn.GetTableNames()])
conn.AddTable(newTblName, 'id int')
self.assertIn(newTblName, [x.strip() for x in conn.GetTableNames()])
self.assertEqual(conn.GetColumnNames(table=newTblName), ['id'])
conn.GetCursor().execute('drop table %s' % (newTblName))
def GetAllDescriptorNames(db, tbl1, tbl2, user='******', password='******'):
""" gets possible descriptor names from a database
**Arguments**
- db: the name of the database to use
- tbl1: the name of the table to be used for reading descriptor values
- tbl2: the name of the table to be used for reading notes about the
descriptors (*descriptions of the descriptors if you like*)
- user: the user name for DB access
- password: the password for DB access
**Returns**
a 2-tuple containing:
1) a list of column names
2) a list of column descriptors
**Notes**
- this uses _Dbase.DbInfo_ and Dfunctionality for querying the database
- it is assumed that tbl2 includes 'property' and 'notes' columns
"""
from rdkit.Dbase.DbConnection import DbConnect
conn = DbConnect(db, user=user, password=password)
colNames = conn.GetColumnNames(table=tbl1)
colDesc = map(lambda x: (x[0].upper(), x[1]),
conn.GetColumns('property,notes', table=tbl2))
for name, desc in countOptions:
colNames.append(name)
colDesc.append((name, desc))
return colNames, colDesc
def _init(self, refCompos, copyBounds=0):
BuildComposite._verbose = 0
conn = DbConnect(self.details.dbName, self.details.tableName)
cols = [x.upper() for x in conn.GetColumnNames()]
cDescs = [x.upper() for x in refCompos.GetDescriptorNames()]
self.assertEqual(cols, cDescs)
self.details.nModels = 10
self.details.lockRandom = 1
self.details.randomSeed = refCompos._randomSeed
self.details.splitFrac = refCompos._splitFrac
if self.details.splitFrac:
self.details.splitRun = 1
else:
self.details.splitRun = 0
if not copyBounds:
self.details.qBounds = [0] * len(cols)
else:
self.details.qBounds = refCompos.GetQuantBounds()[0]
def RunSearch(options, queryFilename):
global sigFactory
if options.similarityType == 'AtomPairs':
fpBuilder = FingerprintUtils.BuildAtomPairFP
simMetric = DataStructs.DiceSimilarity
dbName = os.path.join(options.dbDir, options.pairDbName)
fpTableName = options.pairTableName
fpColName = options.pairColName
elif options.similarityType == 'TopologicalTorsions':
fpBuilder = FingerprintUtils.BuildTorsionsFP
simMetric = DataStructs.DiceSimilarity
dbName = os.path.join(options.dbDir, options.torsionsDbName)
fpTableName = options.torsionsTableName
fpColName = options.torsionsColName
elif options.similarityType == 'RDK':
fpBuilder = FingerprintUtils.BuildRDKitFP
simMetric = DataStructs.FingerprintSimilarity
dbName = os.path.join(options.dbDir, options.fpDbName)
fpTableName = options.fpTableName
if not options.fpColName:
options.fpColName = 'rdkfp'
fpColName = options.fpColName
elif options.similarityType == 'Pharm2D':
fpBuilder = FingerprintUtils.BuildPharm2DFP
simMetric = DataStructs.DiceSimilarity
dbName = os.path.join(options.dbDir, options.fpDbName)
fpTableName = options.pharm2DTableName
if not options.fpColName:
options.fpColName = 'pharm2dfp'
fpColName = options.fpColName
FingerprintUtils.sigFactory = BuildSigFactory(options)
elif options.similarityType == 'Gobbi2D':
from rdkit.Chem.Pharm2D import Gobbi_Pharm2D
fpBuilder = FingerprintUtils.BuildPharm2DFP
simMetric = DataStructs.TanimotoSimilarity
dbName = os.path.join(options.dbDir, options.fpDbName)
fpTableName = options.gobbi2DTableName
if not options.fpColName:
options.fpColName = 'gobbi2dfp'
fpColName = options.fpColName
FingerprintUtils.sigFactory = Gobbi_Pharm2D.factory
elif options.similarityType == 'Morgan':
fpBuilder = FingerprintUtils.BuildMorganFP
simMetric = DataStructs.DiceSimilarity
dbName = os.path.join(options.dbDir, options.morganFpDbName)
fpTableName = options.morganFpTableName
fpColName = options.morganFpColName
extraArgs = {}
if options.similarityMetric == 'tanimoto':
simMetric = DataStructs.TanimotoSimilarity
elif options.similarityMetric == 'dice':
simMetric = DataStructs.DiceSimilarity
elif options.similarityMetric == 'tversky':
simMetric = DataStructs.TverskySimilarity
extraArgs['tverskyA'] = options.tverskyA
extraArgs['tverskyB'] = options.tverskyB
if options.smilesQuery:
mol = Chem.MolFromSmiles(options.smilesQuery)
if not mol:
logger.error('could not build query molecule from smiles "%s"' %
options.smilesQuery)
sys.exit(-1)
options.queryMol = mol
elif options.smartsQuery:
mol = Chem.MolFromSmarts(options.smartsQuery)
if not mol:
logger.error('could not build query molecule from smarts "%s"' %
options.smartsQuery)
sys.exit(-1)
options.queryMol = mol
if options.outF == '-':
outF = sys.stdout
elif options.outF == '':
outF = None
else:
outF = open(options.outF, 'w+')
molsOut = False
if options.sdfOut:
molsOut = True
if options.sdfOut == '-':
sdfOut = sys.stdout
else:
sdfOut = open(options.sdfOut, 'w+')
else:
sdfOut = None
if options.smilesOut:
molsOut = True
if options.smilesOut == '-':
smilesOut = sys.stdout
else:
smilesOut = open(options.smilesOut, 'w+')
else:
smilesOut = None
if queryFilename:
try:
tmpF = open(queryFilename, 'r')
except IOError:
logger.error('could not open query file %s' % queryFilename)
sys.exit(1)
if options.molFormat == 'smiles':
func = GetMolsFromSmilesFile
elif options.molFormat == 'sdf':
func = GetMolsFromSDFile
if not options.silent:
msg = 'Reading query molecules'
if fpBuilder: msg += ' and generating fingerprints'
logger.info(msg)
probes = []
i = 0
nms = []
for nm, smi, mol in func(queryFilename, None, options.nameProp):
i += 1
nms.append(nm)
if not mol:
logger.error('query molecule %d could not be built' % (i))
probes.append((None, None))
continue
if fpBuilder:
probes.append((mol, fpBuilder(mol)))
else:
probes.append((mol, None))
if not options.silent and not i % 1000:
logger.info(" done %d" % i)
else:
probes = None
conn = None
idName = options.molIdName
ids = None
names = None
molDbName = os.path.join(options.dbDir, options.molDbName)
molIdName = options.molIdName
mConn = DbConnect(molDbName)
cns = [(x.lower(), y)
for x, y in mConn.GetColumnNamesAndTypes('molecules')]
idCol, idTyp = cns[0]
if options.propQuery or options.queryMol:
conn = DbConnect(molDbName)
curs = conn.GetCursor()
if options.queryMol:
if not options.silent: logger.info('Doing substructure query')
if options.propQuery:
where = 'where %s' % options.propQuery
else:
where = ''
if not options.silent:
curs.execute('select count(*) from molecules %(where)s' %
locals())
nToDo = curs.fetchone()[0]
join = ''
doSubstructFPs = False
fpDbName = os.path.join(options.dbDir, options.fpDbName)
if os.path.exists(fpDbName) and not options.negateQuery:
curs.execute("attach database '%s' as fpdb" % (fpDbName))
try:
curs.execute('select * from fpdb.%s limit 1' %
options.layeredTableName)
except:
pass
else:
doSubstructFPs = True
join = 'join fpdb.%s using (%s)' % (
options.layeredTableName, idCol)
query = LayeredOptions.GetQueryText(options.queryMol)
if query:
if not where:
where = 'where'
else:
where += ' and'
where += ' ' + query
cmd = 'select %(idCol)s,molpkl from molecules %(join)s %(where)s' % locals(
)
curs.execute(cmd)
row = curs.fetchone()
nDone = 0
ids = []
while row:
id, molpkl = row
if not options.zipMols:
m = _molFromPkl(molpkl)
else:
m = Chem.Mol(zlib.decompress(molpkl))
matched = m.HasSubstructMatch(options.queryMol)
if options.negateQuery:
matched = not matched
if matched:
ids.append(id)
nDone += 1
if not options.silent and not nDone % 500:
if not doSubstructFPs:
logger.info(
' searched %d (of %d) molecules; %d hits so far' %
(nDone, nToDo, len(ids)))
else:
logger.info(
' searched through %d molecules; %d hits so far' %
(nDone, len(ids)))
row = curs.fetchone()
if not options.silent and doSubstructFPs and nToDo:
nFiltered = nToDo - nDone
logger.info(
' Fingerprint screenout rate: %d of %d (%%%.2f)' %
(nFiltered, nToDo, 100. * nFiltered / nToDo))
elif options.propQuery:
if not options.silent: logger.info('Doing property query')
propQuery = options.propQuery.split(';')[0]
curs.execute(
'select %(idCol)s from molecules where %(propQuery)s' %
locals())
ids = [x[0] for x in curs.fetchall()]
if not options.silent:
logger.info('Found %d molecules matching the query' % (len(ids)))
t1 = time.time()
if probes:
if not options.silent: logger.info('Finding Neighbors')
conn = DbConnect(dbName)
cns = conn.GetColumnNames(fpTableName)
curs = conn.GetCursor()
if ids:
ids = [(x, ) for x in ids]
curs.execute(
'create temporary table _tmpTbl (%(idCol)s %(idTyp)s)' %
locals())
curs.executemany('insert into _tmpTbl values (?)', ids)
join = 'join _tmpTbl using (%(idCol)s)' % locals()
else:
join = ''
if cns[0].lower() != idCol.lower():
# backwards compatibility to the days when mol tables had a guid and
# the fps tables did not:
curs.execute("attach database '%(molDbName)s' as mols" % locals())
curs.execute("""
select %(idCol)s,%(fpColName)s from %(fpTableName)s join
(select %(idCol)s,%(molIdName)s from mols.molecules %(join)s)
using (%(molIdName)s)
""" % (locals()))
else:
curs.execute(
'select %(idCol)s,%(fpColName)s from %(fpTableName)s %(join)s'
% locals())
def poolFromCurs(curs, similarityMethod):
row = curs.fetchone()
while row:
id, pkl = row
fp = DepickleFP(pkl, similarityMethod)
yield (id, fp)
row = curs.fetchone()
topNLists = GetNeighborLists(probes,
options.topN,
poolFromCurs(curs,
options.similarityType),
simMetric=simMetric,
simThresh=options.simThresh,
**extraArgs)
uniqIds = set()
nbrLists = {}
for i, nm in enumerate(nms):
topNLists[i].reverse()
scores = topNLists[i].GetPts()
nbrNames = topNLists[i].GetExtras()
nbrs = []
for j, nbrGuid in enumerate(nbrNames):
if nbrGuid is None:
break
else:
uniqIds.add(nbrGuid)
nbrs.append((nbrGuid, scores[j]))
nbrLists[(i, nm)] = nbrs
t2 = time.time()
if not options.silent:
logger.info('The search took %.1f seconds' % (t2 - t1))
if not options.silent: logger.info('Creating output')
curs = mConn.GetCursor()
ids = list(uniqIds)
ids = [(x, ) for x in ids]
curs.execute('create temporary table _tmpTbl (%(idCol)s %(idTyp)s)' %
locals())
curs.executemany('insert into _tmpTbl values (?)', ids)
curs.execute(
'select %(idCol)s,%(molIdName)s from molecules join _tmpTbl using (%(idCol)s)'
% locals())
nmDict = {}
for guid, id in curs.fetchall():
nmDict[guid] = str(id)
ks = list(nbrLists.keys())
ks.sort()
if not options.transpose:
for i, nm in ks:
nbrs = nbrLists[(i, nm)]
nbrTxt = options.outputDelim.join([nm] + [
'%s%s%.3f' % (nmDict[id], options.outputDelim, score)
for id, score in nbrs
])
if outF: print(nbrTxt, file=outF)
else:
labels = [
'%s%sSimilarity' % (x[1], options.outputDelim) for x in ks
]
if outF: print(options.outputDelim.join(labels), file=outF)
for i in range(options.topN):
outL = []
for idx, nm in ks:
nbr = nbrLists[(idx, nm)][i]
outL.append(nmDict[nbr[0]])
outL.append('%.3f' % nbr[1])
if outF: print(options.outputDelim.join(outL), file=outF)
else:
if not options.silent: logger.info('Creating output')
curs = mConn.GetCursor()
ids = [(x, ) for x in set(ids)]
curs.execute('create temporary table _tmpTbl (%(idCol)s %(idTyp)s)' %
locals())
curs.executemany('insert into _tmpTbl values (?)', ids)
molIdName = options.molIdName
curs.execute(
'select %(idCol)s,%(molIdName)s from molecules join _tmpTbl using (%(idCol)s)'
% locals())
nmDict = {}
for guid, id in curs.fetchall():
nmDict[guid] = str(id)
if outF: print('\n'.join(nmDict.values()), file=outF)
if molsOut and ids:
molDbName = os.path.join(options.dbDir, options.molDbName)
cns = [x.lower() for x in mConn.GetColumnNames('molecules')]
if cns[-1] != 'molpkl':
cns.remove('molpkl')
cns.append('molpkl')
curs = mConn.GetCursor()
#curs.execute('create temporary table _tmpTbl (guid integer)'%locals())
#curs.executemany('insert into _tmpTbl values (?)',ids)
cnText = ','.join(cns)
curs.execute(
'select %(cnText)s from molecules join _tmpTbl using (%(idCol)s)' %
locals())
row = curs.fetchone()
molD = {}
while row:
row = list(row)
m = _molFromPkl(row[-1])
guid = row[0]
nm = nmDict[guid]
if sdfOut:
m.SetProp('_Name', nm)
print(Chem.MolToMolBlock(m), file=sdfOut)
for i in range(1, len(cns) - 1):
pn = cns[i]
pv = str(row[i])
print >> sdfOut, '> <%s>\n%s\n' % (pn, pv)
print('$$$$', file=sdfOut)
if smilesOut:
smi = Chem.MolToSmiles(m, options.chiralSmiles)
if smilesOut:
print('%s %s' % (smi, str(row[1])), file=smilesOut)
row = curs.fetchone()
if not options.silent: logger.info('Done!')