def test10BulkOps2(self):
nbits = 10000
bvs = []
for bvi in range(10):
bv = DataStructs.ExplicitBitVect(nbits)
for j in range(nbits):
x = random.randrange(0, nbits)
bv.SetBit(x)
bvs.append(bv)
bvs = tuple(bvs)
sims = DataStructs.BulkTanimotoSimilarity(bvs[0], bvs)
for i in range(len(bvs)):
sim = DataStructs.TanimotoSimilarity(bvs[0], bvs[i])
self.failUnless(feq(sim, sims[i]))
sims = DataStructs.BulkDiceSimilarity(bvs[0], bvs)
for i in range(len(bvs)):
sim = DataStructs.DiceSimilarity(bvs[0], bvs[i])
self.failUnless(feq(sim, sims[i]))
sims = DataStructs.BulkAllBitSimilarity(bvs[0], bvs)
for i in range(len(bvs)):
sim = DataStructs.AllBitSimilarity(bvs[0], bvs[i])
self.failUnless(feq(sim, sims[i]))
sims = DataStructs.BulkOnBitSimilarity(bvs[0], bvs)
for i in range(len(bvs)):
sim = DataStructs.OnBitSimilarity(bvs[0], bvs[i])
self.failUnless(feq(sim, sims[i]))
sims = DataStructs.BulkRogotGoldbergSimilarity(bvs[0], bvs)
for i in range(len(bvs)):
sim = DataStructs.RogotGoldbergSimilarity(bvs[0], bvs[i])
self.failUnless(feq(sim, sims[i]))
sims = DataStructs.BulkTverskySimilarity(bvs[0], bvs, 1, 1)
for i in range(len(bvs)):
sim = DataStructs.TverskySimilarity(bvs[0], bvs[i], 1, 1)
self.failUnless(feq(sim, sims[i]))
sim = DataStructs.TanimotoSimilarity(bvs[0], bvs[i])
self.failUnless(feq(sim, sims[i]))
sims = DataStructs.BulkTverskySimilarity(bvs[0], bvs, .5, .5)
for i in range(len(bvs)):
sim = DataStructs.TverskySimilarity(bvs[0], bvs[i], .5, .5)
self.failUnless(feq(sim, sims[i]))
sim = DataStructs.DiceSimilarity(bvs[0], bvs[i])
self.failUnless(feq(sim, sims[i]))
def test10BulkOps3(self):
nbits = 10000
bvs = numpy.empty((10, ), DataStructs.ExplicitBitVect)
for bvi in range(10):
bv = DataStructs.ExplicitBitVect(nbits)
for j in range(nbits):
x = random.randrange(0, nbits)
bv.SetBit(x)
bvs[bvi] = bv
sims = DataStructs.BulkTanimotoSimilarity(bvs[0], bvs)
for i in range(len(bvs)):
sim = DataStructs.TanimotoSimilarity(bvs[0], bvs[i])
self.assertTrue(feq(sim, sims[i]))
sims = DataStructs.BulkDiceSimilarity(bvs[0], bvs)
for i in range(len(bvs)):
sim = DataStructs.DiceSimilarity(bvs[0], bvs[i])
self.assertTrue(feq(sim, sims[i]))
sims = DataStructs.BulkAllBitSimilarity(bvs[0], bvs)
for i in range(len(bvs)):
sim = DataStructs.AllBitSimilarity(bvs[0], bvs[i])
self.assertTrue(feq(sim, sims[i]))
sims = DataStructs.BulkOnBitSimilarity(bvs[0], bvs)
for i in range(len(bvs)):
sim = DataStructs.OnBitSimilarity(bvs[0], bvs[i])
self.assertTrue(feq(sim, sims[i]))
sims = DataStructs.BulkRogotGoldbergSimilarity(bvs[0], bvs)
for i in range(len(bvs)):
sim = DataStructs.RogotGoldbergSimilarity(bvs[0], bvs[i])
self.assertTrue(feq(sim, sims[i]))
sims = DataStructs.BulkTverskySimilarity(bvs[0], bvs, 1, 1)
for i in range(len(bvs)):
sim = DataStructs.TverskySimilarity(bvs[0], bvs[i], 1, 1)
self.assertTrue(feq(sim, sims[i]))
sim = DataStructs.TanimotoSimilarity(bvs[0], bvs[i])
self.assertTrue(feq(sim, sims[i]))
sims = DataStructs.BulkTverskySimilarity(bvs[0], bvs, .5, .5)
for i in range(len(bvs)):
sim = DataStructs.TverskySimilarity(bvs[0], bvs[i], .5, .5)
self.assertTrue(feq(sim, sims[i]))
sim = DataStructs.DiceSimilarity(bvs[0], bvs[i])
self.assertTrue(feq(sim, sims[i]))
# dictionary for similarity measures
simil_dict = {}
simil_dict['Dice'] = lambda x, y: sorted(DataStructs.BulkDiceSimilarity(x, y),
reverse=True)
simil_dict['Tanimoto'] = lambda x, y: sorted(
DataStructs.BulkTanimotoSimilarity(x, y), reverse=True)
simil_dict['Cosine'] = lambda x, y: sorted(
DataStructs.BulkCosineSimilarity(x, y), reverse=True)
simil_dict['Russel'] = lambda x, y: sorted(
DataStructs.BulkRusselSimilarity(x, y), reverse=True)
simil_dict['Kulczynski'] = lambda x, y: sorted(
DataStructs.BulkKulczynskiSimilarity(x, y), reverse=True)
simil_dict['McConnaughey'] = lambda x, y: sorted(
DataStructs.BulkMcConnaugheySimilarity(x, y), reverse=True)
simil_dict['Manhattan'] = lambda x, y: sorted(
DataStructs.BulkAllBitSimilarity(x, y), reverse=True)
simil_dict['RogotGoldberg'] = lambda x, y: sorted(
DataStructs.BulkRogotGoldbergSimilarity(x, y), reverse=True)
def getBulkSimilarity(fp, fp_list, simil):
'''Calculate the bulk similarity for a given list of fingerprints'''
return simil_dict[simil](fp, fp_list)
# helper functions for the fusion
def printFPs(fps, fpname):
'''Prints a list of fingerprints'''
print "-------------------------------"
print "FUSION DONE FOR:"
for fp in fps: