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142 lines
3.9 KiB
Python
Executable File
142 lines
3.9 KiB
Python
Executable File
from rdkit import RDConfig
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import unittest
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from rdkit.SimDivFilters import rdSimDivPickers
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from rdkit.DataManip.Metric import rdMetricMatrixCalc as rdmmc
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import numpy
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import random
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class TestCase(unittest.TestCase):
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def setUp(self) :
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self.n = 1000
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self.m = 80
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self.d = 2
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self.dataPts = numpy.zeros((self.n, self.d), 'd')
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for i in range(self.n):
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for j in range(self.d):
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self.dataPts[i,j] = random.random()
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self.dMat = rdmmc.GetEuclideanDistMat(self.dataPts)
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def test0MaxMin(self):
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pkr = rdSimDivPickers.MaxMinPicker()
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maxmin = pkr.Pick(self.dMat, self.n, self.m,(886,112))
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self.failUnless(maxmin[0]==886)
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self.failUnless(maxmin[1]==112)
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def func(i,j):
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if i==j:
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return 0.0
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if i<j:
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j,i=i,j
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return self.dMat[i*(i-1)/2+j]
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lmaxmin = pkr.LazyPick(func, self.n, self.m,(886,112))
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self.failUnless(list(lmaxmin)==list(maxmin))
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self.failUnlessRaises(ValueError,lambda:pkr.Pick(self.dMat, self.n, self.m,(1012,)))
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self.failUnlessRaises(ValueError,lambda:pkr.Pick(self.dMat, self.n, self.m,(-1,)))
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maxmin = pkr.Pick(self.dMat, self.n, self.m)
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self.failUnless(maxmin)
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lmaxmin = pkr.LazyPick(func, self.n, self.m)
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self.failUnless(lmaxmin)
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def test1HierarchPick(self) :
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infil = open("test_data/points.csv", 'r')
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lines = infil.readlines()
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infil.close()
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self.dataPts = numpy.zeros((len(lines), 2), 'd')
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labels = []
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i = 0
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for line in lines :
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tlst = line.strip().split(',')
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self.dataPts[i, 0] = float(tlst[1])
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self.dataPts[i, 1] = float(tlst[2])
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labels.append(int(tlst[3]))
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i += 1
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self.dMat = rdmmc.GetEuclideanDistMat(self.dataPts)
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pkr = rdSimDivPickers.HierarchicalClusterPicker(rdSimDivPickers.ClusterMethod.WARD)
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clusters = pkr.Cluster(self.dMat, i, 2)
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# check that each of the clusters have the same label
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for cl in clusters :
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clbl = labels[cl[0]]
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for id in cl:
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assert clbl == labels[id]
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hierarch = pkr.Pick(self.dMat, i, 2)
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assert tuple(hierarch) == (1,30)
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def testIssue208(self) :
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sz = 10
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N=3
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m = []
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for i in range(sz):
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for j in range(i+1,sz):
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m.append(random.random())
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m = numpy.array(m)
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picker = rdSimDivPickers.HierarchicalClusterPicker(rdSimDivPickers.ClusterMethod.WARD)
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p1 = list(picker.Pick(m,sz,N))
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p1.sort()
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p2 = list(picker.Pick(m,sz,N))
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p2.sort()
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self.failUnless(p1==p2)
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def testInts(self) :
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""" make sure we can handle ints too """
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sz = 10
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N=3
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m = []
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for i in range(sz):
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for j in range(i+1,sz):
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m.append(int(100*random.random()))
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m = numpy.array(m)
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picker = rdSimDivPickers.HierarchicalClusterPicker(rdSimDivPickers.ClusterMethod.WARD)
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p1 = list(picker.Pick(m,sz,N))
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p1.sort()
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p2 = list(picker.Pick(m,sz,N))
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p2.sort()
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self.failUnless(p1==p2)
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def testNonUniqueCrash(self) :
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from rdkit import DataStructs
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sz = 10
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nbits=20
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nBitsToSet=int(nbits*.3)
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N=12
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vs = []
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for i in range(sz):
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bv = DataStructs.ExplicitBitVect(nbits)
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for j in range(nBitsToSet):
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val= int(nbits*random.random())
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bv.SetBit(val)
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vs.append(bv)
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vs.append(bv)
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def taniFunc(i,j,bvs = vs):
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d = 1-DataStructs.FingerprintSimilarity(bvs[i],bvs[j])
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return d
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picker = rdSimDivPickers.MaxMinPicker()
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try:
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mm = picker.LazyPick(taniFunc,len(vs),N)
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except:
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ok=False
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else:
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ok=True
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self.failUnless(ok)
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self.failUnless(len(mm)==N)
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picker = None
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ds = []
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nvs = len(vs)
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for i in range(nvs):
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for j in range(i+1,nvs):
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d = taniFunc(i,j)
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ds.append(d)
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m = numpy.array(ds)
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picker = rdSimDivPickers.HierarchicalClusterPicker(rdSimDivPickers.ClusterMethod.WARD)
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p1 = list(picker.Pick(m,nvs,N))
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if __name__ == '__main__':
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unittest.main()
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