rdkit.ML.KNN.DistFunctions module

rdkit.ML.KNN.DistFunctions.EuclideanDist(ex1, ex2, attrs)

>>> v1 = [0,1,0,1]
>>> v2 = [1,0,1,0]
>>> EuclideanDist(v1,v2,range(4))
2.0
>>> EuclideanDist(v1,v1,range(4))
0.0
>>> v2 = [0,0,0,1]
>>> EuclideanDist(v1,v2,range(4))
1.0
>>> v2 = [0,.5,0,.5]
>>> abs(EuclideanDist(v1,v2,range(4))-1./math.sqrt(2))<1e-4
1

rdkit.ML.KNN.DistFunctions.TanimotoDist(ex1, ex2, attrs)

>>> v1 = [0,1,0,1]
>>> v2 = [1,0,1,0]
>>> TanimotoDist(v1,v2,range(4))
1.0
>>> v2 = [1,0,1,1]
>>> TanimotoDist(v1,v2,range(4))
0.75
>>> TanimotoDist(v2,v2,range(4))
0.0

# this tests Issue 122 >>> v3 = [0,0,0,0] >>> TanimotoDist(v3,v3,range(4)) 1.0