Lines Matching +full:- +full:r
12 query=np.array([ 0.08387197, 0.68082274, 1.06756417, 0.88914541, 0.42513398, -0.3259053,
13 -0.80934885, -0.90979435, -0.64026483, 0.06923695])
15 template=np.array([ 1.00000000e+00, 7.96326711e-04, -9.99998732e-01, -2.38897811e-03,
16 9.99994927e-01])
19 r = scipy.spatial.distance.euclidean(xa,xb)
20 return(r)
23 r = scipy.spatial.distance.braycurtis(xa,xb)
24 return(r)
27 r = scipy.spatial.distance.canberra(xa,xb)
28 return(r)
31 r = scipy.spatial.distance.chebyshev(xa,xb)
32 return(r)
35 r = scipy.spatial.distance.cityblock(xa,xb)
36 return(r)
39 r = scipy.spatial.distance.correlation (xa,xb)
40 return(r)
43 r = scipy.spatial.distance.cosine (xa,xb)
44 return(r)
47 r = scipy.spatial.distance.jensenshannon (xa,xb)
48 return(r)
51 r = scipy.spatial.distance.minkowski(xa,xb,p=dim)
52 return(r)
55 r = scipy.spatial.distance.dice (xa,xb)
56 return(r)
59 r = scipy.spatial.distance.hamming (xa,xb)
60 return(r)
63 r = scipy.spatial.distance.jaccard (xa,xb)
64 return(r)
67 r = scipy.spatial.distance.kulsinski (xa,xb)
68 return(r)
71 r = scipy.spatial.distance.rogerstanimoto (xa,xb)
72 return(r)
75 r = scipy.spatial.distance.russellrao (xa,xb)
76 return(r)
79 r = scipy.spatial.distance.sokalmichener (xa,xb)
80 return(r)
83 r = scipy.spatial.distance.sokalsneath (xa,xb)
84 return(r)
87 r = scipy.spatial.distance.yule (xa,xb)
88 return(r)