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1. '''
2. Group Members
3. =============
4. '''
5.
6. userids = ["Thormundur15","Ernir17"] # fill in this array with strings of usernames
7. def mCp1(x,y):
8.     '''Return the Euclidean distance between x and y
9.     '''
10.     summ = 0.0
11.     for i in xrange(0, len(x)):
12.         summ = summ + (x[i] - y[i])**2
13.     summ = sqrt(summ)
14.     return float(round(summ,2))
15.
16. def mCp2(x, y):
17.     '''Return the Manhattan distance between x and y
18.     '''
19.     summ = 0.0
20.     for i in xrange(0, len(x)):
21.         summ = summ + abs(x[i] - y[i])
22.
23.     return float(round(summ,2))
24.
25. def mCp3(x, y):
26.     '''Retun the Hamming distance between x and y
27.     '''
28.     summ = 0.0
29.     for i in xrange(0, len(x)):
30.         if x[i] != y[i]:
31.             summ += 1
32.     return summ
33.
34. def mCp4(x, y):
35.     '''Return the Levenshtein distance between x and y
36.     '''
37.     return mCp3(x, y)
38.
39. def mCp5(x, y):
40.     '''Return the rank distance of the matrices constructed from x and y
41.     '''
42.     return -1
43.
44. def mCp6(L):
45.     '''Check whether L satisfies the axiom of neighborliness w.r.t the Hamming distance
46.     '''
47.     if(len(L) == 1):
48.         return True
49.     for i in xrange(0, len(L)):
50.         foundit = False
51.         for j in xrange(0, len(L)):
52.             if(i == j and L[i][1] != L[j][1]):
53.                 continue
54.                 if 1 >= mCp3(L[i][0], L[j][0]):
55.                     foundit = True
57.             return False
58.     return True
59.
60. def mCp7(L, J):
61.     '''Use the labeled points in L to label the points in J using the nearest neighbor in the Hamming distance
62.     '''
63.     values = []
64.     for i in xrange(0, len(J)):
65.         minLength = 100
66.         val = 100
67.         for j in xrange(0, len(L)):
68.             temp = mCp3(L[j][0], J[i])
69.             if(temp <= minLength):
70.                 if minLength == temp:
71.                     if L[j][1] < val:
72.                         val = L[j][1]
73.                 else:
74.                     minLength = temp
75.                     val = L[j][1]
76.         tempo = (J[i], val)
77.         values.append(tempo)
78.     return values
79.
80. def mCp8(L, J, k):
81.     '''Use the labeled points in L to label the points in J using the k nearest neighbors in the Hamming distance
82.     '''
83.     values = []
84.     for i in xrange(0, len(J)):
85.         valuesFori = []
86.         for j in xrange(0, len(L)):
87.             valuesFori.append([(L[j][1]), mCp3(L[j][0], J[i])])
88.         if(len(L) < k):
89.             k = len(L)
90.         counts = {}
91.         for j in xrange(0, k):
92.             if valuesFori[j][0] in counts:
93.                 counts[valuesFori[j][0]] += 1
94.             else:
95.                 counts[valuesFori[j][0]] = 1
96.         print(max(counts))
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