Mercurial Hosting > traffic-intelligence
comparison python/tests/utils.txt @ 997:4f3387a242a1
updated utils to python 3
author | Nicolas Saunier <nicolas.saunier@polymtl.ca> |
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date | Fri, 25 May 2018 18:15:18 -0400 |
parents | 8e8ec4ece66e |
children |
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996:add667153087 | 997:4f3387a242a1 |
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9 >>> upperCaseFirstLetter(s) == s | 9 >>> upperCaseFirstLetter(s) == s |
10 True | 10 True |
11 | 11 |
12 >>> computeChi2([],[]) | 12 >>> computeChi2([],[]) |
13 0 | 13 0 |
14 >>> computeChi2(range(1,10),range(1,10)) | 14 >>> computeChi2(list(range(1,10)),list(range(1,10))) |
15 0.0 | 15 0.0 |
16 >>> computeChi2(range(1,9),range(1,10)) | 16 >>> computeChi2(list(range(1,9)),list(range(1,10))) |
17 0.0 | 17 0.0 |
18 | 18 |
19 >>> ceilDecimals(1.23, 0) | 19 >>> ceilDecimals(1.23, 0) |
20 2.0 | 20 2.0 |
21 >>> ceilDecimals(1.23, 1) | 21 >>> ceilDecimals(1.23, 1) |
51 | 51 |
52 >>> mostCommon(['a','b','c','b']) | 52 >>> mostCommon(['a','b','c','b']) |
53 'b' | 53 'b' |
54 >>> mostCommon(['a','b','c','b', 'c']) | 54 >>> mostCommon(['a','b','c','b', 'c']) |
55 'b' | 55 'b' |
56 >>> mostCommon(range(10)+[1]) | 56 >>> mostCommon(list(range(10))+[1]) |
57 1 | 57 1 |
58 >>> mostCommon([range(2), range(4), range(2)]) | 58 >>> mostCommon([list(range(2)), list(range(4)), list(range(2))]) |
59 [0, 1] | 59 [0, 1] |
60 | 60 |
61 >>> res = sortByLength([range(3), range(4), range(1)]) | 61 >>> res = sortByLength([list(range(3)), list(range(4)), list(range(1))]) |
62 >>> [len(r) for r in res] | 62 >>> [len(r) for r in res] |
63 [1, 3, 4] | 63 [1, 3, 4] |
64 >>> res = sortByLength([range(3), range(4), range(1), range(5)], reverse = True) | 64 >>> res = sortByLength([list(range(3)), list(range(4)), list(range(1)), list(range(5))], reverse = True) |
65 >>> [len(r) for r in res] | 65 >>> [len(r) for r in res] |
66 [5, 4, 3, 1] | 66 [5, 4, 3, 1] |
67 | 67 |
68 >>> lcss = LCSS(similarityFunc = lambda x,y: abs(x-y) <= 0.1) | 68 >>> lcss = LCSS(similarityFunc = lambda x,y: abs(x-y) <= 0.1) |
69 >>> lcss.compute(range(5), range(5)) | 69 >>> lcss.compute(list(range(5)), list(range(5))) |
70 5 | 70 5 |
71 >>> lcss.compute(range(1,5), range(5)) | 71 >>> lcss.compute(list(range(1,5)), list(range(5))) |
72 4 | 72 4 |
73 >>> lcss.compute(range(5,10), range(5)) | 73 >>> lcss.compute(list(range(5,10)), list(range(5))) |
74 0 | 74 0 |
75 >>> lcss.compute(range(5), range(10)) | 75 >>> lcss.compute(list(range(5)), list(range(10))) |
76 5 | 76 5 |
77 >>> lcss.similarityFunc = lambda x,y: x == y | 77 >>> lcss.similarityFunc = lambda x,y: x == y |
78 >>> lcss.compute(['a','b','c'], ['a','b','c', 'd']) | 78 >>> lcss.compute(['a','b','c'], ['a','b','c', 'd']) |
79 3 | 79 3 |
80 >>> lcss.computeNormalized(['a','b','c'], ['a','b','c', 'd']) #doctest: +ELLIPSIS | 80 >>> lcss.computeNormalized(['a','b','c'], ['a','b','c', 'd']) #doctest: +ELLIPSIS |
104 3 | 104 3 |
105 >>> lcss.subSequenceIndices | 105 >>> lcss.subSequenceIndices |
106 [(0, 0), (2, 1), (3, 2)] | 106 [(0, 0), (2, 1), (3, 2)] |
107 | 107 |
108 >>> alignedLcss = LCSS(lambda x,y:(abs(x-y) <= 0.1), delta = 2, aligned = True) | 108 >>> alignedLcss = LCSS(lambda x,y:(abs(x-y) <= 0.1), delta = 2, aligned = True) |
109 >>> alignedLcss.compute(range(5), range(5)) | 109 >>> alignedLcss.compute(list(range(5)), list(range(5))) |
110 5 | 110 5 |
111 >>> alignedLcss.compute(range(1,5), range(5)) | 111 >>> alignedLcss.compute(list(range(1,5)), list(range(5))) |
112 4 | 112 4 |
113 | 113 |
114 >>> alignedLcss.compute(range(5,10), range(10)) | 114 >>> alignedLcss.compute(list(range(5,10)), list(range(10))) |
115 5 | 115 5 |
116 | 116 |
117 >>> lcss.delta = 2 | 117 >>> lcss.delta = 2 |
118 >>> lcss.compute(range(5,10), range(10)) | 118 >>> lcss.compute(list(range(5,10)), list(range(10))) |
119 0 | 119 0 |
120 >>> alignedLcss.delta = 6 | 120 >>> alignedLcss.delta = 6 |
121 >>> alignedLcss.compute(range(5), range(5)) | 121 >>> alignedLcss.compute(list(range(5)), list(range(5))) |
122 5 | 122 5 |
123 >>> alignedLcss.compute(range(5), range(6)) | 123 >>> alignedLcss.compute(list(range(5)), list(range(6))) |
124 5 | 124 5 |
125 >>> lcss.delta = 10 | 125 >>> lcss.delta = 10 |
126 >>> alignedLcss.compute(range(1,7), range(6)) | 126 >>> alignedLcss.compute(list(range(1,7)), list(range(6))) |
127 5 | 127 5 |
128 >>> lcss = LCSS(lambda x,y: x == y, delta = 2, aligned = True) | 128 >>> lcss = LCSS(lambda x,y: x == y, delta = 2, aligned = True) |
129 >>> lcss.compute(range(20), [2,4,6,7,8,9,11,13], True) | 129 >>> lcss.compute(list(range(20)), [2,4,6,7,8,9,11,13], True) |
130 8 | 130 8 |
131 >>> lcss.subSequenceIndices | 131 >>> lcss.subSequenceIndices |
132 [(2, 0), (4, 1), (6, 2), (7, 3), (8, 4), (9, 5), (11, 6), (13, 7)] | 132 [(2, 0), (4, 1), (6, 2), (7, 3), (8, 4), (9, 5), (11, 6), (13, 7)] |
133 | 133 |
134 >>> lcss = LCSS(metric = 'cityblock', epsilon = 0.1) | 134 >>> lcss = LCSS(metric = 'cityblock', epsilon = 0.1) |
139 >>> lcss.compute([[i] for i in range(5,10)], [[i] for i in range(5)]) | 139 >>> lcss.compute([[i] for i in range(5,10)], [[i] for i in range(5)]) |
140 0 | 140 0 |
141 >>> lcss.compute([[i] for i in range(5)], [[i] for i in range(10)]) | 141 >>> lcss.compute([[i] for i in range(5)], [[i] for i in range(10)]) |
142 5 | 142 5 |
143 | 143 |
144 |