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我想关联 2 个这样的列表:

a=[1337687805.49052, 1337687808.560519, 1337687813.06552, 1337687814.602522,
   1337687817.16352, 1337687823.836521, 1337687831.942522, 1337687837.931519, 
   1337687839.760519, 1337694258.54652, 1337709019.39452, 1337712024.05452, 
   1337714200.05952, 1337714903.08152, 1337721205.97952, 1337721207.05052, 
   1337723273.93052]

b=[1337687803.533521, 1337688287.44452, 1337689866.760521, 1337689866.76352,
   1337690758.328521, 1337691231.61552, 1337691261.578519, 1337691261.68752,
   1337691362.20652, 1337691362.51652, 1337691366.431521, 1337691369.55252,
   1337691369.992521, 1337691387.000521, 1337691391.50552, 1337691406.192519, 
   1337691407.79952, 1337691411.74352, 1337691420.308521, 1337691422.035521, 
   1337691426.60752, 1337691426.753521, 1337691431.44952, 1337691437.87152, 
   1337691438.66452, 1337691448.45452, 1337691450.15852, 1337691451.49252, 
   1337691454.335519, 1337691459.87152, 1337691461.01652, 1337691480.819519, 
   1337691482.980521, 1337691484.914522, 1337691500.15652, 1337691514.32752]

a 和 b 包含一些事件的纪元时间,所以我需要 a 和 b 之间的相关性,做一些有意义的图表,也许相关系数也很有用。目标是比较许多具有不同时间戳的向量 a,b,c,d,...,以了解它们是否具有相似的行为。

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1 回答 1

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我觉得你应该考虑scipy.spatial.distance

您可以使用scipy.spatial.distance.euclidean()或获得相关性scipy.spatial.distance.correlation()

http://docs.scipy.org/doc/scipy/reference/search.html?q=correlation&check_keywords=yes&area=default

于 2012-06-20T16:19:58.897 回答