Mercurial > hg > nsaunier > traffic-intelligence
comparison python/utils.py @ 284:f2cf16ad798f
added LCSS for trajectories
| author | Nicolas Saunier <nicolas.saunier@polymtl.ca> |
|---|---|
| date | Fri, 21 Dec 2012 18:33:36 -0500 |
| parents | abbd4bc13dac |
| children | 5957aa1d69e1 8e66ced156dd |
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| 283:dbe7e53334d7 | 284:f2cf16ad798f |
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| 164 ######################### | 164 ######################### |
| 165 # maths section | 165 # maths section |
| 166 ######################### | 166 ######################### |
| 167 | 167 |
| 168 def LCSS(l1, l2, threshold, distance): | 168 def LCSS(l1, l2, threshold, distance): |
| 169 """returns the longest common subsequence similarity | 169 '''returns the longest common subsequence similarity |
| 170 based on the threshold on distance between two elements of lists l1, l2""" | 170 based on the threshold on distance between two elements of lists l1, l2''' |
| 171 from numpy import zeros | 171 from numpy import zeros, int as npint |
| 172 m = len(l1) | 172 m = len(l1) |
| 173 n = len(l2) | 173 n = len(l2) |
| 174 similarity = zeros((m+1,n+1)) | 174 similarity = zeros((m+1,n+1), dtype = npint) |
| 175 for i in xrange(1,m+1): | 175 for i in xrange(1,m+1): |
| 176 for j in xrange(1,n+1): | 176 for j in xrange(1,n+1): |
| 177 if distance(l1[i-1], l2[j-1])<threshold: | 177 if distance(l1[i-1], l2[j-1])<threshold: |
| 178 similarity[i][j] = similarity[i-1][j-1]+1 | 178 similarity[i][j] = similarity[i-1][j-1]+1 |
| 179 else: | 179 else: |