Mercurial > hg > nsaunier > traffic-intelligence
comparison python/utils.py @ 574:e24eeb244698
first implementation of projection to curvilinear coordinates
| author | Nicolas Saunier <nicolas.saunier@polymtl.ca> |
|---|---|
| date | Wed, 13 Aug 2014 00:00:08 -0400 |
| parents | 0057c04f94d5 |
| children | c5406edbcf12 84690dfe5560 |
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| 573:cae4e5f3fe9f | 574:e24eeb244698 |
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| 248 ''' Compute point-to-point distance (L2 norm, ie Euclidean distance)''' | 248 ''' Compute point-to-point distance (L2 norm, ie Euclidean distance)''' |
| 249 return sqrt((x2-x1)**2+(y2-y1)**2) | 249 return sqrt((x2-x1)**2+(y2-y1)**2) |
| 250 | 250 |
| 251 def crossProduct(l1, l2): | 251 def crossProduct(l1, l2): |
| 252 return l1[0]*l2[1]-l1[1]*l2[0] | 252 return l1[0]*l2[1]-l1[1]*l2[0] |
| 253 | |
| 254 def cat_mvgavg(cat_list, halfWidth): | |
| 255 ''' Return a list of categories/values smoothed according to a window. | |
| 256 halfWidth is the search radius on either side''' | |
| 257 from copy import deepcopy | |
| 258 catgories = deepcopy(cat_list) | |
| 259 smoothed = catgories | |
| 260 for point in range(len(catgories)): | |
| 261 lower_bound_check = max(0,point-halfWidth) | |
| 262 upper_bound_check = min(len(catgories)-1,point+halfWidth+1) | |
| 263 window_values = catgories[lower_bound_check:upper_bound_check] | |
| 264 smoothed[point] = max(set(window_values), key=window_values.count) | |
| 265 return smoothed | |
| 253 | 266 |
| 254 def filterMovingWindow(inputSignal, halfWidth): | 267 def filterMovingWindow(inputSignal, halfWidth): |
| 255 '''Returns an array obtained after the smoothing of the input by a moving average | 268 '''Returns an array obtained after the smoothing of the input by a moving average |
| 256 The first and last points are copied from the original.''' | 269 The first and last points are copied from the original.''' |
| 257 from numpy import ones,convolve,array | 270 from numpy import ones,convolve,array |