Mercurial > hg > nsaunier > traffic-intelligence

comparison python/events.py @ 746:e7ff0f60fef8

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merged new developments (indicator and trajectory clustering)
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Thu, 10 Sep 2015 15:52:45 -0400
parents 0e875a7f5759
children 8ba82b371eea
comparison
equal deleted inserted replaced
727:c6d4ea05a2d0 746:e7ff0f60fef8
1 #! /usr/bin/env python 1 #! /usr/bin/env python
2 '''Libraries for events 2 '''Libraries for events
3 Interactions, pedestrian crossing...''' 3 Interactions, pedestrian crossing...'''
4 4
5 import moving, prediction, indicators, utils, cvutils 5 import moving, prediction, indicators, utils, cvutils, ml
6 from base import VideoFilenameAddable 6 from base import VideoFilenameAddable
7 7
8 import numpy as np 8 import numpy as np
9 9
10 import multiprocessing 10 import multiprocessing
293 allPoints += points 293 allPoints += points
294 else: 294 else:
295 print('unknown type of point: '+pointType) 295 print('unknown type of point: '+pointType)
296 return allPoints 296 return allPoints
297 297
298 def prototypeCluster(interactions, similarityMatrix, alignmentMatrix, indicatorName, minSimilarity): 298 def prototypeCluster(interactions, similarities, indicatorName, minSimilarity, similarityFunc = None, minClusterSize = None, randomInitialization = False):
299 '''Finds exemplar indicator time series for all interactions 299 return ml.prototypeCluster([inter.getIndicator(indicatorName) for inter in interactions], similarities, minSimilarity, similarityFunc, minClusterSize, randomInitialization)
300 Returns the prototype indices (in the interaction list) and the label of each indicator (interaction)
301
302 if an indicator profile (time series) is different enough (<minSimilarity),
303 it will become a new prototype.
304 Non-prototype interactions will be assigned to an existing prototype'''
305
306 # sort indicators based on length
307 indices = range(similarityMatrix.shape[0])
308 def compare(i, j):
309 if len(interactions[i].getIndicator(indicatorName)) > len(interactions[j].getIndicator(indicatorName)):
310 return -1
311 elif len(interactions[i].getIndicator(indicatorName)) == len(interactions[j].getIndicator(indicatorName)):
312 return 0
313 else:
314 return 1
315 indices.sort(compare)
316 # go through all indicators
317 prototypeIndices = [indices[0]]
318 for i in indices[1:]:
319 if similarityMatrix[i][prototypeIndices].max() < minSimilarity:
320 prototypeIndices.append(i)
321
322 # assignment
323 labels = [-1]*similarityMatrix.shape[0]
324 indices = [i for i in range(similarityMatrix.shape[0]) if i not in prototypeIndices]
325 for i in prototypeIndices:
326 labels[i] = i
327 for i in indices:
328 prototypeIndex = similarityMatrix[i][prototypeIndices].argmax()
329 labels[i] = prototypeIndices[prototypeIndex]
330
331 return prototypeIndices, labels
332
333 def prototypeMultivariateCluster(interactions, similarityMatrics, indicatorNames, minSimilarities, minClusterSize):
334 '''Finds exmaple indicator time series (several indicators) for all interactions
335
336 if any interaction indicator time series is different enough (<minSimilarity),
337 it will become a new prototype.
338 Non-prototype interactions will be assigned to an existing prototype if all indicators are similar enough'''
339 pass
340
341 300
342 class Crossing(moving.STObject): 301 class Crossing(moving.STObject):
343 '''Class for the event of a street crossing 302 '''Class for the event of a street crossing
344 303
345 TODO: detecter passage sur la chaussee 304 TODO: detecter passage sur la chaussee