Mercurial > hg > nsaunier > traffic-intelligence

comparison scripts/classify-objects.py @ 682:fbe29be25501 dev

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corrected bug
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Fri, 05 Jun 2015 02:35:29 +0200
parents da1352b89d02
children f3a0b652b590
comparison
equal deleted inserted replaced
681:acce61a1edc8 682:fbe29be25501
44 # log logistic for ped and bik otherwise ((pedBeta/pedAlfa)*((sMean/pedAlfa)**(pedBeta-1)))/((1+(sMean/pedAlfa)**pedBeta)**2.) 44 # log logistic for ped and bik otherwise ((pedBeta/pedAlfa)*((sMean/pedAlfa)**(pedBeta-1)))/((1+(sMean/pedAlfa)**pedBeta)**2.)
45 speedProbabilities = {'car': lambda s: norm(params.meanVehicleSpeed, params.stdVehicleSpeed).pdf(s), 45 speedProbabilities = {'car': lambda s: norm(params.meanVehicleSpeed, params.stdVehicleSpeed).pdf(s),
46 'pedestrian': lambda s: norm(params.meanPedestrianSpeed, params.stdPedestrianSpeed).pdf(s), 46 'pedestrian': lambda s: norm(params.meanPedestrianSpeed, params.stdPedestrianSpeed).pdf(s),
47 'bicycle': lambda s: lognorm(params.scaleCyclistSpeed, loc = 0., scale = np.exp(params.locationCyclistSpeed)).pdf(s)} # lognorm shape, loc, scale 47 'bicycle': lambda s: lognorm(params.scaleCyclistSpeed, loc = 0., scale = np.exp(params.locationCyclistSpeed)).pdf(s)} # lognorm shape, loc, scale
48 48
49 def plotSpeedProbabilities():
50 for k in speedProbabilities:
51 plot(arange(0.1, 50, 0.1), [speedProbabilities[k](s/3.6/25) for s in arange(0.1, 50, 0.1)])
52
49 objects = storage.loadTrajectoriesFromSqlite(params.databaseFilename, 'object') 53 objects = storage.loadTrajectoriesFromSqlite(params.databaseFilename, 'object')
50 features = storage.loadTrajectoriesFromSqlite(params.databaseFilename, 'feature') 54 features = storage.loadTrajectoriesFromSqlite(params.databaseFilename, 'feature')
51 intervals = [] 55 intervals = []
52 for obj in objects: 56 for obj in objects:
53 obj.setFeatures(features) 57 obj.setFeatures(features)