nsaunier/traffic-intelligence: python/moving.py comparison

comparison python/moving.py @ 1012:01db14e947e4

resolved

author	Wendlasida
date	Fri, 01 Jun 2018 10:47:49 -0400
parents	4f0312bee393 cc7c6b821ae6
children	d6f121ded971

comparison

equal deleted inserted replaced

-:4f0312bee393
+:01db14e947e4
 def __iter__(self):
 self.iterInstantNum = -1
 return self
-def next(self):
+def __next__(self):
 if self.iterInstantNum >= self.length()-1:
 raise StopIteration
 else:
 self.iterInstantNum += 1
 return self[self.iterInstantNum]
 def getFirstInstant(self):
 return self.timeInterval.first
 def getLastInstant(self):
 return self.timeInterval.last
+def setFirstInstant(self, t):
+if t <= self.timeInterval.last:
+self.timeInterval.first = t
+else:
+print('new first instant is after last, not changing')
+def setLastInstant(self, t):
+if t >= self.timeInterval.first:
+self.timeInterval.last = t
+else:
+print('new last instant is before first, not changing')
 def getTimeInterval(self):
 return self.timeInterval
 def existsAtInstant(self, t):
 '''Optimized tests of a series of points within (Shapely) polygon (not prepared)'''
 if type(polygon) == PreparedGeometry:
 prepared_polygon = polygon
 else:
 prepared_polygon = prep(polygon)
-return filter(prepared_polygon.contains, points)
+return list(filter(prepared_polygon.contains, points))
 # Functions for coordinate transformation
 # From Paul St-Aubin's PVA tools
 def subsec_spline_dist(splines):
 ''' Prepare list of spline subsegments from a spline list.
 def prepareSplines(splines):
 'Approximates slope singularity by giving some slope roundoff; account for roundoff error'
 for spline in splines:
 p1 = spline[0]
-for i in xrange(len(spline)-1):
+for i in range(len(spline)-1):
 p2 = spline[i+1]
 if(round(p1.x, 10) == round(p2.x, 10)):
 p2.x += 0.0000000001
 if(round(p1.y, 10) == round(p2.y, 10)):
 p2.y += 0.0000000001
 @staticmethod
 def generate(p, v, nPoints):
 t = Trajectory()
 p0 = Point(p.x, p.y)
 t.addPosition(p0)
-for i in xrange(nPoints-1):
+for i in range(nPoints-1):
 p0 += v
 t.addPosition(p0)
 return t, Trajectory([[v.x]*nPoints, [v.y]*nPoints])
 @staticmethod
 return Trajectory([self.positions[0][i],self.positions[1][i]])
 else:
 raise TypeError("Invalid argument type.")
 def __str__(self):
-return ' '.join([self.__getitem__(i).__str__() for i in xrange(self.length())])
+return ' '.join([self.__getitem__(i).__str__() for i in range(self.length())])
 def __repr__(self):
 return self.__str__()
 def __iter__(self):
 self.iterInstantNum = 0
 return self
-def next(self):
+def __next__(self):
 if self.iterInstantNum >= self.length():
 raise StopIteration
 else:
 self.iterInstantNum += 1
 return self[self.iterInstantNum-1]
 return Trajectory([[alpha*x for x in self.getXCoordinates()],
 [alpha*y for y in self.getYCoordinates()]])
 def differentiate(self, doubleLastPosition = False):
 diff = Trajectory()
-for i in xrange(1, self.length()):
+for i in range(1, self.length()):
 diff.addPosition(self[i]-self[i-1])
 if doubleLastPosition:
 diff.addPosition(diff[-1])
 return diff
 Can be accessed through getDistance(idx) and getCumulativeDistance(idx)'''
 self.distances = []
 self.cumulativeDistances = [0.]
 p1 = self[0]
 cumulativeDistance = 0.
-for i in xrange(self.length()-1):
+for i in range(self.length()-1):
 p2 = self[i+1]
 self.distances.append(Point.distanceNorm2(p1,p2))
 cumulativeDistance += self.distances[-1]
 self.cumulativeDistances.append(cumulativeDistance)
 p1 = p2
 intersects with the segment of extremities p1 and p2
 Returns an empty list if there is no crossing'''
 indices = []
 intersections = []
-for i in xrange(self.length()-1):
+for i in range(self.length()-1):
 q1=self.__getitem__(i)
 q2=self.__getitem__(i+1)
 p = segmentIntersection(q1, q2, p1, p2)
 if p is not None:
 if q1.x != q2.x:
 intersects with the line going through p1 and p2
 Returns an empty list if there is no crossing'''
 indices = []
 intersections = []
-for i in xrange(self.length()-1):
+for i in range(self.length()-1):
 q1=self.__getitem__(i)
 q2=self.__getitem__(i+1)
 p = segmentLineIntersection(p1, p2, q1, q2)
 if p is not None:
 if q1.x != q2.x:
 self.lanes[i] = lane
 def differentiate(self, doubleLastPosition = False):
 diff = CurvilinearTrajectory()
 p1 = self[0]
-for i in xrange(1, self.length()):
+for i in range(1, self.length()):
 p2 = self[i]
 diff.addPositionSYL(p2[0]-p1[0], p2[1]-p1[1], p1[2])
 p1=p2
 if doubleLastPosition and self.length() > 1:
 diff.addPosition(diff[-1])
 '''Returns a list of the indices at which the trajectory
 goes past the curvilinear coordinate S1
 (in provided lane if lane is not None)
 Returns an empty list if there is no crossing'''
 indices = []
-for i in xrange(self.length()-1):
+for i in range(self.length()-1):
 q1=self.__getitem__(i)
 q2=self.__getitem__(i+1)
 if q1[0] <= S1 < q2[0] and (lane is None or (self.lanes[i] == lane and self.lanes[i+1] == lane)):
 indices.append(i+(S1-q1[0])/(q2[0]-q1[0]))
 return indices
 self.positions = positions
 @staticmethod
 def concatenate(obj1, obj2, num = None):
 '''Concatenates two objects supposed to overlap temporally '''
-	if num is None:
+if num is None:
-		newNum = obj1.getNum()
+newNum = obj1.getNum()
-	else:
+else:
-		newNum = num
+newNum = num
 commonTimeInterval = obj1.commonTimeInterval(obj2)
 if commonTimeInterval.empty():
 print('The two objects\' time intervals do not overlap: obj1 {} and obj2 {}'.format(obj1.getTimeInterval(), obj2.getTimeInterval()))
 emptyInterval = TimeInterval(min(obj1.getLastInstant(),obj2.getLastInstant()) , max(obj1.getFirstInstant(),obj2.getFirstInstant()))
 positions = Trajectory()
 	py+=vitessey
 	    newObject = MovingObject(newNum, emptyInterval, positions, velocities, userType = obj1.getUserType())
 	    newObject.features = [MovingObject(newNum, emptyInterval, positions, velocities, userType = obj1.getUserType())] #In case there is features to add when we recursively call concatenate
 return MovingObject.concatenate(MovingObject.concatenate(obj1, newObject),obj2)
 else:
 newTimeInterval = TimeInterval.union(obj1.getTimeInterval(), obj2.getTimeInterval())
 # positions
 positions = Trajectory()
 for t in newTimeInterval:
 coords.append(NaN)
 plot(instants, coords, options, **kwargs)
 if withOrigin and len(instants)>0:
 plot([instants[0]], [coords[0]], 'ro', **kwargs)
 else:
 print('Object {} has no curvilinear positions'.format(self.getNum()))
 def setUserType(self, userType):
 self.userType = userType
 def setFeatures(self, features, featuresOrdered = False):
 def play(self, videoFilename, homography = None, undistort = False, intrinsicCameraMatrix = None, distortionCoefficients = None, undistortedImageMultiplication = 1.):
 cvutils.displayTrajectories(videoFilename, [self], homography = homography, firstFrameNum = self.getFirstInstant(), lastFrameNumArg = self.getLastInstant(), undistort = undistort, intrinsicCameraMatrix = intrinsicCameraMatrix, distortionCoefficients = distortionCoefficients, undistortedImageMultiplication = undistortedImageMultiplication)
 def speedDiagnostics(self, framerate = 1., display = False, nInstantsIgnoredAtEnds=0):
 speeds = framerate*self.getSpeeds(nInstantsIgnoredAtEnds)
-coef = utils.linearRegression(range(len(speeds)), speeds)
+coef = utils.linearRegression(list(range(len(speeds))), speeds)
 print('min/5th perc speed: {} / {}\nspeed diff: {}\nspeed stdev: {}\nregression: {}'.format(min(speeds), scoreatpercentile(speeds, 5), speeds[-2]-speeds[1], std(speeds), coef[0]))
 if display:
 from matplotlib.pyplot import figure, axis
 figure(1)
 self.plot()
 '''
 self.curvilinearPositions = CurvilinearTrajectory()
 #For each point
-for i in xrange(int(self.length())):
+for i in range(int(self.length())):
 result = getSYfromXY(self.getPositionAt(i), alignments)
 # Error handling
 if(result is None):
 print('Warning: trajectory {} at point {} {} has alignment errors (spline snapping)\nCurvilinear trajectory could not be computed'.format(self.getNum(), i, self.getPositionAt(i)))
 #Run through objects looking for outlier point
 smoothed_lanes = utils.cat_mvgavg(self.curvilinearPositions.getLanes(),ln_mv_av_win)
 ## Recalculate projected point to new lane
 lanes = self.curvilinearPositions.getLanes()
 if(lanes != smoothed_lanes):
-for i in xrange(len(lanes)):
+for i in range(len(lanes)):
 if(lanes[i] != smoothed_lanes[i]):
 result = getSYfromXY(self.getPositionAt(i),[alignments[smoothed_lanes[i]]])
 # Error handling
 if(result is None):
 if nFeatures == 0:
 print('Empty object features\nCannot compute smooth trajectory')
 else:
 # compute the relative position vectors
 relativePositions = {} # relativePositions[(i,j)] is the position of j relative to i
-for i in xrange(nFeatures):
+for i in range(nFeatures):
-for j in xrange(i):
+for j in range(i):
 fi = self.features[i]
 fj = self.features[j]
 inter = fi.commonTimeInterval(fj)
 if inter.length() >= minCommonIntervalLength:
 xi = array(fi.getXCoordinates()[inter.first-fi.getFirstInstant():int(fi.length())-(fi.getLastInstant()-inter.last)])
 gtMatches = {a.getNum():{} for a in annotations}
 toMatches = {o.getNum():{} for o in objects}
 else:
 gtMatches = None
 toMatches = None
-for t in xrange(firstInstant, lastInstant+1):
+for t in range(firstInstant, lastInstant+1):
 previousMatches = matches.copy()
 # go through currently matched GT-TO and check if they are still matched withing matchingDistance
 toDelete = []
 for a in matches:
 if a.existsAtInstant(t) and matches[a].existsAtInstant(t):
 toDelete.append(a)
 for a in toDelete:
 del matches[a]
 # match all unmatched GT-TO
-matchedGTs = matches.keys()
+matchedGTs = list(matches.keys())
-matchedTOs = matches.values()
+matchedTOs = list(matches.values())
 costs = []
 unmatchedGTs = [a for a in annotations if a.existsAtInstant(t) and a not in matchedGTs]
 unmatchedTOs = [o for o in objects if o.existsAtInstant(t) and o not in matchedTOs]
 nGTs = len(matchedGTs)+len(unmatchedGTs)
 nTOs = len(matchedTOs)+len(unmatchedTOs)
 for k,v in newMatches:
 if costs[k][v] < matchingDistance:
 matches[unmatchedGTs[k]]=unmatchedTOs[v]
 dist += costs[k][v]
 if debug:
-print('{} '.format(t)+', '.join(['{} {}'.format(k.getNum(), v.getNum()) for k,v in matches.iteritems()]))
+print('{} '.format(t)+', '.join(['{} {}'.format(k.getNum(), v.getNum()) for k,v in matches.items()]))
 if returnMatches:
-for a,o in matches.iteritems():
+for a,o in matches.items():
 gtMatches[a.getNum()][t] = o.getNum()
 toMatches[o.getNum()][t] = a.getNum()
 # compute metrics elements
 ct += len(matches)
 mismatches = []
 for a in matches:
 if a in previousMatches:
 if matches[a] != previousMatches[a]:
 mismatches.append(a)
-elif matches[a] in previousMatches.values():
+elif matches[a] in list(previousMatches.values()):
 mismatches.append(matches[a])
 for a in previousMatches:
-if a not in matches and previousMatches[a] in matches.values():
+if a not in matches and previousMatches[a] in list(matches.values()):
 mismatches.append(previousMatches[a])
 if debug:
 for mm in set(mismatches):
 print('{} {}'.format(type(mm), mm.getNum()))
 # some object mismatches may appear twice

Mercurial > hg > nsaunier > traffic-intelligence

comparison python/moving.py @ 1012:01db14e947e4