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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def learnObjects(self, objectPlacements):
 """ Learn each provided object in egocentric space. Touch every location on each object. This method doesn't try move the sensor along a path. Instead it just leaps the sensor to each object location, resetting the location layer with each leap. This method simultaneously learns 4 sets of synapses: - location -> input - input -> location - input -> object - object -> input """

    for monitor in self.monitors.values():
      monitor.afterPlaceObjects(objectPlacements)

    for objectName, objectDict in self.objects.iteritems():
      self.reset()

      objectPlacement = objectPlacements[objectName]

      for locationName, featureName in objectDict.iteritems():
        egocentricLocation = (locationName[0] + objectPlacement[0],
                              locationName[1] + objectPlacement[1])

        locationSDR = self.locations[egocentricLocation]
        featureSDR = self.features[featureName]
        transitionSDR = np.empty(0)

        self.locationLayer.reset()
        self.inputLayer.reset()

        for _ in xrange(10):
          self.doTimestep(locationSDR, transitionSDR, featureSDR,
                          egocentricLocation, learn=True)

        self.inputRepresentations[(featureName, egocentricLocation)] = (
          self.inputLayer.getActiveCells())

      self.objectRepresentations[objectName] = self.objectLayer.getActiveCells()
      self.learnedObjectPlacements[objectName] = objectPlacement