code: def clusterMetrics(timeValues, massValues, massScalingFactor=1):
      
      metrics = dict()
      metrics['meanTime'] = numpy.mean(timeValues)
      metrics['meanMass'] = numpy.mean(massValues)
      metrics['devTime'] = timeValues - metrics['meanTime']
      metrics['devMass'] = massValues - metrics['meanMass']
      #metrics['devMass'] = (1-metrics['meanMass']/massValues)
      metrics['spreadTime'] = numpy.max(timeValues) - numpy.min(timeValues)
      metrics['spreadMass'] = numpy.max(massValues) - numpy.min(massValues)
      #metrics['spreadMass'] = (1-numpy.min(massValues) / numpy.max(massValues))
      metrics['devEuc'] = numpy.sqrt(numpy.power(metrics['devTime'], 2) +
                                     numpy.power(metrics['devMass']*massScalingFactor, 2)
                                     )
      metrics['meanEuc'] = numpy.mean(metrics['devEuc'])
      metrics['devTime'] = metrics['devTime'].tolist()
      metrics['devMass'] = metrics['devMass'].tolist()
      metrics['devEuc'] = metrics['devEuc'].tolist()
      return metrics
docs: #TODO: docstring