#TODO: docstring

def clusterMetrics(timeValues, massValues, massScalingFactor=1):
    """ #TODO: docstring
    """
    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