def getStats(self, stats):
    """ Override of getStats()  in BaseStatsCollector

        stats: A dictionary where all the stats are
        outputted

    """
    BaseStatsCollector.getStats(self, stats)

    sortedNumberList = sorted(self.valueList)
    listLength = len(sortedNumberList)
    min = sortedNumberList[0]
    max = sortedNumberList[-1]
    mean = numpy.mean(self.valueList)
    median = sortedNumberList[int(0.5*listLength)]
    percentile1st = sortedNumberList[int(0.01*listLength)]
    percentile99th = sortedNumberList[int(0.99*listLength)]

    differenceList = \
               [(cur - prev) for prev, cur in itertools.izip(list(self.valueSet)[:-1],
                                                             list(self.valueSet)[1:])]
    if min > max:
      print self.fieldname, min, max, '-----'
    meanResolution = numpy.mean(differenceList)


    stats[self.fieldname]['min'] = min
    stats[self.fieldname]['max'] = max
    stats[self.fieldname]['mean'] = mean
    stats[self.fieldname]['median'] = median
    stats[self.fieldname]['percentile1st'] = percentile1st
    stats[self.fieldname]['percentile99th'] = percentile99th
    stats[self.fieldname]['meanResolution'] = meanResolution

    # TODO: Right now, always pass the data along.
    # This is used for data-dependent encoders.
    passData = True
    if passData:
      stats[self.fieldname]['data'] = self.valueList

    if VERBOSITY > 2:
      print '--'
      print "Statistics:"
      print "min:", min
      print "max:", max
      print "mean:", mean
      print "median:", median
      print "1st percentile :", percentile1st
      print "99th percentile:", percentile99th

      print '--'
      print "Resolution:"
      print "Mean Resolution:", meanResolution

    if VERBOSITY > 3:
      print '--'
      print "Histogram:"
      counts, bins = numpy.histogram(self.valueList, new=True)
      print "Counts:", counts.tolist()
      print "Bins:", bins.tolist()
def getStats(self, stats):
    """ Override of getStats()  in BaseStatsCollector

        stats: A dictionary where all the stats are
        outputted

    """
    BaseStatsCollector.getStats(self, stats)

    sortedNumberList = sorted(self.valueList)
    listLength = len(sortedNumberList)
    min = sortedNumberList[0]
    max = sortedNumberList[-1]
    mean = numpy.mean(self.valueList)
    median = sortedNumberList[int(0.5*listLength)]
    percentile1st = sortedNumberList[int(0.01*listLength)]
    percentile99th = sortedNumberList[int(0.99*listLength)]

    differenceList = \
               [(cur - prev) for prev, cur in itertools.izip(list(self.valueSet)[:-1],
                                                             list(self.valueSet)[1:])]
    if min > max:
      print self.fieldname, min, max, '-----'
    meanResolution = numpy.mean(differenceList)


    stats[self.fieldname]['min'] = min
    stats[self.fieldname]['max'] = max
    stats[self.fieldname]['mean'] = mean
    stats[self.fieldname]['median'] = median
    stats[self.fieldname]['percentile1st'] = percentile1st
    stats[self.fieldname]['percentile99th'] = percentile99th
    stats[self.fieldname]['meanResolution'] = meanResolution

    # TODO: Right now, always pass the data along.
    # This is used for data-dependent encoders.
    passData = True
    if passData:
      stats[self.fieldname]['data'] = self.valueList

    if VERBOSITY > 2:
      print '--'
      print "Statistics:"
      print "min:", min
      print "max:", max
      print "mean:", mean
      print "median:", median
      print "1st percentile :", percentile1st
      print "99th percentile:", percentile99th

      print '--'
      print "Resolution:"
      print "Mean Resolution:", meanResolution

    if VERBOSITY > 3:
      print '--'
      print "Histogram:"
      counts, bins = numpy.histogram(self.valueList, new=True)
      print "Counts:", counts.tolist()
      print "Bins:", bins.tolist()
def getStats ( self , stats ) : BaseStatsCollector . getStats ( self , stats ) sortedNumberList = sorted ( self . valueList ) listLength = len ( sortedNumberList ) min = sortedNumberList [ 0 ] max = sortedNumberList [ - 1 ] mean = numpy . mean ( self . valueList ) median = sortedNumberList [ int ( 0.5 * listLength ) ] percentile1st = sortedNumberList [ int ( 0.01 * listLength ) ] percentile99th = sortedNumberList [ int ( 0.99 * listLength ) ] differenceList = [ ( cur - prev ) for prev , cur in itertools . izip ( list ( self . valueSet ) [ : - 1 ] , list ( self . valueSet ) [ 1 : ] ) ] if min > max : print self . fieldname , min , max , '-----' meanResolution = numpy . mean ( differenceList ) stats [ self . fieldname ] [ 'min' ] = min stats [ self . fieldname ] [ 'max' ] = max stats [ self . fieldname ] [ 'mean' ] = mean stats [ self . fieldname ] [ 'median' ] = median stats [ self . fieldname ] [ 'percentile1st' ] = percentile1st stats [ self . fieldname ] [ 'percentile99th' ] = percentile99th stats [ self . fieldname ] [ 'meanResolution' ] = meanResolution # TODO: Right now, always pass the data along. # This is used for data-dependent encoders. passData = True if passData : stats [ self . fieldname ] [ 'data' ] = self . valueList if VERBOSITY > 2 : print '--' print "Statistics:" print "min:" , min print "max:" , max print "mean:" , mean print "median:" , median print "1st percentile :" , percentile1st print "99th percentile:" , percentile99th print '--' print "Resolution:" print "Mean Resolution:" , meanResolution if VERBOSITY > 3 : print '--' print "Histogram:" counts , bins = numpy . histogram ( self . valueList , new = True ) print "Counts:" , counts . tolist ( ) print "Bins:" , bins . tolist ( )
Override of getStats()  in BaseStatsCollector

        stats: A dictionary where all the stats are
        outputted
Override of getStats () in BaseStatsCollector