Python TimeSeries.append方法代码示例

# 需要导入模块: from graphite.render.datalib import TimeSeries [as 别名]
# 或者: from graphite.render.datalib.TimeSeries import append [as 别名]
def stdev(requestContext, seriesList, time):
  """

  Takes one metric or a wildcard seriesList followed by an integer N.
  Draw the Standard Deviation of all metrics passed for the past N datapoints. 
  
  Example:
  
  .. code-block:: none

    &target=stddev(server*.instance*.threads.busy,30)

  """
  
  count = 0
  for series in seriesList:
    stddevs = TimeSeries("stddev(%s,%.1f)" % (series.name, float(time)), series.start, series.end, series.step, [])
    stddevs.pathExpression = "stddev(%s,%.1f)" % (series.name, float(time))
    avg = safeDiv(safeSum(series[:time]), time)

    if avg is not None:
      sumOfSquares = sum(map(lambda(x): x * x, [v for v in series[:time] if v is not None]))
      (sd, sumOfSquares) = doStdDev(sumOfSquares, 0, 0, time, avg)
      stddevs.append(sd)
    else:
      stddevs.append(None)

    for (index, el) in enumerate(series[time:]):
      if el is None:
        continue

      toDrop = series[index]
      if toDrop is None:
        toDrop = 0

      s = safeSum([safeMul(time, avg), el, -toDrop])
      avg = safeDiv(s, time)

      if avg is not None:
        (sd, sumOfSquares) = doStdDev(sumOfSquares, toDrop, series[index+time], time, avg)
        stddevs.append(sd)
      else:
        stddevs.append(None)

    for i in range(0, time-1):
      stddevs.insert(0, None)

    seriesList[count] = stddevs
    count = count + 1

  return seriesList

# 需要导入模块: from graphite.render.datalib import TimeSeries [as 别名]
# 或者: from graphite.render.datalib.TimeSeries import append [as 别名]
def movingAverage(requestContext, seriesList, windowSize):
  """

  Takes one metric or a wildcard seriesList followed by a number N of datapoints and graphs 
  the average of N previous datapoints.  N-1 datapoints are set to None at the
  beginning of the graph.

  .. code-block:: none

    &target=movingAverage(Server.instance01.threads.busy,10)

  """
  for seriesIndex, series in enumerate(seriesList):
    newName = "movingAverage(%s,%.1f)" % (series.name, float(windowSize))
    newSeries = TimeSeries(newName, series.start, series.end, series.step, [])
    newSeries.pathExpression = newName

    windowIndex = windowSize - 1

    for i in range( len(series) ):
      if i < windowIndex: # Pad the beginning with None's since we don't have enough data
        newSeries.append( None )

      else:
        window = series[i - windowIndex : i + 1]
        nonNull = [ v for v in window if v is not None ]
        if nonNull:
          newSeries.append( sum(nonNull) / len(nonNull) )
        else:
          newSeries.append(None)

    seriesList[ seriesIndex ] = newSeries

  return seriesList

# 需要导入模块: from graphite.render.datalib import TimeSeries [as 别名]
# 或者: from graphite.render.datalib.TimeSeries import append [as 别名]
def centered_mov_avg(requestContext, seriesList, windowSize):
    windowInterval = None
    if isinstance(windowSize, basestring):
        delta = functions.parseTimeOffset(windowSize)
        windowInterval = abs(delta.seconds + (delta.days * 86400))

    if windowInterval:
        bootstrapSeconds = windowInterval
    else:
        bootstrapSeconds = max([s.step for s in seriesList]) * int(windowSize)

    bootstrapList = functions._fetchWithBootstrap(requestContext, seriesList, seconds=bootstrapSeconds)
    result = []

    for bootstrap, series in zip(bootstrapList, seriesList):
        if windowInterval:
            windowPoints = windowInterval / series.step
        else:
            windowPoints = int(windowSize)

        if isinstance(windowSize, basestring):
            newName = 'centeredMovingAverage(%s,"%s")' % (series.name, windowSize)
        else:
            newName = "centeredMovingAverage(%s,%s)" % (series.name, windowSize)
        newSeries = TimeSeries(newName, series.start, series.end, series.step, [])
        newSeries.pathExpression = newName

        offset = len(bootstrap) - len(series)
        logging.info("Offset: %s", offset)
        logging.info("windowPoints: %s", windowPoints)

        for i in range(len(series)):
            window = bootstrap[i + offset - windowPoints + windowPoints / 2:i + offset + windowPoints / 2]
            logging.info("window: %s", len(window))
            newSeries.append(functions.safeAvg(window))

        result.append(newSeries)

    return result