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
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
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
def stdev(requestContext, seriesList, time):
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
def movingAverage(requestContext, seriesList, windowSize):
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
