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https://github.com/panda3d/panda3d.git
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show timings as percentages, don't display max-non-spike profiles, output easier to scan
This commit is contained in:
Darren Ranalli
parent
f7fc1ca70b
commit
232583858c
@ -12,6 +12,11 @@ import marshal
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class PercentStats(pstats.Stats):
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# prints more useful output when sampled durations are shorter than a millisecond
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# lots of this is copied from Python's pstats.py
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def setTotalTime(self, tt):
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# use this to set 'total time' to base time percentages on
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# allows profiles to show timing based on percentages of duration of another profile
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self._totalTime = tt
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def print_stats(self, *amount):
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for filename in self.files:
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print filename
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@ -26,6 +31,8 @@ class PercentStats(pstats.Stats):
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# DCR
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#print "in %.3f CPU seconds" % self.total_tt
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print "in %s CPU milliseconds" % (self.total_tt * 1000.)
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if self._totalTime != self.total_tt:
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print indent, 'percentages are of %s CPU milliseconds' % (self._totalTime * 1000)
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print
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width, list = self.get_print_list(amount)
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if list:
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@ -33,12 +40,15 @@ class PercentStats(pstats.Stats):
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for func in list:
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self.print_line(func)
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print
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print
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# DCR
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#print
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return self
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@staticmethod
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def f8(x):
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return "%7.2f%%" % (x*100.)
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def f8(self, x):
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if self._totalTime == 0.:
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# profiling was too quick for clock resolution...
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return ' Inf%'
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return "%7.2f%%" % ((x*100.) / self._totalTime)
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@staticmethod
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def func_std_string(func_name): # match what old profile produced
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@ -47,21 +57,23 @@ class PercentStats(pstats.Stats):
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def print_line(self, func):
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cc, nc, tt, ct, callers = self.stats[func]
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c = str(nc)
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d = self.total_tt
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f8 = PercentStats.f8
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# DCR
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f8 = self.f8
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if nc != cc:
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c = c + '/' + str(cc)
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print c.rjust(9),
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print f8(tt/d),
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print f8(tt),
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if nc == 0:
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print ' '*8,
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else:
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print f8((tt/nc)/d),
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print f8(ct/d),
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print f8(tt/nc),
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print f8(ct),
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if cc == 0:
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print ' '*8,
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else:
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print f8((ct/cc)/d),
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print f8(ct/cc),
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# DCR
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#print func_std_string(func)
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print PercentStats.func_std_string(func)
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class ProfileSession:
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@ -204,9 +216,10 @@ class ProfileSession:
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del self._filename2ramFile[filename]
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def getResults(self,
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lines=80,
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lines=200,
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sorts=['cumulative', 'time', 'calls'],
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callInfo=False):
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callInfo=False,
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totalTime=None):
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if not self.profileSucceeded():
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output = '%s: profiler already running, could not profile' % self._name
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else:
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@ -232,11 +245,15 @@ class ProfileSession:
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# throw out any cached result strings
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self._resultCache = {}
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if totalTime is None:
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totalTime = self._stats.total_tt
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# make sure the arguments will hash efficiently if callers provide different types
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lines = int(lines)
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sorts = list(sorts)
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callInfo = bool(callInfo)
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k = str((lines, sorts, callInfo))
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totalTime = float(totalTime)
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k = str((lines, sorts, callInfo, totalTime))
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if k in self._resultCache:
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# we've already created this output string, get it from the cache
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output = self._resultCache[k]
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@ -248,6 +265,8 @@ class ProfileSession:
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# print the info to stdout
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s = self._stats
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# make sure our percentages are relative to the correct total time
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s.setTotalTime(totalTime)
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for sort in sorts:
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s.sort_stats(sort)
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s.print_stats(lines)
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@ -11,7 +11,6 @@ class TaskTracker:
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self._namePrefix = namePrefix
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self._durationAverager = Averager('%s-durationAverager' % namePrefix)
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self._avgSession = None
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self._maxNonSpikeSession = None
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if TaskTracker.MinSamples is None:
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# number of samples required before spikes start getting identified
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TaskTracker.MinSamples = config.GetInt('profile-task-spike-min-samples', 30)
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@ -25,10 +24,7 @@ class TaskTracker:
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self._durationAverager.reset()
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if self._avgSession:
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self._avgSession.release()
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if self._maxNonSpikeSession:
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self._maxNonSpikeSession.release()
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self._avgSession = None
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self._maxNonSpikeSession = None
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def getNamePrefix(self, namePrefix):
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return self._namePrefix
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def _checkSpike(self, session):
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@ -40,51 +36,33 @@ class TaskTracker:
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if duration > (self.getAvgDuration() * self.SpikeThreshold):
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isSpike = True
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avgSession = self.getAvgSession()
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maxNSSession = self.getMaxNonSpikeSession()
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self.notify.info('task CPU spike profile (%s):\n'
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'== AVERAGE\n%s\n'
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'== LONGEST NON-SPIKE\n%s\n'
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'== SPIKE\n%s' % (
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self._namePrefix,
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avgSession.getResults(),
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maxNSSession.getResults(),
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session.getResults()))
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s = '\n%s task CPU spike profile (%s) %s\n' % ('=' * 30, self._namePrefix, '=' * 30)
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s += ('~' * 60) + '\n'
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for sorts in (['cumulative'], ['time'], ['calls']):
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s += ('-- AVERAGE --\n%s'
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'-- SPIKE --\n%s' % (
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avgSession.getResults(sorts=sorts, totalTime=duration),
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session.getResults(sorts=sorts)))
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self.notify.info(s)
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return isSpike
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def addProfileSession(self, session):
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isSpike = self._checkSpike(session)
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duration = session.getDuration()
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self._durationAverager.addValue(duration)
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if self.getNumDurationSamples() == self.MinSamples:
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# if we just collected enough samples to check for spikes, see if
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# our max 'non-spike' session collected so far counts as a spike
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# and if so, log it
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if self._checkSpike(self._maxNonSpikeSession):
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self._maxNonSpikeSession = self._avgSession
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storeAvg = True
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storeMaxNS = True
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if self._avgSession is not None:
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avgDur = self.getAvgDuration()
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if abs(self._avgSession.getDuration() - avgDur) < abs(duration - avgDur):
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# current avg data is more average than this new sample, keep the data we've
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# already got stored
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storeAvg = False
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if isSpike:
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storeMaxNS = False
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else:
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if (self._maxNonSpikeSession is not None and
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self._maxNonSpikeSession.getDuration() > duration):
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storeMaxNS = False
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if storeAvg:
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if self._avgSession:
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self._avgSession.release()
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session.acquire()
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self._avgSession = session
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if storeMaxNS:
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if self._maxNonSpikeSession:
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self._maxNonSpikeSession.release()
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session.acquire()
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self._maxNonSpikeSession = session
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def getAvgDuration(self):
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return self._durationAverager.getAverage()
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def getNumDurationSamples(self):
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@ -92,18 +70,13 @@ class TaskTracker:
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def getAvgSession(self):
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# returns profile session for closest-to-average sample
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return self._avgSession
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def getMaxNonSpikeSession(self):
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# returns profile session for closest-to-average sample
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return self._maxNonSpikeSession
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def log(self):
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if self._avgSession:
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self.notify.info('task CPU profile (%s):\n'
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'== AVERAGE\n%s\n'
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'== LONGEST NON-SPIKE\n%s' % (
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self._namePrefix,
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self._avgSession.getResults(),
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self._maxNonSpikeSession.getResults(),
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))
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s = 'task CPU profile (%s):\n' % self._namePrefix
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s += ('~' * 60) + '\n'
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for sorts in (['cumulative'], ['time'], ['calls']):
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s += self._avgSession.getResults(sorts=sorts)
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self.notify.info(s)
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else:
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self.notify.info('task CPU profile (%s): no data collected' % self._namePrefix)
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