def fillHistos(self, monComp):
from App import DataSetMgr
self.msg.debug("filling histograms...")
# short-hands
# milliseconds
ms = Units.ms
dsNames = DataSetMgr.names()
yMinRead = []
yMaxRead = []
yMinWrite = []
yMaxWrite = []
for dsName in dsNames:
if dsName not in monComp.data:
continue
data = monComp.data[dsName]
if 'evt' not in data:
continue
data['evt']['io/cpu/rr'] = data['evt']['io/user/rr'] \
+ data['evt']['io/sys/rr' ]
data['evt']['io/cpu/r'] = data['evt']['io/user/r'] \
+ data['evt']['io/sys/r' ]
yMinRead += [data['evt']['io/cpu/r'][self.minEvt:].min() * ms]
yMaxRead += [data['evt']['io/cpu/r'][self.minEvt:].max() * ms]
data['evt']['io/cpu/w'] = data['evt']['io/user/w'] \
+ data['evt']['io/sys/w' ]
yMinWrite += [data['evt']['io/cpu/w'][self.minEvt:].min() * ms]
yMaxWrite += [data['evt']['io/cpu/w'][self.minEvt:].max() * ms]
yMinRead = min(yMinRead)
yMaxRead = max(yMaxRead)
yMinWrite = min(yMinWrite)
yMaxWrite = max(yMaxWrite)
for dsName in dsNames:
if dsName not in monComp.data:
continue
data = monComp.data[dsName]
if 'evt' not in data:
continue
bins = DataSetMgr.instances[dsName].bins
if 'evt/io' not in monComp.figs:
monComp.figs['evt/io'] = pylab.figure()
monComp.figs['evt/io'].add_subplot(221).hold(True)
monComp.figs['evt/io'].add_subplot(223).hold(True)
monComp.figs['evt/io'].add_subplot(222).hold(True)
monComp.figs['evt/io'].add_subplot(224).hold(True)
## read
fig = monComp.figs['evt/io']
ax = fig.axes[0]
_iy = self.minEvt + len(bins[self.minEvt:])
pl = ax.plot(bins[self.minEvt:],
data['evt']['io/cpu/r'][self.minEvt:_iy] * ms,
linestyle='steps',
label=dsName)
ax.grid(True)
ax.set_title("[%s]" % monComp.name)
ax.set_ylabel('(R) CPU time [ms]')
ax.set_xlabel('Event number')
ax.set_ylim((ax.get_ylim()[0], ax.get_ylim()[1] * 1.1))
h, b = numpy.histogram(data['evt']['io/cpu/r'][self.minEvt:] * ms +
data['evt']['io/cpu/r'][self.minEvt:] * ms,
bins=20,
range=(yMinRead * 0.90, yMaxRead * 1.10))
ax = fig.axes[1]
ax.plot(b, h, label=dsName, ls='steps')
ax.grid(True)
ax.set_xlabel('(R) CPU time [ms]')
ax.set_ylim((ax.get_ylim()[0], ax.get_ylim()[1] * 1.1))
## write
fig = monComp.figs['evt/io']
ax = fig.axes[2]
_iy = self.minEvt + len(bins[self.minEvt:])
pl = ax.plot(bins[self.minEvt:],
data['evt']['io/cpu/w'][self.minEvt:_iy] * ms,
linestyle='steps',
label=dsName)
ax.grid(True)
ax.set_title("[%s]" % monComp.name)
ax.set_ylabel('(W) CPU time [ms]')
ax.set_xlabel('Event number')
ax.set_ylim((ax.get_ylim()[0], ax.get_ylim()[1] * 1.1))
h, b = numpy.histogram(data['evt']['io/cpu/w'][self.minEvt:] * ms +
data['evt']['io/cpu/w'][self.minEvt:] * ms,
bins=20,
range=(yMinWrite * 0.90, yMaxWrite * 1.10))
ax = fig.axes[3]
ax.plot(b, h, label=dsName, ls='steps')
ax.grid(True)
ax.set_xlabel('(W) CPU time [ms]')
ax.set_ylim((ax.get_ylim()[0], ax.get_ylim()[1] * 1.1))
## read
h = data['histos']['io_r_%s' % dsName]
hAvg = bookAvgHist(h, data['evt']['io/cpu/r'] * ms)
data['histos'][h.GetName()] = hAvg
for i in range(len(bins)):
cpuTime = data['evt']['io/cpu/r'][i] * ms
h.Fill(float(bins[i]), cpuTime)
hAvg.Fill(cpuTime)
## write
h = data['histos']['io_w_%s' % dsName]
hAvg = bookAvgHist(h, data['evt']['io/cpu/w'] * ms)
data['histos'][h.GetName()] = hAvg
for i in range(len(bins)):
cpuTime = data['evt']['io/cpu/w'][i] * ms
h.Fill(float(bins[i]), cpuTime)
hAvg.Fill(cpuTime)
pass # loop over datasets
for ax in monComp.figs['evt/io'].axes:
ax.legend(DataSetMgr.labels(), loc='best')
################################################
# ROOT T/P separation overhead
#
for dsName in dsNames:
if dsName not in monComp.data:
continue
data = monComp.data[dsName]
if 'evt' not in data:
continue
bins = DataSetMgr.instances[dsName].bins
if 'evt/rio' not in monComp.figs:
monComp.figs['evt/rio'] = pylab.figure()
monComp.figs['evt/rio'].add_subplot(221).hold(True)
monComp.figs['evt/rio'].add_subplot(223).hold(True)
monComp.figs['evt/rio'].add_subplot(222).hold(True)
monComp.figs['evt/rio'].add_subplot(224).hold(True)
## read
fig = monComp.figs['evt/rio']
ax = fig.axes[0]
_iy = self.minEvt + len(bins[self.minEvt:])
pl = ax.plot(bins[self.minEvt:],
data['evt']['io/cpu/rr'][self.minEvt:_iy] * ms,
linestyle='steps',
label=dsName)
ax.set_title("[%s]" % monComp.name)
ax.set_ylabel('(RR) CPU time [ms]')
ax.set_xlabel('Event number')
ax.set_ylim((ax.get_ylim()[0], ax.get_ylim()[1] * 1.1))
h, b = numpy.histogram(
data['evt']['io/cpu/rr'][self.minEvt:] * ms +
data['evt']['io/cpu/rr'][self.minEvt:] * ms,
bins=20,
range=(yMinRead * 0.90, yMaxRead * 1.10))
ax = fig.axes[1]
ax.plot(b, h, label=dsName, ls='steps')
ax.set_xlabel('(RR) CPU time [ms]')
ax.set_ylim((ax.get_ylim()[0], ax.get_ylim()[1] * 1.1))
_iy = self.minEvt + len(bins[self.minEvt:])
ratios = []
for idx, num in enumerate(
data['evt']['io/cpu/rr'][self.minEvt:_iy]):
den = data['evt']['io/cpu/r'][idx]
if den == 0.: r = 0
else: r = num / den * 100.
ratios.append(r)
## print "%3i %8.3f %8.3f %8.3f" % (idx,num,den,r)
ratios = numpy.array(ratios)
yMinRatio = min(ratios)
yMaxRatio = max(ratios)
## pure ROOT read over T/P read
fig = monComp.figs['evt/rio']
ax = fig.axes[2]
pl = ax.plot(bins[self.minEvt:],
ratios,
linestyle='steps',
label=dsName)
ax.set_title("[%s]" % monComp.name)
ax.set_ylabel('Pure-ROOT over Full read CPU time (%)')
ax.set_xlabel('Event number')
ax.set_ylim((ax.get_ylim()[0], ax.get_ylim()[1] * 1.1))
h, b = numpy.histogram(ratios + ratios,
bins=20,
range=(yMinRatio * 0.90, yMaxRatio * 1.10))
ax = fig.axes[3]
ax.plot(b, h, label=dsName, ls='steps')
ax.set_xlabel('Pure-ROOT over Full read CPU time (%)')
ax.set_ylim((ax.get_ylim()[0], ax.get_ylim()[1] * 1.1))
## read
h = data['histos']['io_rr_%s' % dsName]
hAvg = bookAvgHist(h, data['evt']['io/cpu/rr'] * ms)
data['histos'][h.GetName()] = hAvg
for i in range(len(bins)):
cpuTime = data['evt']['io/cpu/rr'][i] * ms
h.Fill(float(bins[i]), cpuTime)
hAvg.Fill(cpuTime)
pass # loop over datasets
for ax in monComp.figs['evt/io'].axes:
ax.legend(DataSetMgr.labels(), loc='best')
self.msg.debug("filling histograms... [DONE]")
return
def fillHistos(self, monComp):
from App import DataSetMgr
self.msg.debug("filling histograms...")
# short-hands
msg = self.msg
# convert page-size into MB
Mb = Units.Mb
# convert page-size into kB
kb = Units.kb
monName = monComp.name
dsNames = DataSetMgr.names()
ymin = {'vmem':[], 'malloc':[]}
ymax = {'vmem':[], 'malloc':[]}
allGood = True
for dsName in dsNames:
if not dsName in monComp.data:
continue
#print "---",dsName,monComp.name
data = monComp.data[dsName]
if not 'evt' in data:
continue
data = data['evt']
if data is None:
## print "---",dsName,monComp.name,"data['evt'] is None"
continue
if not 'mem' in data.dtype.names:
allGood = False
msg.debug('component [%s] has empty mem infos for '
'dataset [%s]',
monComp.name,
dsName)
## print "--->",dsName,monComp.name,data.dtype.names
continue
## print "+++",dsName,monComp.name
mem = data['mem']
dvmem = mem['vmem'][:,2]
ymin['vmem'].append(dvmem[self.minEvt:].min()*kb)
ymax['vmem'].append(dvmem[self.minEvt:].max()*kb)
dmall = mem['mall'][:,2]
ymin['malloc'].append(dmall[self.minEvt:].min()*kb)
ymax['malloc'].append(dmall[self.minEvt:].max()*kb)
pass
if not allGood:
msg.debug("Something bad happened for component [%s] "
"during 'MemAnalyzer.fillHistos' !!",
monComp.name)
return
if len(ymin['vmem']) == 0 and len(ymax['vmem']) == 0:
self.msg.debug("Component [%s] has no 'evt' level data",
monComp.name)
return
for k in ymin.keys():
ymin[k] = min(ymin[k])
ymax[k] = max(ymax[k])
pass
for dsName in dsNames:
if not dsName in monComp.data:
continue
data = monComp.data[dsName]
if not 'evt' in data:
continue
data = data['evt']
if data is None:
continue
if not 'mem' in data.dtype.names:
continue
bins = DataSetMgr.instances[dsName].bins
if not 'evt/mem' in monComp.figs:
monComp.figs['evt/mem'] = plt.figure()
monComp.figs['evt/mem'].add_subplot(221).hold( True )
monComp.figs['evt/mem'].add_subplot(222).hold( True )
monComp.figs['evt/mem'].add_subplot(223).hold( True )
monComp.figs['evt/mem'].add_subplot(224).hold( True )
fig = monComp.figs['evt/mem']
mem = data['mem']
dvmem = mem['vmem'][:,2]
dmall = mem['mall'][:,2]
## VMem
ax = fig.axes[0]
binMax = len(dvmem[self.minEvt:len(bins)])
pl = ax.plot(bins[self.minEvt:binMax],
dvmem[self.minEvt:binMax] * kb,
linestyle = 'steps',
label = dsName)
ax.grid(True)
ax.set_title ('Delta V-Mem\n[%s]' % monComp.name)
ax.set_ylabel('Delta V-Mem [kb]')
ax.set_xlabel('Event number')
ax.set_ylim((ax.get_ylim()[0]*0.9,
ax.get_ylim()[1]*1.1))
h,b = numpy.histogram(
dvmem[self.minEvt:binMax] * kb,
bins = 20,
range = (ymin['vmem']*0.90, ymax['vmem']*1.10)
)
ax = fig.axes[2]
ax.plot(b[:-1], h, label=dsName, ls='steps')
ax.grid(True)
ax.set_xlabel('Delta V-Mem [kb]')
ax.set_ylim((ax.get_ylim()[0]*0.9, ### ???
ax.get_ylim()[1]*1.1))
## Malloc
ax = fig.axes[1]
pl = ax.plot(bins[self.minEvt:binMax],
dmall[self.minEvt:binMax] * kb,
linestyle = 'steps',
label = dsName)
ax.grid(True)
ax.set_title ('Delta Malloc\n[%s]' % monComp.name)
ax.set_ylabel('Delta Malloc [kb]')
ax.set_xlabel('Event number')
ax.set_ylim((ax.get_ylim()[0]*0.9,
ax.get_ylim()[1]*1.1))
h,b = numpy.histogram(
dmall[self.minEvt:binMax] * kb,
bins = 20,
range = (ymin['malloc']*0.90, ymax['malloc']*1.10)
)
ax = fig.axes[3]
ax.plot(b[:-1], h, label=dsName, ls='steps')
ax.grid(True)
ax.set_xlabel('Delta Malloc [kb]')
ax.set_ylim( (ax.get_ylim()[0]*0.9,
ax.get_ylim()[1]*1.1) )
## ROOT-histos
data = monComp.data[dsName]
hVmem = data['histos']['mem_%s' % dsName]
hAvgVmem = bookAvgHist(hVmem, dvmem * kb)
data['histos'][hVmem.GetName()] = hAvgVmem
hMall = data['histos']['malloc_%s' % dsName]
hAvgMall = bookAvgHist(hMall, dmall * kb)
data['histos'][hMall.GetName()] = hAvgMall
maxRange = min(len(dvmem), len(bins))
for i in range(maxRange):
dVmem = dvmem[i] * kb
hVmem.Fill( float(bins[i]), dVmem )
hAvgVmem.Fill( dVmem )
dMall = dmall[i] * kb
hMall.Fill( float(bins[i]), dMall )
hAvgMall.Fill( dVmem )
pass # loop over datasets
for ax in monComp.figs['evt/mem'].axes:
ax.legend(DataSetMgr.labels(), loc='best')
self.msg.debug( "filling histograms... [DONE]" )
return
def processEvt(self, dataSetMgr, monCompMgr):
from App import DataSetMgr
from PyRootLib import importRoot
ROOT = importRoot(batch=True)
## RootFct = ROOT.TF1
## dummyCanvas = ROOT.TCanvas("dummyFitCanvas")
## import PyRootLib as prl
## self.sum['evt']['histos'] = []
## self.sum['evt']['fig'] = []
## short-hand
ms = Units.ms
kb = Units.kb
Mb = Units.Mb
Mb2Kb = 1000.
msg = self.msg
## get top-20 consumers
dsNames = DataSetMgr.names()
color = DataSetMgr.colorIter()
_txt = self.txt['evt']
monComp = monCompMgr['PerfMonSlice']
yMinCpu = []
yMaxCpu = []
yMinIo = []
yMaxIo = []
for dsName in dsNames:
data = monComp.data[dsName]
histos = data['histos'] = {}
if not 'evt' in data:
continue
data = data['evt']
if data is None:
continue
cpu = data['cpu']
cpu_u = cpu['user']
cpu_s = cpu['sys']
cpu_r = cpu['real']
cpu_c = cpu['cpu']
dcpu_u = cpu_u[:, 2]
dcpu_s = cpu_s[:, 2]
dcpu_r = cpu_r[:, 2]
dcpu_c = cpu_c[:, 2]
mem = data['mem']
vmem = mem['vmem']
dvmem = vmem[:, 2]
rss = mem['rss']
drss = rss[:, 2]
mall = mem['mall']
dmall = mall[:, 2]
nallocs = mem['nmall'][:, 2]
nfrees = mem['nfree'][:, 2]
yMinCpu.append(dcpu_c[self.minEvt:].min() * ms)
yMaxCpu.append(dcpu_c[self.minEvt:].max() * ms)
io = monComp.data[dsName]['io']
io_c = io['w']['cpu']
yMinIo.append(io_c[self.minEvt:].min() * ms)
yMaxIo.append(io_c[self.minEvt:].max() * ms)
## data['mem/vmem/d'] = data['mem/vmem/1'] - data['mem/vmem/0']
## data['mem/rss/d' ] = data['mem/rss/1' ] - data['mem/rss/0' ]
## fill-in some data for ASCII summary
if dsName == '000':
_txt['cpu']['slice'] += [
"%-20s %10.3f %10.3f %10.3f ms" % (
"[u/s/r]",
dcpu_u[self.minEvt:].mean() * ms,
dcpu_s[self.minEvt:].mean() * ms,
dcpu_r[self.minEvt:].mean() * ms,
),
]
_txt['mem']['slice'] += [
"%-20s %10.3f %10.3f %10.3f kB" % (
"[dVmem/dRss/dMalloc]",
dvmem[self.minEvt:].mean() * kb,
drss[self.minEvt:].mean() * kb,
dmall[self.minEvt:].mean() * kb,
),
]
_txt['allocs']['slice'] += [
"%-20s %10i %10i" % (
"[nallocs/nfrees]",
nallocs[self.minEvt:].mean(),
nfrees[self.minEvt:].mean(),
),
]
## book ROOT histos
nEntries = len(dataSetMgr[dsName].bins) - 1
minEvt = dataSetMgr[dsName].bins[self.minEvt]
maxEvt = dataSetMgr[dsName].bins[-1]
hId = 'cpu_%s.%s' % (monComp.name, dsName)
hName = 'cpu_%s' % dsName
histos[hName] = ROOT.TH1F(
hId, "[%s] CPU usage [%s];%s;%s" %
(monComp.name, dsName, "event nbr", "Timing [ms]"), nEntries,
minEvt, maxEvt)
hId = 'vmem_%s.%s' % (monComp.name, dsName)
hName = 'vmem_%s' % dsName
histos[hName] = ROOT.TH1F(
hId, "[%s] VMem usage [%s];%s;%s" %
(monComp.name, dsName, "event nbr", "V-Mem [MB]"), nEntries,
minEvt, maxEvt)
hId = 'rss_%s.%s' % (monComp.name, dsName)
hName = 'rss_%s' % dsName
histos[hName] = ROOT.TH1F(
hId, "[%s] RSS usage [%s];%s;%s" %
(monComp.name, dsName, "event nbr", "RSS [MB]"), nEntries,
minEvt, maxEvt)
hId = 'io_%s.%s' % (monComp.name, dsName)
hName = 'io_%s' % dsName
histos[hName] = ROOT.TH1F(
hId, "[%s] I/O time [%s];%s;%s" %
(monComp.name, dsName, "event nbr", "I/O time [ms]"), nEntries,
minEvt, maxEvt)
pass
yMinIo = min(yMinIo)
yMaxIo = max(yMaxIo)
yMinCpu = min(yMinCpu)
yMaxCpu = max(yMaxCpu)
def markForLegend(p):
setattr(p, '_markedForLegend', True)
def isMarked(p):
return hasattr(p, '_markedForLegend')
memLeak = []
for dsName in dsNames:
if not 'evt' in monComp.data[dsName]:
continue
data = monComp.data[dsName]
cpu = data['evt']['cpu']
cpu_c = cpu['cpu']
dcpu_c = cpu_c[:, 2]
## CPU
bins = dataSetMgr[dsName].bins
xbins = bins[self.minEvt:]
if not 'evt/cpu' in monComp.figs:
monComp.figs['evt/cpu'] = plt.figure()
monComp.figs['evt/cpu'].add_subplot(211).hold(True)
monComp.figs['evt/cpu'].add_subplot(212).hold(True)
fig = monComp.figs['evt/cpu']
ax = fig.axes[0]
pl = ax.plot(xbins,
dcpu_c[self.minEvt:] * ms,
linestyle='steps',
label=dsName)
ax.grid(True)
ax.set_title("CPU time [Begin/End-Event]")
ax.set_ylabel('CPU time [ms]')
ax.set_xlabel('Event number')
ax.set_ylim((ax.get_ylim()[0] * 0.9, ax.get_ylim()[1] * 1.1))
markForLegend(pl[0])
h, b = numpy.histogram(dcpu_c[self.minEvt:] * ms,
bins=20,
range=(yMinCpu * 0.90, yMaxCpu * 1.10))
ax = fig.axes[1]
pl = ax.plot(b[:-1], h, label=dsName, ls='steps')
ax.grid(True)
ax.set_xlabel('CPU time [ms]')
ax.set_ylim((ax.get_ylim()[0], ax.get_ylim()[1] * 1.1))
markForLegend(pl[0])
h = data['histos']['cpu_%s' % dsName]
hAvg = bookAvgHist(h, dcpu_c * ms)
data['histos'][h.GetName()] = hAvg
for i in range(len(bins)):
cpuTime = dcpu_c[i] * ms
h.Fill(float(bins[i]), cpuTime)
hAvg.Fill(cpuTime)
## Mem
mem = data['evt']['mem']
vmem = mem['vmem']
dvmem = vmem[:, 2]
dmall = mem['mall'][:, 2]
if not 'evt/mem' in monComp.figs:
monComp.figs['evt/mem'] = plt.figure()
monComp.figs['evt/mem'].add_subplot(311).hold(True)
monComp.figs['evt/mem'].add_subplot(312).hold(True)
monComp.figs['evt/mem'].add_subplot(313).hold(True)
fig = monComp.figs['evt/mem']
ax = fig.axes[0]
pl = ax.plot(
xbins,
vmem[self.minEvt:, 1] * Mb,
linestyle='steps',
#'o',
label=dsName)
ax.set_title("Memory usage [Begin/End-Event]")
ax.set_ylabel('VMem [MB]')
ax.set_xlabel('Event number')
ax.set_ylim((ax.get_ylim()[0] * 0.9, ax.get_ylim()[1] * 1.1))
ax.grid(True)
markForLegend(pl[0])
## fit
#nFit = int(len(bins)/2.)
#x = bins[-nFit:]
#y = data['evt']['mem/vmem/1'][-nFit:] * Mb
begFit = self._fitSlice[0]
endFit = self._fitSlice[1]
x = bins[begFit:endFit]
y = vmem[begFit:endFit, 1] * Mb
coeffs = numpy.lib.polyfit(x, y, deg=1)
memLeak += [coeffs[0] * kb]
ax.plot(x, numpy.lib.polyval(coeffs, x), '-', color='y', lw=2.)
if dsName == '000':
_txt['mem']['slice'] += [
"%-20s p[0] = %8.3f MB \tp[1] = %8.3f kB" % (
"vmem fit:",
coeffs[1] * Mb,
coeffs[0] * kb, #
)
]
ax = fig.axes[1]
pl = ax.plot(xbins,
mem['rss'][self.minEvt:, 1] * Mb,
linestyle='steps',
label=dsName)
ax.set_ylabel('RSS [MB]')
ax.set_xlabel('Event number')
ax.set_ylim((ax.get_ylim()[0] * 0.9, ax.get_ylim()[1] * 1.1))
ax.grid(True)
markForLegend(pl[0])
ax = fig.axes[2]
pl = ax.plot(xbins,
dmall[self.minEvt:] * Mb,
linestyle='steps',
label=dsName)
ax.set_ylabel('Delta Malloc [MB]')
ax.set_xlabel('Event number')
ax.set_ylim((ax.get_ylim()[0] * 0.9, ax.get_ylim()[1] * 1.1))
ax.grid(True)
markForLegend(pl[0])
h = data['histos']['vmem_%s' % dsName]
hAvg = bookAvgHist(h, mem['vmem'][:, 1] * Mb)
data['histos'][h.GetName()] = hAvg
for i in range(len(bins)):
vmem = mem['vmem'][i, 1] * Mb
h.Fill(float(bins[i]), vmem)
hAvg.Fill(vmem)
h = data['histos']['rss_%s' % dsName]
hAvg = bookAvgHist(h, mem['rss'][:, 1] * Mb)
data['histos'][h.GetName()] = hAvg
for i in range(len(bins)):
rss = mem['rss'][i, 1] * Mb
h.Fill(float(bins[i]), rss)
hAvg.Fill(rss)
## I/O
if not 'evt/io' in monComp.figs:
monComp.figs['evt/io'] = plt.figure()
monComp.figs['evt/io'].add_subplot(211).hold(True)
monComp.figs['evt/io'].add_subplot(212).hold(True)
fig = monComp.figs['evt/io']
ax = fig.axes[0]
io_c = data['io']['w']['cpu']
pl = ax.plot(xbins,
io_c[self.minEvt:] * ms,
linestyle='steps',
label=dsName)
ax.set_title("I/O time [CommitOutput]")
ax.set_ylabel('I/O time [ms]')
ax.set_xlabel('Event number')
ax.set_ylim((ax.get_ylim()[0], ax.get_ylim()[1] * 1.1))
ax.grid(True)
markForLegend(pl[0])
yMinIo *= 0.9
yMaxIo *= 1.1
yMinIo, yMaxIo = min(yMinIo, yMaxIo), max(yMinIo, yMaxIo)
h, b = numpy.histogram(io_c[self.minEvt:] * ms,
bins=20,
range=(yMinIo, yMaxIo))
ax = fig.axes[1]
pl = ax.plot(b[:-1], h, label=dsName, ls='steps')
ax.set_xlabel('I/O time [ms]')
ax.set_ylim((ax.get_ylim()[0], ax.get_ylim()[1] * 1.1))
ax.grid(True)
markForLegend(pl[0])
h = data['histos']['io_%s' % dsName]
hAvg = bookAvgHist(h, io_c * ms)
data['histos'][h.GetName()] = hAvg
for i in range(len(bins)):
cpuTime = io_c[i] * ms
h.Fill(float(bins[i]), cpuTime)
hAvg.Fill(cpuTime)
pass # loop over data sets
## handle mem-leak text
ax = monComp.figs['evt/mem'].axes[0]
ax.text(
0.025,
0.97,
"\n".join("[%s] Leak: %8.3f kB" % (n, leak)
for n, leak in zip(DataSetMgr.labels(), memLeak)),
bbox=dict(facecolor='w'),
#color = '',
fontweight='bold',
#fontsize = 'x-larger',
verticalalignment='top',
transform=ax.transAxes)
for figName, fig in monComp.figs.items():
loc = 'best'
if figName == 'evt/mem': loc = 'lower right'
for ax in fig.axes:
objs = [l for l in ax.lines if isMarked(l)]
ax.legend(
objs,
DataSetMgr.labels(),
#loc='lower right'
#loc='best'
loc=loc)
## get top-20 consumers
self._top_consumers(dataSetMgr,
monCompMgr,
compTypes=('alg', ),
title='Event loop',
storeName='evt',
sliceName='evt',
begSlice=self.minEvt,
endSlice=None)
return
def fillHistos(self, monComp):
from App import DataSetMgr
self.msg.debug("filling histograms...")
# short-hands
msg = self.msg
# milliseconds
ms = Units.ms
monName = monComp.name
dsNames = DataSetMgr.names()
yMin = []
yMax = []
allGood = True
figs = monComp.figs
for dsName in dsNames:
if not monComp.data.has_key(dsName):
continue
data = monComp.data[dsName]
## print "..",dsName,data.keys()
if not 'evt' in data:
continue
data = data['evt']
if data is None:
continue
## print "..",dsName,data.keys()
if not 'cpu' in data.dtype.names:
allGood = False
msg.debug(
'component [%s] has empty cpu/user infos for '
'dataset [%s]', monComp.name, dsName)
continue
cpu = data['cpu']['cpu']
yMin.append(cpu[self.minEvt:, 2].min() * ms)
yMax.append(cpu[self.minEvt:, 2].max() * ms)
if not allGood:
msg.debug(
"Something bad happened for component [%s] "
"during 'CpuAnalyzer.fillHistos' !!", monComp.name)
return
if len(yMin) == 0 and len(yMax) == 0:
msg.debug("Component [%s] has no 'evt' level data", monComp.name)
return
yMin = min(yMin)
yMax = max(yMax)
for dsName in dsNames:
if not monComp.data.has_key(dsName):
continue
data = monComp.data[dsName]
if not 'evt' in data:
continue
bins = DataSetMgr.instances[dsName].bins
if not 'evt/cpu' in monComp.figs:
monComp.figs['evt/cpu'] = plt.figure()
monComp.figs['evt/cpu'].add_subplot(211).hold(True)
monComp.figs['evt/cpu'].add_subplot(212).hold(True)
fig = monComp.figs['evt/cpu']
ax = fig.axes[0]
cpu = data['evt']['cpu']
cpu_c = cpu['cpu']
cpu_u = cpu['user']
cpu_s = cpu['sys']
binMax = len(cpu_c[self.minEvt:len(bins)])
pl = ax.plot(bins[self.minEvt:binMax],
cpu_c[self.minEvt:binMax, 2] * ms,
linestyle='steps',
label=dsName)
ax.grid(True)
ax.set_title("CPU time [%s]" % monComp.name)
ax.set_ylabel('CPU time [ms]')
ax.set_xlabel('Event number')
ax.set_ylim((ax.get_ylim()[0], ax.get_ylim()[1] * 1.1))
h, b = numpy.histogram(cpu_c[self.minEvt:binMax, 2] * ms,
bins=20,
range=(yMin * 0.90, yMax * 1.10))
ax = fig.axes[1]
ax.plot(b[:-1], h, label=dsName, ls='steps')
ax.grid(True)
ax.set_xlabel('CPU time [ms]')
ax.set_ylim((ax.get_ylim()[0], ax.get_ylim()[1] * 1.1))
h = data['histos']['cpu_%s' % dsName]
hAvg = bookAvgHist(h, cpu_c[:, 2] * ms)
data['histos'][h.GetName()] = hAvg
maxRange = min(len(cpu_c), len(bins))
for i in range(maxRange):
cpuTime = cpu_c[i, 2] * ms
h.Fill(float(bins[i]), cpuTime)
hAvg.Fill(cpuTime)
pass # loop over datasets
for ax in monComp.figs['evt/cpu'].axes:
ax.legend(DataSetMgr.labels(dsNames), loc='best')
self.msg.debug("filling histograms... [DONE]")
return