def plot(routePoints=None, profiles=None):
"""
Creates visualization for a one or more conflated timeline(s)
:param routePoints: Indices of the conflated route (Default value = None)
:param profiles: Profiles with timelines to plot (Default value = None)
"""
if isinstance(routePoints, int):
from xpedite.jupyter.plot import buildTxnPlot, buildPmcPlot
from xpedite.analytics.timelineFilter import locateTimeline
profiles = profiles if profiles else globalProfile()
txnId = routePoints
timeline = locateTimeline(profiles, txnId)
if timeline:
display(HTML(buildTxnPlot(timeline)))
if profiles.pmcNames:
display(HTML(buildPmcPlot(timeline)))
return
display(HTML(ERROR_TEXT.format('cannot find transaction for id {}'.format(txnId))))
return
from xpedite.report.flot import FlotBuilder
profile = conflate(profiles, routePoints)
if profile:
flot = FlotBuilder().buildBenchmarkFlot(profile.category, profile.current, profile.benchmarks)
display(HTML(str(flot)))
def buildReport(self,
timelineStats,
benchmarkTlsMap,
probes,
category,
resultOrder,
threshold,
logAbsoluteValues=False,
logTimeline=False,
logData=False):
"""
Builds latency constituent report with statistics, visualizations and timeline table
:param timelineStats: Time line and duration series statistics
:type timelineStats: xpedite.analytics.timeline.TimelineStats
:param benchmarkTlsMap: Time line and duration series statistics for benchmarks
:param probes: List of probes in route, taken by the transaction collection
:param category: Category of the transactions in this profile
:param resultOrder: Sort order for a collection of timelines
:param threshold: Threshold for number of transactions rendered in html reports
:param logAbsoluteValues: Flag to enable reporting of absolute tsc values
:param logTimeline: Flag to enable reporting of timeline details
:param logData: Flag to enable logging of data associated with transaction
"""
uid = makeUniqueId()
tableContainer = self.buildTimelineTable(timelineStats, probes,
resultOrder, threshold, uid,
logAbsoluteValues,
logTimeline, logData)
timelineCollection = self.reorderTimelineRecords(
timelineStats.timelineCollection, resultOrder)
pmuScript = self.buildPmuScript(timelineCollection, uid)
flotBuilder = FlotBuilder()
flotMarkup = flotBuilder.buildBenchmarkFlot(category, timelineStats,
benchmarkTlsMap)
statsReport = StatsBuilder().buildStatsTable(category, timelineStats,
benchmarkTlsMap)
reportTitle = HTML().h3('{} Transaction Time lines'.format(category))
return (HTML_BEGIN + statsReport + flotMarkup + str(reportTitle) +
pmuScript + str(tableContainer) + HTML_END)