def report(self, detail):
"""
Output a report on the collected statistics
The 'detail' argument controls how much detail is provided
(more detail, longer reports)
"""
if not self.aggregationDone:
# aggregate the per probe results before reporting
self.aggregateProbeData()
host = dnsnamelookup(self.dst_addr)
nprobes = len(self.probeReport.keys())
if (detail == 0):
if host:
print "Destination:", self.dst_addr, " / ", host
else:
print "Destination:", self.dst_addr
else:
print "Destination:", self.dst_addr
if host:
print "Reverse DNS:", host
print "Timeinterval:", time.strftime(
"%Y-%m-%dT%H:%MZ",
time.gmtime(self.starttime)), " - ", time.strftime(
"%Y-%m-%dT%H:%MZ", time.gmtime(self.endtime))
print "Number of samples: ", self.samples
print
return
def report(self, detail):
"""
Output a report on the collected statistics
The 'detail' argument controls how much detail is provided
(more detail, longer reports)
"""
if not self.aggregationDone:
# aggregate the per probe results before reporting
self.aggregateProbeData()
host = dnsnamelookup(self.dst_addr)
nprobes = len(self.probeReport.keys())
if (detail == 0):
if host:
print "Destination:", self.dst_addr, " / ", host
else:
print "Destination:", self.dst_addr
else:
print "Destination:", self.dst_addr
if host:
print "Reverse DNS:", host
print "Timeinterval:", time.strftime(
"%Y-%m-%dT%H:%MZ",
time.gmtime(self.starttime)), " - ", time.strftime(
"%Y-%m-%dT%H:%MZ", time.gmtime(self.endtime))
print "Number of traces:", self.samples
print "Number of unique routing vectors:", self.ipvectors
print "Traces reaching target IP address: ", self.completetraces
if (self.completetraces > 0):
print "Average hop count: %.2f" % (float(self.totalhopcount) /
self.completetraces)
else:
print "Average hop count:", "-"
print "Traces not ending at target IP", self.destnotreached
print
print
return
def report(self,detail):
"""
Output a report on the collected statistics
The 'detail' argument controls how much detail is provided
(more detail, longer reports)
"""
if not self.aggregationDone:
# aggregate the per probe results before reporting
self.aggregateProbeData()
host = dnsnamelookup(self.dst_addr)
nprobes = len(self.probeReport.keys())
if (detail==0):
if host:
print "Destination:", self.dst_addr, " / " , host
else:
print "Destination:", self.dst_addr
else:
print "Destination:", self.dst_addr
if host:
print "Reverse DNS:", host
print "Timeinterval:" , time.strftime("%Y-%m-%dT%H:%MZ",time.gmtime(self.starttime)), " - ", time.strftime("%Y-%m-%dT%H:%MZ",time.gmtime(self.endtime))
print "Number of traces:", self.samples
print "Number of unique routing vectors:", self.ipvectors
print "Traces reaching target IP address: ",self.completetraces
if (self.completetraces > 0):
print "Average hop count: %.2f" % (float(self.totalhopcount)/self.completetraces)
else:
print "Average hop count:", "-"
print "Traces not ending at target IP",self.destnotreached
print
print
return
def report(self,detail):
"""
Output a report on the collected statistics
The 'detail' argument controls how much detail is provided
(more detail, longer reports)
"""
if not self.aggregationDone:
# aggregate the per probe results before reporting
self.aggregateProbeData()
# Look for reverse DNS (if any)
host = dnsnamelookup(self.dst_addr)
if (detail==0):
if host:
print "Destination:", self.dst_addr, " / " , host
else:
print "Destination:", self.dst_addr
else:
print "Destination:", self.dst_addr
if host:
print "Reverse DNS:", host
nprobes = len(self.probeReport.keys())
if (self.packets_sent>0):
lost = 100 * (self.packets_sent - self.packets_rcvd)/float(self.packets_sent)
lost = "%.2f%%" % lost
else:
lost = "NA"
if (detail==0):
#minimal view; report median of the medians
if len(self.medianRtts) > 0:
numprobes = len(self.medianRtts)
level500 = int(numprobes * 0.5)
median = self.medianRtts[level500]
median = "%.2fms" % median
else:
median = "NA"
print "sent/received/loss/median %d/%d/%s/%s" % (self.packets_sent,self.packets_rcvd,lost,median)
else:
print "Timeinterval:" , time.strftime("%Y-%m-%dT%H:%MZ",time.gmtime(self.starttime)), " - ", time.strftime("%Y-%m-%dT%H:%MZ",time.gmtime(self.endtime))
print "Packets sent:", self.packets_sent
print "Packets received:", self.packets_rcvd
print "Overall loss rate: %s" % lost
print
print "Total probes measuring: %6d" % nprobes
print "Probes with 100%% errors:%6d" % self.allerrors
if len(self.errorMsgs)>0:
print 'Total errors on probes: %6d' % sum(self.errorMsgs.values())
print 'Most common error:"%s (%dx)"' % sorted(self.errorMsgs.items(),key=lambda x: x[1], reverse=True)[0]
if (nprobes > 1):
print
print "Probes with no packets lost: %6d" % self.lossless
print "Probes with 0%%-5%% loss: %6d" % self.loss0
print "Probes with 5%%-20%% loss: %6d" % self.loss5
print "Probes with 20%%-40%% loss: %6d" % self.loss20
print "Probes with 40%%-60%% loss: %6d" % self.loss40
print "Probes with 60%%-80%% loss: %6d" % self.loss60
print "Probes with 80%%-100%% loss: %6d" % self.loss80
print "Probes with 100%% loss: %6d" % self.loss100
print "Probes not sending any packets:%6d" % self.nodata
print
if len(self.medianRtts) > 0:
numprobes = len(self.medianRtts)
level025 = int(numprobes * 0.025)
level250 = int(numprobes * 0.25)
level500 = int(numprobes * 0.5)
level750 = int(numprobes * 0.75)
level975 = int(numprobes * 0.975)
print "RTT distributions:"
print "-----------------\n"
print '2.5 percentile ("Minimum")'
print "lowest 2.5 percentile RTT in all probes:%8.2fms" % self.minimumRtts[0]
print "2.5%% of probes had 2.5 percentile <= %8.2fms" % self.minimumRtts[level025]
print "25%% of probes had 2.5 percentile <= %8.2fms" % (self.minimumRtts[level250])
print "50%% of probes had 2.5 percentile <= %8.2fms" % (self.minimumRtts[level500])
print "75%% of probes had 2.5 percentile <= %8.2fms" % (self.minimumRtts[level750])
print "97.5%% of probes had 2.5 percentile <= %8.2fms" % (self.minimumRtts[level975])
print "highest 2.5 percentile in all probes %8.2fms" % (self.minimumRtts[numprobes-1])
print
print "Median"
print "lowest median RTT in all probes %9.2fms" % self.medianRtts[0]
print "2.5%% of probes had median RTT <= %9.2fms" % self.medianRtts[level025]
print "25%% of probes had median RTT <= %9.2fms" % (self.medianRtts[level250])
print "50%% of probes had median RTT <= %9.2fms" % (self.medianRtts[level500])
print "75%% of probes had median RTT <= %9.2fms" % (self.medianRtts[level750])
print "97.5%% of probes had median RTT <= %9.2fms" % (self.medianRtts[level975])
print "highest median RTT in all probes %9.2fms" % (self.medianRtts[numprobes-1])
print
print '97.5 percentile ("Maximum")'
print "lowest 97.5 percentile RTT in all probes:%8.2fms" % self.maximumRtts[0]
print "2.5%% of probes had 97.5 percentile <= %8.2fms" % self.maximumRtts[level025]
print "25%% of probes had 97.5 percentile <= %8.2fms" % (self.maximumRtts[level250])
print "50%% of probes had 97.5 percentile <= %8.2fms" % (self.maximumRtts[level500])
print "75%% of probes had 97.5 percentile <= %8.2fms" % (self.maximumRtts[level750])
print "97.5%% of probes had 97.5 percentile <= %8.2fms" % (self.maximumRtts[level975])
print "highest 97.5 percentile in all probes %8.2fms" % (self.maximumRtts[numprobes-1])
print
print
return
def report(self, detail):
"""
Output a report on the collected statistics
The 'detail' argument controls how much detail is provided
(more detail, longer reports)
"""
if not self.aggregationDone:
# aggregate the per probe results before reporting
self.aggregateProbeData()
# Look for reverse DNS (if any)
host = dnsnamelookup(self.dst_addr)
if detail == 0:
if host:
print "Destination:", self.dst_addr, " / ", host
else:
print "Destination:", self.dst_addr
else:
print "Destination:", self.dst_addr
if host:
print "Reverse DNS:", host
nprobes = len(self.probeReport.keys())
if self.packets_sent > 0:
lost = 100 * (self.packets_sent - self.packets_rcvd) / float(self.packets_sent)
lost = "%.2f%%" % lost
else:
lost = "NA"
if detail == 0:
# minimal view; report median of the medians
if len(self.medianRtts) > 0:
numprobes = len(self.medianRtts)
level500 = int(numprobes * 0.5)
median = self.medianRtts[level500]
median = "%.2fms" % median
else:
median = "NA"
print "sent/received/loss/median %d/%d/%s/%s" % (self.packets_sent, self.packets_rcvd, lost, median)
else:
print "Timeinterval:", time.strftime("%Y-%m-%dT%H:%MZ", time.gmtime(self.starttime)), " - ", time.strftime(
"%Y-%m-%dT%H:%MZ", time.gmtime(self.endtime)
)
print "Packets sent:", self.packets_sent
print "Packets received:", self.packets_rcvd
print "Overall loss rate: %s" % lost
print
print "Total probes measuring: %6d" % nprobes
print "Probes with 100%% errors:%6d" % self.allerrors
if len(self.errorMsgs) > 0:
print "Total errors on probes: %6d" % sum(self.errorMsgs.values())
print 'Most common error:"%s (%dx)"' % sorted(self.errorMsgs.items(), key=lambda x: x[1], reverse=True)[
0
]
if nprobes > 1:
print
print "Probes with no packets lost: %6d" % self.lossless
print "Probes with 0%%-5%% loss: %6d" % self.loss0
print "Probes with 5%%-20%% loss: %6d" % self.loss5
print "Probes with 20%%-40%% loss: %6d" % self.loss20
print "Probes with 40%%-60%% loss: %6d" % self.loss40
print "Probes with 60%%-80%% loss: %6d" % self.loss60
print "Probes with 80%%-100%% loss: %6d" % self.loss80
print "Probes with 100%% loss: %6d" % self.loss100
print "Probes not sending any packets:%6d" % self.nodata
print
if len(self.medianRtts) > 0:
numprobes = len(self.medianRtts)
level025 = int(numprobes * 0.025)
level250 = int(numprobes * 0.25)
level500 = int(numprobes * 0.5)
level750 = int(numprobes * 0.75)
level975 = int(numprobes * 0.975)
print "RTT distributions:"
print "-----------------\n"
print '2.5 percentile ("Minimum")'
print "lowest 2.5 percentile RTT in all probes:%8.2fms" % self.minimumRtts[0]
print "2.5%% of probes had 2.5 percentile <= %8.2fms" % self.minimumRtts[level025]
print "25%% of probes had 2.5 percentile <= %8.2fms" % (self.minimumRtts[level250])
print "50%% of probes had 2.5 percentile <= %8.2fms" % (self.minimumRtts[level500])
print "75%% of probes had 2.5 percentile <= %8.2fms" % (self.minimumRtts[level750])
print "97.5%% of probes had 2.5 percentile <= %8.2fms" % (self.minimumRtts[level975])
print "highest 2.5 percentile in all probes %8.2fms" % (self.minimumRtts[numprobes - 1])
print
print "Median"
print "lowest median RTT in all probes %9.2fms" % self.medianRtts[0]
print "2.5%% of probes had median RTT <= %9.2fms" % self.medianRtts[level025]
print "25%% of probes had median RTT <= %9.2fms" % (self.medianRtts[level250])
print "50%% of probes had median RTT <= %9.2fms" % (self.medianRtts[level500])
print "75%% of probes had median RTT <= %9.2fms" % (self.medianRtts[level750])
print "97.5%% of probes had median RTT <= %9.2fms" % (self.medianRtts[level975])
print "highest median RTT in all probes %9.2fms" % (self.medianRtts[numprobes - 1])
print
print '97.5 percentile ("Maximum")'
print "lowest 97.5 percentile RTT in all probes:%8.2fms" % self.maximumRtts[0]
print "2.5%% of probes had 97.5 percentile <= %8.2fms" % self.maximumRtts[level025]
print "25%% of probes had 97.5 percentile <= %8.2fms" % (self.maximumRtts[level250])
print "50%% of probes had 97.5 percentile <= %8.2fms" % (self.maximumRtts[level500])
print "75%% of probes had 97.5 percentile <= %8.2fms" % (self.maximumRtts[level750])
print "97.5%% of probes had 97.5 percentile <= %8.2fms" % (self.maximumRtts[level975])
print "highest 97.5 percentile in all probes %8.2fms" % (self.maximumRtts[numprobes - 1])
print
print
return
