Relax an overly sensentive check in webrtc_stats.py.

tools/perf/metrics/webrtc_stats.py

 # Copyright 2014 The Chromium Authors. All rights reserved.
 # Use of this source code is governed by a BSD-style license that can be
 # found in the LICENSE file.
 
 import json
 import logging
 import re
 
 from metrics import Metric
 from telemetry.core import camel_case
@@ skipping 19 matching lines @@
     # TODO(phoglund): Add much more interesting metrics.
 }
 
 
 def GetReportKind(report):
   if 'audioInputLevel' in report or 'audioOutputLevel' in report:
     return 'audio'
   if 'googFrameRateSent' in report or 'googFrameRateReceived' in report:
     return 'video'
 
-  logging.error('Did not recognize report batch: %s.', report.keys())
+  logging.debug('Did not recognize report batch: %s.', report.keys())
+  # There are other kinds of reports, such as bwestats, which we don't care
+  # about here. For these cases just return 'unknown' which will ignore the
+  # report
   return 'unknown'
 
 
 def DistinguishAudioAndVideo(report, stat_name):
   return GetReportKind(report) + '_' + stat_name
 
 
 def StripAudioVideoDistinction(stat_name):
   return re.sub('^(audio|video)_', '', stat_name)
 
 
 def SortStatsIntoTimeSeries(report_batches):
   time_series = {}
   for report_batch in report_batches:
     for report in report_batch:
       for stat_name, value in report.iteritems():
         if stat_name not in INTERESTING_METRICS:
           continue
+        if GetReportKind(report) == 'unknown':
+          continue
         full_stat_name = DistinguishAudioAndVideo(report, stat_name)
         time_series.setdefault(full_stat_name, []).append(float(value))
 
   return time_series
 
 
 class WebRtcStatisticsMetric(Metric):
   """Makes it possible to measure stats from peer connections."""
 
   def __init__(self):
@@ skipping 18 matching lines @@
 
       for stat_name, values in time_series.iteritems():
         stat_name_underscored = camel_case.ToUnderscore(stat_name)
         trace_name = 'peer_connection_%d_%s' % (i, stat_name_underscored)
         general_name = StripAudioVideoDistinction(stat_name)
         results.AddValue(list_of_scalar_values.ListOfScalarValues(
             results.current_page, trace_name,
             INTERESTING_METRICS[general_name]['units'], values,
             description=INTERESTING_METRICS[general_name]['description'],
             important=False))