Implements peer connection stats measurements in WebRTC call test.

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
+
+from metrics import Metric
+from telemetry.core import camel_case
+from telemetry.value import list_of_scalar_values
+
+INTERESTING_METRICS = {
+    'packetsReceived': {
+        'units': 'packets',
+        'description': 'Packets received by the peer connection',
+    },
+    'packetsSent': {
+        'units': 'packets',
+        'description': 'Packets sent by the peer connection',
+    },
+    'googDecodeMs': {
+        'units': 'ms',
+        'description': 'Time spent decoding.',
+    },
+    'googMaxDecodeMs': {
+        'units': 'ms',
+        'description': 'Maximum time spent decoding one frame.',
+    },
+    # TODO(phoglund): Add much more interesting metrics.
+}
+
+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
+        time_series.setdefault(stat_name, []).append(float(value))
+
+  return time_series
+
+
+class WebRtcStatisticsMetric(Metric):
+  """Makes it possible to measure stats from peer connections."""
+
+  def __init__(self):
+    super(WebRtcStatisticsMetric, self).__init__()
+    self._all_reports = None
+
+  def Start(self, page, tab):
+    pass
+
+  def Stop(self, page, tab):
+    """Digs out stats from data populated by the javascript in webrtc_cases."""
+    self._all_reports = tab.EvaluateJavaScript(
+        'JSON.stringify(window.peerConnectionReports)')
+
+  def AddResults(self, tab, results):
+    if not self._all_reports:
+      return
+
+    reports = json.loads(self._all_reports)
+    for i, report in enumerate(reports):
+      time_series = SortStatsIntoTimeSeries(report)
+
+      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)
+        results.AddValue(list_of_scalar_values.ListOfScalarValues(
+            results.current_page, trace_name,
+            INTERESTING_METRICS[stat_name]['units'], values,
+            description=INTERESTING_METRICS[stat_name]['description'],
+            important=False))