Register metric Histogram names.

telemetry/telemetry/web_perf/timeline_based_measurement.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 collections
 import logging
 from collections import defaultdict
 
 from tracing.metrics import metric_runner
 
 from telemetry.timeline import chrome_trace_category_filter
@@ skipping 266 matching lines @@
     if self._tbm_options.config.enable_chrome_trace:
       # Always enable 'blink.console' category for:
       # 1) Backward compat of chrome clock sync (crbug.com/646925)
       # 2) Allows users to add trace event through javascript.
       # Note that blink.console is extremely low-overhead, so this doesn't
       # affect the tracing overhead budget much.
       chrome_config = self._tbm_options.config.chrome_trace_config
       chrome_config.category_filter.AddIncludedCategory('blink.console')
     platform.tracing_controller.StartTracing(self._tbm_options.config)
 
+  def GetTimelineBasedMetrics(self):
+    return self._tbm_options.GetTimelineBasedMetrics()
+
   def Measure(self, platform, results):
     """Collect all possible metrics and added them to results."""
     platform.tracing_controller.telemetry_info = results.telemetry_info
     trace_result = platform.tracing_controller.StopTracing()
     trace_value = trace.TraceValue(results.current_page, trace_result)
     results.AddValue(trace_value)
 
-    try:
-      if self._tbm_options.GetTimelineBasedMetrics():
-        assert not self._tbm_options.GetLegacyTimelineBasedMetrics(), (
-            'Specifying both TBMv1 and TBMv2 metrics is not allowed.')
-        self._ComputeTimelineBasedMetrics(results, trace_value)
+    if self.GetTimelineBasedMetrics():
+      self._ComputeTimelineBasedMetrics(results, trace_value)
+      # Legacy metrics can be computed, but only if explicitly specified.
+      if self._tbm_options.GetLegacyTimelineBasedMetrics():
+        # Since this imports the trace model in python, it will also clean up
+        # the trace handles for us.
+        self._ComputeLegacyTimelineBasedMetrics(results, trace_result)
       else:
         # Run all TBMv1 metrics if no other metric is specified
         # (legacy behavior)
         if not self._tbm_options.GetLegacyTimelineBasedMetrics():
           logging.warn('Please specify the TBMv1 metrics you are interested in '
                        'explicitly. This implicit functionality will be removed'
                        ' on July 17, 2016.')
           self._tbm_options.SetLegacyTimelineBasedMetrics(
               _GetAllLegacyTimelineBasedMetrics())
         self._ComputeLegacyTimelineBasedMetrics(results, trace_result)
     finally:
       trace_result.CleanUpAllTraces()
 
   def DidRunStory(self, platform):
     """Clean up after running the story."""
     if platform.tracing_controller.is_tracing_running:
       platform.tracing_controller.StopTracing()
 
   def _ComputeTimelineBasedMetrics(self, results, trace_value):
-    metrics = self._tbm_options.GetTimelineBasedMetrics()
+    metrics = self.GetTimelineBasedMetrics()
     extra_import_options = {
       'trackDetailedModelStats': True
     }
 
     mre_result = metric_runner.RunMetric(
         trace_value.filename, metrics, extra_import_options)
     page = results.current_page
 
     failure_dicts = mre_result.failures
     for d in failure_dicts:
@@ skipping 20 matching lines @@
 
     for renderer_thread, interaction_records in (
         threads_to_records_map.iteritems()):
       meta_metrics = _TimelineBasedMetrics(
           model, renderer_thread, interaction_records, self._results_wrapper,
           all_metrics)
       meta_metrics.AddResults(results)
 
     for metric in all_metrics:
       metric.AddWholeTraceResults(model, results)