telemetry: Remove gaps between interactions when calculating smoothness metrics.

tools/telemetry/telemetry/web_perf/metrics/smoothness.py

Index: tools/telemetry/telemetry/web_perf/metrics/smoothness.py
diff --git a/tools/telemetry/telemetry/web_perf/metrics/smoothness.py b/tools/telemetry/telemetry/web_perf/metrics/smoothness.py
index f63fea8bed3b45ec5c6ceaab2248f226f85c7e76..127e0ad05ec0487d5f0fda81284836ab0ba80c06 100644
--- a/tools/telemetry/telemetry/web_perf/metrics/smoothness.py
+++ b/tools/telemetry/telemetry/web_perf/metrics/smoothness.py
@@ -87,6 +87,21 @@ class SmoothnessMetric(timeline_based_metric.TimelineBasedMetric):
                 if d / refresh_period >= min_normalized_delta]
     return (deltas, [delta / refresh_period for delta in deltas])
 
+  @staticmethod
+  def _JoinTimestampRanges(frame_timestamps):
+    """Joins ranges of timestamps, adjusting timestamps to remove deltas
+    between the start of a range and the end of the prior range.
+    """
+    timestamps = []
+    for timestamp_range in frame_timestamps:
+      if len(timestamps) == 0:
+        timestamps.extend(timestamp_range)
+      else:
+        for i in range(1, len(timestamp_range)):
+          timestamps.append(timestamps[-1] +
+              timestamp_range[i] - timestamp_range[i-1])
+    return timestamps
+
   def _ComputeSurfaceFlingerMetric(self, page, stats):
     jank_count = None
     avg_surface_fps = None
@@ -94,7 +109,7 @@ class SmoothnessMetric(timeline_based_metric.TimelineBasedMetric):
     frame_lengths = None
     none_value_reason = None
     if self._HasEnoughFrames(stats.frame_timestamps):

[mithro-old, 2015/04/21 03:45:58]

Why does this metric use stats.frame_timestamps rather than stats.frame_times?
Looking at your unittest the stats.frame_times contains the already calculated
value you need?

[vmiura, 2015/04/21 22:04:46]

I think you're right, it looks like these metrics could be computed from
frame_times.

-      timestamps = FlattenList(stats.frame_timestamps)
+      timestamps = self._JoinTimestampRanges(stats.frame_timestamps)
       frame_count = len(timestamps)
       milliseconds = timestamps[-1] - timestamps[0]
       min_normalized_frame_length = 0.5