diff options
| -rwxr-xr-x | tools/profile_analyzer/profile_analyzer.py | 20 |
1 files changed, 12 insertions, 8 deletions
diff --git a/tools/profile_analyzer/profile_analyzer.py b/tools/profile_analyzer/profile_analyzer.py index 632aeffd3c..bd3181b4ee 100755 --- a/tools/profile_analyzer/profile_analyzer.py +++ b/tools/profile_analyzer/profile_analyzer.py @@ -65,9 +65,9 @@ class ImportantMark(object): def entry(self): return self._entry - def append_post_entry(self, entry): - if self._n > 0: - self._post_stack.append(entry) + def append_post_entry(self, post_entry): + if self._n > 0 and post_entry.thread == self._entry.thread: + self._post_stack.append(post_entry) self._n -= 1 def get_deltas(self): @@ -112,25 +112,29 @@ def entries(): threads = collections.defaultdict(lambda: collections.defaultdict(list)) times = collections.defaultdict(list) important_marks = collections.defaultdict(list) +stack_depth = 0 for entry in entries(): thread = threads[entry.thread] if entry.type == '{': thread[entry.tag].append(entry) + stack_depth += 1 if entry.type == '!': # Save a snapshot of the current stack inside a new ImportantMark instance. - # Get all entries with type '{' from "thread". - stack = [e for entries_for_tag in thread.values() - for e in entries_for_tag if e.type == '{'] - imark_group_key = '{tag}@{file}:{line}'.format(**entry._asdict()) + # Get all entries _for any tag in the thread_. + stack = [e for entries_for_tag in thread.itervalues() + for e in entries_for_tag] + imark_group_key = '{tag}/{thread}@{file}:{line}'.format(**entry._asdict()) important_marks[imark_group_key].append(ImportantMark(entry, stack)) elif entry.type == '}': last = thread[entry.tag].pop() times[entry.tag].append(entry.time - last.time) # Update accounting for important marks. for imarks_group in important_marks.itervalues(): - for imark in imarks_group: + # only access the last "stack_depth" imarks. + for imark in imarks_group[-stack_depth:]: imark.append_post_entry(entry) + stack_depth -= 1 def percentile(vals, percent): """ Calculates the interpolated percentile given a sorted sequence and a |