Added unittest for adjust_upper_limit script

This change adds some unittests for adjust_upper_limit script used by rendering
representative pertf tests.

Bug: chromium:1052361
Change-Id: I5850b5ca888d6dca7318277ca8bd6eb4bdf40a56
Reviewed-on: https://chromium-review.googlesource.com/c/chromium/src/+/2283660Reviewed-by: John Chen <johnchen@chromium.org>
Commit-Queue: Behdad Bakhshinategh <behdadb@chromium.org>
Cr-Commit-Position: refs/heads/master@{#788776}

tools/perf/experimental/representative_perf_test_limit_adjuster/adjust_upper_limits.py

@@ -86,21 +86,21 @@ def FetchItemData(task_id, benchmark, index, temp_dir):
     print("CSV results were not produced!")
 
 
-def GetPercentileValues(benchmark, tags, limit, percentile):
-  """Get the percentile value of recent runs described by given tags.
+def CreateDataframe(benchmark, tags, limit):
+  """Creates the dataframe of values recorded in recent runs.
 
   Given the tags, benchmark this function fetches the data of last {limit}
-  runs, and find the percentile value for each story.
+  runs, and returns a dataframe of values for focused metrics such as
+  frame_times and CPU_wall_time_ratio.
 
   Args:
     benchmark: The benchmark these task are on (desktop/mobile).
     tags: The tags which describe the tasks such as OS and buildername.
     limit: The number of runs to look at.
-    percentile: the percentile to return.
 
   Returns:
-    A dictionary with averages and confidence interval ranges calculated
-    from the percentile of recent runs.
+    A dataframe with averages and confidence interval of frame_times, and
+    average value of CPU_wall_time_ratio of each story of each run.
   """
   items = []
   for tag_set in tags:
@@ -114,7 +114,21 @@ def GetPercentileValues(benchmark, tags, limit, percentile):
       idx += 1
   finally:
     shutil.rmtree(temp_dir)
-  data_frame = pandas.concat(dfs, ignore_index=True)
+  return pandas.concat(dfs, ignore_index=True)
+
+
+def GetPercentileValues(data_frame, percentile):
+  """Get the percentile value of each metric for recorded values in dataframe.
+
+  Args:
+    data_frame: The dataframe with averages and confidence intervals of each
+    story of each run.
+    percentile: the percentile to use for determining the upper limits.
+
+  Returns:
+    A dictionary with averages and confidence interval ranges calculated
+    from the percentile of recent runs.
+  """
 
   if not data_frame.empty:
     avg_df = data_frame.pivot(index='stories', columns='index', values='avg')
@@ -177,9 +191,10 @@ def RecalculateUpperLimits(data_point_count):
   for platform in platform_specific_tags:
     platform_data = platform_specific_tags[platform]
     print('\n- Processing data ({})'.format(platform))
-    results[platform] = GetPercentileValues(
-      platform_data['benchmark'], platform_data['tags'],
-      data_point_count, 0.95)
+
+    dataframe = CreateDataframe(platform_data['benchmark'],
+                                platform_data['tags'], data_point_count)
+    results[platform] = GetPercentileValues(dataframe, 0.95)
 
     # Loop over results and adjust base on current values.
     for story in results[platform]:

tools/perf/experimental/representative_perf_test_limit_adjuster/adjust_upper_limits_unittest.py

+# Copyright 2020 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 adjust_upper_limits
+import pandas as pd
+import os
+import sys
+import unittest
+
+
+def create_sample_dataframe(story_name, count, avg_start, avg_step, ci_start,
+                            ci_step, cpu_wal_start, cpu_wall_step):
+  cols = ['stories', 'avg', 'ci_095', 'cpu_wall_time_ratio', 'index']
+  df = pd.DataFrame(columns=cols)
+  for idx in range(count):
+    avg = avg_start + idx * avg_step
+    ci = ci_start + idx * ci_step
+    cpu_wall = cpu_wal_start + idx * cpu_wall_step
+    df = df.append(
+        {
+            'stories': story_name,
+            'avg': avg,
+            'ci_095': ci,
+            'cpu_wall_time_ratio': cpu_wall,
+            'index': idx
+        },
+        ignore_index=True)
+  return df
+
+
+class TestAdjustUpperLimits(unittest.TestCase):
+  def test_get_percentile_values(self):
+    dataframe = create_sample_dataframe('story_name', 21, 16.0, 0.5, 0.2, 0.01,
+                                        0.2, 0.01)
+    limits = adjust_upper_limits.GetPercentileValues(dataframe, 0.95)
+
+    # Given values for avg: [16, 16.5, 17, ..., 25.5, 26]
+    self.assertEquals(limits['story_name']['avg'], 25.5)
+
+    # Given values for ci_095: [0.2, 0.21, 0.22, ..., 0.39, 0.4]
+    self.assertEquals(limits['story_name']['ci_095'], 0.39)
+
+    # Given values for cpu_wall_time_ratio: [0.2, 0.21, 0.22, ..., 0.39, 0.4]
+    self.assertEquals(limits['story_name']['cpu_wall_time_ratio'], 0.21)