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authorTibor Frank <tifrank@cisco.com>2018-04-26 14:11:11 +0200
committerTibor Frank <tifrank@cisco.com>2018-04-26 14:12:19 +0200
commit52cb667958d954d6233d0865a59d90cca82db026 (patch)
tree74f327202d9e92b98feb381648b140ac72569775
parent0740688e5798f7ab7162fd7f4bc5eb8455164a7c (diff)
Report: Add historical data to performance changes table
Change-Id: If7bce2c86b2fb352368c433c5db81a4a4bc976ed Signed-off-by: Tibor Frank <tifrank@cisco.com>
-rw-r--r--resources/tools/presentation/generator_tables.py19
-rw-r--r--resources/tools/presentation/utils.py2
2 files changed, 10 insertions, 11 deletions
diff --git a/resources/tools/presentation/generator_tables.py b/resources/tools/presentation/generator_tables.py
index 96930cddb6..92f0ceed45 100644
--- a/resources/tools/presentation/generator_tables.py
+++ b/resources/tools/presentation/generator_tables.py
@@ -432,18 +432,17 @@ def table_performance_comparison(table, input_data):
for tst_name in tbl_dict.keys():
item = [tbl_dict[tst_name]["name"], ]
if history:
- for hist_list in tbl_dict[tst_name]["history"].values():
- for hist_data in hist_list:
- if hist_data:
- data_t = remove_outliers(
- hist_data, outlier_const=table["outlier-const"])
- if data_t:
- item.append(round(mean(data_t) / 1000000, 2))
- item.append(round(stdev(data_t) / 1000000, 2))
- else:
- item.extend([None, None])
+ for hist_data in tbl_dict[tst_name]["history"].values():
+ if hist_data:
+ data_t = remove_outliers(
+ hist_data, outlier_const=table["outlier-const"])
+ if data_t:
+ item.append(round(mean(data_t) / 1000000, 2))
+ item.append(round(stdev(data_t) / 1000000, 2))
else:
item.extend([None, None])
+ else:
+ item.extend([None, None])
if tbl_dict[tst_name]["ref-data"]:
data_t = remove_outliers(tbl_dict[tst_name]["ref-data"],
outlier_const=table["outlier-const"])
diff --git a/resources/tools/presentation/utils.py b/resources/tools/presentation/utils.py
index 88baf95928..df543c17ea 100644
--- a/resources/tools/presentation/utils.py
+++ b/resources/tools/presentation/utils.py
@@ -87,7 +87,7 @@ def remove_outliers(input_list, outlier_const=1.5, window=14):
iqr = (upper_quartile - lower_quartile) * outlier_const
quartile_set = (lower_quartile - iqr, upper_quartile + iqr)
result_lst = list()
- for y in data.tolist():
+ for y in input_list:
if quartile_set[0] <= y <= quartile_set[1]:
result_lst.append(y)
return result_lst