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authorTibor Frank <tifrank@cisco.com>2018-04-13 09:40:18 +0200
committerTibor Frank <tifrank@cisco.com>2018-04-13 09:41:45 +0200
commit482bb432e9607bce6cb92d41bf9e299c0e2fc288 (patch)
tree83f417e7c98d3e0773a38f923eb7c90513fc9b9f /resources/tools/presentation/generator_tables.py
parent295a68551716af397597bc721d6a3115572009f9 (diff)
CSIT-1041: Trending dashboard
Change-Id: Ie98b7b8885575be408686b4eec5b539f3bb68d1d Signed-off-by: Tibor Frank <tifrank@cisco.com>
Diffstat (limited to 'resources/tools/presentation/generator_tables.py')
-rw-r--r--resources/tools/presentation/generator_tables.py27
1 files changed, 15 insertions, 12 deletions
diff --git a/resources/tools/presentation/generator_tables.py b/resources/tools/presentation/generator_tables.py
index 9f0096557e..65bf6d562e 100644
--- a/resources/tools/presentation/generator_tables.py
+++ b/resources/tools/presentation/generator_tables.py
@@ -567,7 +567,7 @@ def table_performance_trending_dashboard(table, input_data):
try:
tbl_dict[tst_name]["data"]. \
append(tst_data["result"]["throughput"])
- except TypeError:
+ except (TypeError, KeyError):
pass # No data in output.xml for this test
tbl_lst = list()
@@ -579,7 +579,8 @@ def table_performance_trending_dashboard(table, input_data):
# Test name:
name = tbl_dict[tst_name]["name"]
# Throughput trend:
- trend = list(pd_data.rolling(window=win_size).median())[-2]
+ trend = list(pd_data.rolling(window=win_size, min_periods=2).
+ median())[-2]
# Anomaly:
t_data, _ = find_outliers(pd_data)
last = list(t_data)[-1]
@@ -593,16 +594,18 @@ def table_performance_trending_dashboard(table, input_data):
anomaly = "progression"
else:
anomaly = "normal"
- # Change:
- change = round(float(last - trend) / 1000000, 2)
- # Relative change:
- rel_change = int(relative_change(float(trend), float(last)))
-
- tbl_lst.append([name,
- round(float(last) / 1000000, 2),
- change,
- rel_change,
- anomaly])
+
+ if not isnan(last) and not isnan(trend):
+ # Change:
+ change = round(float(last - trend) / 1000000, 2)
+ # Relative change:
+ rel_change = int(relative_change(float(trend), float(last)))
+
+ tbl_lst.append([name,
+ round(float(last) / 1000000, 2),
+ change,
+ rel_change,
+ anomaly])
# Sort the table according to the relative change
tbl_lst.sort(key=lambda rel: rel[-2], reverse=True)