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authorTibor Frank <tifrank@cisco.com>2018-04-15 19:04:35 +0200
committerTibor Frank <tifrank@cisco.com>2018-04-15 19:04:35 +0200
commit29035746be0145db942832b55555b695da2323d7 (patch)
tree16e9ee75d5b4d4c44f4bf5b7a1a661e463943ca0 /resources/tools
parent4914a78f593124788c754695b79be146c3916c6f (diff)
CSIT-1041: Trending dashboard
Change-Id: I74b2c5d56ccf764868759fd5d7f2301d4ad3d725 Signed-off-by: Tibor Frank <tifrank@cisco.com>
Diffstat (limited to 'resources/tools')
-rw-r--r--resources/tools/presentation/generator_tables.py27
1 files changed, 17 insertions, 10 deletions
diff --git a/resources/tools/presentation/generator_tables.py b/resources/tools/presentation/generator_tables.py
index 81f022ea47..a5a8824dc9 100644
--- a/resources/tools/presentation/generator_tables.py
+++ b/resources/tools/presentation/generator_tables.py
@@ -548,9 +548,9 @@ def table_performance_trending_dashboard(table, input_data):
# Prepare the header of the tables
header = ["Test case",
"Thput trend [Mpps]",
- "Change [Mpps]",
+ "Anomaly [Mpps]",
"Change [%]",
- "Anomaly"]
+ "Classification"]
header_str = ",".join(header) + "\n"
# Prepare data to the table:
@@ -587,14 +587,14 @@ def table_performance_trending_dashboard(table, input_data):
t_stdev = list(t_data.rolling(window=win_size, min_periods=2).
std())[-2]
if isnan(last):
- anomaly = "outlier"
+ classification = "outlier"
last = list(pd_data)[-1]
elif last < (trend - 3 * t_stdev):
- anomaly = "regression"
+ classification = "regression"
elif last > (trend + 3 * t_stdev):
- anomaly = "progression"
+ classification = "progression"
else:
- anomaly = "normal"
+ classification = "normal"
if not isnan(last) and not isnan(trend) and trend != 0:
# Change:
@@ -604,19 +604,26 @@ def table_performance_trending_dashboard(table, input_data):
tbl_lst.append([name,
round(float(trend) / 1000000, 2),
- change,
+ last,
rel_change,
- anomaly])
+ classification])
# Sort the table according to the relative change
- tbl_lst.sort(key=lambda rel: rel[-2], reverse=True)
+ # tbl_lst.sort(key=lambda rel: rel[-2], reverse=True)
+
+ # Sort the table according to the classification
+ tbl_sorted = list()
+ for classification in ("regression", "outlier", "progression", "normal"):
+ tbl_tmp = [item for item in tbl_lst if item[4] == classification]
+ tbl_tmp.sort(key=lambda rel: rel[0])
+ tbl_sorted.extend(tbl_tmp)
file_name = "{0}.{1}".format(table["output-file"], table["output-file-ext"])
logging.info(" Writing file: '{0}'".format(file_name))
with open(file_name, "w") as file_handler:
file_handler.write(header_str)
- for test in tbl_lst:
+ for test in tbl_sorted:
file_handler.write(",".join([str(item) for item in test]) + '\n')
txt_file_name = "{0}.txt".format(table["output-file"])