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Trending: Reduce input data
[csit.git]
/
resources
/
tools
/
presentation
/
generator_tables.py
diff --git
a/resources/tools/presentation/generator_tables.py
b/resources/tools/presentation/generator_tables.py
index
acd3024
..
3bfae47
100644
(file)
--- a/
resources/tools/presentation/generator_tables.py
+++ b/
resources/tools/presentation/generator_tables.py
@@
-551,7
+551,7
@@
def table_soak_vs_ndr(table, input_data):
"{0} Stdev [Mpps]".format(table["reference"]["title"]),
"{0} Throughput [Mpps]".format(table["compare"]["title"]),
"{0} Stdev [Mpps]".format(table["compare"]["title"]),
"{0} Stdev [Mpps]".format(table["reference"]["title"]),
"{0} Throughput [Mpps]".format(table["compare"]["title"]),
"{0} Stdev [Mpps]".format(table["compare"]["title"]),
- "Delta [%]"]
+ "Delta [%]"
, "Stdev of delta [%]"
]
header_str = ",".join(header) + "\n"
except (AttributeError, KeyError) as err:
logging.error("The model is invalid, missing parameter: {0}".
header_str = ",".join(header) + "\n"
except (AttributeError, KeyError) as err:
logging.error("The model is invalid, missing parameter: {0}".
@@
-612,7
+612,8
@@
def table_soak_vs_ndr(table, input_data):
if data_r:
data_r_mean = mean(data_r)
item.append(round(data_r_mean / 1000000, 2))
if data_r:
data_r_mean = mean(data_r)
item.append(round(data_r_mean / 1000000, 2))
- item.append(round(stdev(data_r) / 1000000, 2))
+ data_r_stdev = stdev(data_r)
+ item.append(round(data_r_stdev / 1000000, 2))
else:
data_r_mean = None
item.extend([None, None])
else:
data_r_mean = None
item.extend([None, None])
@@
-620,12
+621,17
@@
def table_soak_vs_ndr(table, input_data):
if data_c:
data_c_mean = mean(data_c)
item.append(round(data_c_mean / 1000000, 2))
if data_c:
data_c_mean = mean(data_c)
item.append(round(data_c_mean / 1000000, 2))
- item.append(round(stdev(data_c) / 1000000, 2))
+ data_c_stdev = stdev(data_c)
+ item.append(round(data_c_stdev / 1000000, 2))
else:
data_c_mean = None
item.extend([None, None])
if data_r_mean and data_c_mean is not None:
item.append(round(relative_change(data_r_mean, data_c_mean), 2))
else:
data_c_mean = None
item.extend([None, None])
if data_r_mean and data_c_mean is not None:
item.append(round(relative_change(data_r_mean, data_c_mean), 2))
+ delta, d_stdev = relative_change_stdev(
+ data_r_mean, data_c_mean, data_r_stdev, data_c_stdev)
+ item.append(round(delta, 2))
+ item.append(round(d_stdev, 2))
tbl_lst.append(item)
# Sort the table according to the relative change
tbl_lst.append(item)
# Sort the table according to the relative change