from numpy import nan, isnan
-from pal_utils import mean, stdev, relative_change, classify_anomalies, \
+from pal_utils import mean, stdev, classify_anomalies, \
convert_csv_to_pretty_txt, relative_change_stdev
f"{table[u'reference'][u'title']} Stdev [Mpps]",
f"{table[u'compare'][u'title']} {hdr_param} [Mpps]",
f"{table[u'compare'][u'title']} Stdev [Mpps]",
- u"Delta [%]"
+ u"Delta [%]",
+ u"Stdev of delta [%]"
]
)
header_str = u",".join(header) + u"\n"
item.extend([u"Not tested", u"Not tested"])
else:
item.extend([u"Not tested", u"Not tested"])
- data_t = tbl_dict[tst_name][u"ref-data"]
- if data_t:
- item.append(round(mean(data_t) / 1000000, 2))
- item.append(round(stdev(data_t) / 1000000, 2))
+ data_r = tbl_dict[tst_name][u"ref-data"]
+ if data_r:
+ data_r_mean = mean(data_r)
+ item.append(round(data_r_mean / 1000000, 2))
+ data_r_stdev = stdev(data_r)
+ item.append(round(data_r_stdev / 1000000, 2))
else:
+ data_r_mean = None
+ data_r_stdev = None
item.extend([u"Not tested", u"Not tested"])
- data_t = tbl_dict[tst_name][u"cmp-data"]
- if data_t:
- item.append(round(mean(data_t) / 1000000, 2))
- item.append(round(stdev(data_t) / 1000000, 2))
+ data_c = tbl_dict[tst_name][u"cmp-data"]
+ if data_c:
+ data_c_mean = mean(data_c)
+ item.append(round(data_c_mean / 1000000, 2))
+ data_c_stdev = stdev(data_c)
+ item.append(round(data_c_stdev / 1000000, 2))
else:
+ data_c_mean = None
+ data_c_stdev = None
item.extend([u"Not tested", u"Not tested"])
if item[-2] == u"Not tested":
pass
# elif topo == u"2n-skx" and u"dot1q" in tbl_dict[tst_name][u"name"]:
# item.append(u"See footnote [1]")
# footnote = True
- elif item[-4] != 0:
- item.append(int(relative_change(float(item[-4]), float(item[-2]))))
+ elif data_r_mean and data_c_mean:
+ 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))
if (len(item) == len(header)) and (item[-3] != u"Not tested"):
tbl_lst.append(item)
f"{table[u'reference'][u'title']} Stdev [Mpps]",
f"{table[u'compare'][u'title']} {hdr_param} [Mpps]",
f"{table[u'compare'][u'title']} Stdev [Mpps]",
- u"Delta [%]"
+ u"Delta [%]",
+ u"Stdev of delta [%]"
]
)
header_str = u",".join(header) + u"\n"
item.extend([u"Not tested", u"Not tested"])
else:
item.extend([u"Not tested", u"Not tested"])
- data_t = tbl_dict[tst_name][u"ref-data"]
- if data_t:
- item.append(round(mean(data_t) / 1000000, 2))
- item.append(round(stdev(data_t) / 1000000, 2))
+ data_r = tbl_dict[tst_name][u"ref-data"]
+ if data_r:
+ data_r_mean = mean(data_r)
+ item.append(round(data_r_mean / 1000000, 2))
+ data_r_stdev = stdev(data_r)
+ item.append(round(data_r_stdev / 1000000, 2))
else:
+ data_r_mean = None
+ data_r_stdev = None
item.extend([u"Not tested", u"Not tested"])
- data_t = tbl_dict[tst_name][u"cmp-data"]
- if data_t:
- item.append(round(mean(data_t) / 1000000, 2))
- item.append(round(stdev(data_t) / 1000000, 2))
+ data_c = tbl_dict[tst_name][u"cmp-data"]
+ if data_c:
+ data_c_mean = mean(data_c)
+ item.append(round(data_c_mean / 1000000, 2))
+ data_c_stdev = stdev(data_c)
+ item.append(round(data_c_stdev / 1000000, 2))
else:
+ data_c_mean = None
+ data_c_stdev = None
item.extend([u"Not tested", u"Not tested"])
if item[-2] == u"Not tested":
pass
# elif topo == u"2n-skx" and u"dot1q" in tbl_dict[tst_name][u"name"]:
# item.append(u"See footnote [1]")
# footnote = True
- elif item[-4] != 0:
- item.append(int(relative_change(float(item[-4]), float(item[-2]))))
+ elif data_r_mean and data_c_mean:
+ 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))
if (len(item) == len(header)) and (item[-3] != u"Not tested"):
tbl_lst.append(item)
f"{table[u'reference'][u'title']} Stdev [Mpps]",
f"{table[u'compare'][u'title']} {hdr_param} [Mpps]",
f"{table[u'compare'][u'title']} Stdev [Mpps]",
- u"Delta [%]"
+ u"Delta [%]",
+ u"Stdev of delta [%]"
]
)
u"cmp-data": list()
}
try:
- result = None
if table[u"include-tests"] == u"MRR":
result = tst_data[u"result"][u"receive-rate"]
elif table[u"include-tests"] == u"PDR":
tbl_lst = list()
for tst_name in tbl_dict:
item = [tbl_dict[tst_name][u"name"], ]
- data_t = tbl_dict[tst_name][u"ref-data"]
- if data_t:
- item.append(round(mean(data_t) / 1000000, 2))
- item.append(round(stdev(data_t) / 1000000, 2))
+ data_r = tbl_dict[tst_name][u"ref-data"]
+ if data_r:
+ data_r_mean = mean(data_r)
+ item.append(round(data_r_mean / 1000000, 2))
+ data_r_stdev = stdev(data_r)
+ item.append(round(data_r_stdev / 1000000, 2))
else:
+ data_r_mean = None
+ data_r_stdev = None
item.extend([None, None])
- data_t = tbl_dict[tst_name][u"cmp-data"]
- if data_t:
- item.append(round(mean(data_t) / 1000000, 2))
- item.append(round(stdev(data_t) / 1000000, 2))
+ data_c = tbl_dict[tst_name][u"cmp-data"]
+ if data_c:
+ data_c_mean = mean(data_c)
+ item.append(round(data_c_mean / 1000000, 2))
+ data_c_stdev = stdev(data_c)
+ item.append(round(data_c_stdev / 1000000, 2))
else:
+ data_c_mean = None
+ data_c_stdev = None
item.extend([None, None])
- if item[-4] is not None and item[-2] is not None and item[-4] != 0:
- item.append(int(relative_change(float(item[-4]), float(item[-2]))))
- if len(item) == len(header):
+ if data_r_mean and data_c_mean:
+ 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
f"{table[u'reference'][u'title']} Stdev [Mpps]",
f"{table[u'compare'][u'title']} Thput [Mpps]",
f"{table[u'compare'][u'title']} Stdev [Mpps]",
- u"Delta [%]", u"Stdev of delta [%]"
+ u"Delta [%]",
+ u"Stdev of delta [%]"
]
header_str = u",".join(header) + u"\n"
except (AttributeError, KeyError) as err: