continue
name = re.sub(REGEX_NIC, u"", test[u"parent"].
replace(u'-ndrpdr', u'').
- replace(u'2n1l-', u'').
- replace(u'avf-', u''))
+ replace(u'2n1l-', u''))
for idx, direction in enumerate(
(u"direction1", u"direction2", )):
try:
continue
name = re.sub(REGEX_NIC, u"", test[u"parent"].
replace(u'-ndrpdr', u'').
- replace(u'2n1l-', u'').
- replace(u'avf-', u''))
+ replace(u'2n1l-', u''))
histograms = list()
for idx_col, direction in enumerate(
(u"direction1", u"direction2", )):
for i, col in enumerate(df_y.columns):
tst_name = re.sub(REGEX_NIC, u"",
col.lower().replace(u'-ndrpdr', u'').
- replace(u'2n1l-', u'').replace(u'avf-', u''))
+ replace(u'2n1l-', u''))
traces.append(plgo.Box(
x=[str(i + 1) + u'.'] * len(df_y[col]),
for i, col in enumerate(df_y.columns):
tst_name = re.sub(REGEX_NIC, u"",
col.lower().replace(u'-ndrpdr', u'').
- replace(u'2n1l-', u'').replace(u'avf-', u''))
+ replace(u'2n1l-', u''))
traces.append(
plgo.Box(
x=[str(i + 1) + u'.'] * len(df_y[col]),
nr_of_samples = list()
for key, val in y_tmp_vals.items():
name = re.sub(REGEX_NIC, u"", key.replace(u'-ndrpdr', u'').
- replace(u'2n1l-', u'').replace(u'avf-', u''))
+ replace(u'2n1l-', u''))
x_vals.append(name) # dir 1
y_vals.append(mean(val[1]) if val[1] else None)
y_mins.append(mean(val[0]) if val[0] else None)
name = re.sub(
REGEX_NIC,
u"",
- test_name.replace(u'-ndrpdr', u'').replace(u'2n1l-', u'').
- replace(u'avf-', u'')
+ test_name.replace(u'-ndrpdr', u'').replace(u'2n1l-', u'')
)
vals[name] = OrderedDict()
y_val_1 = test_vals[u"1"][0] / 1000000.0