in_data = _select_data(in_data, period,
fill_missing=fill_missing,
use_first=use_first)
- try:
- data_x = ["{0}/{1}".format(key, build_info[str(key)][1].split("~")[-1])
- for key in in_data.keys()]
- except KeyError:
- data_x = [key for key in in_data.keys()]
+ # try:
+ # data_x = ["{0}/{1}".format(key, build_info[str(key)][1].split("~")[-1])
+ # for key in in_data.keys()]
+ # except KeyError:
+ # data_x = [key for key in in_data.keys()]
+ hover_text = ["vpp-build: {0}".format(x[1].split("~")[-1])
+ for x in build_info.values()]
+ data_x = [key for key in in_data.keys()]
+
data_y = [val for val in in_data.values()]
data_pd = pd.Series(data_y, index=data_x)
anomalies = pd.Series()
anomalies_res = list()
for idx, item in enumerate(in_data.items()):
- item_pd = pd.Series([item[1], ],
- index=["{0}/{1}".
- format(item[0],
- build_info[str(item[0])][1].split("~")[-1]), ])
+ # item_pd = pd.Series([item[1], ],
+ # index=["{0}/{1}".
+ # format(item[0],
+ # build_info[str(item[0])][1].split("~")[-1]),
+ # ])
+ item_pd = pd.Series([item[1], ], index=[item[0], ])
if item[0] in outliers.keys():
anomalies = anomalies.append(item_pd)
anomalies_res.append(0.0)
"color": color,
"symbol": "circle",
},
+ text=hover_text,
+ hoverinfo="x+y+text+name"
)
traces = [trace_samples, ]
input_data.metadata(job_name, build)["version"]
)
except KeyError:
- pass
+ build_info[build] = ("", "")
# Create the header:
csv_table = list()
row[idx] = str(round(float(item) / 1000000, 2))
except ValueError:
pass
- txt_table.add_row(row)
+ try:
+ txt_table.add_row(row)
+ except Exception as err:
+ logging.warning("Error occurred while generating TXT table:"
+ "\n{0}".format(err))
line_nr += 1
txt_table.align["Build Number:"] = "l"
with open("{0}.txt".format(file_name), "w") as txt_file: