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Report, trending
[csit.git]
/
resources
/
tools
/
presentation
/
generator_CPTA.py
diff --git
a/resources/tools/presentation/generator_CPTA.py
b/resources/tools/presentation/generator_CPTA.py
index
967eb60
..
c3784e9
100644
(file)
--- a/
resources/tools/presentation/generator_CPTA.py
+++ b/
resources/tools/presentation/generator_CPTA.py
@@
-164,19
+164,21
@@
def _evaluate_results(in_data, trimmed_data, window=10):
if len(in_data) > 2:
win_size = in_data.size if in_data.size < window else window
if len(in_data) > 2:
win_size = in_data.size if in_data.size < window else window
- results = [0.0, ]
* win_size
+ results = [0.0, ]
median = in_data.rolling(window=win_size).median()
stdev_t = trimmed_data.rolling(window=win_size, min_periods=2).std()
m_vals = median.values
s_vals = stdev_t.values
d_vals = in_data.values
median = in_data.rolling(window=win_size).median()
stdev_t = trimmed_data.rolling(window=win_size, min_periods=2).std()
m_vals = median.values
s_vals = stdev_t.values
d_vals = in_data.values
- for day in range(win_size, in_data.size):
- if np.isnan(m_vals[day - 1]) or np.isnan(s_vals[day - 1]):
+ for day in range(1, in_data.size):
+ if np.isnan(m_vals[day]) \
+ or np.isnan(s_vals[day]) \
+ or np.isnan(d_vals[day]):
results.append(0.0)
results.append(0.0)
- elif d_vals[day] < (m_vals[day
- 1] - 3 * s_vals[day - 1
]):
+ elif d_vals[day] < (m_vals[day
] - 3 * s_vals[day
]):
results.append(0.33)
results.append(0.33)
- elif (m_vals[day
- 1] - 3 * s_vals[day - 1
]) <= d_vals[day] <= \
- (m_vals[day
- 1] + 3 * s_vals[day - 1
]):
+ elif (m_vals[day
] - 3 * s_vals[day
]) <= d_vals[day] <= \
+ (m_vals[day
] + 3 * s_vals[day
]):
results.append(0.66)
else:
results.append(1.0)
results.append(0.66)
else:
results.append(1.0)
@@
-197,7
+199,7
@@
def _evaluate_results(in_data, trimmed_data, window=10):
return results
return results
-def _generate_trending_traces(in_data, period, moving_win_size=10,
+def _generate_trending_traces(in_data,
build_info,
period, moving_win_size=10,
fill_missing=True, use_first=False,
show_moving_median=True, name="", color=""):
"""Generate the trending traces:
fill_missing=True, use_first=False,
show_moving_median=True, name="", color=""):
"""Generate the trending traces:
@@
-206,6
+208,7
@@
def _generate_trending_traces(in_data, period, moving_win_size=10,
- outliers, regress, progress
:param in_data: Full data set.
- outliers, regress, progress
:param in_data: Full data set.
+ :param build_info: Information about the builds.
:param period: Sampling period.
:param moving_win_size: Window size.
:param fill_missing: If the chosen sample is missing in the full set, its
:param period: Sampling period.
:param moving_win_size: Window size.
:param fill_missing: If the chosen sample is missing in the full set, its
@@
-215,6
+218,7
@@
def _generate_trending_traces(in_data, period, moving_win_size=10,
:param name: Name of the plot
:param color: Name of the color for the plot.
:type in_data: OrderedDict
:param name: Name of the plot
:param color: Name of the color for the plot.
:type in_data: OrderedDict
+ :type build_info: dict
:type period: int
:type moving_win_size: int
:type fill_missing: bool
:type period: int
:type moving_win_size: int
:type fill_missing: bool
@@
-230,18
+234,30
@@
def _generate_trending_traces(in_data, period, moving_win_size=10,
in_data = _select_data(in_data, period,
fill_missing=fill_missing,
use_first=use_first)
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()]
+ 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_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)
data_y = [val for val in in_data.values()]
data_pd = pd.Series(data_y, index=data_x)
- t_data, outliers = find_outliers(data_pd)
+ t_data, outliers = find_outliers(data_pd
, outlier_const=1.5
)
results = _evaluate_results(data_pd, t_data, window=moving_win_size)
anomalies = pd.Series()
anomalies_res = list()
for idx, item in enumerate(in_data.items()):
results = _evaluate_results(data_pd, t_data, window=moving_win_size)
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=[item[0], ])
if item[0] in outliers.keys():
anomalies = anomalies.append(item_pd)
item_pd = pd.Series([item[1], ], index=[item[0], ])
if item[0] in outliers.keys():
anomalies = anomalies.append(item_pd)
@@
-274,6
+290,8
@@
def _generate_trending_traces(in_data, period, moving_win_size=10,
"color": color,
"symbol": "circle",
},
"color": color,
"symbol": "circle",
},
+ text=hover_text,
+ hoverinfo="x+y+text+name"
)
traces = [trace_samples, ]
)
traces = [trace_samples, ]
@@
-362,24
+380,37
@@
def _generate_all_charts(spec, input_data):
:type input_data: InputData
"""
:type input_data: InputData
"""
- builds = spec.cpta["data"].values()[0]
job_name = spec.cpta["data"].keys()[0]
job_name = spec.cpta["data"].keys()[0]
- builds_lst = [str(build) for build in range(builds[0], builds[-1] + 1)]
+
+ builds_lst = list()
+ for build in spec.input["builds"][job_name]:
+ status = build["status"]
+ if status != "failed" and status != "not found":
+ builds_lst.append(str(build["build"]))
# Get "build ID": "date" dict:
# Get "build ID": "date" dict:
- build_
dates = d
ict()
+ build_
info = OrderedD
ict()
for build in builds_lst:
try:
for build in builds_lst:
try:
- build_dates[build] = \
- input_data.metadata(job_name, build)["generated"][:14]
+ build_info[build] = (
+ input_data.metadata(job_name, build)["generated"][:14],
+ input_data.metadata(job_name, build)["version"]
+ )
except KeyError:
except KeyError:
- pass
+ build_info[build] = ("", "")
+ logging.info("{}: {}, {}".format(build,
+ build_info[build][0],
+ build_info[build][1]))
# Create the header:
csv_table = list()
header = "Build Number:," + ",".join(builds_lst) + '\n'
csv_table.append(header)
# Create the header:
csv_table = list()
header = "Build Number:," + ",".join(builds_lst) + '\n'
csv_table.append(header)
- header = "Build Date:," + ",".join(build_dates.values()) + '\n'
+ build_dates = [x[0] for x in build_info.values()]
+ header = "Build Date:," + ",".join(build_dates) + '\n'
+ csv_table.append(header)
+ vpp_versions = [x[1] for x in build_info.values()]
+ header = "VPP Version:," + ",".join(vpp_versions) + '\n'
csv_table.append(header)
results = list()
csv_table.append(header)
results = list()
@@
-416,7
+447,7
@@
def _generate_all_charts(spec, input_data):
for period in chart["periods"]:
# Generate traces:
traces = list()
for period in chart["periods"]:
# Generate traces:
traces = list()
- win_size = 1
0
if period == 1 else 5 if period < 20 else 3
+ win_size = 1
4
if period == 1 else 5 if period < 20 else 3
idx = 0
for test_name, test_data in chart_data.items():
if not test_data:
idx = 0
for test_name, test_data in chart_data.items():
if not test_data:
@@
-426,6
+457,7
@@
def _generate_all_charts(spec, input_data):
test_name = test_name.split('.')[-1]
trace, result = _generate_trending_traces(
test_data,
test_name = test_name.split('.')[-1]
trace, result = _generate_trending_traces(
test_data,
+ build_info=build_info,
period=period,
moving_win_size=win_size,
fill_missing=True,
period=period,
moving_win_size=win_size,
fill_missing=True,
@@
-468,7
+500,11
@@
def _generate_all_charts(spec, input_data):
row[idx] = str(round(float(item) / 1000000, 2))
except ValueError:
pass
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:
line_nr += 1
txt_table.align["Build Number:"] = "l"
with open("{0}.txt".format(file_name), "w") as txt_file: