def generate_series():
test_id = CONF.command.test_id
session = api.get_session()
run_times = api.get_test_run_time_series(test_id, session)
if not CONF.title:
test = api.get_test_by_id(test_id, session)
session.close()
ts = pd.Series(run_times)
ts = utils.filter_dates(ts)
mean = pd.rolling_mean(ts, 20)
rolling_std = pd.rolling_std(ts, 20)
plt.figure()
if not CONF.title:
plt.title(test.test_id)
else:
plt.title(CONF.title)
plt.ylabel("Time (sec.)")
plt.plot(ts.index, ts, "k", label="Run Time")
plt.plot(mean.index, mean, "b", label="Avg. Run Time")
upper_std_dev = mean + 2 * rolling_std
lower_std_dev = mean - 2 * rolling_std
# Set negative numbers to 0
lower_std_dev[lower_std_dev < 0] = 0
plt.fill_between(rolling_std.index, upper_std_dev, lower_std_dev, color="b", alpha=0.2, label="std dev")
plt.legend()
plt.savefig(CONF.output, dpi=900)
return ts
def generate_series():
session = api.get_session()
test_starts = api.get_test_run_series(session)
session.close()
ts = pd.Series(test_starts).resample('D', how='sum')
daily_count = utils.filter_dates(ts)
mean = pd.rolling_mean(daily_count, 10)
rolling_std = pd.rolling_std(daily_count, 10)
plt.figure()
title = CONF.title or 'Number of tests run'
plt.title(title)
plt.ylabel('Number of tests')
plt.plot(daily_count.index, daily_count, 'k', label='Daily Test Count')
plt.plot(mean.index, mean, 'b', label='Avg. Daily Test Count')
upper_std_dev = mean + 2 * rolling_std
lower_std_dev = mean - 2 * rolling_std
# Set negative numbers to 0
lower_std_dev[lower_std_dev < 0] = 0
plt.fill_between(rolling_std.index,
lower_std_dev,
upper_std_dev,
color='b',
alpha=0.2,
label='std dev')
plt.legend()
plt.savefig(CONF.output)
def generate_series():
session = api.get_session()
test_id = api.get_id_from_test_id(CONF.command.test_id, session)
if not test_id:
print("The test_id %s was not found in the database" %
CONF.command.test_id)
exit(2)
run_times = api.get_test_run_time_series(test_id, session)
if not run_times:
print("There was no data found in the database")
exit(3)
if not CONF.title:
test = api.get_test_by_id(test_id, session)
session.close()
ts = pd.Series(run_times)
ts = utils.filter_dates(ts)
if ts.count() == 0:
print("No data available. Check your query and try again.")
exit(-1)
mean = pd.rolling_mean(ts, 20)
rolling_std = pd.rolling_std(ts, 20)
plt.figure()
if not CONF.title:
plt.title(test.test_id)
else:
plt.title(CONF.title)
plt.ylabel('Time (sec.)')
# format x-axis with dates
fig, ax = plt.subplots(1)
fig.autofmt_xdate()
xfmt = dates.DateFormatter("%b %d %Y")
ax.xaxis_date()
ax.xaxis.set_major_formatter(xfmt)
plt.plot(ts.index, ts, 'k', label='Run Time')
plt.plot(mean.index, mean, 'b', label='Avg. Run Time')
upper_std_dev = mean + 2 * rolling_std
lower_std_dev = mean - 2 * rolling_std
# Set negative numbers to 0
lower_std_dev[lower_std_dev < 0] = 0
plt.fill_between(rolling_std.index,
upper_std_dev,
lower_std_dev,
color='b',
alpha=0.2,
label='std dev')
plt.legend()
plt.savefig(CONF.output, dpi=900)
return ts
def generate_series():
session = api.get_session()
test_id = api.get_id_from_test_id(CONF.command.test_id, session)
if not test_id:
print("The test_id %s was not found in the database" %
CONF.command.test_id)
exit(2)
run_times = api.get_test_run_time_series(test_id, session)
if not run_times:
print("There was no data found in the database")
exit(3)
if not CONF.title:
test = api.get_test_by_id(test_id, session)
session.close()
ts = pd.Series(run_times)
ts = utils.filter_dates(ts)
if ts.count() == 0:
print("No data available. Check your query and try again.")
exit(-1)
roll = ts.rolling(window=20, center=False)
mean = roll.mean()
rolling_std = roll.std()
plt.figure()
if not CONF.title:
plt.title(test.test_id)
else:
plt.title(CONF.title)
plt.ylabel('Time (sec.)')
# format x-axis with dates
fig, ax = plt.subplots(1)
fig.autofmt_xdate()
xfmt = dates.DateFormatter("%b %d %Y")
ax.xaxis_date()
ax.xaxis.set_major_formatter(xfmt)
plt.plot(ts.index, ts, 'ko', label='Run Time', markersize=0.45)
plt.plot(mean.index, mean, 'b', label='Avg. Run Time', linewidth=0.45)
upper_std_dev = mean + 2 * rolling_std
lower_std_dev = mean - 2 * rolling_std
# Set negative numbers to 0
lower_std_dev[lower_std_dev < 0] = 0
plt.fill_between(rolling_std.index, upper_std_dev,
lower_std_dev, color='b', alpha=0.2,
label='std dev')
plt.legend()
plt.savefig(CONF.output, dpi=CONF.dpi)
return ts
def generate_series():
session = api.get_session()
test_id = api.get_id_from_test_id(CONF.command.test_id, session)
test_statuses = api.get_test_status_time_series(test_id, session)
if not CONF.title:
test = api.get_test_by_id(test_id, session)
session.close()
ts = pd.Series(test_statuses)
ts = utils.filter_dates(ts)
run_count = len(ts)
if run_count == 0:
print("Query returned no data.")
exit(-1)
failures = ts[ts.isin(['fail', 'unxsuccess'])]
successes = ts[ts.isin(['success', 'xfail'])]
skips = ts[ts.isin(['skip'])]
fail_count = len(failures)
success_count = len(successes)
skip_count = len(skips)
fail_group = failures.groupby(failures.index.date).agg(len)
success_group = successes.groupby(successes.index.date).agg(len)
skip_group = skips.groupby(skips.index.date).agg(len)
if not CONF.title:
plot = fail_group.plot().set_title(test.test_id)
else:
plot = fail_group.plot().set_title(CONF.title)
if CONF.command.success_graph:
if success_count:
success_group.plot()
if CONF.command.skip_graph:
if skip_count:
skip_group.plot()
def percent(count, total):
count = float(count)
total = float(total)
return (count / total) * 100.0
print('Fail Percentage: %.4f%%' % percent(fail_count, run_count))
print('Success Percentage: %.4f%%' % percent(success_count, run_count))
print('Skip Percentage: %.4f%%' % percent(skip_count, run_count))
fig = plot.get_figure()
fig.savefig(CONF.output)
return ts
def generate_series():
session = api.get_session()
test_starts = api.get_test_run_series(session)
session.close()
ts = pd.Series(test_starts).resample('D', how='sum')
daily_count = utils.filter_dates(ts)
mean = pd.rolling_mean(daily_count, 10)
rolling_std = pd.rolling_std(daily_count, 10)
plt.figure()
title = CONF.title or 'Number of tests run'
plt.title(title)
plt.ylabel('Number of tests')
plt.plot(daily_count.index, daily_count, 'k', label='Daily Test Count')
plt.plot(mean.index, mean, 'b', label='Avg. Daily Test Count')
upper_std_dev = mean + 2 * rolling_std
lower_std_dev = mean - 2 * rolling_std
# Set negative numbers to 0
lower_std_dev[lower_std_dev < 0] = 0
plt.fill_between(rolling_std.index, lower_std_dev, upper_std_dev,
color='b', alpha=0.2, label='std dev')
plt.legend()
plt.savefig(CONF.output)