def _sanitize(rule, statistics):
"""Sanitize statistics."""
LOG.debug('sanitize stats %s', statistics)
if rule.get('exclude_outliers'):
key = operator.attrgetter('count')
mean = utils.mean(statistics, key)
stddev = utils.stddev(statistics, key, mean)
lower = mean - 2 * stddev
upper = mean + 2 * stddev
inliers, outliers = utils.anomalies(statistics, key, lower, upper)
if outliers:
LOG.debug('excluded weak datapoints with sample counts %s',
[s.count for s in outliers])
statistics = inliers
else:
LOG.debug('no excluded weak datapoints')
# in practice statistics are always sorted by period start, not
# strictly required by the API though
statistics = statistics[-rule['evaluation_periods']:]
result_statistics = [
getattr(stat, rule['statistic']) for stat in statistics
]
LOG.debug('pruned statistics to %d', len(statistics))
return result_statistics
def _sanitize(alarm, statistics):
"""Sanitize statistics."""
LOG.debug('sanitize stats %s', statistics)
if alarm.rule.get('exclude_outliers'):
key = operator.attrgetter('count')
mean = utils.mean(statistics, key)
stddev = utils.stddev(statistics, key, mean)
lower = mean - 2 * stddev
upper = mean + 2 * stddev
inliers, outliers = utils.anomalies(statistics, key, lower, upper)
if outliers:
LOG.debug('excluded weak datapoints with sample counts %s',
[s.count for s in outliers])
statistics = inliers
else:
LOG.debug('no excluded weak datapoints')
# in practice statistics are always sorted by period start, not
# strictly required by the API though
statistics = statistics[-alarm.rule['evaluation_periods']:]
result_statistics = [getattr(stat, alarm.rule['statistic'])
for stat in statistics]
LOG.debug('pruned statistics to %d', len(statistics))
return result_statistics