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"] :]
LOG.debug("pruned statistics to %d", len(statistics))
return 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']:]
LOG.debug(_('pruned statistics to %d') % len(statistics))
return statistics