package statsd import ( "math" "math/rand" "sort" ) const defaultPercentileLimit = 1000 // RunningStats calculates a running mean, variance, standard deviation, // lower bound, upper bound, count, and can calculate estimated percentiles. // It is based on the incremental algorithm described here: // https://en.wikipedia.org/wiki/Algorithms_for_calculating_variance type RunningStats struct { k float64 n int64 ex float64 ex2 float64 // Array used to calculate estimated percentiles // We will store a maximum of PercLimit values, at which point we will start // randomly replacing old values, hence it is an estimated percentile. perc []float64 PercLimit int sum float64 lower float64 upper float64 // cache if we have sorted the list so that we never re-sort a sorted list, // which can have very bad performance. sorted bool } func (rs *RunningStats) AddValue(v float64) { // Whenever a value is added, the list is no longer sorted. rs.sorted = false if rs.n == 0 { rs.k = v rs.upper = v rs.lower = v if rs.PercLimit == 0 { rs.PercLimit = defaultPercentileLimit } rs.perc = make([]float64, 0, rs.PercLimit) } // These are used for the running mean and variance rs.n += 1 rs.ex += v - rs.k rs.ex2 += (v - rs.k) * (v - rs.k) // add to running sum rs.sum += v // track upper and lower bounds if v > rs.upper { rs.upper = v } else if v < rs.lower { rs.lower = v } if len(rs.perc) < rs.PercLimit { rs.perc = append(rs.perc, v) } else { // Reached limit, choose random index to overwrite in the percentile array rs.perc[rand.Intn(len(rs.perc))] = v } } func (rs *RunningStats) Mean() float64 { return rs.k + rs.ex/float64(rs.n) } func (rs *RunningStats) Variance() float64 { return (rs.ex2 - (rs.ex*rs.ex)/float64(rs.n)) / float64(rs.n) } func (rs *RunningStats) Stddev() float64 { return math.Sqrt(rs.Variance()) } func (rs *RunningStats) Sum() float64 { return rs.sum } func (rs *RunningStats) Upper() float64 { return rs.upper } func (rs *RunningStats) Lower() float64 { return rs.lower } func (rs *RunningStats) Count() int64 { return rs.n } func (rs *RunningStats) Percentile(n int) float64 { if n > 100 { n = 100 } if !rs.sorted { sort.Float64s(rs.perc) rs.sorted = true } i := int(float64(len(rs.perc)) * float64(n) / float64(100)) return rs.perc[clamp(i, 0, len(rs.perc)-1)] } func clamp(i int, min int, max int) int { if i < min { return min } if i > max { return max } return i }