func populateNormalHistogram(t *testing.T, h metrics.Histogram, seed int64, mean, stdev int64) {
rand.Seed(seed)
for i := 0; i < 1234; i++ {
sample := int64(rand.NormFloat64()*float64(stdev) + float64(mean))
h.Observe(sample)
}
}
func httpInstrument(requests metrics.Counter, duration metrics.Histogram) func(http.Handler) http.Handler {
return func(next http.Handler) http.Handler {
return http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
requests.Add(1)
defer func(begin time.Time) { duration.Observe(time.Since(begin).Nanoseconds()) }(time.Now())
next.ServeHTTP(w, r)
})
}
}
// PopulateNormalHistogram makes a series of normal random observations into the
// histogram. The number of observations is determined by Count. The randomness
// is determined by Mean, Stdev, and the seed parameter.
//
// This is a low-level function, exported only for metrics that don't perform
// dynamic quantile computation, like a Prometheus Histogram (c.f. Summary). In
// most cases, you don't need to use this function, and can use TestHistogram
// instead.
func PopulateNormalHistogram(h metrics.Histogram, seed int) {
r := rand.New(rand.NewSource(int64(seed)))
for i := 0; i < Count; i++ {
sample := r.NormFloat64()*float64(Stdev) + float64(Mean)
if sample < 0 {
sample = 0
}
h.Observe(sample)
}
}
// PopulateNormalHistogram populates the Histogram with a normal distribution
// of observations.
func PopulateNormalHistogram(t *testing.T, h metrics.Histogram, seed int64, mean, stdev int64) {
r := rand.New(rand.NewSource(seed))
for i := 0; i < population; i++ {
sample := int64(r.NormFloat64()*float64(stdev) + float64(mean))
if sample < 0 {
sample = 0
}
h.Observe(sample)
}
}
func Measure(h metrics.Histogram, d time.Duration) {
if h != nil && archaius.Conf.Collect {
if d > maxHistObservable {
h.Observe(int64(maxHistObservable))
} else {
h.Observe(int64(d))
}
s := sampleMap[h]
if s != nil && len(s) < sampleCount {
sampleMap[h] = append(s, int64(d))
}
}
}
