ActiveGo 1.8Package gohistogram
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type Histogram ¶
Histogram is the interface that wraps the Add and Quantile methods.
type Histogram interface {
// Add adds a new value, n, to the histogram. Trimming is done
// automatically.
Add(n float64)
// Quantile returns an approximation.
Quantile(n float64) (q float64)
// String returns a string reprentation of the histogram,
// which is useful for printing to a terminal.
String() (str string)
}
type NumericHistogram ¶
type NumericHistogram struct {
// contains filtered or unexported fields
}
func NewHistogram ¶
func NewHistogram(n int) *NumericHistogram
NewHistogram returns a new NumericHistogram with a maximum of n bins.
There is no "optimal" bin count, but somewhere between 20 and 80 bins should be sufficient.
func (*NumericHistogram) Add ¶
func (h *NumericHistogram) Add(n float64)
func (*NumericHistogram) CDF ¶
func (h *NumericHistogram) CDF(x float64) float64
CDF returns the value of the cumulative distribution function at x
func (*NumericHistogram) Count ¶
func (h *NumericHistogram) Count() float64
func (*NumericHistogram) Mean ¶
func (h *NumericHistogram) Mean() float64
Mean returns the sample mean of the distribution
func (*NumericHistogram) Quantile ¶
func (h *NumericHistogram) Quantile(q float64) float64
func (*NumericHistogram) String ¶
func (h *NumericHistogram) String() (str string)
String returns a string reprentation of the histogram, which is useful for printing to a terminal.
func (*NumericHistogram) Variance ¶
func (h *NumericHistogram) Variance() float64
Variance returns the variance of the distribution
type WeightedHistogram ¶
A WeightedHistogram implements Histogram. A WeightedHistogram has bins that have values which are exponentially weighted moving averages. This allows you keep inserting large amounts of data into the histogram and approximate quantiles with recency factored in.
type WeightedHistogram struct {
// contains filtered or unexported fields
}
func NewWeightedHistogram ¶
func NewWeightedHistogram(n int, alpha float64) *WeightedHistogram
NewWeightedHistogram returns a new WeightedHistogram with a maximum of n bins with a decay factor of alpha.
There is no "optimal" bin count, but somewhere between 20 and 80 bins should be sufficient.
Alpha should be set to 2 / (N+1), where N represents the average age of the moving window. For example, a 60-second window with an average age of 30 seconds would yield an alpha of 0.064516129.
func (*WeightedHistogram) Add ¶
func (h *WeightedHistogram) Add(n float64)
func (*WeightedHistogram) CDF ¶
func (h *WeightedHistogram) CDF(x float64) float64
CDF returns the value of the cumulative distribution function at x
func (*WeightedHistogram) Count ¶
func (h *WeightedHistogram) Count() float64
func (*WeightedHistogram) Mean ¶
func (h *WeightedHistogram) Mean() float64
Mean returns the sample mean of the distribution
func (*WeightedHistogram) Quantile ¶
func (h *WeightedHistogram) Quantile(q float64) float64
func (*WeightedHistogram) String ¶
func (h *WeightedHistogram) String() (str string)
String returns a string reprentation of the histogram, which is useful for printing to a terminal.
func (*WeightedHistogram) Variance ¶
func (h *WeightedHistogram) Variance() float64
Variance returns the variance of the distribution