gohistogram - ActiveState ActiveGo 1.8
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Package gohistogram

import "github.com/VividCortex/gohistogram"
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Package gohistogram contains implementations of weighted and exponential histograms.

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