Added support for starting mid-stream
This commit is contained in:
parent
84b41cf7fe
commit
1b669ee5f1
48
ostat.go
48
ostat.go
@ -1,25 +1,31 @@
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package ostat
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package ostat
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import (
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import (
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"fmt"
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"math"
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"math"
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)
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)
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// from http://en.wikipedia.org/wiki/Algorithms_for_calculating_variance#Online_algorithm
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// from http://en.wikipedia.org/wiki/Algorithms_for_calculating_variance#Online_algorithm
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const (
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Population = iota
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Sample
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)
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type OnlineStat struct {
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type OnlineStat struct {
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n int64
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n uint64
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mean float64
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mean float64
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m2 float64
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m2 float64
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Max float64
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Min float64
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Min float64
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typ int64
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Max float64
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typ uint64
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}
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}
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func NewSampleStat() *OnlineStat {
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func NewSampleStat() *OnlineStat {
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return &OnlineStat{
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return &OnlineStat{
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Min: math.Inf(1),
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Min: math.Inf(1),
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Max: math.Inf(-1),
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Max: math.Inf(-1),
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typ: 1,
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typ: Sample,
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}
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}
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}
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}
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@ -27,7 +33,18 @@ func NewPopulationStat() *OnlineStat {
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return &OnlineStat{
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return &OnlineStat{
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Min: math.Inf(1),
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Min: math.Inf(1),
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Max: math.Inf(-1),
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Max: math.Inf(-1),
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typ: 0,
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typ: Population,
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}
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}
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func MidStreamStat(n uint64, mean, stddev, min, max float64, typ uint64) *OnlineStat {
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return &OnlineStat{
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n: n,
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mean: mean,
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m2: stddev * stddev * float64(n),
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Min: min,
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Max: max,
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typ: typ,
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}
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}
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}
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}
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@ -62,3 +79,24 @@ func (os *OnlineStat) Variance() float64 {
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func (os *OnlineStat) StdDev() float64 {
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func (os *OnlineStat) StdDev() float64 {
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return math.Sqrt(os.Variance())
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return math.Sqrt(os.Variance())
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}
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}
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func (os *OnlineStat) String() string {
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return fmt.Sprintf(
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"%+v",
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struct {
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n uint64
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min float64
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max float64
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mean float64
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variance float64
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stdDev float64
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}{
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n: os.n,
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min: os.Min,
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max: os.Max,
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mean: os.Mean(),
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variance: os.Variance(),
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stdDev: os.StdDev(),
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},
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)
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}
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137
ostat_test.go
137
ostat_test.go
@ -1,7 +1,6 @@
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package ostat
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package ostat
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import (
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import (
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"log"
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"math"
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"math"
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"testing"
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"testing"
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)
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)
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@ -130,11 +129,141 @@ func TestEmpty(t *testing.T) {
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}
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}
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}
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}
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func TestReconstitutedStat(t *testing.T) {
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func TestMidStreamStat(t *testing.T) {
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os := OnlineStat{
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ps := OnlineStat{
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n: 3,
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n: 3,
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mean: 8,
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mean: 8,
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m2: 21 * 3,
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m2: 21 * 3,
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typ: Population,
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}
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rps := MidStreamStat(3, 8, 4.5825756949558, 4, 13, Population)
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if math.Abs(ps.Mean()-rps.Mean()) > tolerance {
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t.Errorf("Incorrect Mean Calc: %f %f", ps.Mean(), rps.Mean())
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}
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if math.Abs(ps.Variance()-rps.Variance()) > tolerance {
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t.Errorf("Incorrect Variance Calc: %f %f", ps.Variance(), rps.Variance())
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}
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}
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// probably spent too much time gathering this data and hard-coding it all in
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// here. Alas, this test is to verify that we can start a stat mid-stream, if
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// given the right info at the outset.
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func TestMidStreamStatWithData(t *testing.T) {
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ps := NewPopulationStat()
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first := []float64{7633., 8550., -7874., 586., 7488., 839., 8379., 8716.,
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-9612., -4309., -3923., -9159., 8131., 7392., -1587., 2004.,
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7975., -6135., -3863., 686., -7862., 1707., -7967., -9421.,
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-5618., 2419., -8948., -184., 4450., 7189., 3150., -1879.,
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-6845., -8551., 5629., -6370., 4949., 6865., 118., 2302.,
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-4406., 8384., 5643., -7794., 5752., -1361., 6765., 6258.,
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5602., -4659., 8268., 2154., 345., 123., 7843., -9841.,
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2889., -3665., 6545., -2164., -8135., 8377., 7645., 9759.,
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601., 5924., 3348., -3217., 5076., -9145., -2973., 6195.,
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-8138., -1093., -1432., 813., -6668., -8527., -8646., -670.,
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-940., -911., 1717., -1388., -786., 2819., 6902., -8566.,
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4684., 4809., -4446., -806., 3805., -7975., 1138., 518.,
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-3416., -1797., -2625., -3202.}
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var n int
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var val float64
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for n, val = range first {
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ps.Push(val)
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}
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mss := MidStreamStat(
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uint64(n+1),
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83.590000000000003,
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5722.0924356305177,
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-9841.0,
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9759.0,
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Population,
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)
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mean1 := 83.590000000000003
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variance1 := 32742341.841899995
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min1 := -9841.0
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max1 := 9759.0
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if math.Abs(ps.Mean()-mean1) > tolerance {
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t.Errorf("mean: %f != %f", ps.Mean(), mean1)
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}
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if math.Abs(mss.Mean()-mean1) > tolerance {
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t.Errorf("mean: %f != %f", mss.Mean(), mean1)
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}
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if math.Abs(ps.Variance()-variance1) > tolerance {
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t.Errorf("mean: %f != %f", ps.Variance(), variance1)
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}
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if math.Abs(mss.Variance()-variance1) > tolerance {
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t.Errorf("mean: %f != %f", mss.Variance(), variance1)
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}
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if (ps.Min != mss.Min) || (mss.Min != min1) {
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t.Errorf("min: %f != %f != %f", mss.Min, mss.Min, min1)
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}
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if (ps.Max != mss.Max) || (mss.Max != max1) {
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t.Errorf("max: %f != %f != %f", mss.Max, mss.Max, max1)
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}
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second := []float64{-3.87000000e+02, -4.26800000e+03,
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-1.39900000e+03, 2.00300000e+03, 1.53100000e+03,
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-7.91000000e+02, 4.27300000e+03, 4.22100000e+03,
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-4.84400000e+03, -3.09100000e+03, 4.69300000e+03,
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4.69100000e+03, -9.78700000e+03, -8.23900000e+03,
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2.60100000e+03, -9.01100000e+03, 4.32700000e+03,
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4.62500000e+03, -1.67800000e+03, -9.76300000e+03,
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-9.26700000e+03, -5.80800000e+03, -2.41400000e+03,
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-6.62900000e+03, 3.99500000e+03, 6.71800000e+03,
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-5.48500000e+03, 1.91300000e+03, -2.21000000e+03,
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6.29400000e+03, 9.35500000e+03, -3.24800000e+03,
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4.58200000e+03, -2.91000000e+02, 1.42500000e+03,
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-1.13700000e+03, 5.16900000e+03, -8.36700000e+03,
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-5.49500000e+03, 8.93000000e+02, 9.74800000e+03,
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-8.50100000e+03, 6.47000000e+02, -4.93800000e+03,
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-2.31800000e+03, -5.39100000e+03, 4.55000000e+02,
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9.62000000e+02, -4.39000000e+02, 3.18100000e+03,
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7.39500000e+03, -3.16100000e+03, 6.31400000e+03,
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9.47500000e+03, 3.73500000e+03, 9.48000000e+03,
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-4.14700000e+03, -2.48000000e+02, 2.94000000e+02,
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-9.95100000e+03, 3.82500000e+03, -1.03700000e+03,
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7.33200000e+03, 9.97800000e+03, -3.36200000e+03,
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9.67200000e+03, 5.62600000e+03, -1.93000000e+02,
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-3.41300000e+03, -1.50000000e+01, -2.96000000e+03,
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-5.14800000e+03, 8.41900000e+03, -9.07900000e+03,
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7.37500000e+03, -7.05400000e+03, -8.59400000e+03,
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2.66900000e+03, -7.37600000e+03, -6.99500000e+03,
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2.81800000e+03, 2.87700000e+03, 1.83000000e+02,
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-9.27100000e+03, 5.83400000e+03, 3.00000000e+00,
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-6.02700000e+03, 7.78600000e+03, 1.64700000e+03,
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-5.96500000e+03, -8.60000000e+02, -3.67700000e+03,
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-6.36600000e+03, -2.06000000e+02, -5.33600000e+03,
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-2.31000000e+02, -6.70300000e+03, -4.87900000e+03,
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5.27600000e+03, 9.12600000e+03}
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for _, val = range second {
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ps.Push(val)
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mss.Push(val)
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}
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mean2 := -118.25
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variance2 := 31713809.697500002
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min2 := -9951.0
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max2 := 9978.0
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if math.Abs(ps.Mean()-mean2) > tolerance {
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t.Errorf("mean: %f != %f", ps.Mean(), mean2)
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}
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if math.Abs(mss.Mean()-mean2) > tolerance {
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t.Errorf("mean: %f != %f", mss.Mean(), mean2)
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}
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if math.Abs(ps.Variance()-variance2) > tolerance {
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t.Errorf("mean: %f != %f", ps.Variance(), variance2)
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}
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if math.Abs(mss.Variance()-variance2) > tolerance {
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t.Errorf("mean: %f != %f", mss.Variance(), variance2)
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}
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if (ps.Min != mss.Min) || (mss.Min != min2) {
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t.Errorf("min: %f != %f != %f", mss.Min, mss.Min, min2)
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}
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if (ps.Max != mss.Max) || (mss.Max != max2) {
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t.Errorf("max: %f != %f != %f", mss.Max, mss.Max, max2)
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}
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}
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log.Printf("%+v: mean: %f, stddev: %f", os, os.Mean(), os.StdDev())
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}
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}
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