Codebase list golang-github-montanaflynn-stats / HEAD percentile_test.go
HEAD

Tree @HEAD (Download .tar.gz)

percentile_test.go @HEAD — raw · history · blame 

  1
  2
  3
  4
  5
  6
  7
  8
  9
 10
 11
 12
 13
 14
 15
 16
 17
 18
 19
 20
 21
 22
 23
 24
 25
 26
 27
 28
 29
 30
 31
 32
 33
 34
 35
 36
 37
 38
 39
 40
 41
 42
 43
 44
 45
 46
 47
 48
 49
 50
 51
 52
 53
 54
 55
 56
 57
 58
 59
 60
 61
 62
 63
 64
 65
 66
 67
 68
 69
 70
 71
 72
 73
 74
 75
 76
 77
 78
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
package stats_test

import (
	"reflect"
	"testing"

	"github.com/montanaflynn/stats"
)

func TestPercentile(t *testing.T) {
	m, _ := stats.Percentile([]float64{43, 54, 56, 61, 62, 66}, 90)
	if m != 64.0 {
		t.Errorf("%.1f != %.1f", m, 64.0)
	}
	m, _ = stats.Percentile([]float64{43}, 90)
	if m != 43.0 {
		t.Errorf("%.1f != %.1f", m, 43.0)
	}
	m, _ = stats.Percentile([]float64{1, 2, 3, 4, 5, 6, 7, 8, 9, 10}, 50)
	if m != 5.0 {
		t.Errorf("%.1f != %.1f", m, 5.0)
	}
	m, _ = stats.Percentile([]float64{1, 2, 3, 4, 5, 6, 7, 8, 9, 10}, 99.9)
	if m != 9.5 {
		t.Errorf("%.1f != %.1f", m, 9.5)
	}
	m, _ = stats.Percentile([]float64{1, 2, 3, 4, 5, 6, 7, 8, 9, 10}, 100)
	if m != 10.0 {
		t.Errorf("%.1f != %.1f", m, 10.0)
	}
	_, err := stats.Percentile([]float64{}, 99.9)
	if err != stats.EmptyInputErr {
		t.Errorf("Empty slice didn't return expected error; got %v", err)
	}
	_, err = stats.Percentile([]float64{1, 2, 3, 4, 5}, 0)
	if err != stats.BoundsErr {
		t.Errorf("Zero percent didn't return expected error; got %v", err)
	}
	_, err = stats.Percentile([]float64{1, 2, 3, 4, 5}, 0.13)
	if err != stats.BoundsErr {
		t.Errorf("Too low percent didn't return expected error; got %v", err)
	}
	_, err = stats.Percentile([]float64{1, 2, 3, 4, 5}, 101)
	if err != stats.BoundsErr {
		t.Errorf("Too high percent didn't return expected error; got %v", err)
	}
}

func TestPercentileSortSideEffects(t *testing.T) {
	s := []float64{43, 54, 56, 44, 62, 66}
	a := []float64{43, 54, 56, 44, 62, 66}
	_, _ = stats.Percentile(s, 90)
	if !reflect.DeepEqual(s, a) {
		t.Errorf("%.1f != %.1f", s, a)
	}
}

func BenchmarkPercentileSmallFloatSlice(b *testing.B) {
	for i := 0; i < b.N; i++ {
		_, _ = stats.Percentile(makeFloatSlice(5), 50)
	}
}

func BenchmarkPercentileLargeFloatSlice(b *testing.B) {
	lf := makeFloatSlice(100000)
	b.ResetTimer()
	for i := 0; i < b.N; i++ {
		_, _ = stats.Percentile(lf, 50)
	}
}

func TestPercentileNearestRank(t *testing.T) {
	f1 := []float64{35, 20, 15, 40, 50}
	f2 := []float64{20, 6, 7, 8, 8, 10, 13, 15, 16, 3}
	f3 := makeFloatSlice(101)

	for _, c := range []struct {
		sample  []float64
		percent float64
		result  float64
	}{
		{f1, 30, 20},
		{f1, 40, 20},
		{f1, 50, 35},
		{f1, 75, 40},
		{f1, 95, 50},
		{f1, 99, 50},
		{f1, 99.9, 50},
		{f1, 100, 50},
		{f2, 25, 7},
		{f2, 50, 8},
		{f2, 75, 15},
		{f2, 100, 20},
		{f3, 1, 100},
		{f3, 99, 9900},
		{f3, 100, 10000},
		{f3, 0, 0},
	} {
		got, err := stats.PercentileNearestRank(c.sample, c.percent)
		if err != nil {
			t.Errorf("Should not have returned an error")
		}
		if got != c.result {
			t.Errorf("%v != %v", got, c.result)
		}
	}

	_, err := stats.PercentileNearestRank([]float64{}, 50)
	if err == nil {
		t.Errorf("Should have returned an empty slice error")
	}

	_, err = stats.PercentileNearestRank([]float64{1, 2, 3, 4, 5}, -0.01)
	if err == nil {
		t.Errorf("Should have returned an percentage must be above 0 error")
	}

	_, err = stats.PercentileNearestRank([]float64{1, 2, 3, 4, 5}, 110)
	if err == nil {
		t.Errorf("Should have returned an percentage must not be above 100 error")
	}

}

func BenchmarkPercentileNearestRankSmallFloatSlice(b *testing.B) {
	for i := 0; i < b.N; i++ {
		_, _ = stats.PercentileNearestRank(makeFloatSlice(5), 50)
	}
}

func BenchmarkPercentileNearestRankLargeFloatSlice(b *testing.B) {
	lf := makeFloatSlice(100000)
	b.ResetTimer()
	for i := 0; i < b.N; i++ {
		_, _ = stats.PercentileNearestRank(lf, 50)
	}
}