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https://github.com/VictoriaMetrics/VictoriaMetrics.git
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606035766a
Add a test, which verifies the correct sorting of float64 slices with NaNs. Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/5506 Updates https://github.com/VictoriaMetrics/VictoriaMetrics/pull/5509
84 lines
2.2 KiB
Go
84 lines
2.2 KiB
Go
package promql
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import (
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"math"
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"sort"
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"testing"
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)
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func TestSortWithNaNs(t *testing.T) {
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f := func(a []float64, ascExpected, descExpected []float64) {
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t.Helper()
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equalSlices := func(a, b []float64) bool {
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for i := range a {
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x := a[i]
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y := b[i]
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if math.IsNaN(x) {
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return math.IsNaN(y)
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}
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if math.IsNaN(y) {
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return false
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}
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if x != y {
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return false
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}
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}
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return true
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}
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aCopy := append([]float64{}, a...)
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sort.Slice(aCopy, func(i, j int) bool {
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return lessWithNaNs(aCopy[i], aCopy[j])
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})
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if !equalSlices(aCopy, ascExpected) {
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t.Fatalf("unexpected slice after asc sorting; got\n%v\nwant\n%v", aCopy, ascExpected)
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}
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aCopy = append(aCopy[:0], a...)
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sort.Slice(aCopy, func(i, j int) bool {
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return greaterWithNaNs(aCopy[i], aCopy[j])
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})
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if !equalSlices(aCopy, descExpected) {
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t.Fatalf("unexpected slice after desc sorting; got\n%v\nwant\n%v", aCopy, descExpected)
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}
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}
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f(nil, nil, nil)
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f([]float64{1}, []float64{1}, []float64{1})
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f([]float64{1, nan, 3, 2}, []float64{nan, 1, 2, 3}, []float64{nan, 3, 2, 1})
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f([]float64{nan}, []float64{nan}, []float64{nan})
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f([]float64{nan, nan, nan}, []float64{nan, nan, nan}, []float64{nan, nan, nan})
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f([]float64{nan, 1, nan}, []float64{nan, nan, 1}, []float64{nan, nan, 1})
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f([]float64{nan, 1, 0, 2, nan}, []float64{nan, nan, 0, 1, 2}, []float64{nan, nan, 2, 1, 0})
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}
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func TestModeNoNaNs(t *testing.T) {
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f := func(prevValue float64, a []float64, expectedResult float64) {
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t.Helper()
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result := modeNoNaNs(prevValue, a)
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if math.IsNaN(result) {
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if !math.IsNaN(expectedResult) {
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t.Fatalf("unexpected result; got %v; want %v", result, expectedResult)
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}
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return
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}
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if result != expectedResult {
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t.Fatalf("unexpected result; got %v; want %v", result, expectedResult)
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}
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}
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f(nan, nil, nan)
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f(nan, []float64{123}, 123)
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f(nan, []float64{1, 2, 3}, 1)
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f(nan, []float64{1, 2, 2}, 2)
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f(nan, []float64{1, 1, 2}, 1)
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f(nan, []float64{1, 1, 1}, 1)
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f(nan, []float64{1, 2, 2, 3}, 2)
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f(nan, []float64{1, 1, 2, 2, 3, 3, 3}, 3)
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f(1, []float64{2, 3, 4, 5}, 1)
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f(1, []float64{2, 2}, 2)
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f(1, []float64{2, 3, 3}, 3)
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f(1, []float64{2, 4, 3, 4, 3, 4}, 4)
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f(1, []float64{2, 3, 3, 4, 4}, 3)
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f(1, []float64{4, 3, 2, 3, 4}, 3)
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}
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