[#1316] lint: Fix warnings
Signed-off-by: Ekaterina Lebedeva <ekaterina.lebedeva@yadro.com>
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3 changed files with 11 additions and 10 deletions
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@ -12,7 +12,8 @@ run:
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# output configuration options
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# output configuration options
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output:
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output:
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# colored-line-number|line-number|json|tab|checkstyle|code-climate, default is "colored-line-number"
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# colored-line-number|line-number|json|tab|checkstyle|code-climate, default is "colored-line-number"
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format: tab
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formats:
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- format: tab
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# all available settings of specific linters
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# all available settings of specific linters
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linters-settings:
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linters-settings:
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@ -73,8 +73,8 @@ func newMinAgg() aggregator {
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// newReverseMinNorm returns a normalizer which
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// newReverseMinNorm returns a normalizer which
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// normalize values in range of 0.0 to 1.0 to a minimum value.
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// normalize values in range of 0.0 to 1.0 to a minimum value.
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func newReverseMinNorm(min float64) normalizer {
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func newReverseMinNorm(minV float64) normalizer {
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return &reverseMinNorm{min: min}
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return &reverseMinNorm{min: minV}
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}
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}
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// newSigmoidNorm returns a normalizer which
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// newSigmoidNorm returns a normalizer which
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@ -125,22 +125,22 @@ func (a *meanIQRAgg) Compute() float64 {
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slices.Sort(a.arr)
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slices.Sort(a.arr)
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var min, max float64
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var minV, maxV float64
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const minLn = 4
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const minLn = 4
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if l < minLn {
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if l < minLn {
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min, max = a.arr[0], a.arr[l-1]
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minV, maxV = a.arr[0], a.arr[l-1]
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} else {
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} else {
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start, end := l/minLn, l*3/minLn-1
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start, end := l/minLn, l*3/minLn-1
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min, max = a.arr[start], a.arr[end]
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minV, maxV = a.arr[start], a.arr[end]
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}
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}
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count := 0
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count := 0
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sum := float64(0)
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sum := float64(0)
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for _, e := range a.arr {
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for _, e := range a.arr {
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if e >= min && e <= max {
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if e >= minV && e <= maxV {
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sum += e
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sum += e
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count++
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count++
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}
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}
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@ -94,14 +94,14 @@ func (c *context) addUsedNodes(ns ...NodeInfo) {
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func defaultWeightFunc(ns nodes) weightFunc {
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func defaultWeightFunc(ns nodes) weightFunc {
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mean := newMeanAgg()
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mean := newMeanAgg()
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min := newMinAgg()
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minV := newMinAgg()
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for i := range ns {
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for i := range ns {
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mean.Add(float64(ns[i].capacity()))
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mean.Add(float64(ns[i].capacity()))
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min.Add(float64(ns[i].Price()))
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minV.Add(float64(ns[i].Price()))
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}
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}
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return newWeightFunc(
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return newWeightFunc(
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newSigmoidNorm(mean.Compute()),
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newSigmoidNorm(mean.Compute()),
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newReverseMinNorm(min.Compute()))
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newReverseMinNorm(minV.Compute()))
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}
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}
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