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zeekay
7cf87b230b
The module already called itself github.com/luxfi/node while containing no node in Go: cmd/luxd was twenty-one lines that printed the size of a few types, and the Go column of the matrix measured a VM plugin. A repo that fetches the thing it claims to be has not replaced it, so the Go sources move in — 1515 files, the daemon and everything under it — and the build reaches outside this module for nothing. Rust and C++ sit beside it unchanged and are still measured against it by the differential. That is the point of one repo: the reference implementation and the two ports are the same checkout, so parity is a thing you can run rather than a thing you assert. Verified: builds, and the closure carries no lux-private — checked at build time rather than believed. The daemon starts twelve chains on a local network (P X C Q Z A B G K M F, plus D through its plugin) and reports healthy.
71 lines
1.9 KiB
Go
71 lines
1.9 KiB
Go
// Copyright (C) 2019-2025, Lux Industries Inc. All rights reserved.
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// See the file LICENSE for licensing terms.
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package math
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import (
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"math"
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"time"
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)
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type continuousAverager struct {
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halflife float64
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weightedSum float64
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normalizer float64
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lastUpdated time.Time
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}
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// NewUninitializedAverager creates a new averager with the given halflife. If
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// [Read] is called before [Observe], the zero value will be returned. When
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// [Observe] is called the first time, the averager will be initialized with
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// [value] at that time.
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func NewUninitializedAverager(halfLife time.Duration) Averager {
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// Use 0 as the initialPrediction and 0 as the currentTime, so that when the
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// first observation occurs (at a non-zero time) the initial prediction's
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// weight will become negligible.
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return NewAverager(0, halfLife, time.Time{})
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}
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func NewAverager(
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initialPrediction float64,
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halflife time.Duration,
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currentTime time.Time,
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) Averager {
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return &continuousAverager{
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halflife: float64(halflife) / math.Ln2,
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weightedSum: initialPrediction,
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normalizer: 1,
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lastUpdated: currentTime,
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}
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}
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func (a *continuousAverager) Observe(value float64, currentTime time.Time) {
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delta := a.lastUpdated.Sub(currentTime)
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switch {
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case delta < 0:
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// If the times are called in order, scale the previous values to keep the
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// sizes manageable
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newWeight := math.Exp(float64(delta) / a.halflife)
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a.weightedSum = value + newWeight*a.weightedSum
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a.normalizer = 1 + newWeight*a.normalizer
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a.lastUpdated = currentTime
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case delta == 0:
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// If this is called multiple times at the same wall clock time, no
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// scaling needs to occur
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a.weightedSum += value
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a.normalizer++
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default:
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// If the times are called out of order, don't scale the previous values
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newWeight := math.Exp(float64(-delta) / a.halflife)
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a.weightedSum += newWeight * value
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a.normalizer += newWeight
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}
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}
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func (a *continuousAverager) Read() float64 {
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return a.weightedSum / a.normalizer
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}
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