66. lucy — SoftAcc / Score measuring

Part: V · Systems
Package: github.com/openfluke/welvet/lucy
Status: ok — ✅

When

Adaptation, measurement, or evolution (lucy).

Where

import "github.com/openfluke/welvet/lucy"

cd 66-lucy && source ../env.sh && go run .

Why

Adaptation benches (test41-w, tide, live_gpt) need one shared measuring math — SoftAcc, Availability, AdaptPct, Score — not three copies of the formulas.

What

Pure measuring package: SoftAcc / SoftAccProb, Window + Snapshot, Finalize. No datasets, no train loops. Sine scale 0.10; classification SoftAccProb scale 1.0. Density / synthetic-organism board is §69.

Sample output (captured)

soft=20.0 class=91.0 avail=80.0 score=7680

Live capture from go run ./cmd/runall on local ../../welvet (exit 0).

Source

Copied from the Welvet feature book examples (openfluke.github.io/welvet/examples/66-lucy).

package main

import (
	"fmt"

	"github.com/openfluke/welvet/lucy"
)

func main() {
	a := lucy.SoftAccOne(0.72, 0.80) // sine scale 0.10
	p := lucy.SoftAccProb(0.91, 1.0) // class scale 1.0
	var snap lucy.Snapshot
	snap.AvgAccuracy = 80
	snap.SoftAcc = a
	snap.InferMs = 8
	snap.TrainMs = 2
	snap.Throughput = 12000
	lucy.Finalize(&snap, lucy.Options{AdaptWindows: 10})
	fmt.Printf("soft=%.1f class=%.1f avail=%.1f score=%.0f\n",
		a, p, snap.Availability, snap.Score)
}