Files
rotatingMachine/src/drift/predictionHealth.js
znetsixe c5bb375dd0 P5 wave 1: extract rotatingMachine concerns into focused modules
src/curves/         loader + normalizer (with cross-pressure anomaly
                      detection) + reverseCurve helper
  src/prediction/     predictors (predictFlow/Power/Ctrl) +
                      groupPredictors (lazy group-scope views) +
                      OperatingPoint (pressure-driven prediction setpoints)
  src/drift/          DriftAssessor (per-metric drift) + PredictionHealth
                      (composes flow/power/pressure into HealthStatus +
                      confidence sibling — see OPEN_QUESTIONS 2026-05-10)
  src/pressure/       VirtualPressureChildren (dashboard-sim) +
                      PressureInitialization (real-vs-virtual tracking) +
                      PressureRouter (dispatches by position)
  src/state/          stateBindings (state.emitter listener helper) +
                      isOperationalState
  src/measurement/    measurementHandlers (dispatcher for flow/power/temp/pressure)
  src/flow/           flowController (handleInput body — execSequence,
                      execMovement, flowMovement, emergencystop)
  src/display/        workingCurves (showWorkingCurves + showCoG admin)
  src/commands/       canonical names: set.mode, cmd.startup/shutdown/estop,
                      set.setpoint, set.flow-setpoint,
                      data.simulate-measurement, query.curves, query.cog,
                      child.register. execSequence demuxes by payload.action
                      to canonical cmd.* handlers.
  CONTRACT.md         inputs/outputs/events/children surface

110 basic tests pass (100 new + 10 pre-existing).
specificClass.js / nodeClass.js untouched — integration in P5 wave 2.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-10 21:38:45 +02:00

133 lines
4.8 KiB
JavaScript

'use strict';
const { HealthStatus } = require('generalFunctions');
/**
* PredictionHealth — composes per-metric drift snapshots + pressure
* initialization status into a single HealthStatus plus a numeric
* confidence figure.
*
* Per OPEN_QUESTIONS.md 2026-05-10: HealthStatus carries the standard
* five fields; `confidence` is returned as a sibling on the result.
*/
class PredictionHealth {
/**
* @param {object} ctx
* - getPressureInitializationStatus() -> { initialized, hasDifferential, source, ... }
* - isOperational() -> boolean
* - applyDriftPenalty(drift, confidence, flags, prefix) -> confidence (from DriftAssessor)
* - resolveSetpointBounds?() -> { min, max }
* - getCurrentPosition?() -> number
*/
constructor(ctx = {}) {
this.getPressureInitializationStatus = ctx.getPressureInitializationStatus;
this.isOperational = ctx.isOperational || (() => true);
this.applyDriftPenalty = ctx.applyDriftPenalty || ((_d, c) => c);
this.resolveSetpointBounds = ctx.resolveSetpointBounds;
this.getCurrentPosition = ctx.getCurrentPosition;
}
/**
* @param {object} driftSnapshots — { flow, power, pressure }
* pressure: { level, flags, source } (already-assessed pressure-drift status)
* @returns {{ health: object, confidence: number }}
* health is a frozen HealthStatus shape; confidence ∈ [0,1].
*/
evaluate(driftSnapshots = {}) {
const pressureDrift = driftSnapshots.pressure || { level: 0, flags: [], source: null };
const status = this._safePressureStatus();
const flags = Array.isArray(pressureDrift.flags) ? [...pressureDrift.flags] : [];
let confidence = this._baseConfidenceFromSource(status.source);
if (!this.isOperational()) {
confidence = 0;
flags.push('not_operational');
}
confidence = this._penaltyForPressureDriftLevel(pressureDrift.level, confidence);
confidence = this._penaltyForCurveEdge(confidence, flags);
confidence = this.applyDriftPenalty(driftSnapshots.flow, confidence, flags, 'flow');
confidence = this.applyDriftPenalty(driftSnapshots.power, confidence, flags, 'power');
confidence = Math.max(0, Math.min(1, confidence));
const dedupedFlags = flags.length ? Array.from(new Set(flags)) : ['nominal'];
const worstLevel = this._worstLevelFromSnapshots(pressureDrift, driftSnapshots, dedupedFlags);
const hasNonNominal = dedupedFlags.some((f) => f !== 'nominal');
const effectiveLevel = hasNonNominal ? Math.max(1, worstLevel) : worstLevel;
const sourceTag = pressureDrift.source ?? status.source ?? null;
const health = effectiveLevel === 0
? HealthStatus.ok(this._qualityLabel(confidence), sourceTag)
: HealthStatus.degraded(
effectiveLevel,
dedupedFlags,
this._qualityLabel(confidence),
sourceTag,
);
return { health, confidence };
}
_safePressureStatus() {
if (typeof this.getPressureInitializationStatus !== 'function') {
return { initialized: false, hasDifferential: false, source: null };
}
return this.getPressureInitializationStatus() || { source: null };
}
_baseConfidenceFromSource(source) {
if (source === 'differential') return 0.9;
if (source === 'upstream' || source === 'downstream') return 0.55;
return 0.2;
}
_penaltyForPressureDriftLevel(level, confidence) {
if (level >= 3) return confidence - 0.35;
if (level === 2) return confidence - 0.2;
if (level === 1) return confidence - 0.1;
return confidence;
}
_penaltyForCurveEdge(confidence, flags) {
if (typeof this.getCurrentPosition !== 'function' || typeof this.resolveSetpointBounds !== 'function') {
return confidence;
}
const cur = Number(this.getCurrentPosition());
const bounds = this.resolveSetpointBounds() || {};
const { min, max } = bounds;
if (Number.isFinite(cur) && Number.isFinite(min) && Number.isFinite(max) && max > min) {
const span = max - min;
const edgeDist = Math.min(Math.abs(cur - min), Math.abs(max - cur));
if (edgeDist < span * 0.05) {
flags.push('near_curve_edge');
return confidence - 0.1;
}
}
return confidence;
}
_worstLevelFromSnapshots(pressureDrift, snaps, flags) {
let worst = Number.isFinite(pressureDrift.level) ? pressureDrift.level : 0;
for (const id of ['flow', 'power']) {
const d = snaps[id];
if (!d || !d.valid) continue;
const lvl = Math.max(d.immediateLevel || 0, d.longTermLevel || 0);
if (lvl > worst) worst = lvl;
}
if (flags.includes('not_operational') && worst < 2) worst = 2;
return Math.max(0, Math.min(3, worst));
}
_qualityLabel(confidence) {
if (confidence >= 0.8) return 'high';
if (confidence >= 0.55) return 'medium';
if (confidence >= 0.3) return 'low';
return 'invalid';
}
}
module.exports = PredictionHealth;