05: Update circadian and training metrics without replaying history

lib/aggregate.dart

@@ -6,12 +6,12 @@ export 'src/aggregate/checkpoint.dart';
 export 'src/aggregate/laws.dart';
 export 'src/aggregate/primitives.dart';
 export 'src/onehz/clinical/hrv_time_aggregator.dart' hide hrvTimeOneSlice;
-
-
+export 'src/onehz/clinical/load_trimp_aggregator.dart';
+export 'src/onehz/clinical/cosinor_aggregator.dart';
 export 'src/onehz/sleep/hypnogram_aggregator.dart';
-
+export 'src/onehz/sleep/circadian_np_aggregator.dart';
 export 'src/onehz/clinical/prsa_aggregator.dart';
 export 'src/onehz/foundations/rr_sandwich.dart';
-
-
-
+export 'src/onehz/clinical/readiness_lnrmssd_aggregator.dart';
+export 'src/onehz/sleep/sri_aggregator.dart';
+export 'src/onehz/workout/time_in_zone_aggregator.dart';

lib/onehz.dart

@@ -29,7 +29,8 @@ export 'src/onehz/clinical/hrv_freq.dart';
 export 'src/onehz/clinical/prsa.dart';
 export 'src/onehz/clinical/nocturnal.dart';
 export 'src/onehz/clinical/illness_cusum.dart';
-export 'src/onehz/clinical/readiness_lnrmssd.dart';
+export 'src/onehz/clinical/readiness_lnrmssd.dart'
+    hide readinessLnRmssdFromSuffix;
 export 'src/onehz/clinical/cosinor.dart';
 export 'src/onehz/clinical/load_trimp.dart';
 export 'src/onehz/clinical/stress_si.dart';

lib/src/onehz/clinical/cosinor.dart

@@ -10,9 +10,11 @@
 // the daytime peak — callers choose the period and supply trough-anchored
 // times; this engine just fits. R² is reported so a poor fit is visible.
 
-import 'dart:math' as math;
+import 'dart:typed_data';
+import '../../aggregate/aggregator.dart';
 import '../types.dart';
 import '../util.dart';
+import 'cosinor_aggregator.dart';
 
 class CosinorFit {
   final double mesor; // rhythm-adjusted mean
@@ -60,7 +62,6 @@ class CosinorFit {
 /// reported.
 const double cosinorAcrophaseAlpha = 0.05;
 
-
 /// Minimum samples for a cosinor fit. The model has 3 free parameters
 /// (M, β, γ); with n = 4 there is a single residual degree of freedom, so R²
 /// is essentially an interpolation score (4 RANDOM points routinely fit at
@@ -86,154 +87,17 @@ Metric<CosinorFit> cosinor(
       note: 'invalid cosinor period',
     );
   }
+  // Runs [cosinorAggregator] over the whole series in one slice. Mismatched
+  // lengths cannot be a [TimedValues] batch; they are the same "too few
+  // points" refusal as before.
   if (tHours.length != y.length) {
-    return const Metric<CosinorFit>.absent(tier: Tier.high,
-      inputs_used: ['signal_timeseries'], note: 'too few points for cosinor');
-  }
-  final state = _CosinorState();
-  final w = 2 * math.pi / periodHours;
-  for (var i = 0; i < y.length; i++) {
-    state.addCentered(math.cos(w * tHours[i]), math.sin(w * tHours[i]), y[i]);
-  }
-  return _finishCosinor(state, periodHours: periodHours, minPoints: minPoints);
-}
-
-// Nelson et al. (1979), Methods for cosinor-rhythmometry.
-// Centered least squares changes rounding. Relative 1e-12 gate is a
-// numerical identifiability policy, not a physiological cutoff.
-class _CosinorState {
-  var n = 0;
-  var meanC = 0.0;
-  var meanS = 0.0;
-  var meanY = 0.0;
-  var mCC = 0.0;
-  var mSS = 0.0;
-  var mYY = 0.0;
-  var mCS = 0.0;
-  var mCY = 0.0;
-  var mSY = 0.0;
-
-  void addCentered(double c, double s, double y) {
-    final nextN = n + 1;
-    final dc = c - meanC;
-    final ds = s - meanS;
-    final dy = y - meanY;
-    final nextMeanC = meanC + dc / nextN;
-    final nextMeanS = meanS + ds / nextN;
-    final nextMeanY = meanY + dy / nextN;
-    mCC += dc * (c - nextMeanC);
-    mSS += ds * (s - nextMeanS);
-    mYY += dy * (y - nextMeanY);
-    mCS += dc * (s - nextMeanS);
-    mCY += dc * (y - nextMeanY);
-    mSY += ds * (y - nextMeanY);
-    meanC = nextMeanC;
-    meanS = nextMeanS;
-    meanY = nextMeanY;
-    n = nextN;
-  }
-
-}
-
-Metric<CosinorFit> _finishCosinor(
-  _CosinorState state, {
-  required double periodHours,
-  required int minPoints,
-}) {
-  const inputs = ['signal_timeseries'];
-  final n = state.n;
-  if (n < math.max(4, minPoints) || periodHours <= 0) {
     return const Metric<CosinorFit>.absent(
       tier: Tier.high,
-      inputs_used: inputs,
+      inputs_used: ['signal_timeseries'],
       note: 'too few points for cosinor',
     );
   }
-  // A finite period or response can still overflow the design arithmetic.
-  // Reject invalid moments before NaN can bypass the identifiability gate.
-  if (![state.meanC, state.meanS, state.meanY, state.mCC, state.mSS,
-        state.mYY, state.mCS, state.mCY, state.mSY].every((v) => v.isFinite)) {
-    return const Metric<CosinorFit>.absent(
-      tier: Tier.high,
-      inputs_used: inputs,
-      note: 'non-finite cosinor design',
-    );
-  }
-  final determinant = state.mCC * state.mSS - state.mCS * state.mCS;
-  // The determinant is relative to the diagonal co-moments.  A design needs
-  // at least 1e-12 of that scale after removing its means to identify both
-  // cosine coefficients; below that, numerical noise decides the fit.
-  if (determinant <= 1e-12 * state.mCC * state.mSS) {
-    return const Metric<CosinorFit>.absent(
-      tier: Tier.high,
-      inputs_used: inputs,
-      note: 'singular cosinor design (insufficient phase coverage)',
-    );
-  }
-  final beta =
-      (state.mCY * state.mSS - state.mSY * state.mCS) / determinant;
-  final gamma =
-      (state.mSY * state.mCC - state.mCY * state.mCS) / determinant;
-  final mesor = state.meanY - beta * state.meanC - gamma * state.meanS;
-  final amplitude = math.sqrt(beta * beta + gamma * gamma);
-  final acro = math.atan2(-gamma, beta);
-  final w = 2 * math.pi / periodHours;
-  var phaseHours = -acro / w;
-  phaseHours = phaseHours % periodHours;
-  if (phaseHours < 0) phaseHours += periodHours;
-
-  final ssTot = state.mYY;
-  final ssRes = state.mYY -
-      2 * beta * state.mCY -
-      2 * gamma * state.mSY +
-      beta * beta * state.mCC +
-      gamma * gamma * state.mSS +
-      2 * beta * gamma * state.mCS;
-  final double r2 = ssTot == 0 ? 0.0 : (1 - ssRes / ssTot).clamp(0, 1);
-  final double r2Adj = (1 - (1 - r2) * (n - 1) / (n - 3)).clamp(0, 1);
-  // Zero-amplitude F-test (Nelson 1979): the acrophase is only defined once
-  // the test rejects. A flat or rhythm-free series still yields some
-  // atan2(−γ, β) from residual noise or float rounding.
-  final dof = n - 3;
-  final double ampP;
-  if (ssTot <= 0) {
-    ampP = 1.0;
-  } else if (ssRes <= 0) {
-    ampP = 0.0;
-  } else {
-    final f = ((ssTot - ssRes) / 2) / (ssRes / dof);
-    ampP = _f2Survival(f, dof);
-  }
-  final phaseDefined = ampP < cosinorAcrophaseAlpha;
-
-  return Metric<CosinorFit>(
-    value: CosinorFit(
-      mesor: mesor,
-      amplitude: amplitude,
-      acrophaseRad: phaseDefined ? acro : null,
-      acrophaseHours: phaseDefined ? phaseHours : null,
-      periodHours: periodHours,
-      r2: r2,
-      r2Adj: r2Adj,
-      amplitudeP: ampP,
-    ),
-    confidence: r2Adj.clamp(0.1, 0.95),
-    tier: Tier.high,
-    inputs_used: inputs,
-    note: phaseDefined
-        ? 'single-component cosinor; anchor circadian phase on the nocturnal '
-            'trough, not the daytime peak'
-        : 'single-component cosinor; no resolvable rhythm '
-            '(zero-amplitude test not rejected), acrophase undefined',
-  );
-}
-
-
-/// Upper tail of F(2, d): P(F > f) = (1 + 2f/d)^(−d/2), exact for 2 numerator
-/// degrees of freedom.
-double _f2Survival(double f, int d) {
-  if (f.isNaN) return 1.0;
-  if (f.isInfinite) return 0.0;
-  if (f <= 0) return 1.0;
-  return math.pow(1 + 2 * f / d, -d / 2).toDouble();
+  return cosinorAggregator(periodHours: periodHours, minPoints: minPoints)
+      .run(TimedValues(
+          Float64List.fromList(tHours), Float64List.fromList(y)));
 }