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AnimateDread
0bfc441139 feat: real-ZigZag training labels, HYBRID CPU-oversubscription fix, input cleanup
- Replace the hand-rolled fractal/deviation-%/ATR-trend-context ZigZag
  approximation with the actual MQL5 ZigZag indicator (rebranded as
  CustomIndicators/ADZigZag.mq5, logic untouched) as the training label
  source; bump the settle/confirmation window from 20 to 100 bars so a
  proper leg can form before being trusted, and drop the now-dead
  ZigZagDeviationPct/MinTrendATRMultiple/TrendContextBars inputs.
- Rebrand the stock Volumes indicator the same way (ADVolume.mq5).
- Fix HYBRID mode (AIType=HYBRID) oversubscribing the CPU fallback tier:
  every concurrent CNet instance was independently sizing its worker
  pool off the same global TargetCPULoad input. g_netPeerCount/
  PeerNetworkCount() now split it across however many CNet instances
  (live+shadow x active signals) are actually sharing the CPU.
- Fix NEURONS_REDUCTION_FACTOR's confusing retention-vs-reduction
  semantics so RF_70 means an actual 70% reduction; default to 4 hidden
  layers / RF_70.
- Migrate remaining free-form training/indicator inputs to enums for UI
  consistency; default news filter lookback to 1h, disable every-tick.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
2026-07-16 00:56:33 -04:00